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Tracking Obesity Care Practices in the VHA: A Study on Documentation of Heights, Weights, and Diagnoses

This study focuses on monitoring obesity care practices within the Veterans Health Administration, exploring the documentation of patient heights, weights, and obesity diagnoses from FY02 to FY06. The research examines the screening, monitoring, and recognition of obesity among primary care patients, highlighting potential data errors and limitations in administrative data. The findings reveal variations in care practices and raise questions about the impact on clinical outcomes and future research directions.

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Tracking Obesity Care Practices in the VHA: A Study on Documentation of Heights, Weights, and 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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