TY  - JOUR
AU  - Chen, Julie Yun
AU  - Chao, David
AU  - Wong, Samuel Yeung-shan
AU  - Tse, Tsui Yee Emily
AU  - Wan, Eric Yuk Fai
AU  - Tsang, Joyce Pui Yan
AU  - Leung, Maria Kwan Wa
AU  - Ko, Welchie
AU  - Li, Yim-chu
AU  - Chen, Catherine
AU  - Luk, Wan
AU  - Dao, Man-Chi
AU  - Wong, Michelle
AU  - Leung, Wing Mun
AU  - Lam, Cindy Lo Kuen
PY  - 2022
DA  - 2022/6/22
TI  - Morbidity Patterns in Primary Care in Hong Kong: Protocol for a Practice-Based Morbidity Survey
JO  - JMIR Res Protoc
SP  - e37334
VL  - 11
IS  - 6
KW  - morbidity survey
KW  - primary care
KW  - general practice
KW  - family medicine
AB  - Background: Up-to-date and accurate information about the health problems encountered by primary care doctors is essential to understanding the morbidity pattern of the community to better inform health care policy and practice. Morbidity surveys of doctors allow documentation of actual consultations, reflecting the patient’s reason for seeking care as well as the doctor’s diagnostic interpretation of the illness and management approach. Such surveys are particularly critical in the absence of a centralized primary care electronic medical record database. Objective: With the changing sociodemographic profile of the population and implementation of health care initiatives in the past 10 years, the aim of this study is to determine the morbidity and management patterns in Hong Kong primary care during a pandemic and compare the results with the last survey conducted in 2007-2008. Methods: This will be a prospective, practice-based survey of Hong Kong primary care doctors. Participants will be recruited by convenience and targeted sampling from both public and private sectors. Participating doctors will record the health problems and corresponding management activities for consecutive patient encounters during one designated week in each season of the year. Coding of health problems will follow the International Classification of Primary Care, Second Edition. Descriptive statistics will be used to calculate the prevalence of health problems and diseases as well as the rates of management activities (referral, investigation, prescription, preventive care). Nonlinear mixed effects models will assess the differences between the private and public sectors as well as factors associated with morbidity and management patterns in primary care. Results: The data collection will last from March 1, 2021, to August 31, 2022. As of April 2022, 176 doctor-weeks of data have been collected. Conclusions: The results will provide information about the health of the community and inform the planning and allocation of health care resources. Trial Registration: ClinicalTrials.gov NCT04736992; https://clinicaltrials.gov/ct2/show/NCT04736992 International Registered Report Identifier (IRRID): DERR1-10.2196/37334 
SN  - 1929-0748
UR  - https://www.researchprotocols.org/2022/6/e37334
UR  - https://doi.org/10.2196/37334
UR  - http://www.ncbi.nlm.nih.gov/pubmed/35731566
DO  - 10.2196/37334
ID  - info:doi/10.2196/37334
ER  -