Information system support as a critical success factor for chronic disease management: Necessary but not sufficient
Introduction
Most primary care physicians in the Victoria, British Columbia, the city that first instituted a School of Health Information Science in Canada over 20 years ago, continue to provide clinical care to their chronic disease patients largely without the benefit of computerized support. In 2003, three developments in informatics matured and converged in a collaborative of 30 physicians who embraced the use of informatics for chronic disease management (CDM): (1) a secure and accessible web-based environment, (2) evidence-based decision support tools, and (3) quality improvement (QI) processes. The results were measurable improvements in their practice within a year: the proportion of diabetic patients with hemoglobin A1c blood levels under 8% (indicating good blood sugar control) rose from 62% to 88%; the proportion with lipids meeting target values increased to from 71% to 83%; and a triple index for diabetics management comprised of controlled blood glucose, blood pressure and cholesterol increased from 18.6% to 37.6%. This latter compares favorably to published rates of 7.3% (95% confidence interval, 2.8–11.9%) of adults with diabetes meeting triple index recommendations in the 1999–2000 US National Health and Nutrition Examination Survey (NHANES) [1].
This CDM collaborative won the 2004 Canadian Annual 3M Health Care Quality Team Award for results-oriented projects “that show evidence of sustainable improvements in programs and services achieved through quality teamwork” [2]. The developers of the Collaborative's web-based “CDM toolkit” won the Innovation and Excellence award at the Strategies for Public Sector Transformation Conference for 2004 [3]. Use of the CDM toolkit continues to diffuse throughout British Columbia.
Informatics researchers from the University of Victoria, School of Health Information Science conducted a critical success factor (CSF) analysis to understand how this achievement can be reproduced in other jurisdictions. The need for emulation is great. Research has shown that patients with chronic conditions receive only about 55% of the care recommended on the basis of the best available research evidence [4].
This is particularly problematic for diabetes because it has long been recognized that intensive treatment of diabetes decreases complications like blindness, amputation and kidney failure that are associated with heavy burden of illness and major care costs [5]. Also there is growing recognition of the burden of illness in diabetics related to cardiovascular disease [6]. This paper presents our findings of the determinants of implementation success.
Section snippets
Methods
Qualitative interview-based narratives, mapping and analysis of texts and observation of CDM collaborative meetings were used to understand how knowledge (evidence) was successfully translated into project policy and physician practice in CDM.
Results
Seven components of direct CSFs were identified following coding of 325 passages. These were: project management (21), information and communication technology (56), health delivery system (46), working partnerships (12), funding (48) and models (39), and a number of indirect factors or attributes of the direct CSFs that influence QI (51). The factors are not entirely mutually exclusive categories. How the components emerged as themes in the data is depicted in Fig. 1.
The quality improvement
Conclusion and implications
This study identified a framework of factors critical to the successful implementation of a technology-enabled primary care physician CDM collaboration. The strength and applicability of the case study analysis we report in this paper does not seek to establish impact. The physician collaborative had already demonstrated improved practice quantitatively against indicators obtained from evidence-based guidelines by goal setting and monitoring performance using decision support tools. In this
Acknowledgements
The Canadian Institute for Health Research funded University of Victoria researchers through their Knowledge Translation Fund. The Primary Health Care Transition Fund, the BC Ministry of Health and Vancouver Island Health Authority supported the CDM collaborative.
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