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Abrams MP, Weiner J, Piske M, Enns B, Krebs E, Zang X, Nosyk B, Meisel ZF. Translating and disseminating a localised economic model to support implementation of the 'Ending the HIV Epidemic' initiative to public health policymakers. EVIDENCE & POLICY : A JOURNAL OF RESEARCH, DEBATE AND PRACTICE 2023; 19:554-571. [PMID: 38313044 PMCID: PMC10836837 DOI: 10.1332/174426421x16875142087569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/06/2024]
Abstract
Background Despite significant progress in HIV treatment and prevention, the US remains far from its goal of 'Ending the HIV Epidemic' by 2030. Economic models using local data can synthesise the evidence to help policymakers allocate HIV resources efficiently, but persistent research-to-practice gaps remain. Little is known about how to facilitate the use of economic modelling data among local public health policymakers in real-world settings. Aims and objectives To explore the dissemination of results from a locally-calibrated economic model for HIV prevention and treatment and identify the factors influencing potential uptake of the model for public health decision making at the local level. Methods Four virtual focus groups with 26 local health department policymakers in Baltimore, Miami, Seattle, and New York City were held between July 2020 and May 2021. Qualitative content analysis of transcripts identified key themes around using the localised economic model in policy decisions. Results Participants were interested in using local data in their decisions to allocate resources for HIV prevention/treatment. Six themes emerged: 1) importance of understanding local policy context; 2) health equity considerations; 3) using evidence to support current priorities; 4) difficulty of changing strategies, even incrementally; 5) bang for the incremental buck (efficiency) vs. previous impact; and 6) community values. Conclusion and relevance To optimise acceptance and use of results from economic models, researchers should engage with local community members and public health decision makers early to understand budgetary and community priorities. Participants prioritised evidence that supports their existing strategies, considers budgets and funding streams, and improves health equity; however, real-world budget constraints and conflicting interests serve as barriers to implementing model recommendations and reaching national goals.
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Affiliation(s)
| | | | - Micah Piske
- Centre for Health Evaluation and Outcome Sciences, Canada
| | - Benjamin Enns
- Centre for Health Evaluation and Outcome Sciences, Canada
| | - Emanuel Krebs
- Centre for Health Evaluation and Outcome Sciences, Canada
| | | | - Bohdan Nosyk
- Centre for Health Evaluation and Outcome Sciences and Simon Fraser University, Canada
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Johnson K, Biddell CB, Hassmiller Lich K, Swann J, Delamater P, Mayorga M, Ivy J, Smith RL, Patel MD. Use of Modeling to Inform Decision Making in North Carolina during the COVID-19 Pandemic: A Qualitative Study. MDM Policy Pract 2022; 7:23814683221116362. [PMID: 35923388 PMCID: PMC9340948 DOI: 10.1177/23814683221116362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Accepted: 07/05/2022] [Indexed: 11/17/2022] Open
Abstract
Background. The COVID-19 pandemic has popularized computer-based decision-support models, which are commonly used to inform decision making amidst complexity. Understanding what organizational decision makers prefer from these models is needed to inform model development during this and future crises. Methods. We recruited and interviewed decision makers from North Carolina across 9 sectors to understand organizational decision-making processes during the first year of the COVID-19 pandemic (N = 44). For this study, we identified and analyzed a subset of responses from interviewees (n = 19) who reported using modeling to inform decision making. We used conventional content analysis to analyze themes from this convenience sample with respect to the source of models and their applications, the value of modeling and recommended applications, and hesitancies toward the use of models. Results. Models were used to compare trends in disease spread across localities, estimate the effects of social distancing policies, and allocate scarce resources, with some interviewees depending on multiple models. Decision makers desired more granular models, capable of projecting disease spread within subpopulations and estimating where local outbreaks could occur, and incorporating a broad set of outcomes, such as social well-being. Hesitancies to the use of modeling included doubts that models could reflect nuances of human behavior, concerns about the quality of data used in models, and the limited amount of modeling specific to the local context. Conclusions. Decision makers perceived modeling as valuable for informing organizational decisions yet described varied ability and willingness to use models for this purpose. These data present an opportunity to educate organizational decision makers on the merits of decision-support modeling and to inform modeling teams on how to build more responsive models that address the needs of organizational decision makers. Highlights Organizations from a diversity of sectors across North Carolina (including public health, education, business, government, religion, and public safety) have used decision-support modeling to inform decision making during COVID-19.Decision makers wish for models to project the spread of disease, especially at the local level (e.g., individual cities and counties), and to help estimate the outcomes of policies.Some organizational decision makers are hesitant to use modeling to inform their decisions, stemming from doubts that models could reflect nuances of human behavior, concerns about the accuracy and precision of data used in models, and the limited amount of modeling available at the local level.
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Affiliation(s)
- Karl Johnson
- Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Caitlin B. Biddell
- Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kristen Hassmiller Lich
- Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Julie Swann
- Department of Industrial and Systems Engineering, North Carolina State University, Atlanta, GA, USA
| | - Paul Delamater
- Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Maria Mayorga
- Department of Industrial and Systems Engineering, North Carolina State University, Atlanta, GA, USA
| | - Julie Ivy
- Department of Industrial and Systems Engineering, North Carolina State University, Atlanta, GA, USA
| | - Raymond L. Smith
- Department of Engineering, College of Engineering and Technology, East Carolina University, Greenville, NC, USA
| | - Mehul D. Patel
- Department of Emergency Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Pouwels XGLV, Sampson CJ, Arnold RJG. Opportunities and Barriers to the Development and Use of Open Source Health Economic Models: A Survey. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2022; 25:473-479. [PMID: 35365297 DOI: 10.1016/j.jval.2021.10.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 09/02/2021] [Accepted: 10/05/2021] [Indexed: 06/14/2023]
Abstract
OBJECTIVES Health economic (HE) models are routinely used to support health policy and resource allocation decisions but are often considered "black boxes" that may be prone to error and bias. Open source models (OSMs) have been advocated to increase the transparency, credibility, and reuse of HE models. Previous studies have demonstrated interest in OSMs among the health economics and outcomes research community, but the number of OSMs remains low. METHODS We conducted an online survey of ISPOR (the leading professional society for health economics and outcomes research) members' perspectives on the usefulness of OSMs and barriers to their development and implementation. RESULTS Respondents (N = 230) included academics (27%), pharmaceutical (or related) industry representatives (23%), health research or consulting representatives (21%), governmental or nonprofit agency representatives (10%), and others (19%). Respondents were generally not familiar with barriers to the development and adoption of OSMs. Most agreed that OSMs would improve transparency (92%), efficiency (76%), and HE model reuse (86%) and promote confidence in using HE models (75%). The use of OSMs by health technology assessment authorities was considered a very important indicator of the usefulness of OSMs by 49% of respondents. Three-quarters of respondents perceived legal concerns and the ability to transfer data as important barriers to the development and use of OSMs. CONCLUSIONS Respondents believe that OSMs could increase the transparency, efficiency, and credibility of HE models, but that several barriers hamper their widespread adoption. Our results suggest that fundamental changes may be needed across the health economics and outcomes research community if OSMs are to become widely adopted.
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Affiliation(s)
- Xavier G L V Pouwels
- Department of Health Technology and Services Research, Faculty of Behavioural, Management, and Social Sciences, University of Twente, Enschede, The Netherlands
| | | | - Renée J G Arnold
- National Institutes of Health/National Heart, Lung, and Blood Institute, Bethesda, MD, USA; Master of Public Health Program, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Arnold Consultancy & Technology, LLC, New York, NY, USA.
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Zang X, Mah C, Linh Quan AM, Min JE, Armstrong WS, Behrends CN, Del Rio C, Dombrowski JC, Feaster DJ, Kirk GD, Marshall BDL, Mehta SH, Metsch LR, Pandya A, Schackman BR, Shoptaw S, Strathdee SA, Krebs E, Nosyk B. Human Immunodeficiency Virus transmission by HIV Risk Group and Along the HIV Care Continuum: A Contrast of 6 US Cities. J Acquir Immune Defic Syndr 2022; 89:143-150. [PMID: 34723929 PMCID: PMC8752472 DOI: 10.1097/qai.0000000000002844] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 10/04/2021] [Indexed: 02/03/2023]
Abstract
BACKGROUND Understanding the sources of HIV transmission provides a basis for prioritizing HIV prevention resources in specific geographic regions and populations. This study estimated the number, proportion, and rate of HIV transmissions attributable to individuals along the HIV care continuum within different HIV transmission risk groups in 6 US cities. METHODS We used a dynamic, compartmental HIV transmission model that draws on racial behavior-specific or ethnic behavior-specific and risk behavior-specific linkage to HIV care and use of HIV prevention services from local, state, and national surveillance sources. We estimated the rate and number of HIV transmissions attributable to individuals in the stage of acute undiagnosed HIV, nonacute undiagnosed HIV, HIV diagnosed but antiretroviral therapy (ART) naïve, off ART, and on ART, stratified by HIV transmission group for the 2019 calendar year. RESULTS Individuals with undiagnosed nonacute HIV infection accounted for the highest proportion of total transmissions in every city, ranging from 36.8% (26.7%-44.9%) in New York City to 64.9% (47.0%-71.6%) in Baltimore. Individuals who had discontinued ART contributed to the second highest percentage of total infections in 4 of 6 cities. Individuals with acute HIV had the highest transmission rate per 100 person-years, ranging from 76.4 (58.9-135.9) in Miami to 160.2 (85.7-302.8) in Baltimore. CONCLUSION These findings underline the importance of both early diagnosis and improved ART retention for ending the HIV epidemic in the United States. Differences in the sources of transmission across cities indicate that localized priority setting to effectively address diverse microepidemics at different stages of epidemic control is necessary.
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Affiliation(s)
- Xiao Zang
- Department of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island, United States
| | - Cassandra Mah
- Faculty of Health Sciences, Simon Fraser University; Burnaby, British Columbia, Canada
| | - Amanda My Linh Quan
- Faculty of Health Sciences, Simon Fraser University; Burnaby, British Columbia, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Jeong Eun Min
- Center for Health Evaluation and Outcome Sciences; Vancouver, British Columbia, Canada
| | - Wendy S Armstrong
- Division of Infectious Diseases, Department of Medicine, Emory University, Atlanta, GA, USA
| | - Czarina N Behrends
- Department of Healthcare Policy and Research, Weill Cornell Medical College, New York City, New York, United States
| | - Carlos Del Rio
- Division of Infectious Diseases, Department of Medicine, Emory University, Atlanta, GA, USA
| | - Julia C Dombrowski
- Department of Medicine, Division of Allergy and Infectious Disease, University of Washington, Seattle, Washington, United States
| | - Daniel J Feaster
- Department of Public Health Sciences, Leonard M. Miller School of Medicine, University of Miami, Miami, Florida, United States
| | - Gregory D. Kirk
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States
| | - Brandon DL Marshall
- Department of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island, United States
| | - Shruti H Mehta
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States
| | - Lisa R Metsch
- Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York City, New York, United States
| | - Ankur Pandya
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States
| | - Bruce R Schackman
- Department of Healthcare Policy and Research, Weill Cornell Medical College, New York City, New York, United States
| | - Steven Shoptaw
- School of Medicine, University of California Los Angeles, Los Angeles, California, United States
| | - Steffanie A Strathdee
- School of Medicine, University of California San Diego, La Jolla, California, United States
| | - Emanuel Krebs
- Faculty of Health Sciences, Simon Fraser University; Burnaby, British Columbia, Canada
- Center for Health Evaluation and Outcome Sciences; Vancouver, British Columbia, Canada
| | - Bohdan Nosyk
- Faculty of Health Sciences, Simon Fraser University; Burnaby, British Columbia, Canada
- Center for Health Evaluation and Outcome Sciences; Vancouver, British Columbia, Canada
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Krebs E, Nosyk B. Cost-Effectiveness Analysis in Implementation Science: a Research Agenda and Call for Wider Application. Curr HIV/AIDS Rep 2021; 18:176-185. [PMID: 33743138 PMCID: PMC7980756 DOI: 10.1007/s11904-021-00550-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/23/2021] [Indexed: 11/28/2022]
Abstract
Purpose of Review Cost-effectiveness analysis (CEA) can help identify the trade-offs decision makers face when confronted with alternative courses of action for the implementation of public health strategies. Application of CEA alongside implementation scientific studies remains limited. We aimed to identify areas for future development in order to enhance the uptake and impact of model-based CEA in implementation scientific research. Recent Findings Important questions remain about how to broadly implement evidence-based public health interventions in routine practice. Establishing population-level implementation strategy components and distinct implementation phases, including planning for implementation, the time required to scale-up programs, and sustainment efforts required to maintain them, can help determine the data needed to quantify each of these elements. Model-based CEA can use these data to determine the added value associated with each of these elements across systems, settings, population subgroups, and levels of implementation to provide tailored guidance for evidence-based public health action. There is a need to integrate implementation science explicitly into CEA to adequately capture diverse real-world delivery contexts and make detailed, informed recommendations on the aspects of the implementation process that provide good value. Summary We describe examples of how model-based CEA can integrate implementation scientific concepts and evidence to help tailor evaluations to local context. We also propose six distinct domains for methodological advancement in order to enhance the uptake and impact of model-based cost-effectiveness analysis in implementation scientific research.
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Affiliation(s)
- Emanuel Krebs
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive V5A 1S6, Burnaby, British Columbia, Canada
| | - Bohdan Nosyk
- Faculty of Health Sciences, Simon Fraser University, 8888 University Drive V5A 1S6, Burnaby, British Columbia, Canada.
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