Development and Validation of the Healthcare Expenditure and Location Dynamics in Acute Febrile Illness (HEAL-AFI) Tool: A Community-Based Cohort Study With a Special Focus on Dengue and Chikungunya in the Urban Slum of Delhi, India

急性发热性疾病医疗支出和地域动态(HEAL-AFI)工具的开发与验证:一项以印度德里城市贫民窟登革热和基孔肯雅热为重点的社区队列研究

阅读:1

Abstract

INTRODUCTION: Cost-of-illness (COI) studies quantify the economic burden of diseases, yet existing tools often lack standardized cost domains and contextual adaptation. We developed and validated the Cost of Healthcare Expenditure Questionnaire (CHEQ), a generic tool, and its adaptation for acute febrile illness (HEAL-AFI), tailored to dengue and chikungunya in Delhi slum communities. METHODOLOGY: Conducted in a resettlement colony of Northeast Delhi, this study followed a multistage process with five iterative rounds. Round 1 involved item generation after the literature review. In Round 2, eight experts assessed content validity using Lawshe's method. Round 3 reassessed content validity and translated the tool. Round 4 tested face validity and feasibility among 32 participants and eight interviewers. Round 5 evaluated reliability via test-retest after 12 days using Cohen's κ, intraclass correlation coefficients (ICCs), and Cronbach's α. Data were collected on KoboCollect and analyzed in IBM SPSS Statistics for Windows, version 26.0. RESULTS: Expert review retained 74 items for CHEQ (76 for HEAL-AFI), with CVI improving from 0.78 (Round 2) to 0.92 (Round 3). Face validity demonstrated good clarity and ease of use, with a mean administration time of 24.3 ± 5.1 minutes (T1) and 23.7 ± 4.8 minutes (T2). Reliability was substantial for categorical variables (κ = 0.63-0.79; agreement 72-84%) and excellent for continuous variables (ICC = 0.82-0.94). Internal consistency was high across domains (Cronbach's α = 0.78-0.89). CONCLUSION: CHEQ and HEAL-AFI are validated, reliable, and feasible tools for capturing household healthcare expenditures. CHEQ provides a standardized framework across diseases, while HEAL-AFI contextualizes costs for acute febrile illnesses (AFIs) with geospatial integration. These tools can strengthen COI research and may guide equitable health policy.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。