Feasibility and impact of an evidence-based electronic decision support system for diabetes care in family medicine: protocol for a cluster randomized controlled trial

Implementation Science

Bert Aertgeerts²  Robert Vander Stichele¹  Dirk Ramaekers³  Stijn Van de Velde²  Annemie Heselmans² 

[1] Department of Pharmacology, Universiteit Gent, De Pintelaan 185, Ghent 9000, Belgium;EBMPracticeNet, Kapucijnenvoer 33 blok j, Leuven 3000, Belgium;ZNA Hospital Network Antwerp, Leopoldstraat 26, Antwerp 2000, Belgium

关键词: Guideline implementation;    Electronic health records;    Point-of-care systems;    Clinical;    Decision support systems;    Diabetes mellitus;   

Others  :  813475
DOI  :  10.1186/1748-5908-8-83

 received in 2013-06-26, accepted in 2013-07-31,  发布年份 2013

【 摘 要 】

Background

In Belgium, the construction of the national electronic point-of-care information service, EBMPracticeNet, was initiated in 2011 to optimize quality of care by promoting evidence-based decision-making. The collaboration of the government, healthcare providers, Evidence-Based Medicine (EBM) partners, and vendors of Electronic Health Records (EHR) is unique to this project. All Belgian healthcare professionals get free access to an up-to-date database of validated Belgian and nearly 1,000 international guidelines, incorporated in a portal that also provides EBM information from sources other than guidelines, including computerized clinical decision support that is integrated in the EHRs.

The EBMeDS system is the electronic evidence-based decision support system of EBMPracticeNet. The EBMeDS system covers all clinical areas of diseases and could play a crucial role in response to the emerging challenge posed by chronic conditions. Diabetes was chosen as the analysis topic of interest. The objective of this study is to assess the effectiveness of EBMeDS use in improving diabetes care. This objective will be enhanced by a formal process evaluation to provide crucial information on the feasibility of using the system in daily Belgian family medicine.

Methods

The study is a cluster-randomized trial with before/after measurements conducted in Belgian family medicine. Physicians’ practices will be randomly assigned to the intervention or control group in a 1:1 ratio, to receive either the EBMeDS reminders or to follow the usual care process. Randomization will be performed by a statistical consultant with an electronic random list generator, anonymously for the researchers. The follow-up period of the study will be 12 months with interim analysis points at 3, 6 and 9 months. Primary outcome is the one-year pre- to post-implementation change in HbA1c. Patients will not be informed about the intervention. Data analysts will be kept blinded to the allocation.

Discussion

The knowledge obtained in this study will be useful for further integration in other Belgian software packages. Users’ perceptions and process evaluation will provide information for improving the feasibility of the system.

Trial registration

The trial is registered with the ClinicalTrials.gov registry: NCT01830569.

【 授权许可】

   
2013 Heselmans et al.; licensee BioMed Central Ltd.

【 参考文献 】

• [1]Garg AX, Adhikari NK, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, Sam J, Haynes RB: Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 2005, 293(10):1223-38.
• [2]Eccles MP, Grimshaw JM: Selecting, presenting and delivering clinical guidelines: are there any “magic bullets”? Med J Aust 2004, 180(6 Suppl):S52-S54.
• [3]Johnston ME, Langton KB, Haynes RB, Mathieu A: Effects of computer-based clinical decision support systems on clinician performance and patient outcome. A critical appraisal of research. Ann Intern Med 1994, 120(2):135-142.
• [4]Shea S, DuMouchel W, Bahamonde L: A meta-analysis of 16 randomized controlled trials to evaluate computer-based clinical reminder systems for preventive care in the ambulatory setting. J Am Med Inform Assoc 1996, 3(6):399-409.
• [5]Roshanov PS, Misra S, Gerstein HC, Garg AX, Sebaldt RJ, Mackay JA, Weise-Kelly L, Navarro T, Wilczynski NL, Haynes RB, CCDSS Systematic Review Team: Computerized clinical decision support systems for chronic disease management: a decision-maker-researcher partnership systematic review. Implement Sci 2011, 6:92. BioMed Central Full Text
• [6]Sahota N, Lloyd R, Ramakrishna A, Mackay JA, Prorok JC, Weise-Kelly L, Navarro T, Wilczynski NL, Haynes RB, CCDSS Systematic Review Team: Computerized clinical decision support systems for acute care management: a decision-maker-researcher partnership systematic review of effects on process of care and patient outcomes. Implement Sci 2011, 6:91. BioMed Central Full Text
• [7]Jeffery R, Iserman E, Haynes RB, CDSS Systematic Review Team: Can computerized clinical decision support systems improve diabetes management? A systematic review and meta-analysis. Diabet Med 2013, 30(6):739-745.
• [8]Heselmans A, Van de Velde S, Donceel P, Aertgeerts B, Ramaekers D: Effectiveness of electronic guideline-based implementation systems in ambulatory care settings - a systematic review. Implement Sci 2009, 4:82. BioMed Central Full Text
• [9]Shojania KG, Jennings A, Mayhew A, Ramsay C, Eccles M, Grimshaw J: Effect of point-of-care computer reminders on physician behaviour: a systematic review. CMAJ 2010, 182(5):E216-E225.
• [10]Van de Velde S, Vander Stichele R, Fauquert B, Geens S, Heselmans A, Ramaekers D, Kunnamo I, Aertgeerts B, On behalf of EBMPracticeNET: EBMPracticeNet: A Bilingual National Electronic Point-Of-Care Project For Retrieval Of Evidence-Based Clinical Guideline Information And Decision Support. JMIR Res Protoc 2013, 2(2):e23.
• [11]EBMeDS: Context-Sensitive Guidance At the Point of Care. http://www.ebmeds.org webcite
• [12]Kawamoto K, Houlihan CA, Balas EA, Lobach DF: Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ 2005, 330(7494):765.
• [13]Dorr D, Bonner LM, Cohen AN, Shoai RS, Perrin R, Chaney E, Young AS: Informatics systems to promote improved care for chronic illness: a literature review. J Am Med Inform Assoc 2007, 14(2):156-163.
• [14]Heselmans A, Aertgeerts B, Donceel P, Geens S, Van de Velde S, Ramaekers D: Family physicians’ perceptions and use of electronic clinical decision support during the first year of implementation. J Med Syst 2012, 36(6):3677-3684.
• [15]Coffey R, Matthews T, McDermott K: Diabetes care quality improvement: a resource guide for state action. Rockville MD: Agency for Healthcare Research and Quality; 2004.
• [16]Holbrook A, Thabane L, Keshavjee K, Dolovich L, Bernstein B, Chan D, Troyan S, Foster G, Gerstein H: COMPETE II Investigators: Individualized electronic decision support and reminders to improve diabetes care in the community: COMPETE II randomized trial. CMAJ 2009, 181(1–2):37-44.
• [17]Shojania KG, McDonald KM, Wachter RM, Owens DK: Closing the quality gap: a critical analysis of quality improvement strategies. In Series overview and methodology. Rockville MD: Agency for Healthcare Research and Quality US; 2004. [Technical Reviews, No. 9.1]
• [18]Mathieu C, Nobels F, Peeters G: De kwaliteit en de organisatie van type 2 diabeteszorg. Brussel: Federaal Kenniscentrum voor de gezondheidszorg (KCE). KCE reports 2006., 27ARef. D/2006/10.273/07
• [19]Tricco AC, Ivers NM, Grimshaw JM, Moher D, Turner L, Galipeau J, Halperin I, Vachon B, Ramsay T, Manns B, Tonelli M, Shojania K: Effectiveness of quality improvement strategies on the management of diabetes: a systematic review and meta-analysis. Lancet 2012, 379(9833):2252-2261.
• [20]Wens J, Sunaert P, Nobels F, Feyen L, Van Crombrugge P, Bastiaens H, Van Royen P: Diabetes Mellitus Type 2. Domus Medica; 2009.
• [21]Endocrinologen UZ L, Hart Leuven RZH, Imelda Ziekenhuis B, Diest AZ, RZ Tienen RZ: Sint-Trudo en het Onderzoeksteam Diabetesproject Leuven, ACHG KULeuven: Zorgtraject diabetes. Regionaal behandelingsplan Regio Groot-Leuven. 2011.
• [22]Hulscher ME, Laurant MG, Grol RP: Process evaluation on quality improvement interventions. Qual Saf Health Care 2003, 12(1):40-46.
• [23]Wu L, Forbes A, Griffiths P, Milligan P, While A: Telephone follow-up to improve glycaemic control in patients with Type 2 diabetes: systematic review and meta-analysis of controlled trials. Diabet Med 2010, 27(11):1217-1225.
• [24]Liang X, Wang Q, Yang X, Cao J, Chen J, Mo X, Huang J, Wang L, Gu D: Effect of mobile phone intervention for diabetes on glycaemic control: a meta-analysis. Diabet Med 2011, 28(4):455-463.
• [25]Cleveringa FG, Gorter KJ, Van den Donk M, Rutten GE: Combined task delegation, computerized decision support, and feedback improve cardiovascular risk for type 2 diabetic patients: a cluster randomized trial in primary care. Diabetes Care 2008, 31(12):2273-2275.
• [26]Campbell MK, Piaggio G, Elbourne DR, Altman DG: Consort 2010 statement: extension to cluster randomised trials. BMJ 2012, 345:e5661.
• [27]Norman G, Monteiro S, Salama S: Sample size calculations: should the emperor’s clothes be off the peg or made to measure? BMJ 2012, 345:e5278.