Making Quality Improvement Data Meaningful for Long-Term Care Administrators

Tailoring feedback data to engage end-user stakeholders when sharing organizational context data is a central component of quality improvement and integrated knowledge translation. For over a decade, our research team has collected survey data (using the validated Alberta Context Tool) on modifiable aspects of organizational context from long-term care (LTC) staff (e.g., nurses, unregulated providers) across a representative cohort of 94 LTC facilities in Western Canada. We have fed back data at the facility and care unit level with the goal of making research findings more useful for decision-making and aiding improvement efforts. We have used a binary method (more favourable / less favourable organizational context) to report multidimensional data. While useful to our stakeholders (e.g., administrators) we are continually seeking ways to increase the detail in our reporting, while maintaining usability for stakeholders. We have now developed a more detailed method – the context rank summary, which displays rankings of care units within and across LTC facilities. In this study, we used a qualitative descriptive design to explore perspectives of administrators and managers (leaders) from LTC facilities on the two different methods for reporting survey data. We conducted a total of three focus groups with 16 leaders in the Maritimes and Ontario, Canada. Transcripts were analysed using content analysis. Leaders preferred a feedback report that combines a binary method with the greater detail of the context rank summary. Providing organizational context data that is more meaningful, relevant and actionable could offer an additional path to identifying areas for improvement.

Analysis of responder-based endpoints: improving power through utilising continuous components

Background: Clinical trials and other studies commonly assess effectiveness of an intervention through use of responder-based endpoints. These classify patients based on whether they meet a number of criteria which often involve continuous variables categorised as being above or below a threshold. The proportion of patients who are responders is estimated and, where relevant, compared between groups. An alternative method called the augmented binary method keeps the definition of the endpoint the same but utilises information contained within the continuous component to increase the power considerably (equivalent to increasing the sample size by >30%). In this article we summarise the method and investigate the variety of clinical conditions that use endpoints to which it could be applied.Methods : We reviewed a database of Core Outcome Sets (COS) that covered physiological and mortality trial endpoints recommended for collection in clinical trials of different disorders. We identified responder-based endpoints where the augmented binary method would be useful for increasing power.Results: Out of the 287 COS reviewed, we identified 67 new clinical areas where endpoints were used that would be more efficiently analysed using the augmented binary method. Clinical areas that had particularly high numbers were rheumatology (11 clinical disorders identified), non-solid tumour oncology (10 identified), neurology (9 identified), and cardiovascular (8 identified)Conclusions: The augmented binary method can potentially provide large benefits in a vast array of clinical areas. Further methodological development is needed to account for some types of endpoint.

Analysis of responder-based endpoints: improving power through utilising continuous components

Background Clinical trials and other studies commonly assess effectiveness of an intervention through use of responder-based endpoints. These classify patients based on whether they meet a number of criteria which often involve continuous variables categorised as being above or below a threshold. The proportion of patients who are responders is estimated and, where relevant, compared between groups. An alternative method called the augmented binary method keeps the definition of the endpoint the same but utilises information contained within the continuous component to increase the power considerably (equivalent to increasing the sample size by >30%). In this article we summarise the method and investigate the variety of clinical conditions that use endpoints to which it could be applied. Methods We reviewed a database of Core Outcome Sets (COS) that covered physiological and mortality trial endpoints recommended for collection in clinical trials of different disorders. We identified responder-based endpoints where the augmented binary method would be useful for increasing power. Results Out of the 287 COS reviewed, we identified 67 new clinical areas where endpoints were used that would be more efficiently analysed using the augmented binary method. Clinical areas that had particularly high numbers were rheumatology (11 clinical disorders identified), non-solid tumour oncology (10 identified), neurology (9 identified), and cardiovascular (8 identified) Conclusions The augmented binary method can potentially provide large benefits in a vast array of clinical areas. Further methodological development is needed to account for some types of endpoint.

Probability reasoning in judicial fact-finding

We argue that the laws of probability promote coherent fact-finding and avoid potentially unjust logical contradictions. But we do not argue that a probabilistic Bayesian approach is sufficient or even necessary for good fact-finding. First, we explain the use of probability reasoning in Re D (A Child) [2014] EWHC 121 (Fam) and Re L (A Child) [2017] EWHC 3707 (Fam). Then we criticise the attack on this probabilistic reasoning found in Re A (Children) [2018] EWCA Civ 1718, which is the appeal decision on Re L. We conclude that the attack is unjustified and that the probability statements in the two cases were both valid and useful. We also use probabilistic reasoning to enlighten legal principles related to inherent probability, the Binary Method and the blue bus paradox.

Analysis of responder-based endpoints: improving power through utilising continuous components

Background Clinical trials and other studies commonly assess effectiveness of an intervention through use of responder-based endpoints. These classify patients based on whether they meet a number of criteria which often involve continuous variables categorised as being above or below a threshold. The proportion of patients who are responders is estimated and, where relevant, compared between groups. An alternative method called the augmented binary method keeps the definition of the endpoint the same but utilises information contained within the continuous component to increase the power considerably (equivalent to increasing the sample size by >30%). In this article we summarise the method and investigate the variety of clinical conditions that use endpoints to which it could be applied. Methods We reviewed a database of physiological and mortality trial endpoints recommended for collection in clinical trials of different disorders. We identified responder-based endpoints where the augmented binary method would be useful for increasing power. Results We identified 68 new clinical areas where endpoints were used that would be more efficiently analysed using the augmented binary method. Conclusions The augmented binary method can potentially provide large benefits in a vast array of clinical areas. Further methodological development is needed to account for some types of endpoint.

BINARY METHOD OF THE EPIDEMIOLOGICAL ANALYSIS OF INFECTIOUS INCIDENCE

Article purpose. To present the binary method of the epidemiological analysis of infectious incidence recommended for the characteristic of factors of social-and-ecological systems her defining. Materials and methods. The method of the binary analysis is developed on the basis of the methods of complex studying of epidemic process used in domestic epidemiology which have received the name “retrospective epidemiological analysis of incidence”. For demonstration long-term and annual dynamics of incidence of chicken pox in Vladivostok from 1997 to 2009 is used. The received results. In the binary analysis consecutive division of cumulative incidence into components is carried out, in the beginning, on the leading approaches characterizing biological, social and natural essence of epidemic process and then, by additional criteria, allows to create the statistical model of the studied object suitable for a research of the global phenomena. From biological factors - participation and a role of the infectious and immunological mechanism. Among natural factors - seasonal and year-round elements; social factors - casual and natural manifestations. In Vladivostok from 1997 to 2009 the share of periodic incidence has made 16,7%, basic incidence - 83,3%. Basic incidence was formed due to year-round incidence (17,8%) and seasonal, the main share. In general 82,2% are the share of seasonal incidence and, it forms both the most part of basic incidence, and all periodic incidence. Share of random factors in incidence not of a bike (7,3%). Incidence is formed by mainly natural factors - 92,7%. Conclusion. Use of a binary method has allowed to create logical model of development of epidemic process at chicken pox in Vladivostok. The accounting of a role of the leading factors will be useful to optimization of epidemiological surveillance. The technique of studying of structural elements of the social-and-ecological systems defining formation of incidence of the population is presented in article. Biological factors are the participation and the role of the infectious and immunological mechanism. Natural factors are seasonal and year-round elements; social factors are casual and natural manifestations.