Responsive, Resilient, Restored: A Review of the Role of Data Analytics in Healthcare Amidst Disease Outbreaks
综述了医疗保健与数据分析交叉领域的文献，研究了数据分析方法如何提升医疗系统应对疫情时的响应、韧性和恢复能力，并识别了研究空白与未来方向。
We synthesize the literature at the intersection of healthcare and data analytics and examine the use of data analytics methods to improve responsiveness, resilience, and restoration capabilities of healthcare systems when dealing with pandemic/epidemic outbreaks. We develop a conceptual framework to help us organize, analyze, and identify gaps in current research. Analysis of the literature helps us conclude that most of the work in the field supports healthcare institutions improve in terms of responsiveness and resilience, but more focus is needed to help systems restore to normalcy. We identify research gaps such as the development of robust disease surveillance tools based on novel technologies like AI, evaluating the benefits of coordinating limited resources within regional healthcare systems, and reducing risk within the complex healthcare supply chain. Moreover, based on our findings and interactions with practitioners we identify the need to channel more efforts on developing research that supports healthcare institutions as they seek to return to normalcy in the post pandemic world. Health systems are now operating with fewer resources while dealing with an increased number of patients who present multiple comorbidities, while dealing with ongoing shortages of critical supplies. These challenging conditions have resulted in significant financial losses for several healthcare systems post-pandemic. We propose future research directions that can provide a research agenda to scholars in our field seeking to enhance the responsiveness, resilience, and restoration of healthcare systems in preparation for future disease outbreaks.