A Simple and Interpretable Mortality-Based Value Metric for Condition- or Procedure-Specific Hospital Performance Reporting
Objective: To develop a simple, interpretable value metric (VM) to assess the value of care of hospitals for specific procedures or conditions by operationalizing the value equation: Value = Quality/Cost. Patients and Methods: The present study was conducted on a retrospective cohort from 2015 to 20...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-02-01
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| Series: | Mayo Clinic Proceedings: Innovations, Quality & Outcomes |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2542454822000716 |
| _version_ | 1797903491623026688 |
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| author | Benjamin D. Pollock, PhD Sarah K. Meier, PhD Kari S. Snaza, MBA Nilay D. Shah, PhD Sean C. Dowdy, MD Henry H. Ting, MD, MPH |
| author_facet | Benjamin D. Pollock, PhD Sarah K. Meier, PhD Kari S. Snaza, MBA Nilay D. Shah, PhD Sean C. Dowdy, MD Henry H. Ting, MD, MPH |
| author_sort | Benjamin D. Pollock, PhD |
| collection | DOAJ |
| description | Objective: To develop a simple, interpretable value metric (VM) to assess the value of care of hospitals for specific procedures or conditions by operationalizing the value equation: Value = Quality/Cost. Patients and Methods: The present study was conducted on a retrospective cohort from 2015 to 2018 drawn from the 100% US sample of Medicare inpatient claims. The final cohort comprised 637,341 consecutive inpatient encounters with a cancer-related Medicare Severity-Diagnosis Related Grouping and 13,307 consecutive inpatient encounters with the International Classification of Diseases, Ninth Revision or International Classification of Diseases, Tenth Revision procedure code for partial or total gastrectomy. Claims-based demographic and clinical variables were used for risk adjustment, including age, sex, year, dual eligibility, reason for Medicare entitlement, and binary indicators for each of the Elixhauser comorbidities used in the Elixhauser mortality index. Risk-adjusted 30-day mortality and risk-adjusted encounter-specific costs were combined to form the VM, which was calculated as follows: number needed to treat = 1/(Mortalitynational − Mortalityhospital), and VM = number needed to treat × risk-adjusted cost per encounter. Results: Among hospitals with better-than-average 30-day cancer mortality rates, the cost to prevent 1 excess 30-day mortality for an inpatient cancer encounter ranged from $71,000 (best value) to $1.4 billion (worst value), with a median value of $543,000. Among hospitals with better-than-average 30-day gastrectomy mortality rates, the cost to prevent 1 excess 30-day mortality for an inpatient gastrectomy encounter ranged from $710,000 (best value) to $95 million (worst value), with a median value of $1.8 million. Conclusion: This simple VM may have utility for interpretable reporting of hospitals’ value of care for specific conditions or procedures. We found substantial inter- and intrahospital variation in value when defined as the costs of preventing 1 excess cancer or gastrectomy mortality compared with the national average, implying that hospitals with similar quality of care may differ widely in the value of that care. |
| first_indexed | 2024-04-10T09:33:50Z |
| format | Article |
| id | doaj.art-08b7f2df5f944f059fe9c947c5ec2fa9 |
| institution | Directory Open Access Journal |
| issn | 2542-4548 |
| language | English |
| last_indexed | 2024-04-10T09:33:50Z |
| publishDate | 2023-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Mayo Clinic Proceedings: Innovations, Quality & Outcomes |
| spelling | doaj.art-08b7f2df5f944f059fe9c947c5ec2fa92023-02-18T04:17:19ZengElsevierMayo Clinic Proceedings: Innovations, Quality & Outcomes2542-45482023-02-017118A Simple and Interpretable Mortality-Based Value Metric for Condition- or Procedure-Specific Hospital Performance ReportingBenjamin D. Pollock, PhD0Sarah K. Meier, PhD1Kari S. Snaza, MBA2Nilay D. Shah, PhD3Sean C. Dowdy, MD4Henry H. Ting, MD, MPH5Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Jacksonville, Florida; Correspondence: Address to Benjamin D. Pollock, PhD, MSPH, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic – Stabile 750N, 4500 San Pablo Road, Jacksonville, FL 32224.Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MinnesotaEnterprise Quality, Mayo Clinic, Rochester, MinnesotaDelta Airlines, Atlanta, GeorgiaRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota; Enterprise Quality, Mayo Clinic, Rochester, MinnesotaDelta Airlines, Atlanta, GeorgiaObjective: To develop a simple, interpretable value metric (VM) to assess the value of care of hospitals for specific procedures or conditions by operationalizing the value equation: Value = Quality/Cost. Patients and Methods: The present study was conducted on a retrospective cohort from 2015 to 2018 drawn from the 100% US sample of Medicare inpatient claims. The final cohort comprised 637,341 consecutive inpatient encounters with a cancer-related Medicare Severity-Diagnosis Related Grouping and 13,307 consecutive inpatient encounters with the International Classification of Diseases, Ninth Revision or International Classification of Diseases, Tenth Revision procedure code for partial or total gastrectomy. Claims-based demographic and clinical variables were used for risk adjustment, including age, sex, year, dual eligibility, reason for Medicare entitlement, and binary indicators for each of the Elixhauser comorbidities used in the Elixhauser mortality index. Risk-adjusted 30-day mortality and risk-adjusted encounter-specific costs were combined to form the VM, which was calculated as follows: number needed to treat = 1/(Mortalitynational − Mortalityhospital), and VM = number needed to treat × risk-adjusted cost per encounter. Results: Among hospitals with better-than-average 30-day cancer mortality rates, the cost to prevent 1 excess 30-day mortality for an inpatient cancer encounter ranged from $71,000 (best value) to $1.4 billion (worst value), with a median value of $543,000. Among hospitals with better-than-average 30-day gastrectomy mortality rates, the cost to prevent 1 excess 30-day mortality for an inpatient gastrectomy encounter ranged from $710,000 (best value) to $95 million (worst value), with a median value of $1.8 million. Conclusion: This simple VM may have utility for interpretable reporting of hospitals’ value of care for specific conditions or procedures. We found substantial inter- and intrahospital variation in value when defined as the costs of preventing 1 excess cancer or gastrectomy mortality compared with the national average, implying that hospitals with similar quality of care may differ widely in the value of that care.http://www.sciencedirect.com/science/article/pii/S2542454822000716 |
| spellingShingle | Benjamin D. Pollock, PhD Sarah K. Meier, PhD Kari S. Snaza, MBA Nilay D. Shah, PhD Sean C. Dowdy, MD Henry H. Ting, MD, MPH A Simple and Interpretable Mortality-Based Value Metric for Condition- or Procedure-Specific Hospital Performance Reporting Mayo Clinic Proceedings: Innovations, Quality & Outcomes |
| title | A Simple and Interpretable Mortality-Based Value Metric for Condition- or Procedure-Specific Hospital Performance Reporting |
| title_full | A Simple and Interpretable Mortality-Based Value Metric for Condition- or Procedure-Specific Hospital Performance Reporting |
| title_fullStr | A Simple and Interpretable Mortality-Based Value Metric for Condition- or Procedure-Specific Hospital Performance Reporting |
| title_full_unstemmed | A Simple and Interpretable Mortality-Based Value Metric for Condition- or Procedure-Specific Hospital Performance Reporting |
| title_short | A Simple and Interpretable Mortality-Based Value Metric for Condition- or Procedure-Specific Hospital Performance Reporting |
| title_sort | simple and interpretable mortality based value metric for condition or procedure specific hospital performance reporting |
| url | http://www.sciencedirect.com/science/article/pii/S2542454822000716 |
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