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Objectives Self-monitoring and patient-initiated care (PIC) leads to fewer outpatient clinic visits in patients with established RA with low disease activity (LDA) while healthcare outcomes are similar. This study assesses the cost-effectiveness of PIC with self-monitoring. Methods A 12-month randomized controlled trial was performed with 49 patients in the PIC with self-monitoring group (app-group) and 53 in usual care. The usual care group continued with preplanned visits. The app group had one planned follow-up visit after 12 months and monitored their RA disease activity in a smartphone app. Both groups could make additional appointments at liberty. We included adult RA patients with a disease duration of over 2 years, a disease activity score 28 (DAS28) below 3.2 that were stable on medication for at least 6 months. The effect measure, the DAS28, was measured at 12 months and healthcare resource usage and productivity losses were measured at 3, 6, 9 and 12 months. Results There was no significant difference in mean change of DAS28 (-0.04 mean difference, 95% CI: -0.39, 0.30), nor a statistically significant difference in total costs (mean difference €514, 95% CI:-€266, €3690) in the app group compared with the usual care group. The probability that the app was cost-effective was 0.37 and 0.57 at a willingness-to-pay threshold of 0 and 50 000 €/point improvement DAS28, respectively. Conclusion Although rheumatic care costs were significantly lower in the app group, total costs and effects of PIC with self-monitoring were not different from usual care in RA patients with LDA. [ABSTRACT FROM AUTHOR]

Objectives To identify highly ranked features related to clinicians' diagnosis of clinically relevant knee OA. Methods General practitioners (GPs) and secondary care physicians (SPs) were recruited to evaluate 5–10 years follow-up clinical and radiographic data of knees from the CHECK cohort for the presence of clinically relevant OA. GPs and SPs were gathered in pairs; each pair consisted of one GP and one SP, and the paired clinicians independently evaluated the same subset of knees. A diagnosis was made for each knee by the GP and SP before and after viewing radiographic data. Nested 5-fold cross-validation enhanced random forest models were built to identify the top 10 features related to the diagnosis. Results Seventeen clinician pairs evaluated 1106 knees with 139 clinical and 36 radiographic features. GPs diagnosed clinically relevant OA in 42% and 43% knees, before and after viewing radiographic data, respectively. SPs diagnosed in 43% and 51% knees, respectively. Models containing top 10 features had good performance for explaining clinicians' diagnosis with area under the curve ranging from 0.76–0.83. Before viewing radiographic data, quantitative symptomatic features (i.e. WOMAC scores) were the most important ones related to the diagnosis of both GPs and SPs; after viewing radiographic data, radiographic features appeared in the top lists for both, but seemed to be more important for SPs than GPs. Conclusions Random forest models presented good performance in explaining clinicians' diagnosis, which helped to reveal typical features of patients recognized as clinically relevant knee OA by clinicians from two different care settings. [ABSTRACT FROM AUTHOR]

Objectives Although there is a general focus on early diagnosis and treatment of hip OA, there are no validated diagnostic criteria for early-stage hip OA. The current study aimed to take the first steps in developing diagnostic criteria for early-stage hip OA, using factors obtained through history taking, physical examination, radiography and blood testing at the first consultation in individuals presenting with hip pain, suspicious for hip OA, in primary care. Methods Data of the 543 individuals with 735 symptomatic hips at baseline who had any follow-up data available from the prospective CHECK cohort study were used. A group of 26 clinical experts [general practitioners (GPs), rheumatologists and orthopaedic surgeons] evaluated standardized clinical assessment forms of all subjects on the presence of clinically relevant hip OA 5–10 years after baseline. Using the expert-based diagnoses as reference standard, a backward selection method was used to create predictive models based on pre-defined baseline factors from history taking, physical examination, radiography and blood testing. Results Prevalence of clinically relevant hip OA during follow-up was 22%. Created models contained four to eight baseline factors (mainly WOMAC pain items, painful/restricted movements and radiographic features) and obtained area under the curve between 0.62 (0.002) and 0.71 (0.002). Conclusion Based on clinical and radiographic features of hip OA obtained at first consultation at a GP for pain/stiffness of the hip, the prediction of clinically relevant hip OA within 5–10 years was 'poor' to 'fair'. [ABSTRACT FROM AUTHOR]