Randomized Effectiveness Trial of a Computer-Assisted Intervention to Improve Diabetes Care

Department of Family Medicine, University of Colorado, Denver, Colorado, United States
Diabetes Care (Impact Factor: 8.42). 02/2005; 28(1):33-9. DOI: 10.2337/diacare.28.1.33
Source: PubMed


There is a well-documented gap between diabetes care guidelines and the services received by patients in most health care settings. This report presents 12-month follow-up results from a computer-assisted, patient-centered intervention to improve the level of recommended services patients received from a variety of primary care settings.
A total of 886 patients with type 2 diabetes under the care of 52 primary care physicians participated in the Diabetes Priority Program. Physicians were stratified and randomized to intervention or control conditions and evaluated on two primary outcomes: number of recommended laboratory screenings and recommended patient-centered care activities completed from the National Committee on Quality Assurance/American Diabetes Association Provider Recognition Program (PRP). Secondary outcomes were evaluated using the Problem Areas in Diabetes 2 quality of life scale, lipid and HbA1c levels, and the Patient Health Questionnaire-9 depression scale.
The program was well implemented and significantly improved both the number of laboratory assays and patient-centered aspects of diabetes care patients received compared with those in the control condition. There was overall improvement on secondary outcomes of lipids, HbA1c, quality of life, and depression scores; between-condition differences were not significant.
Staff in small, mixed-payer primary care offices can consistently implement a patient-centered intervention to improve PRP measures of quality of diabetes care. Alternative explanations for why these process improvements did not lead to improved outcomes, and suggested directions for future research are discussed.

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Available from: Alanna Kulchak Rahm
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    • "30 vs. 28 NS > 10.1% 8 vs. 12 NS SBP < 135 mm Hg 58 vs. 60 NS DBP < 80 mm Hg 75 vs. 77 NS LDL-cholesterol < 2.5 mmol/L 35 vs. 48 NS 2.5–3.3 mmol/L 34 vs. 23 NS > 3.3 mmol/L 31 vs. 29 NS Process of care Increase mean sum of measures 0 vs. 1.5 0.014 Glasgow et al. 11 (2005) "
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    ABSTRACT: Purpose: Computerized decision support systems (CDSSs) are often part of a multifaceted intervention to improve diabetes care. We reviewed the effects of CDSSs alone or in combination with other supportive tools in primary care for type 2 diabetes mellitus (T2DM). Materials and methods: A systematic literature search was conducted for January 1990-July 2011 in PubMed, Embase, and the Cochrane Database and by consulting reference lists. Randomized controlled trials (RCTs) in general practice were selected if the interventions consisted of a CDSS alone or combined with a reminder system and/or feedback on performance and/or case management. The intervention had to be compared with usual care. Two pairs of reviewers independently abstracted all available data. The data were categorized by process of care and patient outcome measures. Results: Twenty RCTs met inclusion criteria. In 14 studies a CDSS was combined with another intervention. Two studies were left out of the analysis because of low quality. Four studies with a CDSS alone and four studies with a CDSS and reminders showed improvements of the process of care. CDSS with feedback on performance with or without reminders improved the process of care (one study) and patient outcome (two studies). CDSS with case management improved patient outcome (two studies). CDSS with reminders, feedback on performance, and case management improved both patient outcome and the process of care (two studies). Conclusions: CDSSs used by healthcare providers in primary T2DM care are effective in improving the process of care; adding feedback on performance and/or case management may also improve patient outcome.
    Full-text · Article · Feb 2013 · Diabetes Technology & Therapeutics
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    • "In another study, the authors did not find significant results on changes in cholesterol or HbA1c levels, but they did get significant results on 10 American Diabetes Association standards of care measures--a result they surmise may be related to small sample size and short study duration [12]. In another example, [37] improvements in care processes did not translate into improved surrogate outcomes, possibly because baseline levels were relatively good. There were also some associations between outcomes measured. "
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    ABSTRACT: This systematic review and meta-analysis aims at assessing the composition and performance of care management models evaluated in the last decade and their impact on patient important outcomes. A comprehensive literature search of electronic bibliographic databases was performed to identify care management trials in type 2 diabetes. Random effects meta-analysis was used when feasible to pool outcome measures. Fifty-two studies were eligible. Most commonly reported were surrogate outcomes (such as HbA1c and LDL), followed by process measures (clinic visit or testing frequency). Less frequently reported were quality of life, patient satisfaction, self-care, and healthcare utilization. Most care management modalities were carved out from primary care. Meta-analysis demonstrated a statistically significant but trivial reduction of HbA1c (weighted difference in means -0.21%, 95% confidence interval -0.40 to -0.03, p < .03) and LDL-cholesterol (weighted difference in means -3.38 mg/dL, 95% confidence interval -6.27 to -0.49, p < .02). Most care management programs for patients with type 2 diabetes are 'carved-out', accomplish limited effects on metabolic outcomes, and have unknown effects on patient important outcomes. Comparative effectiveness research of different models of care management is needed to inform the design of medical homes for patients with chronic conditions.
    Full-text · Article · Mar 2012 · BMC Health Services Research
    • "Further study is warranted to validate the results from this study with larger samples that are more representative of the US chronic disease population. The second limitation is the unexplained reasons for the 41% attrition rate in the intervention group, a level higher than the 12%–25% reported for controlled trials involving Web-based interventions[44,46,50]. The six withdrawals and 24 dropouts may have been participants who experienced difficulties using the applications or had expectations for the Web-based intervention that were not met. "
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    ABSTRACT: With almost one-half of Americans projected to have at least one chronic condition before 2020, a vital role of the health care system is to develop informed, engaged individuals who are effective self-managers of their health. Self-management interventions (SMIs) delivered face-to-face or by telephone (traditional SMIs) are associated with improved self-management knowledge, skills, and self-efficacy, which are expressed by the composite construct of patient activation, a predictor of health outcomes. Web-based interventions to support self-management across the spectrum of chronic diseases have the potential to reach a broader population of patients for extended periods than do traditional SMIs. However, evidence of the effectiveness of Web-based interventions on patient activation is sparse. High-quality studies featuring controlled comparisons of patients with different chronic conditions are needed to explore the interaction of Web-based interventions and patient activation. To explore the effect of a Web-based intervention on the patient activation levels of patients with chronic health conditions, measured as attitudes toward knowledge, skills, and confidence in self-managing health. For this 12-week study, prospective participants were selected from the patient panel of a regional health care system in the United States. The 201 eligible participants were randomly assigned to two groups. Intervention group participants had access to MyHealth Online, a patient portal featuring interactive health applications accessible via the Internet. Control participants had access to a health education website featuring various topics. Patient activation was assessed pre- and posttest using the 13-item patient activation measure. Parametric statistical models (t test, analysis of variance, analysis of covariance) were applied to draw inferences. The Web-based intervention demonstrated a positive and significant effect on the patient activation levels of participants in the intervention group. A significant difference in posttest patient activation scores was found between the two groups (F(1,123) = 4.438, P = .04, r = .196). Patients starting at the most advanced development of patient activation (stage 4) in the intervention group did not demonstrate significant change compared with participants beginning at earlier stages. To our knowledge, this is the first study to measure change in patient activation when a Web-based intervention is used by patients living with different chronic conditions. Results suggest that Web-based interventions increase patient activation and have the potential to enhance the self-management capabilities of the growing population of chronically ill people. Activated patients are more likely to adhere to recommended health care practices, which in turn leads to improved health outcomes. Designing Web-based interventions to target a specific stage of patient activation may optimize their effectiveness. For Web-based interventions to reach their potential as a key component of chronic disease management, evidence is needed that this technology produces benefits for a sustained period among a diverse population.
    No preview · Article · Feb 2012 · Journal of Medical Internet Research
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