Patient-Centered Development and Evaluation of a Mobile Wound Tracking Tool

Abstract

Surgical site infections (SSI) are a common, costly and serious problem following surgery, affecting at least 500,000 people annually. Most infections now occur after hospital discharge, placing the burden of recognizing problems and seeking care on patients who are ill-prepared for that responsibility, resulting in reduced quality of life, preventable readmission, and enormous costs on the healthcare system. Yet, few efforts have been made to systematically engage patients in early identification of SSIs to reduce their impact. I will describe a novel approach to addressing this problem: a patient-centered mobile health (mHealth) “app” that enables patients to serially track wound symptoms and photos, and securely communicate with their providers. To this end, I first present a needs assessment among surgical patients and providers. I then describe an iterative process of engagement with these stakeholders resulting in design considerations generalizable to post-acute care mHealth (of which wound tracking is a part). Finally, I evaluate a key consideration of any tool intended to be used clinically—that the data collected (i.e. serial wound photos/symptom data) aid in timely diagnosis of SSI and can support appropriate management decisions. My work has implications beyond a surgical wound tracking tool. As healthcare shifts to the outpatient setting, and patients increasingly expect to access care electronically, new applications that are “patient-centered” yet also embraced by providers will be required. A key stumbling block to provider acceptance is demonstrating clinical utility of patient-generated health data collected by these applications. Addressing these shifts, my work helps map the design space of post-acute care mHealth, taking into account both areas of potential agreement and conflict between patients and providers. In addition, I propose a new heuristic method to aid design of patient-centered health IT. Finally, I demonstrate the clinical value of novel datastreams made possible by this new class of applications, characterized both by more frequent data collection (e.g. signs/symptoms) and novel data types (e.g. photos). I apply these research contributions to strengthen the development of mPOWEr, a real-world wound-tracking tool that seeks to improve clinical outcomes as well as patients’ experience on their way to those outcomes.