research Compendium 2014–2015 Innovations in Healthcare Delivery A National Science Foundation Industry-University Cooperative Research Center Table of Contents The Center for Health Organization Transformation (CHOT) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 The National Science Foundation I/UCRC Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Becoming an Industry Member . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Industry Testimonials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Selected Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 SAFETY, ACCESS, AND EFFICIENCY CLUSTER Project 1Characterizing and Reducing Avoidable Outside Utilization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Project 2 Identifying Emergency Department Efficiency Frontiers and the Factors Associated with Their Efficiency Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Project 3 Predictive Models for System Utilization, Capacity, and Flow Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Project 4Shared Commons Game Theory Models to Improve Antibiotic Stewardship . . . . . . . . . . . . . . . . . . . . . . . . . 12 Project 5 Understanding the Dual Effect of Hospital Safety Culture on Patients and Care Providers; Optimizing Hospital Safety Culture and Reducing Safety Events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 MACRO/POLICY CLUSTER Project 6 Bundle Science Statistical Models and Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Project 7Economics and Potential Financial Model of the Perioperative Surgical Home: Developing a Framework for PSH Design and Action . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Project 8Healthcare Improvement Spread Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Project 9Healthcare System Redesign: Advancing Delivery Quality and Effectiveness . . . . . . . . . . . . . . . . . . . . . . . . . . 17 PATIENT-CENTERED CARE CLUSTER Project 10 A Data Mining Methodology for Patient Adherence to Home-Based Therapies . . . . . . . . . . . . . . . . . . . . . . . 18 Project 11Applying the Studer Group Evidence Based Leadership Principles to Improve Physician Engagement and Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Project 12Can ‘Visiting Specialists’ Coverage Agreements Return a Positive ROI for Sponsoring Institutions? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Project 13Chronic Disease Management: Clinical, Community, and Patient-Centered Approaches . . . . . . . . . . . . . . . . 21 QUALITY AND SAFETY Project 14Analysis of Practice Variance: Outcome and Evidence-Driven Clinical Practice Re-Design . . . . . . . . . . . . . . . . 22 Project 15Hospital Acquired Conditions—Systematic Analysis and Adaptive Approach . . . . . . . . . . . . . . . . . . . . . . . . . 23 Project 16 Quantifying the Impact of Pay-for-Performance Financial Incentives to Reduce Healthcare-Associated Infections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 Project 17Reinventing the Pediatric Primary Care Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Project 18 Using Lean Six Sigma to Reduce Hospital Acquired Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 ENABLING HIT AND CARE COORDINATION CLUSTER Project 19A Combined Human-Factors and Quality Improvement Approach to Assess Health Information Technology Usability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Project 20Automated Languate Translation for Improving Care Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Project 21 2 Designing Health Information Technologies to Help Patient Care Teams Identify and Manage Information Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Project 22 Gamification for Self-Monitoring of Patients for Enhanced Wellness Outcomes . . . . . . . . . . . . . . . . . . . . . . . 30 The Center for Health Organization Transformation (CHOT) MISSION The mission of the Center for Health Organization Transformation (CHOT) is to advance the knowledge and practice of transformational strategies in evidence-based management and clinical practice. CHOT conducts cooperative research among universities, health systems, and other health-related industries. The Center relies on multi-disciplinary approaches to advance and link systems design and organizational technologies in innovation research. CHOT’s current university partners CHOT’s current industry members American Society of Anesthesiologists Partners HealthCare Children’s Healthcare of Atlanta Seattle Children’s Hospital East Texas Medical Center Regional Healthcare System Siemens Grady Health System Studer Group, LLC Highmark Texas Children’s Hospital Meadows Regional Medical Center University of Texas System Morehouse School of Medicine Verizon Northside Anesthesiology Consultants, LLC 3 The National Science Foundation I/UCRC Model As a National Science Foundation industry-university cooperative research center (I/UCRC), CHOT follows a model of an industry-academic partnership that has benefited industry-focused research across more than 50 disciplines. CHOT creates a safe, mutually beneficial, cooperative environment where innovative, leading healthcare industry members can come together in collaboration to: • Support important transformation initiatives addressing health organization management and services • Examine the implementation of transformational strategies • Partner with healthcare management researchers to improve such initiatives and strategies • Participate in research in a cost-effective manner • Play a critical role in shaping the education of future healthcare leaders as managers, engineers, and health professionals 4 Becoming an Industry Member Most observers agree that the old ways of delivering healthcare services are no longer adequate, so stakeholders are increasingly exploring innovative approaches. Industry membership allows partners to be on the forefront of leading that innovation. Our research model relies on the knowledge and experience of healthcare leaders to guide academic research. This cooperative model ensures that the research is both meaningful and applicable to the healthcare industry and provides immediate decision support for CHOT members. • NSF contributes $55,000 to each University Partner to cover the administrative costs of CHOT • Each Industry Member contributes $50,000 per year to its respective University Partner • Ninety percent of industry member funding goes directly to research activities • The CHOT Industry advisory board (IAB) defines the research agenda for CHOT researchers on a yearly basis using a project voting mechanism developed by the IAB Benefits of Joining CHOT • Provides an objective, third-party, analytical perspective to healthcare organizations who seek to optimize the impact of innovations at a fraction of the cost of consulting • Exclusive setting for information sharing and networking with other innovative healthcare systems and industry members across the United States • Using your own organization’s data and a wide range of experienced, skilled researchers and graduate students to evaluate innovation design and implementation • Partnerships among leading health systems and major universities in driving effective innovation in healthcare 5 Industry Testimonials “It has been a pleasure working with the team from CHOT. The projects have helped our organization think differently and helped to develop strategies. The research team has always been very responsive and helped to educate our leadership team on the use of data.” Kay Tittle, President Texas Children’s Pediatrics “The outstanding universities who are the members of CHOT are producing groundbreaking and outstanding research on some of the toughest opportunities facing healthcare today and in the future. In addition, they are helping to prepare very talented students, who are our future employees in the US healthcare system. I am especially impressed with the caliber of the students.” Steven B. Wagman, Vice President Enterprise Solutions Implementation Chair, Healthcare USA Diversity & Inclusion Council, Siemens Healthcare “CHOT is a valuable resource to the American Society of Anesthesiologists (ASA) and the physician committee responsible for developing and disseminating a base of knowledge around the perioperative surgical home (PSH). There is a real and effective synergy between the CHOT researchers and ASA’s in-house research staff. The CHOT research and reports were the perfect combination of academic rigor and objective qualitative information that was instantly relevant and useful to enhance the productivity of ASA’s concept development phase.” Thomas Miller, PhD, MBA, Director of Health Policy Research, American Society of Anesthesiologists 6 Selected Publications Dissemination strategies related to CHOT’s research activities include monthly webinars, presentations at professional and academic research conferences, and publications in peer-reviewed journals. CHOT researchers acknowledge the importance of dissemination as a way to influence the thought leadership of the healthcare delivery domain. This is a list of selected and most recent papers published in leading peerreviewed journals. Bennett-Millburn, A., Griffin, P., Hewitt, M., Savelsbergh, M. “The Value of Remote Monitoring Systems for Treatment of Chronic Disease.” To appear in IIE Transactions on Healthcare Systems Engineering, 2014. Gregory, S.T., Tan, D., Tilrico, M., Edwardson, N., Gamm, L. “Bedside Shift Reports: A Systematic Literature Review.” To appear in Journal of Nursing Administration, October 2014. Griffin, P., Yan, I., “Association of Food Environment and Food Retailers with Obesity in US Adults.” To appear in Health and Place, 2014. Hagen, M.S., Jopling, J.K., Buchman, T.G., Lee, E.K. (2013). “Advancing Public Health and Medical Preparedness with Operations Research.” American Medical Informatics Association Annual Symposium Proceedings: 841-50. Kang, H., Nembhard, H. B., Rafferty, C., DeFlitch, C. (2014). “Patient Flow in the Emergency Department: A Classification and Analysis of Admission Process Policies.” To appear in Annals of Emergency Medicine, 2014. Kash, B.A., Gamm, L.D., and Spaulding, A.C. (2013). “Absorptive Capacity (ACAP) for Transformation in Healthcare: A Framework for Research.” Change Management: An International Journal 13(1): 1-13. Kash, B.A., Spaulding A., Johnson, C.E., and Gamm, L.D. (2014). “Success Factors for Strategic Change Initiatives: A Qualitative Study of Healthcare Administrators’ Perspectives.” Journal of Healthcare Management 59(1):65-82. Kash, B.A., Spaulding, A., Johnson, C.E., Gamm, L.D. (2014). “Relevancy of the Resource Based View in Healthcare Strategic Management: A Comparative Case Study.” To appear in Journal of Strategy and Management, Volume 7 number 3. Kraschnewski J.L., Sciamanna, C., Stuckey, H.L., Chuang, C.H., Lehman, E.B., Hwang, K.O., Sherwood, L.L., Nembhard, H.B. (2013). “A Silent Response to the Obesity Epidemic: Decline in US Physician Weight Counseling.” Medical Care 51(2):186-92. Lee, E.K., Atallah, H.Y., Wright, M.D., Post, E.T., Thomas, C.I.V., Wu, D.T., Haley, L.L. “Transforming emergency department workflow and patient care.” To appear in Interfaces, 2014. Lee, E.K., Lu, T.W., Tal, S., Jose, J. ”Medical Alert Management: An Automated Decision Support Tool to Reduce Alert Fatigue.” To appear in American Medical Informatics Association Proceedings, 2014. Lee, E.K., Pietz, F., Benecke, B., Mason, J., Burel, G. (2013). “Advancing Public Health and Medical Preparedness with Operations Research.” Interfaces 43(1): 79-98. 7 Selected Publications Lee, E.K., Yuan, F., Templeton, A., Yao, R., Kiel, K., Chu, J.C.H. (2013). “Biological Planning for High-Dose Rate Brachytherapy: Application to Cervical Cancer Treatment.” Interfaces 43(5): 462-47. Lee, E.K., Yuan, F., Zhou, R.L., Lahlou, S., Post, E., Wright, M., Atallah, H. Haley, L.L. “Modeling and Optimizing Emergency Department Workflow of Large Urban Public Hospital.” To appear in Interfaces, 2014. Musdal, H., Shiner, B., Chen, T., Ceyhan, M.E., Watts, B.V., Benneyan, J. (2014). “In-person and Video-based Post-Traumatic Stress Disorder Treatment for Veterans: A Location-Allocation Model.” Military Medicine 179(2):150-156. Peck, J.S., Gaehde, S.A., Nightingale, D.J., Gelman, D.Y., Huckins, D.S., Lemons, M.F., Dickson, E.W., Benneyan, J.C. (2013). “Generalizability of a Simple Approach for Predicting Hospital Admission From an Emergency Department.” Academic Emergency Medicine 20(11): 1156-1163. Schuller, K.A., Kash, B.A., Edwardson, N., Gamm, L.D. (2013). “Enabling and Disabling Factors in Implementation of Studer Group’s Evidence-Based Leadership Initiative: A Qualitative Case Study.” Journal of Communication in Healthcare 6(2):90-99. Watts, B.V., Shiner, B., Ceyhan, M.E., Musdal, H., Sinangil, S., Benneyan, J. (2013). “Health Systems Engineering as an Improvement Strategy: A Case Example Using Location – Allocation Modelling.” Journal for Healthcare Quality 35(3): 35-40. 8 Safety, Access, and Efficiency Cluster PROJECT 1 Characterizing and Reducing Avoidable Outside Utilization Description Outside referrals or out-of-network “leakage” is a ubiquitous problem for many health systems, especially accountable care organizations and other health systems with risk-sharing insurance contracts. Leakage occurs when patients within a health system’s population are referred to or otherwise receive care outside that system, with both cost and care continuity implications. Frequently, for various reasons, an index referral leads to a chain of additional referrals with unclear patterns and causality and with poor visibility in billing data as to how, why, and for whom these referrals are occurring (e.g. typically just the visit date, specialist, and original primary care provider are known). This project consists of two objectives, (1) to explore the utility of a variety of analytic methods to help understand, characterize, and describe referrals and leakage patterns, and (2) to help reduce, disrupt, or prevent leakage. Phase 1 will mostly focus on the first objective with a variety of methods tested for their feasibility and utility on pilot data from one or more ACOs. Potential approaches include data mining, classifiers, predictive modeling, and social network analysis. We also will investigate potential approaches to detect, prevent, or mitigate avoidable out-of-system referrals, using methods such as network cuts, agentbased simulation, or systems dynamics models. How this is different than related research Most approaches to managing outside utilization have focused on methods to identify referrals that were appropriate or not, education within a network, and contract mechanisms. The current approach complements this work with data analytic and operations research methods to better understand, prevent, and intervene/minimize leakage. member benefits • Better understanding of how and why leakage occurs • Identification of potential sources and patterns of avoidable leakage • Approaches to detect, prevent, and mitigate avoidable out-of-network referrals 9 Safety, Access, and Efficiency Cluster PROJECT 2 Identifying Emergency Department Efficiency Frontiers and the Factors Associated with Their Efficiency Performance Description Emergency department (ED) crowding has been recognized as a serious concern in hospitals nationwide. In response, healthcare organizations have pushed EDs to tackle the issues that result from crowding and to improve the efficiency of care. However, there exists no single standardized metric to assess hospital performance. As a result, hospitals and external organizations have used many different performance metrics to assess the operational efficiency in EDs. Although the metrics can play a role in representing the efficiency of each ED in a quantitative way, a simple comparison of the numbers can lead to inaccurate conclusions because inputs consumed for the outcomes were not taken into account. Data Envelopment Analysis (DEA) can be a useful tool to evaluate the efficiency of each ED among a set of peer groups and compare their performance. This study aims to develop a datadriven framework for benchmarking efficient EDs and determining appropriate stratifications of all decision making units into peer groups. 10 How this is different than related research Many studies have used time intervals (e.g., door to doctor, door to bed, and length of stay) to measure efficiency of EDs. However, a simple comparison of the numbers can lead to inaccurate conclusions when the definitions of the metrics are not the same and when other significant factors affecting the efficiency are not considered. By using a DEA and statistical methods, this study will develop a framework to define appropriate peer groups in which efficiency of EDs are compared and identify profiles of efficient EDs in each peer group. MEMBER BENEFITS Our industry partnership with Verizon has led to an understanding that for patients, insurance companies and hospitals, gamification will transform the manner in which wellness management is designed and advanced. IT industries can benefit largely from the software platforms developed under this project and a better understanding of the data acquisition, transfer and management needs. Safety, Access, and Efficiency Cluster PROJECT 3 Predictive Models for System Utilization, Capacity, and Flow Optimization Description This is a phase-1 pilot project to scope and initiate a subsequent portfolio of work in the general area of predictive modeling to improve real-time ability to manage patient flow, system utilization, and care pathways. The value of predictive information in healthcare is increasingly appreciated, such as for patient risk identification but less explored in other potentially useful logistics contexts. This project investigates four specific potential general applications, with the objective of obtaining preliminary results and viability vetting in order to influence the focus and direction of subsequent phase-2 projects. In each case preliminary results will be generated and evaluated in order to assess decision making utility and specifics of future projects. Applications include predicting (1) bed demand in intensive and critical care units onethrough-seven days in advance on a rolling basis, (2) system wide patient flow similar to above, (3) long outlier lengths of stay, such as earlier identification of long-term acute care (LTAC) patients, and (4) patients appropriate for palliative care discussions. Primary modeling approaches are envisioned to include Monte Carlo simulation, probability convolutions, logistic regression, and time series analysis. Each application also will be evaluated for the usefulness of predictive information to decision making, via direct analysis and stakeholder interviews. How this is different than related research While predictive models per se are used in many healthcare contexts, most uses tend to focus more on patient risk, changes, or health status than on system status and rates of change. Each above application is of significant interest to a number of health systems in order to better manage the delivery system and its most effective utilization. Additionally, our approach to system flow and bed demand uses a recently developed new probability model, resulting in a fairly large and previously intractable convolution, and a novel generating function approach to its rapid computation. MEMBER BENEFITS • Understanding how to use predictive modeling for bed demand, system utilization, and patient management • Identification of challenges and opportunities • Improved system utilization, costs, flow, and outcomes 11 Safety, Access, and Efficiency Cluster PROJECT 4 Shared Commons Game Theory Models to Improve Antibiotic Stewardship Description Antibiotic resistance remains a growing problem of broad health and cost concern, with significant focus on antimicrobial stewardship as one important intervention. This project develops and uses game theoretic models of stewardship policies, participation rates, and intervention design to help understand resistance spatial-temporal dynamics and how to best limit resistance locally and regionally. In behavioral economics, stewardship can be viewed as a “tragedy of the commons”, Hardin’s analogy of a shared town pasture for which each individual herder has incentive to graze their sheep without concern for the others, thereby reducing the longterm value to everyone. For antibiotic stewardship, this equates to over-use reducing their effectiveness, where short-term incentives exist to use antibiotics for individual care episodes but at the consequence of reducing long-term effectiveness across a community. Results will help analyze regional spread and growth of antibiotic resistance over time as a function of 12 stewardship participation percentages, distribution, and compliance, which will be used to help inform policies and influence awareness, participation, and cooperation in such programs. How this is different than related research While antibiotic stewardship has been promoted by numerous patient safety, epidemiology, and infection control organizations, to our knowledge little-to-no work has been conducted to model the impact of such programs to help understand and inform policy and interventions. MEMBER BENEFITS • Improved understanding of how stewardship policies, participation rates, and consistency impact resistance • Methodology to identify the most effective interventions to reduce the extent and spread of resistance Safety, Access, and Efficiency Cluster PROJECT 5 Understanding the Dual Effect of Hospital Safety Culture on Patients and Care Providers; Optimizing Hospital Safety Culture and Reducing Safety Events Description The healthcare industry in the United States continues to report among the highest rates of workplace injury and illness of all industries. Many studies examine care provider personal safety perceptions and have found these perceptions influence care provider health and wellness. With respect to patient safety, hospitals continue to struggle with effective tools and processes to reduce patient safety events. Retrospective data shows that many of the facets that promote a safe environment for care providers are the same facets as those that promote a safe environment for patient care. This project will identify and assess the facets of safety culture that influence both care provider and patients safety events and determine how safety events may influence patient satisfaction scores (as measured by the Hospital Consumer Assessment of Healthcare Providers and Systems–HCAHPS). studies that examine both patient safety and care provider safety in tandem. Further, safety culture studies have yet to include the influence of poor safety culture on patient and family satisfaction with their care experience. The inclusion of HCAHPS patient satisfaction scores presents the financial imperative for hospitals to optimize their safety culture, a relatively unexplored imperative in safety research. MEMBER BENEFITS The results of this research will assist all hospitals in developing a better understanding of the relationship between patient and care provider safety and the effect of safety events on HCAHPS scores. By identifying the patient/provider commonalities in safety, these relationships will provide hospitals with critical areas of focus to improve the hospital’s safety culture and reduce safety events for both providers and patients and help improve patient satisfaction. How this is different than related research While there are substantive literature bases in both employee and patient safety, there is a dearth of 13 Macro/Policy Cluster PROJECT 6 Bundle Science Statistical Models and Analysis Description Use of evidence-based bundles has become common for monitoring evidence base compliance in many patient safety contexts. Examples include surgical site infections, ventilator pneumonia, acute myocardial infarction, total joint replacement, coronary artery bypass graft surgery, and others. Despite becoming part of routine improvement projects, the evidence base on evidence based bundles is limited at best. Little actually is known about the best way to form bundles, relationships between care elements, individual and combined adverse events (AE) predictive ability and efficacy, or how to use them as intervention triggers. This project therefore addresses several important questions and needs, using data from two or more health systems: (1) Statistical Process Control (SPC) methods for monitoring bundle compliance, including self-starting methods and prototyping an automated surveillance systems, (2) regression analysis of bundle elements, including quantification of interaction terms and the so-called culture-of-safety “bundle effect”, and (3) how to best use these results as an intervention trigger. 14 How this is different than related research Bundles are used increasingly to measure and motivate patient safety improvement activities, typically defined by expert consensus and literature review. Little-to-no statistical work, however, has been conducted on the science of creating and validating bundles themselves, nor using them for prediction and surveillance. Our prior work, additionally, developed new control charts for bundles, with significant detection improvements but also highlighting several limitations and research needs (weighting, start-up, parameter estimation). MEMBER BENEFITS • Increased understanding of how to create and use bundles for patient safety quality improvement • Validated statistical methods for comparing and monitoring bundle compliance over time, manually or in an automated surveillance or triggering system • Understanding of the relative importance and interaction terms of different bundle elements and, more broadly, development of a general bundle science framework Macro/Policy Cluster PROJECT 7 Economics and Potential Financial Model of the Perioperative Surgical Home: Developing a Framework for PSH Design and Action Description The “perioperative surgical home” (PSH) is a relatively new concept that is based, at least in part, upon the patient-centric characteristics of the medical home combined with foci on team science, micro-systems, service line management, carecoordination, and bundled payment. The purpose of this study is to continue to define the “surgical home” conceptually and to identify and describe the economics and detailed financial model of one selected PSH model in the United States. How this is different than related research Unlike the related concept of patient-centered medical home that dates back over 50 years, the PSH is a product of a new environment of care concerned with improved safety, effectiveness, timeliness, and efficiency of surgical care. This research is heavily driven by both theory and practice to more clearly define the financial model of the PSH and its variants across the health care industry. Furthermore, it requires close collaboration with professionals associated with the selected PSH at all stages of the research. MEMBER BENEFITS The sponsor as well as other associations, hospitals, and policy makers will benefit from a clear under standing of the nature, operational design, and financial model for leading PSH programs in the U.S. Specific attention will be given to characteristics of a viable PSH financial model starting with one specific surgical specialty. 15 Macro/Policy Cluster PROJECT 8 Healthcare Improvement Spread Models Description This is a continuation project of a current phase-1 project in response to our industrial advisory board request for proposals looking at the slow spread of improvement in healthcare. The focus is to develop analytic models of the spread of innovations and improvement knowledge across healthcare systems and healthcare quality improvement networks. Phase-1 consisted of two activities: (1) applying social network analysis tools to “map” the structure of several healthcare quality improvement networks to investigate their interconnectedness relating to spread, and (2) developing two proof-of-concept agent-based simulation models of the spread of improvements across such networks. Phase-2 now will continue this work and apply results to two specific applications to: (1) validate our simulation model using real data from two identified networks, and (2) develop an optimization framework to maximize the spread of innovations across the network. We will also generalize knowledge and explore how to bridge the gap between our theoretical work and practical use. 16 How this is different than related research While a significant amount of work by others has focused on project management and the challenge of improvement implementation (e.g. Mayo Clinic Model for Diffusion, IHI Framework for Spread, etc.), less is known about how such projects and innovations actually spread across quality improvement networks, resulting in a need to better understand and accelerate the spread of good ideas across healthcare improvement communities. MEMBER BENEFITS • Better understanding of the evolution and structure of effective and ineffective quality improvement networks • Identification of ideal network structures to promote effective spread of ideas and innovation Macro/Policy Cluster PROJECT 9 Healthcare System Redesign: Advancing Delivery Quality and Effectiveness Description Individual health systems provide various services and allocate different resources for patient care. Healthcare resources including professional and staff time are constrained. Patients are ‘sicker’ often with a combination of chronic diseases. It would already take 16–18 hours daily to do everything the guidelines recommend that primary care provide for their patients. Patient lifestyle patterns are mostly suboptimal with adherence with pharmacotherapy is often limited. This study aims to (1) identify critical variables that impact outcomes (e.g. control of risk factors and prevention of hospital/ ED admission) and inform allocation of limited time and resources for greater effect; (2) address realistically modifiable social determinants of health that will improve community health; and (3) seek greater use of treatment evidence (e.g. secondary EMR usage, “OMICs” data) to advance quality and effective of care delivery. We aim to increase quality and timeliness of care, maximize financial performance, and decrease practice variability across the organization. How this is different than related research This study attempts to combine social-economic and demographics demands, hospital resources, and evidence of treatment (including EMR, Omics, and other laboratory data) to redesign the delivery process for quality and effectiveness of healthcare delivery. While efficiency is often performed via process improvement, patient risk factors, disease patterns and treatment characteristics may shed lights on resource needs and care requirement, and provide holistic health systems redesign opportunities for improving care quality and effectiveness. MEMBER BENEFITS • • • • • Improve quality and efficiency of care Reduce waste Serve more needed patients Improve demand-resource alignment Reduce prolonged LOS (and thus reduce hospital acquired conditions) • Improve capability in the event of pandemic or disaster response. From the patient standpoint, it offers timeliness and personalized evidence-based care, and reduces unnecessary hospital stays and the associated risks and costs. This work has the potential to reduce healthcare delivery disparities. 17 Patient-Centered Care Cluster PROJECT 10 A Data Mining Methodology for Patient Adherence to Home-Based Therapies Description Patient non-adherence to physician-prescribed disease and wellness management protocols is a major challenge in the healthcare industry and has led to an increase in hospital visits, health risks and medical costs. For example, the non-adherence to prescribed medication results in over 125,000 deaths per year and a financial burden to the healthcare system exceeding $100 billion in direct costs. This project will explore patient adherence for those who adopt a proposed sensor and visualization system for remote wellness management and feedback. How this is different than related research Systems such as AutoCITE reveal that remote patient supervision has tangible impact on patient health outcomes. The main limitations of existing techniques are that they are physically invasive, often requiring patients to wear some digitally connected 18 device for an extended period of time. Furthermore, these systems do not provide an integrated healthcare delivery strategy that connects the sensing results to the patients and healthcare officials in a seamless, visually straightforward manner. The proposed project aims to not only predict patient adherence, but also provide feedback to both patients and physicians, which can then help physicians prescribe alternative solutions if a patient is non-adherent. MEMBER BENEFITS Our industry partnership with Verizon has led to an understanding that for patients, insurance companies and hospitals, a convenient and automated technique to monitor treatment progress can lead to large time and money savings. In particular, industries can benefit largely from the research into sensor placement and data management and transfer. This will be an increasingly important field, as low cost sensors we use in our homes become more prevalent. Patient-Centered Care Cluster PROJECT 11 Applying the Studer Group Evidence Based Leadership Principles to Improve Physician Engagement and Performance Description Studer Group, an outcomes-based firm dedicated to improving the patient experience, has been developing its Evidence-Based Leadership technology to help address the issues faced by both health systems, physician practices, and individual physicians successfully integrate. This project proposes the evaluation of the Studer Physician Feedback System (SPFS), (referred to as the intervention), recently developed to assist health system leaders and physicians with hospital/physician integration initiatives. The integration of physicians from independent practice into health systems has proved challenging over the past several decades, and has been met with mixed financial, economic, and physician engagement results. How this is different than related research Current research regarding hospital and physician integration tends to focus on distal outcomes (e.g. financial performance). Further, there is a paucity of evidence regarding tools and methods for health system leaders to guide these efforts, and provide real-time feedback across a variety of dimensions, including clinical, safety, engagement and experience. MEMBER BENEFITS This study offers a unique opportunity to assess such a comprehensive intervention, and disseminate important findings to a practitioner-oriented audience, thus impacting the quality and nature of care in a variety of settings. 19 Patient-Centered Care Cluster PROJECT 12 Can ‘Visiting Specialists’ Coverage Agreements Return a Positive ROI for Sponsoring Institutions? Description Access to specialty care has been and continues to be a pressing issue for rural patients. While it has always been desirable to push care back to these smaller, underserved markets, volume is not typically sufficient to support specialty physician coverage. This problem has been compounded by a reimbursement system that pays physicians on volume rather than value basis. Thus, health systems have begun to spend large amounts of money by subsidizing employed and independent specialists to offer clinics in rural areas. Sponsor systems stand to benefit from offering such subsidies by potentially reducing unnecessary hospitalizations and rehospitalizations for patients who would have otherwise not been seen by a specialist. However, little if any research has been conducted to date to determine if this ‘visiting specialist’ model yields a positive return on investment (ROI) for the sponsoring health system. 20 How this is different than related research Little research has been conducted to measure the visiting specialist model’s impact on quality and costs. None of this research was conducted in light of new CMS penalties on 30-day readmissions, stricter community needs assessment requirements, or more generally on the recent shift towards population health management. MEMBER BENEFITS • Determine if the system’s CHF 30-day re-admission rate for patients in targeted rural markets is affected by the visiting specialist model • Determine if the ROI for the sponsor is system is positive or negative • Identify local factors (e.g., physician-population ratio, frequency of service offerings, mean patient severity index, distance to system etc.) with the biggest impact on the sponsor system’s ROI • Results should also allow researchers to calculate the value of physician impact on the community—a key requirement for community needs assessments Patient-Centered Care Cluster PROJECT 13 Chronic Disease Management: Clinical, Community, and Patient-Centered Approaches Description Sixty-eight percent of Medicare spending goes to people with five or more chronic diseases. Reports found that between 44%–57% of older patients take more than one unnecessary drug. The management of multiple diseases is complicated and offers daunting challenges to healthcare providers. More drugs are prescribed for treatment, which causes reduced adherence of patient to drug therapy, higher possibility of drug-drug interactions, more side effects observed on patients, less effective treatment, and more frequent changes in drug therapies. This results in more hospital visits, heavier burden on the use of health resources and higher medical expenses. The objective of this study covers both the clinical visits, and a patient-home-centric approach to optimize the outcome and sustained health of patients. How this is different than related research First, the project focuses on co-existing multiple conditions, rather than a single disease. Thus, it is more challenging, interesting, and clinically relevant. The project will bring together a multi-team of providers to identify guidelines of multiple disease treatment. It will reduce the time pressure of doctors on unnecessary patient visits, and assists doctors to manage complex treatments. Chronic disease also requires pro-active patient participation as well as fostering a community and culture for healthy living. Active home and community engagement provides a supporting environment. Remote sensors can be fun and offers unique opportunity for health engagement and communication between providers and patients for sustained health improvement. MEMBER BENEFITS The study attempts to deal with chronic disease from both clinical as well as home-community levels. The study will return optimal outcome-driven treatment for multiple conditions with lower cost and better control of disease symptoms. The resulting treatment will also use a minimum amount of drugs, thus reducing the risk of adverse/side effects and increasing the efficacy of the treatment (more drugs mean high risk of non-compliance). This all will translate to improve the quality of care and quality of life of patients. Positive and healthy home and community environments facilitate pro-active patient health engagement, and promote healthy eating. Remote sensors offer care continuation (outside clinic), promote active engagement to sustain broader health improvement. 21 Quality and Safety PROJECT 14 Analysis of Practice Variance: Outcome and Evidence-Driven Clinical Practice Re-Design Description Numerous studies have shown that surgical outcomes differ among hospitals. Why do some sites achieve better outcomes? This is a complex question with many contributing elements. A large factor is the variability in patient characteristics and risk factors. With regard to non-patient factors, it is likely that outcomes are affected by a host of factors broadly related to experience, resources, and experimentation. For example, some centers may commit greater resources to certain procedures. Other centers may encourage experimentation, resulting in adoption of changes in surgical and medical care that appear promising and divergence in management practices from those at other institutions. Practice variance is an important issue to analyze as a means to optimize care delivery (quality and efficiency) and to encourage collaborative learning for broad quality improvement. How this is different than related research Collaboration has the added potential of stimulating new ideas for investigation or new management techniques, and increases our ability to conduct 22 prospective research in a highly specialized clinical setting. Experimentation and discussion among colleagues can lead to the rapid adoption of innovations and avoid the replication of disadvantageous techniques. Collaboration and site visits have not yet been applied to pediatric cardiac surgery. Collaborative learning in pediatric cardiac surgery requires a multi-institutional approach due to relatively low volumes. A national structure for collaborative site visits has never been tried, to our knowledge, in any field. MEMBER BENEFITS • Improve quality and efficiency of care • Successful dissemination of best practice • Reduce length-of-stay through early extubation and improving care coordination and management • Establishment of important CPG for broad national dissemination. Quality and Safety PROJECT 15 Hospital Acquired Conditions— Systematic Analysis and Adaptive Approach Description A Hospital Acquired Condition (HAC) is a medical condition or complication that a patient develops during a hospital stay, which was not present at admission. About one in 25 U.S. patients has at least one infection contracted during the course of their hospital care, according to a 2104 study released by the U.S. Centers for Disease Control and Prevention (CDC), resulting in about 75,000 patients with healthcare-associated infections (HAI) died during their hospitalizations. Hospitals have worked to mitigate HAC as unnecessary resources are tied up, and outcome of patients are compromised. The progress and urgency have been accelerated as the Affordable Care Act imposes HAI penalty. The challenges here are multiple folds, including suboptimal adherence to current prevention recommendations; limitations in surveillance strategies; lack of efficient mechanism for reporting adverse events; inconsistent metrics of measurement; and at times, lack of system-wide research. Most studies are site-specific, e.g., ICU-focus, antibioticsfocus, etc. The interdependencies and multi-faceted potential personnel and process contribution to HACs make it difficult to pinpoint sources for early detection and intervention. Our team has previously made good SSI advances in open heart surgery through system advances. NICU, MRSA, ED, and environmental service, and multiple stakeholders (care givers and providers, patients, and facility/cleaning workers). Terminal cleaning tools and processes will also be observed. Our study is designed to uncover susceptible areas/ processes/procedures over the entire hospital stay period where infection/conditions are acquired with the objective to cultivate a pro-active surveillance system of awareness of infection-prone situations. The team will completely immerse in the day-to-day processes and will map out the multi-faceted interdependencies across processes and systems. Multi-site comparison will be performed. MEMBER BENEFITS • Improve quality of care and treatment outcome for patients • Reduce unnecessary length of stay and extra medical care • Improve provider and patient compliance • Improve hospital surveillance • Improve hospital resource utilization • Improve providers’ morale and confidence • Establish a conducive atmosphere for sustainable process and change transformation where HAC awareness is integral and second nature to service process. How this is different than related research This large-scale system-wide study involves multiple hospitals, units, and services, including OR, ICU, 23 Quality and Safety PROJECT 16 Quantifying the Impact of Pay-for-Performance Financial Incentives to Reduce Healthcare-Associated Infections Description Healthcare-associated infections (HAIs) are infections that patients contract while receiving treatment for medical or surgical conditions, which impose a considerable economic burden on the U.S. healthcare system. According to the Centers for Disease Control and Prevention (CDC), approximately 1 out of every 20 hospitalized patients contract some form of HAI. Further, the estimated medical costs of HAIs to U.S. hospitals range from $30-45 billion. As a result, HAIs have greatly contributed to the escalating costs of hospital care as well as both morbidity and mortality. Pay-forperformance (P4P) initiatives are increasingly used to incentivize providers to improve both care quality and performance. The system-wide implementation of P4P models may help drive down HAIs for participating hospitals, but what are the incentives for hospitals to participate? In this project, we seek to quantify the economic benefit of participating hospitals in Highmark’s P4P financial incentive program in terms of return-on-investment (ROI). We aim to evaluate the effects of hospital P4P program participation on existing levels of care quality and whether there is a decline in the HAI incidence rates for these participating hospitals. 24 How this is different than related research Previous research on the impact of P4P models have focused on improved hospital quality, efficiency, patient care and safety, but a critical gap remains with measuring the actual ROI associated with hospital participation in such P4P financial incentive programs. The objective of our research is to measure the true economic benefit of these financial incentives for both Highmark and participating hospitals, while evaluating the extent to which the QB program may help reduce HAI incidence rates; thereby, serving as a motivator for system-wide implementation. MEMBER BENEFITS Highmark, as a NSF-CHOT partner, has identified the strategic priority around a better understanding of financial incentives for HAI. This project is potentially significant for all NSF-CHOT hospital partners, and we expect to leverage their participation in the effort as appropriate. Quality and Safety PROJECT 17 Reinventing the Pediatric Primary Care Model Description Pediatric primary care has evolved from a reactive delivery model to a more coordinated and proactive model of care over the past 40 years. Today, advancements in pediatric practice guidelines, chronic disease prevention, diagnostic and treatment technologies, and an increasingly engaged parent population present this field with a unique opportunity to reinvent itself. Modern pediatric care networks are now pursuing strategies to engage patients and parents earlier and more often by using innovative technologies and approaches. Further, pediatric primary care networks stand to benefit from improved integration with obstetrics in order to create a continuous stream of healthy parents and children. Finally, pediatric care networks are becoming increasingly proactive with their high acuity patients through the use of remote monitoring technologies and mobile health. In designing these new care models it is important to make informed judgments on what is best suited for well-defined customer segments and existing organization infrastructure. The purpose of this study is to identify best practices of innovative pediatric primary care models (IPCM) and to define operational and financial details of relevant models for future implementation. How this is different than related research As suggested in our initial description, the IPCM is a product of a new environment of care concerned with improved access, effectiveness, timeliness, patient/ parent engagement, and efficiency of pediatric care. IPCM calls for evolving care teams and professional leadership in the reengineering of work processes from obstetrics (when the patient first enters the model) all the way through their transition into adult-oriented care. Thus, this research is heavily driven by both theory and practice to more clearly define IPCMs and their variants across the health care industry. Results of this research will provide a model for IPCM and guide CHOT members in IPCM planning and implementation. MEMBER BENEFITS The sponsor as well as other associations, hospitals, and policy makers will benefit from a clear understanding of the nature, evolution, design components and role of the IPCM in the healthcare industry. Specific attention will be given to characteristics of the IPCM and its contributions to improved, patient/parent engagement, and access to coordinated care models of practice for IPCM programs. 25 Quality and Safety PROJECT 18 Using Lean Six Sigma to Reduce Hospital Acquired Conditions Description In fiscal year 2015, CMS will implement the HospitalAcquired Condition (HAC) Reduction Program. This program mandates that hospitals in the lowest quartile for hospital-acquired infections (conditions that patients did not have when they were admitted to the hospital) or the lowest quartile for medical errors, will receive a 1% penalty on reimbursement, meaning they will only be paid 99% of what otherwise would be paid under inpatient prospective payment system (IPPS). With the average American hospital earning approximately 5% margin, a loss of 1% revenue has the potential to be a significantly negative effect on the financial viability of some hospitals. Further, hospital-acquired conditions are largely preventable and thus programs that serve to reduce HACs are an important facet of optimal patient care. How this is different than related research Limited research has examined retained surgical items using process improvement methodologies. Utilizing a rapid improvement event to test the 26 emergent themes will serve as a unique validation of our findings. Finally, by using both clinical (clinical documentation) and non-clinical (coding process) workflow processes to examine the data and identify process breakdown, this project will serve to optimize the surgical process with respect to preventing retained surgical items. MEMBER BENEFITS The results of this research will assist all hospitals in better utilization of Lean Six Sigma methodologies to examine deficient hospitals processes that result in HACs. Further, by incorporating a rapid improvement event, the project will offer hospitals an important “next–step” in utilizing the study results to improve patient care thereby fostering greater utilization of this research. Enabling HIT and Care Coordination Cluster PROJECT 19 A Combined Human-Factors and Quality Improvement Approach to Assess Health Information Technology Usability Description Electronic Health Records (EHR) play a major role in the efficiency of clinical operations. Although the main objective of EHR is to provide support on clinical activities, several studies have reported that usability issues have caused inefficiencies and dissatisfaction of clinicians. As a result, EHR systems have suffered from lack of acceptance and adoption. The American Recovery and Reinvestment Act (ARRA) of 2009 put the “meaningful use” of EHR as a central priority for the Centers of Medicare & Medicaid Services (CMS) with the main objective of effective use of EHRs to achieve health and efficiency. As a way to support this priority, a three-phase EHR incentive program was developed to implement EHRs in a meaningful way to improve quality and safety of the U.S. healthcare systems. After 2015, financial penalties will be imposed on Medicaid eligible professionals that do not meet all the criteria for meaningful use. on efficiency and satisfaction of clinical users. In addition, most of those studies discuss the EHR usability problem without providing details on how they could be addressed and quantified. Our combined HF-QI framework provides a quantification of EHR usability at the task level and a more detailed mapping of usability issues. Therefore, informed recommendations can be made to improve usability and as a consequence, improve efficiency in clinical settings. MEMBER BENEFITS Identifying and quantifying EHR usability issues at the task level represent a huge opportunity to inform EHR interface designers and identify areas of opportunity for EHR training programs. This will address the efficiency of clinical operations and clinician satisfaction. Therefore, it will have a positive impact not only on people’s health but also in healthcare costs. How this is different than related research Although the ARRA claimed for a meaningful use of certified EHR technologies, only a few studies have investigated the impact of EHR usability issues 27 Enabling HIT and Care Coordination Cluster PROJECT 20 Automated Language Translation for Improving Care Management Description Language barriers pose problems for communication and interaction among patients and healthcare providers. Yet, proper communication is critical for optimal health management and outcomes. To improve patient-provider communication for patients with limited English proficiency (LEP), it is necessary to interpret spoken language and translate written clinical documents to the patient’s primary language of communication. There is mounting evidence that LEP is a risk factor for reduced healthcare accessibility, reduced quality of care, decreased patient satisfaction, poor understanding of provider’s instructions, increased length of hospital stay and increased adverse events and misdiagnoses. Thus, limited patient–provider communication due to the language barrier is a burden to payers, providers and the community as a whole. In this study, we plan to address the translation services and plan to test computer-assisted translation and machine translation (MT), utilizing freely available open source tools such as Google Translate, along with our advanced computing machine translation services to translate discharge summaries to various other languages to improve the accuracy of translations. We will use a combination of carefully customized user dictionaries/templates, based on correct terminology and fine tuning of MT tools, to increase the accuracy of machine translation. 28 How this is different than related research The overall objective of this project is to study the language interpreter/translation services workflows and find opportunities where advanced informatics solutions could provide a robust solution to the language barriers. Our system is the first attempt to automation where the resulting machine translator will continue to learn and improve through multilevel usage. MEMBER BENEFITS Reduced time for language translators to edit the machine translated summaries, reduced time to translate documents and improved quality of the discharge process by providing the documents in the language the patient understands. It will also enhance the discharge for patients speaking languages for which there are no translators. This allows the hospital to set up a community language bank. Once successful, these language access tools could be applied in a variety of settings across the entire healthcare system where language barriers pose problems and to materials such as health education and disease related documents, brochures, health guides and research briefs. Enabling HIT and Care Coordination Cluster PROJECT 21 Designing Health Information Technologies to Help Patient Care Teams Identify and Manage Information Problems Description Patient-care teams frequently encounter information problems during their clinical decision making process. These information problems include wrong, outdated, conflicting, incomplete, or missing information. Information problems can negatively impact the patient-care workflow, lead to misunderstandings about patient information, and potentially lead to medical errors. Although these information problems have existed for some time in paper records, there is an increasing need to focus on them in electronic records due to the tremendous growth in the use of health information technologies (HIT). Consequently, we will investigate the role that HIT plays in supporting or hindering patient care team members’ ability to identify and manage information problems in an inpatient unit of Hershey Medical Center (HMC). The goals of the project will be to (1) identify requirements for HIT features to better support identification and management of information problems and (2) develop low-fidelity prototypes of these features and get feedback from users on their usability/usefulness. How this is different than related research Current medical informatics research focuses primarily what causes information problems and the impact that the information problems have on the workflow of the hospital staff. However, there is little research that examines how these information problems are identified and managed by patient care teams and the role that HIT plays in this process. The intellectual merit of this work lies in addressing an issue in the medical informatics field for which there is currently little research. The broader impact of this research lies in its ability to potentially improve the delivery of care and reduce medical errors. MEMBER BENEFITS Our work is relevant to all the industry members of CHOT. Identifying features that can help reduce information problems can improve the quality of healthcare delivery in hospitals, decrease the chances of medical errors occurring, and lead to the better design of health information technologies. 29 Enabling HIT and Care Coordination Cluster PROJECT 22 Gamification for Self-Monitoring of Patients for Enhanced Wellness Outcomes Description The objective of this project is to investigate the fundamental aspects of gaming (both traditional hardcore gaming and casual mobile gaming) that make them engaging, rewarding and stimulating and apply those research findings towards a more immersive healthcare wellness management solution that can be adopted by patients. The video game industry has grown to become a ~$100 billion industry, with the average age of gamers being 30. The success of mobile games such as angry birds, candy crush, etc. has extended the definition of a “gamer” to include a broad range of individuals of all ages and demographics. The term “gamification” is an emerging paradigm that aims to employ game mechanics and game thinking to change behavior. The current physician-patient relationship is topdown in nature; a physician provides a patient with a specific set of instructions that they must comply with and a patient goes home and is left to manage their wellness until the next hospital visit. In the context of healthcare, gamification aims to transform the patient-physician relationship into a more collaborative experience, where patients themselves are motivated to succeed in their wellness management goals. 30 How this is different than related research The goal of our project is to create the “angry birds/candy crush” of wellness systems, based on the gamification paradigm that appeals to a broad range of individuals (that may not have considered wellness management systems in the past). This project will focus on maintaining engagement in the wellness management apps through a theoretical understanding of how/why the gaming industry is often successful in maintaining user engagement for extended periods of time. MEMBER BENEFITS Our industry partnership with Verizon has led to an understanding that for patients, insurance companies and hospitals, gamification will transform the manner in which wellness management is designed and advanced. IT industries can benefit largely the software platforms developed under this project and a better understanding of the data acquisition, transfer and management needs. Innovations in Healthcare Delivery Contact Information Bita Kash, Ph.D., M.B.A., FACHE Eva K. Lee, Ph.D. Center DirectorCo-Director [email protected]@isye.gatech.edu Jim Benneyan, Ph.D. Harriet Black Nembhard, Ph.D. Co-DirectorCo-Director [email protected]@psu.edu Additional information on CHOT research projects from previous years are available to our members at www.chotnsf.org. This material is based upon work supported by the National Science Foundation under Grant No. IIP-1361509. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. 31 32501 714
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