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Risk-adjusted comparison of blood pressure and low-density lipoprotein (LDL) noncontrol in primary care offices
Karl Hammermeister1, Michael Bronsert, William G Henderson
1the Colorado Health Outcomes Program, the Division of Cardiology, and the Department of Family Medicine, University of Colorado School of Medicine, Aurora; the Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora; the National Research Network, American Academy of Family Physicians, Leawood, KS; DI Consulting, Dallas, TX; the Department of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, Aurora; Fairfax Family Medicine Residency Program, Virginia Commonwealth University, Fairfax; and the Denver VA Medical Center, Denver, CO.
Insights
Electronic health records reveal suboptimal control of cardiovascular disease risk factors like blood pressure and LDL cholesterol in primary care. Risk adjustment is crucial for accurately assessing clinic performance in managing these conditions.
Area of Science:
- Cardiovascular disease prevention
- Health services research
- Primary care quality improvement
Background:
- Population-level control of modifiable cardiovascular disease (CVD) risk factors remains suboptimal.
- Effective strategies are needed to improve guideline concordance in primary care.
Purpose of the Study:
- To demonstrate the utility of electronic health record (EHR) data for assessing guideline adherence.
- To evaluate contemporary rates of uncontrolled blood pressure (BP) and low-density lipoprotein (LDL) cholesterol in primary care.
- To assess the impact of risk adjustment on clinic performance measures for BP and LDL control.
Main Methods:
- An observational study included 232,172 adult patients from 33 primary care clinics with EHRs.
- Rates of BP and LDL noncontrol were calculated from electronically downloaded EHR data.
- Risk adjustment was performed using multivariable models of patient-level variables.
Main Results:
- 16.0% of patients had uncontrolled BP and 14.9% had uncontrolled LDL.
- Risk-adjusted BP noncontrol ranged from 7.7% to 26.5%; LDL noncontrol ranged from 5.8% to 23.6%.
- Most clinics exceeded achievable benchmarks for BP and LDL noncontrol; risk adjustment significantly altered clinic rankings.
Conclusions:
- Electronic data collection from EHRs is feasible for auditing BP and LDL noncontrol in primary care.
- Most clinics exhibit high rates of uncontrolled BP and LDL, exceeding achievable benchmarks.
- Risk adjustment is essential for accurate comparison of clinic performance in managing cardiovascular risk factors.
Objectives:
Population-level control of modifiable cardiovascular disease (CVD) risk factors is suboptimal. The objectives of this study were (1) to demonstrate the use of electronically downloaded electronic health record (EHR) data to assess guideline concordance in a large cohort of primary care patients, (2) to provide a contemporary assessment of blood pressure (BP) and low-density lipoprotein (LDL) noncontrol in primary care, and (3) to demonstrate the effect of risk adjustment of rates of noncontrol of BP and LDL for differences in patient mix on these clinic-level performance measures.
Methods:
This was an observational comparative effectiveness study that included 232,172 adult patients ≥18 years old with ≥1 visit within 2 years in 33 primary care clinics with EHRs. The main measures were rates of BP and LDL noncontrol based on current guidelines and were calculated from electronically downloaded EHR data. Rates of noncontrol were risk-adjusted using multivariable models of patient-level variables.
Results:
Overall, 16.0% of the 227,122 patients with known BP and 14.9% of the 136,771 patients with known LDL were uncontrolled. Clinic-level, risk-adjusted BP noncontrol ranged from 7.7% to 26.5%, whereas that for LDL ranged from 5.8% to 23.6%. Rates of noncontrol exceeded an achievable benchmark for 85% (n = 28) and 79% (n = 26) of the 33 clinics for BP and LDL, respectively. Risk adjustment significantly influences clinic rank order for rate of noncontrol.
Conclusions:
We demonstrated that the use of electronic collection of data from a large cohort of patients from fee-for-service primary care clinics is feasible for the audit of and feedback on BP and LDL noncontrol. Rates of noncontrol for most clinics are substantially higher than those achievable. Risk adjustment of noncontrol rates results in a rank-order of clinics very different from that achieved with nonadjusted data.
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