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A learning collaborative approach can significantly improve adherence to a treat-to-target approach in patients with rheumatoid arthritis, new research suggests.
While numerous clinical trials have shown that a strategy of treating to target achieves better outcomes, compared with usual care, there is evidence that this approach is not always practiced, wrote Daniel H. Solomon, MD, of the division of rheumatology at Brigham and Women’s Hospital, Boston, and his coauthors.
The intervention first involved the faculty developing a set of principles and concepts to describe the goals for implementing treat to target. These were then disseminated to the sites through a single face-to-face learning session and a series of webinars, which were also recorded and made available online. The first session also worked on team building within sites and on cross-site collaborative relationships.
“In this study, we found large benefits, despite using a relatively low-intensity approach to the learning collaborative, with only one face-to-face meeting,” wrote the authors, who noted that altogether the program involved around 20 hours per provider over 9 months.
The investigators used a composite treat-to-target implementation score as the primary outcome, which was based on the presence or absence of four measures deemed central to the principles and concepts of a treat-to-target strategy. The measures were:
- Specifying a disease activity target.
- Recording RA disease activity, using one of four recommended measures (Disease Activity Score-28, Simplified Disease Activity Index, Clinical Disease Activity Index, or Routine Assessment of Patient Index Data 3), with results described numerically or by category (remission, low, moderate, or high).
- When a decision was being made (change in target or change in treatment), documenting shared decision making.
- Basing treatment decisions on target and disease activity measure or describing reasons why treat to target was not adhered to.
The intervention increased the treat-to-target implementation score by 46 percentage points, from 11% to 57%. In comparison, the control arm had an increase of 14 percentage points, from 11% to 25% (P = .004). It achieved a substantial and significant increase in the proportion of participants for whom a treatment target was documented, from 0.6% at baseline to 45.6% at the 9-month follow-up, compared with a 12.5-point increase in the control group. The recording of disease activity increased from 20% to 89.1% in the intervention arm, compared with an increase from 30.2% to 52.3% in the control arm. Similarly, shared decision making increased from 51.3% to 85.9% in the intervention group, compared with a rise from 24.5% to 43% in the control arm.
The study also examined a range of secondary outcomes representing the impact of the intervention on patients. They found that a positive change in treat-to-target adherence score was seen in 83.8% of patients in the intervention arm, compared with 36.8% of patients in the control arm (P = .0001), when almost no patient visits at baseline were adherent to all components of treat to target.
At the 9-month follow-up, 25.9% of visits in the intervention arm were adherent to all four components of the treat-to-target approach, compared with 5.6% in the control arm.
The authors suggested that their learning collaborative approach could be applied across a range of chronic diseases.
“In fact, our model is consistent with the goals and strategy of the Million Hearts campaign to reduce cardiovascular disease burden across the U.S. by targeting five areas of goal-based therapy.”
There were no significant differences between the intervention and control arms in the number of orders for drug-monitoring laboratory tests or radiology orders. However, patients in the intervention arm had fewer adverse events than did those in the control arm (0.26 vs. 0.43 per patient; P = .043).
The investigators noted that the study was relatively small – involving just 11 sites – and the primary outcome was a process measure that did not reflect clinical outcomes and has not been validated.
The study was supported by the National Institutes of Health. One author declared salary support through research grants to his hospital from pharmaceutical companies, while another declared research grants from AbbVie for treat-to-target research activities.
A learning collaborative approach can significantly improve adherence to a treat-to-target approach in patients with rheumatoid arthritis, new research suggests.
While numerous clinical trials have shown that a strategy of treating to target achieves better outcomes, compared with usual care, there is evidence that this approach is not always practiced, wrote Daniel H. Solomon, MD, of the division of rheumatology at Brigham and Women’s Hospital, Boston, and his coauthors.
The intervention first involved the faculty developing a set of principles and concepts to describe the goals for implementing treat to target. These were then disseminated to the sites through a single face-to-face learning session and a series of webinars, which were also recorded and made available online. The first session also worked on team building within sites and on cross-site collaborative relationships.
“In this study, we found large benefits, despite using a relatively low-intensity approach to the learning collaborative, with only one face-to-face meeting,” wrote the authors, who noted that altogether the program involved around 20 hours per provider over 9 months.
The investigators used a composite treat-to-target implementation score as the primary outcome, which was based on the presence or absence of four measures deemed central to the principles and concepts of a treat-to-target strategy. The measures were:
- Specifying a disease activity target.
- Recording RA disease activity, using one of four recommended measures (Disease Activity Score-28, Simplified Disease Activity Index, Clinical Disease Activity Index, or Routine Assessment of Patient Index Data 3), with results described numerically or by category (remission, low, moderate, or high).
- When a decision was being made (change in target or change in treatment), documenting shared decision making.
- Basing treatment decisions on target and disease activity measure or describing reasons why treat to target was not adhered to.
The intervention increased the treat-to-target implementation score by 46 percentage points, from 11% to 57%. In comparison, the control arm had an increase of 14 percentage points, from 11% to 25% (P = .004). It achieved a substantial and significant increase in the proportion of participants for whom a treatment target was documented, from 0.6% at baseline to 45.6% at the 9-month follow-up, compared with a 12.5-point increase in the control group. The recording of disease activity increased from 20% to 89.1% in the intervention arm, compared with an increase from 30.2% to 52.3% in the control arm. Similarly, shared decision making increased from 51.3% to 85.9% in the intervention group, compared with a rise from 24.5% to 43% in the control arm.
The study also examined a range of secondary outcomes representing the impact of the intervention on patients. They found that a positive change in treat-to-target adherence score was seen in 83.8% of patients in the intervention arm, compared with 36.8% of patients in the control arm (P = .0001), when almost no patient visits at baseline were adherent to all components of treat to target.
At the 9-month follow-up, 25.9% of visits in the intervention arm were adherent to all four components of the treat-to-target approach, compared with 5.6% in the control arm.
The authors suggested that their learning collaborative approach could be applied across a range of chronic diseases.
“In fact, our model is consistent with the goals and strategy of the Million Hearts campaign to reduce cardiovascular disease burden across the U.S. by targeting five areas of goal-based therapy.”
There were no significant differences between the intervention and control arms in the number of orders for drug-monitoring laboratory tests or radiology orders. However, patients in the intervention arm had fewer adverse events than did those in the control arm (0.26 vs. 0.43 per patient; P = .043).
The investigators noted that the study was relatively small – involving just 11 sites – and the primary outcome was a process measure that did not reflect clinical outcomes and has not been validated.
The study was supported by the National Institutes of Health. One author declared salary support through research grants to his hospital from pharmaceutical companies, while another declared research grants from AbbVie for treat-to-target research activities.
A learning collaborative approach can significantly improve adherence to a treat-to-target approach in patients with rheumatoid arthritis, new research suggests.
While numerous clinical trials have shown that a strategy of treating to target achieves better outcomes, compared with usual care, there is evidence that this approach is not always practiced, wrote Daniel H. Solomon, MD, of the division of rheumatology at Brigham and Women’s Hospital, Boston, and his coauthors.
The intervention first involved the faculty developing a set of principles and concepts to describe the goals for implementing treat to target. These were then disseminated to the sites through a single face-to-face learning session and a series of webinars, which were also recorded and made available online. The first session also worked on team building within sites and on cross-site collaborative relationships.
“In this study, we found large benefits, despite using a relatively low-intensity approach to the learning collaborative, with only one face-to-face meeting,” wrote the authors, who noted that altogether the program involved around 20 hours per provider over 9 months.
The investigators used a composite treat-to-target implementation score as the primary outcome, which was based on the presence or absence of four measures deemed central to the principles and concepts of a treat-to-target strategy. The measures were:
- Specifying a disease activity target.
- Recording RA disease activity, using one of four recommended measures (Disease Activity Score-28, Simplified Disease Activity Index, Clinical Disease Activity Index, or Routine Assessment of Patient Index Data 3), with results described numerically or by category (remission, low, moderate, or high).
- When a decision was being made (change in target or change in treatment), documenting shared decision making.
- Basing treatment decisions on target and disease activity measure or describing reasons why treat to target was not adhered to.
The intervention increased the treat-to-target implementation score by 46 percentage points, from 11% to 57%. In comparison, the control arm had an increase of 14 percentage points, from 11% to 25% (P = .004). It achieved a substantial and significant increase in the proportion of participants for whom a treatment target was documented, from 0.6% at baseline to 45.6% at the 9-month follow-up, compared with a 12.5-point increase in the control group. The recording of disease activity increased from 20% to 89.1% in the intervention arm, compared with an increase from 30.2% to 52.3% in the control arm. Similarly, shared decision making increased from 51.3% to 85.9% in the intervention group, compared with a rise from 24.5% to 43% in the control arm.
The study also examined a range of secondary outcomes representing the impact of the intervention on patients. They found that a positive change in treat-to-target adherence score was seen in 83.8% of patients in the intervention arm, compared with 36.8% of patients in the control arm (P = .0001), when almost no patient visits at baseline were adherent to all components of treat to target.
At the 9-month follow-up, 25.9% of visits in the intervention arm were adherent to all four components of the treat-to-target approach, compared with 5.6% in the control arm.
The authors suggested that their learning collaborative approach could be applied across a range of chronic diseases.
“In fact, our model is consistent with the goals and strategy of the Million Hearts campaign to reduce cardiovascular disease burden across the U.S. by targeting five areas of goal-based therapy.”
There were no significant differences between the intervention and control arms in the number of orders for drug-monitoring laboratory tests or radiology orders. However, patients in the intervention arm had fewer adverse events than did those in the control arm (0.26 vs. 0.43 per patient; P = .043).
The investigators noted that the study was relatively small – involving just 11 sites – and the primary outcome was a process measure that did not reflect clinical outcomes and has not been validated.
The study was supported by the National Institutes of Health. One author declared salary support through research grants to his hospital from pharmaceutical companies, while another declared research grants from AbbVie for treat-to-target research activities.
FROM ARTHRITIS & RHEUMATOLOGY
Key clinical point:
Major finding: A site-based intervention increased a treat-to-target implementation score by 46 percentage points – from 11% to 57% – compared with a 14–percentage point increase in the control arm.
Data source: The cluster-randomized, wait list–controlled, quality improvement TRACTION trial, involving 11 sites and 641 patients.
Disclosures: The study was supported by the National Institutes of Health. One author declared salary support through research grants to his hospital from pharmaceutical companies, while another declared research grants from AbbVie for treat-to-target research activities.