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Combining Lean and Applied Research methods to improve rigor and efficiency in acute care outcomes research: A case study.

ABSTRACT: Hospital care is the single, largest contributor to health spending, yet evidence to guide value transformation is lacking. The large, real-world studies required to fill this void are challenging to conduct in the complex and fast-paced acute care environment. To address these challenges, we created a framework that combines Lean manufacturing methodology and Applied Research principles. We deployed this framework to design, pilot, and iteratively improve a study protocol testing the effectiveness of an innovative care pathway for patients hospitalized with acute exacerbations of Chronic Obstructive Pulmonary Disease. Over a three month period, the protocol was successfully piloted and refined at a single site, subsequently becoming the basis for a large system-wide randomized controlled trial. This framework combining Lean and Applied Research methods resulted in synergies that neither method could accomplish alone and may serve as a template for learning healthcare systems to efficiently generate real-world evidence in the acute care setting.

SUBMITTER: McWilliams A

PROVIDER: S-EPMC6348236 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Combining Lean and Applied Research methods to improve rigor and efficiency in acute care outcomes research: A case study.

McWilliams Andrew A Schoen Maximilian M Krull Constance C Bilancia Justin J Bacon Marguerite M Pena Edwin E McCall Andrea A Howard Daniel D Roberge Jason J

Contemporary clinical trials communications 20190109

Hospital care is the single, largest contributor to health spending, yet evidence to guide value transformation is lacking. The large, real-world studies required to fill this void are challenging to conduct in the complex and fast-paced acute care environment. To address these challenges, we created a framework that combines Lean manufacturing methodology and Applied Research principles. We deployed this framework to design, pilot, and iteratively improve a study protocol testing the effectiven ...[more]

PMID: 30705993

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Project description:Introduction"Lean" is a set of management principles which focus on increasing value and efficiency by reducing or avoiding waste (e.g., overproduction, defects, inventory, transportation, waiting, motion, over processing). It has been applied to manufacturing, education, and health care, leading to optimized process flow, increased efficiency and increased team empowerment. However, to date, it has not been applied to neuroimaging research.MethodsLean principles, such as Value stream mapping (e.g. a tool with which steps in the workflow can be identified on which to focus improvement efforts), 5S (e.g. an organizational method to boost workplace efficiency and efficacy) and Root-cause analysis (e.g. a problem-solving approach to identify key points of failure in a system) were applied to an ongoing, large neuroimaging study that included seven research visits per participant. All team members participated in a half-day exercise in which the entire project flow was visualized and areas of inefficiency were identified. Changes focused on removing obstacles, standardization, optimal arrangement of equipment and root-cause-analysis. A process for continuous improvement was also implemented. Total time of an experiment was recorded before implementation of Lean for two participants and after implementation of Lean for two participants. Satisfaction of team members was assessed anonymously on a 5-item Likert scale, ranging from much worsened to much improved.ResultsAll team members (N = 6) considered the overall experience of conducting an experiment much improved after implementation of Lean. Five out of six team members indicated a much-improved reduction in time, with the final team member considering this somewhat improved. Average experiment time was reduced by 13% after implementation of Lean (from 142 and 147 minutes to 124 and 128 minutes).DiscussionLean principles can be successfully applied to neuroimaging research. Training in Lean principles for junior research scientists is recommended.

Project description:The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well-annotated genome, wealth of genetic resources, and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost-effective, informative, and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole-genome sequencing. Here, we describe the content and performance of a new iteration of the Mouse Universal Genotyping Array (MUGA), MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: (1) chromosomal sex determination, (2) discrimination between substrains from multiple commercial vendors, (3) diagnostic SNPs for popular laboratory strains, (4) detection of constructs used in genetically engineered mice, and (5) an easy-to-interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA, we genotyped 6899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays, both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived, and recombinant inbred lines. Here, we also report the detection of a substantial number of XO and XXY individuals across a variety of sample types, new markers that expand the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. We provide preliminary evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the relevant main stock. We conclude that MiniMUGA is a valuable platform for genetic QC, and an important new tool to increase the rigor and reproducibility of mouse research.

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Combining Lean and Applied Research methods to improve rigor and efficiency in acute care outcomes research: A case study.

Publications

Combining Lean and Applied Research methods to improve rigor and efficiency in acute care outcomes research: A case study.

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