Search

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. Electronic supplementary material The online version of this article (10.1186/s12913-019-3919-2) contains supplementary material, which is available to authorized users.

Background Many healthcare organizations have developed disclosure policies for large-scale adverse events, including the Veterans Health Administration (VA). This study evaluated VA’s national large-scale disclosure policy and identifies gaps and successes in its implementation. Methods Semi-structured qualitative interviews were conducted with leaders, hospital employees, and patients at nine sites to elicit their perceptions of recent large-scale adverse events notifications and the national disclosure policy. Data were coded using the constructs of the Consolidated Framework for Implementation Research (CFIR). Results We conducted 97 interviews. Insights included how to handle the communication of large-scale disclosures through multiple levels of a large healthcare organization and manage ongoing communications about the event with employees. Of the 5 CFIR constructs and 26 sub-constructs assessed, seven were prominent in interviews. Leaders and employees specifically mentioned key problem areas involving 1) networks and communications during disclosure, 2) organizational culture, 3) engagement of external change agents during disclosure, and 4) a need for reflecting on and evaluating the policy implementation and disclosure itself. Patients shared 5) preferences for personal outreach by phone in place of the current use of certified letters. All interviewees discussed 6) issues with execution and 7) costs of the disclosure. Conclusions CFIR analysis reveals key problem areas that need to be addresses during disclosure, including: timely communication patterns throughout the organization, establishing a supportive culture prior to implementation, using patient-approved, effective communications strategies during disclosures; providing follow-up support for employees and patients, and sharing lessons learned. Electronic supplementary material The online version of this article (doi:10.1186/s12913-016-1903-7) contains supplementary material, which is available to authorized users.

Background We sought to develop a more reliable structured implicit chart review instrument for use in assessing the quality of care for chronic disease and to examine if ratings are more reliable for conditions in which the evidence base for practice is more developed. Methods We conducted a reliability study in a cohort with patient records including both outpatient and inpatient care as the objects of measurement. We developed a structured implicit review instrument to assess the quality of care over one year of treatment. 12 reviewers conducted a total of 496 reviews of 70 patient records selected from 26 VA clinical sites in two regions of the country. Each patient had between one and four conditions specified as having a highly developed evidence base (diabetes and hypertension) or a less developed evidence base (chronic obstructive pulmonary disease or a collection of acute conditions). Multilevel analysis that accounts for the nested and cross-classified structure of the data was used to estimate the signal and noise components of the measurement of quality and the reliability of implicit review. Results For COPD and a collection of acute conditions the reliability of a single physician review was quite low (intra-class correlation = 0.16–0.26) but comparable to most previously published estimates for the use of this method in inpatient settings. However, for diabetes and hypertension the reliability is significantly higher at 0.46. The higher reliability is a result of the reviewers collectively being able to distinguish more differences in the quality of care between patients (p < 0.007) and not due to less random noise or individual reviewer bias in the measurement. For these conditions the level of true quality (i.e. the rating of quality of care that would result from the full population of physician reviewers reviewing a record) varied from poor to good across patients. Conclusions For conditions with a well-developed quality of care evidence base, such as hypertension and diabetes, a single structured implicit review to assess the quality of care over a period of time is moderately reliable. This method could be a reasonable complement or alternative to explicit indicator approaches for assessing and comparing quality of care. Structured implicit review, like explicit quality measures, must be used more cautiously for illnesses for which the evidence base is less well developed, such as COPD and acute, short-course illnesses.

Background Although health disparities have been documented between Medicare beneficiaries based on age (