Medicare Advantage growth and skilled nursing facility finances

OBJECTIVE

To examine the relationship between growth in Medicare Advantage (MA) enrollment and changes in finances at skilled nursing facilities (SNFs).

DATA SOURCES

Medicare SNF cost reports, LTCFocus.org data, and county MA penetration rates.

STUDY DESIGN

We used ordinary least squares regression with SNF and year fixed effects. Our primary outcomes were SNF revenues, expenses, profits, and occupancy. Our primary independent variable was the yearly county Medicare Advantage penetration.

DATA COLLECTION/EXTRACTION

We linked facility-year data from 2012 to 2019 obtained from cost reports and LTCFocus.org to county-year MA penetration.

PRINCIPAL FINDINGS

A 10 percentage point increase in county MA enrollment was associated with a $213,883.89 (95% Confidence Interval [CI]: -296,869.08, -130,898.71) decrease in revenue, a $132,456.19 (95% CI: -203,852.28, -61,060.10) decrease in expenses, and a 0.59 percentage point (95% CI: -0.97, -0.21) decrease in profit margin. A 10 percentage point increase in county MA enrollment was associated with a decline (-318.93; 95% CI: -468.84, -169.02) in the number of resident-days (a measure of occupancy) as well as a decline in the revenue per resident day ($4.50; 95% CI: -6.81, -2.20), potentially because of lower prices in MA. There was also a decline in expenses per patient day (-2.35; 95% CI: -4.76, 0.05), though this was only statistically significant at the 10% level. While increased MA enrollment was associated with a substantial decline in the number of Medicare resident days (487.53; 95% CI: -588.70, -386.37), this was partially offset by an increase in other payer (e.g., private pay) resident days (285.91; 95% CI: 128.18, 443.63). Increased MA enrollment was not associated with changes in the number of Medicaid resident days or a decrease in staffing per resident day.

CONCLUSION

SNFs in counties with more MA growth had substantially greater relative declines in revenue, expenses, and profit margins. The continued growth of MA may result in significant changes in the SNF industry.

Measuring restrictiveness of Medicare Advantage networks: A claims-based approach

OBJECTIVE

To develop and validate a measure of provider network restrictiveness in the Medicare Advantage (MA) population.

DATA SOURCES

Prescription drug event data and beneficiary information for Part D enrollees from the Center for Medicare and Medicaid Services, along with prescriber identifiers; geographic variables from the Area Health Resources Files.

STUDY DESIGN

A prediction model was used to predict the unique number of primary care providers that would have been seen by MA beneficiaries absent network restrictions. The model was trained and validated on Traditional Medicare (TM) beneficiaries. A pseudo-Poisson and a random forest model were evaluated. An observed-to-expected (O/E) ratio was calculated as the number of unique providers seen by MA beneficiaries divided by the number expected based the TM prediction model. Multivariable linear models were used to assess the relationship between network restrictiveness and plan and market factors.

DATA COLLECTION/EXTRACTION METHODS

Prescription drug event data were obtained for a 20% random sample of beneficiaries enrolled in prescription drug coverage from 2011 to 2017.

PRINCIPAL FINDINGS

Health Maintenance Organization plans were more restrictive (O/E = 55.5%; 95% CI 55.3%-55.7%) than Health Maintenance Organization-Point of Service plans (67.2%; 95% CI 66.7%-67.8%) or Preferred Provider Organization plans (74.7%; 95% CI 74.3%-75.1%), and rural areas had more restrictive networks (31.6%; 95% CI 29.0%-34.2%) than metropolitan areas (61.5%; 95% CI 61.3%-61.7%). Multivariable results confirmed these findings, and also indicated that increased provider supply was associated with less restrictive networks.

CONCLUSIONS

We developed a means of estimating provider network restrictiveness in MA from claims data. Our results validate the approach, providing confidence for wider application (e.g., for other markets and specialties) and use for regulation.

Medicare advantage and dialysis facility choice

OBJECTIVE

To compare the characteristics of dialysis facilities used by traditional Medicare (TM) and Medicare advantage (MA) enrollees with end-stage kidney disease (ESKD).

DATA SOURCES

We used 20% TM claims and 100% MA encounter data from 2018 and publicly available data from the Centers for Medicare and Medicaid Services.

STUDY DESIGN

We compared the characteristics of the dialysis facilities treating TM and MA patients in the same ZIP code, adjusting for patient characteristics. The outcome variables were facility ownership, distance to the facility, and several measures of facility quality.

DATA COLLECTION/EXTRACTION

We identified point prevalent dialysis patients as of July 15, 2018.

PRINCIPAL FINDINGS

Compared to TM patients in the same ZIP code, MA patients were 1.84 percentage points more likely to be treated at facilities owned by the largest two dialysis organizations and 1.85 percentage points less likely to be treated at an independently owned facility. MA patients went to further and lower quality facilities than TM patients in the same ZIP code. However, these differences in facility quality were modest. For example, while the mean dialysis facility mortality rate was 21.85, the difference in mortality rates at facilities treating MA and TM patients in the same ZIP code was 0.67 deaths per 100 patient-years. Similarly, MA patients went to facilities that were, on average, 0.15 miles further than TM patients in the same ZIP code.

CONCLUSION

MA enrollees with ESKD were more likely than TM enrollees in the same ZIP code to use the dialysis facilities owned by the two largest chains, travel further for care, and receive care at lower quality facilities. While the magnitude of differences in facility distance and quality was modest, the direction of these results underscores the importance of monitoring dialysis network adequacy as ESKD MA enrollment continues to grow.

Initial Impacts of the Patient Care Networks of Alabama Initiative

OBJECTIVES

To estimate the effects of medical home support on the use of clinical services and Medicaid expenditures.

DATA SOURCE

Medicaid claims.

STUDY DESIGN

A difference-in-differences model where changes in utilization and expenditures of the intervention group are compared to changes in the nonintervention group.

EXTRACTION METHODS

Using Medicaid claims from October 2010 through September 2013, service use and expenditures are measured for 12 months before and 21 months after implementation. Changes for four health status groups are examined separately.

PRINCIPAL FINDINGS

The introduction of community-based support was associated with a small reduction in use and no statistically significant overall effect on expenditures. However, among those with chronic and/or mental health conditions, there were modest, statistically significant increases in use of and expenditures for a range of ambulatory and inpatient health care services, while service use for those without these conditions declined. Emergency department use increased for all groups.

CONCLUSIONS

Community-based support for medical home practices is associated with a shift in the service mix provided to higher cost, more vulnerable subgroups in Medicaid. Such systems are unlikely to be associated with significant overall cost savings, at least in the short term, but may have other benefits.