Sheri Chernetsky Tejedor1,2,3, Joe Sharma3,4, Danielle C Lavallee5, William B Lober5, Heather L Evans6. 1. Department of Medicine, Emory University School of Medicine, Atlanta, Georgia. 2. Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, Georgia. 3. Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia. 4. Department of Surgery, Emory University School of Medicine, Atlanta, Georgia. 5. Department of Surgery, University of Washington, Seattle, Washington. 6. Department of Surgery, Medical University of South Carolina, Charleston, South Carolina.
Abstract
Background: A landscape analysis of mobile health (mHealth) applications and published literature related to their use in surgical site infection (SSI) detection and surveillance was conducted by the Assessing Surgical Site Infection Surveillance Technologies (ASSIST) investigators. Methods: The literature review focused on post-discharge SSI detection or tracking by caregivers or patients using mHealth technology. This report is unique in its review across both commercial and research-based mHealth apps. Apps designed for long-term wound tracking and those focused on care coordination and scheduling were excluded. A structured evaluation framework was used to assess the operational, technical, and policy features of the apps. Results: Of the 10 apps evaluated, only two were in full clinical use. A variety of data were captured by the apps including wound photographs (eight apps), wound measurements (three apps), dressing assessments (two apps), physical activity metrics (three apps), medication adherence (three apps) as well as structured surveys, signs, and symptoms. Free-text responses were permitted by at least two apps. The extent of integration with the native electronic health record system was variable. Conclusion: The examination of rapidly evolving technologies is challenged by lack of standard evaluative methods, such as those more commonly used in clinical research. This review is unique in its application of a structured evaluation framework across both commercial and research-based mHealth apps.
Background: A landscape analysis of mobile health (mHealth) applications and published literature related to their use in surgical site infection (SSI) detection and surveillance was conducted by the Assessing Surgical Site Infection Surveillance Technologies (ASSIST) investigators. Methods: The literature review focused on post-discharge SSI detection or tracking by caregivers or patients using mHealth technology. This report is unique in its review across both commercial and research-based mHealth apps. Apps designed for long-term wound tracking and those focused on care coordination and scheduling were excluded. A structured evaluation framework was used to assess the operational, technical, and policy features of the apps. Results: Of the 10 apps evaluated, only two were in full clinical use. A variety of data were captured by the apps including wound photographs (eight apps), wound measurements (three apps), dressing assessments (two apps), physical activity metrics (three apps), medication adherence (three apps) as well as structured surveys, signs, and symptoms. Free-text responses were permitted by at least two apps. The extent of integration with the native electronic health record system was variable. Conclusion: The examination of rapidly evolving technologies is challenged by lack of standard evaluative methods, such as those more commonly used in clinical research. This review is unique in its application of a structured evaluation framework across both commercial and research-based mHealth apps.
Entities:
Keywords:
health information technology; mobile health (mHealth); patient generated health data (PGHD); post-operative infection; surgical site infection; surveillance
Authors: Martin Hensher; Paul Cooper; Sithara Wanni Arachchige Dona; Mary Rose Angeles; Dieu Nguyen; Natalie Heynsbergh; Mary Lou Chatterton; Anna Peeters Journal: J Am Med Inform Assoc Date: 2021-06-12 Impact factor: 4.497