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Background Reliable benchmarking in Lean healthcare requires widely relevant and applicable domains for outcome metrics and careful attention to contextual levels. These levels have been poorly defined and no framework to facilitate performance benchmarking exists. Methods We systematically searched the Pubmed, Scopus, and Web of Science databases to identify original articles reporting benchmarking on different contextual levels in Lean healthcare and critically appraised the articles. Scarcity and heterogeneity of articles prevented quantitative meta-analyses. We developed a new, widely applicable conceptual framework for benchmarking drawing on the principles of ten commonly used healthcare quality frameworks and four value statements, and suggest an agenda for future research on benchmarking in Lean healthcare. Results We identified 22 articles on benchmarking in Lean healthcare on 4 contextual levels: intra-organizational (6 articles), regional (4), national (10), and international (2). We further categorized the articles by the domains in the proposed conceptual framework: patients (6), employed and affiliated staff (2), costs (2), and service provision (16). After critical appraisal, only one fifth of the articles were categorized as high quality. Conclusions When making evidence-informed decisions based on current scarce literature on benchmarking in healthcare, leaders and managers should carefully consider the influence of context. The proposed conceptual framework may facilitate performance benchmarking and spreading best practices in Lean healthcare. Future research on benchmarking in Lean healthcare should include international benchmarking, defining essential factors influencing Lean initiatives on different levels of context; patient-centered benchmarking; and system-level benchmarking with a balanced set of outcomes and quality measures.

Fueled by public incidents and growing evidence of deficiencies in care, concern over the quality and outcomes of care has increased in both the United Kingdom and the United States. Both countries have launched a number of initiatives to deal with these issues. These initiatives are unlikely to achieve their objectives without explicit consideration of the multilevel approach to change that includes the individual, group/team, organization, and larger environment/system level. Attention must be given to issues of leadership, culture, team development, and information technology at all levels. A number of contingent factors influence these efforts in both countries, which must each balance a number of tradeoffs between centralization and decentralization in efforts to sustain the impetus for quality improvement over time. The multilevel change framework and associated properties provide a framework for assessing progress along the journey.

Background Lean management is growing in popularity in the healthcare sector worldwide, yet healthcare organizations are struggling with assessing the maturity of their Lean implementation and monitoring its change over time. Most existing methods for such assessments are time consuming, require site visits by external consultants, and lack frontline involvement. The original Lean Healthcare Implementation Self-Assessment Instrument (LHISI) was developed by the Center for Lean Engagement and Research (CLEAR), University of California, Berkeley as a Lean principles-based survey instrument that avoids the above problems. We validated the original LHISI in the context of Finnish healthcare. Methods The original HISI survey was sent over a secure organizational email system to the over 26,000 employees of the Hospital District of Helsinki and Uusimaa in March 2020. The data were randomly split with one part used to carry out an exploratory factor analysis (EFA), and the other for testing the resulting model using confirmatory factor analysis (CFA). Results A total of 6073 employees responded to the LHISI survey, for an overall response rate of 23%. The results indicated that the 43 items used in the original LHISI can be reduced to 25 items, and these items measure a five-dimensional model of the progress of Lean implementation: leadership, commitment, standard work, communication, and daily management system. In comparison with a single-factor model, the fit measures for the 5-factor model were better: smaller X 2 , larger comparative fit index (CFI), smaller root mean square error of approximation (RMSEA), and smaller standardized root mean square residual (SRMR). Conclusions The 25 item LHISI is valid and feasible to use in the context of Finnish healthcare. The LHISI allows the organization to self-monitor the progress of its Lean implementation and provides the leadership with actionable knowledge to guide the path towards Lean maturity across the organization. Our findings encourage further studies on the adoption and validation of the LHISI in healthcare organizations worldwide.

BackgroundShared decision-making (SDM) is widely recognized as a core strategy to improve patient-centered care. However, the implementation of SDM in routine care settings has been slow and its impact mixed.ObjectiveWe examine the temporal association of patient activation and patients’ experience with the SDM process to assess the dominant directionality of this relationship.DesignPatient activation, or a patients’ knowledge, skills, and confidence in self-management, was assessed using the 13-item Patient Activation Measure (PAM). Patient-reported assessment of the SDM process was assessed using the 3-item CollaboRATE measure. Patients at 16 adult primary care practices were surveyed in 2015 and 2016 on PAM (α = 0.92), CollaboRATE (α = 0.90), and demographics. The relationship between PAM and CollaboRATE was estimated using a cross-lagged panel model with clustered robust standard errors and practice fixed effects, controlling for patient characteristics.Participants1222 adult patients with diabetes and/or cardiovascular disease with survey responses at baseline (51% response rate) and a 1-year follow-up (73% response rate).ResultsPAM (mean 3.27 vs 3.28 on a range of 1 to 4; p = 0.082) and CollaboRATE (mean 3.62 vs 3.63 on a range of 1 to 5; p = 0.14) did not change significantly over time. In adjusted analyses, the path from baseline PAM to follow-up CollaboRATE (β = 0.35; p < 0.0001) was stronger than the path from baseline CollaboRATE to follow-up PAM (β = 0.04; p = 0.001).ConclusionsThe relationship between patient activation and patients’ experiences of the SDM process is bidirectional, but dominated by baseline patient activation. Rather than promoting the use of SDM for all patients, healthcare organizations should prioritize interventions to promote patient activation and engage patients with relatively high activation in SDM interventions.

In 1999, Walter Leutz wrote a seminal article in The Milbank Quarterly on the need for and ways to better integrate medical and social services. He formulated five new laws and offered three sets of lessons and recommendations. How relevant are the laws, lessons, and recommendations developed over two decades ago to the current challenges of better integrating health and social services? Do they still offer guidance? What has been learned? Are new \"laws\" needed? I assess these questions for each of the five laws and the threesets of lessons and recommendations relevant to the US experience.

We use an established model of organizational identification to try to understand the voluntary cooperative behavior of professionals in organizations. We examined the relationships among physicians' assessments of the attractiveness of a health care system's perceived identity and construed external image, strength of system identification, and cooperative behaviors. We surveyed 1,504 physicians affiliated with three health care systems and collected follow-up data from 285 physicians a year later. Attractiveness of perceived identity and construed external image were positively related to physicians' identification with the system, which in turn was positively related to cooperative behavior. Extensions to the model of organizational identification are suggested.

Shared decision making (SDM) research has emphasized the role of decision aids (DAs) for helping patients make treatment decisions reflective of their preferences, yet there have been few collaborative multi-institutional efforts to integrate DAs in orthopedic consultations and primary care encounters. In the context of routine DA implementation for SDM, we investigate which patient-level characteristics are associated with patient preferences for surgery versus medical management before and after exposure to DAs. We explored whether DA implementation in primary care encounters was associated with greater shifts in patients' treatment preferences after exposure to DAs compared to DA implementation in orthopedic consultations. Retrospective cohort study. 10 High Value Healthcare Collaborative (HVHC) health systems. A total of 495 hip and 1343 adult knee osteoarthritis patients who were exposed to DAs within HVHC systems between July 2012 to June 2015. Nearly 20% of knee patients and 17% of hip patients remained uncertain about their treatment preferences after viewing DAs. Older patients and patients with high pain levels had an increased preference for surgery. Older patients receiving DAs from three HVHC systems that transitioned DA implementation from orthopedics into primary care had lower odds of preferring surgery after DA exposure compared to older patients in seven HVHC systems that only implemented DAs for orthopedic consultations. Patients' treatment preferences were largely stable over time, highlighting that DAs for SDM largely do not necessarily shift preferences. DAs and SDM processes should be targeted at older adults and patients reporting high pain levels. Initiating treatment conversations in primary versus specialty care settings may also have important implications for engagement of patients in SDM via DAs.

The “patient-centered medical home” and the “accountable care organization” are two widely discussed models for delivery-system reform. Drs. Diane Rittenhouse, Stephen Shortell, and Elliott Fisher have identified several strategies for ensuring that these models are mutually reinforcing. With discussions about U.S. health care reform focused heavily on insurance reforms, relatively little attention has been paid to the delivery-system reforms that will be required to improve the quality and coordination of health care and slow the growth of spending. The “patient-centered medical home” (PCMH) and the “accountable care organization” (ACO) are two widely discussed models for delivery-system reform that take complementary approaches to achieving these goals. The PCMH model emphasizes the creation of a strong primary care foundation for the health care system, and the ACO model emphasizes the alignment of incentives and accountability for providers across the . . .

Background Theories, models, and frameworks used by implementation science, including Diffusion of Innovations, tend to focus on the adoption of one innovation, when often organizations may be facing multiple simultaneous adoption decisions. For instance, despite evidence that care management practices (CMPs) are helpful in managing chronic illness, there is still uneven adoption by physician organizations. This exploratory paper leverages this natural variation in uptake to describe inter-organizational patterns in adoption of CMPs and to better understand how adoption choices may be related to one another. Methods We assessed a cross section of national survey data from physician organizations reporting on the use of 20 CMPs (5 each for asthma, congestive heart failure, depression, and diabetes). Item response theory was used to explore patterns in adoption, first considering all 20 CMPs together and then by subsets according to disease focus or CMP type (e.g., registries, patient reminders). Mokken scale analysis explored whether adoption choices were linked by disease focus or CMP type and whether a consistent ordering of adoption choices was present. Results The Mokken scale for all 20 CMPs demonstrated medium scalability ( H  = 0.43), but no consistent ordering. Scales for subsets of CMPs sharing a disease focus had medium scalability (0.4 <  H  < 0.5), while subsets sharing a CMP type had strong scalability ( H  > 0.5). Scales for CMP type consistently ranked diabetes CMPs as most adoptable and depression CMPs as least adoptable. Within disease focus scales, patient reminders were ranked as the most adoptable CMP, while clinician feedback and patient education were ranked the least adoptable. Conclusions Patterns of adoption indicate that innovation characteristics may influence adoption. CMP dissemination efforts may be strengthened by encouraging traditionally non-adopting organizations to focus on more adoptable practices first and then describing a pathway for the adoption of subsequent CMPs. Clarifying why certain CMPs are “less adoptable” may also provide insights into how to overcome CMP adoption constraints.

Background/Objectives: The importance of teams for improving quality of care has received increased attention. We examine both the correlates of self-assessed or perceived team effectiveness and its consequences for actually making changes to improve care for people with chronic illness. Study Setting and Methods: Data were obtained from 40 teams participating in the national evaluation of the Improving Chronic Illness Care Program. Based on current theory and literature, measures were derived of organizational culture, a focus on patient satisfaction, presence of a team champion, team composition, perceived team effectiveness, and the actual number and depth of changes made to improve chronic illness care. Results: A focus on patient satisfaction, the presence of a team champion, and the involvement of the physicians on the team were each consistently and positively associated with greater perceived team effectiveness. Maintaining a balance among culture values of participation, achievement, openness to innovation, and adherence to rules and accountability also appeared to be important. Perceived team effectiveness, in turn, was consistently associated with both a greater number and depth of changes made to improve chronic illness care. The variables examined explain between 24 and 40% of the variance in different dimensions of perceived team effectiveness; between 13% and 26% in number of changes made; and between 20% and 42% in depth of changes made. Conclusions: The data suggest the importance of developing effective teams for improving the quality of care for patients with chronic illness.