Developing a core outcome set for acetabular fractures: a systematic review protocol.

BACKGROUND: Clinical trials investigating acetabular fractures are heterogeneous in their investigated outcomes and their corresponding measurements. Standardization may facilitate comparability and pooling of research results, which would lead to an increase in knowledge about the optimal treatment of acetabular fractures, resulting in long-term evidence-based treatment decisions and improvements in patient care. The aim of this systematic review is to identify the reported outcomes and their measurements from studies on treatments for acetabular fractures to develop a core outcome set which contains the most relevant outcome measures to be included in future studies. METHODS: Studies published in English and German including patients aged 16 years and older, with a surgically treated acetabular fracture, will be included. Studies with nonsurgical treatment, pathologic fractures, polytraumatized patients, and patients younger than 16 years of age will be excluded because other outcomes may be of interest in these cases. Any prospective and retrospective study will be included. Systematic reviews will be excluded, but their included studies will be screened for eligibility. The literature will be searched on MEDLINE, CENTRAL, Web of Science, ClinicalTrials.gov, and WHO ICTRP. Risk of selective reporting of outcomes will be assessed using the Outcome Reporting Bias in Trials classification system. Heterogeneously defined outcomes that measure the same outcome will be grouped and subsequently categorized into outcome domains using the taxonomy of the Core Outcome Measures in Effectiveness Trials Initiative. DISCUSSION: It is expected that a high number of studies will be included, and many outcomes will be identified using different definitions and measurement instruments. A limitation of this systematic review is that only previously investigated outcomes will be detected, thus disregarding potentially relevant outcomes. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022357644.

Changes in cognitive function after a 12-week POWER rehabilitation in older adults with schizophrenia and frailty.

BACKGROUND: The effectiveness of isolated resistance training (RT) on cognitive function among older adults with schizophrenia is insufficiently investigated. This study investigated the effectiveness of 12-weeks POWER rehabilitation, a novel RT regimen, on cognitive function among older patients with schizophrenia and frailty. METHODS: Thirty-two older adults with schizophrenia and frailty were enrolled and randomized to receive either a 12-week, twice weekly POWER rehabilitation, or without add-on training. Cognitive functioning was assessed using mini-mental state examination (MMSE), digit symbol substitution test, color trail task (CTT), and digit span task (DST). Physical performance was assessed by walking speed and hand grip strength. The generalized estimating equations was used to compare pre- and post-training outcome measure between groups. RESULTS: Between-group analysis revealed significant improvement in CTT1 and hand grip strength in the intervention group compared to the controls. Subgroup analyses showed CTT1 performance significantly improved after 12 weeks of POWER rehabilitation in the intervention group (time, p < .001), independent of age, educational level, global cognition, depressive symptoms, and psychotropic medication use. Increased hand grip strength was significantly associated with improved performance in MMSE, CTT1, and DST forward at study endpoint. CONCLUSION: A 12-week POWER rehabilitation for older patients with schizophrenia and frailty is safe and feasible, and may benefit physical and some domains of cognitive functioning.

Machine learning models for abstract screening task - A systematic literature review application for health economics and outcome research.

OBJECTIVE: Systematic literature reviews (SLRs) are critical for life-science research. However, the manual selection and retrieval of relevant publications can be a time-consuming process. This study aims to (1) develop two disease-specific annotated corpora, one for human papillomavirus (HPV) associated diseases and the other for pneumococcal-associated pediatric diseases (PAPD), and (2) optimize machine- and deep-learning models to facilitate automation of the SLR abstract screening. METHODS: This study constructed two disease-specific SLR screening corpora for HPV and PAPD, which contained citation metadata and corresponding abstracts. Performance was evaluated using precision, recall, accuracy, and F1-score of multiple combinations of machine- and deep-learning algorithms and features such as keywords and MeSH terms. RESULTS AND CONCLUSIONS: The HPV corpus contained 1697 entries, with 538 relevant and 1159 irrelevant articles. The PAPD corpus included 2865 entries, with 711 relevant and 2154 irrelevant articles. Adding additional features beyond title and abstract improved the performance (measured in Accuracy) of machine learning models by 3% for HPV corpus and 2% for PAPD corpus. Transformer-based deep learning models that consistently outperformed conventional machine learning algorithms, highlighting the strength of domain-specific pre-trained language models for SLR abstract screening. This study provides a foundation for the development of more intelligent SLR systems.

Key factors in the choice of appropriate outcomes for clinical trials. / Factores clave en la elección de desenlaces apropiados para estudios clínicos.

Health research is the foundation of medical knowledge and healthcare system recommendations. Therefore, choosing appropriate outcomes in studies of therapeutic interventions is a fundamental step in producing evidence and, subsequently, for decision-making. In this article, we propose three key factors for the choice of outcomes: the inclusion of patient-reported outcomes, since they focus on the patient's perception of their health status and quality of life; the consideration of clinically relevant outcomes, which are direct measurements of the patient's health status and, therefore, will be decisive in decision-making; and the use of core outcome sets, a tool that standardizes the measurement and interpretation of outcomes, facilitating the production and synthesis of appropriate evidence for the evidence ecosystem. The correct choice of outcomes will help health decision-makers and clinicians deliver appropriate patient-centered care and optimize the use of resources in healthcare and clinical research.

La investigación en salud es la base del conocimiento médico y de las recomendaciones en los sistemas de salud. Por ello, la elección de desenlaces apropiados en estudios de intervenciones terapéuticas es un paso fundamental en la producción de evidencia y, posteriormente, para la toma de decisiones. En este artículo proponemos tres factores clave para la elección de desenlaces: la inclusión de desenlaces reportados por pacientes, ya que ponen el foco del efecto de la intervención en la percepción que tienen los propios pacientes de su estado de salud y calidad de vida; la consideración de desenlaces clínicamente relevantes, los cuales son mediciones directas del estado de salud del paciente y, por ende serán determinantes en la toma de decisiones; y la utilización de herramienta que estandariza y permite la homogeneización en la medición e interpretación de desenlaces, facilitando la producción y posterior síntesis de evidencia apropiada para el ecosistema de evidencia. La correcta elección de los desenlaces permitirá que la evidencia generada de estos estudios ayude a los tomadores de decisiones en salud y los profesionales clínicos a entregar cuidados apropiados centrados en el paciente y a optimizar el uso de recursos en salud e investigación clínica.

Analysis of outcome reporting in sciatic neuropathy studies: a systematic review of the literature.

PURPOSE: As a first step towards developing a core outcome set (COS) for sciatic neuropathy, the goal of the current study was to perform a systematic review of the literature to identify outcome measures that have been previously reported in studies on sciatic neuropathy. METHODS: A systematic review of the literature from 2000-2024 was performed utilizing PubMed and Medical Subject Headings (MeSH). Identified articles were screened according to study inclusion/exclusion criteria. Outcome measures reported in each included study were recorded and categorized into motor, sensory, pain, patient-reported outcomes, electrodiagnostic outcomes, imaging outcomes, and composite outcomes. Descriptive statistics were performed. RESULTS: A total of 1586 articles were initially identified, and 31 articles met criteria for inclusion and underwent analysis. The most common outcome domain was pain. A pain outcome was reported in 17 (63%) studies. A motor outcome was reported in 10 (37%) studies; 6 (22%) reported a sensory outcome; 1 (4%) reported a composite outcome; 4 (15%) reported an electrodiagnostic outcome; 5 (19%) reported a patient-reported outcome; 3 (11%) reported an imaging outcome. Across the included studies, 21 unique outcomes were reported. CONCLUSIONS: We have identified the outcome measures that have previously been utilized in studies on sciatic neuropathy. Previously used outcome measures fell into seven domains: motor outcomes, sensory outcomes, pain outcomes, patient-reported outcomes, electrodiagnostic outcomes, imaging outcomes, and composite outcomes. Pain outcomes were most commonly used across the included studies.

Factors Associated With Early Motor Function Trajectories in DMD After Glucocorticoid Initiation: Post Hoc Analysis of the FOR-DMD Trial.

BACKGROUND AND OBJECTIVES: Clinical trials in Duchenne muscular dystrophy (DMD) require 3-6 months of stable glucocorticoids, and the primary outcome is explored at 48-52 weeks. The factors that influence the clinical outcome assessment (COA) trajectories soon after glucocorticoid initiation are relevant for the design and analysis of clinical trials of novel drugs. We describe early COA trajectories, associated factors, and the time from glucocorticoid initiation to COA peak. METHODS: This was a prospective 18-month analysis of the Finding the Optimum Corticosteroid Regimen for Duchenne Muscular Dystrophy study. Four COAs were investigated: rise from supine velocity (RFV), 10-meter walk/run velocity (10MWRV), North Star Ambulatory Assessment (NSAA) total score, and 6-minute walk test distance (6MWT). The relationships of baseline age (4-5 vs 6-7 years), COA baseline performance, genotype, and glucocorticoid regimen (daily vs intermittent) with the COA trajectories were evaluated using linear mixed-effects models. RESULTS: One hundred ninety-six glucocorticoid-naïve boys with DMD aged 4-7 years were enrolled. The mean age at baseline was 5.9 ± 1.0 years, 66% (n = 130) were on daily regimens, 55% (n = 107) showed a 6MWT distance >330 metres; 41% (n = 78) showed RFV >0.2 rise/s; 76% (n = 149) showed 10MWRV >0.142 10m/s, and 41.0% (n = 79) showed NSAA total score >22 points. Mean COA trajectories differed by age at glucocorticoid initiation (p < 0.01 for RFV, 10MWRV, and NSAA; p < 0.05 for 6MWT) and regimen (p < 0.01 for RFV, 10MWRV, and NSAA). Boys younger than 6 years reached their peak performance 12-18 months after glucocorticoid initiation. Boys aged 6 years or older on a daily regimen peaked between months 9 and 12 and those on an intermittent regimen by 9 months. The baseline COA performance was associated with the NSAA (p < 0.01) and the 6MWT trajectory in boys younger than 6 years on a daily regimen (p < 0.01). Differences in the mean trajectories by genotype were not significant. DISCUSSION: Glucocorticoid regimen, age, duration of glucocorticoid exposure, and baseline COA performance need to be considered in the design and analysis of clinical trials in young boys with DMD.

Network meta-analysis for an ordinal outcome when outcome categorization varies across trials.

BACKGROUND: Binary outcomes are likely the most common in randomized controlled trials, but ordinal outcomes can also be of interest. For example, rather than simply collecting data on diseased versus healthy study subjects, investigators may collect information on the severity of disease, with no disease, mild, moderate, and severe disease as possible levels of the outcome. While some investigators may be interested in all levels of the ordinal variable, others may combine levels that are not of particular interest. Therefore, when research synthesizers subsequently conduct a network meta-analysis on a network of trials for which an ordinal outcome was measured, they may encounter a network in which outcome categorization varies across trials. METHODS: The standard method for network meta-analysis for an ordinal outcome based on a multinomial generalized linear model is not designed to accommodate the multiple outcome categorizations that might occur across trials. In this paper, we propose a network meta-analysis model for an ordinal outcome that allows for multiple categorizations. The proposed model incorporates the partial information provided by trials that combine levels through modification of the multinomial likelihoods of the affected arms, allowing for all available data to be considered in estimation of the comparative effect parameters. A Bayesian fixed effect model is used throughout, where the ordinality of the outcome is accounted for through the use of the adjacent-categories logit link. RESULTS: We illustrate the method by analyzing a real network of trials on the use of antibiotics aimed at preventing liver abscesses in beef cattle and explore properties of the estimates of the comparative effect parameters through simulation. We find that even with the categorization of the levels varying across trials, the magnitudes of the biases are relatively small and that under a large sample size, the root mean square errors become small as well. CONCLUSIONS: Our proposed method to conduct a network meta-analysis for an ordinal outcome when the categorization of the outcome varies across trials, which utilizes the adjacent-categories logit link, performs well in estimation. Because the method considers all available data in a single estimation, it will be particularly useful to research synthesizers when the network of interest has only a limited number of trials for each categorization of the outcome.

Is the QCI framework suited for monitoring outcomes and costs in a teaching hospital using value-based healthcare principles? A retrospective cohort study.

OBJECTIVES: The objective is to develop a pragmatic framework, based on value-based healthcare principles, to monitor health outcomes per unit costs on an institutional level. Subsequently, we investigated the association between health outcomes and healthcare utilisation costs. DESIGN: This is a retrospective cohort study. SETTING: A teaching hospital in Rotterdam, The Netherlands. PARTICIPANTS: The study was performed in two use cases. The bariatric population contained 856 patients of which 639 were diagnosed with morbid obesity body mass index (BMI) <45 and 217 were diagnosed with morbid obesity BMI ≥45. The breast cancer population contained 663 patients of which 455 received a lumpectomy and 208 a mastectomy. PRIMARY AND SECONDARY OUTCOME MEASURES: The quality cost indicator (QCI) was the primary measures and was defined asQCI = (resulting outcome * 100)/average total costs (per thousand Euros)where average total costs entail all healthcare utilisation costs with regard to the treatment of the primary diagnosis and follow-up care. Resulting outcome is the number of patients achieving textbook outcome (passing all health outcome indicators) divided by the total number of patients included in the care path. RESULTS: The breast cancer and bariatric population had the highest resulting outcome values in 2020 Q4, 0.93 and 0.73, respectively. The average total costs of the bariatric population remained stable (avg, €8833.55, min €8494.32, max €9164.26). The breast cancer population showed higher variance in costs (avg, €12 735.31 min €12 188.83, max €13 695.58). QCI values of both populations showed similar variance (0.3 and 0.8). Failing health outcome indicators was significantly related to higher hospital-based costs of care in both populations (p <0.01). CONCLUSIONS: The QCI framework is effective for monitoring changes in average total costs and relevant health outcomes on an institutional level. Health outcomes are associated with hospital-based costs of care.

COS-PPA: protocol to develop a core outcome set for primary progressive aphasia.

INTRODUCTION: The term primary progressive aphasia (PPA) describes a group of language-led dementias. Disease-modifying treatments that delay, slow or reverse progression of PPA are currently lacking, though a number of interventions to manage the symptoms of PPA have been developed in recent years. Unfortunately, studies exploring the effectiveness of these interventions have used a variety of different outcome measures, limiting comparability. There are more constructs, apart from word retrieval, that are important for people with PPA that have not received much attention in the research literature. Existing core outcome sets (COS) for dementia and non-progressive aphasia do not meet the needs of people with PPA, highlighting a need to develop a specific COS for PPA. METHODS AND ANALYSIS: This protocol describes a three-stage study to identify a COS for PPA interventions in research and clinical practice. The stage 1 systematic review will identify existing speech, language and communication measures used to examine the effectiveness of interventions for PPA in the research literature. Employing a nominal group technique, stage 2 will identify the most important outcomes for people with PPA and their families. The data collected in stages 1 and 2 will be jointly analysed with the project PPI group and will inform the stage 2 modified Delphi consensus study to identify a core outcome measurement set for PPA among a range of research disciplines undertaking intervention studies for people with PPA. ETHICS AND DISSEMINATION: Ethical approval for stage 2 of the study has been sought individually in each country at collaborating institutions and is stated in detail in the manuscript. Stage 3 has been granted ethical approval by the Chairs of UCL Language and Cognition Department Ethics, Project ID LCD-2023-06. Work undertaken at stages 1, 2 and 3 will be published in open-access peer-reviewed journal articles and presented at international scientific conferences. PROSPERO REGISTRATION NUMBER: CRD42022367565.

Evaluation of Outcomes After Anterior Cruciate Ligament Reconstruction: What We Know, What We Have, and What to Consider.

Measurement of success following anterior cruciate ligament reconstruction (ACLR) hinges on the appropriate use of high quality and meaningful outcome measures. We identified and categorized over 100 outcome measures for ACLR using the International Classification of Functioning, Disability and Health (ICF) model. The ICF model is a useful framework to facilitate decisions about outcome selection and describe recovery following ACL injury. We outline key considerations when selecting outcome measures during study design (purpose, measurement properties, sample size, global assessment) or evaluating reported outcomes (measurement properties, sample size, magnitude/precision, clinical relevance, applicability), and discuss challenges in outcome measurement following ACLR.

Composite outcome measures in high-impact critical care randomised controlled trials: a systematic review.

BACKGROUND: The use of composite outcome measures (COM) in clinical trials is increasing. Whilst their use is associated with benefits, several limitations have been highlighted and there is limited literature exploring their use within critical care. The primary aim of this study was to evaluate the use of COM in high-impact critical care trials, and compare study parameters (including sample size, statistical significance, and consistency of effect estimates) in trials using composite versus non-composite outcomes. METHODS: A systematic review of 16 high-impact journals was conducted. Randomised controlled trials published between 2012 and 2022 reporting a patient important outcome and involving critical care patients, were included. RESULTS: 8271 trials were screened, and 194 included. 39.1% of all trials used a COM and this increased over time. Of those using a COM, only 52.6% explicitly described the outcome as composite. The median number of components was 2 (IQR 2-3). Trials using a COM recruited fewer participants (409 (198.8-851.5) vs 584 (300-1566, p = 0.004), and their use was not associated with increased rates of statistical significance (19.7% vs 17.8%, p = 0.380). Predicted effect sizes were overestimated in all but 6 trials. For studies using a COM the effect estimates were consistent across all components in 43.4% of trials. 93% of COM included components that were not patient important. CONCLUSIONS: COM are increasingly used in critical care trials; however effect estimates are frequently inconsistent across COM components confounding outcome interpretations. The use of COM was associated with smaller sample sizes, and no increased likelihood of statistically significant results. Many of the limitations inherent to the use of COM are relevant to critical care research.

Core Outcome Set for Necrotizing Enterocolitis Treatment Trials.

BACKGROUND AND OBJECTIVES: Variability in outcome reporting in necrotizing enterocolitis (NEC) treatment trials hinders conducting meta-analyses and implementing novel treatments. We aimed to develop a core outcome set (COS) for NEC treatment trials including outcome measures most relevant to patients and physicians, from NEC diagnosis to adulthood. METHODS: Clinicians and/or researchers from low-middle- and high-income countries were approached based on their scientific contributions to NEC literature, and patients and parents through local organizations. We presented participants with 45 outcomes used in NEC research, identified through a systematic review. To achieve consensus, outcomes were rated on a scale of 1 to 9 in 3 online Delphi rounds, and discussed at a final consensus meeting. RESULTS: Seventy-one participants from 25 countries completed all Delphi rounds, including 15 patients and family representatives. Thirteen outcomes reached consensus in one of the stakeholder groups and were included in the consensus meeting, 6 outcomes reached consensus in both groups. Twenty-seven participants from both high- and low-middle-income countries attended the online consensus meeting, including family representatives and NEC patients. After discussion and a final vote, 5 outcomes reached consensus to be included: mortality, NEC-related mortality, short bowel syndrome, quality of life, and neurodevelopmental impairment. CONCLUSIONS: This NEC COS includes 5 predominantly long-term outcomes agreed upon by clinicians, patients, and family representatives. Use of this international COS will help standardize outcome selection in clinical trials, ensure these are relevant to those most affected by NEC care, and, ultimately, improve the care of infants with NEC.

Multimorbidity prevalence and health outcome prediction: assessing the impact of lookback periods, disease count, and definition criteria in health administrative data at the population-based level.

BACKGROUND: Health administrative databases play a crucial role in population-level multimorbidity surveillance. Determining the appropriate retrospective or lookback period (LP) for observing prevalent and newly diagnosed diseases in administrative data presents challenge in estimating multimorbidity prevalence and predicting health outcome. The aim of this population-based study was to assess the impact of LP on multimorbidity prevalence and health outcomes prediction across three multimorbidity definitions, three lists of diseases used for multimorbidity assessment, and six health outcomes. METHODS: We conducted a population-based study including all individuals ages > 65 years on April 1st, 2019, in Québec, Canada. We considered three lists of diseases labeled according to the number of chronic conditions it considered: (1) L60 included 60 chronic conditions from the International Classification of Diseases (ICD); (2) L20 included a core of 20 chronic conditions; and (3) L31 included 31 chronic conditions from the Charlson and Elixhauser indices. For each list, we: (1) measured multimorbidity prevalence for three multimorbidity definitions (at least two [MM2+], three [MM3+] or four (MM4+) chronic conditions); and (2) evaluated capacity (c-statistic) to predict 1-year outcomes (mortality, hospitalisation, polypharmacy, and general practitioner, specialist, or emergency department visits) using LPs ranging from 1 to 20 years. RESULTS: Increase in multimorbidity prevalence decelerated after 5-10 years (e.g., MM2+, L31: LP = 1y: 14%, LP = 10y: 58%, LP = 20y: 69%). Within the 5-10 years LP range, predictive performance was better for L20 than L60 (e.g., LP = 7y, mortality, MM3+: L20 [0.798;95%CI:0.797-0.800] vs. L60 [0.779; 95%CI:0.777-0.781]) and typically better for MM3 + and MM4 + definitions (e.g., LP = 7y, mortality, L60: MM4+ [0.788;95%CI:0.786-0.790] vs. MM2+ [0.768;95%CI:0.766-0.770]). CONCLUSIONS: In our databases, ten years of data was required for stable estimation of multimorbidity prevalence. Within that range, the L20 and multimorbidity definitions MM3 + or MM4 + reached maximal predictive performance.

Fractional amplitude of low-frequency fluctuations in sensory-motor networks and limbic system as a potential predictor of treatment response in patients with schizophrenia.

BACKGROUND: Previous investigations have revealed substantial differences in neuroimaging characteristics between healthy controls (HCs) and individuals diagnosed with schizophrenia (SCZ). However, we are not entirely sure how brain activity links to symptoms in schizophrenia, and there is a need for reliable brain imaging markers for treatment prediction. METHODS: In this longitudinal study, we examined 56 individuals diagnosed with 56 SCZ and 51 HCs. The SCZ patients underwent a three-month course of antipsychotic treatment. We employed resting-state functional magnetic resonance imaging (fMRI) along with fractional Amplitude of Low Frequency Fluctuations (fALFF) and support vector regression (SVR) methods for data acquisition and subsequent analysis. RESULTS: In this study, we initially noted lower fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, coupled with higher fALFF values in the left hippocampus and right putamen in SCZ patients compared to the HCs at baseline. However, when comparing fALFF values in brain regions with abnormal baseline fALFF values for SCZ patients who completed the follow-up, no significant differences in fALFF values were observed after 3 months of treatment compared to baseline data. The fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, and the left postcentral gyrus were useful in predicting treatment effects. CONCLUSION: Our findings suggest that reduced fALFF values in the sensory-motor networks and increased fALFF values in the limbic system may constitute distinctive neurobiological features in SCZ patients. These findings may serve as potential neuroimaging markers for the prognosis of SCZ patients.

Federally Qualified Health Centers' Screening for Social Risk Factors and Health Outcomes.

Federally Qualified Health Centers (FQHCs) are ideally positioned to identify and address health-related social needs, but little is understood about the relationship between social risk factor (SRF) screening and health outcomes. We studied 1352 FQHCs from the 2019 Uniform Data System. Ordinary least squares regression was used to estimate the relationship between SRF screening and the percentage of patients with adequately controlled diabetes and hypertension. Results show 71% of the FQHCs in the sample collected SRFs. FQHCs' screened for SRFs had higher percentages of patients with adequately controlled diabetes (69.5% vs 67.0%, P < .001) and hypertension (63.8% vs 59.4%, P < .001) relative to FQHCs not collecting SRFs.

Categorization of the amyotrophic lateral sclerosis population via the clinical determinant of post-onset ΔFS for study design and medical practice.

The amyotrophic lateral sclerosis (ALS) functional rating scale-revised (ALSFRS-R) has become the most widely utilized measure of disease severity in patients with ALS, with change in ALSFRS-R from baseline being a trusted primary outcome measure in ALS clinical trials. This is despite the scale having several established limitations, and although alternative scales have been proposed, it is unlikely that these will displace ALSFRS-R in the foreseeable future. Here, we discuss the merits of delta FS (ΔFS), the slope or rate of ALSFRS-R decline over time, as a relevant tool for innovative ALS study design, with an as yet untapped potential for optimization of drug effectiveness and patient management. In our view, categorization of the ALS population via the clinical determinant of post-onset ΔFS is an important study design consideration. It serves not only as a critical stratification factor and basis for patient enrichment but also as a tool to explore differences in treatment response across the overall population; thereby, facilitating identification of responder subgroups. Moreover, because post-onset ΔFS is derived from information routinely collected as part of standard patient care and monitoring, it provides a suitable patient selection tool for treating physicians. Overall, post-onset ΔFS is a very attractive enrichment tool that is, can and should be regularly incorporated into ALS trial design.

Using the technology acceptance model to assess clinician perceptions and experiences with a rheumatoid arthritis outcomes dashboard: qualitative study.

BACKGROUND: Improving shared decision-making using a treat-to-target approach, including the use of clinical outcome measures, is important to providing high quality care for rheumatoid arthritis (RA). We developed an Electronic Health Record (EHR) integrated, patient-facing sidecar dashboard application that displays RA outcomes, medications, and lab results for use during clinical visits ("RA PRO dashboard"). The purpose of this study was to assess clinician perceptions and experiences using the dashboard in a university rheumatology clinic. METHODS: We conducted focus group (FG) discussions with clinicians who had access to the dashboard as part of a randomized, stepped-wedge pragmatic trial. FGs explored clinician perceptions towards the usability, acceptability, and usefulness of the dashboard. FG data were analyzed thematically using deductive and inductive techniques; generated themes were categorized into the domains of the Technology Acceptance Model (TAM). RESULTS: 3 FG discussions were conducted with a total of 13 clinicians. Overall, clinicians were enthusiastic about the dashboard and expressed the usefulness of visualizing RA outcome trajectories in a graphical format for motivating patients, enhancing patient understanding of their RA outcomes, and improving communication about medications. Major themes that emerged from the FG analysis as barriers to using the dashboard included inconsistent collection of RA outcomes leading to sparse data in the dashboard and concerns about explaining RA outcomes, especially to patients with fibromyalgia. Other challenges included time constraints and technical difficulties refreshing the dashboard to display real-time data. Methods for integrating the dashboard into the visit varied: some clinicians used the dashboard at the beginning of the visit as they documented RA outcomes; others used it at the end to justify changes to therapy; and a few shared it only with stable patients. CONCLUSIONS: The study provides valuable insights into clinicians' perceptions and experiences with the RA PRO dashboard. The dashboard showed promise in enhancing patient-clinician communication, shared decision-making, and overall acceptance among clinicians. Addressing challenges related to data collection, education, and tailoring dashboard use to specific patient populations will be crucial for maximizing its potential impact on RA care. Further research and ongoing improvements in dashboard design and implementation are warranted to ensure its successful integration into routine clinical practice.