Currently Viewing:
The American Journal of Managed Care September 2019
VA Geriatric Scholars Program’s Impact on Prescribing Potentially Inappropriate Medications
Zachary Burningham, PhD; Wei Chen, PhD; Brian C. Sauer, PhD; Regina Richter Lagha, PhD; Jared Hansen, MStat; Tina Huynh, MPH, MHA; Shardool Patel, PharmD; Jianwei Leng, MStat; Ahmad Halwani, MD; and B. Josea Kramer, PhD
The Sociobehavioral Phenotype: Applying a Precision Medicine Framework to Social Determinants of Health
Ravi B. Parikh, MD, MPP; Sachin H. Jain, MD, MBA; and Amol S. Navathe, MD, PhD
From the Editorial Board: Jan E. Berger, MD, MJ
Jan E. Berger, MD, MJ
Medicaid Managed Care: Issues for Enrollees With Serious Mental Illness
Jean P. Hall, PhD; Tracey A. LaPierre, PhD; and Noelle K. Kurth, MS
Multi-Payer Advanced Primary Care Practice Demonstration on Quality of Care
Musetta Leung, PhD; Christopher Beadles, MD, PhD; Melissa Romaire, PhD; and Monika Gulledge, MPH; for the MAPCP Evaluation Team
Physician-Initiated Payment Reform: A New Path Toward Value
Suhas Gondi, BA; Timothy G. Ferris, MD, MPH; Kavita K. Patel, MD, MSHS; and Zirui Song, MD, PhD
Currently Reading
Managed Care for Long-Stay Nursing Home Residents: An Evaluation of Institutional Special Needs Plans
Brian E. McGarry, PT, PhD; and David C. Grabowski, PhD
Did Medicare Advantage Payment Cuts Affect Beneficiary Access and Affordability?
Laura Skopec, MS; Joshua Aarons, BA; and Stephen Zuckerman, PhD
Medicare Shared Savings Program ACO Network Comprehensiveness and Patient Panel Stability
Cassandra Leighton, MPH; Evan Cole, PhD; A. Everette James, JD, MBA; and Julia Driessen, PhD
Which Patients Are Persistently High-Risk for Hospitalization?
Evelyn T. Chang, MD, MSHS; Rebecca Piegari, MS; Edwin S. Wong, PhD; Ann-Marie Rosland, MD, MS; Stephan D. Fihn, MD, MPH; Sandeep Vijan, MD; and Jean Yoon, PhD, MHS
Call Center Performance Affects Patient Perceptions of Access and Satisfaction
Kevin N. Griffith, MPA; Donglin Li, MPH; Michael L. Davies, MD; Steven D. Pizer, PhD; and Julia C. Prentice, PhD

Managed Care for Long-Stay Nursing Home Residents: An Evaluation of Institutional Special Needs Plans

Brian E. McGarry, PT, PhD; and David C. Grabowski, PhD
This study examines UnitedHealthcare’s Institutional Special Needs Plans and their association with hospital and skilled nursing facility use.
METHODS

Data

This study used 2014 to 2015 data from 2 sources. To obtain information on I-SNP beneficiaries, we accessed a unique longitudinal UnitedHealthcare I-SNP database, which contained the claims for UnitedHealthcare I-SNP members submitted to the plan by the nursing homes and other plan providers (eg, physicians, hospitals).

Healthcare utilization for FFS Medicare beneficiaries was obtained from the CMS 5% Sample Limited Data Set, which includes Part A (inpatient) and Part B (physician, outpatient) claims (see eAppendix [available at ajmc.com] for additional details).

Sample Construction

The study period consists of 1 year following the start of long-term (≥90 days) nursing home care for residents in both the I-SNP group and the FFS Medicare comparison group.

Nursing home residents in the I-SNP group and the comparison group were selected from their respective databases if they began receiving long-term nursing home care during calendar year 2014. I-SNP beneficiaries were excluded if their nursing homes were not identified as “mature” in terms of their I-SNP model adoption (see eAppendix for details).

Given differences in local treatment patterns and state policies, individuals in the FFS Medicare comparison group were drawn from the same states as the I-SNP beneficiaries. We examined individuals from 13 states in this study: Arizona, Colorado, Connecticut, Florida, Georgia, New Jersey, New York, North Carolina, Ohio, Pennsylvania, Rhode Island, Washington, and Wisconsin. Importantly, we were unable to match individuals in FFS Medicare to a particular nursing home due to data limitations. As such, geographic matching of I-SNP and FFS Medicare individuals cannot occur below the state level.

We identified 8052 I-SNP members from 755 nursing homes in these 13 states that met the study criteria and 12,982 qualifying FFS Medicare beneficiaries receiving long-term nursing home care in these same states.

Study Outcomes

We examined several utilization outcomes in this study. Specifically, we separately examined ED, inpatient, and SNF utilization per 1000 long-term nursing home residents. Given the current policy interest in hospital readmissions from the SNF setting,18 we also examined an all-cause 30-day readmission rate per 1000 residents. This measure was defined as a second acute hospital inpatient admission for any reason within 30 days of the original hospital admission.

Analyses

We compared mean utilization across the I-SNP and FFS Medicare samples using a nonparametric Wilcoxon text, which makes no distributional assumptions. We first examined unweighted utilization across the 2 groups. Next, we used a logit model to predict enrollment in the I-SNP model based on age, gender, and state of residence. Unfortunately, we were unable to include additional variables, such as Medicaid eligibility status, in our weighting due to data limitations; however, we know that the majority (87%) of I-SNP enrollees are dually eligible for Medicare and Medicaid. We used the inverse of the probability of treatment weights to propensity match the 2 groups. A balance table was constructed to examine model diagnostics.

To examine the potential spending implications of any observed differences in clinical care use across the I-SNP and FFS groups, we also calculated the change in FFS Medicare spending for long-term nursing home residents if we applied utilization estimates from the I-SNP sample. Given skewed healthcare spending, we first obtained the median spending estimates on inpatient, ED, and SNF episodes from our FFS Medicare sample. Our results are robust to using mean spending values. We then multiplied the I-SNP and FFS Medicare utilization estimates from our most conservative approach (adjusting for sample demographics) with these spending estimates. The difference provides an estimate of the spending change, assuming that FFS Medicare beneficiaries had the utilization patterns of I-SNP beneficiaries. Finally, we adjusted these numbers up to population-level estimates using the total number of long-term FFS Medicare residents in the United States.

The study was approved by the Harvard Medical School Institutional Review Board.


 
Copyright AJMC 2006-2020 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
x
Welcome the the new and improved AJMC.com, the premier managed market network. Tell us about yourself so that we can serve you better.
Sign Up