Michaels, Maria MBA; Jakhmola, Priya MBA, MS; Lubin, Ira M. PhD; Fochtmann, Laura J. MD, MBI; Casey, Donald E. Jr MD, MPH, MBA; Opelka, Frank G. MD, FACS; Skapik, Julia MD, MPH, FAMIA; Larsen, Kevin MD, FACP; Tailor, Amrita PhD, MPH; Matson-Koffman, Dyann DrPH, MPH, CHES Author Information

The need for a method to examine complex, multidisciplinary processes involving many diverse organizations initially led multiple US federal agencies to adopt the traditional Kaizen, a Lean process improvement method typically used within a single organization, to encompass multiple organizations each with its own leadership and priorities. First, the Centers for Medicare and Medicaid Services and the Office of the National Coordinator for Health Information Technology adapted Kaizen to federal agency processes for the development of electronic clinical quality measures. Later, the Centers for Disease Control and Prevention (CDC) further modified this adapted Kaizen during its Adapting Clinical Guidelines for the Digital Age (ACG) initiative, which aimed to improve the broader scope of guideline development and implementation. This is a methods article to document the adapted Kaizen method for future use in similar complex processes, illustrating how to apply the adapted Kaizen through CDC's ACG initiative and showing the reach achieved by using the adapted Kaizen method. The adapted Kaizen includes pre-Kaizen planning, a Kaizen event, and post-Kaizen implementation that accommodate multidisciplinary and multi-organizational participation. ACG included 5 workgroups that each developed products to support their respective scope: Guideline Creation, Informatics Framework, Translation and Implementation, Communication and Dissemination, and Evaluation. Despite challenges gathering diverse perspectives and balancing the competing priorities of multiple organizations, the ACG participants produced interrelated standards, processes, and tools-further described in separate publications-that programs and partners have leveraged. Use of a siloed approach may not have supported the development and dissemination of these products.

Background Closing the gap between care recommended by evidence-based guidelines and care delivered in practice is an ongoing challenge across systems and delivery models. Clinical decision support systems (CDSSs) are widely deployed to augment clinicians in their complex decision-making processes. Despite published success stories, the poor usability of many CDSSs has contributed to fragmented workflows and alert fatigue. Objective This study aimed to validate the application of a user-centered design (UCD) process in the development of a standards-based medication recommender for type 2 diabetes mellitus in a simulated setting. The prototype app was evaluated for effectiveness, efficiency, and user satisfaction. Methods We conducted interviews with 8 clinical leaders with 8 rounds of iterative user testing with 2-8 prescribers in each round to inform app development. With the resulting prototype app, we conducted a validation study with 43 participants. The participants were assigned to one of two groups and completed a 2-hour remote user testing session. Both groups reviewed mock patient facts and ordered diabetes medications for the patients. The Traditional group used a mock electronic health record (EHR) for the review in Period 1 and used the prototype app in Period 2, while the Tool group used the prototype app during both time periods. The perceived cognitive load associated with task performance during each period was assessed with the National Aeronautics and Space Administration Task Load Index. Participants also completed the System Usability Scale (SUS) questionnaire and Kano Survey. Results Average SUS scores from the questionnaire, taken at the end of 5 of the 8 user testing sessions, ranged from 68-86. The results of the validation study are as follows: percent adherence to evidence-based guidelines was greater with the use of the prototype app than with the EHR across time periods with the Traditional group (prototype app mean 96.2 vs EHR mean 72.0, P<.001) and between groups during Period 1 (Tool group mean 92.6 vs Traditional group mean 72.0, P<.001). Task completion times did not differ between groups (P=.23), but the Tool group completed medication ordering more quickly in Period 2 (Period 1 mean 130.7 seconds vs Period 2 mean 107.7 seconds, P<.001). Based on an adjusted α level owing to violation of the assumption of homogeneity of variance (Ps>.03), there was no effect on screens viewed and on perceived cognitive load (all Ps>.14). Conclusions Through deployment of the UCD process, a point-of-care medication recommender app holds promise of improving adherence to evidence-based guidelines; in this case, those from the American Diabetes Association. Task-time performance suggests that with practice the T2DM app may support a more efficient ordering process for providers, and SUS scores indicate provider satisfaction with the app.

Health information technology has been embraced as a strategy to facilitate patients' access to their health information and engagement in care. However, not all patients are able to access, or are capable of using, a computer or mobile device. Although family caregivers assist individuals with some of the most challenging and costly health needs, their role in health information technology is largely undefined and poorly understood. This perspective discusses challenges and opportunities of engaging family caregivers through the use of consumer-oriented health information technology. We compile existing evidence to make the case that involving family caregivers in health information technology as desired by patients is technically feasible and consistent with the principles of patient-centered and family-centered care. We discuss how more explicit and purposeful engagement of family caregivers in health information technology could advance clinical quality and patient safety by increasing the transparency, accuracy, and comprehensiveness of patient health information across settings of care. Finally, we describe how clarifying and executing patients' desires to involve family members or friends through health information technology would provide family caregivers greater legitimacy, convenience, and timeliness in health system interactions, and facilitate stronger partnerships between patients, family caregivers, and health care professionals.

PURPOSE A coordinated multidisciplinary process to reduce medication errors related to patient discharges to skilled-nursing facilities (SNFs) is described. SUMMARY After determining that medication errors were a frequent cause of readmission among patients discharged to SNFs, a medical center launched a two-phase quality-improvement project focused on cardiac and medical patients. Phase one of the project entailed a three-month failure modes and effects analysis of existing procedures discharge, followed by the development and pilot testing of a multidisciplinary, closed-loop workflow process involving staff and resident physicians, clinical nurse coordinators, and clinical pharmacists. During pilot testing of the new workflow process, the rate of discharge medication errors involving SNF patients was tracked, and data on medication-related readmissions in a designated intervention group (n = 87) and a control group of patients (n = 1893) discharged to SNFs via standard procedures during a nine-month period were collected, with the data stratified using severity of illness (SOI) classification. Analysis of the collected data indicated a cumulative 30-day medication-related readmission rate for study group patients in the minor, moderate, and major SOI categories of 5.4% (4 of 74 patients), compared with a rate of 9.5% (169 of 1780 patients) in the control group. In phase 2 of the project, the revised SNF discharge medication reconciliation procedure was implemented throughout the hospital; since hospitalwide implementation of the new workflow, the readmission rate for SNF patients has been maintained at about 6.7%. CONCLUSION Implementing a standardized discharge order reconciliation process that includes pharmacists led to decreased readmission rates and improved care for patients discharged to SNFs.

5 University of California San Diego, Division of Hospital Medicine, Department of Medicine, San Diego, California D ata collection, analysis, and presentation are key to the success of any hospital glycemic control initiative. Such efforts enable the management team to track improvements in processes and outcomes, make necessary changes to their quality improvement efforts, justify the provision of necessary time and resources, and share their results with others. Reliable metrics for assessing glycemic control and frequency of hypoglycemia are essential to accomplish these tasks and to assess whether interventions result in more benefit than harm. Hypoglycemia metrics must be especially convincing because fear of hypoglycemia remains a major source of clinical inertia, impeding efforts to improve glucose control. Currently, there are no official standards or guidelines for formulating metrics on the quality of inpatient glycemic control. This creates several problems. First, different metrics vary in their biases and in their responsiveness to change. Thus, use of a poor metric could lead to either a falsely positive or falsely negative impression that a quality improvement intervention is in fact improving glycemic control. Second, the proliferation of different measures and analytical plans in the research and quality improvement literature make it very difficult for hospitals to compare baseline performance, determine need for improvement, and understand which interventionsmay bemost effective. A related article in this supplement provides the rationale for improved inpatient glycemic control. That article argues that the current state of inpatient glycemic control, with the frequent occurrence of severe hyperglycemia and irrational insulin ordering, cannot be considered acceptable, especially given the large body of data (albeit largely observational) linking hyperglycemia to negative patient outcomes. However, regardless of whether one is an advocate or skeptic of tighter glucose control in the intensive care unit (ICU) and especially the non-ICU setting, there is no question that standardized, valid, and reliable metrics are needed to compare efforts to improve glycemic control, better understand whether such control actually improves patient care, and closely monitor patient safety. This article provides a summary of practical suggestions to assess glycemic control, insulin use patterns, and safety (hypoglycemia and severe hyperglycemia). In particular, we discuss the pros and cons of various measurement choices. We conclude with a tiered summary of recommendations for practical metrics No honoraria were paid to any authors for time and expertise spent on the writing of this article.

5 MedStar Diabetes Institute, Washington, DC. R ecently, there has been a heightened interest in improving the quality and safety of the management of diabetes and hyperglycemia in the hospital. While observational data strongly suggests an association of hyperglycemia with morbidity and mortality in adults on general medicine and surgery units, clinical research has not yet defined the best practices for managing hyperglycemia in the hospital outside the intensive care unit (ICU). As a result, many physicians do not have a well-formulated approach to managing hyperglycemia in the noncritically ill hospital patient, and the use of insulin therapy to attain targeted blood glucose (BG) control is often subject to practice variability, leading to suboptimal glycemic outcomes. Practical ‘‘guidelines’’ for the management of this common clinical problem have been formulated by experts in the field, based on understanding of the physiology of glucose and insulin dynamics, the characteristics of currently available insulin preparations, and clinical experience. In 2004, in Clement et al., the American Diabetes Association published a technical review promoting the use of physiologic (‘‘basal-nutritional-correction dose’’) insulin regimens in the hospital to achieve targeted glycemic outcomes. This approach has been disseminated via review articles, and more recently, a randomized, controlled trial demonstrated that hospitalized type 2 diabetes patients experienced better glycemic control when treated with a physiologic insulin regimen than when treated with sliding-scale insulin alone. The Society of Hospital Medicine has assembled a Glycemic Control Task Force, which is charged with providing physicians and hospitals with practical tools to improve the safety and efficacy of diabetes management in the hospital. One product of this work is an educational module that serves as a tutorial on the best practice for the management of diabetes and hyperglycemia in the noncritically ill hospital patient. This article is based on that module, and provides a practical summary of the key concepts that will allow clinicians to confidently employ physiologic insulin regimens when caring for their hospital patients. Case: Ms. X is a 56-year-old obese woman with type 2 diabetes mellitus who is admitted for treatment of an infected diabetes-related foot ulcer. The patient will be allowed to eat dinner in a couple of hours, but the surgeons have requested that she be kept ‘‘nothing by mouth’’ (NPO) after midnight for surgical debridement in the morning. Her current weight is 100 kg, and her No honoraria were paid to any authors for time and expertise spent on the writing of this article.

This study is a cost-benefits analysis of the recommendations of the Centers for Disease Control and Prevention for presumptive anti-malarial treatment among departing West African refugees. We conducted a retrospective chart review of symptomatic, blood smear-positive cases of malaria seen in Minneapolis, Minnesota, from 1996 through 2005. Billing charges of U.S. care were compared with estimates of implementation costs for overseas treatment. Fifty-eight symptomatic malaria infections occurred among West African refugees. After overseas pre-departure presumptive treatment, symptomatic malaria in arriving refugees decreased from 8.2% to 0%. The pre-departure number needed to treat to prevent one case of symptomatic malaria is 13.9 (95% confidence interval = 9.8-24). The average U.S. billing charge for each malaria case is $1,730. Overseas implementation costs for presumptive treatment are estimated to be between $141 and $346 to prevent one U.S. malaria case. Overseas presumptive pre-departure anti-malarial therapy prevents clinical malaria in refugees and results in cost-benefits when the malaria prevalence is > 1%. Overseas presumptive therapy has greater cost-benefits than U.S. based screening and treatment strategies.