Commentary on “Computerized clinical decision support system for diabetes in primary care does not improve quality of care: a cluster randomized controlled trial”
The month’s featured article by Heselmans and colleagues reports on the effectiveness of a computerized clinical decision support system (CCDS), called EBMeDS, in improving diabetes care within the Belgian primary care setting. 1 This article was of great interest to me because of the increasing focus on the use of clinical decision support (CDS) tools as a promising approach to improve delivery of guideline recommended care for patients with chronic disease. In addition, CDS tools are increasingly considered a critical component of learning health care systems. CDS tools link patient information from the electronic health record with evidence-based guidelines and generates automated reminders or messages to health care providers.
Yet, research has been mixed with regard to the effectiveness of CDS tools to manage chronic health conditions and improve health outcomes. According to the authors, many trials have showed no benefits of CDS in improving conditions such as hypertension and asthma and reasons for their ineffectiveness are not always known, although higher use rates have been cited as a contributor to the success of these tools. This study sought to understand whether the EBMeDS system would be effective in improving diabetes care, while also conducting a process evaluation that included assessments of barriers and facilitators to implementation from the perspective of primary care physicians.
The authors found that the system was not effective in changing HbA1c (primary outcome) and discuss several possible reasons for this finding. For example, the study did not include additional implementation strategies such as audit and feedback or patient education to support the use of the CCDS in practice. The authors also used the GUIDES checklist to evaluate the system. GUIDES is designed to help identify factors that affect success of a CDS intervention (i.e., context, content, system, and implementation). 2 The authors identified a need to improve relevance of the reminders to physicians (content) and reported that the system was difficult to engage with because of physicians’ existing workload (context). However, most users found the system itself was easy to use (system). Implementation of the CCDS was strengthened by adapting it to the Belgian primary care context before the study began. The authors also discussed that data on the actual use of the CCDS components (e.g., “click events” or number of times a reminder was triggered) was limited, which made it challenging to draw conclusions on the use of the system. Comprehensively understanding whether the CCDS and similar tools here in the U.S. are implemented as intended (i.e., intervention fidelity) is critical to understanding whether the lack of effect on patient outcomes is due to the intervention itself or the implementation. The authors conclude that major barriers were shortcomings of the EBMeDS system and how the data were coded across practices, and the lack of strategies to support greater use of the system.
In summary, although the study occurred in Belgium, it is a great example of how implementation science can be integrated with clinical informatics. As healthcare systems increasingly rely on CDS tools to improve delivery of guideline recommended care, and the success of CDS largely depends on their use, implementation science can help to provide a roadmap on how to best integrate CDS tools within complex healthcare systems.
Read the full abstract.
¹ Heselmans, A., Delvaux, N., Laenen, A., Van de Velde, S., Ramaekers, D., Kunnamo, I., & Aertgeerts, B. (2020). Computerized clinical decision support system for diabetes in primary care does not improve quality of care: a cluster-randomized controlled trial. Implement Sci, 15(1), 5. doi:10.1186/s13012-019-0955-6
² Van de Velde, S., Kunnamo, I., Roshanov, P., Kortteisto, T., Aertgeerts, B., Vandvik, P. O., Flottorp, S., & GUIDES expert panel (2018). The GUIDES checklist: development of a tool to improve the successful use of guideline-based computerised clinical decision support. Implementation science : IS, 13(1), 86. https://doi.org/10.1186/s13012-018-0772-3