One challenge lies in the collection of PRO data in a consistent manner. “You have to ensure that data is valid, reliable, contextualized, and interpreted correctly," Fuller explained. “But, as PRO data is often collected across many points in time, there is a risk that patients aren't engaged consistently." For example, there are difficulties in ensuring that post-surgery joint replacement patients will reliably participate in data collection over the course of a full year.
An even greater challenge, Fuller noted, is applying the conclusions drawn from PRO measures to make direct improvements to the care delivery system. “We may have the PRO data, but without sufficient clinical interpretation and clinical context they may not be considered valid," he added. Altering reimbursement models to reward quality could change practice patterns, but for PROs to play a role in determining those changes, healthcare leaders must first be convinced that they're a significant component of quality.
The standardization of PRO measures remains the largest barrier to implementation. Many physicians now accept a number of broad-based, disease-agnostic PRO measures, like the Treatment Satisfaction Questionnaire for Medication (TQSM) and the Short Form Health Survey (SF-36). However, there is limited consensus around a number of disease-specific measures, which must often be validated for highly specific patient populations. The Patient-Reported Outcomes Measurement Information System (PROMIS) has led efforts to standardize self-reported measures for a variety of diseases.