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What Is the Relationship Between Clinician-reported and Patient-reported Outcomes in Orthopaedic Surgery?
Megha R Aepala1, Sara Kiani2, Teja Yeramosu3
1School of Medicine, University of California, San Francisco, CA, USA.
Background:
Patient-reported outcome measures (PROMs) and clinician-reported outcome measures (CROMs) are designed to capture different dimensions of treatment response: the patient's experience and the clinician's assessment, respectively. Because of that, some degree of discordance between them is expected. However, the nature and magnitude of PROM-CROM correlations across orthopaedic subspecialties have not been systematically characterized. Understanding where they converge and where they diverge may help clinicians and researchers select instrument pairings that capture complementary dimensions of treatment response for different musculoskeletal conditions.
Questions/Purposes:
(1) Do CROMs correlate differently with condition-specific PROMs compared with general health PROMs? (2) Do PROMs show distinct correlations with hard CROMs (objective, performance-based measures without patient-reported outcomes) versus soft CROMs (objective, performance-based measures including patient-reported domains)? (3) How do PROMs and CROMs compare in their ability to detect change over time as measured by responsiveness indices such as effect size, standardized response mean, and other related metrics?
Methods:
We systematically searched Medline via PubMed, Embase, and Web of Science Core Collection in July 2025. Two reviewers independently performed title, abstract, and full-text screening. Studies were included when they directly compared PROMs and CROMs for orthopaedic-related topics. Extracted variables included study design, sample size, Spearman and Pearson correlation coefficients, and responsiveness. CROMs were classified as "hard" or "soft" based on the extent to which the instrument relied on patient input. Hard CROMs represent objective, performance-based or clinician-measured outcomes that do not require patient-reported information, whereas soft CROMs include clinician-administered instruments that incorporate patient-reported symptoms or functional assessments. PROMs were categorized as either generic or condition specific (joint-, region-, disease-specific) according to established definitions. All reported correlation coefficients were extracted and included regardless of statistical significance to comprehensively characterize the magnitude and variability of associations between PROMs and CROMs. Responsiveness was defined as the comparative sensitivity of PROMs and CROMs to clinical change, assessed using effect sizes, standardized response means, and related metrics. Thirty studies met inclusion criteria; 27 reported PROM-CROM correlations and nine evaluated responsiveness. The included studies encompassed a variety of musculoskeletal conditions, including musculoskeletal tumors (n = 4), distal radius fractures (n = 3), total joint arthroplasty and osteoarthritis (n = 11), pediatric limb deformities (n = 3), foot and ankle disorders (n = 7), spine (n = 1), and trauma (n = 1), with sample sizes ranging from 20 to 717 (mean = 143). Assessment of study quality, using an adapted Consensus-based Standards for the Selection of Health Measurement Instruments risk of bias framework, revealed that most studies were of "low risk" or "some concerns" because of incomplete paired PROM-CROM outcome data rather than flaws in design or analysis.
Results:
In evaluating relationships between PROMs and CROMs across orthopaedic subspecialties, condition-specific PROMs generally showed stronger correlations with corresponding CROMs, including the Toronto Extremity Salvage Score (r = 0.75 to 0.81) and the patient-reported American Orthopaedic Foot & Ankle Society (AOFAS) score (r = 0.70). In contrast, general health measures such as the EQ-5D time trade-off (r = -0.29 to 0.13) and certain region-specific instruments, including the Oswestry Disability Index (r = 0.27) and several upper extremity PROMs (r = -0.046 to 0.41), often demonstrated weaker correlations with CROMs. When evaluating differences in correlation by CROM subtype, PROMs tended to correlate more strongly with soft CROMs, such as the AOFAS score, Musculoskeletal Tumor Society score, and Harris hip score, than with hard CROMs. In comparing responsiveness between PROMs and CROMs, condition-specific PROMs, including the Manchester-Oxford Foot Questionnaire, the WOMAC, and Knee Society Score, were more often sensitive to clinical change than CROMs, except in rehabilitation-focused settings, where hard CROM responsiveness was often greater than for PROMs and soft CROMs.
Conclusion:
Based on currently available studies related to musculoskeletal conditions, PROMs and CROMs show variable associations with one another. The stronger correlations between soft CROMs and condition-specific PROMs suggest that when the goal is to establish benchmarks, a condition-specific PROM should be paired with a soft CROM. In contrast, hard CROMs may be particularly useful in short-term rehabilitation settings, where objective performance changes are a primary focus of evaluation. We recommend that orthopaedic studies and registries include, at a minimum, one condition-specific PROM (or soft CROM) and one hard CROM to ensure a multidimensional assessment of patient outcomes and improve interpretability across studies.
Level Of Evidence:
Level III, therapeutic study.
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