Leveraging Clinical Databases for Epidemiologic (Population) Research. The Pan Asian Cohort Study (PACS) at the Palo Alto Medical Foundation (PAMF)

Transcription

1 Leveraging Clinical Databases for Epidemiologic (Population) Research The Pan Asian Cohort Study (PACS) at the Palo Alto Medical Foundation (PAMF)

2 Palo Alto Medical Foundation (PAMF) San Francisco Bay Area 3 counties: 11 clinics and centers 240,000+ active patients

3 Pan Asian Cohort Study (PACS) Lack of information for Type 2 diabetes and obesity for Asian American subgroups: Screening Incidence Prevalence Risk factors Care BMI cut point

4 Disparities in Diabetes Risk Screening Risk Care Asian Indian Risk (Odds ratio* for diabetes, 95% CI) Chinese Filipino Japanese Korean Vietnamese Non Hispanic White Asian American *after adjusting for age, sex, and BMI. Data from BRFSS. McNeely, M. J. and E. J. Boyko (2004).

5 (1) PAMF catchment area represents all six major Asian subgroups. % Asian out of county population % Asian out of U.S. population: 4.5% 24.9% 24.2% 31.2% Census

6 Distribution of Asian American ethnicities similar between PAMF/PAD catchment and U.S. Breakdown of Asian American population United States PAMF/PAD catchment area Summary File 1, 2; PCT5. U.S. Census Bureau, 2006 American Community Survey.

7 Preliminary findings: Disparities seen with disaggregation Sometimes differences in Asian Americans as an aggregate are driven by specific Asian subgroups. Sometimes differences in Asians are masked when aggregated. Consistency in differences in Asian American subgroups are noticed when disaggregated.

8 Preliminary findings: diabetes (men) + + * + Age and BMI adjusted Age-adjusted prevalence prevalence of of diabetes for for men men (with 95% Confidence Interval) + = + = statistically significant from NHW at at p p < <.0001 = = statistically significant from Asian (all) at at p p < <.0001 *

9 Preliminary findings: diabetes (women) +* + + * Age and BMI adjusted Age-adjusted prevalence prevalence of of diabetes for for women * (with 95% Confidence Interval) + = + = statistically significant from NHW at at p p < <.0001 = = statistically significant from Asian (all) at at p p < <.0001

10 Preliminary findings: Low HDL (Men) Preliminary findings: Low HDL (men) + * * + + * * Age and BMI adjusted Age-adjusted prevalence prevalence of diabetes of low HDL for for men men (with 95% Confidence Interval) + = + = statistically significant from NHW at at p p < <.0001 = = statistically significant from Asian (all) at at p p < <.0001 *

11 Preliminary findings: Low HDL (women) + * * * Age and BMI adjusted Age-adjusted prevalence of of diabetes low HDL for for women (with 95% Confidence Interval) + = + = statistically significant from NHW at at p p < <.0001 = = statistically significant from Asian (all) at at p p < <.0001 *

12 Preliminary findings: Hypertension Men Women Age and BMI adjusted prevalence of hypertension (with 95% Confidence Interval) + = statistically significant from NHW at p <.0001 = statistically significant from Asian (all) at p <.0001

13 Preliminary findings: High triglycerides Men Women Age and BMI adjusted prevalence of high triglycerides (with 95% Confidence Interval) + = statistically significant from NHW at p <.0001 = statistically significant from Asian (all) at p <.0001

14 Preliminary findings: Metabolic syndrome (men) 42% 25% increased risk 17% 23 25

15 Preliminary findings: Metabolic syndrome (women) 15% increased risk 22% 7% 23 25

16 The Y Y Paradox: Limitations of BMI as Measure of Adiposity Across Populations BMI: Identical BMIs Yajnik CS, Yudkin JS. Lancet, 2004; 363:163. Body fat: 9.1% 21.2% Big difference in body fat

17 Lancet, 2004 BMI > 23 kg/m 2 overweight BMI > 25 kg/m 2 obese

18 Using Electronic Health Records to Create an Epidemiologic Cohort

19 Harnessing PAMF s clinical database For a research cohort: (1) Identify Asian racial/ethnic subgroups (1) Check for sufficient population (2) Construct an electronic, record linked cohort (Asian and NHW who are 35+)

20 (1) Identifying Asian racial/ethnic subgroups: By self report

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22 Numbers of Asian Patients at PAMF: surname analysis and self report 80,000 60,000 70,937 63,583 40,000 20,000 0 Current, self report Projected, self report 23,555 20,310 20,601 7,972 5,991 5,852 6,907 2,567 2,005 2,241 Asian Indian Chinese Filipino Japanese Korean Vietnamese

23 Harnessing PAMF s clinical database For a research cohort: (1) Identify Asian racial/ethnic subgroups (1) Check for sufficient population (2) Construct an electronic, record linked cohort (Asian and NHW who are 35+)

24 Constructing a dynamic, record linked cohort Additional Lab Data Available EHR initiation Future Follow Up Funding period Reconstructed Longitudinal Cohort for Incidence and Predictors Longitudinal Cohort followed forward for incidence and predictors

25 Questions in using a clinical cohort

26 Completeness and reliability of clinical data 1) Reliability in diagnosing diabetes 2) Differential screening rates 3) Large sample size 4) Reliability of Laboratory Data

27 (1) EHR is superior in accuracy to administrative claims data. Sensitivity in measuring diabetes: Electronic Health Record 97.6% Administrative Claims Data 75.0% Misses 25% of diabetic patients 0.0% 20.0% 40.0% 60.0% 80.0% 100.0% Gold standard: manual chart review Tang, P. C., M. Ralston, et al. (2007).

28 Completeness and reliability of clinical data 1) Reliability in diagnosing diabetes 2) Differential screening rates 3) Large sample size 4) Reliability of Laboratory Data

29 (2) Screening rates high compared to cohort study response rates. 100% Avg study NHWs response rate Asian (all) 80% 60% 40% 20% 0% BMI BP Glucose

30 Completeness and reliability of clinical data 1) Reliability in diagnosing diabetes 2) Differential screening rates 3) Large sample size 4) Reliability of Laboratory Data

31 (3) Large Asian Population MESA Coordinating Center. MESA Table 3. Seattle: University of Washington. Kagan A, Popper J, Rhoads G. Factors related to stroke incidence in Hawaii Japanese men. The Honolulu Heart Study. Stroke. January 1, ;11(1):14-21.

32 Completeness and reliability of clinical data 1) Reliability in diagnosing diabetes 2) Differential screening rates 3) Large sample size 4) Reliability of Laboratory Data

33 Proportion of patients with LDL Control (LDL 100 mg/dl) * *Statistically significant at p = using multivariate analysis.

34 Posterior Means: LDL November 2006

35 Posterior Means: HDL Change point, November 2006 Plot of the mean HDL by day from Mar 2000 to Mar Change point analysis highlighted the date 11/06/2006 as a candidate for change (shown in red). This is consistent with information from the lab that an analyzer change occurred in Nov 2006.

36 Google Search Terms: PAMF South Asian PAMF PRANA

37 LATHA PALANIAPPAN