Use of a Preventive Index to Examine Clinic-Level Factors Associated With Delivery of Preventive Care.

Hatch BA1, Tillotson CJ2, Huguet N3, Hoopes MJ2, Marino M4, DeVoe JE5.

Author information

1: Department of Family Medicine, Oregon Health & Science University, Portland, Oregon; OCHIN, Inc., Portland, Oregon. Electronic address: adamusb@ohsu.edu.
2: OCHIN, Inc., Portland, Oregon.
3: Department of Family Medicine, Oregon Health & Science University, Portland, Oregon.
4: Department of Family Medicine, Oregon Health & Science University, Portland, Oregon; Biostatistics Group, Portland State University School of Public Health, Oregon Health & Science University, Portland, Oregon.
5: Department of Family Medicine, Oregon Health & Science University, Portland, Oregon; OCHIN, Inc., Portland, Oregon.

Abstract

INTRODUCTION:

There is an increasing need for the development of new methods to understand factors affecting delivery of preventive care. This study applies a new measurement approach and assesses clinic-level factors associated with preventive care delivery.

METHODS:

This retrospective longitudinal cohort study of 94 community health centers used electronic health record data from the OCHIN community health information network, 2014-2015. Clinic-level preventive ratios (time covered by a preventive service/time eligible for a preventive service) were calculated in 2017 for 12 preventive services with A or B recommendations from the U.S. Preventive Services Task Force along with an aggregate preventive index for all services combined. For each service, multivariable negative binomial regression modeling and calculated rate ratios assessed the association between clinic-level variables and delivery of care.

RESULTS:

Of ambulatory community health center visits, 59.8% were Medicaid-insured and 10.4% were uninsured. Ambulatory community health centers served 16.9% patients who were Hispanic, 13.1% who were nonwhite, and 68.7% who had household incomes <138% of the federal poverty line. Clinic-level preventive ratios ranged from 3% (hepatitis C screening) to 93% (blood pressure screening). The aggregate preventive index including all screening measures was 47% (IQR, 42%-50%). At the clinic level, having a higher percentage of uninsured visits was associated with lower preventive ratios for most (7 of 12) preventive services.

CONCLUSIONS:

Approaches that use individual preventive ratios and aggregate prevention indices are promising for understanding and improving preventive service delivery over time. Health insurance remains strongly associated with access to needed preventive care, even for safety net clinic populations.