Salar Ghamat, Mojtaba Araghi, Lauren E. Cipriano, Michael Silverman
{"title":"EXPRESS: Influencing Primary Care Antibiotic Prescription Behavior Using Financial Incentives","authors":"Salar Ghamat, Mojtaba Araghi, Lauren E. Cipriano, Michael Silverman","doi":"10.1177/10591478241264022","DOIUrl":null,"url":null,"abstract":"Antibiotic resistance is an ongoing public health crisis fueled by overuse and misuse of antibiotics. The goal of this paper is to examine the impact of action-based incentive payments on reducing inappropriate antibiotic prescriptions in primary care, where thirty to fifty percent of antibiotic prescriptions are inappropriate. Various financial incentive programs to reduce the rate of inappropriate antibiotic prescriptions have been implemented and studied empirically. However, there have not been analytical studies to evaluate payment model contract design features and the potential for payment models to impact diagnosis decision making. We develop a stylized physician compensation model to study the interaction between a payer and a provider. The payer offers a payment contract, with a bonus tied to the prescription, to maximize social welfare, considering total costs of providing care and social harm from antibiotic resistance. Given the contract offered and their own opportunity cost associated with factors such as fear of misdiagnosis and time spent explaining to patients why antibiotics are not indicated, the provider chooses whether or not to prescribe antibiotics to patients for whom antibiotics are not clinically indicated. We consider four cases: when diagnostic accuracy relies on symptom presentation vs. additional diagnostic testing and when the opportunity cost of not prescribing antibiotics is public vs. private information of the provider. When there is no information asymmetry, an action-based incentive payment can coordinate care and achieve the first-best policy, decreasing the rate of inappropriate prescribing, even when incentive payments can affect the diagnosis behavior. However, when the diagnosis depends on additional testing, the first-best policy results in fewer inappropriate antibiotic prescriptions, when the test has high specificity. Therefore, when an accurate technical diagnostic is available, a simple to implement action-based incentive payment can be effective in reducing inappropriate antibiotic prescribing. In the realistic setting where the provider’s opportunity cost is private information, an action-based incentive payment cannot eliminate inappropriate antibiotic prescribing. In these settings, the introduction of point of care diagnostics to aid in objective diagnostic criteria will reduce the unintended consequences of the contract.","PeriodicalId":20623,"journal":{"name":"Production and Operations Management","volume":null,"pages":null},"PeriodicalIF":4.8000,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Production and Operations Management","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1177/10591478241264022","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0
Abstract
Antibiotic resistance is an ongoing public health crisis fueled by overuse and misuse of antibiotics. The goal of this paper is to examine the impact of action-based incentive payments on reducing inappropriate antibiotic prescriptions in primary care, where thirty to fifty percent of antibiotic prescriptions are inappropriate. Various financial incentive programs to reduce the rate of inappropriate antibiotic prescriptions have been implemented and studied empirically. However, there have not been analytical studies to evaluate payment model contract design features and the potential for payment models to impact diagnosis decision making. We develop a stylized physician compensation model to study the interaction between a payer and a provider. The payer offers a payment contract, with a bonus tied to the prescription, to maximize social welfare, considering total costs of providing care and social harm from antibiotic resistance. Given the contract offered and their own opportunity cost associated with factors such as fear of misdiagnosis and time spent explaining to patients why antibiotics are not indicated, the provider chooses whether or not to prescribe antibiotics to patients for whom antibiotics are not clinically indicated. We consider four cases: when diagnostic accuracy relies on symptom presentation vs. additional diagnostic testing and when the opportunity cost of not prescribing antibiotics is public vs. private information of the provider. When there is no information asymmetry, an action-based incentive payment can coordinate care and achieve the first-best policy, decreasing the rate of inappropriate prescribing, even when incentive payments can affect the diagnosis behavior. However, when the diagnosis depends on additional testing, the first-best policy results in fewer inappropriate antibiotic prescriptions, when the test has high specificity. Therefore, when an accurate technical diagnostic is available, a simple to implement action-based incentive payment can be effective in reducing inappropriate antibiotic prescribing. In the realistic setting where the provider’s opportunity cost is private information, an action-based incentive payment cannot eliminate inappropriate antibiotic prescribing. In these settings, the introduction of point of care diagnostics to aid in objective diagnostic criteria will reduce the unintended consequences of the contract.
期刊介绍:
The mission of Production and Operations Management is to serve as the flagship research journal in operations management in manufacturing and services. The journal publishes scientific research into the problems, interest, and concerns of managers who manage product and process design, operations, and supply chains. It covers all topics in product and process design, operations, and supply chain management and welcomes papers using any research paradigm.