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EMR Use is Not Associated with Better Diabetes Care Patrick J OConnor, MD, MPH Stephen E Asche, MA A Lauren Crain, PhD Leif I Solberg, MD William A Rush,

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Presentation on theme: "EMR Use is Not Associated with Better Diabetes Care Patrick J OConnor, MD, MPH Stephen E Asche, MA A Lauren Crain, PhD Leif I Solberg, MD William A Rush,"— Presentation transcript:

1 EMR Use is Not Associated with Better Diabetes Care Patrick J OConnor, MD, MPH Stephen E Asche, MA A Lauren Crain, PhD Leif I Solberg, MD William A Rush, PhD Robin R Whitebird, PhD, MSW

2 Electronic medical record (EMR) High expectations that EMRs will improve care quality since 1980; IOM reports 1992 $10+ billion spent in US in last 5 years 400 EMR vendors Healthcare Information and Management Systems Society Office EMRs now used by about 35% of physicians nationally

3 EMR Core Functions – IOM, 2003 health information and data results management order entry decision support electronic communication patient support administrative processes reporting, population health mgmt

4 Research Question Do patients receiving care at clinics using EMRs have better quality of diabetes care, compared to patients receiving care at clinics not using EMRs?

5 Project Quest Multi-site 3 year study involving 19 medical groups, 85 clinics, 700 providers and 7865 adult DM or CHD patients Designed to identify patient, physician, clinic and group factors related to quality of care for adults with diabetes or heart disease Funded by Agency for Healthcare Research and Quality (AHRQ)

6 Data Sources Administrative data Diabetes determination (based on diagnosis & pharmacy codes), limited demographic information Patient survey (2001) Socio-demographic information Clinic medical director survey (2001) Report on use of EMR Other clinic variables Chart audit (2000, 2001, 2002) HbA1c, LDL, SBP (last in each year)

7 Project Quest Diabetes Sample Diabetes patients in 1999 (based on ICD-9 and pharmacy codes), N=4802 HealthPartners insurance, 19+ years old in 1999 Returned patient survey, N=2838 Self-report confirmed having diabetes, N=2754 Consented to chart audit, N=2019 Linked to a clinic in which a clinic medical director completed a survey N=1491 DM patients from N=60 clinics

8 EMR item Does your clinic use computerized medical record systems that include provider entry of data 60 clinic medical directors responded 14 (23.3%) replied yes n=441 patients in EMR clinics n=1050 patients in non-EMR clinics

9 Diabetes patients at clinics with and without an EMR EMR (n=441) Non-EMR (n=1050) Age (mean)*64.260.7 Female (%)*51.543.8 Duration DM (mean)* 11.510.3 Charlson (mean) 1.61.4 * p <.05

10 Diabetes patients at clinics with and without an EMR EMRNon-EMR A1c (mean, sd) 7.3 (1.21) (n=359) 7.3 (1.34) (n=877) LDL (mean, sd) 101.4 (30.1) (n=246) 101.8 (30.0) (n=680) SBP (mean, sd) 132.5 (17.6) (n=397) 130.8 (17.3) (n=934) Year 2002 clinical values. Bivariate analysis.

11 Multilevel analysis Used MLwiN adjusted treatment, and adjusted time by treatment analysis Used up to 3 clinical values per patient Nested yearly values within person within provider within clinic (clean hierarchy) Predict clinical values, and change in clinical values over time, as a function of EMR Patient covariates: age, sex, education, duration of DM, Charlson score, CHD status, BMI Provider covariate: physician specialty

12 Multilevel analysis: HbA1c and change in HbA1c CoeffSEp Intercept7.31-- EMR present -0.07.11.56 Patient and provider covariates included Time by treatment analysis: LR test p=.14

13 Multilevel analysis: LDL and change in LDL CoeffSEp Intercept106.4-- EMR present 0.11.7.95 Patient and provider covariates included Time by treatment analysis: LR test p=.37

14 Multilevel analysis: SBP and change in SBP CoeffSEp Intercept128.8-- EMR present 1.18.82.15 Patient and provider covariates included Time by treatment analysis: LR test p=.90

15 Conclusions EMR use not associated with better glucose, BP, or lipid control in adults with diabetes

16 Strengths of Study Large number of patients with diabetes Multiple levels of data collection (patient, provider, clinic medical director) Uniform data collection procedures and standards at all clinics Use of hierarchical analytic models to accommodate nested data

17 Potential Limitations Generalizability to other regions or patient populations is uncertain; 60 clinics in one state Observational study precludes causal inference Clinic systems already in place vs. pre-post design No information on 1) EMR features / functionality, 2) extent to which EMR is used, 3) extent to which practitioners are trained to use the EMR Clinic EMR examined in isolation (no other clinic variables considered in same analysis) Some patients link to multiple providers and clinics, but we have simplified the hierarchy to link to one clinic

18 Compare to Other Studies Meigs 02 at Mass General ClinicsEMR increased A1c tests but did not improve A1c level Montori 02 at MayoEMR improved number of A1c tests but did not improve A1c or LDL level OConnor 01 at HPMGEMR use led to more A1c tests, but worse A1c levels Crabtree 06 at NJ clinicsEMR using clinics no better than non-EMR for DM care

19 Implications Anticipated benefits of very expensive EMRs for improving diabetes (and other chronic disease) care have yet to be realized Office systems not yet redesigned to take advantage of EMR potential Physician training to use EMRs not standardized or optimized More research needed if the potential of very expensive EMRs to support better care is to be realized

20 Questions or comments? Patrick OConnor MD MPH HealthPartners Research Foundation Patrick.J.Oconnor@HealthPartnersPatrick.J.Oconnor@HealthPartners. Com

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