Letters To The Editor

Dr. Horwitz appropriately notes that anemia of chronic disease may be better described as anemia of inflammation.[1, 2] We used the more traditional nomenclature for the sake of clarity to those readers who may not be familiar with the newer terminology. We do agree that there is often a role for hematology evaluation, but believe it should be based on the needs of the individual case and the needs of the organization. To be effective, any algorithm must maintain some flexibility for clinical judgment, and must also meet the needs of local stakeholders. We recommend that prior to implementing a preoperative anemia algorithm it is reviewed by the appropriate parties, which would typically include, but not be limited to, clinical leadership in anesthesia, surgery, medicine, and hematology.

Dr. Horwitz appropriately notes that anemia of chronic disease may be better described as anemia of inflammation.[1, 2] We used the more traditional nomenclature for the sake of clarity to those readers who may not be familiar with the newer terminology. We do agree that there is often a role for hematology evaluation, but believe it should be based on the needs of the individual case and the needs of the organization. To be effective, any algorithm must maintain some flexibility for clinical judgment, and must also meet the needs of local stakeholders. We recommend that prior to implementing a preoperative anemia algorithm it is reviewed by the appropriate parties, which would typically include, but not be limited to, clinical leadership in anesthesia, surgery, medicine, and hematology.

Dr. Horwitz appropriately notes that anemia of chronic disease may be better described as anemia of inflammation.[1, 2] We used the more traditional nomenclature for the sake of clarity to those readers who may not be familiar with the newer terminology. We do agree that there is often a role for hematology evaluation, but believe it should be based on the needs of the individual case and the needs of the organization. To be effective, any algorithm must maintain some flexibility for clinical judgment, and must also meet the needs of local stakeholders. We recommend that prior to implementing a preoperative anemia algorithm it is reviewed by the appropriate parties, which would typically include, but not be limited to, clinical leadership in anesthesia, surgery, medicine, and hematology.

There is one thing I would like to add to the flowsheet for management of preoperative anemia that Hohmuth et al.[1] have incorporated into their recent review titled Patient‐Centered Blood Management. Anemia of chronic disease, now called anemia of chronic inflammation,[2] is still a diagnosis of exclusion, and I would recommend a hematology evaluation before the final step of starting somebody on erythropoietic agents.

There is one thing I would like to add to the flowsheet for management of preoperative anemia that Hohmuth et al.[1] have incorporated into their recent review titled Patient‐Centered Blood Management. Anemia of chronic disease, now called anemia of chronic inflammation,[2] is still a diagnosis of exclusion, and I would recommend a hematology evaluation before the final step of starting somebody on erythropoietic agents.

There is one thing I would like to add to the flowsheet for management of preoperative anemia that Hohmuth et al.[1] have incorporated into their recent review titled Patient‐Centered Blood Management. Anemia of chronic disease, now called anemia of chronic inflammation,[2] is still a diagnosis of exclusion, and I would recommend a hematology evaluation before the final step of starting somebody on erythropoietic agents.

We agree with Drs. Arora and Mahmud that emerging mobile health (mHealth) approaches to improving patient engagement will need to demonstrate their value to advance health and healthcare. The potential for mHealth to do this has been often described[1, 2] but, so far, rarely measured or demonstrated.

The technology costs of our tablet‐based intervention[3] were low: 2 iPads at $400 each. The real expense was for personnel: research assistants needed to teach patients how to use the technology effectively. In the future, we hope to shift device and software orientation to patient‐care assistants, nurses, or even digital assistants, nonmedical personnel who have technical expertise with the health‐related devices and software needed to engage with the electronic health record and educational materials. Thus, at least part of the challenge of cost‐effectiveness aside from improved outcomeswill be demonstrating eventual time savings for providers who no longer need to hand deliver or explain paper pamphlets or printouts, or shepherd patients through their digitally assisted education.

One day we may muse, what did we do before mHealth? as we might do now when using mobile technologies for nonhealth‐related tasks like getting directions or making a call. Indeed, who can remember the last time they routinely used a paper map or phonebook for these daily tasks? Our prescription for tablets is a step in that direction, but we will need to also reimagine patient education and related daily tasks at the hospital and system level to realize the potential of lower costs and higher quality care we can achieve using mHealth.[4]

We agree with Drs. Arora and Mahmud that emerging mobile health (mHealth) approaches to improving patient engagement will need to demonstrate their value to advance health and healthcare. The potential for mHealth to do this has been often described[1, 2] but, so far, rarely measured or demonstrated.

The technology costs of our tablet‐based intervention[3] were low: 2 iPads at $400 each. The real expense was for personnel: research assistants needed to teach patients how to use the technology effectively. In the future, we hope to shift device and software orientation to patient‐care assistants, nurses, or even digital assistants, nonmedical personnel who have technical expertise with the health‐related devices and software needed to engage with the electronic health record and educational materials. Thus, at least part of the challenge of cost‐effectiveness aside from improved outcomeswill be demonstrating eventual time savings for providers who no longer need to hand deliver or explain paper pamphlets or printouts, or shepherd patients through their digitally assisted education.

One day we may muse, what did we do before mHealth? as we might do now when using mobile technologies for nonhealth‐related tasks like getting directions or making a call. Indeed, who can remember the last time they routinely used a paper map or phonebook for these daily tasks? Our prescription for tablets is a step in that direction, but we will need to also reimagine patient education and related daily tasks at the hospital and system level to realize the potential of lower costs and higher quality care we can achieve using mHealth.[4]

We agree with Drs. Arora and Mahmud that emerging mobile health (mHealth) approaches to improving patient engagement will need to demonstrate their value to advance health and healthcare. The potential for mHealth to do this has been often described[1, 2] but, so far, rarely measured or demonstrated.

The technology costs of our tablet‐based intervention[3] were low: 2 iPads at $400 each. The real expense was for personnel: research assistants needed to teach patients how to use the technology effectively. In the future, we hope to shift device and software orientation to patient‐care assistants, nurses, or even digital assistants, nonmedical personnel who have technical expertise with the health‐related devices and software needed to engage with the electronic health record and educational materials. Thus, at least part of the challenge of cost‐effectiveness aside from improved outcomeswill be demonstrating eventual time savings for providers who no longer need to hand deliver or explain paper pamphlets or printouts, or shepherd patients through their digitally assisted education.

One day we may muse, what did we do before mHealth? as we might do now when using mobile technologies for nonhealth‐related tasks like getting directions or making a call. Indeed, who can remember the last time they routinely used a paper map or phonebook for these daily tasks? Our prescription for tablets is a step in that direction, but we will need to also reimagine patient education and related daily tasks at the hospital and system level to realize the potential of lower costs and higher quality care we can achieve using mHealth.[4]

We are pleased to see positive results from the use of tablet computers (tablets) in engaging patients, as presented by Greyson and colleagues.[1] Patient engagement is correlated with better patient‐reported health outcomes.[2] But how do we justify any additional costs in the current climate?

The answer lies in the value delivered.[3] Achieving high‐value care means delivering the best outcomes at the lowest cost. Indeed, a growing number of studies are demonstrating improved outcomes with mobile technology. In Cleveland, tablet‐based self‐reporting in cancer patients improved communication of symptoms to physicians.[4] In Australia, chronic obstructive pulmonary disease patients engaged in tablet‐facilitated physical rehabilitation reported improved symptoms and exercise tolerance.[5] In Haiti, tablet‐delivered education sustainably improved knowledge of human immunodeficiency virus prevention and behavior among internally displaced women.[6]

What the extant literature is lacking, however, are studies demonstrating the cost‐effectiveness of mobile interventions. Digital platforms are unlikely to gain traction without these data. Some exceptions exist, but they are in the minority.[7] It is clear that engaged patients demonstrate better outcomes. However, future studies exploring the use of digital platforms would be well advised to include measures of cost‐effectiveness to build a true value‐based rationale for their integration into daily practice.

We are pleased to see positive results from the use of tablet computers (tablets) in engaging patients, as presented by Greyson and colleagues.[1] Patient engagement is correlated with better patient‐reported health outcomes.[2] But how do we justify any additional costs in the current climate?

The answer lies in the value delivered.[3] Achieving high‐value care means delivering the best outcomes at the lowest cost. Indeed, a growing number of studies are demonstrating improved outcomes with mobile technology. In Cleveland, tablet‐based self‐reporting in cancer patients improved communication of symptoms to physicians.[4] In Australia, chronic obstructive pulmonary disease patients engaged in tablet‐facilitated physical rehabilitation reported improved symptoms and exercise tolerance.[5] In Haiti, tablet‐delivered education sustainably improved knowledge of human immunodeficiency virus prevention and behavior among internally displaced women.[6]

What the extant literature is lacking, however, are studies demonstrating the cost‐effectiveness of mobile interventions. Digital platforms are unlikely to gain traction without these data. Some exceptions exist, but they are in the minority.[7] It is clear that engaged patients demonstrate better outcomes. However, future studies exploring the use of digital platforms would be well advised to include measures of cost‐effectiveness to build a true value‐based rationale for their integration into daily practice.

We are pleased to see positive results from the use of tablet computers (tablets) in engaging patients, as presented by Greyson and colleagues.[1] Patient engagement is correlated with better patient‐reported health outcomes.[2] But how do we justify any additional costs in the current climate?

The answer lies in the value delivered.[3] Achieving high‐value care means delivering the best outcomes at the lowest cost. Indeed, a growing number of studies are demonstrating improved outcomes with mobile technology. In Cleveland, tablet‐based self‐reporting in cancer patients improved communication of symptoms to physicians.[4] In Australia, chronic obstructive pulmonary disease patients engaged in tablet‐facilitated physical rehabilitation reported improved symptoms and exercise tolerance.[5] In Haiti, tablet‐delivered education sustainably improved knowledge of human immunodeficiency virus prevention and behavior among internally displaced women.[6]

What the extant literature is lacking, however, are studies demonstrating the cost‐effectiveness of mobile interventions. Digital platforms are unlikely to gain traction without these data. Some exceptions exist, but they are in the minority.[7] It is clear that engaged patients demonstrate better outcomes. However, future studies exploring the use of digital platforms would be well advised to include measures of cost‐effectiveness to build a true value‐based rationale for their integration into daily practice.

Fanucchi et al. provide compelling evidence that geographic localization decreases pager frequency in a dose‐dependent fashion.[1] However, the study's inability to capture the burden of face‐to‐face interruptions for localized teams undermines their conclusion that reduced paging will decrease resident workload and increase physician efficiency.

Although in‐person communications are less prone to error, psychological research suggests it is the actual interruption (and not just the modality) that disrupts cognitive processes and thus impedes problem solving, decision making, patient care efficiency, and safety.[2]

One study based in a teaching hospital emergency room (an effectively completely geographically localized care setting) found that attending physicians were interrupted once every 13.8 minutes on average. Only 1.86% of intrusions were from pages; 85.7% were face‐to‐face interruptions by nurses or medical staff.[3] Anecdotal evidence after restructuring our hospital's housestaff medicine teams to a geographic model was analogous. Such frequent disruptions would contradict Fanucchi et al.'s claim that direct communication[s]lead to fewer overall interruptions,[1] and would nullify the benefit of decreased paging.

Geographic localization offers potential advantages. However, rigorous scrutiny measuring amalgamate pager and in‐person interruptions is needed to know whether these translate into tangible workflow benefits.

Fanucchi et al. provide compelling evidence that geographic localization decreases pager frequency in a dose‐dependent fashion.[1] However, the study's inability to capture the burden of face‐to‐face interruptions for localized teams undermines their conclusion that reduced paging will decrease resident workload and increase physician efficiency.

Although in‐person communications are less prone to error, psychological research suggests it is the actual interruption (and not just the modality) that disrupts cognitive processes and thus impedes problem solving, decision making, patient care efficiency, and safety.[2]

One study based in a teaching hospital emergency room (an effectively completely geographically localized care setting) found that attending physicians were interrupted once every 13.8 minutes on average. Only 1.86% of intrusions were from pages; 85.7% were face‐to‐face interruptions by nurses or medical staff.[3] Anecdotal evidence after restructuring our hospital's housestaff medicine teams to a geographic model was analogous. Such frequent disruptions would contradict Fanucchi et al.'s claim that direct communication[s]lead to fewer overall interruptions,[1] and would nullify the benefit of decreased paging.

Geographic localization offers potential advantages. However, rigorous scrutiny measuring amalgamate pager and in‐person interruptions is needed to know whether these translate into tangible workflow benefits.

Fanucchi et al. provide compelling evidence that geographic localization decreases pager frequency in a dose‐dependent fashion.[1] However, the study's inability to capture the burden of face‐to‐face interruptions for localized teams undermines their conclusion that reduced paging will decrease resident workload and increase physician efficiency.

Although in‐person communications are less prone to error, psychological research suggests it is the actual interruption (and not just the modality) that disrupts cognitive processes and thus impedes problem solving, decision making, patient care efficiency, and safety.[2]

One study based in a teaching hospital emergency room (an effectively completely geographically localized care setting) found that attending physicians were interrupted once every 13.8 minutes on average. Only 1.86% of intrusions were from pages; 85.7% were face‐to‐face interruptions by nurses or medical staff.[3] Anecdotal evidence after restructuring our hospital's housestaff medicine teams to a geographic model was analogous. Such frequent disruptions would contradict Fanucchi et al.'s claim that direct communication[s]lead to fewer overall interruptions,[1] and would nullify the benefit of decreased paging.

Geographic localization offers potential advantages. However, rigorous scrutiny measuring amalgamate pager and in‐person interruptions is needed to know whether these translate into tangible workflow benefits.

We acknowledge that our inability to measure in‐person interruptions is a limitation of our study. We maintain that while in‐person interruptions may increase in geographically localized patient care units, this form of direct face‐to‐face communication is more effective, efficient and decreases the latent errors inherent in alphanumeric paging.

Dr. Gandiga cites a study conducted in an emergency department where the vast majority of interruptions to attending physicians were in person from nurses or medical staff. We feel that this study cannot be extrapolated to medical floors, as the workflow and patient flow in an emergency department is very different than on a medical floor. The continuous throughput of patients in an emergency department would require ongoing and frequent communication between the different members of the care team. In addition, the physicians in that study were receiving an average of 1 page in 12 hours, compared to greater than 25 in 12 hours for our interns on a localized service, which illustrates the problem with comparing the emergency department to a localized medical floor.[1, 2]

We believe that the benefits of geographically localized care models, which include dramatic decreases in paging, improved efficiency, and greater agreement on the plan of care, outweigh the probable increases in in‐person interruptions. Additional study is indeed warranted to further clarify this discussion.

We acknowledge that our inability to measure in‐person interruptions is a limitation of our study. We maintain that while in‐person interruptions may increase in geographically localized patient care units, this form of direct face‐to‐face communication is more effective, efficient and decreases the latent errors inherent in alphanumeric paging.

Dr. Gandiga cites a study conducted in an emergency department where the vast majority of interruptions to attending physicians were in person from nurses or medical staff. We feel that this study cannot be extrapolated to medical floors, as the workflow and patient flow in an emergency department is very different than on a medical floor. The continuous throughput of patients in an emergency department would require ongoing and frequent communication between the different members of the care team. In addition, the physicians in that study were receiving an average of 1 page in 12 hours, compared to greater than 25 in 12 hours for our interns on a localized service, which illustrates the problem with comparing the emergency department to a localized medical floor.[1, 2]

We believe that the benefits of geographically localized care models, which include dramatic decreases in paging, improved efficiency, and greater agreement on the plan of care, outweigh the probable increases in in‐person interruptions. Additional study is indeed warranted to further clarify this discussion.

We acknowledge that our inability to measure in‐person interruptions is a limitation of our study. We maintain that while in‐person interruptions may increase in geographically localized patient care units, this form of direct face‐to‐face communication is more effective, efficient and decreases the latent errors inherent in alphanumeric paging.

Dr. Gandiga cites a study conducted in an emergency department where the vast majority of interruptions to attending physicians were in person from nurses or medical staff. We feel that this study cannot be extrapolated to medical floors, as the workflow and patient flow in an emergency department is very different than on a medical floor. The continuous throughput of patients in an emergency department would require ongoing and frequent communication between the different members of the care team. In addition, the physicians in that study were receiving an average of 1 page in 12 hours, compared to greater than 25 in 12 hours for our interns on a localized service, which illustrates the problem with comparing the emergency department to a localized medical floor.[1, 2]

We believe that the benefits of geographically localized care models, which include dramatic decreases in paging, improved efficiency, and greater agreement on the plan of care, outweigh the probable increases in in‐person interruptions. Additional study is indeed warranted to further clarify this discussion.

After reading the letter to the editor from Neil Goldfarb, we are concerned that the focus of our study[1] was misinterpreted. Upon reviewing the methodology for Leapfrog's Hospital Safety Score in May 2013, we were surprised to find that Leapfrog uses 2 separate scoring methodologies, depending on whether the hospital participates in the Leapfrog Hospital Survey. Survey participants are scored from 26 measures, whereas nonparticipants are scored from only 18 measures3 of which are imputed from other data sourceswith recalibrated weightings for each measure. Measuring and publicly disclosing hospital information are paramount to improving safety and quality, and we applaud Leapfrog for taking a leading role in this. However, our report demonstrated that Leapfrog's Hospital Safety Score, which was attained through 2 separate methodologies, may result in unintended inconsistency or misinterpretation.

We believe Mr. Goldfarb misunderstood our notion of statistical significance. In the report, we acknowledged that the mean score differences between participating and nonparticipating hospitals in our sample were not statistically significant, possibly due to small sample size. However, this was not the focus of our report. Utilizing a mean imputation approach, we rescored the nonparticipating hospitals in our sample as if they had participated in the Leapfrog Hospital Survey. The differences between the original nonparticipant scores and their respective participant estimations were not statistically significant. However, due to the cutoff points Leapfrog uses to assign letter grades, these differences resulted in a letter grade change for many of the nonparticipating hospitals in our sample.

We wish to clarify that a hospital's choice to participate or not to participate in the Leapfrog Hospital Survey is not a reflection of their willingness to promote patient safety. Hospitals voluntarily report data to numerous private organizations and are required to report hundreds of quality and safety measures to government agencies. The 26 (or 18) measures included in Leapfrog's Hospital Safety Score are merely a fraction of the measures hospitals already report.

Finally, we regret that our brief report has been mischaracterized by Neil Goldfarb as being clearly biased against the work of the Leapfrog Group. This is far from our intent. Throughout the manuscript, we repeatedly acknowledge Leapfrog's contribution in patient safety improvement; our work does not intend to discredit Leapfrog's hard‐earned reputation. We provide a recommendation that Leapfrog produce 2 separate reports for participating and nonparticipating hospitals to maintain clarity. Our research has followed academic protocol, has undergone a stringent peer‐review process, and included full disclosure of any potential conflicts of interest. We hope our analysis will contribute to the continuing improvement of Leapfrog's hospital patient safety reporting.

After reading the letter to the editor from Neil Goldfarb, we are concerned that the focus of our study[1] was misinterpreted. Upon reviewing the methodology for Leapfrog's Hospital Safety Score in May 2013, we were surprised to find that Leapfrog uses 2 separate scoring methodologies, depending on whether the hospital participates in the Leapfrog Hospital Survey. Survey participants are scored from 26 measures, whereas nonparticipants are scored from only 18 measures3 of which are imputed from other data sourceswith recalibrated weightings for each measure. Measuring and publicly disclosing hospital information are paramount to improving safety and quality, and we applaud Leapfrog for taking a leading role in this. However, our report demonstrated that Leapfrog's Hospital Safety Score, which was attained through 2 separate methodologies, may result in unintended inconsistency or misinterpretation.

We believe Mr. Goldfarb misunderstood our notion of statistical significance. In the report, we acknowledged that the mean score differences between participating and nonparticipating hospitals in our sample were not statistically significant, possibly due to small sample size. However, this was not the focus of our report. Utilizing a mean imputation approach, we rescored the nonparticipating hospitals in our sample as if they had participated in the Leapfrog Hospital Survey. The differences between the original nonparticipant scores and their respective participant estimations were not statistically significant. However, due to the cutoff points Leapfrog uses to assign letter grades, these differences resulted in a letter grade change for many of the nonparticipating hospitals in our sample.

We wish to clarify that a hospital's choice to participate or not to participate in the Leapfrog Hospital Survey is not a reflection of their willingness to promote patient safety. Hospitals voluntarily report data to numerous private organizations and are required to report hundreds of quality and safety measures to government agencies. The 26 (or 18) measures included in Leapfrog's Hospital Safety Score are merely a fraction of the measures hospitals already report.

Finally, we regret that our brief report has been mischaracterized by Neil Goldfarb as being clearly biased against the work of the Leapfrog Group. This is far from our intent. Throughout the manuscript, we repeatedly acknowledge Leapfrog's contribution in patient safety improvement; our work does not intend to discredit Leapfrog's hard‐earned reputation. We provide a recommendation that Leapfrog produce 2 separate reports for participating and nonparticipating hospitals to maintain clarity. Our research has followed academic protocol, has undergone a stringent peer‐review process, and included full disclosure of any potential conflicts of interest. We hope our analysis will contribute to the continuing improvement of Leapfrog's hospital patient safety reporting.

After reading the letter to the editor from Neil Goldfarb, we are concerned that the focus of our study[1] was misinterpreted. Upon reviewing the methodology for Leapfrog's Hospital Safety Score in May 2013, we were surprised to find that Leapfrog uses 2 separate scoring methodologies, depending on whether the hospital participates in the Leapfrog Hospital Survey. Survey participants are scored from 26 measures, whereas nonparticipants are scored from only 18 measures3 of which are imputed from other data sourceswith recalibrated weightings for each measure. Measuring and publicly disclosing hospital information are paramount to improving safety and quality, and we applaud Leapfrog for taking a leading role in this. However, our report demonstrated that Leapfrog's Hospital Safety Score, which was attained through 2 separate methodologies, may result in unintended inconsistency or misinterpretation.

We believe Mr. Goldfarb misunderstood our notion of statistical significance. In the report, we acknowledged that the mean score differences between participating and nonparticipating hospitals in our sample were not statistically significant, possibly due to small sample size. However, this was not the focus of our report. Utilizing a mean imputation approach, we rescored the nonparticipating hospitals in our sample as if they had participated in the Leapfrog Hospital Survey. The differences between the original nonparticipant scores and their respective participant estimations were not statistically significant. However, due to the cutoff points Leapfrog uses to assign letter grades, these differences resulted in a letter grade change for many of the nonparticipating hospitals in our sample.

We wish to clarify that a hospital's choice to participate or not to participate in the Leapfrog Hospital Survey is not a reflection of their willingness to promote patient safety. Hospitals voluntarily report data to numerous private organizations and are required to report hundreds of quality and safety measures to government agencies. The 26 (or 18) measures included in Leapfrog's Hospital Safety Score are merely a fraction of the measures hospitals already report.

Finally, we regret that our brief report has been mischaracterized by Neil Goldfarb as being clearly biased against the work of the Leapfrog Group. This is far from our intent. Throughout the manuscript, we repeatedly acknowledge Leapfrog's contribution in patient safety improvement; our work does not intend to discredit Leapfrog's hard‐earned reputation. We provide a recommendation that Leapfrog produce 2 separate reports for participating and nonparticipating hospitals to maintain clarity. Our research has followed academic protocol, has undergone a stringent peer‐review process, and included full disclosure of any potential conflicts of interest. We hope our analysis will contribute to the continuing improvement of Leapfrog's hospital patient safety reporting.

As the Executive Director of a purchaser coalition that has been promoting hospital participation in the Leapfrog Hospital Survey in our region, I found the brief report from Hwang and colleagues, Hospital Patient Safety Grades May Misrepresent Hospital Performance,[1] troubling. Putting aside the methodological vagaries and the lack of statistical significance to the findings, the authors have a clear bias against the work of the Leapfrog Group. As acknowledged in the disclosures, their institution does not participate in the Leapfrog Hospital Survey. What is not acknowledged is that their institution has not performed particularly well on the hospital safety score.

The authors note in their introduction that according to Leapfrog, 4 to 6 days are required for a hospital to compile the necessary survey data with an additional 90‐minute time commitment to enter the data, and state that this is a significant time commitment for many hospitals. Although it undoubtedly is a significant time commitment, apparently more than 1400 hospitals have found the time and made a commitment to measuring and publicly disclosing information that will help consumers, purchasers, and health plans identify and select safer, higher‐quality care providers. In addition, many studies have shown that public reporting helps to drive providers to improve. In the 12 years since To Err Is Human[2] was published, nothing suggests that the number of deaths associated with medical errors has diminished; in fact, a recent study suggested that over 400,000 deaths may occur annually due to errors.[3] In light of these ongoing safety concerns, is a commitment of 4 to 6 days really too large an investment?

It is time that America's hospitals stopped whining about the burden of public reporting and recognized that their customers have a right to, and are starting to demand, better data on quality, safety, and costs of care. If the Hospital Safety Score is indeed biased against nonreporting hospitals (and I remain unconvinced from this poorly designed study that it is), the main message of the article should have been that hospitals need to start reporting their data, not that the Leapfrog Group needs to change its methodology.

As the Executive Director of a purchaser coalition that has been promoting hospital participation in the Leapfrog Hospital Survey in our region, I found the brief report from Hwang and colleagues, Hospital Patient Safety Grades May Misrepresent Hospital Performance,[1] troubling. Putting aside the methodological vagaries and the lack of statistical significance to the findings, the authors have a clear bias against the work of the Leapfrog Group. As acknowledged in the disclosures, their institution does not participate in the Leapfrog Hospital Survey. What is not acknowledged is that their institution has not performed particularly well on the hospital safety score.

The authors note in their introduction that according to Leapfrog, 4 to 6 days are required for a hospital to compile the necessary survey data with an additional 90‐minute time commitment to enter the data, and state that this is a significant time commitment for many hospitals. Although it undoubtedly is a significant time commitment, apparently more than 1400 hospitals have found the time and made a commitment to measuring and publicly disclosing information that will help consumers, purchasers, and health plans identify and select safer, higher‐quality care providers. In addition, many studies have shown that public reporting helps to drive providers to improve. In the 12 years since To Err Is Human[2] was published, nothing suggests that the number of deaths associated with medical errors has diminished; in fact, a recent study suggested that over 400,000 deaths may occur annually due to errors.[3] In light of these ongoing safety concerns, is a commitment of 4 to 6 days really too large an investment?

It is time that America's hospitals stopped whining about the burden of public reporting and recognized that their customers have a right to, and are starting to demand, better data on quality, safety, and costs of care. If the Hospital Safety Score is indeed biased against nonreporting hospitals (and I remain unconvinced from this poorly designed study that it is), the main message of the article should have been that hospitals need to start reporting their data, not that the Leapfrog Group needs to change its methodology.

As the Executive Director of a purchaser coalition that has been promoting hospital participation in the Leapfrog Hospital Survey in our region, I found the brief report from Hwang and colleagues, Hospital Patient Safety Grades May Misrepresent Hospital Performance,[1] troubling. Putting aside the methodological vagaries and the lack of statistical significance to the findings, the authors have a clear bias against the work of the Leapfrog Group. As acknowledged in the disclosures, their institution does not participate in the Leapfrog Hospital Survey. What is not acknowledged is that their institution has not performed particularly well on the hospital safety score.

The authors note in their introduction that according to Leapfrog, 4 to 6 days are required for a hospital to compile the necessary survey data with an additional 90‐minute time commitment to enter the data, and state that this is a significant time commitment for many hospitals. Although it undoubtedly is a significant time commitment, apparently more than 1400 hospitals have found the time and made a commitment to measuring and publicly disclosing information that will help consumers, purchasers, and health plans identify and select safer, higher‐quality care providers. In addition, many studies have shown that public reporting helps to drive providers to improve. In the 12 years since To Err Is Human[2] was published, nothing suggests that the number of deaths associated with medical errors has diminished; in fact, a recent study suggested that over 400,000 deaths may occur annually due to errors.[3] In light of these ongoing safety concerns, is a commitment of 4 to 6 days really too large an investment?

It is time that America's hospitals stopped whining about the burden of public reporting and recognized that their customers have a right to, and are starting to demand, better data on quality, safety, and costs of care. If the Hospital Safety Score is indeed biased against nonreporting hospitals (and I remain unconvinced from this poorly designed study that it is), the main message of the article should have been that hospitals need to start reporting their data, not that the Leapfrog Group needs to change its methodology.