OBJECTIVE: Population-level strategies to organize and deliver care may improve diabetes management. We conducted a multiclinic controlled trial of population management in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: We created diabetic patient registries (n = 3,079) for four primary care clinics within a single academic health center. In the intervention clinic (n = 898), a nurse practitioner used novel clinical software (PopMan) to identify patients on a weekly basis with outlying values for visit and testing intervals and last measured levels of HbA1c, LDL cholesterol, and blood pressure. For these patients, the nurse practitioner e-mailed a concise patient-specific summary of evidence-based management suggestions directly to primary care providers (PCPs). Population changes in risk factor testing, medication prescription, and risk factor levels from baseline (1 January 2000 to 31 August 2001) to follow-up (1 December 2001 to 31 July 2003) were compared with the three usual-care control clinics (n = 2,181). RESULTS: Patients had a mean age of 65 years, were mostly white (81%), and the majority were insured by Medicare/Medicaid (62%). From baseline to follow-up, the increase in proportion of patients tested for HbA1c (P = 0.004) and LDL cholesterol (P < 0.001) was greater in the intervention than control sites. Improvements in diabetes-related medication prescription and levels of HbA1c, LDL cholesterol, and blood pressure in the intervention clinic were balanced by similar improvements in the control sites. CONCLUSIONS: Population-level clinical registries combined with summarized recommendations to PCPs had a modest effect on management. The intervention was limited by good overall quality of care at baseline and temporal improvements in all control clinics. It is unknown whether this intervention would have had greater impact in clinical settings with lower overall quality. Further research into more effective methods of translating population registry information into action is required. Copyright 2004 American Diabetes Association
OBJECTIVE: Population-level strategies to organize and deliver care may improve diabetes management. We conducted a multiclinic controlled trial of population management in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: We created diabeticpatient registries (n = 3,079) for four primary care clinics within a single academic health center. In the intervention clinic (n = 898), a nurse practitioner used novel clinical software (PopMan) to identify patients on a weekly basis with outlying values for visit and testing intervals and last measured levels of HbA1c, LDL cholesterol, and blood pressure. For these patients, the nurse practitioner e-mailed a concise patient-specific summary of evidence-based management suggestions directly to primary care providers (PCPs). Population changes in risk factor testing, medication prescription, and risk factor levels from baseline (1 January 2000 to 31 August 2001) to follow-up (1 December 2001 to 31 July 2003) were compared with the three usual-care control clinics (n = 2,181). RESULTS:Patients had a mean age of 65 years, were mostly white (81%), and the majority were insured by Medicare/Medicaid (62%). From baseline to follow-up, the increase in proportion of patients tested for HbA1c (P = 0.004) and LDL cholesterol (P < 0.001) was greater in the intervention than control sites. Improvements in diabetes-related medication prescription and levels of HbA1c, LDL cholesterol, and blood pressure in the intervention clinic were balanced by similar improvements in the control sites. CONCLUSIONS: Population-level clinical registries combined with summarized recommendations to PCPs had a modest effect on management. The intervention was limited by good overall quality of care at baseline and temporal improvements in all control clinics. It is unknown whether this intervention would have had greater impact in clinical settings with lower overall quality. Further research into more effective methods of translating population registry information into action is required. Copyright 2004 American Diabetes Association
Authors: Utibe R Essien; Wei He; Alaka Ray; Yuchiao Chang; Jonathan R Abraham; Daniel E Singer; Steven J Atlas Journal: J Gen Intern Med Date: 2019-04-08 Impact factor: 5.128
Authors: Rebecca Hanratty; Raymond O Estacio; L Miriam Dickinson; Vijayalaxmi Chandramouli; John F Steiner; Edward P Havranek Journal: J Health Care Poor Underserved Date: 2008-05