Prioritizing Hepatitis C Treatment in US Prisons

被引:24
作者
Ayer, Turgay [1 ]
Zhang, Can [2 ]
Bonifonte, Anthony [3 ]
Spaulding, Anne C. [4 ]
Chhatwal, Jagpreet [5 ]
机构
[1] Georgia Inst Technol, H Milton Stewart Sch Ind & Syst Engn, Atlanta, GA 30318 USA
[2] Duke Univ, Fuqua Sch Business, Durham, NC 27708 USA
[3] Denison Univ, Data Analyt Program, Granville, OH 43023 USA
[4] Emory Univ, Rollins Sch Publ Hlth, Atlanta, GA 30322 USA
[5] Harvard Med Sch, Inst Technol Assessment, Massachusetts Gen Hosp, Boston, MA 02114 USA
基金
美国国家科学基金会;
关键词
public health; hepatitis C; resource allocation; treatment prioritization; multi-armed bandits; agent-based simulation; VIRUS-INFECTION; UNITED-STATES; COST-EFFECTIVENESS; INDEX POLICIES; HIV; ALLOCATION; SOFOSBUVIR; PREVENTION; HEALTH; INDEXABILITY;
D O I
10.1287/opre.2018.1812
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Hepatitis C virus (HCV) prevalence in prison systems is 10 times higher than in the general population, and hence prison systems offer a unique opportunity to control the HCV epidemic. New HCV treatment drugs are very effective, but providing treatment to all inmates is prohibitively expensive, which precludes universal HCV treatment in prison systems. As such, current practice recommends prioritizing treatment based on clinical and incarceration-related factors, including disease staging, remaining sentence length, and injection drug use (IDU) status. However, there is controversy about how these factors should be incorporated because of the complicated trade-offs. In this study, we propose a restless bandit modeling framework to support hepatitis C treatment prioritization decisions in U.S. prisons. We first prove indexability for our problem and derive several structural properties of the well-known Whittle's index, based on which we derive a closed-form expression of the Whittle's index for patients with advanced liver disease. From the interpretation of this closed-form expression, we anticipate that the performance of the Whittle's index would degrade as the treatment capacity increases, and to address this limitation, we propose a capacity-adjusted closed-form index policy. We parameterize and validate our model using real-world data and published studies and test the performance of our proposed policy against several benchmark policies using a realistic agent-based simulation model. Our results shed light on several controversial health policy issues in hepatitis C treatment prioritization: (1) prioritization based on only liver health status, a commonly practiced policy, is suboptimal compared with many other policies; further, considering remaining sentence length of inmates and IDU status in addition to liver health status in prioritization decisions can lead to a significant performance improvement; (2) while usually prioritizing patients with longer sentence lengths is the right choice, prioritizing patients with shorter remaining sentence lengths may be preferable if the treatment capacity inside the prison system is not very tight and the linkage-to-care level outside the prison system is low; and (3) among patients with advanced liver disease, IDUs should not be prioritized unless their reinfection is very well controlled.
引用
收藏
页码:853 / 873
页数:21
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