A Last-Ditch Effort and Personalized Surgeon Letter Improves PROMs Follow-Up Rate in Sports Medicine Patients: A Crossover Randomized Controlled Trial

Methods to increase response to postal and electronic questionnaires

BACKGROUND

Self-administered questionnaires are widely used to collect data in epidemiological research, but non-response reduces the effective sample size and can introduce bias. Finding ways to increase response to postal and electronic questionnaires would improve the quality of epidemiological research.

OBJECTIVES

To identify effective strategies to increase response to postal and electronic questionnaires.

SEARCH METHODS

We searched 14 electronic databases up to December 2021 and manually searched the reference lists of relevant trials and reviews. We contacted the authors of all trials or reviews to ask about unpublished trials; where necessary, we also contacted authors to confirm the methods of allocation used and to clarify results presented.

SELECTION CRITERIA

Randomised trials of methods to increase response to postal or electronic questionnaires. We assessed the eligibility of each trial using pre-defined criteria.

DATA COLLECTION AND ANALYSIS

We extracted data on the trial participants, the intervention, the number randomised to intervention and comparison groups and allocation concealment. For each strategy, we estimated pooled odds ratios (OR) and 95% confidence intervals (CI) in a random-effects model. We assessed evidence for selection bias using Egger's weighted regression method and Begg's rank correlation test and funnel plot. We assessed heterogeneity amongst trial odds ratios using a Chi2 test and quantified the degree of inconsistency between trial results using the I2 statistic.

MAIN RESULTS

Postal We found 670 eligible trials that evaluated over 100 different strategies of increasing response to postal questionnaires. We found substantial heterogeneity amongst trial results in half of the strategies. The odds of response almost doubled when: using monetary incentives (odds ratio (OR) 1.86; 95% confidence interval (CI) 1.73 to 1.99; heterogeneity I2 = 85%); using a telephone reminder (OR 1.96; 95% CI 1.03 to 3.74); and when clinical outcome questions were placed last (OR 2.05; 95% CI 1.00 to 4.24). The odds of response increased by about half when: using a shorter questionnaire (OR 1.58; 95% CI 1.40 to 1.78); contacting participants before sending questionnaires (OR 1.36; 95% CI 1.23 to 1.51; I2 = 87%); incentives were given with questionnaires (i.e. unconditional) rather than when given only after participants had returned their questionnaire (i.e. conditional on response) (OR 1.53; 95% CI 1.35 to 1.74); using personalised SMS reminders (OR 1.53; 95% CI 0.97 to 2.42); using a special (recorded) delivery service (OR 1.68; 95% CI 1.36 to 2.08; I2 = 87%); using electronic reminders (OR 1.60; 95% CI 1.10 to 2.33); using intensive follow-up (OR 1.69; 95% CI 0.93 to 3.06); using a more interesting/salient questionnaire (OR 1.73; 95% CI 1.12 to 2.66); and when mentioning an obligation to respond (OR 1.61; 95% CI 1.16 to 2.22). The odds of response also increased with: non-monetary incentives (OR 1.16; 95% CI 1.11 to 1.21; I2 = 80%); a larger monetary incentive (OR 1.24; 95% CI 1.15 to 1.33); a larger non-monetary incentive (OR 1.15; 95% CI 1.00 to 1.33); when a pen was included (OR 1.44; 95% CI 1.38 to 1.50); using personalised materials (OR 1.15; 95% CI 1.09 to 1.21; I2 = 57%); using a single-sided rather than a double-sided questionnaire (OR 1.13; 95% CI 1.02 to 1.25); using stamped return envelopes rather than franked return envelopes (OR 1.23; 95% CI 1.13 to 1.33; I2 = 69%), assuring confidentiality (OR 1.33; 95% CI 1.24 to 1.42); using first-class outward mailing (OR 1.11; 95% CI 1.02 to 1.21); and when questionnaires originated from a university (OR 1.32; 95% CI 1.13 to 1.54). The odds of response were reduced when the questionnaire included questions of a sensitive nature (OR 0.94; 95% CI 0.88 to 1.00). Electronic We found 88 eligible trials that evaluated over 30 different ways of increasing response to electronic questionnaires. We found substantial heterogeneity amongst trial results in half of the strategies. The odds of response tripled when: using a brief letter rather than a detailed letter (OR 3.26; 95% CI 1.79 to 5.94); and when a picture was included in an email (OR 3.05; 95% CI 1.84 to 5.06; I2 = 19%). The odds of response almost doubled when: using monetary incentives (OR 1.88; 95% CI 1.31 to 2.71; I2 = 79%); and using a more interesting topic (OR 1.85; 95% CI 1.52 to 2.26). The odds of response increased by half when: using non-monetary incentives (OR 1.60; 95% CI 1.25 to 2.05); using shorter e-questionnaires (OR 1.51; 95% CI 1.06 to 2.16; I2 = 94%); and using a more interesting e-questionnaire (OR 1.85; 95% CI 1.52 to 2.26). The odds of response increased by a third when: offering survey results as an incentive (OR 1.36; 95% CI 1.16 to 1.59); using a white background (OR 1.31; 95% CI 1.10 to 1.56); and when stressing the benefits to society of response (OR 1.38; 95% CI 1.07 to 1.78; I2 = 41%). The odds of response also increased with: personalised e-questionnaires (OR 1.24; 95% CI 1.17 to 1.32; I2 = 41%); using a simple header (OR 1.23; 95% CI 1.03 to 1.48); giving a deadline (OR 1.18; 95% CI 1.03 to 1.34); and by giving a longer time estimate for completion (OR 1.25; 95% CI 0.96 to 1.64). The odds of response were reduced when: "Survey" was mentioned in the e-mail subject (OR 0.81; 95% CI 0.67 to 0.97); when the email or the e-questionnaire was from a male investigator, or it included a male signature (OR 0.55; 95% CI 0.38 to 0.80); and by using university sponsorship (OR 0.84; 95%CI 0.69 to 1.01). The odds of response using a postal questionnaire were over twice those using an e-questionnaire (OR 2.33; 95% CI 2.25 to 2.42; I2 = 98%). Response also increased when: providing a choice of response mode (electronic or postal) rather than electronic only (OR 1.76 95% CI 1.67 to 1.85; I2 = 97%); and when administering the e-questionnaire by computer rather than by smartphone (OR 1.62 95% CI 1.36 to 1.94).

AUTHORS' CONCLUSIONS

Researchers using postal and electronic questionnaires can increase response using the strategies shown to be effective in this Cochrane review.

Changes From Baseline in Patient- Reported Outcomes at 1 Year Versus 2 Years After Rotator Cuff Repair: A Systematic Review and Meta-analysis

BACKGROUND

Most orthopaedic journals currently require reporting outcomes of surgical interventions for at least 2 postoperative years, but there have been no rigorous studies on this matter. Various patient-reported outcome (PRO) measures (PROMs) have been used to assess the status of the shoulder after rotator cuff repair (RCR).

HYPOTHESIS

We hypothesized that the mean shoulder-specific PROMs at 1 year improve substantially over baseline but that there is no clinically meaningful difference between the mean 1- and 2-year PROMs after RCR.

STUDY DESIGN

Meta-analysis; Level of evidence, 2.

METHODS

We conducted a systematic review of published randomized controlled trials (RCTs) and prospective cohort studies (level of evidence 1 and 2) reporting the shoulder-specific American Shoulder and Elbow Surgeons (ASES), the Constant, or the Western Ontario Rotator Cuff (WORC) Index scores at baseline, 1 year, and 2 years after RCR. The methodologic quality of studies was assessed. Also, the random effects meta-analyses of changes in PROMs for each of the first and second postoperative years were conducted.

RESULTS

Fifteen studies (n = 11 RCTs; n = 4 cohort studies) with a total of 1371 patients were included. Studies were highly heterogeneous, but no visual evidence of major publication bias was observed. The weighted means of the baseline PROMs were 46.2 points for the ASES score, 46.4 points for the Constant score, and 38.8 points for the WORC Index. The first-year summary increments were 41.1 (95% CI, 36.0-46.2) points for the ASES score, 34.2 (95% CI, 28.8-39.6) points for the Constant score, and 42.9 (95% CI, 37.3-48.4) points for the WORC Index. In contrast, the second-year summary increments were 2.3 (95% CI, 1-3.6) points for the ASES score, 3.2 (95% CI, 1.9-4.4) points for the Constant score, and 2 (95% CI, -0.1 to 4) points for the WORC Index.

CONCLUSION

All PROMs improved considerably from baseline to 1 year, but only very small gains that were below the minimal clinically important differences were observed between 1 year and 2 years after RCR. This study did not find any evidence for requiring a minimum of 2 years of follow-up for publication of PROs after RCR. Our results suggest that focusing on 1-year PROMs after RCR would foster more timely reporting, better control of selection bias, and better allocation of research resources.

Loss to patient-reported outcome measure follow-up after hip arthroplasty and knee arthroplasty

Aims

The aim of this study was to determine satisfaction rates after hip and knee arthroplasty in patients who did not respond to postoperative patient-reported outcome measures (PROMs), characteristics of non-responders, and contact preferences to maximize response rates.

Methods

A prospective cohort study of patients planned to undergo hip arthroplasty (n = 713) and knee arthroplasty (n = 737) at a UK university teaching hospital who had completed preoperative PROMs questionnaires, including the EuroQol five-dimension health-related quality of life score, and Oxford Hip Score (OHS) and Oxford Knee Score (OKS). Follow-up questionnaires were sent by post at one year, including satisfaction scoring. Attempts were made to contact patients who did not initially respond. Univariate, logistic regression, and receiver operator curve analysis was performed.

Results

At one year, 667 hip patients (93.5%) and 685 knee patients (92.9%) had undergone surgery and were alive. No response was received from 151/667 hip patients (22.6%), 83 (55.0%) of whom were ultimately contacted); or from 108/685 knee patients (15.8%), 91 (84.3%) of whom were ultimately contacted. There was no difference in satisfaction after arthroplasty between initial non-responders and responders for hips (74/81 satisfied vs 476/516 satisfied; p = 0.847) or knees (81/93 satisfied vs 470/561 satisfied; p = 0.480). Initial non-response and persistent non-response was associated with younger age, higher BMIs, and worse preoperative PROMs for both hip and knee patients (p < 0.050). Being in employment was associated with persistent non-response for hip patients (p = 0.047). Multivariate analysis demonstrated that younger age (p < 0.038), higher BMI (p = 0.018), and poorer preoperative OHS (p = 0.031) were independently associated with persistent non-response to hip PROMs. No independent associations were identified for knees. Using a threshold of > 66.4 years predicted a preference for contact by post (area under the curve 0.723 (95% confidence interval (CI) 0.647 to 0.799; p < 0.001, though this CI crosses the 0.7 limit considered reliable).

Conclusion

The majority of initial non-responders were ultimately contactable with effort. Satisfaction rates were not inferior in patients who did not initially respond to PROMs.

Cite this article: Bone Jt Open 2022;3(4):275–283.

Nonresponder bias in hand surgery: analysis of 1945 cases lost to follow-up over a 6-year period

The primary aim of this study was to identify factors associated with nonresponse to routinely collected patient-reported outcome measures (PROMs) after hand surgery. The secondary aim was to investigate the impact of nonresponder bias on postoperative PROMs. We identified 4357 patient episodes for which the patients received pre- and 1-year postoperative questionnaires. The response rate was 55%. Univariate and regression analyses were undertaken to determine factors predicting nonresponse. We developed a predictive model for the postoperative Quick version of the Disabilities of the Arm, Shoulder, and Hand (QuickDASH) scores for nonresponders using imputation. Younger age, increasing deprivation, higher comorbidity, worse preoperative QuickDASH scores and unemployment predicted nonresponse. No significant difference in mean postoperative QuickDASH score was observed between the responders, and the scores for the responders combined with the predicted scores for the nonresponders. Preoperative function was the primary predictor of postoperative outcome. These results challenge the dogma that 'loss to follow-up' automatically invalidates the results of a study.Level of evidence: III.

Feasibility and acceptability of electronic administration of patient reported outcomes using mHealth platform in emergency department patients with non-medical opioid use

Background

The emergency department (ED) offers an important opportunity to identify patients with opioid use disorder (OUD) and initiate treatment. However, post-ED follow-up is challenging, and novel approaches to enhance care transitions are urgently needed. Outcomes following ED visits have traditionally focused on overdose, treatment engagement, and mortality with an absence of patient reported outcomes (PROs), for example patient ability to schedule follow-up OUD treatment appointments or pick up a prescription medication, that may better inform evaluation of treatment pathways and near-term outcomes after acute events. In the context of increasing novel secure mobile health (mHealth) platforms, we explored the feasibility and acceptability of electronically collecting PROs from ED patients with non-medical opioid use to enhance care in the ED and transitions of care.

Methods

ED patients with non-medical opioid use or opioid overdose who endorsed willingness and ability to complete electronic surveys after discharge were enrolled from a tertiary, urban academic ED. Participants were enrolled in an mHealth platform, shared electronic health records with researchers, and completed electronic surveys of PROs at baseline, three- and thirty-days post discharge from the hospital, including questions about ability to schedule a follow-up appointment, pick up a prescription medication and overdose risk behaviors. Primary outcomes were measures of feasibility and acceptability of electronic PRO collection among ED patients with non-medical opioid use.

Results

Among 1,808 patients assessed for eligibility between June-December 2019, 101 of 130 (78%) eligible adult patients consented to participate. Ninety-six (95%) of 101 patients completed registration in the mHealth platform, and 77/96 (80%) were successful in sharing their electronic health data. Completion rates for the baseline, three-day and thirty-day surveys were 97% (93/96), 49% (47/96) and 42% (40/96). Implementation challenges included short engagement window during ED visit, limited access to smartphones/computers, insufficient battery life of participant phone to access email and password, forgotten emails and passwords, multi-step verification processes for account set-up, and complaints about hospital care, most of which were effectively addressed by study personnel.

Conclusions

ED patients with OUD were willing to share electronic health information and PROs, although implementation challenges were common, and more than half of participants were lost-to-follow-up after hospital discharge at 30 days. Efforts to streamline communication and remove barriers to engagement are needed to improve the collection of PROs and pathways of care in ED patients with OUD.

Clinical Trial Registration ClinicalTrials.gov (NCT03985163). Date of Registration: June 10, 2019, Retrospectively registered (First enrollment June 8, 2019). https://clinicaltrials.gov/ct2/show/record/NCT03985163

Strategies to improve retention in randomised trials

BACKGROUND

Poor retention of participants in randomised trials can lead to missing outcome data which can introduce bias and reduce study power, affecting the generalisability, validity and reliability of results. Many strategies are used to improve retention but few have been formally evaluated.

OBJECTIVES

To quantify the effect of strategies to improve retention of participants in randomised trials and to investigate if the effect varied by trial setting.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Scopus, PsycINFO, CINAHL, Web of Science Core Collection (SCI-expanded, SSCI, CPSI-S, CPCI-SSH and ESCI) either directly with a specified search strategy or indirectly through the ORRCA database. We also searched the SWAT repository to identify ongoing or recently completed retention trials. We did our most recent searches in January 2020.

SELECTION CRITERIA

We included eligible randomised or quasi-randomised trials of evaluations of strategies to increase retention that were embedded in 'host' randomised trials from all disease areas and healthcare settings. We excluded studies aiming to increase treatment compliance.

DATA COLLECTION AND ANALYSIS

We extracted data on: the retention strategy being evaluated; location of study; host trial setting; method of randomisation; numbers and proportions in each intervention and comparator group. We used a risk difference (RD) and 95% confidence interval (CI) to estimate the effectiveness of the strategies to improve retention. We assessed heterogeneity between trials. We applied GRADE to determine the certainty of the evidence within each comparison.

MAIN RESULTS

We identified 70 eligible papers that reported data from 81 retention trials. We included 69 studies with more than 100,000 participants in the final meta-analyses, of which 67 studies evaluated interventions aimed at trial participants and two evaluated interventions aimed at trial staff involved in retention. All studies were in health care and most aimed to improve postal questionnaire response. Interventions were categorised into broad comparison groups: Data collection; Participants; Sites and site staff; Central study management; and Study design. These intervention groups consisted of 52 comparisons, none of which were supported by high-certainty evidence as determined by GRADE assessment. There were four comparisons presenting moderate-certainty evidence, three supporting retention (self-sampling kits, monetary reward together with reminder or prenotification and giving a pen at recruitment) and one reducing retention (inclusion of a diary with usual follow-up compared to usual follow-up alone). Of the remaining studies, 20 presented GRADE low-certainty evidence and 28 presented very low-certainty evidence. Our findings do provide a priority list for future replication studies, especially with regard to comparisons that currently rely on a single study.

AUTHORS' CONCLUSIONS

Most of the interventions we identified aimed to improve retention in the form of postal questionnaire response. There were few evaluations of ways to improve participants returning to trial sites for trial follow-up. None of the comparisons are supported by high-certainty evidence. Comparisons in the review where the evidence certainty could be improved with the addition of well-done studies should be the focus for future evaluations.

Associations of preoperative patient mental health status and sociodemographic and clinical characteristics with baseline pain, function, and satisfaction in patients undergoing primary shoulder arthroplasty

HYPOTHESIS AND BACKGROUND

Shoulder pain and dysfunction are common indications for shoulder arthroplasty, yet the factors that are associated with these symptoms are not fully understood. This study aimed to investigate the associations of patient and disease-specific factors with preoperative patient-reported outcome measures (PROMs) in patients undergoing primary shoulder arthroplasty. We hypothesized that worse mental health status assessed by the Veterans RAND 12-Item Health Survey (VR-12) mental component score (MCS), glenoid bone loss, and increasing rotator cuff tear severity would be associated with lower values for the preoperative total Penn Shoulder Score (PSS) and its pain, function, and satisfaction subscores.

METHODS

We prospectively identified 12 patient factors and 4 disease-specific factors as possible statistical predictors of preoperative PROMs in patients undergoing primary shoulder arthroplasty at a single institution over a 3-year period. Multivariable statistical modeling and Akaike information criterion comparisons were used to investigate the unique associations with, and relative importance of, these factors in accounting for variation in the preoperative PSS and its subscores.

RESULTS

A total of 788 cases performed by 12 surgeons met the inclusion criteria, with a preoperative median total PSS of 31 points (pain, 10 points; function, 18 points; and satisfaction, 1 point). As hypothesized, a lower VR-12 MCS was associated with lower preoperative PSS pain, function, and total scores, but patients with intact status or small to medium rotator cuff tears had modestly lower PSS pain subscores (ie, more pain) than patients with large to massive superior-posterior rotator cuff tears. Glenoid bone loss was not associated with the preoperative PSS. Female sex and fewer years of education (for all 4 outcomes), lower VR-12 MCS and preoperative opioid use (for all outcomes but satisfaction), and rotator cuff tear severity (for pain only) were the factors most prominently associated with preoperative PROMs.

CONCLUSION

In addition to mental health status and rotator cuff tear status, patient sex, years of education, and preoperative opioid use were most prominently associated with preoperative PROMs in patients undergoing shoulder arthroplasty. Further studies are needed to investigate whether these factors will also predict postoperative PROMs.