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Based on the panel data of 31 provinces (municipalities and autonomous regions) in China from 2012 to 2019, this paper constructs the evaluation index system of basic medical and health services in China from seven dimensions: medical and health facilities, health expenditure, medical services, traditional Chinese medicine hospital services, maternal and child health care, people's health and medical security, disease control and public health. The entropy method was used to measure the level of basic medical and health services in China, and its spatial differences and convergence characteristics were further investigated. In this study, we employ the entropy weight method, σ convergence, and β convergence as our primary methodologies. The entropy weight method is used to evaluate the variability of each indicator, determine the weights of indicators, and quantify the information content of the data. σ convergence illustrates the process by which the variance of a sample decreases over time. β convergence refers to the gradual approach of variables within an economic system towards their long-term equilibrium level over time. The results show that: (1) The scores of basic medical and health services in China's four major regions (including Northeast, East, Central and West) remain in a relatively stable state, with small fluctuations and great room for improvement; (2) There are significant regional differences in the level of basic medical and health services in China, and the intra-regional differences are much greater than the inter-regional differences; (3) There is no significant σ convergence observed in China and its four major regions; however, there is a notable presence of β convergence. [ABSTRACT FROM AUTHOR]

Background: The goal of Lean Enterprise Transformation (LET) is to go beyond simply using Lean tools and instead embed Lean principles and practices in the system so that it becomes a fundamental, collective mindset of the entire enterprise. The Veterans Engineering Resource Center (VERC) launched the Veterans Affairs (VA) LET pilot program to improve quality, safety, and the Veteran's experience. A national evaluation will examine the pilot program sites' implementation processes, outcomes and impacts, and abilities to improve LET adoption and sustainment. This paper describes the evaluation design for the VA LET national evaluation and describes development of a conceptual framework to evaluate LET specifically in healthcare settings.Methods: A targeted literature review of Lean evaluation frameworks was performed to inform the development of the conceptual framework. Key domains were identified by a multidisciplinary expert group and then validated with key stakeholders. The national evaluation design will examine LET implementation using qualitative, survey, and quantitative methods at ten VA facilities. Qualitative data include site visits, interviews, and field observation notes. Survey data include an employee engagement survey to be administered to front-line staff at all pilot sites. Quantitative data include site-level quality improvement metrics collected by the Veterans Services Support Center. Qualitative, quantitative, and mixed-methods analyses will be conducted to examine implementation of LET strategic initiatives and variations in implementation success across sites.Discussion: This national evaluation of a large-scale LET implementation effort will provide insights helpful to other systems interested in embarking on a Lean journey. Additionally, we created a multi-faceted conceptual framework to capture the specific features of a Lean healthcare organization. This framework will guide this evaluation and may be useful as an assessment tool for other organizations interested in implementing Lean principles at an enterprise level. [ABSTRACT FROM AUTHOR]

Background: There are many challenges in delivering and evaluating knowledge for healthcare, but the lack of clear routes from knowledge to practice is a root cause of failures in safety within healthcare. Various types and sources of knowledge are relevant at different levels within the healthcare system. These need to be delivered in a timely way that is useful and actionable for those providing services or developing policies. How knowledge is taken up and used through networks and relationships, and the difficulties in attributing change to knowledge-based interventions, present challenges to understanding how knowledge into action (K2A) work influences healthcare outcomes. This makes it difficult to demonstrate the importance of K2A work, and harness support for its development and resourcing. This paper presents the results from a project commissioned by NHS Education for Scotland (NES) and Healthcare Improvement Scotland (HIS) to create an evaluation framework to help understand the NHS Scotland Knowledge into Action model.Methods: The team took a developmental approach to creating an evaluation framework that would be useful and practical. This included a literature review to ensure the evaluation was evidence-based; adaptation of contribution analysis for K2A project; action research with K2A project leads to refine the work and develop suitable measures.Results: Principles for evaluation and an evaluation framework based on contribution analysis were developed and implemented on a trial project. An outcomes chain was developed for the K2A programme and specific projects. This was used to design, collect and collate evidence of the K2A intervention. Data collected routinely by the intervention was supplemented with specific feedback measures from K2A project users.Conclusions: The evaluation approach allowed for scrutiny of both processes and outcomes and was adaptable to projects on different scales. This framework has proved useful as a planning, reflecting and evaluation tool for K2A, and could be more widely used to evidence the ways in which knowledge to action work helps improve healthcare outcomes. [ABSTRACT FROM AUTHOR]

Background: While there have been efforts to develop frameworks to guide healthcare priority setting; there has been limited focus on evaluation frameworks. Moreover, while the few frameworks identify quality indicators for successful priority setting, they do not provide the users with strategies to verify these indicators. Kapiriri and Martin (Health Care Anal 18:129-147, 2010) developed a framework for evaluating priority setting in low and middle income countries. This framework provides BOTH parameters for successful priority setting and proposes means of their verification. Before its use in real life contexts, this paper presents results from a validation process of the framework.Methods: The framework validation involved 53 policy makers and priority setting researchers at the global, national and sub-national levels (in Uganda). They were requested to indicate the relative importance of the proposed parameters as well as the feasibility of obtaining the related information. We also pilot tested the proposed means of verification.Results: Almost all the respondents evaluated all the parameters, including the contextual factors, as 'very important'. However, some respondents at the global level thought 'presence of incentives to comply', 'reduced disagreements', 'increased public understanding,' 'improved institutional accountability' and 'meeting the ministry of health objectives', which could be a reflection of their levels of decision making. All the proposed means of verification were assessed as feasible with the exception of meeting observations which would require an insider. These findings results were consistent with those obtained from the pilot testing.Conclusions: These findings are relevant to policy makers and researchers involved in priority setting in low and middle income countries. To the best of our knowledge, this is one of the few initiatives that has involved potential users of a framework (at the global and in a Low Income Country) in its validation. The favorable validation of all the parameters at the national and sub-national levels implies that the framework has potential usefulness at those levels, as is. The parameters that were disputed at the global level necessitate further discussion when using the framework at that level. The next step is to use the validated framework in evaluating actual priority setting at the different levels. [ABSTRACT FROM AUTHOR]