What are the perspectives of patients with hand and wrist conditions, chronic pain, and patients recovering from stroke on the use of patient and outcome information in everyday care? A Mixed-Methods study.

PURPOSE: To evaluate the patients' perspectives on the use of patient- and outcome information tools in everyday care and to investigate which characteristics affect general understanding and perceived value of patient- and outcome information. METHODS: This mixed-methods study included surveys and interviews on understanding, experience, decision-support, and perceived value in patients with hand and wrist conditions and chronic pain. We synthesized our quantitative and qualitative findings using a triangulation protocol and identified factors independently associated with general understanding and perceived value of patient- and outcome information using hierarchical logistic regression. RESULTS: We included 3379 patients. The data triangulation indicated that patients understand the outcome information, they find it valuable, it supports decision-making, and it improves patient-clinician interaction. The following variables were independently associated with better general understanding: having more difficulty with questionnaires (standardized odds ratio 0.34 [95%-CI 031-0.38]), having a finger condition (0.72 [0.57-0.92]), longer follow-up (0.75 [0.61-0.91]), and undergoing surgical treatment (ref: non-surgical treatment, 1.33 [1.11-1.59]). For more general value, these were: having more difficulty with questionnaires (0.40 [0.36-0.44]), having a wrist condition (0.71 [0.54-0.92]), better hand function (1.12 [1.02-1.22]), and requiring help with questionnaires (1.65 [1.33-2.05]). CONCLUSION: Patients value the use of patient- and outcome information tools in daily care and find it easy to understand. The factors associated with understanding and value can be targeted to personalized and value-based healthcare. We recommend using outcome information to improve patient independence, empowerment, and involvement in decision-making.

Explaining Personalized Activity Limitations in Patients With Hand and Wrist Disorders: Insights from Sociodemographic, Clinical, and Mindset Characteristics.

OBJECTIVES: To investigate the association of sociodemographic, clinical, and mindset characteristics on outcomes measured with a patient-specific patient-reported outcome measure (PROM); the Patient Specific Functional Scale (PSFS). Secondly, we examined whether these factors differ when a fixed-item PROM, the Michigan Hand Outcome Questionnaire (MHQ), is used as an outcome. DESIGN: Cohort study, using the aforementioned groups of factors in a hierarchical linear regression. SETTING: Twenty-six clinics for hand and wrist conditions in the Netherlands. PARTICIPANTS: Two samples of patients with various hand and wrist conditions and treatments: n=7111 (PSFS) and n=5872 (MHQ). INTERVENTIONS: NA. MAIN OUTCOME MEASURES: The PSFS and MHQ at 3 months. RESULTS: The PSFS exhibited greater between-subject variability in baseline, follow-up, and change scores than the MHQ. Better PSFS outcomes were associated with: no involvement in litigation (ß[95% confidence interval=-0.40[-0.54;-0.25]), better treatment expectations (0.09[0.06;0.13]), light workload (0.08[0.03;0.14]), not smoking (-0.07[-0.13;-0.01]), men sex (0.07[0.02;0.12]), better quality of life (0.07[0.05;0.10]), moderate workload (0.06[0.00;0.13]), better hand satisfaction (0.05[0.02; 0.07]), less concern (-0.05[-0.08;-0.02]), less pain at rest (-0.04[-0.08;-0.00]), younger age (-0.04[-0.07;-0.01]), better comprehensibility (0.03[0.01;0.06]), better timeline perception (-0.03[-0.06;-0.01]), and better control (-0.02[-0.04;-0.00]). The MHQ model was highly similar but showed a higher R2 than the PSFS model (0.41 vs 0.15), largely due to the R2 of the baseline scores (0.23 for MHQ vs 0.01 for PSFS). CONCLUSIONS: Health care professionals can improve personalized activity limitations by addressing treatment expectations and illness perceptions, which affect PSFS outcomes. Similar factors affect the MHQ, but the baseline MHQ score has a stronger association with the outcome score than the PSFS. While the PSFS is better for individual patient evaluation, we found that it is difficult to explain PSFS outcomes based on baseline characteristics compared with the MHQ. Using both patient-specific and fixed-item instruments helps health care professionals develop personalized treatment plans that meet individual needs and goals.

Driving Factors of Recommending a Hand Surgery Clinic After Surgery.

PURPOSE: Since a patient's recommendation of a clinic to others is an important indicator of patient experience, more insight is needed into the underlying factors that motivate such recommendations. This retrospective cohort study assessed the relative contribution of the following: (1) patient-related characteristics, (2) treatment outcome, (3) satisfaction with treatment outcome, and (4) patients' experience with the process of care to patients' recommendation of a specific clinic after elective surgery. METHODS: Patients of specialized outpatient hand surgery clinics (N = 6,895) reported the likelihood of recommending the clinic to friends or family 3-5 months after surgery by filling in the Net Promoter Score. Potential predictors of the Net Promoter Score were preoperative patient characteristics, patient-reported treatment outcomes, satisfaction with treatment outcome, and experience with several health care delivery domains. Linear regression analyses were used to examine the contribution of the predictors. RESULTS: Mean age of the patients was 53 (SD, 14) years, 62.5% were women, and 62.5% were employed. Preoperative patient characteristics explained 1% of the variance in clinic recommendations. An additional 6% was explained by the treatment outcome, 21.6% by satisfaction with treatment outcome, and 33.8% by patients' experience with care delivery (total explained variance was 62.3%). The strongest independent predictors of clinic recommendations were positive experiences with the quality of the facilities and the communication skills of the physician. CONCLUSIONS: Patient recommendations are more strongly driven by patients' experience with care delivery than by treatment outcome and patient characteristics. CLINICAL RELEVANCE: In elective surgery, improving patient experiences is pivotal in boosting patient recommendation of the clinic.

Patient-Reported and Clinical Outcomes After Tendon Autograft Reconstruction of the Thumb Ulnar Collateral Ligament.

PURPOSE: This study aimed to report clinical and patient-reported outcomes collected in a registry after thumb ulnar collateral ligament (UCL) reconstruction with a free tendon autograft. Furthermore, the patient-reported outcomes of patients with persistent instability after reconstruction and patients with concomitant metacarpophalangeal joint arthritis diagnosed during surgery were analyzed. METHODS: Patients undergoing reconstruction with a tendon autograft between December 2011 and February 2021 were included. Michigan Hand Outcomes Questionnaire (MHQ) scores at baseline were compared with those at 3 and 12 months after surgery. Stability was tested at 3 months after surgery. Tip and key pinch strength and metacarpophalangeal joint range of motion were measured at baseline and 12 months after surgery. RESULTS: We included 31 patients with thumb UCL insufficiency or failed UCL surgery who underwent reconstruction. The MHQ total score improved significantly from 62 at baseline to 75 at 3 months and continued to increase to 84 at 12 months after surgery. The MHQ function and pain scores improved significantly from intake to 3 and 12 months after surgery. Twenty-six of 31 patients (84%) regained postoperative metacarpophalangeal stability. Key pinch strength improved significantly 12 months after surgery from 5.2 kg at baseline to 6.4 kg at 12 months. The MHQ total, pain, and function scores of patients with persistent instability remained similar from baseline to 12 months after surgery. In four patients with metacarpophalangeal arthritis, the MHQ total and pain score improved significantly from baseline to 3 and 12 months after surgery. CONCLUSIONS: Patient-reported outcomes, including pain and function, improved after thumb UCL reconstruction with a tendon autograft. Although the sample size of patients with thumb metacarpophalangeal arthritis diagnosed during surgery was small, they reached adequate patient-reported outcomes at 12 months after surgery. TYPE OF STUDY/LEVEL OF EVIDENCE: Therapeutic IV.

The Figure-of-Eight Ligament Reconstruction in Thumb Carpometacarpal Instability: Surgical Technique and Clinical Outcomes.

PURPOSE: This study reviewed the results of the figure-of-eight ligament reconstruction, a technique used in the surgical management of thumb carpometacarpal (CMC) instability. This technique establishes joint stability through forces originating within the CMC joint, providing volar and dorsal support. METHODS: We evaluated the outcomes of 15 patients with nontraumatic, nonarthritic thumb CMC instability treated with the figure-of-eight ligament reconstruction technique. This technique involves routing a graft of the palmaris longus tendon through the base of the first metacarpal and trapezium bone in a figure-of-eight fashion. Preoperative visual analog scale (0-100) for pain and Michigan Hand Outcomes Questionnaire total scores were compared with 3- and 12-month postoperative scores. Secondary outcomes included strength, range of motion, patient satisfaction, return to work, and complications. RESULTS: A significant improvement between intake and 12 months after surgery was observed for both Michigan Hand Outcomes Questionnaire total scores (53, SD 3 vs 70, SD 4) and visual analog scale pain scores (63, SD 4 vs 36, SD 7). Additionally, after surgery, restored thumb CMC joint stability was reported for all patients. Strength and range of motion improved between intake and 12 months after surgery. The median return to work was 6 weeks. Nine (60%) patients rated their satisfaction as "excellent" or "good," and 11 (73%) patients said that they would undergo the surgery again. CONCLUSIONS: The figure-of-eight ligament reconstruction significantly improves pain and function in patients with thumb CMC instability while restoring joint stability and preserving range of motion, making it a suitable technique. TYPE OF STUDY/LEVEL OF EVIDENCE: Therapeutic IV.

The Validity and Responsiveness of the Patient-Specific Functional Scale in Patients With First Carpometacarpal Osteoarthritis.

PURPOSE: The purpose of this study was to assess the content, construct, and discriminative validity and responsiveness of the Patient-Specific Functional Scale (PSFS) in patients with thumb carpometacarpal arthritis. METHODS: Data were collected at Xpert Clinics, comprising 34 outpatient hand surgery and hand therapy clinics in the Netherlands. We included 267 patients for content validity and 323 patients for construct validity and responsiveness. The PSFS items were classified into the International Classification of Function Core Set for Hand Conditions to assess content validity. We used hypothesis testing to investigate the construct validity and responsiveness. The Michigan Hand Outcomes Questionnaire was used as a comparator instrument. The standardized response mean was calculated to evaluate the magnitude of change. For discriminative validity, we used independent t tests to discriminate between satisfied and dissatisfied patients. RESULTS: We classified 98% of the PSFS items in the International Classification of Function "activities" and "participation" domains, indicating good content validity. Two of six hypotheses for construct validity and three of six hypotheses for responsiveness were confirmed. The standardized response mean for the PSFS was 0.57 (0.46-0.68) and 0.47 (0.35-0.58) for the Michigan Hand Outcomes Questionnaire total score. The mean PSFS score showed good discriminative validity because it could distinguish between satisfied and dissatisfied patients at the 3-month follow-up. CONCLUSIONS: The PSFS scores showed good content and discriminative validity in patients with first carpometacarpal arthritis. Hypothesis testing for responsiveness and construct validity indicates that the PSFS measures a unique construct different from the Michigan Hand Outcomes Questionnaire. CLINICAL RELEVANCE: The PSFS may be a useful scale for measuring the patient-specific status of individuals with thumb carpometacarpal arthritis.

Involvement in a Personal Injury Claim Is Associated With More Pain and Delayed Return to Work After Elective Nonsurgical or Surgical Treatment for Hand or Wrist Disorders: A Propensity Score-matched Comparative Study.

BACKGROUND: A small proportion of patients treated for a hand or wrist condition are also involved in a personal injury claim that may or may not be related to the reason for seeking treatment. There are already indications that patients involved in a personal injury claim have more severe symptoms preoperatively and worse surgical outcomes. However, for nonsurgical treatment, it is unknown whether involvement in a personal injury claim affects treatment outcomes. Similarly, it is unknown whether treatment invasiveness affects the association between involvement in a personal injury claim and the outcomes of nonsurgical treatment. Finally, most studies did not take preoperative differences into account. QUESTIONS/PURPOSES: (1) Do patients with a claim have more pain during loading, less function, and longer time to return to work after nonsurgical treatment than matched patients without a personal injury claim? (2) Do patients with a personal injury claim have more pain, less function, and longer time to return to work after minor surgery than matched patients without a personal injury claim? (3) Do patients with a personal injury claim have more pain, less function, and longer time to return to work after major surgery than matched patients without a personal injury claim? METHODS: We used data from a longitudinally maintained database of patients treated for hand or wrist disorders in the Netherlands between December 2012 and May 2020. During the study period, 35,749 patients for whom involvement in a personal injury claim was known were treated nonsurgically or surgically for hand or wrist disorders. All patients were invited to complete the VAS (scores range from 0 to 100) for pain and hand function before treatment and at follow-up. We excluded patients who did not complete the VAS on pain and hand function before treatment and those who received a rare treatment, which we defined as fewer than 20 occurrences in our dataset, resulting in 29,101 patients who were eligible for evaluation in this study. Employed patients (66% [19,134 of 29,101]) were also asked to complete a questionnaire regarding return to work. We distinguished among nonsurgical treatment (follow-up at 3 months), minor surgery (such as trigger finger release, with follow-up of 3 months), and major surgery (such as trapeziectomy, with follow-up at 12 months). The mean age was 53 ± 15 years, 64% (18,695 of 29,101) were women, and 2% (651 of 29,101) of all patients were involved in a personal injury claim. For each outcome and treatment type, patients with a personal injury claim were matched to similar patients without a personal injury claim using 1:2 propensity score matching to account for differences in patient characteristics and baseline pain and hand function. For nonsurgical treatment VAS analysis, there were 115 personal injury claim patients and 230 matched control patients, and for return to work analysis, there were 83 claim and 166 control patients. For minor surgery VAS analysis, there were 172 personal injury claim patients and 344 matched control patients, and for return to work analysis, there were 108 claim and 216 control patients. For major surgery VAS analysis, there were 129 personal injury claim patients and 258 matched control patients, and for return to work analysis, there were 117 claim and 234 control patients. RESULTS: For patients treated nonsurgically, those with a claim had more pain during load at 3 months than matched patients without a personal injury claim (49 ± 30 versus 39 ± 30, adjusted mean difference 9 [95% confidence interval (CI) 2 to 15]; p = 0.008), but there was no difference in hand function (61 ± 27 versus 66 ± 28, adjusted mean difference -5 [95% CI -11 to 1]; p = 0.11). Each week, patients with a personal injury claim had a 39% lower probability of returning to work than patients without a claim (HR 0.61 [95% CI 0.45 to 0.84]; p = 0.002). For patients with an injury claim at 3 months after minor surgery, there was more pain (44 ± 30 versus 34 ± 29, adjusted mean difference 10 [95% CI 5 to 15]; p < 0.001), lower function (60 ± 28 versus 69 ± 28, adjusted mean difference -9 [95% CI -14 to -4]; p = 0.001), and 32% lower probability of returning to work each week (HR 0.68 [95% CI 0.52 to 0.89]; p = 0.005). For patients with an injury claim at 1 year after major surgery, there was more pain (36 ± 29 versus 27 ± 27, adjusted mean difference 9 [95% CI 4 to 15]; p = 0.002), worse hand function (66 ± 28 versus 76 ± 26, adjusted mean difference -9 [95% CI -15 to -4]; p = 0.001), and a 45% lower probability of returning to work each week (HR 0.55 [95% CI 0.42 to 0.73]; p < 0.001). CONCLUSION: Personal injury claim involvement was associated with more posttreatment pain and a longer time to return to work for patients treated for hand or wrist disorders, regardless of treatment invasiveness. Patients with a personal injury claim who underwent surgery also rated their postoperative hand function as worse than similar patients who did not have a claim. Depending on treatment invasiveness, only 42% to 55% of the personal injury claim patients experienced a clinically relevant improvement in pain. We recommend that clinicians extensively discuss the expected treatment outcomes and the low probability of a clinically relevant improvement in pain with their personal injury claim patients and that they broach the possibility of postponing treatment. LEVEL OF EVIDENCE: Level III, therapeutic study.

Treatment Invasiveness and Illness Perceptions Are Strongly Associated With Outcome Expectations in Patients Treated for Hand or Wrist Conditions: A Cross-sectional Study.

BACKGROUND: Multiple studies have shown that more-positive outcome expectations are associated with better treatment outcomes. Although this has not been shown to represent a causal relationship, there nonetheless is an interest in positively modifying outcome expectations to improve treatment outcomes. However, little is known about what is independently associated with outcome expectations in clinical practice. For example, it is unknown to what extent expectations are associated with treatment or patient characteristics such as sociodemographics or with patient-reported outcome measures (PROMs) on patient perceptions of physical or mental health or illness. Studying factors associated with outcome expectations may provide relevant information for clinicians and researchers aiming to improve outcome expectations. Improving expectations might, in turn, improve treatment outcomes. QUESTION/PURPOSE: Which factors (that is, sociodemographics, PROMs, illness perceptions, treatment, surgeon, and location) are independently associated with outcome expectations in patients with hand or wrist conditions? METHODS: This was a cross-sectional study. Between July 2018 and December 2021, we screened 21,327 patients with a diagnosed hand or wrist condition with complete baseline sociodemographic data such as age and workload. Sixty percent (12,765 of 21,327) of patients completed all relevant PROMs. We excluded patients receiving rare treatments, leaving 58% (12,345 of 21,327) for inclusion in the final sample. Those who participated were more often scheduled for surgical treatment and had higher expectations. We performed a multilevel analysis involving two steps. First, we evaluated whether patients receiving the same treatment, being counseled by the same surgeon, or being treated at the same location have more similar outcome expectations. We found that only patients receiving the same treatment had more similar outcome expectations. Therefore, we used a multilevel regression model to account for this correlation within treatments, and added treatment characteristics (such as nonsurgical versus minor or major surgery) to potential explanatory factors. Second, in the multilevel hierarchical regression analysis, we added sociodemographics (Model 1), PROMs for physical and mental health (Model 2), illness perceptions (Model 3), and treatment characteristics (most-definitive model) to assess the explained variance in outcome expectations per step and the relative association with outcome expectations. RESULTS: Sociodemographic factors such as age and workload explained 1% of the variance in outcome expectations. An additional 2% was explained by baseline PROMs for physical and mental health, 9% by illness perceptions, and 18% by treatment characteristics, resulting in an explained variance of 29% of the most-definitive model. A large number of patient and treatment characteristics were associated with outcome expectations. We used standardized betas to compare the magnitude of the effect of the different continuous and categorical variables. Among the associated variables, minor surgery (standardized beta [ß] = 0.56 [95% confidence interval 0.44 to 0.68]; p < 0.001) and major surgery (ß = 0.61 [95% CI 0.49 to 0.73]; p < 0.001) had the strongest positive association with outcome expectations (receiving surgery is associated with higher outcome expectations than nonsurgical treatment). A longer illness duration expected by the patient (-0.23 [95% CI -0.24 to -0.21]; p < 0.001) and being treated for the same condition as before (-0.08 [95% CI -0.14 to -0.03]; p = 0.003) had the strongest negative association with outcome expectations. CONCLUSION: Outcome expectations are mainly associated with the invasiveness of the treatment and by patients' illness perceptions; patients before surgical treatment have more positive expectations of the treatment outcome than patients before nonsurgical treatment, even after accounting for differences in clinical and psychosocial profiles. In addition, patients with a more-positive perception of their illness had more-positive expectations of their treatment. Our findings suggest expectation management should be tailored to the specific treatment (such as surgical versus nonsurgical) and the specific patient (including their perception of their illness). It may be more beneficial to test and implement expectation management strategies for nonsurgical treatments such as physical therapy than for surgical treatments, given that our findings indicate a greater need to do so. An additional advantage of such a strategy is that successful interventions may prevent converting to surgical interventions, which is a goal of the stepped-care principles of standard care. Future studies might investigate the causality of the association between pretreatment expectations and outcomes by performing an experimental study such as a randomized controlled trial, in which boosting expectations is compared with usual care in nonsurgical and surgical groups. LEVEL OF EVIDENCE: Level III, prognostic study.

The Ultrashort Mental Health Screening Tool Is a Valid and Reliable Measure With Added Value to Support Decision-making.

BACKGROUND: Mental health influences symptoms, outcomes, and decision-making in musculoskeletal healthcare. Implementing measures of mental health in clinical practice can be challenging. An ultrashort screening tool for mental health with a low burden is currently unavailable but could be used as a conversation starter, expectation management tool, or decision support tool. QUESTIONS/PURPOSES: (1) Which items of the Pain Catastrophizing Scale (PCS), Patient Health Questionnaire (PHQ-4), and Brief Illness Perception Questionnaire (B-IPQ) are the most discriminative and yield a high correlation with the total scores of these questionnaires? (2) What is the construct validity and added clinical value (explained variance for pain and hand function) of an ultrashort four-item mental health screening tool? (3) What is the test-retest reliability of the screening tool? (4) What is the response time for the ultrashort screening tool? METHODS: This was a prospective cohort study. Data collection was part of usual care at Xpert Clinics, the Netherlands, but prospective measurements were added to this study. Between September 2017 and January 2022, we included 19,156 patients with hand and wrist conditions. We subdivided these into four samples: a test set to select the screener items (n = 18,034), a validation set to determine whether the selected items were solid (n = 1017), a sample to determine the added clinical value (explained variance for pain and hand function, n = 13,061), and a sample to assess the test-retest reliability (n = 105). Patients were eligible for either sample if they completed all relevant measurements of interest for that particular sample. To create an ultrashort screening tool that is valid, reliable, and has added value, we began by picking the most discriminatory items (that is, the items that were most influential for determining the total score) from the PCS, PHQ-4, and B-IPQ using chi-square automated interaction detection (a machine-learning algorithm). To assess construct validity (how well our screening tool assesses the constructs of interest), we correlated these items with the associated sum score of the full questionnaire in the test and validation sets. We compared the explained variance of linear models for pain and function using the screening tool items or the original sum scores of the PCS, PHQ-4, and B-IPQ to further assess the screening tool's construct validity and added value. We evaluated test-retest reliability by calculating weighted kappas, ICCs, and the standard error of measurement. RESULTS: We identified four items and used these in the screening tool. The screening tool items were highly correlated with the PCS (Pearson coefficient = 0.82; p < 0.001), PHQ-4 (0.87; p < 0.001), and B-IPQ (0.85; p < 0.001) sum scores, indicating high construct validity. The full questionnaires explained only slightly more variance in pain and function (10% to 22%) than the screening tool did (9% to 17%), again indicating high construct validity and much added clinical value of the screening tool. Test-retest reliability was high for the PCS (ICC 0.75, weighted kappa 0.75) and B-IPQ (ICC 0.70 to 0.75, standard error of measurement 1.3 to 1.4) items and moderate for the PHQ-4 item (ICC 0.54, weighted kappa 0.54). The median response time was 43 seconds, against more than 4 minutes for the full questionnaires. CONCLUSION: Our ultrashort, valid, and reliable screening tool for pain catastrophizing, psychologic distress, and illness perception can be used before clinician consultation and may serve as a conversation starter, an expectation management tool, or a decision support tool. The clinical utility of the screening tool is that it can indicate that further testing is warranted, guide a clinician when considering a consultation with a mental health specialist, or support a clinician in choosing between more invasive and less invasive treatments. Future studies could investigate how the tool can be used optimally and whether using the screening tool affects daily clinic decisions. LEVEL OF EVIDENCE: Level II, diagnostic study.

System identification: a feasible, reliable and valid way to quantify upper limb motor impairments.

BACKGROUND: Upper limb impairments in a hemiparetic arm are clinically quantified by well-established clinical scales, known to suffer poor validity, reliability, and sensitivity. Alternatively, robotics can assess motor impairments by characterizing joint dynamics through system identification. In this study, we establish the merits of quantifying abnormal synergy, spasticity, and changes in joint viscoelasticity using system identification, evaluating (1) feasibility and quality of parametric estimates, (2) test-retest reliability, (3) differences between healthy controls and patients with upper limb impairments, and (4) construct validity. METHODS: Forty-five healthy controls, twenty-nine stroke patients, and twenty cerebral palsy patients participated. Participants were seated with the affected arm immobilized in the Shoulder-Elbow-Perturbator (SEP). The SEP is a one-degree-of-freedom perturbator that enables applying torque perturbations to the elbow while providing varying amounts of weight support to the human arm. Participants performed either a 'do not intervene' or a resist task. Elbow joint admittance was quantified and used to extract elbow viscosity and stiffness. Fifty-four of the participants performed two sessions to establish the test-retest reliability of the parameters. Construct validity was assessed by correlating system identification parameters to parameters extracted using a SEP protocol that objectifies current clinical scales (Re-Arm protocol). RESULTS: Feasibility was confirmed by all participants successfully completing the study protocol within ~ 25 min without reporting pain or burden. The parametric estimates were good with a variance-accounted-for of ~ 80%. A fair to excellent test-retest reliability was found ([Formula: see text]) for patients, except for elbow stiffness with full weight support ([Formula: see text]). Compared to healthy controls, patients had a higher elbow viscosity and stiffness during the 'do not intervene' task and lower viscosity and stiffness during the resist task. Construct validity was confirmed by a significant (all [Formula: see text]) but weak to moderate ([Formula: see text]) correlation with parameters from the Re-Arm protocol. CONCLUSIONS: This work demonstrates that system identification is feasible and reliable for quantifying upper limb motor impairments. Validity was confirmed by differences between patients and controls and correlations with other measurements, but further work is required to optimize the experimental protocol and establish clinical value.

Multiple Compression Syndromes of the Same Upper Extremity: Prevalence, Risk Factors, and Treatment Outcomes of Concomitant Treatment.

PURPOSE: Multiple nerve compression syndromes can co-occur. Little is known about this coexistence, especially about risk factors and surgical outcomes. Therefore, this study aimed to describe the prevalence of multiple nerve compression syndromes in the same arm in a surgical cohort and determine risk factors. Additionally, the surgical outcomes of concomitant treatment were studied. METHODS: The prevalence of surgically treated multiple nerve compression syndromes within one year was assessed using a review of patients' electronic records. Patient characteristics, comorbidities, and baseline scores of the Boston Carpal Tunnel Questionnaire were considered as risk factors. To determine the treatment outcomes of simultaneous treatment, patients who underwent concomitant carpal tunnel release (CTR) and cubital tunnel release (CubTR) were selected. The treatment outcomes were Boston Carpal Tunnel Questionnaire scores at intake and at 3 and 6 months after the surgery, satisfaction 6 months after the surgery, and return to work within the first year. RESULTS: A total of 7,867 patients underwent at least one nerve decompression between 2011 and 2021. Of these patients, 2.9% underwent multiple decompressions for the same upper extremity within one year. The risk factors for this were severe symptoms, younger age, and smoking. Furthermore, the treatment outcomes of concomitant CTR and CubTR did not differ from those of CubTR alone. The median time to return to work after concomitant treatment was 6 weeks. Patients who underwent CTR or CubTR alone returned to work after 4 weeks. CONCLUSIONS: Approximately 3% of the patients who underwent surgical treatment for nerve compression syndrome underwent decompression for another nerve within 1 year. Patients who report severe symptoms at intake, are younger, or smoke are at a greater risk. Patients with carpal and cubital tunnel syndrome may benefit from simultaneous decompression. The time to return to work may be less than if they underwent decompressions in separate procedures, whereas their surgical outcomes are comparable with those of CubTR alone. TYPE OF STUDY/LEVEL OF EVIDENCE: Therapeutic IV.

Prevalence of Complications and Association With Patient-Reported Outcomes After Trapeziectomy With a Weilby Sling: A Cohort Study.

PURPOSE: The primary aim of this study was to report complications during the first year after trapeziectomy with Weilby sling using a standardized tool designed by the International Consortium for Health Outcome Measures. The secondary aim was to determine the association of complications and patient-reported outcomes 12 months after surgery. METHODS: We included patients who underwent trapeziectomy with Weilby sling between November 2013 and December 2018. All complications during the first year were scored using the International Consortium for Health Outcomes Measurement Complications in Hand and Wrist conditions (ICHAW) tool. Pain and hand function were measured before surgery and 12 months after surgery using the Michigan Hand Outcomes Questionnaire (MHQ). Minimally Important Change thresholds of 18.6 for MHQ pain and 9.4 for MHQ function were used to determine clinical importance. RESULTS: Of 531 patients after trapeziectomy with Weilby sling, 65% had an uneventful recovery, 16% experienced ICHAW Grade 1 deviations only, and 19% experienced Grade 2 or 3 deviations, including requiring antibiotics, corticosteroid injections, or additional surgery. On average, patients improved in pain and hand function, even in the presence of ICHAW events. Although all ICHAW grades were associated with poorer patient-reported outcomes 12 months after surgery, Grade 2 and 3 exceeded the Minimally Important Change threshold for pain and/or function. CONCLUSIONS: In 531 patients, 65% had an uneventful recovery, 16% experienced ICHAW Grade 1 deviations only, and 19% experienced grade 2 or 3 deviations. We recommend describing Grade 1 as "adverse protocol deviations" and grade 2 and 3 as complications, because of clinically relevant poorer patient-reported outcomes 12 months after surgery. The ICHAW is a promising tool to evaluate systematically and compare complications in hand surgery, although we recommend further evaluation. TYPE OF STUDY/LEVEL OF EVIDENCE: Therapeutic IV.

Patient-Reported Outcomes and Function After Surgical Repair of the Ulnar Collateral Ligament of the Thumb.

PURPOSE: The purpose of this study was to report prospectively collected patient-reported outcomes of patients who underwent open thumb ulnar collateral ligament (UCL) repair and to find risk factors associated with poor patient-reported outcomes. METHODS: Patients undergoing open surgical repair for a complete thumb UCL rupture were included between December 2011 and February 2021. Michigan Hand Outcomes Questionnaire (MHQ) total scores at baseline were compared to MHQ total scores at three and 12 months after surgery. Associations between the 12-month MHQ total score and several variables (i.e., sex, injury to surgery time, K-wire immobilization) were analyzed. RESULTS: Seventy-six patients were included. From baseline to three and 12 months after surgery, patients improved significantly with a mean MHQ total score of 65 (standard deviation [SD] 15) to 78 (SD 14) and 87 (SD 12), respectively. We did not find any differences in outcomes between patients who underwent surgery in the acute (<3 weeks) setting compared to a delayed setting (<6 months). CONCLUSIONS: We found that patient-reported outcomes improve significantly at three and 12 months after open surgical repair of the thumb UCL compared to baseline. We did not find an association between injury to surgery time and lower MHQ total scores. This suggests that acute repair for full-thickness UCL tears might not always be necessary. TYPE OF STUDY/LEVEL OF EVIDENCE: Therapeutic II.

A Sensor-Based Feedback Device Stimulating Daily Life Upper Extremity Activity in Stroke Patients: A Feasibility Study.

This study aims to evaluate the feasibility and explore the efficacy of the Arm Activity Tracker (AAT). The AAT is a device based on wrist-worn accelerometers that provides visual and tactile feedback to stimulate daily life upper extremity (UE) activity in stroke patients. METHODS: A randomised, crossover within-subject study was conducted in sub-acute stroke patients admitted to a rehabilitation centre. Feasibility encompassed (1) adherence: the dropout rate and the number of participants with insufficient AAT data collection; (2) acceptance: the technology acceptance model (range: 7-112) and (3) usability: the system usability scale (range: 0-100). A two-way ANOVA was used to estimate the difference between the baseline, intervention and control conditions for (1) paretic UE activity and (2) UE activity ratio. RESULTS: Seventeen stroke patients were included. A 29% dropout rate was observed, and two participants had insufficient data collection. Participants who adhered to the study reported good acceptance (median (IQR): 94 (77-111)) and usability (median (IQR): 77.5 (75-78.5)-). We found small to medium effect sizes favouring the intervention condition for paretic UE activity (η2G = 0.07, p = 0.04) and ratio (η2G = 0.11, p = 0.22). CONCLUSION: Participants who adhered to the study showed good acceptance and usability of the AAT and increased paretic UE activity. Dropouts should be further evaluated, and a sufficiently powered trial should be performed to analyse efficacy.

Determining the Minimally Important Change of the Michigan Hand outcomes Questionnaire in patients undergoing trigger finger release.

INTRODUCTION: The Michigan Hand outcomes Questionnaire (MHQ) is a widely used instrument to evaluate treatment results for hand conditions. Establishing the Minimally Important Change (MIC) is essential for interpreting change in outcome that is clinically relevant. PURPOSE OF THE STUDY: The purpose of this study was to determine the MIC of the MHQ total and subscale scores in patients undergoing trigger finger release. STUDY DESIGN: This is a prospective cohort study conducted between December 2011 and February 2020. METHODS: Patients completed the MHQ prior to surgery and 3 months postoperatively. The MIC of the MHQ was determined using 5 anchor-based methods (ie, 2 anchor mean change methods and 3 receiver operating characteristic methods). The median MIC value was determined to represent the triangulated MIC. RESULTS: A total of 1814 patients were included. The MIC for the MHQ total score ranged from 7.7 to 10.9, with a triangulated estimate of 9.3. The MIC estimates for 5 of 6 of the MHQ subscales ranged from 7.7 to 20.0. No MICs could be determined for the MHQ subscale "aesthetics" due to low correlations between the anchor questions and MHQ change scores. CONCLUSIONS: These MIC estimates can contribute to the interpretation of clinical outcomes following trigger finger release and for assessment of power in prospective trials.

Rasch Analysis of the Michigan Hand Questionnaire.

OBJECTIVES: The Michigan Hand Questionnaire (MHQ) is a commonly used evaluation for hand problems, but previous work reports conflicting evidence regarding the subscale structures. Rasch analysis uses probabilistic modeling of items and responses: if scale items can be fit to the Rasch model, it provides evidence of construct validity and interval-level measurement for precise statistical estimates. We conducted Rasch analysis on the MHQ to evaluate model fit, unidimensionality of the subscales, bias across person factors, and conversion to interval metrics. METHODS: We conducted a secondary Rasch analysis of MHQ data from 924 persons with thumb basal joint osteoarthritis using the RUMM2030 software. Modeling was based on responses for the most affected hand and person factors including age, sex, type of work, whether the dominant side was the most affected, and surgical status. The analysis plan followed the published recommendations for examinations of person and item fit, with iterative adjustments as required. RESULTS: A total of 11 of the 37 items required rescoring to create orderly progression of scoring thresholds. Only the overall hand function and pain subscales could be fit to the Rasch model, demonstrating unidimensionality and good reliability of fit estimates. Dividing the activities of daily living subscale into unilateral and bilateral activities also allowed unilateral activities to fit the model. Persistent misfitting in other subscales suggested local dependency and response bias across multiple person factors. CONCLUSIONS: This Rasch analysis of the MHQ raises concerns regarding the validity and fundamental measurement properties of this widely used outcome evaluation when used as a summary score.

Which Factors Are Associated With Satisfaction With Treatment Results in Patients With Hand and Wrist Conditions? A Large Cohort Analysis.

BACKGROUND: Satisfaction with treatment results is an important outcome domain in striving for patient-centered and value-based healthcare. Although numerous studies have investigated factors associated with satisfaction with treatment results, most studies used relatively small samples. Additionally, many studies have only investigated univariable associations instead of multivariable associations; to our knowledge, none have investigated the independent association of baseline sociodemographics, quality of life, improvement in pain and function, experiences with healthcare delivery, and baseline measures of mental health with satisfaction with treatment results. QUESTIONS/PURPOSES: (1) What factors are independently associated with satisfaction with treatment results at 3 months post-treatment in patients treated for common hand and wrist conditions? (2) What factors are independently associated with the willingness to undergo the treatment again at 3 months post-treatment in patients treated for common hand and wrist conditions? Among the factors under study were baseline sociodemographics, quality of life, improvement in pain and function, experiences with healthcare delivery, and baseline measures of mental health. METHODS: Between August 2018 and May 2020, we included patients who underwent carpal tunnel release, nonsurgical or surgical treatment for thumb-base osteoarthritis, trigger finger release, limited fasciectomy for Dupuytren contracture, or nonsurgical treatment for midcarpal laxity in one of the 28 centers of Xpert Clinics in the Netherlands. We screened 5859 patients with complete sociodemographics and data at baseline. Thirty-eight percent (2248 of 5859) of these patients had complete data at 3 months. Finally, participants were eligible for inclusion if they provided a relevant answer to the three patient-reported experience measure (PREM) items. A total of 424 patients did not do this because they answered "I don't know" or "not applicable" to a PREM item, leaving 31% (1824 of 5859) for inclusion in the final sample. A validated Satisfaction with Treatment Result Questionnaire was administered at 3 months, which identified the patients' level of satisfaction with treatment results so far on a 5-point Likert scale (research question 1, with answers of poor, moderate, fair, good, or excellent) and the patients' willingness to undergo the treatment again under similar circumstances (research question 2, with answers of yes or no). A hierarchical logistic regression model was used to identify whether baseline sociodemographics, quality of life, change in outcome (patient-reported outcome measures for hand function and pain), baseline measures of mental health (including treatment credibility [the extent to which a patient attributes credibility to a treatment] and expectations, illness perception, pain catastrophizing, anxiety, and depression), and PREMs were associated with each question of the Satisfaction with Treatment Result Questionnaire at 3 months post-treatment. We dichotomized responses to our first question as good and excellent, which were considered more satisfied, and poor, moderate, and fair, which were considered less satisfied. After dichotomization, 57% (1042 of 1824) of patients were classified as more satisfied with the treatment results. RESULTS: The following variables were independently associated with satisfaction with treatment results, with an area under the curve of 0.82 (95% confidence interval 0.80 to 0.84) (arranged from the largest to the smallest standardized odds ratio [SOR]): greater decrease in pain during physical load (standardized odds ratio 2.52 [95% CI 2.18 to 2.92]; p < 0.001), patient's positive experience with the explanation of the pros and cons of the treatment (determined with the question: "Have you been explained the pros and cons of the treatment or surgery?") (SOR 1.83 [95% CI 1.41 to 2.38]; p < 0.001), greater improvement in hand function (SOR 1.76 [95% CI 1.54 to 2.01]; p < 0.001), patients' positive experience with the advice for at-home care (determined with the question: "Were you advised by the healthcare providers on how to deal with your illness or complaints in your home situation?") (SOR 1.57 [95% CI 1.21 to 2.04]; p < 0.001), patient's better personal control (determined with the question: "How much control do you feel you have over your illness?") (SOR 1.24 [95% CI 1.1 to 1.40]; p < 0.001), patient's more positive treatment expectations (SOR 1.23 [95% CI 1.04 to 1.46]; p = 0.02), longer expected illness duration by the patient (SOR 1.20 [95% CI 1.04 to 1.37]; p = 0.01), a smaller number of symptoms the patient saw as part of the illness (SOR 0.84 [95% CI 0.72 to 0.97]; p = 0.02), and less concern about the illness the patient experiences (SOR 0.84 [95% CI 0.72 to 0.99]; p = 0.04). For willingness to undergo the treatment again, the following variables were independently associated with an AUC of 0.81 (95% CI 0.78 to 0.83) (arranged from the largest to the smallest standardized OR): patient's positive experience with the information about the pros and cons (determined with the question: "Have you been explained the pros and cons of the treatment or surgery?") (SOR 2.05 [95% CI 1.50 to 2.80]; p < 0.001), greater improvement in hand function (SOR 1.80 [95% CI 1.54 to 2.11]; p < 0.001), greater decrease in pain during physical load (SOR 1.74 [95% CI 1.48 to 2.07]; p < 0.001), patient's positive experience with the advice for at home (determined with the question: "Were you advised by the healthcare providers on how to deal with your illness or complaints in your home situation?") (SOR 1.52 [95% CI 1.11 to 2.07]; p = 0.01), patient's positive experience with shared decision-making (determined with the question: "Did you decide together with the care providers which care or treatment you will receive?") (SOR 1.45 [95% CI 1.06 to 1.99]; p = 0.02), higher credibility the patient attributes to the treatment (SOR 1.44 [95% CI 1.20 to 1.73]; p < 0.001), longer symptom duration (SOR 1.27 [95% CI 1.09 to 1.52]; p < 0.01), and patient's better understanding of the condition (SOR 1.17 [95% CI 1.01 to 1.34]; p = 0.03). CONCLUSION: Our findings suggest that to directly improve satisfaction with treatment results, clinicians might seek to: (1) improve the patient's experience with healthcare delivery, (2) try to influence illness perception, and (3) boost treatment expectations and credibility. Future research should confirm whether these suggestions are valid and perhaps also investigate whether satisfaction with treatment results can be predicted (instead of explained, as was done in this study). Such prediction models, as well as other decision support tools that investigate patient-specific needs, may influence experience with healthcare delivery, expectations, or illness perceptions, which in turn may improve satisfaction with treatment results. LEVEL OF EVIDENCE: Level III, therapeutic study.

Machine Learning Can be Used to Predict Function but Not Pain After Surgery for Thumb Carpometacarpal Osteoarthritis.

BACKGROUND: Surgery for thumb carpometacarpal osteoarthritis is offered to patients who do not benefit from nonoperative treatment. Although surgery is generally successful in reducing symptoms, not all patients benefit. Predicting clinical improvement after surgery could provide decision support and enhance preoperative patient selection. QUESTIONS/PURPOSES: This study aimed to develop and validate prediction models for clinically important improvement in (1) pain and (2) hand function 12 months after surgery for thumb carpometacarpal osteoarthritis. METHODS: Between November 2011 and June 2020, 2653 patients were surgically treated for thumb carpometacarpal osteoarthritis. Patient-reported outcome measures were used to preoperatively assess pain, hand function, and satisfaction with hand function, as well as the general mental health of patients and mindset toward their condition. Patient characteristics, medical history, patient-reported symptom severity, and patient-reported mindset were considered as possible predictors. Patients who had incomplete Michigan Hand outcomes Questionnaires at baseline or 12 months postsurgery were excluded, as these scores were used to determine clinical improvement. The Michigan Hand outcomes Questionnaire provides subscores for pain and hand function. Scores range from 0 to 100, with higher scores indicating less pain and better hand function. An improvement of at least the minimum clinically important difference (MCID) of 14.4 for the pain score and 11.7 for the function score were considered "clinically relevant." These values were derived from previous reports that provided triangulated estimates of two anchor-based and one distribution-based MCID. Data collection resulted in a dataset of 1489 patients for the pain model and 1469 patients for the hand function model. The data were split into training (60%), validation (20%), and test (20%) dataset. The training dataset was used to select the predictive variables and to train our models. The performance of all models was evaluated in the validation dataset, after which one model was selected for further evaluation. Performance of this final model was evaluated on the test dataset. We trained the models using logistic regression, random forest, and gradient boosting machines and compared their performance. We chose these algorithms because of their relative simplicity, which makes them easier to implement and interpret. Model performance was assessed using discriminative ability and qualitative visual inspection of calibration curves. Discrimination was measured using area under the curve (AUC) and is a measure of how well the model can differentiate between the outcomes (improvement or no improvement), with an AUC of 0.5 being equal to chance. Calibration is a measure of the agreement between the predicted probabilities and the observed frequencies and was assessed by visual inspection of calibration curves. We selected the model with the most promising performance for clinical implementation (that is, good model performance and a low number of predictors) for further evaluation in the test dataset. RESULTS: For pain, the random forest model showed the most promising results based on discrimination, calibration, and number of predictors in the validation dataset. In the test dataset, this pain model had a poor AUC (0.59) and poor calibration. For function, the gradient boosting machine showed the most promising results in the validation dataset. This model had a good AUC (0.74) and good calibration in the test dataset. The baseline Michigan Hand outcomes Questionnaire hand function score was the only predictor in the model. For the hand function model, we made a web application that can be accessed via https://analyse.equipezorgbedrijven.nl/shiny/cmc1-prediction-model-Eng/. CONCLUSION: We developed a promising model that may allow clinicians to predict the chance of functional improvement in an individual patient undergoing surgery for thumb carpometacarpal osteoarthritis, which would thereby help in the decision-making process. However, caution is warranted because our model has not been externally validated. Unfortunately, the performance of the prediction model for pain is insufficient for application in clinical practice. LEVEL OF EVIDENCE: Level III, therapeutic study.

What Are the Minimally Important Changes of Four Commonly Used Patient-reported Outcome Measures for 36 Hand and Wrist Condition-Treatment Combinations?

BACKGROUND: Patient-reported outcome measures (PROMs) are frequently used to assess treatment outcomes for hand and wrist conditions. To adequately interpret these outcomes, it is important to determine whether a statistically significant change is also clinically relevant. For this purpose, the minimally important change (MIC) was developed, representing the minimal within-person change in outcome that patients perceive as a beneficial treatment effect. Prior studies demonstrated substantial differences in MICs between condition-treatment combinations, suggesting that MICs are context-specific and cannot be reliably generalized. Hence, a study providing MICs for a wide diversity of condition-treatment combinations for hand and wrist conditions will contribute to more accurate treatment evaluations. QUESTIONS/PURPOSES: (1) What are the MICs of the most frequently used PROMs for common condition-treatment combinations of hand and wrist conditions? (2) Do MICs vary based on the invasiveness of the treatment (nonsurgical treatment or surgical treatment)? METHODS: This study is based on data from a longitudinally maintained database of patients with hand and wrist conditions treated in one of 26 outpatient clinics in the Netherlands between November 2013 and November 2020. Patients were invited to complete several validated PROMs before treatment and at final follow-up. All patients were invited to complete the VAS for pain and hand function. Depending on the condition, patients were also invited to complete the Michigan Hand outcomes Questionnaire (MHQ) (finger and thumb conditions), the Patient-rated Wrist/Hand Evaluation (PRWHE) (wrist conditions), or the Boston Carpal Tunnel Questionnaire (BCTQ) (nerve conditions). Additionally, patients completed the validated Satisfaction with Treatment Result Questionnaire at final follow-up. Final follow-up timepoints were 3 months for nonsurgical and minor surgical treatment (including trigger finger release) and 12 months for major surgical treatment (such as trapeziectomy). Our database included 55,651 patients, of whom we excluded 1528 who only required diagnostic management, 25,099 patients who did not complete the Satisfaction with Treatment Result Questionnaire, 3509 patients with missing data in the PROM of interest at baseline or follow-up, and 1766 patients who were part of condition-treatment combinations with less than 100 patients. The final sample represented 43% (23,749) of all patients and consisted of 36 condition-treatment combinations. In this final sample, 26% (6179) of patients were managed nonsurgically and 74% (17,570) were managed surgically. Patients had a mean ± SD age of 55 ± 14 years, and 66% (15,593) of patients were women. To estimate the MIC, we used two anchor-based methods (the anchor mean change and the MIC predict method), which were triangulated afterward to obtain a single MIC. Applying this method, we calculated the MIC for 36 condition-treatment combinations, comprising 22 different conditions, and calculated the MIC for combined nonsurgical and surgical treatment groups. To examine whether the MIC differs between nonsurgical and surgical treatments, we performed a Wilcoxon signed rank test to compare the MICs of all PROM scores between nonsurgical and surgical treatment. RESULTS: We found a large variation in triangulated MICs between the condition-treatment combinations. For example, for nonsurgical treatment of hand OA, the MICs of VAS pain during load clustered around 10 (interquartile range 8 to 11), for wrist osteotomy/carpectomy it was around 25 (IQR 24 to 27), and for nerve decompression it was 21. Additionally, the MICs of the MHQ total score ranged from 4 (nonsurgical treatment of CMC1 OA) to 15 (trapeziectomy with LRTI and bone tunnel), for the PRWHE total score it ranged from 2 (nonsurgical treatment of STT OA) to 29 (release of first extensor compartment), and for the BCTQ Symptom Severity Scale it ranged from 0.44 (nonsurgical treatment of carpal tunnel syndrome) to 0.87 (carpal tunnel release). An overview of all MIC values is available in a freely available online application at: https://analyse.equipezorgbedrijven.nl/shiny/mic-per-treatment/. In the combined treatment groups, the triangulated MIC values were lower for nonsurgical treatment than for surgical treatment (p < 0.001). The MICs for nonsurgical treatment can be approximated to be one-ninth (IQR 0.08 to 0.13) of the scale (approximately 11 on a 100-point instrument), and surgical treatment had MICs that were approximately one-fifth (IQR 0.14 to 0.24) of the scale (approximately 19 on a 100-point instrument). CONCLUSION: MICs vary between condition-treatment combinations and differ depending on the invasiveness of the intervention. Patients receiving a more invasive treatment have higher treatment expectations, may experience more discomfort from their treatment, or may feel that the investment of undergoing a more invasive treatment should yield greater improvement, leading to a different perception of what constitutes a beneficial treatment effect. CLINICAL RELEVANCE: Our findings indicate that the MIC is context-specific and may be misleading if applied inappropriately. Implementation of these condition-specific and treatment-specific MICs in clinical research allows for a better study design and to achieve more accurate treatment evaluations. Consequently, this could aid clinicians in better informing patients about the expected treatment results and facilitate shared decision-making in clinical practice. Future studies may focus on adaptive techniques to achieve individualized MICs, which may ultimately aid clinicians in selecting the optimal treatment for individual patients.

Rasch analysis of the brief Michigan Hand Questionnaire in patients with thumb osteoarthritis.

BACKGROUND: The brief Michigan Hand Questionnaire (brief MHQ) is a 12-item self-reported measure of hand function for patients with hand disorders which has been validated using Classical Test Theory. Rasch analysis can provide more detailed psychometric information. The purpose of this Rasch analysis is to assess the psychometric properties of the brief MHQ for patients with thumb osteoarthritis, and to make recommendations for improvements to the questionnaire if needed.  METHODS: The Michigan Hand Questionnaire and demographic data were collected from 923 thumb osteoarthritis patients treated in specialized clinics for hand surgery and therapy in the Netherlands. Rasch analysis was performed on the 12 items of the brief MHQ using RUMM 2030 to assess the fit of the brief MHQ to the Rasch model. To determine fit, analysis of fit summary statistics, individual person fit and individual item fit were assessed. Threshold distributions were assessed to identify if any items required rescoring. The Person Separation Index was calculated to measure reliability of the questionnaire. Differential item functioning was assessed to identify item bias, and Principal Component Analysis was performed to identify unidimensionality and local dependence. RESULTS: The brief MHQ showed misfit (χ2 = 1312.5, p < 0.0001) with 6 items having disordered thresholds and 9 items requiring rescoring. After deleting 3 of the rescored items due to significant item fit residuals, the brief MHQ had an acceptable reliability (Cronbach's alpha = 0.79). Misfit to the model (χ2 = 49.6, p = 0.0001), multidimensionality (10.2% of t-tests were significant), and item bias from non-uniform differential item functioning for 7 items across many person variables were still found. CONCLUSION: Although no satisfactory solutions were found to correct the misfit to the Rasch model, it is recommended that the response options of the brief MHQ be rescored, and that items 6, 9 and 10 be removed. The lack of unidimensionality indicates that the items do not represent the singular construct of hand disability and that totalling the scores of the brief MHQ does not provide a valid measure of hand disability for people with thumb osteoarthritis. The 37-item Michigan Hand Questionnaire may provide a better assessment of hand disability for patients with thumb osteoarthritis.