We still do not have comprehensive knowledge of which framework of patient-centered care (PCC) is appropriate for diabetes care, which elements of PCC are evidence-based, and the mechanism by which PCC elements are associated with outcomes through mediators. In this review, we elaborate on these issues. We found that for diabetes care, PCC elements such as autonomy support (patient individuality), cooperation and collaboration (system-level approach), com-munication and education (behavior change techniques), emotional support (biopsychosocial approach), and family/other involvement and support are critically important. All of these factors are directly associated with different patient outcomes and indirectly associated with outcomes through patient activation. We present the practical implications of these PCC elements.
To analyze the amount of variation in these risk-adjusted adverse outcomes corresponding to the care of premature births. In addition, hospitals were ranked according to their unadjusted and adjusted rates, and we assessed the degree of concordance between these rankings. Finally, the correlations of hospital-adjusted adverse outcomes were also tested. The study utilized the 5-year Taiwan Premature Infant Follow-up Network (TPFN) database in Taiwan from 2014 to 2018, and the sample size was 6482. We calculated the "observed over expected" (OE) ratio every year to form the risk-adjusted adverse outcome rate for each hospital. There was a larger variation in the risk-adjusted rate for NEC and the second-largest variation for IVH. Regarding the concordances between the unadjusted and adjusted ranks, the ranks for mortality had the lowest concordance (coefficient of concordance 0.64), and only a few of the risk-adjusted rates between outcomes were significantly correlated. The results of the TPFN show that there is room to improve performance in terms of large variations in NEC and IVH. Furthermore, risk adjustment is important, especially for mortality, since the ranks for mortality have the lowest concordance. Finally, we cannot generate a conclusion regarding whether a hospital is high in quality if we only take 1 or 2 adverse outcomes as profiling measures because only a few of the risk-adjusted rates between outcomes were significantly correlated.
There is a lack of evidence that shows whether a report card can improve health outcomes in terms of infection rates or unscheduled readmission by using rigorous methods to evaluate its impact. We used the National Health Insurance Administration’s claims database from 1 January 2004 to 30 December 2013 and a time series analysis to evaluate the impact of the quality report card initiative on three negative outcomes of total knee replacement for each quarter of the year, including the rates of superficial infection of a knee replacement, deep infection of knee arthroplasty and unplanned readmissions for surgical site infection. These negative outcomes (original scale) do not show significant decreases in terms of superficial infection (−0.05‰, −0.63 to 0.53‰, P = 0.87), deep infection (−0.003‰, −0.19 to 0.18‰, P = 0.97) and unscheduled readmission (0.02‰, −0.21 to 0.25‰, P = 0.88). The total knee replacement public report card initiative did not improve the rate of infection and unscheduled readmission for surgical site infection. This report card in Taiwan should involve physicians’ participation in the design and be tailored to be suitable for reading by patients in order to further enhance the chance of improvement in these negative outcomes.