Observational Analysis of a Generalized, Health Plan-led Community Health Worker Intervention in Medicaid.

INTRODUCTION/OBJECTIVES: In 2018, a Medicaid managed care plan launched a new community health worker (CHW) initiative in several counties within a state, designed to improve the health and quality of life of members who could benefit from additional services. The CHW program involved telephonic and face-to-face visits from CHWs who provided support, empowerment, and education to members, while identifying and addressing health and social issues. The primary objective of this study was to evaluate the impact of a generalized (not disease-specific), health plan-led CHW program on overall healthcare use and spending. METHODS: This retrospective cohort study used data from adult members who received the CHW intervention (N = 538 participants) compared to those who were identified for participation but were unable to be reached (N = 435 nonparticipants). Outcomes measures included healthcare utilization, including scheduled and emergency inpatient admissions, emergency department (ED) visits, and outpatient visits; and healthcare spending. The follow-up period for all outcome measures was 6 months. Using generalized linear models, 6-month change scores were regressed on baseline characteristics to adjust for between-group differences (eg, age, sex, comorbidities) and an indicator for group. RESULTS: Program participants experienced a greater increase in outpatient evaluation and management visits (0.09 per member per month [PMPM]) than the comparison group during the first 6 months of the program. This greater increase was observed across in-person (0.07 PMPM), telehealth (0.03 PMPM), and primary care (0.06 PMPM) visits. There was no observed difference in inpatient admissions, ED utilization or allowed medical spending and pharmacy spending. CONCLUSIONS: A health plan-led CHW program successfully increased multiple forms of outpatient utilization in a historically disadvantaged population of patients. Health plans may be particularly well positioned to finance, sustain, and scale programs that address social drivers of health.

The Association Between Mammography Screening Frequency and Breast Cancer Treatment and Outcomes: A Retrospective Cohort Study.

OBJECTIVE: Guidelines for optimal frequency of screening mammography vary by professional society. Sparse evidence exists on the association between screening frequency and breast cancer treatment options. The main objective was to examine differences in cancer treatment rendered for U.S. women with different numbers of screenings prior to breast cancer diagnosis. Cancer stage at diagnosis and health care cost were assessed in secondary analyses. METHODS: This IRB-exempt retrospective study used administrative claims data to identify women aged 44 or older with various numbers of mammographic screenings ≥11 months apart, during the four years prior to incident breast cancer diagnosis from January 2010 to December 2018. Outcomes were assessed over the six months following diagnosis. Generalized linear regression models were used to compare women with differing numbers of mammograms, adjusting for patient characteristics. RESULTS: Claims data review identified 25 492 women who met inclusion criteria. There was a stepwise improvement in each of these screening categories such that women with four screenings, compared to women with only one screening, experienced higher rates of lumpectomy (70% vs 55%) and radiation therapy (48% vs 36%), lower rates of mastectomy (27% vs 34%) and chemotherapy (28% vs 36%), less stage 3 or 4 cancer at diagnosis (15% vs 29%), and lower health care costs within six months postdiagnosis (P < 0.001). Results were similar in a subgroup limited to women aged 44 to 49 at diagnosis. CONCLUSION: Potential benefits of more frequent screening include less aggressive treatment and lower health care costs among women who develop breast cancer.

Provider Charges And State Surprise Billing Laws: Evidence From New York And California.

Surprise billing laws that allow dispute arbitration relying on provider charges may incentivize out-of-network providers to increase their charges to increase upcoming or future out-of-network payments. Although the federal No Surprises Act forbids arbitrators from considering charges during payment disputes over surprise bills covered by the act, states with existing laws can continue to use the specified state laws, which may allow the consideration of charges. This analysis examined provider charges in two such states, using claims data to compare trends in billed charges for out-of-network care during surprise bill scenarios involving nonemergency inpatient hospitalizations. The analysis considered New York, where state law uses arbitration tied to charges; California, where state law uses a payment standard rather than charges; and a comparison group of states without a law regarding surprise billing. We estimated that provider out-of-network charges for the nonemergency out-of-network bills we studied increased by $1,157 (24 percent) in New York after the passage of New York's surprise billing law and decreased by $752 (25 percent) in California compared to states without surprise billing laws. Assistant surgeons and surgical assistants had a large increase in charges in New York from before to after the law's passage, which may have driven the overall increase in charges.

Multimorbidity and Decision-Making Preferences Among Older Adults.

PURPOSE: Understanding individuals' preferences for participating in health care decisions is foundational to delivering person-centered care. We aimed to (1) explore preferences for health care decision making among older adults, and (2) identify multimorbidity profiles associated with preferring less active, ie, passive, participation among older US adults. METHOD: Ours was a cross-sectional, nationally representative study of 2,017 National Health and Aging Trends Study respondents. Passive decision-making preference was defined as preferring to leave decisions to physicians. Multimorbidity profiles, based on 13 prevalent chronic conditions, were examined as (1) presence of 2 or more conditions, (2) a simple conditions count, and (3) a condition clusters count. Multiple logistic regression was used with adjustment for age, sex, education, English proficiency, and mobility limitation. RESULTS: Most older adults preferred to participate actively in making health care decisions. Older adults with 4 or more conditions, however, and those with multiple condition clusters are relatively less likely to prefer active decision making. CONCLUSIONS: Primary care physicians should initiate a shared decision-making process with older adults with 4 or more conditions or multiple condition clusters. Physicians should anticipate variation in decision-making preferences among older adults and adapt a decision-making process that suits individuals' preferences for participation to ensure person-centered care delivery.