Background: Little is known about pain and opiate use at home directly after total knee replacement (TKR). Due to adverse effects, low opiate use is desired. An electronic health app (PainCoach) was developed to guide patients in pain control and opiate use. Objective: The aim of this paper was to investigate the effects of the PainCoach app on pain control and opiate use in patients who underwent TKR during the first 2 weeks at home after surgery. Methods: In an unblinded randomized controlled trial, patients scheduled for TKR were offline recruited and randomized to a PainCoach group or control group. In the PainCoach group, the PainCoach app was downloaded on each patient’s smartphone or tablet. In response to the patient’s input of the pain experienced, the PainCoach app gave advice on pain medication use, exercises/rest, and when to call the clinic. This advice was the same as that received during usual care. The control group received usual care. The primary outcomes were opiate use and visual analog scale (VAS) pain scores at rest, during activity, and at night during the first 2 weeks at home after surgery, which were collected daily from day 1 until 14 postoperatively by online questionnaires. The actual amount of app use was recorded, and active use was defined as ≥12 total app uses. Results: The pain scores did not differ between the groups. The PainCoach group (n=38) used 23.2% less opiates (95% CI −38.3 to −4.4; P=.02) and 14.6% more acetaminophen (95% CI 8.2-21.3; P<.001) when compared with the findings in the control group (n=33). The PainCoach app was used 12 (IQR 4.5-22.0) times per patient. In the active PainCoach subgroup (n=19), the following were noted when compared with the findings in the control group: 4.1 times faster reduction of the VAS pain score during activity (95% CI −7.5 to −0.8; P=.02), 6.3 times faster reduction of the VAS pain score at night (95% CI −10.1 to −2.6; P=.001), 44.3% less opiate use (95% CI −59.4 to −23.5; P<.001), 76.3% less gabapentin use (95% CI −86.0 to −59.8; P<.001), and 21.0% more acetaminophen use (95% CI 12.6-30.0; P<.001). Conclusions: The use of the PainCoach app contributes to reduced opiate use in the initial period at home after TKR. Active use of this app leads to a further reduction in opiate use and improved pain control. Trial Registration: ClinicalTrials.gov NCT03961152; https://clinicaltrials.gov/ct2/show/NCT03961152

The response rate on patient-reported outcome measurements (PROMs) necessary to adequately evaluate a treatment and improve patient care is unknown. Hospitals generally aim for the highest possible response rate without insight into the increase in costs involved. This study aimed to investigate which PROMs response rate is achievable in relation to the costs in an orthopaedic practice. In an observational study, patients planned for orthopaedic surgery were asked to participate per surgical procedure (5769 surgical procedures at 5300 patients). Patient-reported outcomes (PROs) collection with a digital online automated PROMs collection system (minimal effort) was compared to a combined automated system and manual collection (maximal effort). Response rate was calculated preoperative and at two postoperative time points separately, and on all three time points together. Costs were calculated for the study period, per year and per surgical procedure. Calculations were executed for all surgical procedures and for three subgroups: knee arthroplasty, hip arthroplasty and anterior cruciate ligament reconstruction (ACLR). Using maximal effort the response rate increased for all surgical procedures compared to minimal effort; the preoperative response rate from 86% to 100% and the postoperative response rates from 55% to 83% (3 or 6 months) and 53% to 83% (12 months). Concerning the response at all three time points for all surgical procedures, minimal effort resulted in 44% response rate and increased to 76% with maximal effort. Lowest postoperative response rates were found in the ACLR group for both maximal and minimal effort. A costs difference of €5.55–€5.98 per surgical procedure between maximal and minimal effort was found. A two times higher PROMs response rate for patients responding at all three time points (44% versus 76%) is achievable with maximal effort compared to the use of an automated PROMs collection system only. Manual collection adds a cost of €5.5–€6 per surgical procedure to automated PROMs collection alone. It is debatable if these additional costs are justifiable from a value-based health care perspective as the response rate for adequate evaluation of a treatment is still unknown.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Modern healthcare focuses on Shared Decision Making (SDM) because of its positive effects on patient satisfaction, therapy compliance, and outcomes. Patients’ knowledge about their illness and available treatment options, gained through medical education, is one of the key drivers for SDM. Current patient education relies heavily on medical consultation and is known to be ineffective. Objective: To determine whether providing patients with information in a subdivided, categorized, and interactive manner via an educational app for smartphone or tablet may increase the knowledge of their illness. Methods: A surgeon blinded randomized controlled trial was conducted with 213 patients who were referred to one of the six Dutch hospitals by their general practitioner owing to knee complaints that were indicative of knee osteoarthritis (OA). An interactive app that, in addition to standard care, actively sends informative and pertinent content to patients about their illness on a daily basis by means of push notifications in the week prior to their consultation. The primary outcome was the level of perceived and actual knowledge that patients had about their knee complaints and the relevant treatment options after the intervention. Results: In total 122 patients were enrolled in the control group and 91 in the intervention group. After the intervention, the level of actual knowledge (measured on a 0-36 scale) was 52% higher in the app group (26.4 versus 17.4, P < 0.001). Moreover, within the app group, the level of perceived knowledge (measured on a 0-25 scale) increased by 22% during the week within the app group (from 13.5 to 16.5, P < 0.001), compared to no gain in the control group. Conclusions: Actively offering patients information in a subdivided (per day), categorized (per theme), and interactive (video and quiz questions) manner significantly increases their levels of knowledge (both perceived and actual), compared to standard care educational practices. Clinical Trial: The trial was approved by the regional Medical Ethical Board (Maxima Medisch Centrum, Eindhoven, The Netherlands), reference number N16.130.

Background: Unknown is which response rate on patient-reported outcome measures (PROMs) is needed to both obtain an accurate outcome and ensure generalizability in evaluating total hip arthroplasty (THA) procedures. Without an evidence based minimum response rate (MRR) on THA PROMs, it is possible that hospitals report invalid patient-reported outcomes (PROs) due to a too low response rate. Alternatively, hospitals may invest too much in achieving an unnecessary high response rate. The aim of this study is to gain an insight into the MRR on PROMs needed to adequately evaluate THA procedures from a clinical perspective. Methods: Retrospective study on prospective collected data of primary, elective THA procedures was performed. MRR was investigated for each PROM (NRS pain at rest, NRS pain during activity, EQ-5D-3L, HOOS-PS, anchor function, OHS, anchor pain and NRS satisfaction) separately to calculate the primary outcome: MRR for the THA PROMs set. MRR on a PROM needed to have (condition 1.) similar PRO change score (3 month score minus preoperative score) including confidence interval, (condition 2.) maintaining the influence of each change score predictor and (condition 3.) equal distribution of each predictor, as those of a 100% PROM response rate group. Per PROM, a 100%-group was identified with all patients having the PRO change score. Randomly assessed groups of 90% till 10% response rate (in total 90 groups) were compared with the 100%-group. Linear mixed model analyses and linear regressions were executed. Results: The MRR for the THA PROMs set was 100% (range: 70–100% per PROM). The first condition resulted in a MRR of 60%, the second condition in a MRR of 100% and the third condition in a MRR of 10%. Conclusions: A 100% response rate on PROMs is needed in order to adequately evaluate THA procedures from a clinical perspective. All stakeholders using THA PROs should be aware that 100% of the THA patients should respond on both preoperative and 3 month postoperative PROMs. For now, taking the first step in improving evaluation of THA for quality control by achieving at least two of the three conditions of MRR, advised is to require a response rate on PROMs of 60% as the lower limit.

Background: Mobile eHealth apps are important tools in personal health care management. The Patient Journey app was developed to inform patients with musculoskeletal disorders during their perioperative period. The app contains timely information, video exercises, and functional tasks. Although the Patient Journey app and other health apps are widely used, little research is available on how patients appreciate these apps. Objective: The primary aim of this study was to evaluate the user-friendliness of the Patient Journey app in terms of its usability and the attitudes of users toward the app. The secondary aim was to evaluate positive and negative user experiences. Methods: A web-based questionnaire was sent to 2114 patients scheduled for surgery for a musculoskeletal disorder. Primary outcomes were usability (measured with the System Usability Scale) and user attitudes regarding the Patient Journey app (assessed with the second part of the eHealth Impact Questionnaire). The secondary outcomes were evaluated with multiple choice questions and open-ended questions, which were analyzed via inductive thematic content analyses. Results: Of the 940 patients who responded, 526 used the Patient Journey app. The usability of the app was high (System Usability Scale: median 85.0, IQR 72.5-92.5), and users had a positive attitude toward the Information and Presentation provided via the app (eHealth Impact Questionnaire: median 78.0, IQR 68.8-84.4). The app did not adequately improve the users’ confidence in discussing health with others (eHealth Impact Questionnaire: median 63.9, IQR 50.0-75.0) or motivation to manage health (eHealth Impact Questionnaire: median 61.1, IQR 55.6-72.2). Three core themes emerged regarding positive and negative user experiences: (1) content and information, (2) expectations and experiences, and (3) technical performance. Users experienced timely information and instructions positively and found that the app prepared and guided them optimally through the perioperative period. Negative user experiences were overly optimistic information, scarcely presented information about pain (medication), lack of reference data, insufficient information regarding clinical course deviations and complications, and lack of interaction with clinicians. Conclusions: The Patient Journey app is a usable, informative, and presentable tool to inform patients with musculoskeletal disorders during their perioperative period. The qualitative analyses identified aspects that can further improve the user experiences of the app.