Currently Viewing:
The American Journal of Managed Care November 2016
Referrals and the PCMH: How Well Do We Know Our Neighborhood?
Andrew Schreiner, MD; Patrick Mauldin, PhD, Jingwen Zhang, MS; Justin Marsden, BS; and William Moran, MD, MS
Currently Reading
Does Medicare Advantage Enrollment Affect Home Healthcare Use?
Daniel A. Waxman, MD, PhD; Lillian Min, MD, MSHS; Claude M. Setodji, PhD; Mark Hanson, PhD; Neil S. Wenger, MD, MPH; and David A. Ganz, MD, PhD
Prescribers' Perceptions of Medication Discontinuation: Survey Instrument Development and Validation
Amy Linsky, MD, MSc; Steven R. Simon, MD, MPH; Kelly Stolzmann, MS; Barbara G. Bokhour, PhD; and Mark Meterko, PhD
Enhancing Patient and Family Engagement Through Meaningful Use Stage 3: Opportunities and Barriers to Implementation
Jaclyn Rappaport, MPP, MBA; Sara Galantowicz, MPH; Andrea Hassol, MSPH; Anisha Illa, BS; Sid Thornton, PhD; Shan He, PhD; Jean Adams, RN, ACIO; and Charlie Sawyer, MD, FACP
Integrated Care Organizations: Medicare Financing for Care at Home
Karen Davis, PhD; Amber Willink, PhD; and Cathy Schoen, MS
Reconsidering the Economic Value of Multiple Sclerosis Therapies
Tiffany Shih, PhD; Craig Wakeford, MA; Dennis Meletiche, PharmD; Jesse Sussell, PhD; Adrienne Chung, PhD; Yanmei Liu, MS; Jin Joo Shim, MS; and Darius Lakdawalla, PhD
Health Systems Tackling Social Determinants of Health: Promises, Pitfalls, and Opportunities of Current Policies
Krisda H. Chaiyachati, MD, MPH; David T. Grande, MD, MPA; and Jaya Aysola, MD, DTMH, MPH
Maternal Mental Health and Infant Mortality for Healthy-Weight Infants
Susan E. White, PhD, RHIA, CHDA, and Robert W. Gladden, MA, BS
The Role of Internal Medicine Subspecialists in Patient Care Management
Jonathan L. Vandergrift, MS; Bradley M. Gray, PhD; James D. Reschovsky, PhD; Eric S. Holmboe, MD; and Rebecca S. Lipner, PhD
Medical Home Transformation and Breast Cancer Screening
Amy W. Baughman, MD, MPH; Phyllis Brawarsky, MPH; Tracy Onega, PhD, MS; Tor D. Tosteson, ScD; Qianfei Wang, MS; Anna N.A. Tosteson, ScD; and Jennifer S. Haas, MD, MSc

Does Medicare Advantage Enrollment Affect Home Healthcare Use?

Daniel A. Waxman, MD, PhD; Lillian Min, MD, MSHS; Claude M. Setodji, PhD; Mark Hanson, PhD; Neil S. Wenger, MD, MPH; and David A. Ganz, MD, PhD
Medicare Advantage beneficiaries use less home healthcare than do their fee-for-service counterparts, but there is marked regional variation in use by both groups.

To compare home health utilization and clinical outcomes between Medicare beneficiaries in the fee-for-service (FFS) and Medicare Advantage (MA) programs, and to compare regional variation.

Study Design: We used the 2010 and 2011 Outcome and Assessment Information Set to identify all home health episodes begun in 2010 and to measure 7 clinical home health outcomes that are defined by CMS for public reporting.

Methods: We modeled the probability of home health use, the duration of home health episodes, and each clinical outcome measure as a function of MA versus FFS enrollment and model-specific risk adjustors. Empirical Bayes predictions from generalized linear mixed models were aggregated by hospital referral region (HRR) to create standardized regional measures of home health utilization and mean episode duration
Results: We identified 30,837,130 FFS and 10,594,658 MA beneficiaries (excluding those dually eligible for Medicaid). After adjusting for demographic and clinical patient characteristics, the odds of receiving home health among FFS enrollees were 1.83 times those of MA (95% CI, 1.82-1.84). Adjusted home health duration was 34% longer for FFS (95% CI, 32%-34%). Outcomes differences were small in magnitude and inconsistent across measures. Regional variations in use and duration were substantial for both FFS and MA enrollees. Within HRRs, correlations between FFS and MA utilization rates and between FFS and MA episode durations were 0.51 and 0.94, respectively.

Conclusions: MA beneficiaries use less home health than their FFS counterparts, but regional factors affect utilization, independent of insurance status.

Am J Manag Care. 2016;22(11):714-720
Take-Away Points

Home health utilization is a substantial source of Medicare costs; however, whether enrollment in a Medicare Advantage (MA) plan affects home heathcare use is unknown. We compared nationwide and intra-regional use of home health between beneficiaries enrolled in fee-for-service (FFS) Medicare and MA plans. Our findings were as follows:
  • FFS beneficiaries used substantially more care, even after adjusting for patient and demographic characteristics.
  • Functional outcomes were similar, although FFS episodes were 33% longer in duration.
  • Adjusted utilization varied markedly across regions for both FFS and MA, suggesting that MA plans cannot entirely overcome non–health-related regional forces driving use.
Although more than 30% of all Medicare beneficiaries are enrolled in the Medicare Advantage (MA) program,1 studies focusing on the MA patient population are relatively rare, in large part because there are no claims to use as a data source. The capitated payment model introduces a financial incentive to limit wasteful care, whereas none exists in the fee-for-service (FFS) system. However, few published studies have directly measured and compared how much a particular service is used in the 2 systems.2-4

One venue where care is documented for all Medicare beneficiaries is home health. All patients receiving care through CMS-certified home health agencies are required to have a comprehensive clinical assessment at the start and end of care, using the Outcome and Assessment Information Set (OASIS) instrument. For both FFS and MA beneficiaries, there is therefore a record not only that care occurred, but also of the clinical status at the start of care and of the functional outcome. Thus, home health provides a unique window through which the 2 programs can be compared.

The use of home health within Medicare is a topic ripe for review. Home health accounted for more than 5% of all FFS Medicare spending ($18.4 billion) in 2011,5 and an Institute of Medicine (IOM) report identified postacute care as the leading source of unexplained regional variation in healthcare spending via FFS.6,7 In a report to Congress, the Medicare Payment Advisory Commission (MedPAC) suggested that much of the variation in home health use reflected “fraud, waste, and abuse,” and noted that “the broad program standards and fragmented nature of the FFS program do not encourage effective targeting of the benefit.”5,8 Whether MA plans, with their incentives to avoid unnecessary care, are more effective at managing home health use is a natural next question. As a first step toward answering it, we compared home health utilization, regional variation, and clinical outcomes among beneficiaries enrolled in the MA and FFS programs.


Study Design

We identified all home health episodes among Medicare beneficiaries that started in 2010 and ended by December 31, 2011. We first performed a beneficiary-level analysis, comparing the probability (after adjusting for patient characteristics) that an FFS versus an MA beneficiary would have at least 1 home health episode. For those who received home health, we also compared the total number of days enrolled and 7 clinical outcomes that are publicly reported by CMS on the “Home Health Compare” website: improvement in the 3 measures of activities of daily living; acute care hospitalizations; and improvements in pain, dyspnea, and management of oral medications.9 Each of these measures is risk-adjusted (per CMS specifications) using the results of the OASIS assessment at the start of care.10 With the exception of the hospital utilization measure, outcomes are defined by comparing end-of-care and start-of-care OASIS assessments, and are defined only for patients who remain living in the community at the end of the episode.

We first compared each study endpoint as adjusted averages across the FFS and MA populations. Then, to better understand patterns of utilization differences between FFS and MA, we compared FFS and MA beneficiaries within each of the 306 hospital referral regions (HRRs). HRRs were chosen as the geographic unit of interest because the system partitions the country into mutually exclusive regional healthcare markets, which were felt to be the best available approximation for regions serviced by home health agencies.6

Data Sources

Using the 100% OASIS file, we grouped start-of-care and end-of-care assessments into episodes according to CMS specifications.9 OASIS episodes represent a complete cycle of care that ends only when a patient is hospitalized, dies, or is discharged to the community. An OASIS episode may encompass 1 or more 60-day billing episodes, as defined by the home health prospective payment system.8 To each OASIS episode (observation), we merged in data from the  100% denominator file and from a file containing Hierarchical Condition Category (HCC) scores (which represent the ratio of an individual’s expected cost to that of an average beneficiary).11 The Medicare health insurance claim number or the combination of Social Security number and date of birth were used as unique identifiers.  We also added demographic data from the American Community Survey, using 5-year estimates for 2007 to 2011, by linking via the zip code of each beneficiary.12

Because patients who were dually eligible for Medicare and Medicaid may have received home health benefits through Medicaid—which would not have been visible to us—we excluded dual-eligible beneficiaries from the analysis. All others were included.

Statistical Models

Nationwide comparison. We used logistic regression with robust standard errors to model the odds of receiving home health and the odds of each of the 7 clinical home health outcomes. We used a generalized linear model with a log link and Gaussian distribution to model the geometric mean number of days enrolled in home health (for those who received care). For models of utilization, risk adjustors included age, sex, HCC score, and 2 socioeconomic indicators from the 2007 to 2011 American Community Survey: deciles of median household income in the Zip Code Tabulation Area (ZCTA) and the proportion of households in the ZCTA with only 1 resident (among those with 1 or more residents aged ≥65), as surrogates for the beneficiary’s income and the probability that they live alone. For home health duration, we used 2 additional risk adjustors: whether the initial home health episode started after a hospitalization (postacute) and whether it followed a surgical procedure. For each clinical outcome, we used an extensive set of outcome-specific risk adjustors (derived from the baseline OASIS assessment) that is specified by CMS for the Home Health Compare program.10

Region-by-region analysis. To generate region-specific standardized utilization rates, we used generalized linear mixed models (with logit link for the probability of receiving home health and log link for home health duration) to model home health use as described for the national analysis, but added a random intercept for HRR. We then aggregated recycled empirical Bayes predictions to create a standardized utilization rate (or mean duration) for MA and FFS, for each of the 306 HRRs.13,14 We presented our results graphically by plotting each region’s FFS utilization rate against the MA utilization rate, and reported the correlation coefficients for MA versus FFS across the 306 HRRs.

In keeping with recent reports by MedPAC and the IOM, we quantified regional variation by reporting the ratio of the 90th percentile versus the 10th percentile of regional utilization.6 We reported these ratios separately for the FFS and MA populations.


After excluding 8,254,838 individuals dually eligible for Medicare and Medicaid, we identified 30,837,130 FFS beneficiaries and 10,594,658 MA beneficiaries. Baseline characteristics and unadjusted home health utilization rates are summarized in Table 1. Among the general population, MA patients were slightly older, whereas in the population using home health, the opposite was true. HCC scores were higher for MA in both populations.

Of those enrolled in FFS, 6.3% had at least 1 home health episode; of those in MA, 3.9% did. Among FFS beneficiaries who used home health, the average number of enrolled days was 75.8; among MA beneficiaries, it was 56.3 days. Although MA patients using home health had higher HCC scores than their FFS counterparts (suggesting a higher disease burden), they had less baseline disability according to each of 6 different measures at the start-of-care OASIS assessment. Home health more commonly started after a hospitalization and/or a surgical procedure for MA patients.

FFS Versus MA: Adjusted National Estimates

Regression results are shown in Tables 2 and 3. We estimated that among the general Medicare population, the odds of starting home health during 2010 were 1.82-fold higher for those enrolled in FFS versus MA, after adjusting for patient characteristics and socioeconomic indicators. Among those who did start home health in 2010, we estimated that the FFS patients were enrolled an average of 34% more days than their MA counterparts, after risk adjustment.

The relationship between FFS versus MA, in regard to clinical home health outcomes, was inconsistent, and observed differences were small in magnitude: FFS outcomes were better with regard to pain (odds ratio [OR], 1.08; 95% CI, 1.07-1.09), ambulation (OR, 1.01; 95% CI, 1.00-1.02; P = .03), and management of medications (OR, 1.06;  95% CI, 1.04-1.07); and MA outcomes were better with regard to bed transfer (OR, 0.98;  95% CI, 0.97-0.99), dyspnea (OR, 0.99;  95% CI, 0.98-1.00; P = .02), and hospital utilization (an adverse outcome) (OR, 1.16; 95% CI, 1.15-1.17). Improved bathing was not significantly related to FFS versus MA enrollment (OR, 1.00; 95% CI, 0.98-1.02). Hospital utilization, which measures whether home health ended in hospitalization rather than discharge to the community, was the outcome with the greatest difference (favoring MA). Of note, this outcome is not adjusted for duration of home health. Because FFS patients—who have longer home health episodes—spend more time at risk for hospitalization while enrolled, this relationship may be confounded.

Regional Variation

Among the 10% of HRRs (ie, 31 of 306 HRRs) with the highest proportions of FFS beneficiaries with 1 or more home health episodes (90th-percentile FFS), we estimated that 9.4% of all FFS beneficiaries used home health, whereas among the 31 HRRs with the lowest proportion (10th-percentile FFS), only 4.2% did. The ratio of the 90th percentile/10th percentile for FFS was, therefore, 2.2. For MA patients, the 90th percentile for use of home health was 6.3%, the 10th percentile was 2.2%, and the ratio was 2.8. The higher 90th/10th percentile ratio for MA means that by this measure, regional variation in home health use was higher for MA patients than for FFS patients.

An analogous evaluation of the duration of home health episodes yielded the following results: in the 90th-percentile HRR (with regard to average episode duration), mean duration was estimated to be 92 days for FFS and 67 days for MA. The 10th percentile was 39 days for FFS and 31 days for MA. The ratios of 90th/10th percentiles were 2.4 for FFS and 2.2 for MA.

Copyright AJMC 2006-2018 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
Welcome the the new and improved, the premier managed market network. Tell us about yourself so that we can serve you better.
Sign Up