Joshi Anushree, Panchamia Jallavi, Pandya Apurvakumar
Department of Health Policy, Management and Behavioral Science, Indian Institute of Public Health Gandhinagar, Gandhinagar, Gujarat, India.
JMIR Res Protoc. 2024 Dec 9;13:e59621. doi: 10.2196/59621.
Retaining specialist physicians in rural parts of India poses a fundamental challenge, which affects the health care system's functionality and provision of standard health care services. There has been an acute shortfall of specialist physicians in the fields of medicine, pediatrics, obstetrics and gynecology, and surgery at rural community health centers. This necessitates urgent policy focus to address the shortages and design effective rural retention strategies. In this study, which uses a discrete choice experiment (DCE), individuals choose from multiple-choice preferences that resemble hypothetical job descriptions.
DCEs are a quantitative approach to assessing several aspects of job selection. This study aims to develop a detailed plan of a DCE method used to determine specialist physicians' job choices. This protocol outlines the DCE method, which uses an exploratory sequential mixed methods research design to understand specialist physicians' preferences and design reward packages that would effectively motivate them to work in underserved regions.
The qualitative phase of the study involved identifying job attributes and their corresponding levels for the DCE. We followed a meticulous process, which included reviewing relevant literature, performing qualitative pilot work, conducting in-depth individual interviews, and consulting with medical and health experts. The quantitative phase involved generating a D-efficient orthogonal fractional factorial design using Ngene software to create choice scenarios using the identified job factors and their corresponding levels. The generated choice scenarios were blocked into 6 versions in 6 blocks. The DCE was undertaken among final-year postgraduate medical residents and specialist physicians from several health care facilities in Rajasthan. Various statistical models will be applied to explore the response variability and quantify the trade-offs that participants are willing to make for nonmonetary features as a substitute for adjustments in the monetary attribute.
After the ethics committee's approval of the study, the qualitative data collection phase occurred from September to December 2021, while the quantitative phase took place from May to August 2022. Six attributes and 14 levels were identified and established through qualitative surveys. The experimental design resulted in 36 choice situations, which were grouped into 6 blocks. The preliminary investigation demonstrated that the instrument was valid and reliable. Statistical data analysis has been initiated, and the principal findings are expected to be disseminated in January 2025.
The protocol provides a systematic framework to assess specialist physicians' preferences regarding working in rural health care centers. This research has the potential to substantially influence the future of rural health care by laying the foundation for understanding specialist physicians' choices, which will help design future incentive schemes, policy interventions, and research.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/59621.
在印度农村地区留住专科医生是一项根本性挑战，这影响着医疗保健系统的功能以及标准医疗服务的提供。农村社区卫生中心在医学、儿科、妇产科和外科等领域的专科医生严重短缺。这就需要政策紧急关注以解决短缺问题并制定有效的农村留住策略。在本研究中，采用离散选择实验（DCE），让个体从类似于假设工作描述的多项选择偏好中进行选择。
DCE是一种评估工作选择多个方面的定量方法。本研究旨在制定一个详细的DCE方法计划，用于确定专科医生的工作选择。本方案概述了DCE方法，该方法采用探索性序列混合方法研究设计来了解专科医生的偏好，并设计能有效激励他们在服务不足地区工作的薪酬方案。
研究的定性阶段涉及确定DCE的工作属性及其相应水平。我们遵循了一个细致的过程，包括查阅相关文献、开展定性试点工作、进行深入的个人访谈以及咨询医学和健康专家。定量阶段涉及使用Ngene软件生成一个D效率正交分式析因设计，以利用确定的工作因素及其相应水平创建选择情景。生成的选择情景被分成6个区组的6个版本。DCE在拉贾斯坦邦几家医疗机构的医学研究生最后一年学员和专科医生中进行。将应用各种统计模型来探索反应变异性，并量化参与者愿意为非货币特征做出的权衡，以替代货币属性的调整。
在伦理委员会批准该研究后，定性数据收集阶段于2021年9月至12月进行，而定量阶段于2022年5月至8月进行。通过定性调查确定并确立了6个属性和14个水平。实验设计产生了36种选择情况，分为6个区组。初步调查表明该工具有效且可靠。统计数据分析已启动，主要研究结果预计于2025年1月发布。
该方案提供了一个系统框架，以评估专科医生对在农村医疗中心工作的偏好。这项研究有可能通过为理解专科医生的选择奠定基础，从而对农村医疗保健的未来产生重大影响，这将有助于设计未来的激励计划、政策干预措施和研究。
国际注册报告识别号（IRRID）：DERR1-10.2196/59621。
