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

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

BMI = wt (kg)/[h

t (m)]2

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

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/wtsrecorded in FY03-FY06? (“monitoring”)2. What proportion received a diagnosis of

obesity in FY02-FY06? (“recognition”)

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!)

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)

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

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

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

50

55

6065

70

75

8085

90

95

FY02 FY03 FY04 FY05 FY06

Fiscal Year

% P

C P

atie

nts

Scr

een

ed

wit

h H

t &

Wt

VISN AVISN BVISN CVISN DVISN EVISN F

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

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%)

Cohort Identification: BMI Method 1

Maximum wt FY02 & Minimum ht FY02-FY06

Cohort Identification: BMI Method 1

Minimum ht/ Maximum wt

N (%) BMI>30

371,842 39.9%

BMI M (SD) 34.8 (4.8)

BMI Range 30.0 – 161.8

# BMI > 70 252

# ht<60 in 7,078

# wt<170 lb 4,006

Among 933,088 PC patients with ht FY02 & wt FY02-FY06

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

Cohort Identification & Refinement

Minimum ht/ Maximum wt

Modal ht/Mdof Median wts

N (%) obese 371,842 39.9%

330,802 35.5%

BMI M (SD) 34.8 (4.8) 34.5 (4.4)

BMI Range 30.0 – 161.8 30.0 – 95.4

# BMI > 70 252 70

# ht<60 in 7,078 2,968

# wt<170 lb

4,006 2,553Among 933,088 PC patients with ht FY02 & wt FY02-FY06

Obesity Monitoring Cohort survivors For those with PC visit, determined

proportion with wt & ht (or wt only) recorded each year FY03-FY06

Cohort Characteristics

SurvivorsN=290,558

NonSurvivors

N=40,244BMI > 35 33% 33%

> 60 yrs 53% 81%

Male 94% 97%

Minority 16% 15%Total Obese Cohort N=330,802

50556065707580859095

100

FY03 FY04 FY05 FY06

Fiscal Year

% O

bes

e C

oh

ort

Su

rviv

ors

M

on

ito

red

wit

h H

t &

Wt VISN A

VISN BVISN CVISN DVISN EVISN F

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

50

60

70

80

90

100

110

FY03 FY04 FY05 FY06

Fiscal Year

% O

bes

e C

oh

ort

Su

rviv

ors

M

on

ito

red

wit

h H

t &

Wt

OR

Wt

On

lyVISN AVISN BVISN CVISN DVISN EVISN F

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

Obesity Recognition Cohort survivors Proportion with ICD-9-CM codes

278, 278.00, 278.01, 259.9, V77.8 FY02 only and FY02-FY06

Cohort Survivors Diagnosed with Obesity

Diagnosis in FY02?

Diagnosis in FY02-06?

Yes 27% 51%

No 73% 49%

Total Survivors

290,558 290,558

Obesity Dx in Cohort Survivors with Class I vs Class II+ Obesity

Obesity DxFY02-FY06? BMI < 35 BMI > 35

Yes 41% 72%

No 59% 28%

Total 193,462 97,096

p < .0001, Cohort Survivors N=290,558

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

Discussion

Significant variation in screening & monitoringearly 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

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

Q U E S T I O N S ?