Improving Patient Experience and Primary Care Quality for Patients With Complex Chronic Disease Using the Electronic Patient-Reported Outcomes Tool: Adopting Qualitative Methods Into a User-Centered Design Approach

Abstract

Background Many mHealth technologies do not meet the needs of patients with complex chronic disease and disabilities (CCDDs) who are among the highest users of health systems worldwide. Furthermore, many of the development methodologies used in the creation of mHealth and eHealth technologies lack the ability to embrace users with CCDD in the specification process. This paper describes how we adopted and modified development techniques to create the electronic Patient-Reported Outcomes (ePRO) tool, a patient-centered mHealth solution to help improve primary health care for patients experiencing CCDD. Objective This paper describes the design and development approach, specifically the process of incorporating qualitative research methods into user-centered design approaches to create the ePRO tool. Key lessons learned are offered as a guide for other eHealth and mHealth research and technology developers working with complex patient populations and their primary health care providers. Methods Guided by user-centered design principles, interpretive descriptive qualitative research methods were adopted to capture user experiences through interviews and working groups. Consistent with interpretive descriptive methods, an iterative analysis technique was used to generate findings, which were then organized in relation to the tool design and function to help systematically inform modifications to the tool. User feedback captured and analyzed through this method was used to challenge the design and inform the iterative development of the tool. Results Interviews with primary health care providers (n=7) and content experts (n=6), and four focus groups with patients and carers (n=14) along with a PICK analysis—Possible, Implementable, (to be) Challenged, (to be) Killed—guided development of the first prototype. The initial prototype was presented in three design working groups with patients/carers (n=5), providers (n=6), and experts (n=5). Working group findings were broken down into categories of what works and what does not work to inform modifications to the prototype. This latter phase led to a major shift in the purpose and design of the prototype, validating the importance of using iterative codesign processes. Conclusions Interpretive descriptive methods allow for an understanding of user experiences of patients with CCDD, their carers, and primary care providers. Qualitative methods help to capture and interpret user needs, and identify contextual barriers and enablers to tool adoption, informing a redesign to better suit the needs of this diverse user group. This study illustrates the value of adopting interpretive descriptive methods into user-centered mHealth tool design and can also serve to inform the design of other eHealth technologies. Our approach is particularly useful in requirements determination when developing for a complex user group and their health care providers. ...

Evidence-Based Evaluation of eHealth Interventions: Systematic Literature Review

“…Table 1 provides a compilation of the phases along with the area of focus and key activities within each phase. [20,[21][22][23]25].  Define the objectives of the to-be-developed technology [20,24].…”

“… Define the objectives of the to-be-developed technology [20,24]. Contextual Inquiry  Identify the end-users and stakeholders to define and analyze the characteristics of the context the technology is going to be implemented [20,21,[23][24][25].…”

“…Prioritize the critical values of the technology derived from the end-users and stakeholders' needs [12,[22][23][24][25]. Requirements specification…”

“…Translate the values into functional and technical requirements that frame the final design and the technology development [12,[23][24][25]. Pre-testing phase Conduct short-term trials…”

“…Provide evidence of efficacy of the technology [12,25,26].  Measure factors such as optimal intensity, timing, safety, feasibility, usability, intervention content, and logistic issues [21,22,26].…”