Can peer effects explain prescribing appropriateness? a social network analysis.

BACKGROUND: Optimizing prescribing practices is important due to the substantial clinical and financial costs of polypharmacy and an increasingly aging population. Prior research shows the importance of social relationships in driving prescribing behaviour. Using social network analysis, we examine the relationship between a physician practices' connectedness to peers and their prescribing performance in two German regions. METHODS: We first mapped physician practice networks using links established between two practices that share 8 or more patients; we calculated network-level (density, average path length) and node-level measures (degree, betweenness, eigenvector). We defined prescribing performance as the total number of inappropriate medications prescribed or appropriate medications not prescribed (PIMs) to senior patients (over the age of 65) during the calendar year 2016. We used FORTA (Fit fOR The Aged) algorithm to classify medication appropriateness. Negative binomial regression models estimate the association between node-level measures and prescribing performance of physician practices controlling for patient comorbidity, provider specialization, percentage of seniors in practice, and region. We conducted two sensitivity analyses to test the robustness of our findings - i) limiting the network mapping to patients younger than 65; ii) limiting the network ties to practices that share more than 25 patients. RESULTS: We mapped two patient-sharing networks including 436 and 270 physician practices involving 28,508 and 20,935 patients and consisting of 217,126 and 154,274 claims in the two regions respectively. Regression analyses showed a practice's network connectedness as represented by degree, betweenness, and eigenvector centrality, is significantly negatively associated with prescribing performance (degree-bottom vs. top quartile aRR = 0.04, 95%CI: 0.035,0.045; betweenness-bottom vs. top quartile aRR = 0.063 95%CI: 0.052,0.077; eigenvector-bottom vs. top quartile aRR = 0.039, 95%CI: 0.034,0.044). CONCLUSIONS: Our study provides evidence that physician practice prescribing performance is associated with their peer connections and position within their network. We conclude that practices occupying strategic positions at the edge of networks with advantageous access to novel information are associated with better prescribing outcomes, whereas highly connected practices embedded in insulated information environments are associated with poor prescribing performance.

Cooperation Improvement in an Integrated Healthcare Network: A Social Network Analysis.

Background: Cooperation is a core feature of integrated healthcare systems and an important link in their value-creating mechanism. The premise is that providers who cooperate can promote more efficient use of health services while improving health outcomes. We studied the performance of an integrated healthcare system in improving regional cooperation. Methods: Using claims data and social network analysis, we constructed the professional network from 2004 to 2017. Cooperation was studied by analyzing the evolution of network properties at network and physician practice (node) level. The impact of the integrated system was studied with a dynamic panel model that compared practices that participated in the integrated system versus nonparticipants. Results: The regional network evolved favourably towards cooperation. Network density increased 1.4% on average per year, while mean distance decreased 0.78%. At the same time, practices participating in the integrated system became more cooperative compared to other practices in the region: Degree (1.64e-03, p = 0.07), eigenvector (3.27e-03, p = 0.06) and betweenness (4.56e-03, p < 0.001) centrality increased more for participating practices. Discussion: Findings can be explained by the holistic approach to patients' care needs and coordination efforts of integrated healthcare. The paper provides a valuable design for performance assessment of professional cooperation. Highlights: Using claims data and social network analysis, we identify a regional cooperation network and conduct a panel analysis to measure the impact of an integrated care initiative on enhancing professional cooperation.Physician practices participating in the integrated system became more cooperative and improved their influence in the regional network more than non-participating practices.Integrated healthcare systems effectively incentivize cooperation through a holistic approach to patient care needs and coordination efforts.

Improving the evaluation of an integrated healthcare system using entropy balancing: Population health improvements in Gesundes Kinzigtal.

Background: Evidence of integrated healthcare networks' effect on population health is scarce. Moreover, current designs for evaluating such networks have shortcomings that can result in misleading conclusions. Our paper evaluates Gesundes Kinzigtal, a best-practice integrated healthcare network, using an innovative design that enlightens the discussion about health gains produced by integrated healthcare. Research question: What is the effect of Gesundes Kinzigtal on population health? Methods: We evaluated the effect of the integrated healthcare initiative by performing a quasi-experimental evaluation based on entropy balancing. Integrated network participants were compared to a control group and followed for five years. Claims data from 2004 to 2018 was used. Population health outcomes correspond to survival (Cox hazard ratio, Kaplan-Meier curve), mortality ratio, mean age at the time of death, and years of life lost or gained. Design validity was evaluated by assessing group balance at baseline. Finally, we compared our results to those obtained using a previously published design for evaluating integrated networks. Results: The treatment group was composed of 9083 network participants, compared to an equivalent control group, showing, respectively, a mortality ratio of 5.4% vs 7.5% (p < 0.05), mean age at the time of death of 80.1 vs 80.3 (p > 0.05) and a gain of 0.2 years of life per person for the treatment group (p > 0.05). The Cox hazard ratio (0.72; p < 0.05) and mean survival time (1784 vs 1768 days; p < 0.05) showed better survival for treated participants. Results using the previously published design were more favorable for the treatment group; however, the design excluded participants significantly associated with greater healthcare needs. Discussion: The integrated network had a favorable effect on participants' mortality and survival risk. Previous evaluations based on propensity score matching might overestimate the network's impact on population health by excluding participants with greater healthcare needs.

Exploring Changes to the Actionability of COVID-19 Dashboards Over the Course of 2020 in the Canadian Context: Descriptive Assessment and Expert Appraisal Study.

BACKGROUND: Public web-based COVID-19 dashboards are in use worldwide to communicate pandemic-related information. Actionability of dashboards, as a predictor of their potential use for data-driven decision-making, was assessed in a global study during the early stages of the pandemic. It revealed a widespread lack of features needed to support actionability. In view of the inherently dynamic nature of dashboards and their unprecedented speed of creation, the evolution of dashboards and changes to their actionability merit exploration. OBJECTIVE: We aimed to explore how COVID-19 dashboards evolved in the Canadian context during 2020 and whether the presence of actionability features changed over time. METHODS: We conducted a descriptive assessment of a pan-Canadian sample of COVID-19 dashboards (N=26), followed by an appraisal of changes to their actionability by a panel of expert scorers (N=8). Scorers assessed the dashboards at two points in time, July and November 2020, using an assessment tool informed by communication theory and health care performance intelligence. Applying the nominal group technique, scorers were grouped in panels of three, and evaluated the presence of the seven defined features of highly actionable dashboards at each time point. RESULTS: Improvements had been made to the dashboards over time. These predominantly involved data provision (specificity of geographic breakdowns, range of indicators reported, and explanations of data sources or calculations) and advancements enabled by the technologies employed (customization of time trends and interactive or visual chart elements). Further improvements in actionability were noted especially in features involving local-level data provision, time-trend reporting, and indicator management. No improvements were found in communicative elements (clarity of purpose and audience), while the use of storytelling techniques to narrate trends remained largely absent from the dashboards. CONCLUSIONS: Improvements to COVID-19 dashboards in the Canadian context during 2020 were seen mostly in data availability and dashboard technology. Further improving the actionability of dashboards for public reporting will require attention to both technical and organizational aspects of dashboard development. Such efforts would include better skill-mixing across disciplines, continued investment in data standards, and clearer mandates for their developers to ensure accountability and the development of purpose-driven dashboards.

Simulation modeling to assess performance of integrated healthcare systems: Literature review to characterize the field and visual aid to guide model selection.

BACKGROUND: The guiding principle of many health care reforms is to overcome fragmentation of service delivery and work towards integrated healthcare systems. Even though the value of integration is well recognized, capturing its drivers and its impact as part of health system performance assessment is challenging. The main reason is that current assessment tools only insufficiently capture the complexity of integrated systems, resulting in poor impact estimations of the actions taken towards the 'Triple Aim'. We describe the unique nature of simulation modeling to consider key health reform aspects: system complexity, optimization of actions, and long-term assessments. RESEARCH QUESTION: How can the use and uptake of simulation models be characterized in the field of performance assessment of integrated healthcare systems? METHODS: A systematic search was conducted between 2000 and 2018, in 5 academic databases (ACM D. Library, CINAHL, IEEE Xplore, PubMed, Web of Science) complemented with grey literature from Google Scholar. Studies using simulation models with system thinking to assess system performance in topics relevant to integrated healthcare were selected for revision. RESULTS: After screening 2274 articles, 30 were selected for analysis. Five modeling techniques were characterized, across four application areas in healthcare. Complexity was defined in nine aspects, embedded distinctively in each modeling technique. 'What if?' & 'How to?' scenarios were identified as methods for system optimization. The mean time frame for performance assessments was 18 years. CONCLUSIONS: Simulation models can evaluate system performance emphasizing the complex relations between components, understanding the system's adaptability to change in short or long-term assessments. These advantages position them as a useful tool for complementing performance assessment of integrated healthcare systems in their pursuit of the 'Triple Aim'. Besides literacy in modeling techniques, accurate model selection is facilitated after identification and prioritization of the complexities that rule system performance. For this purpose, a tool for selecting the most appropriate simulation modeling techniques was developed.

Features Constituting Actionable COVID-19 Dashboards: Descriptive Assessment and Expert Appraisal of 158 Public Web-Based COVID-19 Dashboards.

BACKGROUND: Since the outbreak of COVID-19, the development of dashboards as dynamic, visual tools for communicating COVID-19 data has surged worldwide. Dashboards can inform decision-making and support behavior change. To do so, they must be actionable. The features that constitute an actionable dashboard in the context of the COVID-19 pandemic have not been rigorously assessed. OBJECTIVE: The aim of this study is to explore the characteristics of public web-based COVID-19 dashboards by assessing their purpose and users ("why"), content and data ("what"), and analyses and displays ("how" they communicate COVID-19 data), and ultimately to appraise the common features of highly actionable dashboards. METHODS: We conducted a descriptive assessment and scoring using nominal group technique with an international panel of experts (n=17) on a global sample of COVID-19 dashboards in July 2020. The sequence of steps included multimethod sampling of dashboards; development and piloting of an assessment tool; data extraction and an initial round of actionability scoring; a workshop based on a preliminary analysis of the results; and reconsideration of actionability scores followed by joint determination of common features of highly actionable dashboards. We used descriptive statistics and thematic analysis to explore the findings by research question. RESULTS: A total of 158 dashboards from 53 countries were assessed. Dashboards were predominately developed by government authorities (100/158, 63.0%) and were national (93/158, 58.9%) in scope. We found that only 20 of the 158 dashboards (12.7%) stated both their primary purpose and intended audience. Nearly all dashboards reported epidemiological indicators (155/158, 98.1%), followed by health system management indicators (85/158, 53.8%), whereas indicators on social and economic impact and behavioral insights were the least reported (7/158, 4.4% and 2/158, 1.3%, respectively). Approximately a quarter of the dashboards (39/158, 24.7%) did not report their data sources. The dashboards predominately reported time trends and disaggregated data by two geographic levels and by age and sex. The dashboards used an average of 2.2 types of displays (SD 0.86); these were mostly graphs and maps, followed by tables. To support data interpretation, color-coding was common (93/158, 89.4%), although only one-fifth of the dashboards (31/158, 19.6%) included text explaining the quality and meaning of the data. In total, 20/158 dashboards (12.7%) were appraised as highly actionable, and seven common features were identified between them. Actionable COVID-19 dashboards (1) know their audience and information needs; (2) manage the type, volume, and flow of displayed information; (3) report data sources and methods clearly; (4) link time trends to policy decisions; (5) provide data that are "close to home"; (6) break down the population into relevant subgroups; and (7) use storytelling and visual cues. CONCLUSIONS: COVID-19 dashboards are diverse in the why, what, and how by which they communicate insights on the pandemic and support data-driven decision-making. To leverage their full potential, dashboard developers should consider adopting the seven actionability features identified.

Robotic-assisted surgery in medial unicompartmental knee arthroplasty: does it improve the precision of the surgery and its clinical outcomes? Systematic review.

There is a high prevalence of knee osteoarthritis that affects only the medial tibiofemoral compartment. In this group of patients with severe disease, the medial unicompartmental knee arthroplasty (UKA) is an excellent choice. However, this technique has a great learning curve due to the lower tolerance of improper positioning and alignment. In this context, the robotic-assisted surgery (RAS) arises as an option to improve the accuracy and secondarily enhance the clinical outcomes related to the UKA. The objective in this study is to determine if there are significant advantages with the use of RAS over conventional surgery (CS). In the systematic review of the literature, classification of the results in three main subjects: (A) precision and alignment; (B) functional results and clinical parameters; (C) survivorship. We found 272 studies, of which 15 meet the inclusion and exclusion criteria. There is mostly described that RAS significantly improves the accuracy in position (80-100% of planned versus performed P < 0.05), alignment (2-3 times less error variance P < 0.05) and selection of the proper size of the implants (69.23% of correct size femoral implants versus 16.67% using CS P < 0.0154). Recently, there is mild evidence about benefits in the early rehabilitation and post-operative pain, but in all studies reviewed, there is no advantages of RAS in the long-term functional evaluation. There is no strong literature that supports a longer survival of the prothesis with RAS, being the longest mean follow-up reported of 29.6 months. RAS is a useful tool in increasing the precision of the medial UKA implant placement. However, there is still a lack of evidence that properly correlates this improvement in accuracy with better clinical, functional and survival results.