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A Simple and Interpretable Mortality-Based Value Metric for Condition- or Procedure-Specific Hospital Performance

Benjamin D Pollock1, Sarah K Meier2, Kari S Snaza3

  • 1Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Jacksonville, Florida.

Mayo Clinic Proceedings. Innovations, Quality & Outcomes
|December 12, 2022
PubMed
Summary
This summary is machine-generated.

A new value metric (VM) assesses hospital care value using quality and cost. It revealed significant differences in the cost to prevent mortality for cancer and gastrectomy patients, highlighting variations in healthcare value.

Keywords:
CMS, Centers for Medicare and Medicaid ServicesMIPS, Merit-based Incentive Payment SystemMS-DRG, Medicare Severity-Diagnosis Related GroupingMSPB, Medicare Spending per BeneficiaryNNT, number needed to treatVM, value metric

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Area of Science:

  • Health Services Research
  • Health Economics
  • Medical Informatics

Background:

  • Assessing hospital value of care is crucial for healthcare efficiency.
  • Existing metrics may lack interpretability for specific conditions or procedures.
  • The value equation (Value = Quality/Cost) provides a framework for evaluation.

Purpose of the Study:

  • To develop a simple, interpretable value metric (VM) for hospital care.
  • To operationalize the value equation (Value = Quality/Cost) for specific conditions.
  • To assess inter- and intrahospital variations in healthcare value.

Main Methods:

  • Retrospective cohort study using 2015-2018 Medicare inpatient claims.
  • Included cancer-related Medicare Severity-Diagnosis Related Groupings and gastrectomy procedures.
  • Risk-adjusted 30-day mortality and costs were used to calculate the VM.

Main Results:

  • For cancer care, the cost to prevent one excess 30-day mortality ranged from $71,000 to $1.4 billion (median $543,000).
  • For gastrectomy, this cost ranged from $710,000 to $95 million (median $1.8 million).
  • Substantial inter- and intrahospital variations in value were observed.

Conclusions:

  • The developed VM offers a simple, interpretable way to report hospital value.
  • Significant variations in value exist even among hospitals with similar quality.
  • This metric can aid in understanding and improving healthcare value for specific procedures.