Adoption of Patient-Reported Outcomes by Health Systems and Physician Practices in the USA

BACKGROUND

Patient-reported outcome measures (PROs) can help clinicians adjust treatments and deliver patient-centered care, but organizational adoption of PROs remains low.

OBJECTIVE

This study examines the extent of PRO adoption among health systems and physician practices nationally and examines the organizational capabilities associated with more extensive PRO adoption.

DESIGN

Two nationally representative surveys were analyzed in parallel to assess health system and physician practice capabilities associated with adoption of PROs of disability, pain, and depression.

PARTICIPANTS

A total of 323 US health system and 2,190 physician practice respondents METHODS: Multivariable regression models separately estimated the association of health system and physician practice capabilities associated with system-level and practice-level adoption of PROs.

MAIN MEASURES

Health system and physician practice adoption of PROs for depression, pain, and disability.

KEY RESULTS

Pain (50.6%) and depression (43.8%) PROs were more commonly adopted by all hospitals and medical groups within health systems compared to disability PROs (26.5%). In adjusted analyses, systems with more advanced health IT functions were more likely to use disability (p<0.05) and depression (p<0.01) PROs than systems with less advanced health IT. Practice-level advanced health IT was positively associated with use of depression PRO (p<0.05), but not disability or pain PRO use. Practices with more chronic care management processes, broader medical and social risk screening, and more processes to support patient responsiveness were more likely to adopt each of the three PROs. Compared to independent physician practices, system-owned practices and community health centers were less likely to adopt PROs.

CONCLUSIONS

Chronic care management programs, routine screening, and patient-centered care initiatives can enable PRO adoption at the practice level. Developing these practice-level capabilities may improve PRO adoption more than solely expanding health IT functions.

The Centers for Medicaid and Medicare Services State Innovation Models Initiative and Social Risk Factors: Improved Diagnosis Among Hospitalized Adults With Diabetes

INTRODUCTION

Unaddressed social risks among hospitalized patients with chronic conditions contribute to costly complications and preventable hospitalizations. This study examines whether the Centers for Medicaid and Medicare Services State Innovation Models initiative, through payment and delivery system reforms, accelerates the diagnosis of social risk factors among hospitalized adults with diabetes.

METHODS

Encounter-level data were from the Agency for Healthcare Research and Quality Healthcare Cost and Utilization Project State Inpatient Databases (2010-2015, N=5,040,456). Difference-in-difference logistic regression estimated the extent to which hospitalized adults with diabetes in 4 State Innovation Models states (Arkansas, Massachusetts, Oregon, and Vermont) had increased odds of having a social risk factor diagnosed with an ICD-9 V code compared with hospitalized adults with diabetes in 4 comparison states (Arizona, Georgia, New Jersey, and New Mexico) 2 years after implementation. Data were analyzed between June and December 2019.

RESULTS

Adults with diabetes who were hospitalized in State Innovation Models states had a 30% greater increase in the odds of having a V code documented after implementation than adults with diabetes who were hospitalized in comparison states (AOR=1.29, 95% CI=1.07, 1.56). However, V code use remained infrequent, with only 2.05% of encounters, on average, having any V codes on record in State Innovation Models states after implementation.

CONCLUSIONS

The State Innovation Models initiative slightly but significantly improved the diagnosis of social risks among hospitalized adults with diabetes. State-led delivery system and payment reform may help support movement of hospitals toward better recognition and management of social determinants of health.