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Forum for Health Economics & Policy

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Better Quality of Care or Healthier Patients? Hospital Utilization by Medicare Advantage and Fee-for-Service Enrollees

Lauren Hersch Nicholas
  • Corresponding author
  • Institute for Social Research and Center for Healthcare Outcomes and Policy, University of Michigan, 426 Thompson St, 4205 MISQ, Ann Arbor, MI 48103
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Published Online: 2013-05-15 | DOI: https://doi.org/10.1515/fhep-2012-0037

Abstract

Do differences in rates of use among managed care and Fee-for-Service Medicare beneficiaries reflect selection bias or successful care management by insurers? I demonstrate a new method to estimate the treatment effect of insurance status on health care utilization. Using clinical information and risk-adjustment techniques on data on acute admission that are unrelated to recent medical care, I create a proxy measure of unobserved health status. I find that positive selection accounts for between one-quarter and one-third of the risk-adjusted differences in rates of hospitalization for ambulatory care sensitive conditions and elective procedures among Medicare managed care and Fee-for-Service enrollees in 7 years of Healthcare Cost and Utilization Project State Inpatient Databases from Arizona, Florida, New Jersey and New York matched to Medicare enrollment data. Beyond selection effects, I find that managed care plans reduce rates of potentially preventable hospitalizations by 12.5 per 1000 enrollees (compared to mean of 46 per 1000) and reduce annual rates of elective admissions by 4 per 1000 enrollees (mean 18.6 per 1000).

Keywords: hospital utilization; managed care; Medicare; selection bias

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About the article

Corresponding author: Lauren Hersch Nicholas, Institute for Social Research and Center for Healthcare Outcomes and Policy, University of Michigan, 426 Thompson St, 4205 MISQ, Ann Arbor, MI 48103, Phone: +734-764-2562, e-mail:


Published Online: 2013-05-15

Published in Print: 2013-01-01


Considerable research has been done to validate these hospitalizations as quality indicators (UCSF-Stanford 2001; Billings 2003). These indicators have been widely used to assess quality of care in FFS Medicare and for the under-65 population.

Prior to the introduction of the drug benefit, there was little FFS coverage for outpatient prescription drugs. Following the recent introduction of the Medicare prescription drug benefit, beneficiaries enrolled in MMC plans have had access to drug benefits with lower monthly premiums and less cost sharing on average than the stand-alone drug benefits available to those in FFS Medicare (Carino 2006). Plans can also rebate all or part of enrollees’ Part B premiums.

New and more comprehensive measures of risk adjustment are currently used. There is lack of consensus as to whether favorable selection into MMC has increased (Brown et al. 2011) or decreased (McWilliams et al. 2012) in response to the new policies.

Separate indicators for MMC enrollees were not reported in New Jersey prior to 2003.

MMC patients are flagged using the state-specific flag for MMC; Medicare Risk in Arizona, Medicare HMO or PPO in Florida, and Medicare HMO in New Jersey and New York.

HCUP data are de-identified, so hospitalizations cannot be matched to specific enrollees in the BASF file.

Since chronic conditions are identified in the BASF data using a claims-based algorithm, these indicators cannot be reliably calculated for MMC enrollees. Hip fractures are the only marker condition included in the BASF, precluding a more comprehensive analysis. In this analysis, I treat all beneficiaries who have ever met the claims criteria for diagnosis (including current and previous year), as having a comorbid condition. Hip fractures occur during the study year only.


Citation Information: Forum for Health Economics and Policy, ISSN (Online) 1558-9544, ISSN (Print) 2194-6191, DOI: https://doi.org/10.1515/fhep-2012-0037.

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