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.

Tailoring and evaluating treatment with the Patient-Specific Needs Evaluation: A Patient-Centered Approach.

BACKGROUND: No patient-reported instrument assesses patient-specific information needs, treatment goals, and Personal Meaningful Gain (PMG, a novel construct evaluating individualized, clinically relevant improvement). This study reports the development of the Patient-Specific Needs Evaluation (PSN) and examines its discriminative validity (i.e., its ability to distinguish satisfied from dissatisfied patients) and test-retest reliability in patients with hand or wrist conditions. METHODS: A mixed-methods approach was used to develop and validate the PSN, following COSMIN guidelines, including pilot testing, a survey (pilot: n=223, final PSN: n=275), cognitive debriefing (n=16), expert input, and validation. Discriminative validity was assessed by comparing the satisfaction level of patients who did or did not achieve their PMG (n=1,985) and test-retest reliability using absolute agreement, Cohen's kappa, and ICCs (n=102). We used a sample of 2,860 patients to describe responses to the final PSN. RESULTS: The PSN has only five questions (completion time ±3 minutes) and is freely accessible online. The items and response options were considered understandable by 90-92% and complete by 84-89% of the end-users. The PSN had excellent discriminative validity (Cramer's V: 0.48, p<0.001) and moderate to high test-retest reliability (Kappa: 0.46-0.68, ICCs: 0.53-0.73). CONCLUSIONS: The PSN is a freely available patient-centered decision-support tool that helps clinicians tailor their consultations to the patient's individual needs and goals. It contains the PMG, a novel construct evaluating individualized, clinically relevant treatment outcomes. The PSN may function as a conversation starter, facilitate expectation management, and aid shared decision-making. The PSN is implementation-ready and can be readily adapted to other patient populations. LEVEL OF EVIDENCE: I.

Long-Term Outcomes of Nonsurgical Treatment of Thumb Carpometacarpal Osteoarthritis: A Cohort Study.

BACKGROUND: Although nonsurgical treatment of thumb carpometacarpal (CMC-1) osteoarthritis (OA) provides short-term improvement, the durability of these effects beyond 1 year is unknown. In this study, we investigated patient-reported pain and limitations in activities of daily living (ADL) at >5 years following nonsurgical treatment (i.e., exercise therapy and use of an orthosis) for CMC-1 OA. We hypothesized that pain and limitations in ADL would not worsen after 12 months. Secondary outcomes were satisfaction with treatment results and health-related quality of life at >5 years of follow-up and the rate of conversion to surgery. METHODS: This was a multicenter, prospective cohort study using 2 overlapping samples. The change in the Michigan Hand Outcomes Questionnaire (MHQ) subscales of pain and ADL between 12 months and >5 years was the primary outcome as measured in the first sample (n = 170), which consisted of patients who did not undergo conversion to surgery. Additional measurement time points included baseline and 3 months. We evaluated conversion to surgery in a second sample, which included all patients who responded to the invitation for this follow-up study (n = 217). RESULTS: At a median follow-up of 6.6 years (range, 5.1 to 8.7 years), the score on the MHQ pain subscale did not differ significantly from that at 12 months. The score on the MHQ ADL improved by 4.4 points (95% confidence interval [CI],1.5 to 7.2) compared with 12 months, but this was not clinically relevant. At >5 years, 5% of the patients rated their satisfaction as "poor," 14% as "moderate," 26% as "fair," 39% as "good," and 16% as "excellent." The median EuroQol-5 Dimensions-5 Levels (EQ-5D-5L) index score was 0.852 (range, 0.135 to 1). The rate of conversion to surgery was 22% (95% CI,16.4% to 27.7%) at a median follow-up of 7 years (range, 5.5 to 9.0 years). CONCLUSIONS: We found positive outcomes at >5 years of follow-up for nonsurgical treatment of CMC-1 OA, with no worsening of pain or of limitations in ADL after 12 months. Our findings support nonsurgical treatment as the first treatment choice and suggest that treatment effects are sustainable. LEVEL OF EVIDENCE: Therapeutic Level II . See Instructions for Authors for a complete description of levels of evidence.

Changes in illness perception, pain catastrophizing, and psychological distress following hand surgeon consultation: A prospective study.

BACKGROUND: Baseline mindset factors are important factors that influence treatment decisions and outcomes. Theoretically, improving the mindset prior to treatment may improve treatment decisions and outcomes. This prospective cohort study evaluated changes in patients' mindset following hand surgeon consultation. Additionally, we assessed if the change in illness perception differed between surgical and nonsurgical patients. METHODS: The primary outcome was illness perception, measured using the total score of the Brief Illness Perception Questionnaire (B-IPQ, range 0-80). Secondary outcomes were the B-IPQ subscales, pain catastrophizing (measured using the Pain Catastrophizing Scale (PCS)), and psychological distress (measured using the Patient Health Questionnaire-4). RESULTS: A total of 276 patients with various hand and wrist conditions completed the mindset questionnaires before and after hand surgeon consultation (median time interval: 15 days). The B-IPQ total score improved from 39.7 (±10.6) before to 35.8 (±11.3) after consultation (p < 0.0001, Cohen's d = 0.36); scores also improved for the B-IPQ subscales Coherence, Concern, Emotional Response, Timeline, Treatment Control, and Identity and the PCS. There were no changes in the other outcomes. Surgical patients improved on the B-IPQ subscales Treatment Control and Timeline, while nonsurgical patients did not. CONCLUSIONS: Illness perception and pain catastrophizing improved following hand surgeon consultation, suggesting that clinicians may actively influence the patients' mindset during consultations, and that they may try to enhance this effect to improve outcomes. Furthermore, surgical patients improved more in illness perceptions, indicating that nonsurgical patients may benefit from a more targeted strategy for changing mindset.

Factors Associated with Treatment Outcome Satisfaction Six Months after Upper Blepharoplasty: A Large Cohort Study.

Background: Upper blepharoplasty is the most popular facial cosmetic surgery. Although there are a variety of reasons to undergo this procedure, all patients expect an optimal cosmetic result. However, little is known about the factors that influence satisfaction with treatment outcome. Objectives: We assessed to what extent patient characteristics, clinician-rated and postsurgical outcome measures, and patient-reported satisfaction with facial appearance and quality-of-life are associated with patient-reported satisfaction with treatment outcome after a primary upper blepharoplasty. Methods: This study was performed in 583 patients with an upper blepharoplasty between 2016 and 2021. The primary outcome was satisfaction with treatment outcome 6 months postoperatively using the FACE-Q. Determinants were baseline patient characteristics (demographics), preoperative and postoperative clinician-rated and surgical outcome measures, and preoperative and postoperative FACE-Q appearance and quality-of-life scales. Hierarchical linear regression analysis was used to determine how much of the variance in satisfaction with outcome could be explained by these groups of determinants. Results: A total of 63% of the variance could be explained by the five groups of determinants of which 8% was explained by the baseline patient characteristics and clinician-rated and patient-reported outcomes together, another 8% by the postoperative clinician-rated outcomes, and the remaining 47% by the postoperative patient-reported outcomes. Conclusions: Patient characteristics, clinician-rated outcome measures, and baseline FACE-Q appearance and quality-of-life scores were of limited value in explaining satisfaction with treatment outcome. However, the postoperative FACE-Q appearance scale and the decision to undergo a blepharoplasty were strongly associated with satisfaction with treatment outcome.

"Patient-Reported Satisfaction and Health-Related Quality of Life in Patients with Breast Augmentation: A follow-up of six months".

BACKGROUND: To evaluate the success of a breast augmentation, it is essential to measure outcomes from the patient perspective since a successful aesthetic result is especially determined by the patient. This study aimed to evaluate patient-reported satisfaction with their breasts, psychosocial, physical, and sexual well-being in patients undergoing breast augmentation using validated questionnaires. METHODS: This is a multicenter cohort study based on ongoing routinely-collected data. Patient-reported satisfaction and health-related quality of life were assessed with the BREAST-Q Augmentation Module at intake and six months postoperatively. RESULTS: A total of 1405 patients were included. Large changes in BREAST-Q scores (range, 0-100) between intake and six months postoperatively were seen: satisfaction with their breasts (mean, effect size: +57, 3.8), psychosocial well-being (+38, 2.1), physical well-being (-14, -1.2), and sexual well-being (+44, 2.4). Moreover, improvements in all four scales were not dependent on their intake scores and all postoperative scores reached similar levels. A decreased physical well-being of the chest was measured post-surgery. The satisfaction with the breasts scale correlated moderately to strongly with the psychosocial and sexual well-being scale 6 months post-surgery. Subgroup analysis based on patient characteristics found no differences in outcomes, except for BMI. CONCLUSION: Significant improvement in patient-reported satisfaction with their breasts, psychosocial, and sexual well-being can be seen six months after breast augmentation despite a declined physical well-being after treatment. Postoperative satisfaction levels do not depend on preoperative scores. These insights can contribute to improve preoperative communication between surgeon and patient regarding the expected outcomes.

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.

Outcomes of an exercise program in patients with dorsal or volar midcarpal laxity: a cohort study of 213 patients.

PURPOSE: Describing the outcomes of an exercise program on wrist and hand function for patients with midcarpal instability (MCI). MATERIALS AND METHODS: This study has a prospective cohort design. Two hundred and thirteen patients with MCI were included. The intervention was a 3-month exercise program consisting of hand therapy and home exercises. The primary outcome was perceived wrist and hand function evaluated with the Patient-Rated Wrist/Hand Evaluation (PRWHE) three months after treatment onset. Secondary outcomes were conversion to surgery, pain, and satisfaction with treatment results. RESULTS: PRWHE total scores improved from 51 ± 19 (mean ± SD) to 33 ± 24 at 3 months (95% CI: 36-30, p < 0.001). All visual analog scales for pain demonstrated clinically relevant improvements at 6 weeks and 3 months (p < 0.001). At 3 months, 81% of the participants would undergo the treatment again. After a median follow-up of 2.8 years, 46 patients (22%) converted to surgery. CONCLUSIONS: We found clinically relevant improvements in hand and wrist function and pain. Most participants would undergo treatment again and 78% of the participants did not convert to surgery. Hence, non-invasive treatment should be the primary treatment choice for patients with MCI.

Midcarpal instability (MCI) is a disabling condition and treatment options are limited.Patients with MCI can benefit from an exercise program aiming to improve the strength and coordination of the wrist muscles.Participants improved in hand/wrist function and 78% did not convert to surgery.Non-invasive treatment should be the primary treatment choice for these patients.

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.

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.

Collaborative hand surgery clinical research without sharing individual patient data; proof of principle study.

High-quality research in hand surgery is increasingly important. A vital component is national and international multicenter collaborative research because of better generalizability and larger sample sizes. However, sharing patient data between centers can be hampered by regulations and privacy issues or reluctance to share patient data. Therefore, in this paper, we illustrate an approach for collaborative clinical research without sharing patient data while obtaining similar outcomes. To illustrate that this collaborative clinical research approach without sharing patient data leads to similar outcomes compared to aggregating all individual patient data in one database, we simulate an approach of performing meta-analyses on summary statistics of individual-center data. In the simulation, we compare the results to conventional analyses in an existing multicenter database of patients treated for Dupuytren's disease at three different centers with either limited fasciectomy (LF) or needle aponeurotomy (PNF). We share example data and all analysis code in a public GitHub Library. We found similar results for the meta-analysis approach without sharing individual patient data as in the conventional approach for 1) the proportion of patients treated for recurrences, 2) the Total MHQ score after both treatments, 3) the comparison of Total MHQ score after both treatments, and 4) the comparison of both treatments when correcting for confounders with regression analysis. CLINICAL SIGNIFICANCE: We illustrate how collaborative studies can be performed without sharing individual patient data while obtaining similar results as with conventional analyses. This approach can help speed up collaborative research without losing precision in outcome analysis.

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.

Predicting Clinically Relevant Patient-Reported Symptom Improvement After Carpal Tunnel Release: A Machine Learning Approach.

BACKGROUND: Symptom improvement is an important goal when considering surgery for carpal tunnel syndrome. There is currently no prediction model available to predict symptom improvement for patients considering a carpal tunnel release (CTR). OBJECTIVE: To predict using a model the probability of clinically relevant symptom improvement at 6 mo after CTR. METHODS: We split a cohort of 2119 patients who underwent a mini-open CTR and completed the Boston Carpal Tunnel Questionnaire preoperatively and 6 mo postoperatively into training (75%) and validation (25%) data sets. Patients who improved more than the minimal clinically important difference of 0.8 at the Boston Carpal Tunnel Questionnaire-symptom severity scale were classified as "improved." Logistic regression, random forests, and gradient boosting machines were considered to train prediction models. The best model was selected based on discriminative ability (area under the curve) and calibration in the validation data set. This model was further assessed in a holdout data set (N = 397). RESULTS: A gradient boosting machine with 5 predictors was chosen as optimal trade-off between discriminative ability and the number of predictors. In the holdout data set, this model had an area under the curve of 0.723, good calibration, sensitivity of 0.77, and specificity of 0.55. The positive predictive value was 0.50, and the negative predictive value was 0.81. CONCLUSION: We developed a prediction model for clinically relevant symptom improvement 6 mo after a CTR, which required 5 patient-reported predictors (18 questions) and has reasonable discriminative ability and good calibration. The model is available online and might help shared decision making when patients are considering a CTR.

Associations between positive treatment outcome expectations, illness understanding, and outcomes: a cohort study on non-operative treatment of first carpometacarpal osteoarthritis.

PURPOSE: More positive outcome expectations and illness perceptions are associated with better outcomes for patients with several osteoarthritic orthopedic conditions. However, it is unknown whether these factors also influence outcomes of non-operative treatment for first carpometacarpal osteoarthritis (CMC-1 OA). Therefore, we assess the role of pre-treatment outcome expectations and illness perceptions in reports of pain and hand function 3 months after non-operative treatment for CMC-1 OA. MATERIALS AND METHODS: We conducted a cohort study with 219 patients treated non-operatively for CMC-1 OA between September 2017 and October 2018. Patients were included in the study if they completed measures of pain and hand function, illness perceptions (scale: 0-10), and expectations (scale: 3-27) as part of routine outcome measurements. Pain and hand function were measured before treatment and 3 months after starting treatment using the Dutch version of the Michigan Hand Outcomes Questionnaire. Multivariable linear regression analysis was used to assess the influence of outcome expectations and illness perceptions on pain and hand function. RESULTS: Both positive outcome expectations (B = 0.64; 95% CI [0.1-1.2]) and a better illness understanding (an illness perception subdomain; B = 1.53; 95% CI [0.2-2.9]) at baseline were associated with less pain at 3 months. For hand function, similar estimates were found. CONCLUSIONS: We found that positive outcome expectations and a better illness understanding, were associated with a better outcome of non-operative treatment for CMC-1 OA.IMPLICATIONS FOR REHABILITATIONNon-operative treatment can often be successful for patients with arthritis of the thumb.Outcome expectations and illness perceptions are associated with pain and hand function 3 months after non-operative treatment for thumb base osteoarthritis.Improving the outcome expectations and illness perceptions of patients through better education could improve the outcome of non-operative treatment.

Assessment of Patient Satisfaction With Appearance, Psychological Well-being, and Aging Appraisal After Upper Blepharoplasty: A Multicenter Prospective Cohort Study.

BACKGROUND: To determine the success of an upper blepharoplasty, a popular cosmetic procedure, it is essential to measure outcomes from the patient perspective because these often outweigh objective outcomes. OBJECTIVES: This study aimed to assess patient-reported satisfaction with facial appearance, psychological well-being, and aging appraisal after upper blepharoplasty with validated questionnaires. METHODS: This prospective cohort study included upper blepharoplasty patients from 8 outpatient clinics. Patient-reported satisfaction was assessed with the FACE-Q at intake, and 6 and 12 months postoperatively. RESULTS: In total, 2134 patients were included. High satisfaction with outcome and decision to undergo treatment were measured 6 months postoperatively. Large improvements in FACE-Q scores (range, 0-100) between intake and 6 months postoperatively were seen for satisfaction with appearance (mean, effect size: eyes +48, 2.6; upper eyelids +48, 3.1; facial appearance overall +26, 1.4), psychological well-being (+11, 0.56), and aging appraisal (+22, 1.0). Patients reported they appeared a mean [standard deviation] 3.3 [5.2] years younger postblepharoplasty. No clinically relevant changes were seen between 6 and 12 months. Additionally, improvements in appearance were not dependent on their intake scores, whereas improvements in psychological well-being and aging appraisal were smaller in patients with higher intake scores. Satisfaction with treatment outcome was strongly correlated with appearance satisfaction but not with aging appraisal. CONCLUSIONS: Significant improvements in patient satisfaction regarding appearance, psychological well-being, and aging appraisal can be seen 6 months after blepharoplasty, and outcomes remain stable up to 12 months postoperatively. These data may be used to inform patients and clinicians and improve the overall quality of care.

Long-term patient-reported outcomes for open surgery of the triangular fibrocartilage complex.

AIMS: Studies on long-term patient-reported outcomes after open surgery for triangular fibrocartilage complex (TFCC) are scarce. Surgeons and patients would benefit from self-reported outcome data on pain, function, complications, and satisfaction after this surgery to enhance shared decision-making. The aim of this study is to determine the long-term outcome of adults who had open surgery for the TFCC. METHODS: A prospective cohort study that included patients with open surgery for the TFCC between December 2011 and September 2015. In September 2020, we sent these patients an additional follow-up questionnaire, including the Patient-Rated Wrist Evaluation (PRWE), to score satisfaction, complications, pain, and function. RESULTS: A total of 113 patients were included in the analysis. At ≥ 60 months after an open TFCC reinsertion, we found a mean PRWE total score of 19 (SD 21), a mean PRWE pain score of 11 (SD 11), and a PRWE function score of 9 (SD 10). The percentage of patients obtaining minimum clinically important difference rose from 77% at 12 months to 83% at more than 60 months (p < 0.001). Patients reported fewer complications than surgeons, and overall complication rate was low. CONCLUSION: Outcomes of patient-reported pain, function scores, and satisfaction are improved five years after open surgery for the TFCC. Cite this article: Bone Jt Open 2021;2(11):981-987.

Closing the loop: a 10-year experience with routine outcome measurements to improve treatment in hand surgery.

Routine outcome measurements as a critical prerequisite of value-based healthcare have received considerable attention recently. There has been less attention for the last step in value-based healthcare where measurement of outcomes also leads to improvement in the quality of care. This is probably not without reason, since the last part of the learning cycle: 'Closing the loop', seems the hardest to implement.The journey from measuring outcomes to changing daily care can be troublesome. As early adopters of value-based healthcare, we would like to share our 10 years of experience in this journey.Examples of feedback loops are shown based on outcome measurements implemented to improve our daily care process as a focused hand surgery and hand therapy clinic.Feedback loops can be used to improve shared decision making, to monitor or predict treatment progression over time, for extreme value detection, improve journal clubs, and surgeon evaluation.Our goal as surgeons to improve treatment should not stop at the act of implementing routine outcome measurements.We should implement routine analysis and routine feedback loops, because real-time performance feedback can accelerate our learning cycle. Cite this article: EFORT Open Rev 2021;6:439-450. DOI: 10.1302/2058-5241.6.210012.