Predicting Health Access During Critical Public Health Crises: An Analysis of Medical Office Responses to the COVID-19 Pandemic.

Journal of occupational and environmental medicine Pub Date : 2024-11-28 DOI:10.1097/JOM.0000000000003284

Nancy Zhong, Kirsten Wohlars, Mary Lee-Wong, Robert Promisloff, Niloofar Mirsaidi, Lawrence Amsel, Anthony Szema

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Abstract

Objectives: This study explores how ambulatory medical practices adapted their policies in response to the global COVID-19 crisis. Practice and provider characteristics were used to build an artificial intelligence model that predicts future medical practice closures during critical events.

Methods: We surveyed 261 outpatient medical practices and collected information on clinician age, gender, the protective measures implemented, closure status, and utilization of telemedicine services. These data were used to build an artificial intelligence model that predicts practice closure in future critical public health events.

Results: Responses varied by specialty, location, and physician characteristics. These factors predicted closure status in 85.45% of test cases.

Conclusion: This paper demonstrates that practice characteristics can assist in predicting medical practice responses to public health events.

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重大公共卫生危机期间的卫生可及性预测：医疗机构应对COVID-19大流行的分析

目的：本研究探讨门诊医疗实践如何调整其政策以应对全球COVID-19危机。实践和提供者特征被用于构建人工智能模型，该模型预测在关键事件期间未来的医疗实践关闭。方法：对261家门诊诊所进行调查，收集临床医生的年龄、性别、实施的保护措施、关闭情况和远程医疗服务的利用情况。这些数据被用来建立一个人工智能模型，预测未来重大公共卫生事件中诊所关闭的情况。结果：反应因专科、地点和医生特征而异。这些因素预测了85.45%的测试用例的关闭状态。结论：实践特征有助于预测医疗实践对公共卫生事件的反应。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Journal of occupational and environmental medicine

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