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Medical Documentation in Low- and Middle-income Countries: Lessons Learned from Implementing Specialized Charting
Andrew M Ferry1,2, Matthew J Davis1,2, Ewa Rumprecht3
1Division of Plastic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Tex.
Background:
The implementation of electronic health record (EHR) software at healthcare facilities in low- and middle-income countries (LMICs) is limited by financial and technological constraints. Smile Train, the world's largest cleft charity, developed a cleft treatment EHR system, Smile Train Express (STX), and distributed it to their partnered institutions. The purpose of this study was to investigate trends in medical documentation practices amongst Smile Train-partner institutions to characterize the impact that specialized EHR software has on medical documentation practices at healthcare facilities in LMICs.
Methods:
Surveys were administered electronically to 843 Smile Train-partnered institutions across 68 LMICs. The survey inquired about institutions' internet connection, documentation methods used during patient encounters, rationale for using said methods, and documentation methods for cloud-based storage of healthcare data. Institutions were grouped by economic and geographic subgroups for analysis.
Results:
A total of 162 institutions (19.2%) responded to the survey. Most institutions employed paper charting (64.2%) or institutional EHR software (25.9%) for data entry during a patient encounter with the latter's use varying significantly across geographical subgroups (P = 0.01). STX was used by 18 institutions (11.1%) during a patient encounter. Workflow was the most frequently cited reason for institutions to employ their entry method during a patient encounter (51.4%).
Conclusions:
The provision of STX to partnered institutions influenced medical documentation practices at several institutions; however, regulations and guidelines have likely limited its complete integration into clinical workflows. Further studies are needed to characterize trends in medical documentation in LMICs at a more granular level.
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