Affiliations
Associate Professor of Medicine, Associate Dean for Medical Education, Pennsylvania State University College of Medicine, Hershey, Pennsylvania
Given name(s)
Jed D.
Family name
Gonzalo
Degrees
MD, MSc

Quality and Safety During Off Hours

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Quality and safety during the off hours in medicine units: A mixed methods study of front‐line provider perspectives

Patients experience acute illness at all hours of the day. In acute care hospitals, over 60% of patient admissions occur outside of normal business hours, or the off hours.[1, 2] Similarly, the acute decompensation of patients already admitted to hospital‐based units is frequent, with 90% of rapid responses occurring between 9 pm and 6 am.[3] Research suggests worse hospital performance during off hours, including increased patient falls, in‐hospital cardiac arrest mortality, and severity of hospital employee injuries.[2, 4, 5, 6, 7]

Although hospital‐based services should match care demand, the disparity between patient acuity and hospital capability at night is significant. Off hours typically have lower staffing of nurses, and attending and housestaff physicians, and ancillary staff as well as limited availability of consultative and supportive services.[8] Additionally, off‐hours providers are subject to the physiological effects of imbalanced circadian rhythms, including fatigue, attenuating their abilities to provide high‐quality care. The significant patient care needs mandate continuous patient care delivery without compromising quality or safety. To achieve this, further defining the barriers to delivering quality care during off hours is essential to improvement efforts in medicine‐based units.

Previous investigations have found increased occurrence and severity of worker accidents, increased potential for higher occurrence of preventable adverse patient events, and decreased performance during off hours.[4, 9, 10] Additionally, detrimental effects of off‐hours care may be further magnified by rotating employees through both day and night shifts, a common practice in academic hospitals.[11, 12] Potentially modifiable outcomes, such as patient fall rate and in‐hospital cardiac arrest survival differ markedly between day and night shifts.[6, 13] These studies primarily report on specific diseases, such as myocardial infarction and stroke, and are investigated from the perspective of hospital‐level outcomes.

To our knowledge, no study has reported provider‐perceived quality and safety issues occurring during off hours in an academic setting. Likewise, although off‐hours collaborative care requires shared, interprofessional conceptualization regarding care delivery, this perspective has not been reported. Understanding the similarities and differences between provider perceptions will allow the construction of an interprofessional team mental model, facilitating the design of future quality improvement initiatives.[14, 15] Our objectives were to: (1) identify off‐hours quality and safety issues, (2) assess which issues are perceived as most significant, and (3) evaluate differences in perceptions of these issues between nurses, and attending and housestaff physicians.

METHODS

Study Design

To investigate quality and safety issues occurring during off hours, we employed a prospective, mixed‐methods sequential exploratory study design, involving an initial qualitative analysis of adverse events followed by quantitative survey assessment.[16] We chose a mixed‐methods approach because provider‐perceived off‐hours issues had not been explicitly identified in the literature, requiring preliminary qualitative assessment. For the purpose of this study, we defined off hours as the 7 pm to 7am time period, which overlapped night shifts for both nurses and physicians. The study was approved by the institutional review board as a quality improvement project.

Study Setting

The study was conducted at a 378‐bed, university‐based acute care hospital in central Pennsylvania. There are a total of 64 internal medicine beds located in 2 units: a general medicine unit (44 beds, staffed by 60 nurses, nurse‐to‐patient ratio 1:4) and an intermediate care unit (20 beds, staffed by 41 nurses, nurse‐to‐patient ratio 1:3). The medicine residency program consists of 69 residents and 14 combined internal medicinepediatrics residents. During the day, 3 teaching teams and 1 nonteaching team care for all medicine patients. Overnight, 3 junior/senior level residents admit patients to the medicine service, whereas 2 interns provide cross‐coverage for all medicine and specialty service patients. Starting in September 2012 (before data collection), an overnight faculty‐level academic hospitalist, or nocturnist, provided on‐site housestaff supervision.

Qualitative Data Collection

For the qualitative analysis, we used 2 methods to develop our database. First, we created an electronic survey (see Supporting Information, Appendix 1, in the online version of this article) to identify near misses/adverse events occurring overnight, distributed to the nocturnist, 3 daytime hospitalists, and unit charge nurses following each shift (October 2012March 2013). The survey items were developed for the purpose of this study, with several items modified from a previously published survey.[17] Second, residency program directors recorded field notes during end‐of‐rotation debriefings (1 hour) with departing overnight housestaff, which were then dictated and transcribed. The subsequent analysis from these sources informed the quantitative survey (see Supporting Information, Appendix 2, in the online version of this article).

Survey Instrument

Three months after the initiation of qualitative data collection, 1 investigator (J.D.G.) developed a preliminary codebook to identify categories and themes. From this codebook, the research team drafted a survey instrument (the complete qualitative analysis occurred after survey development). To maintain focus on systematic quality improvement, items related to perceived mismanagement, relationship tensions, and professionalism were excluded. The survey was pilot‐tested with 5 faculty physicians and 2 nursing staff, prompting several modifications to improve clarity. Primary demographic items included provider role (nurse, attending physician, or housestaff physician) and years in current role. The 24 survey items were grouped into 5 different categories: (1) Quality of Care Delivery, (2) Communication and Coordination, (3) Staffing and Supervision, (4) Patient Transfers, and (5) Consulting Service Issues. Each item was investigated on a 7‐point scale (1=lowest rating, 7=highest rating). Descriptive text was provided at the extremes (choices 1 and 7), whereas intermediary values (26) did not have descriptive cues. The descriptive anchors for Quality of Care Delivery and Patient Transfers were 1=never and 7=always, whereas the descriptive anchors Communication and Coordination and Staffing and Supervision were 1=poor and 7=superior; Consulting Service Issues used a mix of both. Providers with off‐hours experience were asked to rank 4 time periods (710 pm, 10 pm1 am, 14 am, 47 am) regarding quality of care delivery in the medicine units (1=best, 4=worst). We asked both daytime and nighttime providers about perceptions of off‐hours care because, given the boundary spanning the nature of medical care across work shifts, daytime providers frequently identify issues not apparent until hours (or even days) after completion of a night shift. A similar design was used in prior work investigating safety at night.[17]

Quantitative Data Collection

In June of 2013, we emailed a survey link (www.surveymonkey.com) to all medicine nurses, and attending and housestaff physicians. The email described the study, explained the voluntary nature of the project, and stated informed consent was implied by survey completion. As an incentive, respondents were provided an option to enter their name into a raffle to win 1 of 50, $5 gift certificates. Following the initial invitation, 3 weekly email reminders were sent by the lead investigator (J.D.G.) requesting completion.

Data Analysis

Using the preliminary codebook, 2 investigators (J.D.G., E.M.) jointly analyzed a segment of the dataset using Atlas.ti 6.0 (Scientific Software, Berlin, Germany). Two investigators independently coded the data, compared codes for agreement, and updated the codebook. The remaining data were coded independently, with regular adjudication sessions to modify the codebook. All investigators reviewed and agreed upon themes and representative quotations.

Descriptive statistics, Pearson correlation statistics, Kruskal‐Wallis tests, and signed rank tests (with Bonferroni correction) were used to report group characteristics, correlate rank order, make comparisons between groups (nursing staff, and attending and housestaff physicians; day/night providers), and compare quality rankings by time period, respectively. The data were analyzed using SAS 9.3 (SAS Institute Inc., Cary, NC) and Stata/IC‐8 (StataCorp, College Park, TX).

RESULTS

Qualitative Analysis of Off‐Hours' Adverse Events and Near Misses

A total of 190 events were reported by daytime attending physicians (n=100), nocturnists (n=60), and nighttime charge nurses (n=30). Although questions asked participants to describe near misses/adverse events, respondents also reported a number of global quality issues not related to specific events. Similarly, debriefing sessions with housestaff (n=5) addressed both specific overnight events and residency‐related issues. Seven themes were identified: (1) perceived mismanagement, (2) quality of delivery processes, (3) communication and coordination, (4) staffing and supervision, (5) patient transfers, (6) consulting service issues, and, (7) professionalism/relational tensions. Table 1 lists the code frequencies and exemplary quotations.

Quality and Safety Issues Occurring During the Off Hours in Medicine Units as Reported by Medicine Nurses, and Attending and Housestaff Physicians (322 Total Coding References)*
Category and ThemesCode Frequency No. (% of 322)Representative Quotation
  • NOTE: Abbreviations: BiPaP, bilevel positive airway pressure; DNI, do not intubate; DNR, do not resuscitate; ED, emergency department; EMR, electronic medical record; IV, intravenous; MRI, magnetic resonance imaging; stat, immediately. *Surveys from nursing staff, nocturnists, and daytime attending physicians produced 276 coding references; focus groups with residents produced 46 coding references (total 322). Code frequency indicates the number of times the specific code was identified or referenced in the analysis. For example, if a particular communication issue was discussed in detail, the code may have been referenced more than once. Of the 190 survey‐reported events, 74 received2 coding references. Quality of Delivery Processes included issues related to timeliness and delays (34 coding references) and patient safety issues (29 coding references).

Perceived mismanagement97 (30)We had a new admission to the general medicine unit with atrial flutter and rapid ventricular response who did not receive rate controlling agents but rather received diuretics. [The patient's] heart rate remained between 110 and 130 overnight, with a troponin rise in the am likely from demand. The attending note states rate controllers and discussed with housestaff, but this was not performed.
Quality of delivery processes63 (20)One patient had a delay in MRI scanning in the off hours due to the scanner being down and scheduling. When the patient went down, there seemed to be little attempt to make sure patient went through scanner; unclear if housestaff called or not to come to assist. Now, the delay in care is even further along.
Communication and coordination50 (16)A patient was transferred to the intermediate care unit with hypercarbic respiratory failure. The patient had delay of >1 hour to receive IV Bumex because pharmacy would not release the dose from Pyxis, and the nurse did not let us know there was a delay. When I asked the nurse why, she responded because she's not the only patient I have. I pointed out that the patient was in failure and needed Bumex, stat. If we had not clearly communicated either verbally or via computer, she should let us know how to do that better.
Staffing and supervision39 (12)A patient was admitted DNR/DNI with advanced dementia, new on BiPaP at 100%, and hypotensive. The team's intern [identified] the need for interventions, including a central line. This was discussed with overloaded intensive care unit resident. The intern struggled until another resident assisted along with the night attending. Issues included: initial triage, no resident backup for team, and attending backup. I should have been more hands on in the moment to assist the intern navigating the system of care. Many issues here, but no senior resident was involved in care until [late].
Patient transfers38 (12)One patient went from the emergency department [to us] on the 5th floor at 7:45 pm. The ED placed an order for packed red blood cells and it was written at 4:45 pm. When patient arrived on our floor at 7:45 pm, the transfusion had not been started. The floor nurse started it at 8:10 pm .
Consulting services18 (6)Regarding a new outside hospital transfer, the medicine team was informed that [the consulting service] would place official consult on the chart when imaging studies from the outside institution were available. Despite this, the consult was still not done after 36 hours, and [we are] still waiting. We contacted service several times.
Professionalism and relational tensions17 (5)[One admission from the emergency department] involved a patient who received subcutaneous insulin for hyperkalemia as opposed to intravenous insulin. When brought to [their] attention, they became very confrontational and abrupt and denied having ordered or administered it that way, although it was documented in the EMR.

Perceived Mismanagement

Participants commonly questioned the decision making, diagnosis, or management of off‐hours providers. Concerns included the response to acute illness (eg, delay in calling a code), treatment decisions (eg, diuresis in a patient with urinary retention), or omission of necessary actions (eg, no cultures ordered for septicemia).

Quality of Delivery Processes

Participants frequently described quality of care delivery issues primarily related to timeliness or delays in delivery processes (34/63 coding references), or patient safety issues (29/63 coding references). Described events revealed concerns about the timeliness of lab reporting, imaging, blood draws, and medication ordering/processing.

Communication and Coordination

Breakdowns in communication and coordination often threatened patient safety. Identified issues included poor communication between primary physicians, nurses, consulting services, and emergency department (ED) providers, as well as documentation within the electronic medical record.

Staffing and Supervision

Several events highlighted staffing or supervision limitations, such as perceived low nursing or physician staffing levels. The degree of nocturnist supervision was polarizing, with both increased and decreased levels of supervision reported as limiting care delivery (or housestaff education).

Patient Transfers

Patient transfers to medicine units from the ED, other inpatient units, or outside hospitals, were identified several times as an influential factor. The care transition and need for information exchange led to a perceived compromise in quality or safety.

Consulting Service Issues

Several examples highlighted perceived issues related to the communication, coordination, or timeliness of consultant services in providing care.

Professionalism/Relational Tensions

Last, providers described situations in which they perceived lack of professionalism or relational tensions between providers, either in regard to interactions or clinical decisions in patient care.

Quantitative Results

Of 214 surveys sent, data were collected from 160 respondents (75% response), including 64/101 nursing staff (63% response), 25/28 attending physicians (80% response), and 71/85 housestaff physicians (84% response). Table 2 describes the participant demographics.

Demographics of Medicine Nursing Staff, and Attending and Housestaff Physicians (n=160).
VariableNo. (%)
  • NOTE: Abbreviations: SD, standard deviation. *Senior resident includes third‐ and fourth‐year medicine or medicine/pediatrics residents.

Nursing staff64 (40)
Intermediate care unit20
General medicine ward44
All night shifts16
Mix of day and night shifts26
Years of experience, mean (SD)7.7 (9.7)
Attending physicians25 (16)
No. providing care only at night4
No. of weeks as overnight hospitalist in past year, mean (SD)11.5 (4.1)
No. providing care only during the day21
Years since residency graduation, mean (SD)9.0 (8.5)
Medicine residents71 (44)
Intern27
Junior resident23
Senior resident*21

Off‐Hours Quality and Safety Issues

Ratings and comparisons of the 24 items are shown in Table 3. For all items, the mean rating was below 5 (7‐point scale). Lowest‐rated (least optimal) items were: timeliness, safety, and communication involved with patients admitted from the ED, number of attending physicians, and timeliness of consults and blood draws. Highest‐rated (more optimal) items were: timely reporting of labs, timely identification of deteriorating status, medication ordering and processing, communication between physicians, and safety and communication involved with intraservice transfers.

Comparison of Quality and Safety Issues Occurring During Off Hours as Reported by Nursing Staff, and Attending and Housestaff Physicians (n=160)
Category and Survey Item, Mean (SD)*Total (160)Providers With Night ExperienceNighttime Providers (116)Daytime Providers (44)P Value
Nurses (41)Attending Physicians (4)Housestaff (71)P Value
  • NOTE: Abbreviations: SD, standard deviation. *Answer choices included 7 options from 1 (poor) to 7 (superior). Kruskal‐Wallis with ties. Daytime providers are individuals without any night experience; all housestaff, given night float rotations, were included in the nighttime providers group.

Quality of care delivery        
Timely reporting of labs at night4.70 (1.39)5.12 (1.50)4.50 (1.00)4.61 (1.47)0.114.78 (1.48)4.48 (1.11)0.09
Timely identification of deteriorating status4.67 (1.34)4.88 (1.36)5.00 (0.82)4.85 (1.20)0.934.86 (1.24)4.16 (1.45)0.006
Medication ordering and processing4.63 (1.13)4.88 (1.25)5.25 (0.50)4.66 (1.08)0.194.76 (1.13)4.27 (1.06)0.01
Timely completion of imaging at night4.29 (1.32)4.32 (1.46)4.75 (0.96)4.39 (1.29)0.884.38 (1.34)4.05 (1.26)0.12
Timely reporting of results at night4.19 (1.43)4.27 (1.53)4.00 (1.83)4.11 (1.44)0.844.16 (1.47)4.27 (1.30)0.76
Timely med release from pharmacy at night4.16 (1.29)4.00 (1.32)4.50 (0.58)4.28 (1.29)0.444.19 (1.28)4.09 (1.31)0.90
Timely blood draws at night3.96 (1.52)4.63 (1.44)4.50 (0.58)3.53 (1.49)<0.0013.96 (1.54)3.98 (1.47)0.98
Communication and coordination
Communication between physicians4.63 (1.26)4.29 (1.23)6.00 (1.15)5.14 (1.12)<0.0014.87 (1.24)3.98 (1.09)<0.001
Communication between nursing and pharmacy4.39 (1.27)4.83 (1.41)5.00 (0.82)4.27 (1.29)0.044.49 (1.34)4.11 (4.11)0.08
Communication between nursing and physicians4.39 (1.28)4.44 (1.36)5.00 (0.82)4.58 (1.31)0.644.54 (1.31)3.98 (1.13)0.01
Documentation in medical record4.33 (1.36)5.00 (1.36)6.00 (0.82)4.23 1.19)<0.0014.56 (1.31)3.70 (1.30)<0.001
Ease of contacting primary providers at night4.31 (1.29)4.46 (1.27)6.00 (0.00)4.54 (1.18)0.024.56 (1.22)3.66 (1.27)<0.001
Staffing and supervision
No. of nursing staff4.51 (1.27)4.54 (1.50)5.50 (0.58)4.59 (1.21)0.254.60 (1.31)4.25 (1.14)0.025
Supervision of housestaff4.43 (1.34)4.56 (1.40)6.25 (0.50)4.55 (1.34)0.034.61 (1.37)3.95 (1.14)0.002
No. of housestaff4.09 (1.39)4.27 (1.40)4.50 (1.29)4.11 (1.44)0.704.18 (1.41)3.86 (1.32)0.12
No. of ancillary staff4.00 (1.40)4.27 (1.53)5.75 (0.96)3.85 (1.40)0.024.06 (1.48)3.84 (1.18)0.27
No. of attending physicians3.79 (1.50)3.49 (1.76)5.25 (0.96)3.89 (1.43)0.073.79 (1.57)3.80 (1.32)0.98
Patient transfers
For patients accepted to medicine from another medicine unit
Timely and safe patient transfers4.56 (1.28)5.15 (1.11)4.75 (0.50)4.55 (1.23)0.0254.77 (1.20)4.00 (1.33)0.001
High quality communication between providers4.55 (1.35)5.34 (1.13)5.00 (0.82)4.49 (1.22)0.0014.81 (1.24)3.86 (1.41)<0.001
For patients admitted from emergency department to medicine unit
Appropriate testing and treatment4.16 (1.34)4.15 (1.30)4.00 (1.83)4.21 (1.43)0.964.18 (1.39)4.11 (1.20)0.66
Timely and safe transfers3.89 (1.38)3.63 (1.50)5.50 (0.58)4.08 (1.32)0.023.97 (1.40)3.68 1.29)0.23
High‐quality communication between providers2.93 (1.38)2.56 (1.23)3.75 (1.26)3.00 (1.39)0.082.87 (1.35)3.07 (1.47)0.41
Consulting service issues
Timely consults at night4.04 (1.35)4.27 (1.28)4.00 (0.82)4.10 (1.47)0.694.16 (1.38)3.73 (1.25)0.053
Communication between consults and physicians3.93 (1.40)3.46 (1.45)5.75 (1.26)4.35 (1.27)<0.0014.09 (1.42)3.50 (1.27)0.016

Comparisons Between Professional Groups With Night Experience

Of the 24 items, 11 showed statistically significant differences between groups (P<0.05). Items with the largest difference between groups included: timely blood draws at night (housestaff physicians lowest), communication between physicians (nursing lowest), documentation in medical record (housestaff physicians lowest), and communication between consults and physicians (nursing lowest). The rank order between housestaff physicians and nurses, and housestaff and attending physicians showed moderately positive correlations (r=0.61, P=0.002 and r=0.47, P=0.022, respectively). The correlation between nurses and attending physicians showed a weak correlation (r=0.19, P=0.375).

Comparisons Between Front‐Line Providers With and Without Night Experience

Of the 24 items, 12 showed statistically significant differences between groups (P<0.05), with day providers reporting lower ratings in all 12. Items with the largest difference between groups included: communication between consults and physicians, ease of contacting providers, communication between providers, documentation, and safety and communication related to transfers from other units. The rank order between night and day groups showed a statistically significant positive correlation (r=0.65, P=0.001).

Perceived Highest Quality of Care Time Period During Off Hours

Compared with other time periods, all providers ranked 4 to 7 am as the period with the lowest quality of care delivery (mean rank 3.2, P0.001) (Figure 1). Nursing staff and attending physicians both ranked the 10 pm to 1 am time period as the best period (mean of 2.0 and 1.5, respectively), whereas housestaff physicians ranked the 7 to 10 pm as the best time period (mean 1.62). The only statistical difference between provider groups for any given time period was the 7 to 10 pm time period (P=0.002).

Figure 1
Comparison of mean rankings of quality within specific time periods during the night shift as reported by off‐hours providers—nursing staff, and attending and housestaff physicians (N = 116).

DISCUSSION

In this prospective, mixed‐methods study evaluating perceived off‐hours quality and safety issues, several themes were identified, including perceived mismanagement, insufficient quality of delivery processes, communication/coordination breakdowns, and staffing and supervision issues. In the quantitative analysis, lowest‐rated items (lowest quality) related to timeliness/safety/communication involved with ED transfers, number of attending physicians, and timeliness of consults and blood draws. Highest‐rated items (highest quality) related to timeliness of lab reporting and identification of deteriorating patients, medication ordering/processing, communication between physicians, and safety/communication during intraservice transfers. In general, day providers reported lower ratings than night providers on nearly all quality‐related items. Nursing staff reported the lowest ratings regarding communication between physicians and consults, whereas housestaff physicians reported the lowest ratings regarding documentation in the medical record and timely blood draws. These between‐group differences reveal the lack of shared conceptual understanding regarding off‐hours care delivery.

Our qualitative results reveal several significant issues related to care delivery during off hours, many of which are not obtainable by hospital‐level data or chart review.[18] For hospital‐based medicine units, an understanding of the structure‐ and process‐related factors associated with events is required for quality improvement efforts. Although the primary focus for this work was the off hours, it is plausible that providers may have identified similar issues as important issues during daytime hours. Our study was not designed to investigate if these perceived issues are specific to off hours, or if these issues are an accurate reflection of objective events occurring during this time period. We believe this topic deserves further investigation, as understanding if these off‐hours perceptions are unique to this time period would change the scope of future quality improvement initiatives.

The most significant finding in the quantitative results was the vulnerability in quality and safety during patient admissions from the ED, specifically in relation to communication and timeliness of transfer. Between‐unit handoffs for patients admitted from the ED to medicine units have been identified as particularly vulnerable to breakdowns in the communication process.[19, 20, 21, 22] There are multiple etiologies, including clinical uncertainty, higher acuity in patient illness early in hospitalization, and cultural differences between services.[23] Additionally, patterns of communication and standardized handoff processes are often insufficient. In our hospital system, the transfer process relies primarily upon synchronous communication methods without standardized, asynchronous information exchange. We hypothesize front‐line providers perceive this lack of standardization as a primary threat to quality. Because approximately 60% of new patient admissions from the ED to medicine service (both in our hospital and in prior studies) occur during off hours, these findings highlight a need for subsequent study and quality improvement efforts.[24]

During the time of this study, our medicine units were staffed at night by 5 medicine housestaff physicians and 1 academic hospitalist, or nocturnist. In efforts to improve quality and safety during off hours, our hospital, as well as other health systems, implemented the nocturnist position, a faculty‐level attending physician to provide off‐hours clinical care and housestaff supervision.[25] Although participants reported a moderate rating of housestaff supervision, participants provided lower scores for staffing numbers of nurses, and housestaff and attending physicians, despite nocturnist presence. With both increased off‐hours supervision in our hospital and increasing use of faculty‐level physicians in other academic programs, these results provide context for the anticipated level of overnight housestaff supervision.[26, 27] To our knowledge, this is the first study to investigate perceived overnight quality issues on medicine units following such staffing models. Although this model of direct, on‐site supervision in academic medicine programs may help offset staffing and supervisory issues during off hours, the nocturnist role is insufficient to offset threats to quality/safety already inherent within the system. Furthermore, prospective trials following implementation of nocturnist systems have shown mixed results in improving patient outcomes.[28] These findings have led some to question whether resources dedicated to nocturnist staffing may be better allocated to other overnight initiatives, highlighting the need for a more subtle understanding of quality issues to design targeted interventions.[29]

A notable finding from this work is that providers without night experience reported lower scores for 20 of 24 items, highlighting their perceptions of the quality of care delivery during off hours are lower than those who experience this environment. Although day providers are not directly experiencing off‐hours delivery processes, these providers receive and detect the results from care delivery at night.[17] Most nurse, physician, and hospital leaders are present in the hospital only during day hours, requiring these individuals to account for differences in perceived and actual care delivered overnight.[1] These individuals make critical decisions pertaining to process changes and quality improvement efforts in these units. We believe these results raise awareness for leadership decisions and quality improvement efforts in medicine service units, specifically to focus on overnight issues beyond staffing issues alone.

All respondent groups ranked the latter half of the shift (17 am) as lower in quality compared to the first 6 hours (7 pm1 am). This finding is contrary to our hypothesis that earlier time periods, during the majority of patient admissions (and presumed higher workload for all providers), would be perceived as lower quality. Reasons for this finding are unknown, but may relate to end‐of‐shift tasks, sign‐out preparation, provider fatigue, or disease‐related concerns (eg, increased incidence of stroke and myocardial infarction) during the latter portions of night shifts. One study identified a decrease in nursing clinical judgments from the beginning to end of 12‐hour shifts, with a potential suggested mechanism of decrease in ability to maintain attention during judgments.[30] Additionally, in a study by Folkard et al., risk was highest within the first several hours and fell substantially thereafter during a shift.[9] To our knowledge, no work has investigated perceived or objective quality outcomes by time period during the off‐hours shift in medicine units. Further work could help delineate why provider‐perceived compromises in quality occur late in off‐hours shifts and whether this correlates to safety events.

There are several limitations to our study. First, although all surveys were pilot tested for content validity, the construct validity was not rigorously assessed. Second, although data were collected from all participant groups, the collection methods were unbalanced, favoring attending‐level physician perspectives. Although the relative incidence of vulnerabilities in quality and safety should be interpreted with caution, our methods and general taxonomy provide a framework for developing and monitoring the perceptions of future interventions. Due to limitations in infrastructure, our findings could not be independently validated through review of reported adverse events, but previous investigations have found the vast majority of adverse events are not detected by standard anonymous reporting.[31, 32, 33] Our methodology (used in our prior work) may provide an independent means of detecting causes of poor quality not easily observed through routine surveillance.[22] Although many survey items showed statistical differences between provider groups, the clinical significance is subject to interpretation. Last, the perceptions and events related to our institution may not be fully generalizable to other academic programs or service lines, particularly in community‐based, nonteaching hospitals.

In conclusion, our results suggest a significant discrepancy between the concerns of day and night providers regarding the quality of care delivered to inpatients during the off hours, specifically with issues related to communication, quality‐of‐care delivery processes, and patient transfers from the ED. Although specific concerns may be institution‐ (and service line‐) dependent, appropriately designing initiatives to improve the quality of care delivered overnight will need to take the perspectives of both provider groups into account. Additionally, educational initiatives should focus on achieving a shared mental model among all providers to improve collaboration and performance.

Acknowledgements

The authors thank the nurses, internal medicine housestaff physicians, and general internal medicine attending physicians at the Penn State Hershey Medical Center for their participation in this study.

Disclosure: Nothing to report.

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  15. Burtscher MJ, Manser T. Team mental models and their potential to improve teamwork and safety: a review and implications for future research in healthcare. Saf Sci. 2012;50(5):13441354.
  16. Creswell JW. Editorial: mapping the field of mixed methods research. J Mix Methods Res. 2009;3(2):95108.
  17. White C, Del Rey JG. Decreasing adverse events through night talks: an interdisciplinary, hospital‐based quality improvement project. Perm J. Fall 2009;13(4):1622.
  18. Classen DC, Resar R, Griffin F, et al. “Global trigger tool” shows that adverse events in hospitals may be ten times greater than previously measured. Health Aff (Millwood). 2011;30(4):581589.
  19. Horwitz LI, Meredith T, Schuur JD, Shah NR, Kulkarni RG, Jenq GY. Dropping the baton: a qualitative analysis of failures during the transition from emergency department to inpatient care. Ann Emerg Med. 2009;53(6):701710.e704.
  20. McKinney M. Smoothing transitions. Joint Commission targets patient handoffs. Mod Healthc. 2010;40(43):89.
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Patients experience acute illness at all hours of the day. In acute care hospitals, over 60% of patient admissions occur outside of normal business hours, or the off hours.[1, 2] Similarly, the acute decompensation of patients already admitted to hospital‐based units is frequent, with 90% of rapid responses occurring between 9 pm and 6 am.[3] Research suggests worse hospital performance during off hours, including increased patient falls, in‐hospital cardiac arrest mortality, and severity of hospital employee injuries.[2, 4, 5, 6, 7]

Although hospital‐based services should match care demand, the disparity between patient acuity and hospital capability at night is significant. Off hours typically have lower staffing of nurses, and attending and housestaff physicians, and ancillary staff as well as limited availability of consultative and supportive services.[8] Additionally, off‐hours providers are subject to the physiological effects of imbalanced circadian rhythms, including fatigue, attenuating their abilities to provide high‐quality care. The significant patient care needs mandate continuous patient care delivery without compromising quality or safety. To achieve this, further defining the barriers to delivering quality care during off hours is essential to improvement efforts in medicine‐based units.

Previous investigations have found increased occurrence and severity of worker accidents, increased potential for higher occurrence of preventable adverse patient events, and decreased performance during off hours.[4, 9, 10] Additionally, detrimental effects of off‐hours care may be further magnified by rotating employees through both day and night shifts, a common practice in academic hospitals.[11, 12] Potentially modifiable outcomes, such as patient fall rate and in‐hospital cardiac arrest survival differ markedly between day and night shifts.[6, 13] These studies primarily report on specific diseases, such as myocardial infarction and stroke, and are investigated from the perspective of hospital‐level outcomes.

To our knowledge, no study has reported provider‐perceived quality and safety issues occurring during off hours in an academic setting. Likewise, although off‐hours collaborative care requires shared, interprofessional conceptualization regarding care delivery, this perspective has not been reported. Understanding the similarities and differences between provider perceptions will allow the construction of an interprofessional team mental model, facilitating the design of future quality improvement initiatives.[14, 15] Our objectives were to: (1) identify off‐hours quality and safety issues, (2) assess which issues are perceived as most significant, and (3) evaluate differences in perceptions of these issues between nurses, and attending and housestaff physicians.

METHODS

Study Design

To investigate quality and safety issues occurring during off hours, we employed a prospective, mixed‐methods sequential exploratory study design, involving an initial qualitative analysis of adverse events followed by quantitative survey assessment.[16] We chose a mixed‐methods approach because provider‐perceived off‐hours issues had not been explicitly identified in the literature, requiring preliminary qualitative assessment. For the purpose of this study, we defined off hours as the 7 pm to 7am time period, which overlapped night shifts for both nurses and physicians. The study was approved by the institutional review board as a quality improvement project.

Study Setting

The study was conducted at a 378‐bed, university‐based acute care hospital in central Pennsylvania. There are a total of 64 internal medicine beds located in 2 units: a general medicine unit (44 beds, staffed by 60 nurses, nurse‐to‐patient ratio 1:4) and an intermediate care unit (20 beds, staffed by 41 nurses, nurse‐to‐patient ratio 1:3). The medicine residency program consists of 69 residents and 14 combined internal medicinepediatrics residents. During the day, 3 teaching teams and 1 nonteaching team care for all medicine patients. Overnight, 3 junior/senior level residents admit patients to the medicine service, whereas 2 interns provide cross‐coverage for all medicine and specialty service patients. Starting in September 2012 (before data collection), an overnight faculty‐level academic hospitalist, or nocturnist, provided on‐site housestaff supervision.

Qualitative Data Collection

For the qualitative analysis, we used 2 methods to develop our database. First, we created an electronic survey (see Supporting Information, Appendix 1, in the online version of this article) to identify near misses/adverse events occurring overnight, distributed to the nocturnist, 3 daytime hospitalists, and unit charge nurses following each shift (October 2012March 2013). The survey items were developed for the purpose of this study, with several items modified from a previously published survey.[17] Second, residency program directors recorded field notes during end‐of‐rotation debriefings (1 hour) with departing overnight housestaff, which were then dictated and transcribed. The subsequent analysis from these sources informed the quantitative survey (see Supporting Information, Appendix 2, in the online version of this article).

Survey Instrument

Three months after the initiation of qualitative data collection, 1 investigator (J.D.G.) developed a preliminary codebook to identify categories and themes. From this codebook, the research team drafted a survey instrument (the complete qualitative analysis occurred after survey development). To maintain focus on systematic quality improvement, items related to perceived mismanagement, relationship tensions, and professionalism were excluded. The survey was pilot‐tested with 5 faculty physicians and 2 nursing staff, prompting several modifications to improve clarity. Primary demographic items included provider role (nurse, attending physician, or housestaff physician) and years in current role. The 24 survey items were grouped into 5 different categories: (1) Quality of Care Delivery, (2) Communication and Coordination, (3) Staffing and Supervision, (4) Patient Transfers, and (5) Consulting Service Issues. Each item was investigated on a 7‐point scale (1=lowest rating, 7=highest rating). Descriptive text was provided at the extremes (choices 1 and 7), whereas intermediary values (26) did not have descriptive cues. The descriptive anchors for Quality of Care Delivery and Patient Transfers were 1=never and 7=always, whereas the descriptive anchors Communication and Coordination and Staffing and Supervision were 1=poor and 7=superior; Consulting Service Issues used a mix of both. Providers with off‐hours experience were asked to rank 4 time periods (710 pm, 10 pm1 am, 14 am, 47 am) regarding quality of care delivery in the medicine units (1=best, 4=worst). We asked both daytime and nighttime providers about perceptions of off‐hours care because, given the boundary spanning the nature of medical care across work shifts, daytime providers frequently identify issues not apparent until hours (or even days) after completion of a night shift. A similar design was used in prior work investigating safety at night.[17]

Quantitative Data Collection

In June of 2013, we emailed a survey link (www.surveymonkey.com) to all medicine nurses, and attending and housestaff physicians. The email described the study, explained the voluntary nature of the project, and stated informed consent was implied by survey completion. As an incentive, respondents were provided an option to enter their name into a raffle to win 1 of 50, $5 gift certificates. Following the initial invitation, 3 weekly email reminders were sent by the lead investigator (J.D.G.) requesting completion.

Data Analysis

Using the preliminary codebook, 2 investigators (J.D.G., E.M.) jointly analyzed a segment of the dataset using Atlas.ti 6.0 (Scientific Software, Berlin, Germany). Two investigators independently coded the data, compared codes for agreement, and updated the codebook. The remaining data were coded independently, with regular adjudication sessions to modify the codebook. All investigators reviewed and agreed upon themes and representative quotations.

Descriptive statistics, Pearson correlation statistics, Kruskal‐Wallis tests, and signed rank tests (with Bonferroni correction) were used to report group characteristics, correlate rank order, make comparisons between groups (nursing staff, and attending and housestaff physicians; day/night providers), and compare quality rankings by time period, respectively. The data were analyzed using SAS 9.3 (SAS Institute Inc., Cary, NC) and Stata/IC‐8 (StataCorp, College Park, TX).

RESULTS

Qualitative Analysis of Off‐Hours' Adverse Events and Near Misses

A total of 190 events were reported by daytime attending physicians (n=100), nocturnists (n=60), and nighttime charge nurses (n=30). Although questions asked participants to describe near misses/adverse events, respondents also reported a number of global quality issues not related to specific events. Similarly, debriefing sessions with housestaff (n=5) addressed both specific overnight events and residency‐related issues. Seven themes were identified: (1) perceived mismanagement, (2) quality of delivery processes, (3) communication and coordination, (4) staffing and supervision, (5) patient transfers, (6) consulting service issues, and, (7) professionalism/relational tensions. Table 1 lists the code frequencies and exemplary quotations.

Quality and Safety Issues Occurring During the Off Hours in Medicine Units as Reported by Medicine Nurses, and Attending and Housestaff Physicians (322 Total Coding References)*
Category and ThemesCode Frequency No. (% of 322)Representative Quotation
  • NOTE: Abbreviations: BiPaP, bilevel positive airway pressure; DNI, do not intubate; DNR, do not resuscitate; ED, emergency department; EMR, electronic medical record; IV, intravenous; MRI, magnetic resonance imaging; stat, immediately. *Surveys from nursing staff, nocturnists, and daytime attending physicians produced 276 coding references; focus groups with residents produced 46 coding references (total 322). Code frequency indicates the number of times the specific code was identified or referenced in the analysis. For example, if a particular communication issue was discussed in detail, the code may have been referenced more than once. Of the 190 survey‐reported events, 74 received2 coding references. Quality of Delivery Processes included issues related to timeliness and delays (34 coding references) and patient safety issues (29 coding references).

Perceived mismanagement97 (30)We had a new admission to the general medicine unit with atrial flutter and rapid ventricular response who did not receive rate controlling agents but rather received diuretics. [The patient's] heart rate remained between 110 and 130 overnight, with a troponin rise in the am likely from demand. The attending note states rate controllers and discussed with housestaff, but this was not performed.
Quality of delivery processes63 (20)One patient had a delay in MRI scanning in the off hours due to the scanner being down and scheduling. When the patient went down, there seemed to be little attempt to make sure patient went through scanner; unclear if housestaff called or not to come to assist. Now, the delay in care is even further along.
Communication and coordination50 (16)A patient was transferred to the intermediate care unit with hypercarbic respiratory failure. The patient had delay of >1 hour to receive IV Bumex because pharmacy would not release the dose from Pyxis, and the nurse did not let us know there was a delay. When I asked the nurse why, she responded because she's not the only patient I have. I pointed out that the patient was in failure and needed Bumex, stat. If we had not clearly communicated either verbally or via computer, she should let us know how to do that better.
Staffing and supervision39 (12)A patient was admitted DNR/DNI with advanced dementia, new on BiPaP at 100%, and hypotensive. The team's intern [identified] the need for interventions, including a central line. This was discussed with overloaded intensive care unit resident. The intern struggled until another resident assisted along with the night attending. Issues included: initial triage, no resident backup for team, and attending backup. I should have been more hands on in the moment to assist the intern navigating the system of care. Many issues here, but no senior resident was involved in care until [late].
Patient transfers38 (12)One patient went from the emergency department [to us] on the 5th floor at 7:45 pm. The ED placed an order for packed red blood cells and it was written at 4:45 pm. When patient arrived on our floor at 7:45 pm, the transfusion had not been started. The floor nurse started it at 8:10 pm .
Consulting services18 (6)Regarding a new outside hospital transfer, the medicine team was informed that [the consulting service] would place official consult on the chart when imaging studies from the outside institution were available. Despite this, the consult was still not done after 36 hours, and [we are] still waiting. We contacted service several times.
Professionalism and relational tensions17 (5)[One admission from the emergency department] involved a patient who received subcutaneous insulin for hyperkalemia as opposed to intravenous insulin. When brought to [their] attention, they became very confrontational and abrupt and denied having ordered or administered it that way, although it was documented in the EMR.

Perceived Mismanagement

Participants commonly questioned the decision making, diagnosis, or management of off‐hours providers. Concerns included the response to acute illness (eg, delay in calling a code), treatment decisions (eg, diuresis in a patient with urinary retention), or omission of necessary actions (eg, no cultures ordered for septicemia).

Quality of Delivery Processes

Participants frequently described quality of care delivery issues primarily related to timeliness or delays in delivery processes (34/63 coding references), or patient safety issues (29/63 coding references). Described events revealed concerns about the timeliness of lab reporting, imaging, blood draws, and medication ordering/processing.

Communication and Coordination

Breakdowns in communication and coordination often threatened patient safety. Identified issues included poor communication between primary physicians, nurses, consulting services, and emergency department (ED) providers, as well as documentation within the electronic medical record.

Staffing and Supervision

Several events highlighted staffing or supervision limitations, such as perceived low nursing or physician staffing levels. The degree of nocturnist supervision was polarizing, with both increased and decreased levels of supervision reported as limiting care delivery (or housestaff education).

Patient Transfers

Patient transfers to medicine units from the ED, other inpatient units, or outside hospitals, were identified several times as an influential factor. The care transition and need for information exchange led to a perceived compromise in quality or safety.

Consulting Service Issues

Several examples highlighted perceived issues related to the communication, coordination, or timeliness of consultant services in providing care.

Professionalism/Relational Tensions

Last, providers described situations in which they perceived lack of professionalism or relational tensions between providers, either in regard to interactions or clinical decisions in patient care.

Quantitative Results

Of 214 surveys sent, data were collected from 160 respondents (75% response), including 64/101 nursing staff (63% response), 25/28 attending physicians (80% response), and 71/85 housestaff physicians (84% response). Table 2 describes the participant demographics.

Demographics of Medicine Nursing Staff, and Attending and Housestaff Physicians (n=160).
VariableNo. (%)
  • NOTE: Abbreviations: SD, standard deviation. *Senior resident includes third‐ and fourth‐year medicine or medicine/pediatrics residents.

Nursing staff64 (40)
Intermediate care unit20
General medicine ward44
All night shifts16
Mix of day and night shifts26
Years of experience, mean (SD)7.7 (9.7)
Attending physicians25 (16)
No. providing care only at night4
No. of weeks as overnight hospitalist in past year, mean (SD)11.5 (4.1)
No. providing care only during the day21
Years since residency graduation, mean (SD)9.0 (8.5)
Medicine residents71 (44)
Intern27
Junior resident23
Senior resident*21

Off‐Hours Quality and Safety Issues

Ratings and comparisons of the 24 items are shown in Table 3. For all items, the mean rating was below 5 (7‐point scale). Lowest‐rated (least optimal) items were: timeliness, safety, and communication involved with patients admitted from the ED, number of attending physicians, and timeliness of consults and blood draws. Highest‐rated (more optimal) items were: timely reporting of labs, timely identification of deteriorating status, medication ordering and processing, communication between physicians, and safety and communication involved with intraservice transfers.

Comparison of Quality and Safety Issues Occurring During Off Hours as Reported by Nursing Staff, and Attending and Housestaff Physicians (n=160)
Category and Survey Item, Mean (SD)*Total (160)Providers With Night ExperienceNighttime Providers (116)Daytime Providers (44)P Value
Nurses (41)Attending Physicians (4)Housestaff (71)P Value
  • NOTE: Abbreviations: SD, standard deviation. *Answer choices included 7 options from 1 (poor) to 7 (superior). Kruskal‐Wallis with ties. Daytime providers are individuals without any night experience; all housestaff, given night float rotations, were included in the nighttime providers group.

Quality of care delivery        
Timely reporting of labs at night4.70 (1.39)5.12 (1.50)4.50 (1.00)4.61 (1.47)0.114.78 (1.48)4.48 (1.11)0.09
Timely identification of deteriorating status4.67 (1.34)4.88 (1.36)5.00 (0.82)4.85 (1.20)0.934.86 (1.24)4.16 (1.45)0.006
Medication ordering and processing4.63 (1.13)4.88 (1.25)5.25 (0.50)4.66 (1.08)0.194.76 (1.13)4.27 (1.06)0.01
Timely completion of imaging at night4.29 (1.32)4.32 (1.46)4.75 (0.96)4.39 (1.29)0.884.38 (1.34)4.05 (1.26)0.12
Timely reporting of results at night4.19 (1.43)4.27 (1.53)4.00 (1.83)4.11 (1.44)0.844.16 (1.47)4.27 (1.30)0.76
Timely med release from pharmacy at night4.16 (1.29)4.00 (1.32)4.50 (0.58)4.28 (1.29)0.444.19 (1.28)4.09 (1.31)0.90
Timely blood draws at night3.96 (1.52)4.63 (1.44)4.50 (0.58)3.53 (1.49)<0.0013.96 (1.54)3.98 (1.47)0.98
Communication and coordination
Communication between physicians4.63 (1.26)4.29 (1.23)6.00 (1.15)5.14 (1.12)<0.0014.87 (1.24)3.98 (1.09)<0.001
Communication between nursing and pharmacy4.39 (1.27)4.83 (1.41)5.00 (0.82)4.27 (1.29)0.044.49 (1.34)4.11 (4.11)0.08
Communication between nursing and physicians4.39 (1.28)4.44 (1.36)5.00 (0.82)4.58 (1.31)0.644.54 (1.31)3.98 (1.13)0.01
Documentation in medical record4.33 (1.36)5.00 (1.36)6.00 (0.82)4.23 1.19)<0.0014.56 (1.31)3.70 (1.30)<0.001
Ease of contacting primary providers at night4.31 (1.29)4.46 (1.27)6.00 (0.00)4.54 (1.18)0.024.56 (1.22)3.66 (1.27)<0.001
Staffing and supervision
No. of nursing staff4.51 (1.27)4.54 (1.50)5.50 (0.58)4.59 (1.21)0.254.60 (1.31)4.25 (1.14)0.025
Supervision of housestaff4.43 (1.34)4.56 (1.40)6.25 (0.50)4.55 (1.34)0.034.61 (1.37)3.95 (1.14)0.002
No. of housestaff4.09 (1.39)4.27 (1.40)4.50 (1.29)4.11 (1.44)0.704.18 (1.41)3.86 (1.32)0.12
No. of ancillary staff4.00 (1.40)4.27 (1.53)5.75 (0.96)3.85 (1.40)0.024.06 (1.48)3.84 (1.18)0.27
No. of attending physicians3.79 (1.50)3.49 (1.76)5.25 (0.96)3.89 (1.43)0.073.79 (1.57)3.80 (1.32)0.98
Patient transfers
For patients accepted to medicine from another medicine unit
Timely and safe patient transfers4.56 (1.28)5.15 (1.11)4.75 (0.50)4.55 (1.23)0.0254.77 (1.20)4.00 (1.33)0.001
High quality communication between providers4.55 (1.35)5.34 (1.13)5.00 (0.82)4.49 (1.22)0.0014.81 (1.24)3.86 (1.41)<0.001
For patients admitted from emergency department to medicine unit
Appropriate testing and treatment4.16 (1.34)4.15 (1.30)4.00 (1.83)4.21 (1.43)0.964.18 (1.39)4.11 (1.20)0.66
Timely and safe transfers3.89 (1.38)3.63 (1.50)5.50 (0.58)4.08 (1.32)0.023.97 (1.40)3.68 1.29)0.23
High‐quality communication between providers2.93 (1.38)2.56 (1.23)3.75 (1.26)3.00 (1.39)0.082.87 (1.35)3.07 (1.47)0.41
Consulting service issues
Timely consults at night4.04 (1.35)4.27 (1.28)4.00 (0.82)4.10 (1.47)0.694.16 (1.38)3.73 (1.25)0.053
Communication between consults and physicians3.93 (1.40)3.46 (1.45)5.75 (1.26)4.35 (1.27)<0.0014.09 (1.42)3.50 (1.27)0.016

Comparisons Between Professional Groups With Night Experience

Of the 24 items, 11 showed statistically significant differences between groups (P<0.05). Items with the largest difference between groups included: timely blood draws at night (housestaff physicians lowest), communication between physicians (nursing lowest), documentation in medical record (housestaff physicians lowest), and communication between consults and physicians (nursing lowest). The rank order between housestaff physicians and nurses, and housestaff and attending physicians showed moderately positive correlations (r=0.61, P=0.002 and r=0.47, P=0.022, respectively). The correlation between nurses and attending physicians showed a weak correlation (r=0.19, P=0.375).

Comparisons Between Front‐Line Providers With and Without Night Experience

Of the 24 items, 12 showed statistically significant differences between groups (P<0.05), with day providers reporting lower ratings in all 12. Items with the largest difference between groups included: communication between consults and physicians, ease of contacting providers, communication between providers, documentation, and safety and communication related to transfers from other units. The rank order between night and day groups showed a statistically significant positive correlation (r=0.65, P=0.001).

Perceived Highest Quality of Care Time Period During Off Hours

Compared with other time periods, all providers ranked 4 to 7 am as the period with the lowest quality of care delivery (mean rank 3.2, P0.001) (Figure 1). Nursing staff and attending physicians both ranked the 10 pm to 1 am time period as the best period (mean of 2.0 and 1.5, respectively), whereas housestaff physicians ranked the 7 to 10 pm as the best time period (mean 1.62). The only statistical difference between provider groups for any given time period was the 7 to 10 pm time period (P=0.002).

Figure 1
Comparison of mean rankings of quality within specific time periods during the night shift as reported by off‐hours providers—nursing staff, and attending and housestaff physicians (N = 116).

DISCUSSION

In this prospective, mixed‐methods study evaluating perceived off‐hours quality and safety issues, several themes were identified, including perceived mismanagement, insufficient quality of delivery processes, communication/coordination breakdowns, and staffing and supervision issues. In the quantitative analysis, lowest‐rated items (lowest quality) related to timeliness/safety/communication involved with ED transfers, number of attending physicians, and timeliness of consults and blood draws. Highest‐rated items (highest quality) related to timeliness of lab reporting and identification of deteriorating patients, medication ordering/processing, communication between physicians, and safety/communication during intraservice transfers. In general, day providers reported lower ratings than night providers on nearly all quality‐related items. Nursing staff reported the lowest ratings regarding communication between physicians and consults, whereas housestaff physicians reported the lowest ratings regarding documentation in the medical record and timely blood draws. These between‐group differences reveal the lack of shared conceptual understanding regarding off‐hours care delivery.

Our qualitative results reveal several significant issues related to care delivery during off hours, many of which are not obtainable by hospital‐level data or chart review.[18] For hospital‐based medicine units, an understanding of the structure‐ and process‐related factors associated with events is required for quality improvement efforts. Although the primary focus for this work was the off hours, it is plausible that providers may have identified similar issues as important issues during daytime hours. Our study was not designed to investigate if these perceived issues are specific to off hours, or if these issues are an accurate reflection of objective events occurring during this time period. We believe this topic deserves further investigation, as understanding if these off‐hours perceptions are unique to this time period would change the scope of future quality improvement initiatives.

The most significant finding in the quantitative results was the vulnerability in quality and safety during patient admissions from the ED, specifically in relation to communication and timeliness of transfer. Between‐unit handoffs for patients admitted from the ED to medicine units have been identified as particularly vulnerable to breakdowns in the communication process.[19, 20, 21, 22] There are multiple etiologies, including clinical uncertainty, higher acuity in patient illness early in hospitalization, and cultural differences between services.[23] Additionally, patterns of communication and standardized handoff processes are often insufficient. In our hospital system, the transfer process relies primarily upon synchronous communication methods without standardized, asynchronous information exchange. We hypothesize front‐line providers perceive this lack of standardization as a primary threat to quality. Because approximately 60% of new patient admissions from the ED to medicine service (both in our hospital and in prior studies) occur during off hours, these findings highlight a need for subsequent study and quality improvement efforts.[24]

During the time of this study, our medicine units were staffed at night by 5 medicine housestaff physicians and 1 academic hospitalist, or nocturnist. In efforts to improve quality and safety during off hours, our hospital, as well as other health systems, implemented the nocturnist position, a faculty‐level attending physician to provide off‐hours clinical care and housestaff supervision.[25] Although participants reported a moderate rating of housestaff supervision, participants provided lower scores for staffing numbers of nurses, and housestaff and attending physicians, despite nocturnist presence. With both increased off‐hours supervision in our hospital and increasing use of faculty‐level physicians in other academic programs, these results provide context for the anticipated level of overnight housestaff supervision.[26, 27] To our knowledge, this is the first study to investigate perceived overnight quality issues on medicine units following such staffing models. Although this model of direct, on‐site supervision in academic medicine programs may help offset staffing and supervisory issues during off hours, the nocturnist role is insufficient to offset threats to quality/safety already inherent within the system. Furthermore, prospective trials following implementation of nocturnist systems have shown mixed results in improving patient outcomes.[28] These findings have led some to question whether resources dedicated to nocturnist staffing may be better allocated to other overnight initiatives, highlighting the need for a more subtle understanding of quality issues to design targeted interventions.[29]

A notable finding from this work is that providers without night experience reported lower scores for 20 of 24 items, highlighting their perceptions of the quality of care delivery during off hours are lower than those who experience this environment. Although day providers are not directly experiencing off‐hours delivery processes, these providers receive and detect the results from care delivery at night.[17] Most nurse, physician, and hospital leaders are present in the hospital only during day hours, requiring these individuals to account for differences in perceived and actual care delivered overnight.[1] These individuals make critical decisions pertaining to process changes and quality improvement efforts in these units. We believe these results raise awareness for leadership decisions and quality improvement efforts in medicine service units, specifically to focus on overnight issues beyond staffing issues alone.

All respondent groups ranked the latter half of the shift (17 am) as lower in quality compared to the first 6 hours (7 pm1 am). This finding is contrary to our hypothesis that earlier time periods, during the majority of patient admissions (and presumed higher workload for all providers), would be perceived as lower quality. Reasons for this finding are unknown, but may relate to end‐of‐shift tasks, sign‐out preparation, provider fatigue, or disease‐related concerns (eg, increased incidence of stroke and myocardial infarction) during the latter portions of night shifts. One study identified a decrease in nursing clinical judgments from the beginning to end of 12‐hour shifts, with a potential suggested mechanism of decrease in ability to maintain attention during judgments.[30] Additionally, in a study by Folkard et al., risk was highest within the first several hours and fell substantially thereafter during a shift.[9] To our knowledge, no work has investigated perceived or objective quality outcomes by time period during the off‐hours shift in medicine units. Further work could help delineate why provider‐perceived compromises in quality occur late in off‐hours shifts and whether this correlates to safety events.

There are several limitations to our study. First, although all surveys were pilot tested for content validity, the construct validity was not rigorously assessed. Second, although data were collected from all participant groups, the collection methods were unbalanced, favoring attending‐level physician perspectives. Although the relative incidence of vulnerabilities in quality and safety should be interpreted with caution, our methods and general taxonomy provide a framework for developing and monitoring the perceptions of future interventions. Due to limitations in infrastructure, our findings could not be independently validated through review of reported adverse events, but previous investigations have found the vast majority of adverse events are not detected by standard anonymous reporting.[31, 32, 33] Our methodology (used in our prior work) may provide an independent means of detecting causes of poor quality not easily observed through routine surveillance.[22] Although many survey items showed statistical differences between provider groups, the clinical significance is subject to interpretation. Last, the perceptions and events related to our institution may not be fully generalizable to other academic programs or service lines, particularly in community‐based, nonteaching hospitals.

In conclusion, our results suggest a significant discrepancy between the concerns of day and night providers regarding the quality of care delivered to inpatients during the off hours, specifically with issues related to communication, quality‐of‐care delivery processes, and patient transfers from the ED. Although specific concerns may be institution‐ (and service line‐) dependent, appropriately designing initiatives to improve the quality of care delivered overnight will need to take the perspectives of both provider groups into account. Additionally, educational initiatives should focus on achieving a shared mental model among all providers to improve collaboration and performance.

Acknowledgements

The authors thank the nurses, internal medicine housestaff physicians, and general internal medicine attending physicians at the Penn State Hershey Medical Center for their participation in this study.

Disclosure: Nothing to report.

Patients experience acute illness at all hours of the day. In acute care hospitals, over 60% of patient admissions occur outside of normal business hours, or the off hours.[1, 2] Similarly, the acute decompensation of patients already admitted to hospital‐based units is frequent, with 90% of rapid responses occurring between 9 pm and 6 am.[3] Research suggests worse hospital performance during off hours, including increased patient falls, in‐hospital cardiac arrest mortality, and severity of hospital employee injuries.[2, 4, 5, 6, 7]

Although hospital‐based services should match care demand, the disparity between patient acuity and hospital capability at night is significant. Off hours typically have lower staffing of nurses, and attending and housestaff physicians, and ancillary staff as well as limited availability of consultative and supportive services.[8] Additionally, off‐hours providers are subject to the physiological effects of imbalanced circadian rhythms, including fatigue, attenuating their abilities to provide high‐quality care. The significant patient care needs mandate continuous patient care delivery without compromising quality or safety. To achieve this, further defining the barriers to delivering quality care during off hours is essential to improvement efforts in medicine‐based units.

Previous investigations have found increased occurrence and severity of worker accidents, increased potential for higher occurrence of preventable adverse patient events, and decreased performance during off hours.[4, 9, 10] Additionally, detrimental effects of off‐hours care may be further magnified by rotating employees through both day and night shifts, a common practice in academic hospitals.[11, 12] Potentially modifiable outcomes, such as patient fall rate and in‐hospital cardiac arrest survival differ markedly between day and night shifts.[6, 13] These studies primarily report on specific diseases, such as myocardial infarction and stroke, and are investigated from the perspective of hospital‐level outcomes.

To our knowledge, no study has reported provider‐perceived quality and safety issues occurring during off hours in an academic setting. Likewise, although off‐hours collaborative care requires shared, interprofessional conceptualization regarding care delivery, this perspective has not been reported. Understanding the similarities and differences between provider perceptions will allow the construction of an interprofessional team mental model, facilitating the design of future quality improvement initiatives.[14, 15] Our objectives were to: (1) identify off‐hours quality and safety issues, (2) assess which issues are perceived as most significant, and (3) evaluate differences in perceptions of these issues between nurses, and attending and housestaff physicians.

METHODS

Study Design

To investigate quality and safety issues occurring during off hours, we employed a prospective, mixed‐methods sequential exploratory study design, involving an initial qualitative analysis of adverse events followed by quantitative survey assessment.[16] We chose a mixed‐methods approach because provider‐perceived off‐hours issues had not been explicitly identified in the literature, requiring preliminary qualitative assessment. For the purpose of this study, we defined off hours as the 7 pm to 7am time period, which overlapped night shifts for both nurses and physicians. The study was approved by the institutional review board as a quality improvement project.

Study Setting

The study was conducted at a 378‐bed, university‐based acute care hospital in central Pennsylvania. There are a total of 64 internal medicine beds located in 2 units: a general medicine unit (44 beds, staffed by 60 nurses, nurse‐to‐patient ratio 1:4) and an intermediate care unit (20 beds, staffed by 41 nurses, nurse‐to‐patient ratio 1:3). The medicine residency program consists of 69 residents and 14 combined internal medicinepediatrics residents. During the day, 3 teaching teams and 1 nonteaching team care for all medicine patients. Overnight, 3 junior/senior level residents admit patients to the medicine service, whereas 2 interns provide cross‐coverage for all medicine and specialty service patients. Starting in September 2012 (before data collection), an overnight faculty‐level academic hospitalist, or nocturnist, provided on‐site housestaff supervision.

Qualitative Data Collection

For the qualitative analysis, we used 2 methods to develop our database. First, we created an electronic survey (see Supporting Information, Appendix 1, in the online version of this article) to identify near misses/adverse events occurring overnight, distributed to the nocturnist, 3 daytime hospitalists, and unit charge nurses following each shift (October 2012March 2013). The survey items were developed for the purpose of this study, with several items modified from a previously published survey.[17] Second, residency program directors recorded field notes during end‐of‐rotation debriefings (1 hour) with departing overnight housestaff, which were then dictated and transcribed. The subsequent analysis from these sources informed the quantitative survey (see Supporting Information, Appendix 2, in the online version of this article).

Survey Instrument

Three months after the initiation of qualitative data collection, 1 investigator (J.D.G.) developed a preliminary codebook to identify categories and themes. From this codebook, the research team drafted a survey instrument (the complete qualitative analysis occurred after survey development). To maintain focus on systematic quality improvement, items related to perceived mismanagement, relationship tensions, and professionalism were excluded. The survey was pilot‐tested with 5 faculty physicians and 2 nursing staff, prompting several modifications to improve clarity. Primary demographic items included provider role (nurse, attending physician, or housestaff physician) and years in current role. The 24 survey items were grouped into 5 different categories: (1) Quality of Care Delivery, (2) Communication and Coordination, (3) Staffing and Supervision, (4) Patient Transfers, and (5) Consulting Service Issues. Each item was investigated on a 7‐point scale (1=lowest rating, 7=highest rating). Descriptive text was provided at the extremes (choices 1 and 7), whereas intermediary values (26) did not have descriptive cues. The descriptive anchors for Quality of Care Delivery and Patient Transfers were 1=never and 7=always, whereas the descriptive anchors Communication and Coordination and Staffing and Supervision were 1=poor and 7=superior; Consulting Service Issues used a mix of both. Providers with off‐hours experience were asked to rank 4 time periods (710 pm, 10 pm1 am, 14 am, 47 am) regarding quality of care delivery in the medicine units (1=best, 4=worst). We asked both daytime and nighttime providers about perceptions of off‐hours care because, given the boundary spanning the nature of medical care across work shifts, daytime providers frequently identify issues not apparent until hours (or even days) after completion of a night shift. A similar design was used in prior work investigating safety at night.[17]

Quantitative Data Collection

In June of 2013, we emailed a survey link (www.surveymonkey.com) to all medicine nurses, and attending and housestaff physicians. The email described the study, explained the voluntary nature of the project, and stated informed consent was implied by survey completion. As an incentive, respondents were provided an option to enter their name into a raffle to win 1 of 50, $5 gift certificates. Following the initial invitation, 3 weekly email reminders were sent by the lead investigator (J.D.G.) requesting completion.

Data Analysis

Using the preliminary codebook, 2 investigators (J.D.G., E.M.) jointly analyzed a segment of the dataset using Atlas.ti 6.0 (Scientific Software, Berlin, Germany). Two investigators independently coded the data, compared codes for agreement, and updated the codebook. The remaining data were coded independently, with regular adjudication sessions to modify the codebook. All investigators reviewed and agreed upon themes and representative quotations.

Descriptive statistics, Pearson correlation statistics, Kruskal‐Wallis tests, and signed rank tests (with Bonferroni correction) were used to report group characteristics, correlate rank order, make comparisons between groups (nursing staff, and attending and housestaff physicians; day/night providers), and compare quality rankings by time period, respectively. The data were analyzed using SAS 9.3 (SAS Institute Inc., Cary, NC) and Stata/IC‐8 (StataCorp, College Park, TX).

RESULTS

Qualitative Analysis of Off‐Hours' Adverse Events and Near Misses

A total of 190 events were reported by daytime attending physicians (n=100), nocturnists (n=60), and nighttime charge nurses (n=30). Although questions asked participants to describe near misses/adverse events, respondents also reported a number of global quality issues not related to specific events. Similarly, debriefing sessions with housestaff (n=5) addressed both specific overnight events and residency‐related issues. Seven themes were identified: (1) perceived mismanagement, (2) quality of delivery processes, (3) communication and coordination, (4) staffing and supervision, (5) patient transfers, (6) consulting service issues, and, (7) professionalism/relational tensions. Table 1 lists the code frequencies and exemplary quotations.

Quality and Safety Issues Occurring During the Off Hours in Medicine Units as Reported by Medicine Nurses, and Attending and Housestaff Physicians (322 Total Coding References)*
Category and ThemesCode Frequency No. (% of 322)Representative Quotation
  • NOTE: Abbreviations: BiPaP, bilevel positive airway pressure; DNI, do not intubate; DNR, do not resuscitate; ED, emergency department; EMR, electronic medical record; IV, intravenous; MRI, magnetic resonance imaging; stat, immediately. *Surveys from nursing staff, nocturnists, and daytime attending physicians produced 276 coding references; focus groups with residents produced 46 coding references (total 322). Code frequency indicates the number of times the specific code was identified or referenced in the analysis. For example, if a particular communication issue was discussed in detail, the code may have been referenced more than once. Of the 190 survey‐reported events, 74 received2 coding references. Quality of Delivery Processes included issues related to timeliness and delays (34 coding references) and patient safety issues (29 coding references).

Perceived mismanagement97 (30)We had a new admission to the general medicine unit with atrial flutter and rapid ventricular response who did not receive rate controlling agents but rather received diuretics. [The patient's] heart rate remained between 110 and 130 overnight, with a troponin rise in the am likely from demand. The attending note states rate controllers and discussed with housestaff, but this was not performed.
Quality of delivery processes63 (20)One patient had a delay in MRI scanning in the off hours due to the scanner being down and scheduling. When the patient went down, there seemed to be little attempt to make sure patient went through scanner; unclear if housestaff called or not to come to assist. Now, the delay in care is even further along.
Communication and coordination50 (16)A patient was transferred to the intermediate care unit with hypercarbic respiratory failure. The patient had delay of >1 hour to receive IV Bumex because pharmacy would not release the dose from Pyxis, and the nurse did not let us know there was a delay. When I asked the nurse why, she responded because she's not the only patient I have. I pointed out that the patient was in failure and needed Bumex, stat. If we had not clearly communicated either verbally or via computer, she should let us know how to do that better.
Staffing and supervision39 (12)A patient was admitted DNR/DNI with advanced dementia, new on BiPaP at 100%, and hypotensive. The team's intern [identified] the need for interventions, including a central line. This was discussed with overloaded intensive care unit resident. The intern struggled until another resident assisted along with the night attending. Issues included: initial triage, no resident backup for team, and attending backup. I should have been more hands on in the moment to assist the intern navigating the system of care. Many issues here, but no senior resident was involved in care until [late].
Patient transfers38 (12)One patient went from the emergency department [to us] on the 5th floor at 7:45 pm. The ED placed an order for packed red blood cells and it was written at 4:45 pm. When patient arrived on our floor at 7:45 pm, the transfusion had not been started. The floor nurse started it at 8:10 pm .
Consulting services18 (6)Regarding a new outside hospital transfer, the medicine team was informed that [the consulting service] would place official consult on the chart when imaging studies from the outside institution were available. Despite this, the consult was still not done after 36 hours, and [we are] still waiting. We contacted service several times.
Professionalism and relational tensions17 (5)[One admission from the emergency department] involved a patient who received subcutaneous insulin for hyperkalemia as opposed to intravenous insulin. When brought to [their] attention, they became very confrontational and abrupt and denied having ordered or administered it that way, although it was documented in the EMR.

Perceived Mismanagement

Participants commonly questioned the decision making, diagnosis, or management of off‐hours providers. Concerns included the response to acute illness (eg, delay in calling a code), treatment decisions (eg, diuresis in a patient with urinary retention), or omission of necessary actions (eg, no cultures ordered for septicemia).

Quality of Delivery Processes

Participants frequently described quality of care delivery issues primarily related to timeliness or delays in delivery processes (34/63 coding references), or patient safety issues (29/63 coding references). Described events revealed concerns about the timeliness of lab reporting, imaging, blood draws, and medication ordering/processing.

Communication and Coordination

Breakdowns in communication and coordination often threatened patient safety. Identified issues included poor communication between primary physicians, nurses, consulting services, and emergency department (ED) providers, as well as documentation within the electronic medical record.

Staffing and Supervision

Several events highlighted staffing or supervision limitations, such as perceived low nursing or physician staffing levels. The degree of nocturnist supervision was polarizing, with both increased and decreased levels of supervision reported as limiting care delivery (or housestaff education).

Patient Transfers

Patient transfers to medicine units from the ED, other inpatient units, or outside hospitals, were identified several times as an influential factor. The care transition and need for information exchange led to a perceived compromise in quality or safety.

Consulting Service Issues

Several examples highlighted perceived issues related to the communication, coordination, or timeliness of consultant services in providing care.

Professionalism/Relational Tensions

Last, providers described situations in which they perceived lack of professionalism or relational tensions between providers, either in regard to interactions or clinical decisions in patient care.

Quantitative Results

Of 214 surveys sent, data were collected from 160 respondents (75% response), including 64/101 nursing staff (63% response), 25/28 attending physicians (80% response), and 71/85 housestaff physicians (84% response). Table 2 describes the participant demographics.

Demographics of Medicine Nursing Staff, and Attending and Housestaff Physicians (n=160).
VariableNo. (%)
  • NOTE: Abbreviations: SD, standard deviation. *Senior resident includes third‐ and fourth‐year medicine or medicine/pediatrics residents.

Nursing staff64 (40)
Intermediate care unit20
General medicine ward44
All night shifts16
Mix of day and night shifts26
Years of experience, mean (SD)7.7 (9.7)
Attending physicians25 (16)
No. providing care only at night4
No. of weeks as overnight hospitalist in past year, mean (SD)11.5 (4.1)
No. providing care only during the day21
Years since residency graduation, mean (SD)9.0 (8.5)
Medicine residents71 (44)
Intern27
Junior resident23
Senior resident*21

Off‐Hours Quality and Safety Issues

Ratings and comparisons of the 24 items are shown in Table 3. For all items, the mean rating was below 5 (7‐point scale). Lowest‐rated (least optimal) items were: timeliness, safety, and communication involved with patients admitted from the ED, number of attending physicians, and timeliness of consults and blood draws. Highest‐rated (more optimal) items were: timely reporting of labs, timely identification of deteriorating status, medication ordering and processing, communication between physicians, and safety and communication involved with intraservice transfers.

Comparison of Quality and Safety Issues Occurring During Off Hours as Reported by Nursing Staff, and Attending and Housestaff Physicians (n=160)
Category and Survey Item, Mean (SD)*Total (160)Providers With Night ExperienceNighttime Providers (116)Daytime Providers (44)P Value
Nurses (41)Attending Physicians (4)Housestaff (71)P Value
  • NOTE: Abbreviations: SD, standard deviation. *Answer choices included 7 options from 1 (poor) to 7 (superior). Kruskal‐Wallis with ties. Daytime providers are individuals without any night experience; all housestaff, given night float rotations, were included in the nighttime providers group.

Quality of care delivery        
Timely reporting of labs at night4.70 (1.39)5.12 (1.50)4.50 (1.00)4.61 (1.47)0.114.78 (1.48)4.48 (1.11)0.09
Timely identification of deteriorating status4.67 (1.34)4.88 (1.36)5.00 (0.82)4.85 (1.20)0.934.86 (1.24)4.16 (1.45)0.006
Medication ordering and processing4.63 (1.13)4.88 (1.25)5.25 (0.50)4.66 (1.08)0.194.76 (1.13)4.27 (1.06)0.01
Timely completion of imaging at night4.29 (1.32)4.32 (1.46)4.75 (0.96)4.39 (1.29)0.884.38 (1.34)4.05 (1.26)0.12
Timely reporting of results at night4.19 (1.43)4.27 (1.53)4.00 (1.83)4.11 (1.44)0.844.16 (1.47)4.27 (1.30)0.76
Timely med release from pharmacy at night4.16 (1.29)4.00 (1.32)4.50 (0.58)4.28 (1.29)0.444.19 (1.28)4.09 (1.31)0.90
Timely blood draws at night3.96 (1.52)4.63 (1.44)4.50 (0.58)3.53 (1.49)<0.0013.96 (1.54)3.98 (1.47)0.98
Communication and coordination
Communication between physicians4.63 (1.26)4.29 (1.23)6.00 (1.15)5.14 (1.12)<0.0014.87 (1.24)3.98 (1.09)<0.001
Communication between nursing and pharmacy4.39 (1.27)4.83 (1.41)5.00 (0.82)4.27 (1.29)0.044.49 (1.34)4.11 (4.11)0.08
Communication between nursing and physicians4.39 (1.28)4.44 (1.36)5.00 (0.82)4.58 (1.31)0.644.54 (1.31)3.98 (1.13)0.01
Documentation in medical record4.33 (1.36)5.00 (1.36)6.00 (0.82)4.23 1.19)<0.0014.56 (1.31)3.70 (1.30)<0.001
Ease of contacting primary providers at night4.31 (1.29)4.46 (1.27)6.00 (0.00)4.54 (1.18)0.024.56 (1.22)3.66 (1.27)<0.001
Staffing and supervision
No. of nursing staff4.51 (1.27)4.54 (1.50)5.50 (0.58)4.59 (1.21)0.254.60 (1.31)4.25 (1.14)0.025
Supervision of housestaff4.43 (1.34)4.56 (1.40)6.25 (0.50)4.55 (1.34)0.034.61 (1.37)3.95 (1.14)0.002
No. of housestaff4.09 (1.39)4.27 (1.40)4.50 (1.29)4.11 (1.44)0.704.18 (1.41)3.86 (1.32)0.12
No. of ancillary staff4.00 (1.40)4.27 (1.53)5.75 (0.96)3.85 (1.40)0.024.06 (1.48)3.84 (1.18)0.27
No. of attending physicians3.79 (1.50)3.49 (1.76)5.25 (0.96)3.89 (1.43)0.073.79 (1.57)3.80 (1.32)0.98
Patient transfers
For patients accepted to medicine from another medicine unit
Timely and safe patient transfers4.56 (1.28)5.15 (1.11)4.75 (0.50)4.55 (1.23)0.0254.77 (1.20)4.00 (1.33)0.001
High quality communication between providers4.55 (1.35)5.34 (1.13)5.00 (0.82)4.49 (1.22)0.0014.81 (1.24)3.86 (1.41)<0.001
For patients admitted from emergency department to medicine unit
Appropriate testing and treatment4.16 (1.34)4.15 (1.30)4.00 (1.83)4.21 (1.43)0.964.18 (1.39)4.11 (1.20)0.66
Timely and safe transfers3.89 (1.38)3.63 (1.50)5.50 (0.58)4.08 (1.32)0.023.97 (1.40)3.68 1.29)0.23
High‐quality communication between providers2.93 (1.38)2.56 (1.23)3.75 (1.26)3.00 (1.39)0.082.87 (1.35)3.07 (1.47)0.41
Consulting service issues
Timely consults at night4.04 (1.35)4.27 (1.28)4.00 (0.82)4.10 (1.47)0.694.16 (1.38)3.73 (1.25)0.053
Communication between consults and physicians3.93 (1.40)3.46 (1.45)5.75 (1.26)4.35 (1.27)<0.0014.09 (1.42)3.50 (1.27)0.016

Comparisons Between Professional Groups With Night Experience

Of the 24 items, 11 showed statistically significant differences between groups (P<0.05). Items with the largest difference between groups included: timely blood draws at night (housestaff physicians lowest), communication between physicians (nursing lowest), documentation in medical record (housestaff physicians lowest), and communication between consults and physicians (nursing lowest). The rank order between housestaff physicians and nurses, and housestaff and attending physicians showed moderately positive correlations (r=0.61, P=0.002 and r=0.47, P=0.022, respectively). The correlation between nurses and attending physicians showed a weak correlation (r=0.19, P=0.375).

Comparisons Between Front‐Line Providers With and Without Night Experience

Of the 24 items, 12 showed statistically significant differences between groups (P<0.05), with day providers reporting lower ratings in all 12. Items with the largest difference between groups included: communication between consults and physicians, ease of contacting providers, communication between providers, documentation, and safety and communication related to transfers from other units. The rank order between night and day groups showed a statistically significant positive correlation (r=0.65, P=0.001).

Perceived Highest Quality of Care Time Period During Off Hours

Compared with other time periods, all providers ranked 4 to 7 am as the period with the lowest quality of care delivery (mean rank 3.2, P0.001) (Figure 1). Nursing staff and attending physicians both ranked the 10 pm to 1 am time period as the best period (mean of 2.0 and 1.5, respectively), whereas housestaff physicians ranked the 7 to 10 pm as the best time period (mean 1.62). The only statistical difference between provider groups for any given time period was the 7 to 10 pm time period (P=0.002).

Figure 1
Comparison of mean rankings of quality within specific time periods during the night shift as reported by off‐hours providers—nursing staff, and attending and housestaff physicians (N = 116).

DISCUSSION

In this prospective, mixed‐methods study evaluating perceived off‐hours quality and safety issues, several themes were identified, including perceived mismanagement, insufficient quality of delivery processes, communication/coordination breakdowns, and staffing and supervision issues. In the quantitative analysis, lowest‐rated items (lowest quality) related to timeliness/safety/communication involved with ED transfers, number of attending physicians, and timeliness of consults and blood draws. Highest‐rated items (highest quality) related to timeliness of lab reporting and identification of deteriorating patients, medication ordering/processing, communication between physicians, and safety/communication during intraservice transfers. In general, day providers reported lower ratings than night providers on nearly all quality‐related items. Nursing staff reported the lowest ratings regarding communication between physicians and consults, whereas housestaff physicians reported the lowest ratings regarding documentation in the medical record and timely blood draws. These between‐group differences reveal the lack of shared conceptual understanding regarding off‐hours care delivery.

Our qualitative results reveal several significant issues related to care delivery during off hours, many of which are not obtainable by hospital‐level data or chart review.[18] For hospital‐based medicine units, an understanding of the structure‐ and process‐related factors associated with events is required for quality improvement efforts. Although the primary focus for this work was the off hours, it is plausible that providers may have identified similar issues as important issues during daytime hours. Our study was not designed to investigate if these perceived issues are specific to off hours, or if these issues are an accurate reflection of objective events occurring during this time period. We believe this topic deserves further investigation, as understanding if these off‐hours perceptions are unique to this time period would change the scope of future quality improvement initiatives.

The most significant finding in the quantitative results was the vulnerability in quality and safety during patient admissions from the ED, specifically in relation to communication and timeliness of transfer. Between‐unit handoffs for patients admitted from the ED to medicine units have been identified as particularly vulnerable to breakdowns in the communication process.[19, 20, 21, 22] There are multiple etiologies, including clinical uncertainty, higher acuity in patient illness early in hospitalization, and cultural differences between services.[23] Additionally, patterns of communication and standardized handoff processes are often insufficient. In our hospital system, the transfer process relies primarily upon synchronous communication methods without standardized, asynchronous information exchange. We hypothesize front‐line providers perceive this lack of standardization as a primary threat to quality. Because approximately 60% of new patient admissions from the ED to medicine service (both in our hospital and in prior studies) occur during off hours, these findings highlight a need for subsequent study and quality improvement efforts.[24]

During the time of this study, our medicine units were staffed at night by 5 medicine housestaff physicians and 1 academic hospitalist, or nocturnist. In efforts to improve quality and safety during off hours, our hospital, as well as other health systems, implemented the nocturnist position, a faculty‐level attending physician to provide off‐hours clinical care and housestaff supervision.[25] Although participants reported a moderate rating of housestaff supervision, participants provided lower scores for staffing numbers of nurses, and housestaff and attending physicians, despite nocturnist presence. With both increased off‐hours supervision in our hospital and increasing use of faculty‐level physicians in other academic programs, these results provide context for the anticipated level of overnight housestaff supervision.[26, 27] To our knowledge, this is the first study to investigate perceived overnight quality issues on medicine units following such staffing models. Although this model of direct, on‐site supervision in academic medicine programs may help offset staffing and supervisory issues during off hours, the nocturnist role is insufficient to offset threats to quality/safety already inherent within the system. Furthermore, prospective trials following implementation of nocturnist systems have shown mixed results in improving patient outcomes.[28] These findings have led some to question whether resources dedicated to nocturnist staffing may be better allocated to other overnight initiatives, highlighting the need for a more subtle understanding of quality issues to design targeted interventions.[29]

A notable finding from this work is that providers without night experience reported lower scores for 20 of 24 items, highlighting their perceptions of the quality of care delivery during off hours are lower than those who experience this environment. Although day providers are not directly experiencing off‐hours delivery processes, these providers receive and detect the results from care delivery at night.[17] Most nurse, physician, and hospital leaders are present in the hospital only during day hours, requiring these individuals to account for differences in perceived and actual care delivered overnight.[1] These individuals make critical decisions pertaining to process changes and quality improvement efforts in these units. We believe these results raise awareness for leadership decisions and quality improvement efforts in medicine service units, specifically to focus on overnight issues beyond staffing issues alone.

All respondent groups ranked the latter half of the shift (17 am) as lower in quality compared to the first 6 hours (7 pm1 am). This finding is contrary to our hypothesis that earlier time periods, during the majority of patient admissions (and presumed higher workload for all providers), would be perceived as lower quality. Reasons for this finding are unknown, but may relate to end‐of‐shift tasks, sign‐out preparation, provider fatigue, or disease‐related concerns (eg, increased incidence of stroke and myocardial infarction) during the latter portions of night shifts. One study identified a decrease in nursing clinical judgments from the beginning to end of 12‐hour shifts, with a potential suggested mechanism of decrease in ability to maintain attention during judgments.[30] Additionally, in a study by Folkard et al., risk was highest within the first several hours and fell substantially thereafter during a shift.[9] To our knowledge, no work has investigated perceived or objective quality outcomes by time period during the off‐hours shift in medicine units. Further work could help delineate why provider‐perceived compromises in quality occur late in off‐hours shifts and whether this correlates to safety events.

There are several limitations to our study. First, although all surveys were pilot tested for content validity, the construct validity was not rigorously assessed. Second, although data were collected from all participant groups, the collection methods were unbalanced, favoring attending‐level physician perspectives. Although the relative incidence of vulnerabilities in quality and safety should be interpreted with caution, our methods and general taxonomy provide a framework for developing and monitoring the perceptions of future interventions. Due to limitations in infrastructure, our findings could not be independently validated through review of reported adverse events, but previous investigations have found the vast majority of adverse events are not detected by standard anonymous reporting.[31, 32, 33] Our methodology (used in our prior work) may provide an independent means of detecting causes of poor quality not easily observed through routine surveillance.[22] Although many survey items showed statistical differences between provider groups, the clinical significance is subject to interpretation. Last, the perceptions and events related to our institution may not be fully generalizable to other academic programs or service lines, particularly in community‐based, nonteaching hospitals.

In conclusion, our results suggest a significant discrepancy between the concerns of day and night providers regarding the quality of care delivered to inpatients during the off hours, specifically with issues related to communication, quality‐of‐care delivery processes, and patient transfers from the ED. Although specific concerns may be institution‐ (and service line‐) dependent, appropriately designing initiatives to improve the quality of care delivered overnight will need to take the perspectives of both provider groups into account. Additionally, educational initiatives should focus on achieving a shared mental model among all providers to improve collaboration and performance.

Acknowledgements

The authors thank the nurses, internal medicine housestaff physicians, and general internal medicine attending physicians at the Penn State Hershey Medical Center for their participation in this study.

Disclosure: Nothing to report.

References
  1. Shulkin DJ. Like night and day—shedding light on off‐hours care. N Engl J Med. 2008;358(20):20912093.
  2. Hillson SD, Dowd B, Rich EC, Luxenberg MG. Call nights and patient care. J Gen Intern Med. 1992;7(4):405410.
  3. Kaplan Lj, Maerz Ll, Schuster K, et al. Uncovering system errors using a rapid response team: cross‐coverage caught in the crossfire. Discussion. J Trauma. 2009;67(1):173179.
  4. Horwitz IB, McCall BP. The impact of shift work on the risk and severity of injuries for hospital employees: an analysis using Oregon workers' compensation data. Occup Med (Lond). 2004;54(8):556563.
  5. Bell CM, Redelmeier DA. Mortality among patients admitted to hospitals on weekends as compared with weekdays. N Engl J Med. 2001;345(9):663668.
  6. Patrician PA, Loan L, McCarthy M, et al. The association of shift‐level nurse staffing with adverse patient events. J Nurs Adm. 2011;41(2):6470.
  7. Lloyd‐Jones D, Adams RJ, Brown TM, et al. Heart disease and stroke statistics—2010 update A report from the American Heart Association. Circulation. 2010;121(7):e46e215.
  8. Spetz J, Seago JA, Coffman J, Rosenoff E, O'Neil E. Minimum Nurse Staffing Ratios In California Acute Care Hospitals. Oakland, CA: California Workforce Initiative; 2000.
  9. Folkard S, Tucker P. Shift work, safety and productivity. Occup Med (Lond). 2003;53(2):95101.
  10. Smith L, Folkard S, Poole C. Increased injuries on night shift. Lancet. 1994;344(8930):11371139.
  11. Wagstaff AS, Lie J‐AS. Shift and night work and long working hours‐a systematic review of safety implications. Scand J Work Environ Health. 2011:37(3):173185.
  12. Gold DR, Rogacz S, Bock N, et al. Rotating shift work, sleep, and accidents related to sleepiness in hospital nurses. Am J Public Health. 1992;82(7):10111014.
  13. Peberdy MA, Ornato JP, Larkin GL, et al. Survival from in‐hospital cardiac arrest during nights and weekends. JAMA. 2008;299(7):785792.
  14. Mathieu JE, Heffner TS, Goodwin GF, Salas E, Cannon‐Bowers JA. The influence of shared mental models on team process and performance. J Appl Psychol. 2000;85(2):273.
  15. Burtscher MJ, Manser T. Team mental models and their potential to improve teamwork and safety: a review and implications for future research in healthcare. Saf Sci. 2012;50(5):13441354.
  16. Creswell JW. Editorial: mapping the field of mixed methods research. J Mix Methods Res. 2009;3(2):95108.
  17. White C, Del Rey JG. Decreasing adverse events through night talks: an interdisciplinary, hospital‐based quality improvement project. Perm J. Fall 2009;13(4):1622.
  18. Classen DC, Resar R, Griffin F, et al. “Global trigger tool” shows that adverse events in hospitals may be ten times greater than previously measured. Health Aff (Millwood). 2011;30(4):581589.
  19. Horwitz LI, Meredith T, Schuur JD, Shah NR, Kulkarni RG, Jenq GY. Dropping the baton: a qualitative analysis of failures during the transition from emergency department to inpatient care. Ann Emerg Med. 2009;53(6):701710.e704.
  20. McKinney M. Smoothing transitions. Joint Commission targets patient handoffs. Mod Healthc. 2010;40(43):89.
  21. Wohlauer MV, Arora VM, Horwitz LI, Bass EJ, Mahar SE, Philibert I. The patient handoff: a comprehensive curricular blueprint for resident education to improve continuity of care. Acad Med. 2012;87(4):411418.
  22. Gonzalo JD, Yang JJ, Stuckey HL, Fischer CM, Sanchez LD, Herzig SJ. Patient care transitions from the emergency department to the medicine ward: evaluation of a standardized electronic signout tool. Int J Qual Health Care. 2014;26(4):337347.
  23. Hilligoss B, Cohen MD. The unappreciated challenges of between‐unit handoffs: negotiating and coordinating across boundaries. Ann Emerg Med. 2013;61(2):155160.
  24. Khanna R, Wachsberg K, Marouni A, Feinglass J, Williams MV, Wayne DB. The association between night or weekend admission and hospitalization‐relevant patient outcomes. J Hosp Med. 2011;6(1):1014.
  25. Walkinshaw E. Middle‐of‐the‐night medicine is rarely patient‐centred. CMAJ. 2011;183(13):14671468.
  26. Farnan JM, Burger A, Boonyasai RT, et al. Survey of overnight academic hospitalist supervision of trainees. J Hosp Med. 2012;7(7):521523.
  27. Haber LA, Lau CY, Sharpe BA, Arora VM, Farnan JM, Ranji SR. Effects of increased overnight supervision on resident education, decision‐making, and autonomy. J Hosp Med. 2012;7(8):606610.
  28. Kerlin MP, Small DS, Cooney E, et al. A randomized trial of nighttime physician staffing in an intensive care unit. N Engl J Med. 2013;368(23):22012209.
  29. Levy MM. Intensivists at night: putting resources in the right place. Crit Care. 2013;17(5):1008.
  30. McClelland LE, Switzer FS, Pilcher JJ. Changes in nurses' decision making during a 12‐h day shift. Occup Med (Lond). 2013;63(1):6065.
  31. Cullen DJ, Bates DW, Small SD, Cooper JB, Nemeskal AR, Leape LL. The incident reporting system does not detect adverse drug events: a problem for quality improvement. Jt Comm J Qual Improv. 1995;21(10):541548.
  32. Stanhope N, Crowley‐Murphy M, Vincent C, O'Connor AM, Taylor‐Adams SE. An evaluation of adverse incident reporting. J Eval Clin Pract. 1999;5(1):512.
  33. Barach P, Small SD. Reporting and preventing medical mishaps: lessons from non‐medical near miss reporting systems. BMJ. 2000;320(7237):759763.
References
  1. Shulkin DJ. Like night and day—shedding light on off‐hours care. N Engl J Med. 2008;358(20):20912093.
  2. Hillson SD, Dowd B, Rich EC, Luxenberg MG. Call nights and patient care. J Gen Intern Med. 1992;7(4):405410.
  3. Kaplan Lj, Maerz Ll, Schuster K, et al. Uncovering system errors using a rapid response team: cross‐coverage caught in the crossfire. Discussion. J Trauma. 2009;67(1):173179.
  4. Horwitz IB, McCall BP. The impact of shift work on the risk and severity of injuries for hospital employees: an analysis using Oregon workers' compensation data. Occup Med (Lond). 2004;54(8):556563.
  5. Bell CM, Redelmeier DA. Mortality among patients admitted to hospitals on weekends as compared with weekdays. N Engl J Med. 2001;345(9):663668.
  6. Patrician PA, Loan L, McCarthy M, et al. The association of shift‐level nurse staffing with adverse patient events. J Nurs Adm. 2011;41(2):6470.
  7. Lloyd‐Jones D, Adams RJ, Brown TM, et al. Heart disease and stroke statistics—2010 update A report from the American Heart Association. Circulation. 2010;121(7):e46e215.
  8. Spetz J, Seago JA, Coffman J, Rosenoff E, O'Neil E. Minimum Nurse Staffing Ratios In California Acute Care Hospitals. Oakland, CA: California Workforce Initiative; 2000.
  9. Folkard S, Tucker P. Shift work, safety and productivity. Occup Med (Lond). 2003;53(2):95101.
  10. Smith L, Folkard S, Poole C. Increased injuries on night shift. Lancet. 1994;344(8930):11371139.
  11. Wagstaff AS, Lie J‐AS. Shift and night work and long working hours‐a systematic review of safety implications. Scand J Work Environ Health. 2011:37(3):173185.
  12. Gold DR, Rogacz S, Bock N, et al. Rotating shift work, sleep, and accidents related to sleepiness in hospital nurses. Am J Public Health. 1992;82(7):10111014.
  13. Peberdy MA, Ornato JP, Larkin GL, et al. Survival from in‐hospital cardiac arrest during nights and weekends. JAMA. 2008;299(7):785792.
  14. Mathieu JE, Heffner TS, Goodwin GF, Salas E, Cannon‐Bowers JA. The influence of shared mental models on team process and performance. J Appl Psychol. 2000;85(2):273.
  15. Burtscher MJ, Manser T. Team mental models and their potential to improve teamwork and safety: a review and implications for future research in healthcare. Saf Sci. 2012;50(5):13441354.
  16. Creswell JW. Editorial: mapping the field of mixed methods research. J Mix Methods Res. 2009;3(2):95108.
  17. White C, Del Rey JG. Decreasing adverse events through night talks: an interdisciplinary, hospital‐based quality improvement project. Perm J. Fall 2009;13(4):1622.
  18. Classen DC, Resar R, Griffin F, et al. “Global trigger tool” shows that adverse events in hospitals may be ten times greater than previously measured. Health Aff (Millwood). 2011;30(4):581589.
  19. Horwitz LI, Meredith T, Schuur JD, Shah NR, Kulkarni RG, Jenq GY. Dropping the baton: a qualitative analysis of failures during the transition from emergency department to inpatient care. Ann Emerg Med. 2009;53(6):701710.e704.
  20. McKinney M. Smoothing transitions. Joint Commission targets patient handoffs. Mod Healthc. 2010;40(43):89.
  21. Wohlauer MV, Arora VM, Horwitz LI, Bass EJ, Mahar SE, Philibert I. The patient handoff: a comprehensive curricular blueprint for resident education to improve continuity of care. Acad Med. 2012;87(4):411418.
  22. Gonzalo JD, Yang JJ, Stuckey HL, Fischer CM, Sanchez LD, Herzig SJ. Patient care transitions from the emergency department to the medicine ward: evaluation of a standardized electronic signout tool. Int J Qual Health Care. 2014;26(4):337347.
  23. Hilligoss B, Cohen MD. The unappreciated challenges of between‐unit handoffs: negotiating and coordinating across boundaries. Ann Emerg Med. 2013;61(2):155160.
  24. Khanna R, Wachsberg K, Marouni A, Feinglass J, Williams MV, Wayne DB. The association between night or weekend admission and hospitalization‐relevant patient outcomes. J Hosp Med. 2011;6(1):1014.
  25. Walkinshaw E. Middle‐of‐the‐night medicine is rarely patient‐centred. CMAJ. 2011;183(13):14671468.
  26. Farnan JM, Burger A, Boonyasai RT, et al. Survey of overnight academic hospitalist supervision of trainees. J Hosp Med. 2012;7(7):521523.
  27. Haber LA, Lau CY, Sharpe BA, Arora VM, Farnan JM, Ranji SR. Effects of increased overnight supervision on resident education, decision‐making, and autonomy. J Hosp Med. 2012;7(8):606610.
  28. Kerlin MP, Small DS, Cooney E, et al. A randomized trial of nighttime physician staffing in an intensive care unit. N Engl J Med. 2013;368(23):22012209.
  29. Levy MM. Intensivists at night: putting resources in the right place. Crit Care. 2013;17(5):1008.
  30. McClelland LE, Switzer FS, Pilcher JJ. Changes in nurses' decision making during a 12‐h day shift. Occup Med (Lond). 2013;63(1):6065.
  31. Cullen DJ, Bates DW, Small SD, Cooper JB, Nemeskal AR, Leape LL. The incident reporting system does not detect adverse drug events: a problem for quality improvement. Jt Comm J Qual Improv. 1995;21(10):541548.
  32. Stanhope N, Crowley‐Murphy M, Vincent C, O'Connor AM, Taylor‐Adams SE. An evaluation of adverse incident reporting. J Eval Clin Pract. 1999;5(1):512.
  33. Barach P, Small SD. Reporting and preventing medical mishaps: lessons from non‐medical near miss reporting systems. BMJ. 2000;320(7237):759763.
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Quality and safety during the off hours in medicine units: A mixed methods study of front‐line provider perspectives
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Address for correspondence and reprint requests: Jed Gonzalo, MD, Division of General Internal Medicine, Penn State Hershey Medical Center–HO34, 500 University Drive, Hershey, PA, 17033; Telephone: 717‐531‐8161; Fax: 717‐531‐7726; E‐mail: [email protected]
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Bedside Interprofessional Rounds

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Bedside interprofessional rounds: Perceptions of benefits and barriers by internal medicine nursing staff, attending physicians, and housestaff physicians

Interprofessional collaborative care (IPCC) involves members from different professions working together to enhance communication, coordination, and healthcare quality.[1, 2, 3] Because several current healthcare policy initiatives include financial incentives for increased quality of care, there has been resultant interest in the implementation of IPCC in healthcare systems.[4, 5] Unfortunately, many hospitals have found IPCC difficult to achieve. Hospital‐based medicine units are complex, time‐constrained environments requiring a high degree of collaboration and mutual decision‐making between nurses, physicians, therapists, pharmacists, care coordinators, and patients. In addition, despite recommendations for interprofessional collaborative care, the implementation and assessment of IPCC within this environment has not been well studied.[6, 7]

On academic internal medicine services, the majority of care decisions occur during rounds. Although rounds provide a common structure, the participants, length, location, and agenda of rounds tend to vary by institution and individual physician preference.[8, 9, 10, 11] Traditionally, ward rounds occur mostly in hallways and conference rooms rather than the patient's bedside.[12] Additionally, during rounds, nurse‐physician collaboration occurs infrequently, estimated at <10% of rounding time.[13] Recently, an increased focus on quality, safety, and collaboration has inspired the investigation and implementation of new methods to increase interprofessional collaboration during rounds, but many of these interventions occurred away from the patient's bedside.[14, 15] One trial of bedside interprofessional rounds (BIRs) by Curley et al. suggested improvements in patient‐level outcomes (cost and length of stay) versus traditional physician‐based rounds.[16] Although interprofessional nurse‐physician rounds at patients' bedsides may represent an ideal process, limited work has investigated this activity.[17]

A prerequisite for successful and sustained integration of BIRs is a shared conceptualization among physicians and nurses regarding the process. Such a shared conceptualization would include perceptions of benefits and barriers to implementation.[18] Currently, such perceptions have not been measured. In this study, we sought to evaluate perceptions of front‐line care providers on inpatient units, specifically nursing staff, attending physicians, and housestaff physicians, regarding the benefits and barriers to BIRs.

METHODS

Study Design and Participants

In June 2013, we performed a cross‐sectional assessment of front‐line providers caring for patients on the internal medicine services in our academic hospital. Participants included medicine nursing staff in acute care and intermediate care units, medicine and combined medicine‐pediatrics housestaff physicians, and general internal medicine faculty physicians who supervised the housestaff physicians.

Study Setting

The study was conducted at a 378‐bed, university‐based, acute care teaching hospital in central Pennsylvania. There are a total of 64 internal medicine beds located in2 units, a general medicine unit (44 beds, staffed by 60 nurses, nurse‐to‐patient ratio 1:4) and an intermediate care unit (20 beds, staffed by 41 nurses, nurse‐to‐patient ratio 1:3). Both units are staffed by the general internal medicine physician teams. The academic medicine residency program consists of 69 internal medicine housestaff and 14 combined internal medicine‐pediatrics housestaff. Five teams, organized into 3 academic teaching teams and 2 nonteaching teams, provide care for all patients admitted to the medicine units. Teaching teams consist of 1 junior (postgraduate year [PGY]2) or senior (PGY34) housestaff member, 2 interns (PGY1), 2 medical students, and 1 attending physician.

There are several main features of BIRs in our medicine units. The rounding team of physicians alerts the assigned nurse about the start of rounds. In our main medicine unit, each doorway is equipped with a light that allows the physician team to indicate the start of the BIRs encounter. Case presentations by trainees occur either in the hallway or bedside, at the discretion of the attending physician. During bedside encounters, nurses typically contribute to the discussion about clinical status, decision making, patient concerns, and disposition. Patients are encouraged to contribute to the discussion and are provided the opportunity to ask questions.

For the purposes of this study, we specifically defined BIRs as: encounters that include the team of providers, at least 2 physicians plus a nurse or other care provider, discussing the case at the patient's bedside. In our prior work performed during the same time period as this study, we used the same definition to examine the incidence of and time spent in BIRs in both of our medicine units.[19] We found that 63% to 81% of patients in both units received BIRs. As a result, we assumed all nursing staff, attending physicians, and housestaff physicians had experienced this process, and their responses to this survey were contextualized in these experiences.

Survey Instrument

We developed a survey instrument specifically for this study. We derived items primarily from our prior qualitative work on physician‐based team bedside rounds and a literature review.[20, 21, 22, 23, 24, 25] For the benefits to BIRs, we developed items related to 5 domains, including factors related to the patient, education, communication/coordination/teamwork, efficiency and process, and outcomes.[20, 26] For the barriers to BIRs, we developed items related to 4 domains, including factors related to the patient, time, systems issues, and providers (nurses, attending physicians, and housestaff physicians).[22, 24, 25] We included our definition of BIRs into the survey instructions. We pilot tested the survey with 3 medicine faculty and 3 nursing staff and, based on our pilot, modified several questions to improve clarity. Primary demographic items in the survey included identification of provider role (nurses, attending physicians, or housestaff physicians) and years in the current role. Respondent preference for the benefits and barriers were investigated on a 7‐point scale (1=lowest response and 7=high response possible). Descriptive text was provided at the extremes (choice 1 and 7), but intermediary values (26) did not have descriptive cues.[27] As an incentive, the end of the survey provided respondents with an option for submitting their name to be entered into a raffle to win 1 of 50, $5 gift certificates to a coffee shop.

Prior to the end of the academic year in June 2013, we sent a survey link via e‐mail to all medicine nursing staff, housestaff physicians, and attending physicians. The email described the study and explained the voluntary nature of the work, and that informed consent would be implied by survey completion. Following the initial e‐mail, 3 additional weekly e‐mail reminders were sent by the lead investigator. The study was approved by the institutional review board at the Pennsylvania State College of Medicine.

Data Analysis

Descriptive statistics were used to examine the characteristics of the 3 respondent groups and combined totals for each survey item. The nonparametric Wilcoxon rank sum test was used to compare the average values between groups (nursing staff vs all physicians, attending physicians vs housestaff physicians) for both sets of survey variables (benefits and barriers). The nonparametric correlation statistical test Spearman rank was used to assess the degree of correlation between respondent groups for both survey variables. The data were analyzed using SAS 9.3 (SAS Institute, Cary, NC) and Stata/IC‐8 (StataCorp, College Station, Texas).

RESULTS

Of the 171 surveys sent, 149 participants completed surveys (response rate 87%). Responses were received from 53/58 nursing staff (91% response), 21/28 attending physicians (75% response), and 75/85 housestaff physicians (88% response). Table 1 describes the participant response demographics.

Demographics of Nursing Staff, Attending Physicians, and Housestaff Participants (N=149)
VariableValue
  • NOTE: Abbreviations: SD, standard deviation.

  • Senior resident includes third‐ and fourth‐year medicine or medicine/pediatrics residents.

Nursing staff, n=58, n (%)53 (36)
Intermediate care unit, n (%)14 (26)
General medicine ward, n (%)39 (74)
All day shifts, n (%)25 (47)
Mix of day and night shifts, n (%)32 (60)
Years of experience, mean (SD)7.4 (9)
Attending physicians, n=28, n (%)21 (14)
Years since residency graduation, mean (SD)10.5 (8)
No. of weeks in past year serving as teaching attending, mean (SD)9.1(8)
Housestaff physicians (n=85), n (%)75 (50)
Intern, n (%)28 (37)
Junior resident, n (%)25 (33)
Senior resident, n (%)a22 (29)

Benefits of BIRs

Respondents' perceptions of the benefits of BIRs are shown by mean value (between 1 and 7) for the total respondent pool and by each participant group (Table 2). Six of the 7 highest‐ranked benefits were related to communication, coordination, and teamwork, including improves communication between nurses and physicians, improves awareness of clinical issues that need to be addressed, and improves team‐building between nurses and physicians. Lowest‐ranked benefits were related to efficiency, process, and outcomes, including decreases patients' hospital length‐of‐stay, improves timeliness of consultations, and reduces ordering of unnecessary tests and treatments. Comparing mean values among the 3 groups, all 18 items showed statistical differences in response rates (all P values <0.05). Nursing staff reported more favorable ratings than both attending physicians and housestaff physicians for each of the 18 items, whereas attending physicians reported more favorable ratings than housestaff physicians in 16/18 items. The rank order among provider groups showed a high degree of correlation (r=0.92, P<0.001).

Comparisons of Ratings of the Benefits to Bedside Interprofessional Rounds as Reported by Nursing Staff, Attending Physicians, and Housestaff Physicians (N=149).
Survey ItemaItem DomainTotal, N=149, Mean (SD)Nurses, N=53, Mean (SD)Attending Physicians, N=21, Mean (SD)House staff Physicians, N=75, Mean (SD)b
  • NOTE: Abbreviations: CCT, communication/coordination/teamwork; E, education; EP, efficiency and process‐related factors; O, outcomes; P, patient‐related factors; SD, standard deviation.

  • Answer choices included 7 options from 1 (not at all) to 7 (definitely).

  • There were no statistical differences between intern physicians and junior and senior housestaff physicians.

  • P<0.01 vs all physicians from Wilcoxon rank sum test.

  • P<0.01 vs housestaff physicians from Wilcoxon rank sum test.

Improves communication between nurses and physicians.CCT6.26 (1.11)6.74 (0.59)c6.52 (1.03)d5.85 (1.26)
Improves awareness of clinical issues needing to be addressed.CCT6.05 (1.12)6.57 (0.64)c5.95 (1.07)5.71 (1.26)
Improves team‐building between nurses and physicians.CCT6.03 (1.32)6.72 (0.60)c6.14 (1.11)5.52 (1.51)
Improves coordination of the patient's care.CCT5.98 (1.34)6.60 (0.72)c6.00 (1.18)5.53 (1.55)
Improves nursing contributions to a patient's care plan.CCT5.91 (1.25)6.47 (0.77)c6.14 (0.85)5.44 (1.43)
Improves quality of care delivered in our unit.O5.72 (1.42)6.34 (0.83)c5.81 (1.33)5.25 (1.61)
Improves appreciation of the roles/contributions of other providers.CCT5.69 (1.49)6.36 (0.86)c5.90 (1.04)5.16 (1.73)
Promotes shared decision making between patients and providers.P5.62 (1.51)6.43 (0.77)c5.57 (1.40)5.05 (1.68)
Improves patients' satisfaction with their hospitalization.P, O5.53 (1.40)6.15 (0.95)c5.38 (1.12)5.13 (1.58)
Provides more respect/dignity to patients.P5.31 (1.55)6.23 (0.89)c5.10 (1.18)4.72 (1.71)
Decreases number of pages/phone calls between nurses and physicians.EP5.28 (1.82)6.28 (0.93)c5.24 (1.30)4.57 (2.09)
Improves educational opportunities for housestaff/students.E5.07 (1.77)6.08 (0.98)c4.81 (1.60)4.43 (1.93)
Improves the efficiency of your work.EP5.01 (1.77)6.04 (1.13)c4.90 (1.30)4.31 (1.92)
Improves adherence to evidence‐based guidelines or interventions.EP4.89 (1.79)6.06 (0.91)c4.00 (1.18)4.31 (1.97)
Improves the accuracy of your sign‐outs (or reports) to the next shift.EP4.80 (1.99)6.30 (0.93)c4.05 (1.66)3.95 (2.01)
Reduces ordering of unnecessary tests and treatments.O4.51 (1.86)5.77 (1.15)c3.86 (1.11)3.8 (1.97)
Improves the timeliness of consultations.EP4.28 (1.99)5.66 (1.22)c3.24 (1.48)3.59 (2.02)
Decreases patients' hospital length of stay.O4.15 (1.68)5.04 (1.24)c3.95 (1.16)3.57 (1.81)

Barriers to BIRs

Respondents' perceptions of barriers to BIRs are shown by mean value (between 1 and 7) for the total respondent pool and by each participant group (Table 3). The 6 highest‐ranked barriers were related to time, including nursing staff have limited time, the time required for bedside nurse‐physician encounters, and coordinating the start time of encounters with arrival of both physicians and nursing. The lowest‐ranked barriers were related to provider‐ and patient‐related factors, including patient lack of comfort with bedside nurse‐physician encounters, attending physicians/housestaff lack bedside skills, and attending physicians lack comfort with bedside nurse‐physician encounters. Comparing mean values between groups, 10 of 21 items showed statistical differences (P<0.05). The rank order among groups showed moderate correlation (nurses‐attending physicians r=0.62, nurses‐housestaff physicians r=0.76, attending physicians‐housestaff physicians r=0.82). A qualitative inspection of disparities among respondent groups highlighted that nursing staff were more likely to rank bedside rounds are not part of the unit's culture lower than physician groups.

Comparisons of Perceived Barriers to Bedside Interprofessional Rounds as Reported by Nursing Staff, Attending Physicians, and Housestaff Physicians (N=149)
Survey ItemaItem DomainTotal, N=149, Mean (SD)Nurses, n=53, Mean (SD)Attending Physicians, n=21, Mean (SD)Housestaff Physicians, n=75,b Mean (SD)
  • NOTE: Abbreviations: P, patient‐related factors; PR, provider‐related factors; S, systems issues; T, time.

  • Answer choices included 7 options from 1 (not at all) to 7 (definitely).

  • There were no statistical differences between intern physicians and junior and senior housestaff physicians.

  • P<0.01 vs all physicians from Wilcoxon rank sum test.

  • P<0.01 vs housestaff physicians from Wilcoxon rank sum test.

Nursing staff have limited time.T4.89 (1.34)4.96 (1.27)4.86 (1.65)4.85 (1.30)
Coordinating start time of encounters with arrival of physicians and nursing.T4.80 (1.50)4.58 (1.43)5.24 (1.45)4.84 (1.55)
Housestaff have limited time.T4.68 (1.47)4.56 (1.26)4.24 (1.81)4.89 (1.48)
Attending physicians have limited time.T4.50 (1.49)4.81 (1.34)4.33 (1.65)4.34 (1.53)
Other acutely sick patients in unit.T4.39 (1.42)4.79 (1.30)c4.52 (1.21)4.08 (1.49)
Time required for bedside nurse‐physician encounters.T4.32 (1.55)4.85 (1.38)c3.62 (1.80)4.15 (1.49)
Lack of use of the pink‐rounding light to alert nursing staff.S3.77 (1.75)4.71 (1.70)c3.48 (1.86)3.19 (1.46)
Patient not available (eg, off to test, getting bathed)S3.74 (1.40)3.98 (1.28)4.52 (1.36)d3.35 (1.37)
Large team size.S3.64 (1.74)3.12 (1.58)c3.95 (1.83)3.92 (1.77)
Patients in dispersed locations (eg, other units or in different hallways).S3.64 (1.77)2.77 (1.55)c4.52 (1.83)4.00 (1.66)
Bedside nurse‐physician rounds are not part of the unit's culture.S3.35 (1.94)2.25 (1.47)c4.76 (1.92)3.72 (1.85)
Limitations in physical facilities (eg, rooms too small, limited chairs).S3.25 (1.71)2.71 (1.72)3.33 (1.71)3.59 (1.62)
Insufficient nurse engagement during bedside nurse‐physician encounters.PR3.24 (1.63)2.71 (1.47)c3.67 (1.68)3.49 (1.65)
Patient on contact or respiratory isolation.S3.20 (1.82)2.42 (1.67)c3.43 (1.63)3.69 (1.80)
Language barrier between providers and patients.P2.69 (1.37)2.77 (1.39)2.57 (1.08)2.68 (1.43)
Privacy/sensitive patient issues.P2.65 (1.45)2.27 (1.24)2.57 (1.33)2.93 (1.56)
Housestaff lack comfort with bedside nurse‐physician encounters.PR2.55 (1.49)2.48 (1.15)2.67 (1.68)2.57 (1.65)
Nurses lack comfort with bedside nurse‐physician encounters.PR2.45 (1.45)2.35 (1.27)2.48 (1.66)2.51 (1.53)
Attending physicians lack comfort with bedside nurse‐physician encounters.PR2.35 (1.38)2.33 (1.25)2.33 (1.62)2.36 (1.41)
Attending physician/housestaff lack bedside skills (eg, history, exam).PR2.34 (1.34)2.19 (1.19)2.85 (1.69)2.30 (1.32)
Patient lack of comfort with bedside nurse‐physician encounters.P2.33 (1.48)2.23 (1.37)1.95 (1.32)2.5 (1.59)

DISCUSSION

In this study, we sought to compare perceptions of nurses and physicians on the benefits and barriers to BIRs. Nursing staff ranked each benefit higher than physicians, though rank orders of specific benefits were highly correlated. Highest‐ranked benefits related to coordination and communication more than quality or process benefits. Across groups, the highest‐ranked barriers to BIRs were related to time, whereas the lowest‐ranked factors were related to provider and patient discomfort. These results highlight important similarities and differences in perceptions between front‐line providers.

The highest‐ranked benefits were related to improved interprofessional communication and coordination. Combining interprofessional team members during care delivery allows for integrated understanding of daily care plans and clinical issues, and fosters collaboration and a team‐based atmosphere.[1, 20, 26] The lowest‐ranked benefits were related to more tangible measures, including length of stay, timely consultations, and judicious laboratory ordering. This finding contrasts with the limited literature demonstrating increased efficiency in general medicine units practicing IPCC.[16] These rankings may reflect a poor understanding or self‐assessment of outcome measures by healthcare providers, representing a potential focus for educational initiatives. Future investigations using objective assessment methods of outcomes and collaboration will provide a more accurate understanding of these findings.

The highest‐ranked barriers were related to time and systems issues. Several studies of physician‐based bedside rounds have identified systems‐ and time‐related issues as primary limiting barriers.[22, 24] In units without colocalization of patients and providers, finding receptive times for BIRs can be difficult. Although time‐related issues could be addressed by decreasing patient‐provider ratios, these changes require substantial investment in resources. A reasonable degree of improvement in efficiency and coordination is expected following acclimation to BIRs or by addressing modifiable systems factors to increase this activity. Less costly interventions, such as tailoring provider schedules, prescheduling patient rounding times, and geographic colocalization of patients and providers may be more feasible. However, the clinical microsystems within which medicine patients are cared for are often chaotic and disorganized at the infrastructural and cultural levels, which may be less influenced by surface‐level interventions. Such interventions may be ward specific and require customization to individual team needs.

The lowest‐ranked barriers to BIRs were related to provider‐ and patient‐related factors, including comfort level of patients and providers. Prior work on bedside rounds has identified physicians who are apprehensive about performing bedside rounds, but those who experience this activity are more likely to be comfortable with it.[12, 28] Our results from a culture where BIRs occur on nearly two‐thirds of patients suggest provider discomfort is not a predominant barrier.[22, 29] Additionally, educators have raised concerns about patient discomfort with bedside rounds, but nearly all studies evaluating patients' perspectives reveal patient preference for bedside case presentations over activities occurring in alternative locations.[30, 31, 32] Little work has investigated patient preference for BIRs as per our definition; our participants do not believe patients are discomforted by BIRs, building upon evidence in the literature for patient preferences regarding bedside activities.

Nursing staff perceptions of the benefits and culture related to BIRs were more positive than physicians. We hypothesize several reasons for this disparity. First, nursing staff may have more experience with observing and understanding the positive impact of BIRs and therefore are more likely to understand the positive ramifications. Alternatively, nursing staff may be satisfied with active integration into traditional physician‐centric decisions. Additionally, the professional culture and educational foundation of the nursing culture is based upon a patient‐centered approach and therefore may be more aligned with the goals of BIRs. Last, physicians may have competing priorities, favoring productivity and didactic learning rather than interprofessional collaboration. Further investigation is required to understand differences between nurses and physicians, in addition to other providers integral to BIRs (eg, care coordinators, pharmacists). Regardless, during the implementation of interprofessional collaborative care models, our findings suggest initial challenges, and the focus of educational initiatives may necessitate acclimating physician groups to benefits identified by front‐line nursing staff.

There are several limitations to our study. We investigated the perceptions of medicine nurses and physicians in 1 teaching hospital, limiting generalizability to other specialties, other vital professional groups, and nonteaching hospitals. Additionally, BIRs has been a focus of our hospital for several years. Therefore, perceived barriers may differ in BIRs‐nave hospitals. Second, although pilot‐tested for content, the construct validity of the instrument was not rigorously assessed, and the instrument was not designed to measure benefits and barriers not explicitly identified during pilot testing. Last, although surveys were anonymous, the possibility of social desirability bias exists, thereby limiting accuracy.

For over a century, physician‐led rounds have been the preferred modality for point‐of‐care decision making.[10, 15, 32, 33] BIRs address our growing understanding of patient‐centered care. Future efforts should address the quality of collaboration and current hospital and unit structures hindering patient‐centered IPCC and patient outcomes.

Acknowledgements

The authors thank the medicine nursing staff and physicians for their dedication to patient‐centered care and willingness to participate in this study.

Disclosures: The Department of Medicine at the Penn State Hershey Medical Center provided funding for this project. There are no conflicts of interest to report.

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References
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Interprofessional collaborative care (IPCC) involves members from different professions working together to enhance communication, coordination, and healthcare quality.[1, 2, 3] Because several current healthcare policy initiatives include financial incentives for increased quality of care, there has been resultant interest in the implementation of IPCC in healthcare systems.[4, 5] Unfortunately, many hospitals have found IPCC difficult to achieve. Hospital‐based medicine units are complex, time‐constrained environments requiring a high degree of collaboration and mutual decision‐making between nurses, physicians, therapists, pharmacists, care coordinators, and patients. In addition, despite recommendations for interprofessional collaborative care, the implementation and assessment of IPCC within this environment has not been well studied.[6, 7]

On academic internal medicine services, the majority of care decisions occur during rounds. Although rounds provide a common structure, the participants, length, location, and agenda of rounds tend to vary by institution and individual physician preference.[8, 9, 10, 11] Traditionally, ward rounds occur mostly in hallways and conference rooms rather than the patient's bedside.[12] Additionally, during rounds, nurse‐physician collaboration occurs infrequently, estimated at <10% of rounding time.[13] Recently, an increased focus on quality, safety, and collaboration has inspired the investigation and implementation of new methods to increase interprofessional collaboration during rounds, but many of these interventions occurred away from the patient's bedside.[14, 15] One trial of bedside interprofessional rounds (BIRs) by Curley et al. suggested improvements in patient‐level outcomes (cost and length of stay) versus traditional physician‐based rounds.[16] Although interprofessional nurse‐physician rounds at patients' bedsides may represent an ideal process, limited work has investigated this activity.[17]

A prerequisite for successful and sustained integration of BIRs is a shared conceptualization among physicians and nurses regarding the process. Such a shared conceptualization would include perceptions of benefits and barriers to implementation.[18] Currently, such perceptions have not been measured. In this study, we sought to evaluate perceptions of front‐line care providers on inpatient units, specifically nursing staff, attending physicians, and housestaff physicians, regarding the benefits and barriers to BIRs.

METHODS

Study Design and Participants

In June 2013, we performed a cross‐sectional assessment of front‐line providers caring for patients on the internal medicine services in our academic hospital. Participants included medicine nursing staff in acute care and intermediate care units, medicine and combined medicine‐pediatrics housestaff physicians, and general internal medicine faculty physicians who supervised the housestaff physicians.

Study Setting

The study was conducted at a 378‐bed, university‐based, acute care teaching hospital in central Pennsylvania. There are a total of 64 internal medicine beds located in2 units, a general medicine unit (44 beds, staffed by 60 nurses, nurse‐to‐patient ratio 1:4) and an intermediate care unit (20 beds, staffed by 41 nurses, nurse‐to‐patient ratio 1:3). Both units are staffed by the general internal medicine physician teams. The academic medicine residency program consists of 69 internal medicine housestaff and 14 combined internal medicine‐pediatrics housestaff. Five teams, organized into 3 academic teaching teams and 2 nonteaching teams, provide care for all patients admitted to the medicine units. Teaching teams consist of 1 junior (postgraduate year [PGY]2) or senior (PGY34) housestaff member, 2 interns (PGY1), 2 medical students, and 1 attending physician.

There are several main features of BIRs in our medicine units. The rounding team of physicians alerts the assigned nurse about the start of rounds. In our main medicine unit, each doorway is equipped with a light that allows the physician team to indicate the start of the BIRs encounter. Case presentations by trainees occur either in the hallway or bedside, at the discretion of the attending physician. During bedside encounters, nurses typically contribute to the discussion about clinical status, decision making, patient concerns, and disposition. Patients are encouraged to contribute to the discussion and are provided the opportunity to ask questions.

For the purposes of this study, we specifically defined BIRs as: encounters that include the team of providers, at least 2 physicians plus a nurse or other care provider, discussing the case at the patient's bedside. In our prior work performed during the same time period as this study, we used the same definition to examine the incidence of and time spent in BIRs in both of our medicine units.[19] We found that 63% to 81% of patients in both units received BIRs. As a result, we assumed all nursing staff, attending physicians, and housestaff physicians had experienced this process, and their responses to this survey were contextualized in these experiences.

Survey Instrument

We developed a survey instrument specifically for this study. We derived items primarily from our prior qualitative work on physician‐based team bedside rounds and a literature review.[20, 21, 22, 23, 24, 25] For the benefits to BIRs, we developed items related to 5 domains, including factors related to the patient, education, communication/coordination/teamwork, efficiency and process, and outcomes.[20, 26] For the barriers to BIRs, we developed items related to 4 domains, including factors related to the patient, time, systems issues, and providers (nurses, attending physicians, and housestaff physicians).[22, 24, 25] We included our definition of BIRs into the survey instructions. We pilot tested the survey with 3 medicine faculty and 3 nursing staff and, based on our pilot, modified several questions to improve clarity. Primary demographic items in the survey included identification of provider role (nurses, attending physicians, or housestaff physicians) and years in the current role. Respondent preference for the benefits and barriers were investigated on a 7‐point scale (1=lowest response and 7=high response possible). Descriptive text was provided at the extremes (choice 1 and 7), but intermediary values (26) did not have descriptive cues.[27] As an incentive, the end of the survey provided respondents with an option for submitting their name to be entered into a raffle to win 1 of 50, $5 gift certificates to a coffee shop.

Prior to the end of the academic year in June 2013, we sent a survey link via e‐mail to all medicine nursing staff, housestaff physicians, and attending physicians. The email described the study and explained the voluntary nature of the work, and that informed consent would be implied by survey completion. Following the initial e‐mail, 3 additional weekly e‐mail reminders were sent by the lead investigator. The study was approved by the institutional review board at the Pennsylvania State College of Medicine.

Data Analysis

Descriptive statistics were used to examine the characteristics of the 3 respondent groups and combined totals for each survey item. The nonparametric Wilcoxon rank sum test was used to compare the average values between groups (nursing staff vs all physicians, attending physicians vs housestaff physicians) for both sets of survey variables (benefits and barriers). The nonparametric correlation statistical test Spearman rank was used to assess the degree of correlation between respondent groups for both survey variables. The data were analyzed using SAS 9.3 (SAS Institute, Cary, NC) and Stata/IC‐8 (StataCorp, College Station, Texas).

RESULTS

Of the 171 surveys sent, 149 participants completed surveys (response rate 87%). Responses were received from 53/58 nursing staff (91% response), 21/28 attending physicians (75% response), and 75/85 housestaff physicians (88% response). Table 1 describes the participant response demographics.

Demographics of Nursing Staff, Attending Physicians, and Housestaff Participants (N=149)
VariableValue
  • NOTE: Abbreviations: SD, standard deviation.

  • Senior resident includes third‐ and fourth‐year medicine or medicine/pediatrics residents.

Nursing staff, n=58, n (%)53 (36)
Intermediate care unit, n (%)14 (26)
General medicine ward, n (%)39 (74)
All day shifts, n (%)25 (47)
Mix of day and night shifts, n (%)32 (60)
Years of experience, mean (SD)7.4 (9)
Attending physicians, n=28, n (%)21 (14)
Years since residency graduation, mean (SD)10.5 (8)
No. of weeks in past year serving as teaching attending, mean (SD)9.1(8)
Housestaff physicians (n=85), n (%)75 (50)
Intern, n (%)28 (37)
Junior resident, n (%)25 (33)
Senior resident, n (%)a22 (29)

Benefits of BIRs

Respondents' perceptions of the benefits of BIRs are shown by mean value (between 1 and 7) for the total respondent pool and by each participant group (Table 2). Six of the 7 highest‐ranked benefits were related to communication, coordination, and teamwork, including improves communication between nurses and physicians, improves awareness of clinical issues that need to be addressed, and improves team‐building between nurses and physicians. Lowest‐ranked benefits were related to efficiency, process, and outcomes, including decreases patients' hospital length‐of‐stay, improves timeliness of consultations, and reduces ordering of unnecessary tests and treatments. Comparing mean values among the 3 groups, all 18 items showed statistical differences in response rates (all P values <0.05). Nursing staff reported more favorable ratings than both attending physicians and housestaff physicians for each of the 18 items, whereas attending physicians reported more favorable ratings than housestaff physicians in 16/18 items. The rank order among provider groups showed a high degree of correlation (r=0.92, P<0.001).

Comparisons of Ratings of the Benefits to Bedside Interprofessional Rounds as Reported by Nursing Staff, Attending Physicians, and Housestaff Physicians (N=149).
Survey ItemaItem DomainTotal, N=149, Mean (SD)Nurses, N=53, Mean (SD)Attending Physicians, N=21, Mean (SD)House staff Physicians, N=75, Mean (SD)b
  • NOTE: Abbreviations: CCT, communication/coordination/teamwork; E, education; EP, efficiency and process‐related factors; O, outcomes; P, patient‐related factors; SD, standard deviation.

  • Answer choices included 7 options from 1 (not at all) to 7 (definitely).

  • There were no statistical differences between intern physicians and junior and senior housestaff physicians.

  • P<0.01 vs all physicians from Wilcoxon rank sum test.

  • P<0.01 vs housestaff physicians from Wilcoxon rank sum test.

Improves communication between nurses and physicians.CCT6.26 (1.11)6.74 (0.59)c6.52 (1.03)d5.85 (1.26)
Improves awareness of clinical issues needing to be addressed.CCT6.05 (1.12)6.57 (0.64)c5.95 (1.07)5.71 (1.26)
Improves team‐building between nurses and physicians.CCT6.03 (1.32)6.72 (0.60)c6.14 (1.11)5.52 (1.51)
Improves coordination of the patient's care.CCT5.98 (1.34)6.60 (0.72)c6.00 (1.18)5.53 (1.55)
Improves nursing contributions to a patient's care plan.CCT5.91 (1.25)6.47 (0.77)c6.14 (0.85)5.44 (1.43)
Improves quality of care delivered in our unit.O5.72 (1.42)6.34 (0.83)c5.81 (1.33)5.25 (1.61)
Improves appreciation of the roles/contributions of other providers.CCT5.69 (1.49)6.36 (0.86)c5.90 (1.04)5.16 (1.73)
Promotes shared decision making between patients and providers.P5.62 (1.51)6.43 (0.77)c5.57 (1.40)5.05 (1.68)
Improves patients' satisfaction with their hospitalization.P, O5.53 (1.40)6.15 (0.95)c5.38 (1.12)5.13 (1.58)
Provides more respect/dignity to patients.P5.31 (1.55)6.23 (0.89)c5.10 (1.18)4.72 (1.71)
Decreases number of pages/phone calls between nurses and physicians.EP5.28 (1.82)6.28 (0.93)c5.24 (1.30)4.57 (2.09)
Improves educational opportunities for housestaff/students.E5.07 (1.77)6.08 (0.98)c4.81 (1.60)4.43 (1.93)
Improves the efficiency of your work.EP5.01 (1.77)6.04 (1.13)c4.90 (1.30)4.31 (1.92)
Improves adherence to evidence‐based guidelines or interventions.EP4.89 (1.79)6.06 (0.91)c4.00 (1.18)4.31 (1.97)
Improves the accuracy of your sign‐outs (or reports) to the next shift.EP4.80 (1.99)6.30 (0.93)c4.05 (1.66)3.95 (2.01)
Reduces ordering of unnecessary tests and treatments.O4.51 (1.86)5.77 (1.15)c3.86 (1.11)3.8 (1.97)
Improves the timeliness of consultations.EP4.28 (1.99)5.66 (1.22)c3.24 (1.48)3.59 (2.02)
Decreases patients' hospital length of stay.O4.15 (1.68)5.04 (1.24)c3.95 (1.16)3.57 (1.81)

Barriers to BIRs

Respondents' perceptions of barriers to BIRs are shown by mean value (between 1 and 7) for the total respondent pool and by each participant group (Table 3). The 6 highest‐ranked barriers were related to time, including nursing staff have limited time, the time required for bedside nurse‐physician encounters, and coordinating the start time of encounters with arrival of both physicians and nursing. The lowest‐ranked barriers were related to provider‐ and patient‐related factors, including patient lack of comfort with bedside nurse‐physician encounters, attending physicians/housestaff lack bedside skills, and attending physicians lack comfort with bedside nurse‐physician encounters. Comparing mean values between groups, 10 of 21 items showed statistical differences (P<0.05). The rank order among groups showed moderate correlation (nurses‐attending physicians r=0.62, nurses‐housestaff physicians r=0.76, attending physicians‐housestaff physicians r=0.82). A qualitative inspection of disparities among respondent groups highlighted that nursing staff were more likely to rank bedside rounds are not part of the unit's culture lower than physician groups.

Comparisons of Perceived Barriers to Bedside Interprofessional Rounds as Reported by Nursing Staff, Attending Physicians, and Housestaff Physicians (N=149)
Survey ItemaItem DomainTotal, N=149, Mean (SD)Nurses, n=53, Mean (SD)Attending Physicians, n=21, Mean (SD)Housestaff Physicians, n=75,b Mean (SD)
  • NOTE: Abbreviations: P, patient‐related factors; PR, provider‐related factors; S, systems issues; T, time.

  • Answer choices included 7 options from 1 (not at all) to 7 (definitely).

  • There were no statistical differences between intern physicians and junior and senior housestaff physicians.

  • P<0.01 vs all physicians from Wilcoxon rank sum test.

  • P<0.01 vs housestaff physicians from Wilcoxon rank sum test.

Nursing staff have limited time.T4.89 (1.34)4.96 (1.27)4.86 (1.65)4.85 (1.30)
Coordinating start time of encounters with arrival of physicians and nursing.T4.80 (1.50)4.58 (1.43)5.24 (1.45)4.84 (1.55)
Housestaff have limited time.T4.68 (1.47)4.56 (1.26)4.24 (1.81)4.89 (1.48)
Attending physicians have limited time.T4.50 (1.49)4.81 (1.34)4.33 (1.65)4.34 (1.53)
Other acutely sick patients in unit.T4.39 (1.42)4.79 (1.30)c4.52 (1.21)4.08 (1.49)
Time required for bedside nurse‐physician encounters.T4.32 (1.55)4.85 (1.38)c3.62 (1.80)4.15 (1.49)
Lack of use of the pink‐rounding light to alert nursing staff.S3.77 (1.75)4.71 (1.70)c3.48 (1.86)3.19 (1.46)
Patient not available (eg, off to test, getting bathed)S3.74 (1.40)3.98 (1.28)4.52 (1.36)d3.35 (1.37)
Large team size.S3.64 (1.74)3.12 (1.58)c3.95 (1.83)3.92 (1.77)
Patients in dispersed locations (eg, other units or in different hallways).S3.64 (1.77)2.77 (1.55)c4.52 (1.83)4.00 (1.66)
Bedside nurse‐physician rounds are not part of the unit's culture.S3.35 (1.94)2.25 (1.47)c4.76 (1.92)3.72 (1.85)
Limitations in physical facilities (eg, rooms too small, limited chairs).S3.25 (1.71)2.71 (1.72)3.33 (1.71)3.59 (1.62)
Insufficient nurse engagement during bedside nurse‐physician encounters.PR3.24 (1.63)2.71 (1.47)c3.67 (1.68)3.49 (1.65)
Patient on contact or respiratory isolation.S3.20 (1.82)2.42 (1.67)c3.43 (1.63)3.69 (1.80)
Language barrier between providers and patients.P2.69 (1.37)2.77 (1.39)2.57 (1.08)2.68 (1.43)
Privacy/sensitive patient issues.P2.65 (1.45)2.27 (1.24)2.57 (1.33)2.93 (1.56)
Housestaff lack comfort with bedside nurse‐physician encounters.PR2.55 (1.49)2.48 (1.15)2.67 (1.68)2.57 (1.65)
Nurses lack comfort with bedside nurse‐physician encounters.PR2.45 (1.45)2.35 (1.27)2.48 (1.66)2.51 (1.53)
Attending physicians lack comfort with bedside nurse‐physician encounters.PR2.35 (1.38)2.33 (1.25)2.33 (1.62)2.36 (1.41)
Attending physician/housestaff lack bedside skills (eg, history, exam).PR2.34 (1.34)2.19 (1.19)2.85 (1.69)2.30 (1.32)
Patient lack of comfort with bedside nurse‐physician encounters.P2.33 (1.48)2.23 (1.37)1.95 (1.32)2.5 (1.59)

DISCUSSION

In this study, we sought to compare perceptions of nurses and physicians on the benefits and barriers to BIRs. Nursing staff ranked each benefit higher than physicians, though rank orders of specific benefits were highly correlated. Highest‐ranked benefits related to coordination and communication more than quality or process benefits. Across groups, the highest‐ranked barriers to BIRs were related to time, whereas the lowest‐ranked factors were related to provider and patient discomfort. These results highlight important similarities and differences in perceptions between front‐line providers.

The highest‐ranked benefits were related to improved interprofessional communication and coordination. Combining interprofessional team members during care delivery allows for integrated understanding of daily care plans and clinical issues, and fosters collaboration and a team‐based atmosphere.[1, 20, 26] The lowest‐ranked benefits were related to more tangible measures, including length of stay, timely consultations, and judicious laboratory ordering. This finding contrasts with the limited literature demonstrating increased efficiency in general medicine units practicing IPCC.[16] These rankings may reflect a poor understanding or self‐assessment of outcome measures by healthcare providers, representing a potential focus for educational initiatives. Future investigations using objective assessment methods of outcomes and collaboration will provide a more accurate understanding of these findings.

The highest‐ranked barriers were related to time and systems issues. Several studies of physician‐based bedside rounds have identified systems‐ and time‐related issues as primary limiting barriers.[22, 24] In units without colocalization of patients and providers, finding receptive times for BIRs can be difficult. Although time‐related issues could be addressed by decreasing patient‐provider ratios, these changes require substantial investment in resources. A reasonable degree of improvement in efficiency and coordination is expected following acclimation to BIRs or by addressing modifiable systems factors to increase this activity. Less costly interventions, such as tailoring provider schedules, prescheduling patient rounding times, and geographic colocalization of patients and providers may be more feasible. However, the clinical microsystems within which medicine patients are cared for are often chaotic and disorganized at the infrastructural and cultural levels, which may be less influenced by surface‐level interventions. Such interventions may be ward specific and require customization to individual team needs.

The lowest‐ranked barriers to BIRs were related to provider‐ and patient‐related factors, including comfort level of patients and providers. Prior work on bedside rounds has identified physicians who are apprehensive about performing bedside rounds, but those who experience this activity are more likely to be comfortable with it.[12, 28] Our results from a culture where BIRs occur on nearly two‐thirds of patients suggest provider discomfort is not a predominant barrier.[22, 29] Additionally, educators have raised concerns about patient discomfort with bedside rounds, but nearly all studies evaluating patients' perspectives reveal patient preference for bedside case presentations over activities occurring in alternative locations.[30, 31, 32] Little work has investigated patient preference for BIRs as per our definition; our participants do not believe patients are discomforted by BIRs, building upon evidence in the literature for patient preferences regarding bedside activities.

Nursing staff perceptions of the benefits and culture related to BIRs were more positive than physicians. We hypothesize several reasons for this disparity. First, nursing staff may have more experience with observing and understanding the positive impact of BIRs and therefore are more likely to understand the positive ramifications. Alternatively, nursing staff may be satisfied with active integration into traditional physician‐centric decisions. Additionally, the professional culture and educational foundation of the nursing culture is based upon a patient‐centered approach and therefore may be more aligned with the goals of BIRs. Last, physicians may have competing priorities, favoring productivity and didactic learning rather than interprofessional collaboration. Further investigation is required to understand differences between nurses and physicians, in addition to other providers integral to BIRs (eg, care coordinators, pharmacists). Regardless, during the implementation of interprofessional collaborative care models, our findings suggest initial challenges, and the focus of educational initiatives may necessitate acclimating physician groups to benefits identified by front‐line nursing staff.

There are several limitations to our study. We investigated the perceptions of medicine nurses and physicians in 1 teaching hospital, limiting generalizability to other specialties, other vital professional groups, and nonteaching hospitals. Additionally, BIRs has been a focus of our hospital for several years. Therefore, perceived barriers may differ in BIRs‐nave hospitals. Second, although pilot‐tested for content, the construct validity of the instrument was not rigorously assessed, and the instrument was not designed to measure benefits and barriers not explicitly identified during pilot testing. Last, although surveys were anonymous, the possibility of social desirability bias exists, thereby limiting accuracy.

For over a century, physician‐led rounds have been the preferred modality for point‐of‐care decision making.[10, 15, 32, 33] BIRs address our growing understanding of patient‐centered care. Future efforts should address the quality of collaboration and current hospital and unit structures hindering patient‐centered IPCC and patient outcomes.

Acknowledgements

The authors thank the medicine nursing staff and physicians for their dedication to patient‐centered care and willingness to participate in this study.

Disclosures: The Department of Medicine at the Penn State Hershey Medical Center provided funding for this project. There are no conflicts of interest to report.

Interprofessional collaborative care (IPCC) involves members from different professions working together to enhance communication, coordination, and healthcare quality.[1, 2, 3] Because several current healthcare policy initiatives include financial incentives for increased quality of care, there has been resultant interest in the implementation of IPCC in healthcare systems.[4, 5] Unfortunately, many hospitals have found IPCC difficult to achieve. Hospital‐based medicine units are complex, time‐constrained environments requiring a high degree of collaboration and mutual decision‐making between nurses, physicians, therapists, pharmacists, care coordinators, and patients. In addition, despite recommendations for interprofessional collaborative care, the implementation and assessment of IPCC within this environment has not been well studied.[6, 7]

On academic internal medicine services, the majority of care decisions occur during rounds. Although rounds provide a common structure, the participants, length, location, and agenda of rounds tend to vary by institution and individual physician preference.[8, 9, 10, 11] Traditionally, ward rounds occur mostly in hallways and conference rooms rather than the patient's bedside.[12] Additionally, during rounds, nurse‐physician collaboration occurs infrequently, estimated at <10% of rounding time.[13] Recently, an increased focus on quality, safety, and collaboration has inspired the investigation and implementation of new methods to increase interprofessional collaboration during rounds, but many of these interventions occurred away from the patient's bedside.[14, 15] One trial of bedside interprofessional rounds (BIRs) by Curley et al. suggested improvements in patient‐level outcomes (cost and length of stay) versus traditional physician‐based rounds.[16] Although interprofessional nurse‐physician rounds at patients' bedsides may represent an ideal process, limited work has investigated this activity.[17]

A prerequisite for successful and sustained integration of BIRs is a shared conceptualization among physicians and nurses regarding the process. Such a shared conceptualization would include perceptions of benefits and barriers to implementation.[18] Currently, such perceptions have not been measured. In this study, we sought to evaluate perceptions of front‐line care providers on inpatient units, specifically nursing staff, attending physicians, and housestaff physicians, regarding the benefits and barriers to BIRs.

METHODS

Study Design and Participants

In June 2013, we performed a cross‐sectional assessment of front‐line providers caring for patients on the internal medicine services in our academic hospital. Participants included medicine nursing staff in acute care and intermediate care units, medicine and combined medicine‐pediatrics housestaff physicians, and general internal medicine faculty physicians who supervised the housestaff physicians.

Study Setting

The study was conducted at a 378‐bed, university‐based, acute care teaching hospital in central Pennsylvania. There are a total of 64 internal medicine beds located in2 units, a general medicine unit (44 beds, staffed by 60 nurses, nurse‐to‐patient ratio 1:4) and an intermediate care unit (20 beds, staffed by 41 nurses, nurse‐to‐patient ratio 1:3). Both units are staffed by the general internal medicine physician teams. The academic medicine residency program consists of 69 internal medicine housestaff and 14 combined internal medicine‐pediatrics housestaff. Five teams, organized into 3 academic teaching teams and 2 nonteaching teams, provide care for all patients admitted to the medicine units. Teaching teams consist of 1 junior (postgraduate year [PGY]2) or senior (PGY34) housestaff member, 2 interns (PGY1), 2 medical students, and 1 attending physician.

There are several main features of BIRs in our medicine units. The rounding team of physicians alerts the assigned nurse about the start of rounds. In our main medicine unit, each doorway is equipped with a light that allows the physician team to indicate the start of the BIRs encounter. Case presentations by trainees occur either in the hallway or bedside, at the discretion of the attending physician. During bedside encounters, nurses typically contribute to the discussion about clinical status, decision making, patient concerns, and disposition. Patients are encouraged to contribute to the discussion and are provided the opportunity to ask questions.

For the purposes of this study, we specifically defined BIRs as: encounters that include the team of providers, at least 2 physicians plus a nurse or other care provider, discussing the case at the patient's bedside. In our prior work performed during the same time period as this study, we used the same definition to examine the incidence of and time spent in BIRs in both of our medicine units.[19] We found that 63% to 81% of patients in both units received BIRs. As a result, we assumed all nursing staff, attending physicians, and housestaff physicians had experienced this process, and their responses to this survey were contextualized in these experiences.

Survey Instrument

We developed a survey instrument specifically for this study. We derived items primarily from our prior qualitative work on physician‐based team bedside rounds and a literature review.[20, 21, 22, 23, 24, 25] For the benefits to BIRs, we developed items related to 5 domains, including factors related to the patient, education, communication/coordination/teamwork, efficiency and process, and outcomes.[20, 26] For the barriers to BIRs, we developed items related to 4 domains, including factors related to the patient, time, systems issues, and providers (nurses, attending physicians, and housestaff physicians).[22, 24, 25] We included our definition of BIRs into the survey instructions. We pilot tested the survey with 3 medicine faculty and 3 nursing staff and, based on our pilot, modified several questions to improve clarity. Primary demographic items in the survey included identification of provider role (nurses, attending physicians, or housestaff physicians) and years in the current role. Respondent preference for the benefits and barriers were investigated on a 7‐point scale (1=lowest response and 7=high response possible). Descriptive text was provided at the extremes (choice 1 and 7), but intermediary values (26) did not have descriptive cues.[27] As an incentive, the end of the survey provided respondents with an option for submitting their name to be entered into a raffle to win 1 of 50, $5 gift certificates to a coffee shop.

Prior to the end of the academic year in June 2013, we sent a survey link via e‐mail to all medicine nursing staff, housestaff physicians, and attending physicians. The email described the study and explained the voluntary nature of the work, and that informed consent would be implied by survey completion. Following the initial e‐mail, 3 additional weekly e‐mail reminders were sent by the lead investigator. The study was approved by the institutional review board at the Pennsylvania State College of Medicine.

Data Analysis

Descriptive statistics were used to examine the characteristics of the 3 respondent groups and combined totals for each survey item. The nonparametric Wilcoxon rank sum test was used to compare the average values between groups (nursing staff vs all physicians, attending physicians vs housestaff physicians) for both sets of survey variables (benefits and barriers). The nonparametric correlation statistical test Spearman rank was used to assess the degree of correlation between respondent groups for both survey variables. The data were analyzed using SAS 9.3 (SAS Institute, Cary, NC) and Stata/IC‐8 (StataCorp, College Station, Texas).

RESULTS

Of the 171 surveys sent, 149 participants completed surveys (response rate 87%). Responses were received from 53/58 nursing staff (91% response), 21/28 attending physicians (75% response), and 75/85 housestaff physicians (88% response). Table 1 describes the participant response demographics.

Demographics of Nursing Staff, Attending Physicians, and Housestaff Participants (N=149)
VariableValue
  • NOTE: Abbreviations: SD, standard deviation.

  • Senior resident includes third‐ and fourth‐year medicine or medicine/pediatrics residents.

Nursing staff, n=58, n (%)53 (36)
Intermediate care unit, n (%)14 (26)
General medicine ward, n (%)39 (74)
All day shifts, n (%)25 (47)
Mix of day and night shifts, n (%)32 (60)
Years of experience, mean (SD)7.4 (9)
Attending physicians, n=28, n (%)21 (14)
Years since residency graduation, mean (SD)10.5 (8)
No. of weeks in past year serving as teaching attending, mean (SD)9.1(8)
Housestaff physicians (n=85), n (%)75 (50)
Intern, n (%)28 (37)
Junior resident, n (%)25 (33)
Senior resident, n (%)a22 (29)

Benefits of BIRs

Respondents' perceptions of the benefits of BIRs are shown by mean value (between 1 and 7) for the total respondent pool and by each participant group (Table 2). Six of the 7 highest‐ranked benefits were related to communication, coordination, and teamwork, including improves communication between nurses and physicians, improves awareness of clinical issues that need to be addressed, and improves team‐building between nurses and physicians. Lowest‐ranked benefits were related to efficiency, process, and outcomes, including decreases patients' hospital length‐of‐stay, improves timeliness of consultations, and reduces ordering of unnecessary tests and treatments. Comparing mean values among the 3 groups, all 18 items showed statistical differences in response rates (all P values <0.05). Nursing staff reported more favorable ratings than both attending physicians and housestaff physicians for each of the 18 items, whereas attending physicians reported more favorable ratings than housestaff physicians in 16/18 items. The rank order among provider groups showed a high degree of correlation (r=0.92, P<0.001).

Comparisons of Ratings of the Benefits to Bedside Interprofessional Rounds as Reported by Nursing Staff, Attending Physicians, and Housestaff Physicians (N=149).
Survey ItemaItem DomainTotal, N=149, Mean (SD)Nurses, N=53, Mean (SD)Attending Physicians, N=21, Mean (SD)House staff Physicians, N=75, Mean (SD)b
  • NOTE: Abbreviations: CCT, communication/coordination/teamwork; E, education; EP, efficiency and process‐related factors; O, outcomes; P, patient‐related factors; SD, standard deviation.

  • Answer choices included 7 options from 1 (not at all) to 7 (definitely).

  • There were no statistical differences between intern physicians and junior and senior housestaff physicians.

  • P<0.01 vs all physicians from Wilcoxon rank sum test.

  • P<0.01 vs housestaff physicians from Wilcoxon rank sum test.

Improves communication between nurses and physicians.CCT6.26 (1.11)6.74 (0.59)c6.52 (1.03)d5.85 (1.26)
Improves awareness of clinical issues needing to be addressed.CCT6.05 (1.12)6.57 (0.64)c5.95 (1.07)5.71 (1.26)
Improves team‐building between nurses and physicians.CCT6.03 (1.32)6.72 (0.60)c6.14 (1.11)5.52 (1.51)
Improves coordination of the patient's care.CCT5.98 (1.34)6.60 (0.72)c6.00 (1.18)5.53 (1.55)
Improves nursing contributions to a patient's care plan.CCT5.91 (1.25)6.47 (0.77)c6.14 (0.85)5.44 (1.43)
Improves quality of care delivered in our unit.O5.72 (1.42)6.34 (0.83)c5.81 (1.33)5.25 (1.61)
Improves appreciation of the roles/contributions of other providers.CCT5.69 (1.49)6.36 (0.86)c5.90 (1.04)5.16 (1.73)
Promotes shared decision making between patients and providers.P5.62 (1.51)6.43 (0.77)c5.57 (1.40)5.05 (1.68)
Improves patients' satisfaction with their hospitalization.P, O5.53 (1.40)6.15 (0.95)c5.38 (1.12)5.13 (1.58)
Provides more respect/dignity to patients.P5.31 (1.55)6.23 (0.89)c5.10 (1.18)4.72 (1.71)
Decreases number of pages/phone calls between nurses and physicians.EP5.28 (1.82)6.28 (0.93)c5.24 (1.30)4.57 (2.09)
Improves educational opportunities for housestaff/students.E5.07 (1.77)6.08 (0.98)c4.81 (1.60)4.43 (1.93)
Improves the efficiency of your work.EP5.01 (1.77)6.04 (1.13)c4.90 (1.30)4.31 (1.92)
Improves adherence to evidence‐based guidelines or interventions.EP4.89 (1.79)6.06 (0.91)c4.00 (1.18)4.31 (1.97)
Improves the accuracy of your sign‐outs (or reports) to the next shift.EP4.80 (1.99)6.30 (0.93)c4.05 (1.66)3.95 (2.01)
Reduces ordering of unnecessary tests and treatments.O4.51 (1.86)5.77 (1.15)c3.86 (1.11)3.8 (1.97)
Improves the timeliness of consultations.EP4.28 (1.99)5.66 (1.22)c3.24 (1.48)3.59 (2.02)
Decreases patients' hospital length of stay.O4.15 (1.68)5.04 (1.24)c3.95 (1.16)3.57 (1.81)

Barriers to BIRs

Respondents' perceptions of barriers to BIRs are shown by mean value (between 1 and 7) for the total respondent pool and by each participant group (Table 3). The 6 highest‐ranked barriers were related to time, including nursing staff have limited time, the time required for bedside nurse‐physician encounters, and coordinating the start time of encounters with arrival of both physicians and nursing. The lowest‐ranked barriers were related to provider‐ and patient‐related factors, including patient lack of comfort with bedside nurse‐physician encounters, attending physicians/housestaff lack bedside skills, and attending physicians lack comfort with bedside nurse‐physician encounters. Comparing mean values between groups, 10 of 21 items showed statistical differences (P<0.05). The rank order among groups showed moderate correlation (nurses‐attending physicians r=0.62, nurses‐housestaff physicians r=0.76, attending physicians‐housestaff physicians r=0.82). A qualitative inspection of disparities among respondent groups highlighted that nursing staff were more likely to rank bedside rounds are not part of the unit's culture lower than physician groups.

Comparisons of Perceived Barriers to Bedside Interprofessional Rounds as Reported by Nursing Staff, Attending Physicians, and Housestaff Physicians (N=149)
Survey ItemaItem DomainTotal, N=149, Mean (SD)Nurses, n=53, Mean (SD)Attending Physicians, n=21, Mean (SD)Housestaff Physicians, n=75,b Mean (SD)
  • NOTE: Abbreviations: P, patient‐related factors; PR, provider‐related factors; S, systems issues; T, time.

  • Answer choices included 7 options from 1 (not at all) to 7 (definitely).

  • There were no statistical differences between intern physicians and junior and senior housestaff physicians.

  • P<0.01 vs all physicians from Wilcoxon rank sum test.

  • P<0.01 vs housestaff physicians from Wilcoxon rank sum test.

Nursing staff have limited time.T4.89 (1.34)4.96 (1.27)4.86 (1.65)4.85 (1.30)
Coordinating start time of encounters with arrival of physicians and nursing.T4.80 (1.50)4.58 (1.43)5.24 (1.45)4.84 (1.55)
Housestaff have limited time.T4.68 (1.47)4.56 (1.26)4.24 (1.81)4.89 (1.48)
Attending physicians have limited time.T4.50 (1.49)4.81 (1.34)4.33 (1.65)4.34 (1.53)
Other acutely sick patients in unit.T4.39 (1.42)4.79 (1.30)c4.52 (1.21)4.08 (1.49)
Time required for bedside nurse‐physician encounters.T4.32 (1.55)4.85 (1.38)c3.62 (1.80)4.15 (1.49)
Lack of use of the pink‐rounding light to alert nursing staff.S3.77 (1.75)4.71 (1.70)c3.48 (1.86)3.19 (1.46)
Patient not available (eg, off to test, getting bathed)S3.74 (1.40)3.98 (1.28)4.52 (1.36)d3.35 (1.37)
Large team size.S3.64 (1.74)3.12 (1.58)c3.95 (1.83)3.92 (1.77)
Patients in dispersed locations (eg, other units or in different hallways).S3.64 (1.77)2.77 (1.55)c4.52 (1.83)4.00 (1.66)
Bedside nurse‐physician rounds are not part of the unit's culture.S3.35 (1.94)2.25 (1.47)c4.76 (1.92)3.72 (1.85)
Limitations in physical facilities (eg, rooms too small, limited chairs).S3.25 (1.71)2.71 (1.72)3.33 (1.71)3.59 (1.62)
Insufficient nurse engagement during bedside nurse‐physician encounters.PR3.24 (1.63)2.71 (1.47)c3.67 (1.68)3.49 (1.65)
Patient on contact or respiratory isolation.S3.20 (1.82)2.42 (1.67)c3.43 (1.63)3.69 (1.80)
Language barrier between providers and patients.P2.69 (1.37)2.77 (1.39)2.57 (1.08)2.68 (1.43)
Privacy/sensitive patient issues.P2.65 (1.45)2.27 (1.24)2.57 (1.33)2.93 (1.56)
Housestaff lack comfort with bedside nurse‐physician encounters.PR2.55 (1.49)2.48 (1.15)2.67 (1.68)2.57 (1.65)
Nurses lack comfort with bedside nurse‐physician encounters.PR2.45 (1.45)2.35 (1.27)2.48 (1.66)2.51 (1.53)
Attending physicians lack comfort with bedside nurse‐physician encounters.PR2.35 (1.38)2.33 (1.25)2.33 (1.62)2.36 (1.41)
Attending physician/housestaff lack bedside skills (eg, history, exam).PR2.34 (1.34)2.19 (1.19)2.85 (1.69)2.30 (1.32)
Patient lack of comfort with bedside nurse‐physician encounters.P2.33 (1.48)2.23 (1.37)1.95 (1.32)2.5 (1.59)

DISCUSSION

In this study, we sought to compare perceptions of nurses and physicians on the benefits and barriers to BIRs. Nursing staff ranked each benefit higher than physicians, though rank orders of specific benefits were highly correlated. Highest‐ranked benefits related to coordination and communication more than quality or process benefits. Across groups, the highest‐ranked barriers to BIRs were related to time, whereas the lowest‐ranked factors were related to provider and patient discomfort. These results highlight important similarities and differences in perceptions between front‐line providers.

The highest‐ranked benefits were related to improved interprofessional communication and coordination. Combining interprofessional team members during care delivery allows for integrated understanding of daily care plans and clinical issues, and fosters collaboration and a team‐based atmosphere.[1, 20, 26] The lowest‐ranked benefits were related to more tangible measures, including length of stay, timely consultations, and judicious laboratory ordering. This finding contrasts with the limited literature demonstrating increased efficiency in general medicine units practicing IPCC.[16] These rankings may reflect a poor understanding or self‐assessment of outcome measures by healthcare providers, representing a potential focus for educational initiatives. Future investigations using objective assessment methods of outcomes and collaboration will provide a more accurate understanding of these findings.

The highest‐ranked barriers were related to time and systems issues. Several studies of physician‐based bedside rounds have identified systems‐ and time‐related issues as primary limiting barriers.[22, 24] In units without colocalization of patients and providers, finding receptive times for BIRs can be difficult. Although time‐related issues could be addressed by decreasing patient‐provider ratios, these changes require substantial investment in resources. A reasonable degree of improvement in efficiency and coordination is expected following acclimation to BIRs or by addressing modifiable systems factors to increase this activity. Less costly interventions, such as tailoring provider schedules, prescheduling patient rounding times, and geographic colocalization of patients and providers may be more feasible. However, the clinical microsystems within which medicine patients are cared for are often chaotic and disorganized at the infrastructural and cultural levels, which may be less influenced by surface‐level interventions. Such interventions may be ward specific and require customization to individual team needs.

The lowest‐ranked barriers to BIRs were related to provider‐ and patient‐related factors, including comfort level of patients and providers. Prior work on bedside rounds has identified physicians who are apprehensive about performing bedside rounds, but those who experience this activity are more likely to be comfortable with it.[12, 28] Our results from a culture where BIRs occur on nearly two‐thirds of patients suggest provider discomfort is not a predominant barrier.[22, 29] Additionally, educators have raised concerns about patient discomfort with bedside rounds, but nearly all studies evaluating patients' perspectives reveal patient preference for bedside case presentations over activities occurring in alternative locations.[30, 31, 32] Little work has investigated patient preference for BIRs as per our definition; our participants do not believe patients are discomforted by BIRs, building upon evidence in the literature for patient preferences regarding bedside activities.

Nursing staff perceptions of the benefits and culture related to BIRs were more positive than physicians. We hypothesize several reasons for this disparity. First, nursing staff may have more experience with observing and understanding the positive impact of BIRs and therefore are more likely to understand the positive ramifications. Alternatively, nursing staff may be satisfied with active integration into traditional physician‐centric decisions. Additionally, the professional culture and educational foundation of the nursing culture is based upon a patient‐centered approach and therefore may be more aligned with the goals of BIRs. Last, physicians may have competing priorities, favoring productivity and didactic learning rather than interprofessional collaboration. Further investigation is required to understand differences between nurses and physicians, in addition to other providers integral to BIRs (eg, care coordinators, pharmacists). Regardless, during the implementation of interprofessional collaborative care models, our findings suggest initial challenges, and the focus of educational initiatives may necessitate acclimating physician groups to benefits identified by front‐line nursing staff.

There are several limitations to our study. We investigated the perceptions of medicine nurses and physicians in 1 teaching hospital, limiting generalizability to other specialties, other vital professional groups, and nonteaching hospitals. Additionally, BIRs has been a focus of our hospital for several years. Therefore, perceived barriers may differ in BIRs‐nave hospitals. Second, although pilot‐tested for content, the construct validity of the instrument was not rigorously assessed, and the instrument was not designed to measure benefits and barriers not explicitly identified during pilot testing. Last, although surveys were anonymous, the possibility of social desirability bias exists, thereby limiting accuracy.

For over a century, physician‐led rounds have been the preferred modality for point‐of‐care decision making.[10, 15, 32, 33] BIRs address our growing understanding of patient‐centered care. Future efforts should address the quality of collaboration and current hospital and unit structures hindering patient‐centered IPCC and patient outcomes.

Acknowledgements

The authors thank the medicine nursing staff and physicians for their dedication to patient‐centered care and willingness to participate in this study.

Disclosures: The Department of Medicine at the Penn State Hershey Medical Center provided funding for this project. There are no conflicts of interest to report.

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References
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Journal of Hospital Medicine - 9(10)
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Journal of Hospital Medicine - 9(10)
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Bedside interprofessional rounds: Perceptions of benefits and barriers by internal medicine nursing staff, attending physicians, and housestaff physicians
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Address for correspondence and reprint requests: Jed D. Gonzalo, MD, Assistant Professor of Medicine and Public Health Sciences, Assistant Dean for Health Systems Education, Pennsylvania State University College of Medicine, 500 University Drive, Hershey, PA 17033; Telephone: 1‐717‐531‐8161; Fax: 1‐717‐531‐7726; E‐mail: [email protected]
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