Evaluating Diabetes Outcomes and Costs Within an Ambulatory Setting: A Strategic Approach Utilizing a Clinical Decision Support System

Diabetes affects 22.3 million people in the United States.1 It is a major cause of heart disease and stroke and is the seventh leading cause of death.2 Patients with diabetes are at two to four times greater risk of myocardial infarction (MI) than those without diabetes, and diabetes is the primary reason for renal failure, blindness, and nontraumatic limb amputations.3 Preventive care practices can reduce the development of severe vision loss by 50–60%, reduce foot amputations by 45–85%, and lower blood pressure to reduce proteinuria, a risk factor for developing kidney disease, by ~ 35%.2 Despite evidence that complications related to diabetes are preventable,4,5 only 52% of individuals with diabetes meet guidelines targeting an A1C of < 7.0%, and only 18% meet combined glycemic, lipid, and blood pressure goals.6 In addition to significant morbidity, diabetes has a substantial financial impact. Medical expenses for people with diabetes are more than two times higher than for those without diabetes.2 Total national health care and related costs for the treatment of all people with diabetes total ~ $245 billion.1 Complications from diabetes, such as chronic kidney disease, can cost health care organizations $33 billion per year.2 Most diabetes care is provided in the community in the primary care setting,3 and diabetes is the fourth most frequent reason for ambulatory physician visits.7 A gap exists between optimal and actual care, constituting a wide “quality chasm,”8 which underscores the need for innovative approaches to change the current practice of diabetes care. Clinical decision support systems (CDSSs) have been suggested as a viable solution to these pressing issues.9 CDSSs have been defined as systems providing an automated process for comparing patient-specific characteristics against a computerized knowledge base, with resulting recommendations or …

[1]  A D Oxman,et al.  No magic bullets: a systematic review of 102 trials of interventions to improve professional practice. , 1995, CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne.

[2]  Patient Care Outcomes of the SEAHEC Improving Performance in Practice (IPIP) Experience , 2013, The Journal of the American Board of Family Medicine.

[3]  Vicente Plaza,et al.  Coste-efectividad de una intervención basada en las recomendaciones de la Global INitiative for Asthma (GINA), mediante un sistema informatizado de apoyo a la decisión clínica: un ensayo con aleatorización de médicos , 2005 .

[4]  D. Rodbard,et al.  Rapid improvement of glycemic control in type 2 diabetes using weekly intensive multifactorial interventions: structured glucose monitoring, patient education, and adjustment of therapy-a randomized controlled trial. , 2011, Diabetes technology & therapeutics.

[5]  P. Hogan,et al.  Economic Costs of Diabetes in the U , 2013 .

[6]  S. Boren,et al.  The use and effectiveness of electronic clinical decision support tools in the ambulatory/primary care setting: a systematic review of the literature. , 2008, Informatics in primary care.

[7]  F. Hu,et al.  Trends in cardiovascular health metrics and associations with all-cause and CVD mortality among US adults. , 2012, JAMA.

[8]  D. Hoover,et al.  Glycemic control in HIV-infected patients with diabetes mellitus and rates of meeting American Diabetes Association management guidelines. , 2011, AIDS patient care and STDs.

[9]  Fernando García-Alonso,et al.  [Cost-effectiveness of an intervention based on the Global INitiative for Asthma (GINA) recommendations using a computerized clinical decision support system: a physicians randomized trial]. , 2005, Medicina clinica.

[10]  Julie M. Fiskio,et al.  Technology Evaluation: A Randomized Trial of Electronic Clinical Reminders to Improve Quality of Care for Diabetes and Coronary Artery Disease , 2005, J. Am. Medical Informatics Assoc..

[11]  L. Pezzin,et al.  Just-in-time evidence-based e-mail "reminders" in home health care: impact on patient outcomes. , 2005, Health services research.

[12]  Bruce Fireman,et al.  Can disease management reduce health care costs by improving quality? , 2004, Health affairs.

[13]  G. Rutten,et al.  Combined Task Delegation, Computerized Decision Support, and Feedback Improve Cardiovascular Risk for Type 2 Diabetic Patients , 2008, Diabetes Care.

[14]  D. Robbins,et al.  Impact of computer-generated personalized goals on HbA(1c). , 2002, Diabetes care.

[15]  V. Beral,et al.  The 21st century hazards of smoking and benefits of stopping: a prospective study of one million women in the UK , 2013, BDJ.

[16]  Patrick J O'Connor,et al.  Impact of an Electronic Medical Record on Diabetes Quality of Care , 2005, The Annals of Family Medicine.

[17]  William H. Herman,et al.  The Economic Costs of Diabetes: Is It Time for a New Treatment Paradigm? , 2013, Diabetes Care.

[18]  J. Leonardi-Bee,et al.  Blood Pressure Reduction and Secondary Prevention of Stroke and Other Vascular Events: A Systematic Review , 2003, Stroke.

[19]  C. Quinn,et al.  WellDoc mobile diabetes management randomized controlled trial: change in clinical and behavioral outcomes and patient and physician satisfaction. , 2008, Diabetes technology & therapeutics.

[20]  S. Saydah,et al.  The Prevalence of Meeting A1C, Blood Pressure, and LDL Goals Among People With Diabetes, 1988–2010 , 2013, Diabetes Care.

[21]  Peter J. Hannan,et al.  Improving Diabetes Care in Practice , 2008, Diabetes Care.

[22]  A. Dobson,et al.  Infrastructure for large‐scale quality‐improvement projects: Early lessons from North Carolina improving performance in practice , 2010, The Journal of continuing education in the health professions.

[23]  K. Peterson,et al.  Strategies to improve diabetes care delivery. , 1998, The Journal of family practice.

[24]  Ronald Brazg,et al.  Performance of a new test strip for freestyle blood glucose monitoring systems. , 2011, Diabetes technology & therapeutics.

[25]  Karim Keshavjee,et al.  Individualized electronic decision support and reminders to improve diabetes care in the community: COMPETE II randomized trial , 2009, Canadian Medical Association Journal.

[26]  G. Rutten,et al.  Cost-Effectiveness of the Diabetes Care Protocol, a Multifaceted Computerized Decision Support Diabetes Management Intervention That Reduces Cardiovascular Risk , 2009, Diabetes Care.

[27]  David M Nathan,et al.  A controlled trial of web-based diabetes disease management: the MGH diabetes primary care improvement project. , 2003, Diabetes care.

[28]  Plamen Nikolov,et al.  Economic Costs of Diabetes in the U.S. in 2002 , 2003, Diabetes care.

[29]  J. Maurice New WHO plan targets the demise of sleeping sickness , 2013, The Lancet.

[30]  W. Herman,et al.  Improving diabetes processes of care in managed care. , 2003, Diabetes care.

[31]  P. Basch Quality of health care delivered to adults in the United States. , 2003, New England Journal of Medicine.

[32]  C. McDonald,et al.  Effects of computerized guidelines for managing heart disease in primary care , 2003, Journal of General Internal Medicine.

[33]  Richard W Grant,et al.  A controlled trial of population management: diabetes mellitus: putting evidence into practice (DM-PEP). , 2004, Diabetes care.

[34]  K. Shojania,et al.  Effects of quality improvement strategies for type 2 diabetes on glycemic control: a meta-regression analysis. , 2006, JAMA.

[35]  Beth C Bock,et al.  Clinic-based support to help overweight patients with type 2 diabetes increase physical activity and lose weight. , 2008, Archives of internal medicine.