Advancing Personalized Web-Based Decision Reports for Enhanced Patient Care

Although patient-reported outcomes (PROs) are increasingly growing in popularity, the assessment of the patient’s perspective of PRO-based applications is lacking. Results of a recent evaluation uncovered opportunities to refine a personalized web-based decision report and other patient-facing PRO applications, including filtering web-based dashboards and scalable educational supports to enable more independent patient use and understanding, according to a study published in Journal of Evaluation in Clinical Practice.¹

Sarah Pila, PhD

Credit: Northwestern University

PROs are designed to measure what matters most to patients, including health-related quality of life, physical function, and symptoms, and can support patient engagement and assist in more personalized care. For patients with total knee/hip replacement (TKR/THR), feedback from patients can help to support decision-making in combination with other clinical data.²

“Patient-facing PRO feedback may help with perioperative expectation setting and minimize post-TKR/THR dissatisfaction,” wrote Sarah Pila, PhD, research assistant professor of Medical Social Sciences at Northwestern University Feinberg School of Medicine, and colleagues. “Additionally, PRO-based feedback may help patients better understand their current and future health status and reduce related anxiety about undergoing treatment. Such benefits may have implications for reducing disparities since limited willingness to undergo surgery has been linked in some patient subgroups to persistent underutilization of TKR/THR.”

Investigators used a qualitative evaluation to determine patients’ acceptability of a web-based report for total hip and knee replacement to identify ways to better refine the report. The evaluation was embedded in a pragmatic cluster randomized trial.

Prior to their first visit to an orthopedic surgeon or physician assistant, patients completed electronic PROs, including standard measures for TKR/THR quality reporting, and self-reported information regarding sociodemographic characteristics, comorbidities, and pain in other knee and hip joints.

A total of 25 patients with knee and hip osteoarthritis were asked about their experiences using the personalized decision report for a surgical consultation. The report included current PRO scores of general physical health, pain, and function, information on alternative nonoperative treatment options, and tailored predictive postoperative PRO scores. Inductive and deductive coding was used to analyze interview data.

Ultimately, 3 major categories for evaluation were discovered: content of the report (ie what information was included), engagement with the report (ie points of interaction), and the presentation of data within the report (ie how information was displayed). Although patients generally liked the report, they were more likely to favor pages of the report based on where they were in their decision-making process.

Areas of confusion in data presentation included terminology, graph orientation, and interpretation of T-scores. They also noted educational support needs to better engage with the information provided.

Investigators wrote generalizability may be limited due to the sample’s limited diversity regarding race, ethnicity, and educational background. Additionally, those who participated in the interviews may not be representative of the total trial sample, as similar opt-in interviews are more likely to attract patients who either love or hate the process, rather than an “average” patient. COVID-19 may have further complicated findings due to the report receipt occasionally occurring after the office visit and therefore impacted how patients perceived the usefulness of the report.

“Opportunities for further tailoring of reports and scalable educational supports likely extend beyond this specific application and suggest directions for future research when designing and deploying personalized decision reports for clinical decision-making,” investigators concluded.

References

1. ^{Pila S, Stern BZ, Rothrock NE, Franklin PD. Evaluating a web-based personalized decision report for total knee or hip replacement: Lessons learned from patients [published online ahead of print, 2023 Jun 14]. J Eval Clin Pract. 2023;10.1111/jep.13887. doi:10.1111/jep.13887}
2. ^{Franklin PD, Zheng H, Bond C, Lavallee DC. Translating clinical and patient-reported data to tailored shared decision reports with predictive analytics for knee and hip arthritis. Qual Life Res. 2021; 30(11): 3171-3178.}