Examining perspectives on the adoption and use of computer-based patient-reported outcomes among clinicians and health professionals: a Q methodology study

Abstract

Objective To determine factors that influence the adoption and use of patient-reported outcomes (PROs) in the electronic health record (EHR) among users. Materials and Methods Q methodology, supported by focus groups, semistructured interviews, and a review of the literature was used for data collection about opinions on PROs in the EHR. An iterative thematic analysis resulted in 49 statements that study participants sorted, from most unimportant to most important, under the following condition of instruction: “What issues are most important or most unimportant to you when you think about the adoption and use of patient-reported outcomes within the electronic health record in routine clinical care?” Using purposive sampling, 50 participants were recruited to rank and sort the 49 statements online, using HTMLQ software. Principal component analysis and Varimax rotation were used for data analysis using the PQMethod software. Results Participants were mostly physicians (24%) or physician/researchers (20%). Eight factors were identified. Factors included the ability of PROs in the EHR to enable: efficient and reliable use; care process improvement and accountability; effective and better symptom assessment; patient involvement for care quality; actionable and practical clinical decisions; graphical review and interpretation of results; use for holistic care planning to reflect patients’ needs; and seamless use for all users. Discussion The success of PROs in the EHR in clinical settings is not dependent on a “one size fits all” strategy, demonstrated by the diversity of viewpoints identified in this study. A sociotechnical approach for implementing PROs in the EHR may help improve its success and sustainability. Conclusions PROs in the EHR are most important to users when the technology is used to improve patient outcomes. Future research must focus on the impact of embedding this EHR functionality on care processes.

Facilitators and barriers to implementing electronic patient-reported outcome and experience measures in a health care setting: a systematic review

“…The full details of the study’s characteristics are presented in Table 1 . All studies were published after 2012, and conducted in eight countries: Netherlands [ 8 , 31 , 33 – 35 ], Finland [ 42 ], Denmark [ 26 ], United Stated of America [ 7 , 9 , 24 , 27 , 28 , 30 , 32 , 38 , 40 , 41 , 43 ], Italy [ 4 ], Canada [ 25 , 27 , 36 , 37 ], Germany [ 39 ], and the United Kingdom [ 29 ]. The majority of studies (22/24) investigated ePROMs in isolation, one study investigated only ePREMs [ 4 ], and one study investigated both ePROMs/ePREMs [ 25 ].…”

“…The majority of studies (22/24) investigated ePROMs in isolation, one study investigated only ePREMs [ 4 ], and one study investigated both ePROMs/ePREMs [ 25 ]. The most common clinical setting was oncology, with 29% (7/24) of the included studies [ 8 , 33 , 34 , 36 – 39 , 42 ], followed by general hospital settings (3/24, 12%) [ 4 , 32 , 35 ]. Study designs were primarily qualitative (13/24) or mixed methods (7/24), but also included four observational quantitative studies.…”

“…Study designs were primarily qualitative (13/24) or mixed methods (7/24), but also included four observational quantitative studies. Across both qualitative and mixed-methods study designs, qualitative data were collected through interviews in 12 studies [ 24 – 26 , 28 – 30 , 32 – 34 , 38 – 40 , 43 ], focus groups in six studies [ 7 , 9 , 25 , 29 , 32 , 36 ], and open-ended survey questions in five studies [ 4 , 8 , 31 , 35 , 38 ]. In studies that included a quantitative component, quantitative data were collected via close-ended survey questions in 11 studies [ 8 , 27 , 31 – 38 , 40 ], a workflow audit in only one study [ 40 ], and Q-sorting in only one study [ 32 ].…”

“…Design quality and packaging of ePROMs were prominent constructs identified in 17 studies. Several studies have noted the benefits of ePROMs in providing an insightful, easy to read patient summary or snapshot [ 9 , 29 , 32 , 35 , 36 , 43 ], along with graphical visualisations to easily see trends [ 8 , 28 – 30 , 32 , 35 , 38 , 39 , 41 , 43 ]. It was also considered important to ensure patients received ePROM results promptly after appointments [ 26 ].…”

“…On the other hand, a significant barrier emerged when it was difficult to visualise data or obtain a summary due to limited visualisation options [ 30 , 34 ]. The inability to distinguish potentially abnormal results due to a lack of clearly defined threshold scores was considered a barrier [ 9 , 24 , 29 , 32 , 36 , 43 ]. In contrast, ePROM systems which clearly identified results that exceeded threshold scores and supplied real-time notifications of those requiring urgent responses was considered to support implementation success [ 30 , 35 ].…”