MBAX 6332 Week 7 Health Policy Equity Analysis Example

Even Rules, Uneven Landing: An Equity Analysis of Medicare's Hospital-Acquired Condition Reduction Program Across Three Groups the Program Reaches Differently

Student Name

Walden University

MBAX 6332: Health Policy and Systems Thinking

Instructor Name

Month Day, Year

Even Rules, Uneven Landing: An Equity Analysis of Medicare's Hospital-Acquired Condition Reduction Program Across Three Groups the Program Reaches Differently

Premise

A payment rule applied the same way to every hospital can land unevenly on the hospitals and patients it reaches. This analysis follows the Hospital-Acquired Condition Reduction Program to three groups it affects differently, each representing a different way a policy can miss people: patients of hospitals the program penalizes disproportionately, patients whose harms the program does not count and patients in hospitals the program does not cover at all. Its author works in a composite hospital's quality office. Each section follows the same order: who the group is, how the program reaches them, what the evidence shows and what cannot be known. Braveman (2006) frames equity as a concern with avoidable health differences that follow social advantage, and the analysis asks whether the program narrows or widens such disparities.

Group 1: Patients of Hospitals Penalized Unevenly

The first group is patients of safety-net hospitals, which serve a disproportionate share of low-income and uninsured patients. The program reaches them through their hospitals' finances. Rajaram et al. (2015) report that safety-net hospitals were penalized in the program's first year at a rate roughly eight points above other hospitals. A later study of more than 3,000 hospitals by Sankaran et al. (2019) reached a similar conclusion from a different angle: the hospitals penalized had more patients of low socioeconomic status, and the penalty bought no measurable clinical gain, so the program risked widening inequity by drawing money from hospitals serving disadvantaged patients. With slim operating margins, a safety-net hospital may fund the penalty by cutting staff or services.

A comparison with another Medicare program is instructive. The Hospital Readmissions Reduction Program, after criticism of its effect on safety-net hospitals, was changed by the 21st Century Cures Act to compare hospitals within peer groups defined by their share of patients eligible for both Medicare and Medicaid. The hospital-acquired condition program has no comparable adjustment. Whether such an adjustment would be appropriate is debated, since some argue that adjusting for patient mix excuses poorer care; but the absence of any adjustment means the penalty falls more heavily where patients are poorer.

What cannot be known from available data is how much of the difference reflects worse care, sicker patients or more testing. Each explanation implies a different response.

Group 2: Patients Whose Harms Are Not Counted

The second group is patients harmed in ways the program does not measure. The program counts a specific list of conditions: certain infections and the patient safety indicators in its composite measure. Harms outside that list, such as many medication errors, delirium or harms that appear only after discharge, do not affect a hospital's score. Neither do infections that are never tested for and therefore never confirmed. Haut and Pronovost (2011) noted that outcome measures depend on how intensively hospitals look for complications.

This section must begin with what cannot be known: by definition, the program's data say nothing about harms it does not count. Sheetz et al. (2019) offer an indirect clue. In a Michigan surgical registry, conditions the program targeted declined after it began, but conditions it did not target declined more, suggesting that the program did not draw improvement efforts away from uncounted harms, though it also did not add to them. Whether the same holds for medical patients, or for patients whose infections were never cultured, is unknown.

Group 3: Patients in Hospitals the Program Does Not Cover

The third group is patients in hospitals outside the program. The statute covers only hospitals paid through Medicare's standard per-discharge inpatient rates, 42 U.S.C. § 1395ww(p), which excludes critical access hospitals, the small rural hospitals that serve many isolated communities, along with children's and cancer hospitals, and Maryland hospitals, which operate under a separate state arrangement. Patients in critical access hospitals receive whatever protection the program offers only indirectly, through national attention to infection prevention. Rural patients are therefore less covered by this lever than urban ones. Whether that matters depends on whether the program works at all; if it does not, exclusion costs little.

How the Groups Overlap

The three groups are not separate populations. A low-income patient in a rural area may be served by a safety-net hospital in the nearest city for surgery and by a critical access hospital closer to home for a later admission, and may suffer a harm the program does not count in either. Overlap matters because the program's effects compound for the same people: their larger hospital faces more frequent penalties, their local hospital is outside the program and some of their harms are invisible to it. An equity analysis that treats each group alone would understate how much the program's reach depends on where a patient lives and how much money they have.

What the Three Groups Show Together

Each group is missed in a different way: penalized unevenly, not counted or not covered. Together they suggest that the program's benefits, if any, accrue mainly to patients in larger hospitals with the resources to improve, while its costs fall more heavily on hospitals serving poorer patients. A program meant to protect all Medicare patients may widen the gap it should narrow. The recommendation in this course, reporting testing intensity, addresses part of the first group's problem by separating vigilance from harm; it does not address the second or third groups, which would require broader measures and coverage.

References

Braveman, P. (2006). Health disparities and health equity: Concepts and measurement. Annual Review of Public Health, 27, 167-194. https://doi.org/10.1146/annurev.publhealth.27.021405.102103

Haut, E. R., & Pronovost, P. J. (2011). Surveillance bias in outcomes reporting. JAMA, 305(23), 2462-2463. https://doi.org/10.1001/jama.2011.822

Hospital-acquired conditions, 42 U.S.C. § 1395ww(p) (2024).

Rajaram, R., Chung, J. W., Kinnier, C. V., Barnard, C., Mohanty, S., Pavey, E. S., McHugh, M. C., & Bilimoria, K. Y. (2015). Hospital characteristics associated with penalties in the Centers for Medicare & Medicaid Services Hospital-Acquired Condition Reduction Program. JAMA, 314(4), 375-383. https://doi.org/10.1001/jama.2015.8609

Sankaran, R., Sukul, D., Nuliyalu, U., Gulseren, B., Engler, T. A., Arntson, E., Zlotnick, H., Dimick, J. B., & Ryan, A. M. (2019). Changes in hospital safety following penalties in the US Hospital Acquired Condition Reduction Program: Retrospective cohort study. BMJ, 366, l4109. https://doi.org/10.1136/bmj.l4109

Sheetz, K. H., Dimick, J. B., Englesbe, M. J., & Ryan, A. M. (2019). Hospital-acquired condition reduction program is not associated with additional patient safety improvement. Health Affairs, 38(11), 1858-1865. https://doi.org/10.1377/hlthaff.2018.05504