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Obesity Care Practices in the VHA: Documentation of Heights, Weights, & Obesity Diagnoses

Obesity Care Practices in the VHA: Documentation of Heights, Weights, & Obesity Diagnoses. Polly Hitchcock No ël Veterans Evidence-based Research, Dissemination, & Implementation Center (VERDICT). VA HSR&D IIR 05-121-2. Collaborators. VERDICT/UT Health Science Center San Antonio:

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Obesity Care Practices in the VHA: Documentation of Heights, Weights, & Obesity Diagnoses

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  1. Obesity Care Practices in the VHA: Documentation of Heights, Weights, & Obesity Diagnoses Polly Hitchcock Noël Veterans Evidence-based Research, Dissemination, & Implementation Center (VERDICT) VA HSR&D IIR 05-121-2

  2. Collaborators VERDICT/UT Health Science Center San Antonio: Copeland L, Hazuda H, Pugh MJ, Wang CP, McCarthy A, Bollinger M VA National Ctr for Health Promotion & Disease Prevention: Kahwati L, Jones KR Site PIs: Nelson K, Hoffman V, Dundon P, Tsevat J, Arterburn D, Foulis P, Mossop PA

  3. BMI = wt (kg)/[ht (m)]2

  4. Relevance • MOVE! uses population-based approach to screening • VHA “indicator” for screening introduced FY08 – national clinical reminder under discussion • % of PC & MH patients screened with BMI & offered treatment if “at-risk” • HEDIS/NCQA is developing & piloting obesity screening measure

  5. Presentation Objectives A. What proportion of primary care patients had their hts & wts recorded in the EMR FY02-FY06? (“screening”) B. Among a cohort of primary care patients meeting BMI criteria for obesity in FY02: 1. What proportion had their hts/wts recorded in FY03-FY06? (“monitoring”) 2. What proportion received a diagnosis of obesity in FY02-FY06? (“recognition”)

  6. Design • inception cohort of primary care patients with BMI > 30 • heights & weights recorded in EMR in FY02 • followed FY03-FY06 • 6 regions (“VISNs”) (early & late adopters of MOVE!)

  7. Data Sources Administrative Data: • Sociodemographic, diagnostic, and utilization data from NPCD • Pharmacy data from PBM • Mortality data from MINI-VITALS • Heights & weights obtained from VHA’s new Corporate Data Warehouse (CDW)

  8. Weight (& Height) Data Inherently variable over time • changes in energy balance • disease, surgery, injury, or aging Variety of sources/opportunities for error • Measurement & reporting errors • Data entry errors

  9. Data Error Examples • Among 847,976 primary care pts with multiple hts recorded in same year, 21,051 (2.5%) had hts differ by > 2 -10 inches • Among 105,425 occurrences of pts > 2 wts recorded on same day, 10,054 (9.5%) had wts differ by >10-1,000 lbs

  10. Obesity Screening • > 1 PC visits each year for each VISN (where majority of care received) • hts & wts recorded in EMR in their VISN for each FY02-FY06

  11. *Primary care population ↑ from 1,053,228 in FY02 to 1,342,688 in FY06

  12. Cohort Identification • > 1 PC visits in the 6 VISNs in FY02 (N=1,053,228) • wts & hts filtered to remove “biologically implausible” values • wt & ht FY02: 844,066 (80.1%) wt FY02 & ht FY02-06: 89,018 ( 8.5%) Total: 933,088 (88.6%)

  13. Cohort Identification: BMI Method 1 • Maximum wt FY02 & • Minimum ht FY02-FY06

  14. Cohort Identification: BMI Method 1 Among 933,088 PC patients with ht FY02 & wt FY02-FY06

  15. Cohort Identification: BMI Method 2 • median wt for each quarter of FY02, then “median of median wts” • mode of all ht values FY02-FY06; in case of > 2 modes: if diff < 3 inches, averaged if diff > 3 inches, eliminated

  16. Cohort Identification & Refinement Among 933,088 PC patients with ht FY02 & wt FY02-FY06

  17. Obesity Monitoring • Cohort survivors • For those with PC visit, determined proportion with wt & ht (or wt only) recorded each year FY03-FY06

  18. Cohort Characteristics Total Obese Cohort N=330,802

  19. *Among 290,558 with PC visit each year (89.6% in FY02 to 82.3% in FY06)

  20. *Among 290,558 with PC visit each year (89.6% in FY02 to 82.3% in FY06)

  21. Obesity Recognition • Cohort survivors • Proportion with ICD-9-CM codes 278, 278.00, 278.01, 259.9, V77.8 • FY02 only and FY02-FY06

  22. Cohort Survivors Diagnosed with Obesity

  23. Obesity Dx in Cohort Survivors with Class I vs Class II+ Obesity p < .0001, Cohort Survivors N=290,558

  24. Limitations • administrative data • hts, wts, & dxs may be entered in “text fields” & not captured by administrative data • recording & data entry errors • cohort may be misspecified • obesity based on BMI • not representative of entire VHA

  25. Discussion Significant variation in screening & monitoring early MOVE! adopters performed better Characteristics of those not screened unknown Significant # do not have dxs or hts recorded – perceptions of importance? • majority of cohort > 60 yrs • BMI used to dose medications & calculate ventilation unit parameters • implications for health services research

  26. Next Steps • Describe variations in other obesity care practices & factors that predict • Examine the impact of obesity care practices on BMI and other important clinical outcomes • Identify longitudinal patterns (latent classes) of BMI trends over time

  27. Q U E S T I O N S ?

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