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Operational Recommendations for Scarce Resource Allocation in a Public Health Crisis.

ABSTRACT: The coronavirus disease 2019 pandemic may require rationing of various medical resources if demand exceeds supply. Theoretical frameworks for resource allocation have provided much needed ethical guidance, but hospitals still need to address objective practicalities and legal vetting to operationalize scarce resource allocation schemata. To develop operational scarce resource allocation processes for public health catastrophes, including the coronavirus disease 2019 pandemic, five health systems in Maryland formed a consortium-with diverse expertise and representation-representing more than half of all hospitals in the state. Our efforts built on a prior statewide community engagement process that determined the values and moral reference points of citizens and health-care professionals regarding the allocation of ventilators during a public health catastrophe. Through a partnership of health systems, we developed a scarce resource allocation framework informed by citizens' values and by general expert consensus. Allocation schema for mechanical ventilators, ICU resources, blood components, novel therapeutics, extracorporeal membrane oxygenation, and renal replacement therapies were developed. Creating operational algorithms for each resource posed unique challenges; each resource's varying nature and underlying data on benefit prevented any single algorithm from being universally applicable. The development of scarce resource allocation processes must be iterative, legally vetted, and tested. We offer our processes to assist other regions that may be faced with the challenge of rationing health-care resources during public health catastrophes.

SUBMITTER: Ehmann MR

PROVIDER: S-EPMC7521357 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Operational Recommendations for Scarce Resource Allocation in a Public Health Crisis.

Ehmann Michael R MR Zink Elizabeth K EK Levin Amanda B AB Suarez Jose I JI Belcher Harolyn M E HME Daugherty Biddison Elizabeth L EL Doberman Danielle J DJ D'Souza Karen K Fine Derek M DM Garibaldi Brian T BT Gehrie Eric A EA Golden Sherita H SH Gurses Ayse P AP Hill Peter M PM Hughes Mark T MT Kahn Jeffrey P JP Koch Colleen G CG Marx Jason J JJ Meisenberg Barry R BR Natterman Jeffrey J Rushton Cynda H CH Sapirstein Adam A Selinger Stephen R SR Stephens R Scott RS Toner Eric S ES Unguru Yoram Y van Stone Maureen M Kachalia Allen A

Chest 20200928 3

The coronavirus disease 2019 pandemic may require rationing of various medical resources if demand exceeds supply. Theoretical frameworks for resource allocation have provided much needed ethical guidance, but hospitals still need to address objective practicalities and legal vetting to operationalize scarce resource allocation schemata. To develop operational scarce resource allocation processes for public health catastrophes, including the coronavirus disease 2019 pandemic, five health systems ...[more]

PMID: 32991873

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Project description:BackgroundTo better meet people's growing demand for medical and health services, 21 cities in Guangdong Province were involved in the reform of public hospitals in 2017. This paper evaluates the equity and efficiency of public hospitals' health resource allocation in Guangdong Province and explores ways to change the current situation.MethodsData were collected from the Guangdong Health Statistical Yearbook 2016-2020 and Guangdong Statistical Yearbook 2017-2021. The Gini coefficient (G), Theil index (T), and health resource density index (HRDI) were used to measure the equity of health resource allocation. An improved three-stage DEA method was applied in efficiency evaluation. The entropy weight method was employed to calculate the weight of different indicators to obtain a comprehensive indicator representing the overall volume of health resources in each city. A two-dimensional matrix was drawn between the HRDI of the comprehensive indicator and efficiency and the per capita government financial subsidies and efficiency to observe the coordination of equity and efficiency across regions.ResultsFrom 2016 to 2020, the G of public hospital, bed, and health technician allocation by population remained below 0.2, while that by geographical area ranged from 0.4 to 0.6; the G of government financial subsidies by population was above 0.4, while that by geographical area was greater than 0.7. The results for T showed that inequality mainly comes from intraregional differences, and the Pearl River Delta contributes most to the overall differences. Although the HRDI of the Pearl River Delta is far greater than that of other regions, obvious differences exist across cities in the region. Only 38.1% of cities were found to be efficient in 2020. The Pearl River Delta was in the first quadrant, and the other three regions were in the third quadrant, accounting for a large proportion.ConclusionThe equity of government financial subsidies allocation was the worst, and there were distinct regional differences in the geographical distribution of health resources. The development of healthcare within the Pearl River Delta was highly unbalanced. The development of healthcare was uneven between the Pearl River Delta, eastern, western, and mountainous regions. In addition, most cities in the eastern, western, and mountainous regions bore the dual pressures of relatively insufficient health resources and inefficiency.

Project description:Background. The complexity of decision science models may prevent their use to assist in decision making. User-centered design (UCD) principles provide an opportunity to engage end users in model development and refinement, potentially reducing complexity and increasing model utilization in a practical setting. We report our experiences with UCD to develop a modeling tool for cancer control planners evaluating cancer survivorship interventions. Design. Using UCD principles (described in the article), we developed a dynamic cohort model of cancer survivorship for individuals with female breast, colorectal, lung, and prostate cancer over 10 y. Parameters were obtained from the National Program of Cancer Registries and peer-reviewed literature, with model outcomes captured in quality-adjusted life-years and net monetary benefit. Prototyping and iteration were conducted with structured focus groups involving state cancer control planners and staff from the Centers for Disease Control and Prevention and the American Public Health Association. Results. Initial feedback highlighted model complexity and unclear purpose as barriers to end user uptake. Revisions addressed complexity by simplifying model input requirements, providing clear examples of input types, and reducing complex language. Wording was added to the results page to explain the interpretation of results. After these updates, feedback demonstrated that end users more clearly understood how to use and apply the model for cancer survivorship resource allocation tasks. Conclusions. A UCD approach identified challenges faced by end users in integrating a decision aid into their workflow. This approach created collaboration between modelers and end users, tailoring revisions to meet the needs of the users. Future models developed for individuals without a decision science background could leverage UCD to ensure the model meets the needs of the intended audience.HighlightsModel complexity and unclear purpose are 2 barriers that prevent lay users from integrating decision science tools into their workflow.Modelers could integrate the user-centered design framework when developing a model for lay users to reduce complexity and ensure the model meets the needs of the users.

Project description:ObjectivesWhen healthcare systems are overwhelmed, accurate assessments of patients' predicted mortality risks are needed to ensure effective allocation of scarce resources. Organ dysfunction scores can serve this essential role, but their evaluation in this context has been limited so far. In this study, we sought to assess the performance of three organ dysfunction scores in both critically ill adults and children at clinically relevant mortality thresholds and timeframes for resource allocation and compare it with two published prioritization schemas.DesignRetrospective observational cohort study.SettingThree large academic medical centers in the United States.PatientsCritically ill adults and children.InterventionsNone.Measurements and main resultsWe calculated the daily Sequential Organ Failure Assessment score in adults and the Pediatric Logistic Organ Dysfunction 2 score and the Pediatric Sequential Organ Failure Assessment score in children. There were 49,290 (11.6% mortality) and 19,983 children (2.5% mortality) included in the analysis. Both the Sequential Organ Failure Assessment and Pediatric Sequential Organ Failure Assessment scores had adequate discrimination across relevant timeframes and adequate distribution across relevant mortality thresholds. Additionally, we found that the only published state prioritization schema that includes pediatric and adult patients had poor alignment of mortality risks, giving adults a systematic advantage over children.ConclusionsIn the largest analysis of organ dysfunction scores in a general population of critically ill adults and children to date, we found that both the Sequential Organ Failure Assessment and Pediatric Sequential Organ Failure Assessment scores had adequate performance across relevant mortality thresholds and timeframes for resource allocation. Published prioritization schemas that include both pediatric and adult patients may put children at a disadvantage. Furthermore, the distribution of patient and mortality risk in the published schemas may not adequately stratify patients for some high-stakes allocation decisions. This information may be useful to bioethicists, healthcare leaders, and policy makers who are developing resource allocation policies for critically ill patients.

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Operational Recommendations for Scarce Resource Allocation in a Public Health Crisis.

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Operational Recommendations for Scarce Resource Allocation in a Public Health Crisis.

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