1. Coordination of Care, Information Support, and Quality of Diabetes Care : A STARNet Study Michael L. Parchman, MD, MPH Raquel L. Romero, MD Jacqueline A. Pugh, MD STAR Net

2. Type 2 Diabetes A complex chronic illness Primary Care Encounters characterized by many competing demands: –Additional chronic illnesses per patient 4.6 (SD 2.3) –Chronic medications per patient was 6.4 (SD 3.1) –2.2 (S.D. 1.8) medication prescriptions were provided during the visit. –25% of all visits there was a change in medications. –Length of each visit was 17.5 (S.D. 9.1) minutes. –An average of 15.5 (S.D. 7.7) topics were discussed per visit, for an average of 1.1 minutes per topic.

3. Coordination of Care “Availability of information about prior problems and services and the recognition of that information as it bears on needs for current services.” -Starfield B.

4. The Chronic Care Model (CCM)

5. Clinical Information Support “Timely, useful information about individual patients and populations of patients with diabetes is a critical feature of effective programs, especially those that employ population-based approaches.” -Intro to section on CIS in the Assessment of Chronic Illness Care Survey

6. Objective To determine if availability of information is associated with coordination of care, and if coordination of care is associated with quality of care for patients with type 2 diabetes in small autonomous primary care clinics.

7. Methods 20 Primary Care Clinics –South Texas Ambulatory Research Network (STARNet) –“Snowball” recruitment –Diversity Solo (single-handed) practices (n=11) Group practices (n=3, physicians=10) Community Health Center (n=1; physician=1) VA Primary Care clinics (n=2; physicians=11) City/county health clinics (n=3; physicians =12)

8. Methods 30-32 consecutive adult patients presenting with an established dx of type 2 DM Data collection –Patient survey (demographics, Components of Primary Care Instrument, CPCI) –Chart Abstraction (6 process measures of quality of care) –Clinician survey (Assessing Chronic Illness Care, ACIC, Survey)

9. CPCI: Coordination of Care “I want one doctor to coordinate all of the health care I receive” “This doctor keeps track of all my health care” “This doctor always follows up on a problem I’ve had, either at the next visit or by phone” “This doctor communicates with other health care providers I see” “This doctor does not always know about care I have received at other places”

10. ACIC Survey A validated measure of the presence of the elements of the CCM in primary care settings (Bonomi AE, HSR 2002) –Organizational Support –Community Linkages –Self Management Support –Decision Support –Delivery System Design –Clinical Information Systems

11. Clinical Information System A registry of patients with diabetes Reminders to providers at time of visits Feedback about diabetes guideline adherence Information about sub-groups of patients needing services Patient treatment plans established collaboratively

12. Quality of Care In the past 12 months: –BP measured twice –A1c once –Urine MA once –Lipids once –Foot exam once –Eye exam referral once 1 point for each indicator (possible range of scores 0 to 6)

13. HLM Model Level-1 Model: Patient Quality of Care Score = B0 + B1*(AGE) + B2*(SEX) + B3*(NUMDIAG) + B4*(VIS12MON) + B5*(HISPANIC) + B6*(HSGRAD) + B7*(COORDSCO) + R Level-2 Model: Clinic B0 = G00 + G01*(EMR) + G02*(CIS_MEAN) + U0 B1 = G10 + U1 B2 = G20 + U2 B3 = G30 + U3 B4 = G40 + U4 B5 = G50 + U5 B6 = G60 + U6 B7 = G70 + U7

14. Results Mean (SD) or % (n=618) Age58.6 (12.9) % Male51.5 % Hispanic57.3 % High School Graduate64.7 # Visits prior 12 months6.4 (3.9) Number of Dx4.6(2.3) Coordination of Care Score5.5 (0.8) Quality of Care Score4.4 (1.4)

15. EMR 6 of 20 clinics with comprehensive EMR –Visit notes –Lab data –Consulting reports –Etc. No difference in CIS score between clinics with and without an EMR

16. HLM Results Final estimation of fixed effects (with robust standard errors): OUTCOME: Quality of Care Score ---------------------------------------------------------------------------------------------------------------------- Standard Approx. Fixed Effect Coefficient Error T-ratio d.f. P-value ---------------------------------------------------------------------------------------------------------------------- For INTRCPT1, B0 INTRCPT2, G00 3.830.29 13.0 17 0.000 EMR, G01 0.78 0.24 3.26 17 0.005 CIS_MEAN, G02 0.11 0.04 3.07 17 0.007 For AGE slope, B1 INTRCPT2, G10 0.01 0.004 1.74 19 0.097 For SEX slope, B2 INTRCPT2, G20 0.02 0.10 0.23 19 0.816 For NUMDIAG slope, B3 INTRCPT2, G30 -0.02 0.03 -0.84 19 0.411 For VIS12MON slope, B4 INTRCPT2, G40 0.06 0.01 4.45 19 0.000 For HISPANIC slope, B5 INTRCPT2, G50 0.29 0.09 3.34 19 0.004 For HSGRAD slope, B6 INTRCPT2, G60 0.20 0.13 1.47 19 0.158 For COORDSCO slope, B7 INTRCPT2, G70 0.15 0.06 2.41 19 0.027 --------------------------------------------------------------------------------------------

17. Results The mean Quality of Care Score was: –0.78 higher in clinics with an EMR –0.14 higher for every 1 point increase in CIS score (independent of presence of EMR) A 1 point increase in coordination of care score was associated with a 0.15 increase in quality of care score ICC for quality of care score was 0.32: approximately 1/3 of variation in quality of diabetes care at clinic level, not patient level.

18. Conclusions Quality of Diabetes care is related to structural elements within the primary care clinic: EMR and clinical information systems Patient perception of coordination of care is associated with process indicators of quality over the prior 12 months. Effective and efficient methods for helping small autonomous primary care clinics improve coordination of care and information systems are needed

19. Acknowledgments Funding for this study was provided by AHRQ, Grant # K08 HS013008-02; HRSA Grant # 5D12HP00008-02; and the South Texas Health Research Center. Special thanks to the physicians and office staff of the South Texas Ambulatory Research Network (STARNet) Contact email: parchman@uthscsa.edu