Long-term spill-over impact of COVID-19 on health and healthcare of people with non-communicable diseases: a study protocol for a population-based cohort and health economic study. Issue 8 (16th August 2022)

• Record Type: Journal Article
• Authors: Youn, Hin Moi; Quan, Jianchao; Mak, Ivy Lynn; Yu, Esther Yee Tak; Lau, Chak Sing; Ip, Mary Sau Man; Tang, Sydney Chi Wai; Wong, Ian Chi Kei; Lau, Kui Kai; Lee, Michael Shing Fung; Ng, Carmen S; Grépin, Karen Ann; Chao, David Vai Kiong; Ko, Welchie Wai Kit; Lam, Cindy Lo Kuen; Wan, Eric Yuk Fai
• Is Part Of: BMJ open. Volume 12:Issue 8(2022)
• Publication Date: 2022-08-16
• Subjects: COVID-19 -- PUBLIC HEALTH -- HEALTH ECONOMICS -- PRIMARY CARE; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2022-063150
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Introduction: The COVID-19 pandemic has a significant spill-over effect on people with non-communicable diseases (NCDs) over the long term, beyond the direct effect of COVID-19 infection. Evaluating changes in health outcomes, health service use and costs can provide evidence to optimise care for people with NCDs during and after the pandemic, and to better prepare outbreak responses in the future. Methods and analysis: This is a population-based cohort study using electronic health records of the Hong Kong Hospital Authority (HA) CMS, economic modelling and serial cross-sectional surveys on health service use. This study includes people aged ≥18 years who have a documented diagnosis of diabetes mellitus, hypertension, cardiovascular disease, cancer, chronic respiratory disease or chronic kidney disease with at least one attendance at the HA hospital or clinic between 1 January 2010 and 31 December 2019, and without COVID-19 infection. Changes in all-cause mortality, disease-specific outcomes, and health services use rates and costs will be assessed between pre-COVID-19 and-post-COVID-19 pandemic or during each wave using an interrupted time series analysis. The long-term health economic impact of healthcare disruptions during the COVID-19 pandemic will be studied using microsimulation modelling. Multivariable Cox proportional hazards regression and Poisson/negative binomial regression will be used to evaluate the effect of different modes of supplementary care on health outcomes. Ethics and dissemination: The study was approved by the institutional review board of the University of Hong Kong, the HA Hong Kong West Cluster (reference number UW 21–297). The study findings will be disseminated through peer-reviewed publications and international conferences.