Dataset Information

Governance for clinical decision support: case studies and recommended practices from leading institutions.

ABSTRACT:

Objective

Clinical decision support (CDS) is a powerful tool for improving healthcare quality and ensuring patient safety; however, effective implementation of CDS requires effective clinical and technical governance structures. The authors sought to determine the range and variety of these governance structures and identify a set of recommended practices through observational study.

Design

Three site visits were conducted at institutions across the USA to learn about CDS capabilities and processes from clinical, technical, and organizational perspectives. Based on the results of these visits, written questionnaires were sent to the three institutions visited and two additional sites. Together, these five organizations encompass a variety of academic and community hospitals as well as small and large ambulatory practices. These organizations use both commercially available and internally developed clinical information systems.

Measurements

Characteristics of clinical information systems and CDS systems used at each site as well as governance structures and content management approaches were identified through extensive field interviews and follow-up surveys.

Results

Six recommended practices were identified in the area of governance, and four were identified in the area of content management. Key similarities and differences between the organizations studied were also highlighted.

Conclusion

Each of the five sites studied contributed to the recommended practices presented in this paper for CDS governance. Since these strategies appear to be useful at a diverse range of institutions, they should be considered by any future implementers of decision support.

SUBMITTER: Wright A

PROVIDER: S-EPMC3116253 | biostudies-literature | 2011 Mar-Apr

REPOSITORIES: biostudies-literature

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Publications

Governance for clinical decision support: case studies and recommended practices from leading institutions.

Wright Adam A Sittig Dean F DF Ash Joan S JS Bates David W DW Feblowitz Joshua J Fraser Greg G Maviglia Saverio M SM McMullen Carmit C Nichol W Paul WP Pang Justine E JE Starmer Jack J Middleton Blackford B

Journal of the American Medical Informatics Association : JAMIA 20110120 2

<h4>Objective</h4>Clinical decision support (CDS) is a powerful tool for improving healthcare quality and ensuring patient safety; however, effective implementation of CDS requires effective clinical and technical governance structures. The authors sought to determine the range and variety of these governance structures and identify a set of recommended practices through observational study.<h4>Design</h4>Three site visits were conducted at institutions across the USA to learn about CDS capabili ...[more]

PMID: 21252052

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Project description:BackgroundLimited consideration of clinical decision support (CDS) design best practices, such as a user-centered design, is often cited as a key barrier to CDS adoption and effectiveness. The application of CDS best practices is resource intensive; thus, institutions often rely on commercially available CDS tools that are created to meet the generalized needs of many institutions and are not user centered. Beyond resource availability, insufficient guidance on how to address key aspects of implementation, such as contextual factors, may also limit the application of CDS best practices. An implementation science (IS) framework could provide needed guidance and increase the reproducibility of CDS implementations.ObjectiveThis study aims to compare the effectiveness of an enhanced CDS tool informed by CDS best practices and an IS framework with a generic, commercially available CDS tool.MethodsWe conducted an explanatory sequential mixed methods study. An IS-enhanced and commercial CDS alert were compared in a cluster randomized trial across 28 primary care clinics. Both alerts aimed to improve beta-blocker prescribing for heart failure. The enhanced alert was informed by CDS best practices and the Practical, Robust, Implementation, and Sustainability Model (PRISM) IS framework, whereas the commercial alert followed vendor-supplied specifications. Following PRISM, the enhanced alert was informed by iterative, multilevel stakeholder input and the dynamic interactions of the internal and external environment. Outcomes aligned with PRISM's evaluation measures, including patient reach, clinician adoption, and changes in prescribing behavior. Clinicians exposed to each alert were interviewed to identify design features that might influence adoption. The interviews were analyzed using a thematic approach.ResultsBetween March 15 and August 23, 2019, the enhanced alert fired for 61 patients (106 alerts, 87 clinicians) and the commercial alert fired for 26 patients (59 alerts, 31 clinicians). The adoption and effectiveness of the enhanced alert were significantly higher than those of the commercial alert (62% vs 29% alerts adopted, P<.001; 14% vs 0% changed prescribing, P=.006). Of the 21 clinicians interviewed, most stated that they preferred the enhanced alert.ConclusionsThe results of this study suggest that applying CDS best practices with an IS framework to create CDS tools improves implementation success compared with a commercially available tool.Trial registrationClinicalTrials.gov NCT04028557; http://clinicaltrials.gov/ct2/show/NCT04028557.

Project description:ObjectiveDecision support systems linked to administrative databases provide a unique opportunity to monitor adherence to guidelines and target disease management strategies towards patients not receiving guideline-based therapy. The objective of this study was to evaluate the discrepancy between actual asthma treatments prescribed by primary care physicians compared to those recommended by evidence-based guidelines using a decision support tool linked to a provincial health administrative database.DesignThe drug and medical services information of individuals with asthma was identified from the provincial health database and was pushed through an asthma decision support system (ADSS). Recommendations aimed at optimising asthma treatment were generated on two index dates, 15 September 2007 (index date 1) and 15 March 2008 (index date 2).SettingPrimary care settings in a large Canadian metropolitan area.ParticipantsIndividuals with asthma and provincial health insurance primary and secondary outcome measures: well controlled asthma.Results16 803 eligible individuals were identified on index date 1, and 18 103 on index date 2. The distribution of recommendation categories was similar on both index dates. 94% were classified as well controlled and 7% as not well controlled. Among well-controlled individuals, the largest proportion was in the maintain treatment category (63.8%), followed by the maintain/decrease treatment category (28.2%) and the decrease treatment category (2.7%). Almost all individuals who were not well controlled had the recommendation to increase treatment (88%) with a small proportion in the refer category (1%).ConclusionsThe ADSS was able to identify subgroups of patients from an administrative database that could benefit from a medication review and possible change. Decision support systems linked to an administrative database can be used to identify individuals with uncontrolled asthma or prescriptions that deviate from recommended treatment. When connected to the point of care, this can provide an opportunity for physicians to intervene early.

Project description:BACKGROUND:Health research has scientific, social and political impacts. To achieve such impacts, several institutions need to participate; however, health research funding institutions are seldom nominated in the literature as essential players. The attention they have received has so far focused mainly on their role in knowledge translation, informing policy-making and the need to organise health research systems. In this article, we will focus solely on the governance of national health research funding institutions. Our objectives are to identify the main functions of governance for such institutions and actionable governance functions. This research should be useful in several ways, including in highlighting, tracking and measuring the governance trends in a given funding institution, and to forestall low-level governance. METHODS:First, we reviewed existing frameworks in the grey literature, selecting seven relevant documents. Second, we developed an integrated framework for health research funding institution governance and management. Third, we extracted actionable information for governance by selecting a mix of North American, European and Asian institutions that had documentation available in English (e.g. annual report, legal status, strategy). RESULTS:The framework contains 13 functions - 5 dedicated to governance (intelligence acquisition, resourcing and instrumentation, relationships management, accountability and performance, and strategy formulation), 3 dedicated to management (priority-setting, financing and knowledge transfer), and 5 dedicated to transversal logics that apply to both governance and management (ethics, transparency, capacity reinforcement, monitoring and evaluation, and public engagement). CONCLUSIONS:Herein, we provide a conceptual contribution for scholars in the field of governance and health research as well as a practical contribution, with actionable functions for high-level managers in charge of the governance of health research funding institutions.

Dataset Information

Governance for clinical decision support: case studies and recommended practices from leading institutions.

Objective

Design

Measurements

Results

Conclusion

Publications

Governance for clinical decision support: case studies and recommended practices from leading institutions.

Similar Datasets

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