Answer the following questions - Submit bulleted summary of key points.
· Why is patient flow a difficult objective to achieve in units that have patients with complicated medical conditions?
· How are hospital patients and staff potentially affected by poor patient flow?
· What are the major uses of flow dashboards inpatient care units?
From ‘Solution Shop’ Model To ‘Focused Factory’ In Hospital Surgery: Increasing Care Value And Predictability By David Cook, Jeffrey E. Thompson, Elizabeth B. Habermann, Sue L. Visscher, Joseph A. Dearani, Veronique L. Roger, and Bijan J. Borah From ‘Solution Shop’ Model To ‘Focused Factory’ In Hospital Surgery: Increasing Care Value And Predictability ABSTRACT The full-service US hospital has been described organizationally as a “solution shop,” in which medical problems are assumed to be unstructured and to require expert physicians to determine each course of care. If universally applied, this model contributes to unwarranted variation in care, which leads to lower quality and higher costs. We purposely disrupted the adult cardiac surgical practice that we led at Mayo Clinic, in Rochester, Minnesota, by creating a “focused factory” model (characterized by a uniform approach to delivering a limited set of high-quality products) within the practice’s solution shop. Key elements of implementing the new model were mapping the care process, segmenting the patient population, using information technology to communicate clearly defined expectations, and empowering nonphysician providers at the bedside. Using a set of criteria, we determined that the focused-factory model was appropriate for 67 percent of cardiac surgical patients. We found that implementation of the model reduced resource use, length-of-stay, and cost. Variation was markedly reduced, and outcomes were improved. Assigning patients to different care models increases care value and the predictability of care process, outcomes, and costs while preserving (in a lesser clinical footprint) the strengths of the solution shop. We conclude that creating a focused-factory model within a solution shop, by applying industrial engineering principles and health information technology tools and changing the model of work, is very effective in both improving quality and reducing costs. S urgical care in a hospital can be char- acterized by the term “complexity,” driven in large part by the fact that most full-service hospitals operate as “solution shops.”1,2(p75) These shops are “structured to diagnose and recommend solutions to unstructured problems.”2(p xxiv) The solution-shop concept was originally used to de- scribemanufacturing.However, it is particularly appropriate to hospital-based surgical care, in which decision making usually relies upon sur- geons’ specific training, intuition, and experi- ence to define the course of care. Solution-shop thinking is imbedded in US physician culture and education and is a critical component of advanced care delivery. But sys- tems engineering, process analysis, quality con- trol, and manufacturing science3 suggest that the uniform application of what amounts to a nineteenth-century craftsman model of medi- cine is insufficient to meet twenty-first-century health care needs. doi: 10.1377/hlthaff.2013.1266 HEALTH AFFAIRS 33, NO. 5 (2014): 746–755 ©2014 Project HOPE— The People-to-People Health Foundation, Inc. David Cook (cook.david@ mayo.edu) is a professor in the Department of Anesthesiology, Division of Cardiovascular Anesthesiology, Center for the Science of Health Care Delivery, Mayo Clinic College of Medicine, in Rochester, Minnesota. Jeffrey E. Thompson is director of operations management, United Surgical Partners, in Addison, Texas. Elizabeth B. Habermann is an associate professor of health services research, Center for the Science of Health Care Delivery, Mayo Clinic College of Medicine. Sue L. Visscher is an assistant professor of health services research, Center for the Science of Health Care Delivery, Mayo Clinic College of Medicine. Joseph A. Dearani is a professor in the Department of Surgery, Division of Cardiovascular Surgery, Mayo Clinic College of Medicine. Veronique L. Roger is a professor of epidemiology and medicine, Center for the Science of Health Care Delivery, Mayo Clinic College of Medicine. Bijan J. Borah is an assistant professor of health services research, Center for the Science of Health Care Delivery, Mayo Clinic College of Medicine. 746 Health Affairs May 2014 33:5 Hospital Productivity Downloaded from HealthAffairs.org on November 29, 2021. Copyright Project HOPE—The People-to-People Health Foundation, Inc. For personal use only. All rights reserved. Reuse permissions at HealthAffairs.org. Some care demands solution-shop thinking. However, its universal application leads to wide variations in practice and runs counter to stan- dardized best-practice models.With such think- ing, the same problemmay be approached in ten different ways by ten physicians. The resulting unwarranted variation increases cost; reduces quality;4–7 and impedes the acquisition of norma- tive data on practice, health outcomes, and cost. The conceptual alternative to the solution shop is the “focused factory,”1 which is charac- terized by a uniform approach to delivering a limited set of high-quality products. Clayton Christensen and coauthors2 provide multiple examples of this concept in health care, from so-called minute clinics to specialty surgical hospitals. In primary care, there has been a movement away from the solution-shop model, with stan- dardized care increasingly being provided by nonphysicians. However, in the high-acuity, full-service hospital—and in hospital-based sur- gery, in particular—the solution-shop model re- mains strong. Our experience suggests that the dominance of the model is correlated with both the acuity of the care provided and the length of training of the surgical provider. Thus, for a full- service hospital, the critical questions are which problems or populations of patients are best addressed by solution-shop models and which by focused-factory models, and how those mod- els should interact. In 2009we—the leaders of a clinical practice at Mayo Clinic, in Rochester, Minnesota—initiated apractice redesigneffort to improve the value (in terms of outcomes divided by cost) of cardiac surgical care.8 All clinical divisions in the service line were represented, and the effort was sup- ported by staff from finance, practice analysis, health information technology (IT), and project management.What resulted at a very large aca- demic hospital serving both a community and a complex referral populationwas the creationof a focused-factory model that currently manages more than 60 percent of an annual cardiac sur- gery population of more than 2,000 patients. Moving From Solution Shop To Focused Factory Our practice redesign began with three parallel efforts: stakeholder analysis, practice analysis, and the application of management tools (such as Lean, Six Sigma, and value-stream mapping) to the delivery of surgical care.9 We analyzed resource use in each care environment and each process step thatwas common toall adult cardiac surgery patients. A primary focus was variation. Wemade several critical observations: Practice variation was high; variation was driven by ex- pectations that were poorly defined or commu- nicated; such expectations led to “overcare”— that is, more care than was needed, and often care that was provided for too long; the care process was organized as a series of starts and stops; data on length-of-stay in the intensive care unit (ICU) and the hospital indicated that more than half of patients could be expected to have a predictable course of care;10 and tools such as Lean and Six Sigma were poorly suited for use in changing a practice model based on a culture of physician-specific decision making. These observations supported calls by pro- viders, payers, andhealth policy experts for stan- dardized practices to reduce unwarranted varia- tion, reduce cost, and improve quality.5–7,11 Implementation of the focused-factory model took place in the following six stages: identifica- tion and segmentation of the population suited to the model; creation of a clinical pathway of linked protocols for the operating room, ICU, and progressive care unit (PCU) or floor; design, building, and adoption of health IT systems to communicate care protocols and the identifica- tion of the focused-factory population; empow- erment of bedside providers (nurses, respiratory therapists, and nurse practitioners) to advance care—that is, tomove the patient through a proc- ess of de-escalating care—without physician in- put when appropriate; locating patients with similar care processes and conditions of similar clinical complexity near each other, in an at- tempt to create a “plant within a plant”;12 and a phased rollout. Mapping the process of care and its variation allowed us to estimate the proportion of the pa- tient population suited to a standardized care model as well as the process improvement tar- gets for each major care step. Then, using both a priori (predesignation) and post hoc (confirma- tion) methods, we segmented the population into focused-factory and non-focused-factory groups for subsequent care. Using predeter- mined criteria—such as surgical complexity, the number of major medical morbidities, and risk—before surgery, we used our health IT sys- tem to designate patients who were suitable for the focused-factory group. To allow for po- tential changes in patients’ clinical status, con- firmation of suitability by the anesthesiologist was required at the end of surgery for patients to remain in that group. If patients were not identified before surgery as suitable but met the criteria after surgery, a provider then as- signed them to the focused-factory group. Following our analysis of the process of care, we reviewed best practices and then built proto- cols that drove the management of all major May 2014 33:5 Health Affairs 747 Downloaded from HealthAffairs.org on November 29, 2021. Copyright Project HOPE—The People-to-People Health Foundation, Inc. For personal use only. All rights reserved. Reuse permissions at HealthAffairs.org. steps in the process. Individual protocols for the ICU and PCUwere subsequently bundled togeth- er and put into tiers of meta-orders.13 The indi- vidual ICU protocols included weaning patients from mechanical ventilation, weaning patients from hemodynamic infusions, removing in- dwelling central lines, and preparing patients for discharge from the ICU. The individual PCU protocols were for removing patients’ Foley catheters, chest tubes, and pacemaker wires; ad- vancing patients’ diet from liquids to semisolids and then solids; and improving ambulation—for example, moving from walking with assistance to walking independently. All protocols were de- signed to make care advancement the default when clinical criteria were met. We used health IT systems to acquire and report data on care process events, identify focused-factory patients, populate pharmacy orders, support bed planning and staffing, and confirm patients’ continued suitability for the care management strategy. This use of health IT addressed barriers in communicating both care expectations and responsibility for advanc- ing the care process. Identification of the care population and com- munication of care expectations (by protocol and health IT systems) empowered bedside providers to advance care without a physician’s input when clinical criteria were met.When pa- tients failed to meet criteria for such advance- ment, they were managed directly by physicians (using the solution-shop approach) until their clinical status allowed them to return to focused- factory management. Our stakeholder analysis showed that having both patients with routine conditions and those with complex conditions in the same care unit resulted in complex workflows, competition for internal resources, inability to acquire and re- port meaningful unit-specific metrics, and cul- tural barriers related to care management. Iden- tifying and confirming patients’ focused-factory status allowed thesepatients tobegrouped in the same ICU after surgery, and subsequently in the same PCU. The model was implemented between late 2009 and mid-2011. Its rollout occurred in stages, with operating room practice changes primarily in 2009, ICU practice changes in 2010, and PCU care