Further optimization of the reliability of the 28-joint disease activity score in patients with early rheumatoid arthritis

BACKGROUND: The 28-joint Disease Activity Score (DAS28) combines scores on a 28-tender and swollen joint count (TJC28 and SJC28), a patient-reported measure for general health (GH), and an inflammatory marker (either the erythrocyte sedimentation rate [ESR] or the C-reactive protein [CRP]) into a composite measure of disease activity in rheumatoid arthritis (RA). This study examined the reliability of the DAS28 in patients with early RA using principles from generalizability theory and evaluated whether it could be increased by adjusting individual DAS28 component weights. METHODS: Patients were drawn from the DREAM registry and classified into a "fast response" group (N = 466) and "slow response" group (N = 80), depending on their pace of reaching remission. Composite reliabilities of the DAS28-ESR and DAS28-CRP were determined with the individual components' reliability, weights, variances, error variances, correlations and covariances. Weight optimization was performed by minimizing the error variance of the index. RESULTS: Composite reliabilities of 0.85 and 0.86 were found for the DAS28-ESR and DAS28-CRP, respectively, and were approximately equal across patients groups. Component reliabilities, however, varied widely both within and between sub-groups, ranging from 0.614 for GH ("slow response" group) to 0.912 for ESR ("fast response" group). Weight optimization increased composite reliability even further. In the total and "fast response" groups, this was achieved mostly by decreasing the weight of the TJC28 and GH. In the "slow response" group, though, the weights of the TJC28 and SJC28 were increased, while those of the inflammatory markers and GH were substantially decreased. CONCLUSIONS: The DAS28-ESR and the DAS28-CRP are reliable instruments for assessing disease activity in early RA and reliability can be increased even further by adjusting component weights. Given the low reliability and weightings of the general health component across subgroups it is recommended to explore alternative patient-reported outcome measures for inclusion in the DAS28

Big Data for personalized healthcare

Big Data, often defined according to the 5V model (volume, velocity, variety, veracity and value), is seen as the key towards personalized healthcare. However, it also confronts us with new technological and ethical challenges that require more sophisticated data management tools and data analysis techniques. This vision paper aims to better understand the technological and ethical challenges we face when using and managing Big Data in healthcare as well as the way in which it impacts our way of working, our health, and our wellbeing. A mixed-methods approach (including a focus group, interviews, and an analysis of social media) was used to gain a broader picture about the pros and cons of using Big Data for personalized healthcare from three different perspectives: Big Data experts, healthcare workers, and the online public. All groups acknowledge the positive aspects of applying Big Data in healthcare, touching upon a wide array of issues, both scientifically and socially. By sharing health data, value can be created that goes beyond the individual patient. The Big Data revolution in healthcare is seen as a promising and innovative development. Yet potential facilitators and barriers need to be faced first to reach its full potential. Concerns were raised about privacy, trust, reliability, safety, purpose limitation, liability, profiling, data ownership, and loss of autonomy. Also, the importance of adding the people-centered view to the rather data-centered 5V model is stressed, in order to get a grip on the opportunities for using Big Data in personalized healthcare. People should be aware that the development of Big Data advancements is not self-evident

Validity of summing painful joint sites to assess joint-pain comorbidity in hip or knee osteoarthritis

BACKGROUND: Previous studies in patients with hip and knee osteoarthritis (OA) have advocated the relevance of assessing the number of painful joint sites, other than the primary affected joint, in both research and clinical practice. However, it is unclear whether joint-pain comorbidities can simply be summed up. METHODS: A total of 401 patients with hip or knee OA completed questionnaires on demographic variables and joint-pain comorbidities. Rasch analysis was performed to evaluate whether a sum score of joint-pain comorbidities can be calculated. RESULTS: Self-reported joint-pain comorbidities showed a good fit to the Rasch model and were not biased by gender, age, disease duration, BMI, or patient group. As a group, joint-pain comorbidities covered a reasonable range of severity levels, although the sum score had rather low reliability levels suggesting it cannot discriminate well among patients. CONCLUSIONS: Joint-pain comorbidities, in other than the primary affected joints, can be summed into a joint pain comorbidity score. Nevertheless, its use is discouraged for individual decision making purposes since its lacks discriminative power in patients with minimal or extreme joint pain

Translation and validation of the Dutch version of the Effective Consumer Scale (EC-17)

PURPOSE: The Effective Consumer Scale (EC-17) measures the skills of musculoskeletal patients in managing their own healthcare. The objectives of this study were to translate the EC-17 into Dutch and to further evaluate its psychometric properties. METHODS: The EC-17 was translated and cognitively pretested following cross-cultural adaptation guidelines. Two hundred and thirty-eight outpatients (52 % response rate) with osteoarthritis or fibromyalgia completed the EC-17 along with other validated measures. Three weeks later, 101 patients completed the EC-17 again. RESULTS: Confirmatory factor analysis supported the unidimensional structure of the scale. The items adequately fit the Rasch model and only one item demonstrated differential item functioning. Person reliability was high (0.92), but item difficulty levels tended to cluster around the middle of the scale, and measurement precision was highest for moderate and lower levels of skills. The scale demonstrated adequate test-retest reliability (ICC = 0.71), and correlations with other measures were largely as expected. CONCLUSION: The results supported the validity and reliability of the Dutch version of the EC-17, but suggest that the scale is best targeted at patients with relatively low levels of skills. Future studies should further examine its sensitivity to change in a clinical trial specifically aimed at improving effective consumer skills

Technology to support integrated Antimicrobial Stewardship Programs:A user centered and stakeholder driven development approach

The rise of antimicrobial resistance (AMR) is a severe global health problem. Tackling this problem requires the prudent prescribing of antimicrobials. This is promoted through Antimicrobial Stewardship Programs (ASPs). In this position paper we describe i) how a socio-technical multidisciplinary approach (based on the CeHRes Roadmap) can be applied in the development and implementation of Antimicrobial Stewardship technologies and ii) how this approach can be of value to support Antimicrobial Stewardship in practice. The CeHRes Roadmap entails five different phases to explore and test how an eHealth technology can be tailored to the target group and successfully implemented in practice: i) contextual inquiry, ii) value specification, iii) design, iv) operationalization, v) evaluation. In this position paper we describe the lessons learned from research and practice to guide future developments of technology based ASP interventions. Since AMR is a huge wicked problem on a global level, it requires innovative methods and models to empower general public and professionals to be proactive rather than reactive in a digitalized world. We highlight how to combat the dangerous rise of antimicrobial resistance in the future