Documentation of body mass index and control of associated risk factors in a large primary care network

Stephanie A. Rose; Alexander Turchin; Richard W. Grant; James B. Meigs

doi:10.1186/1472-6963-9-236

Documentation of body mass index and control of associated risk factors in a large primary care network

Stephanie A. Rose
, Alexander Turchin
, Richard W. Grant
, James B. Meigs

Research output: Contribution to journal › Article › peer-review

23 Scopus citations

Abstract

Background. Body mass index (BMI) will be a reportable health measure in the United States (US) through implementation of Healthcare Effectiveness Data and Information Set (HEDIS) guidelines. We evaluated current documentation of BMI, and documentation and control of associated risk factors by BMI category, based on electronic health records from a 12-clinic primary care network. Methods. We conducted a cross-sectional analysis of 79,947 active network patients greater than 18 years of age seen between 7/05 - 12/06. We defined BMI category as normal weight (NW, 18-24.9 kg/m²), overweight (OW, 25-29.9), and obese (OB, ≥ 30). We measured documentation (yes/no) and control (above/below) of the following three risk factors: blood pressure (BP) ≤130/≤85 mmHg, low-density lipoprotein (LDL) ≤130 mg/dL (3.367 mmol/L), and fasting glucose <100 mg/dL (5.55 mmol/L) or casual glucose <200 mg/dL (11.1 mmol/L). Results. BMI was documented in 48,376 patients (61%, range 34-94%), distributed as 30% OB, 34% OW, and 36% NW. Documentation of all three risk factors was higher in obesity (OB = 58%, OW = 54%, NW = 41%, p for trend <0.0001), but control of all three was lower (OB = 44%, OW = 49%, NW = 62%, p = 0.0001). The presence of cardiovascular disease (CVD) or diabetes modified some associations with obesity, and OB patients with CVD or diabetes had low rates of control of all three risk factors (CVD: OB = 49%, OW = 50%, NW = 56%; diabetes: OB = 42%, OW = 47%, NW = 48%, p < 0.0001 for adiposity-CVD or diabetes interaction). Conclusions. In a large primary care network BMI documentation has been incomplete and for patients with BMI measured, risk factor control has been poorer in obese patients compared with NW, even in those with obesity and CVD or diabetes. Better knowledge of BMI could provide an opportunity for improved quality in obesity care.

Original language	English
Article number	236
Journal	BMC Health Services Research
Volume	9
DOIs	https://doi.org/10.1186/1472-6963-9-236
State	Published - 2009

Funding

We thank Peter Shrader and Amy Cohen for their assistance with the analysis, and Daniel Singer, M.D., for review and comment on an earlier draft of the manuscript. Dr. Rose was supported by an Institutional National Research Service Award #5 T32 HP11001-19. Dr. Grant was supported by an NIDDK Career Development Award (K23 DK067452). Dr. Meigs was supported by NIDDK K24 DK080140. Dr. Meigs currently has research grants from GlaxoSmithKline and sanofi-aventis, and has consulting agreements with GlaxoSmithKline, sanofi-aventis, Interleukin Genetics, Kalypsis, and Outcomes Science. This work has been presented in poster form at the New England Regional Society of General Internal Medicine Conference in March of 2008, the Massachusetts Medical Society Poster Symposium in April of 2008, where it was the Second Prize Winner for Clinical Research, the Massachusetts General Hospital Clinical Research Day in May of 2008, and the Obesity Society Annual Meeting on October 6, 2008.

Funders	Funder number
National Heart, Lung, and Blood Institute (NHLBI)	T32HL007609
National Institute of Diabetes and Digestive and Kidney Diseases	K24 DK080140, K23 DK067452
GlaxoSmithKline

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

ASJC Scopus subject areas

Health Policy

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10.1186/1472-6963-9-236

Cite this

@article{2fb925db13734e47aab71714a37c45d6,

title = "Documentation of body mass index and control of associated risk factors in a large primary care network",

abstract = "Background. Body mass index (BMI) will be a reportable health measure in the United States (US) through implementation of Healthcare Effectiveness Data and Information Set (HEDIS) guidelines. We evaluated current documentation of BMI, and documentation and control of associated risk factors by BMI category, based on electronic health records from a 12-clinic primary care network. Methods. We conducted a cross-sectional analysis of 79,947 active network patients greater than 18 years of age seen between 7/05 - 12/06. We defined BMI category as normal weight (NW, 18-24.9 kg/m2), overweight (OW, 25-29.9), and obese (OB, ≥ 30). We measured documentation (yes/no) and control (above/below) of the following three risk factors: blood pressure (BP) ≤130/≤85 mmHg, low-density lipoprotein (LDL) ≤130 mg/dL (3.367 mmol/L), and fasting glucose <100 mg/dL (5.55 mmol/L) or casual glucose <200 mg/dL (11.1 mmol/L). Results. BMI was documented in 48,376 patients (61\%, range 34-94\%), distributed as 30\% OB, 34\% OW, and 36\% NW. Documentation of all three risk factors was higher in obesity (OB = 58\%, OW = 54\%, NW = 41\%, p for trend <0.0001), but control of all three was lower (OB = 44\%, OW = 49\%, NW = 62\%, p = 0.0001). The presence of cardiovascular disease (CVD) or diabetes modified some associations with obesity, and OB patients with CVD or diabetes had low rates of control of all three risk factors (CVD: OB = 49\%, OW = 50\%, NW = 56\%; diabetes: OB = 42\%, OW = 47\%, NW = 48\%, p < 0.0001 for adiposity-CVD or diabetes interaction). Conclusions. In a large primary care network BMI documentation has been incomplete and for patients with BMI measured, risk factor control has been poorer in obese patients compared with NW, even in those with obesity and CVD or diabetes. Better knowledge of BMI could provide an opportunity for improved quality in obesity care.",

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T1 - Documentation of body mass index and control of associated risk factors in a large primary care network

AU - Rose, Stephanie A.

AU - Turchin, Alexander

AU - Grant, Richard W.

AU - Meigs, James B.

PY - 2009

Y1 - 2009

N2 - Background. Body mass index (BMI) will be a reportable health measure in the United States (US) through implementation of Healthcare Effectiveness Data and Information Set (HEDIS) guidelines. We evaluated current documentation of BMI, and documentation and control of associated risk factors by BMI category, based on electronic health records from a 12-clinic primary care network. Methods. We conducted a cross-sectional analysis of 79,947 active network patients greater than 18 years of age seen between 7/05 - 12/06. We defined BMI category as normal weight (NW, 18-24.9 kg/m2), overweight (OW, 25-29.9), and obese (OB, ≥ 30). We measured documentation (yes/no) and control (above/below) of the following three risk factors: blood pressure (BP) ≤130/≤85 mmHg, low-density lipoprotein (LDL) ≤130 mg/dL (3.367 mmol/L), and fasting glucose <100 mg/dL (5.55 mmol/L) or casual glucose <200 mg/dL (11.1 mmol/L). Results. BMI was documented in 48,376 patients (61%, range 34-94%), distributed as 30% OB, 34% OW, and 36% NW. Documentation of all three risk factors was higher in obesity (OB = 58%, OW = 54%, NW = 41%, p for trend <0.0001), but control of all three was lower (OB = 44%, OW = 49%, NW = 62%, p = 0.0001). The presence of cardiovascular disease (CVD) or diabetes modified some associations with obesity, and OB patients with CVD or diabetes had low rates of control of all three risk factors (CVD: OB = 49%, OW = 50%, NW = 56%; diabetes: OB = 42%, OW = 47%, NW = 48%, p < 0.0001 for adiposity-CVD or diabetes interaction). Conclusions. In a large primary care network BMI documentation has been incomplete and for patients with BMI measured, risk factor control has been poorer in obese patients compared with NW, even in those with obesity and CVD or diabetes. Better knowledge of BMI could provide an opportunity for improved quality in obesity care.

AB - Background. Body mass index (BMI) will be a reportable health measure in the United States (US) through implementation of Healthcare Effectiveness Data and Information Set (HEDIS) guidelines. We evaluated current documentation of BMI, and documentation and control of associated risk factors by BMI category, based on electronic health records from a 12-clinic primary care network. Methods. We conducted a cross-sectional analysis of 79,947 active network patients greater than 18 years of age seen between 7/05 - 12/06. We defined BMI category as normal weight (NW, 18-24.9 kg/m2), overweight (OW, 25-29.9), and obese (OB, ≥ 30). We measured documentation (yes/no) and control (above/below) of the following three risk factors: blood pressure (BP) ≤130/≤85 mmHg, low-density lipoprotein (LDL) ≤130 mg/dL (3.367 mmol/L), and fasting glucose <100 mg/dL (5.55 mmol/L) or casual glucose <200 mg/dL (11.1 mmol/L). Results. BMI was documented in 48,376 patients (61%, range 34-94%), distributed as 30% OB, 34% OW, and 36% NW. Documentation of all three risk factors was higher in obesity (OB = 58%, OW = 54%, NW = 41%, p for trend <0.0001), but control of all three was lower (OB = 44%, OW = 49%, NW = 62%, p = 0.0001). The presence of cardiovascular disease (CVD) or diabetes modified some associations with obesity, and OB patients with CVD or diabetes had low rates of control of all three risk factors (CVD: OB = 49%, OW = 50%, NW = 56%; diabetes: OB = 42%, OW = 47%, NW = 48%, p < 0.0001 for adiposity-CVD or diabetes interaction). Conclusions. In a large primary care network BMI documentation has been incomplete and for patients with BMI measured, risk factor control has been poorer in obese patients compared with NW, even in those with obesity and CVD or diabetes. Better knowledge of BMI could provide an opportunity for improved quality in obesity care.

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Documentation of body mass index and control of associated risk factors in a large primary care network

Abstract

Funding

UN SDGs

ASJC Scopus subject areas

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