Patient Registries and Health Outcomes in Diabetes: A Retrospective Study Nipa Shah, MD1; Fern Webb, PhD1; Liane Hannah, BSH1; Carmen Smotherman, MS2;

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Patient Registries and Health Outcomes in Diabetes: A Retrospective Study Nipa Shah, MD1; Fern Webb, PhD1; Liane Hannah, BSH1; Carmen Smotherman, MS2; Dale Kraemer, PhD2 1Department of Community Health and Family Medicine; 2 Center for Health Equity and Quality Research   Results HgA1c Levels by Visit & Clinic Group Introduction Patients at all primary care clinics, regardless of registry status, had improvements in HgA1c values over time. Patients in clinics with established registries failed to have more improvement in HgA1c values than patients in clinics without registries. HgA1c values for patients at clinics with established registries had higher baseline HgA1c values than patients at clinics without registries. The National Committee for Quality Assurance (NCQA) has: Led regarding patient centered medical home (PCMH) attributes Provided certification to qualifying primary care centers Organizations committed to converting to a PCMH, it is critical to measure PCMH attributes during all phases of implementation in order to evaluate effectiveness of various components. A key attribute for improving quality care is establishing a system that collects patient data via a patient registry. A patient registry is essentially a database that allows proactive management of patients, especially those with chronic diseases. Little is known about the effectiveness of a patient registry as it relates to health outcomes of patients living with diabetes. Propensity-Score-Matched Results To control for potential confounding, a propensity-score-matched analysis was conducted to make registry and non-registry patients as similar as possible. Matched analysis produced lower baseline HgA1c values for patients in registries compared to non-registry patients. Purpose Discussion Baseline characteristics among patients from registry and non-registry clinics     Full sample (n=1038) Propensity-score-matched subsample (n=222) Variable* Registry n=713, (%) Non-registry n=325, (%) Registry (n=111) Hg-A1C 1 7.88 (2.10) 7.43 (1.85) 7.58 (1.69) 7.71 (2.14) Age1 59.7 (12.6) 61.7 (13.6) 61.4 (12.3) 62.4 (13.2) BMI1 33.9 (8.1) 32.4 (7.6) 34.8 (7.6) 33.7 (6.7) Location Urban Core 331 (50) 37 (12) 27 (24) Other 326 (50) 284 (88) 84 (76) Gender Female 400 (56) 183 (56) 59 (53) Male 313 (44) 142 (44) 52 (47) Race Black 427 (65) 92 (29) 54 (49) 53 (48) White 201 (31) 172 (54) 51 (46) 49 (44) 29 (4) 57 (17) 6 (5) 9 (8) Insurance Medicaid/Limited 287 (44) 53 (17) 21 (19) 25 (23) Medicare 277 (42) 165 (51) 65 (59) 60 (54) Private 93 (14) 103 (32) 26 (23) Lipid disorder Yes 612 (86) 257 (79) 94 (85) 92 (83) No 101 (14) 68 (21) 17 (15) 19 (17) Overweight / obese 182 (26) 100 (31) 39 (35) 37 (33) 531 (74) 225 (69) 72 (65) 74 (37) Hypertension 607 (85) 274 (84) 98 (88) 97 (87) 106 (15) 51 (16) 13 (12) 14 (13) The purpose of this retrospective study was to measure hemoglobin A1c (HgA1c) values within a random sample of patients living with diabetes, comparing clinics with an established patient registry (n=6) to those who had not (n=16). Registries are being used in various PCMH settings. This observational study showed that patients getting diabetes care at a clinic with a registry did not have significantly lower HgA1c values than patients in clinics without a diabetes registry. As more practices begin to implement registries, careful evaluation should be given to understand what specific attributes of a registry directly influence and improve the monitoring of HgA1c values. Methods Source Population & Sampling Frame: 22 UF family medicine primary clinics Inclusion/Exclusion Criteria: Diabetic patients ages > 18 years visiting one of the 22 primary care centers between 1/2010 – 12/2011 were given an equal chance of having their records randomly selected for inclusion. Diabetic patients with Type I or gestational diabetes were excluded. Data Collection/Extraction: After IRB approval, trained team members collected data from the existing electronic medical record [EMR] (AllScripts). Registry Status: A clinic was coded as ‘Yes’ if patients with diabetes were entered into an electronic record specifically for tracking purposes. Hemoglobin A1c (HgA1c) values are the primary outcome. Up to the three (3) most recent HgA1c values and testing dates noted in the EMR were recorded. Health Outcomes: Patient health outcomes and socio-demographics collected from AllScripts for randomly selected charts only. Lipid metabolism and hypertension also collected. No patient contact information collected. Data Analysis: Mean (standard deviations) were estimated for age, body mass index [BMI], and frequencies (percentages) for ethnicity/race, gender, insurance type, marital status and location. The primary analysis, using a mixed-model, repeated-measures of analysis of variance (ANOVA) model compared HgA1c values a) between registry and non-registry clinics and b) over time for registry versus non-registry clinics using a mixed-model, repeated-measures analysis of variance (ANOVA) model. Strengths & Limitations Strengths Examining the association between registry use and HgA1c values (disease processes) is a relatively unexplored area. Analyzing data from clinical settings to observe actual processes rather than those reported, while controlling for confounding provides validity to results. Limitations May fail to measure the specific PCMH attribute within registries that influence health outcomes. May require more follow up time to observe significant differences in HgA1c values between registry and non-registry clinics. Conclusions More research is required to fully understand the impact of registries to improve health among patients living with diabetes. More research is also needed to examine other PCMH components and their effectiveness to improve care.   *data are summarized using counts and percentages unless specified otherwise 1Mean (standard deviation) This research was funded by the University of Florida Dean’s Fund Grant [Nipa Shah, MD: PI (2011)]