Linking AM-PAC Mobility and Daily Activity to the PROMIS Physical Function Metric

Linking QuickDASH and PROMIS Upper-Extremity Computer-Adaptive Test Scores in Hand Surgery: A Crosswalk Study

PURPOSE

Assessment of patient-reported outcome measures (PROMs) for hand and upper-extremity surgery patients using measures such as the Quick Disabilities of the Arm, Shoulder, and Hand (qDASH), as well as general measures including the Patient-Reported Outcomes Measurement Information System Upper Extremity Physical Function domain via a Computer-Adaptive Test (PROMIS UE CAT), has become commonplace. The aim of this study was to link, for crosswalking, the qDASH measure to both versions of the PROMIS UE CAT (v1.2 and v2.0).

METHODS

We included 18,944 hand and upper-extremity patients who completed both versions of the PROMIS UE CAT and the qDASH at the same clinical encounter. Shoulder pathology was excluded. Score linkage was performed using the R package equate, and multiple equating models (linear regression, identity, mean, linear, equipercentile, and circle-arc models) were used to establish crosswalk tables.

RESULTS

Mean qDASH and PROMIS UE CAT v1.2 scores were 38.2 (SD = 23.1) and 36.6 (SD = 9.8), respectively. Mean qDASH and PROMIS UE CAT v2.0 scores were 37.3 (SD = 21.8) and 38.3 (SD = 10.4), respectively. Pearson correlations had very strong linear relationships between the qDASH and the PROMIS UE CAT v1.2 and PROMIS UE CAT v2.0 (r = -0.83 [-0.84, -0.92] and r = -0.80 [-0.81, -0.80], respectively). For the equipercentile equating models, the intraclass correlation coefficient (ICC) had very strong positive relationships to linking measures with ICC = 0.85 (0.84, 0.86) for the qDASH-UE CAT v1.2 crosswalk and ICC = 0.83 (0.82, 0.84) for the qDASH-UE CAT v2.0 crosswalk.

CONCLUSIONS

The linkages establish crosswalk tables using equipercentile equating models to convert the PROMIS UE CAT v1.2 and v2.0 scores to the qDASH and vice versa.

CLINICAL RELEVANCE

This study provides crosswalk tables for commonly collected PROMs in hand surgery, increasing the comparability of results between centers using different PROMs to study the same conditions or treatments.

Outcome Measures and Patient-Reported Metrics in Cancer Rehabilitation

PURPOSE OF REVIEW

The current panorama of measurement tools for use in cancer rehabilitation is reviewed. For rehabilitation purposes, evaluating function is of the highest priority.

RECENT FINDINGS

From a patient-reported outcome (PRO) standpoint, SF-36 and EORTC-QLQ-C30 are in most common use in cancer rehabilitation research; these are quality of life measures that contain functional subdomains. Newer tools which are based on item response theory and have options for both computer assisted or short form (SF) administration, including the Patient-Reported Outcomes Measurement Information System (PROMIS) and Activity Measure for Post-acute Care (AMPAC) instruments, show increasing use, especially PROMIS Physical Function SF, and, recently, PROMIS Cancer Function Brief 3D, which has been validated in the cancer population, with domains of physical function, fatigue, and social participation, to track clinical rehabilitation outcomes. Evaluating objective measures of function in cancer patients is also crucial. Utilization of clinically feasible tools for cancer rehabilitation, to employ for both screening purposes and for monitoring of rehabilitation treatment efficacy, is an evolving area, much needed to promote further research and improved, consistent clinical care for cancer patients and survivors.

Can Patient-Reported Outcome Measurement Information System Measures Estimate High Impact Chronic Pain After Total Joint Arthroplasty?

BACKGROUND

High impact chronic pain (HICP) is not typically measured following orthopedic surgeries, but has a substantial negative impact on postoperative quality of life. This analysis determined which Patient-Reported Outcome Measurement Information System (PROMIS) measures accurately estimate HICP status following total joint arthroplasty (TJA).

METHODS

This was a secondary analysis of a hip and knee TJA cohort. HICP status was determined by two items from the Graded Chronic Pain Scale-Revised. The cohort (n = 2,400) consisted of 47.5% hip (n = 1,142) and 52.5% knee TJA (n = 1,258). For total hip arthroplasty (THA), 53.7% were women (n = 615), 48.6% were 65 years or older (n = 557), 72.5% completed the survey more than 24 months after first surgery (n = 831), and 9.9% had HICP (n = 114). For total knee arthroplasty (TKA), 54.3% were women (n = 687), 59.3% were 65 years or older (n = 750), 72.3% survey completed the survey more than 24 months after first surgery (n = 915), and 11.5% had HICP (n = 145). Included PROMIS measures were pain interference, physical function, anxiety, and sleep disturbance. First, discriminant function analysis determined PROMIS measure contribution to HICP status. Then, area under the curve (AUC) calculated the accuracy of PROMIS measures to estimate HICP status. Influences of sociodemographic and surgical characteristics on AUC were explored in sensitivity analyses.

RESULTS

Results for TKA and THA were similar so they are presented collectively for the sake of brevity. Mean differences were identified for all PROMIS measures for those with HICP (All P values < 0.01). Pain interference (β = 0.934) and sleep disturbance (β = 0.154) were independently correlated with HICP status in discriminant function analyses. The AUC (95% CIs) for HICP were as follows: pain interference (.952-.973), physical function (.921-.949), sleep (.780-.838), and anxiety (.687-.757). Sensitivity analyses revealed little change in AUC and HICP cutoff scores for PROMIS pain interference and physical function.

CONCLUSION

Two PROMIS measures commonly administered as standard of care for orthopedics, pain interference, and physical function, can be used to estimate HICP status for THA and TKA, thereby refining assessment of TJA outcomes.

Activity Measure for Post-Acute Care “6-Clicks” Basic Mobility Scores Predict Discharge Destination After Acute Care Hospitalization in Select Patient Groups: A Retrospective, Observational Study

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A standardized Basic Mobility score of 42.9 predicts home vs institution discharge.

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Orthopedic diagnoses may have a cutoff score of 41.5 to predict home discharge.

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Cutoff scores vary by diagnostic group and discharge destination.

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Cutoff scores vary by time of assessment relative to admission for some diagnoses.

Objectives

To establish cutoff scores for the Activity Measure for Post-Acute Care “6-Clicks” standardized Basic Mobility scores (sBMSs) for predicting discharge destination after acute care hospitalization for diagnostic subgroups within an acute care population and to evaluate the need for a second score to improve predictive ability.

Design

Retrospective, observational design.

Setting

Major medical center in metropolitan area.

Participants

Electronic medical records of 1696 adult patients (>18 years) admitted to acute care from January to October 2018. Records were stratified by orthopedic, cardiac, pulmonary, stroke, and other neurological diagnoses (N=1696). Interventions: None

Main Outcome Measure

Physical therapists scored patients’ sBMSs after referral for physical therapy and prior to discharge. Receiver operating characteristic curves delineated sBMS cutoff scores distinguishing various pairings of home, home with services, inpatient rehabilitation, or skilled nursing facility discharges. First and second sBMSs were compared with percentage change of the area under the curve and inferential statistics.

Results

Home vs institution cutoff score was 42.88 for combined sample, pulmonary and neurological cases. The cutoff score for orthopedic diagnoses score was 41.46. Cardiac and stroke model quality invalidated cutoff scores. Home without services vs skilled nursing discharges and home with services vs skilled nursing discharges were predicted with varying cutoff scores per diagnosis. sBMS cutoff scores collected closer to discharge were either the same or higher than first cutoffs, with varying effects on predictive ability.

Conclusions

sBMSs can help decide institution vs home discharge and finer distinctions among discharge settings for some diagnostic groups. A single sBMS may provide sufficient assistance with discharge destination decisions but timing of scoring and diagnostic group may influence cutoff score selection.

Key Data Elements for Longitudinal Tracking of Physical Function: A Modified Delphi Consensus Study

OBJECTIVE

Physical function is associated with important outcomes, yet there is often a lack of continuity in routine assessment. The purpose of this study was to determine data elements and instruments for longitudinal measurement of physical function in routine care among patients transitioning from acute care hospital setting to home with home health care.

METHODS

A 4-round modified Delphi process was conducted with 13 participants with expertise in physical therapy, health care administration, health services research, physiatry/medicine, and health informatics. Three anonymous rounds identified important and feasible data elements. A fourth in-person round finalized the recommended list of individual data elements. Next, 2 focus groups independently provided additional perspectives from other stakeholders.

RESULTS

Response rates were 100% for online rounds 1, 3, and 4 and 92% for round 2. In round 1, 9 domains were identified: physical function, participation, adverse events, behavioral/emotional health, social support, cognition, complexity of illness/disease burden, health care utilization, and demographics. Following the fourth round, 27 individual data elements were recommended. Of these, 20 (74%) are "administrative" and available from most hospital electronic medical records. Additional focus groups confirmed these selections and provided input on standardizing collection methods. A website has been developed to share these results and invite other health care systems to participate in future data sharing of these identified data elements.

CONCLUSION

A modified Delphi consensus process was used to identify critical data elements to track changes in patient physical function in routine care as they transition from acute hospital to home with home health.

IMPACT

Expert consensus on comprehensive and feasible measurement of physical function in routine care provides health care professionals and institutions with guidance in establishing discrete medical records data that can improve patient care, discharge decisions, and future research.