Supporting the pursuit of professionalism during a crisis.

BACKGROUND: Crisis plans for healthcare organisations most often focus on operational needs including staffing, supplies and physical plant needs. Less attention is focused on how leaders can support and encourage individual clinical team members to conduct themselves as professionals during a crisis. METHODS: This qualitative study analysed observations from 79 leaders at 160 hospitals that participate in two national professionalism programmes who shared their observations in focus group discussions about what they believed were the essential elements of leading and addressing professional accountability during a crisis. RESULTS: Analysis of focus group responses identified six leadership practices adopted by healthcare organisations, which were felt to be essential for organisations to navigate the crisis successfully. Unique aspects of maintaining professionalism during each phase of the pandemic were identified and described. CONCLUSIONS: Leaders need a plan to support an organiation's pursuit of professionalism during a crisis. Leaders participating in this study identified practices that should be carefully woven into efforts to support the ongoing safety and quality of the care delivered by healthcare organisations before, during and after a crisis. The lessons learnt from the COVID-19 pandemic may be useful during subsequent crises and challenges that a healthcare organisation might experience.

NLM and the IAIMS initiative: Cross-institutional academic/advanced systems contributing to the evolution of networked information and resources.

The Integrated Academic/Advanced Information Systems (IAIMS) program began in 1983 and was based on a study by the Association of American Medical Colleges (AAMC). Donald A.B. Lindberg M.D. was a member of the AAMC Advisory Committee. The U.S. National Library of Medicine (NLM) grants for IAIMS were initiated in 1984 the same year Dr. Lindberg became Director of the NLM. This chapter presents an overview of IAIMS and its progression through three stages with Dr. Lindberg's leadership.

NLM and the IAIMS Initiative: Cross-Institutional Academic/Advanced Systems Contributing to the Evolution of Networked Information and Resources.

The Integrated Academic/Advanced Information Systems (IAIMS) program began in 1983 and was based on a study by the Association of American Medical Colleges (AAMC). Donald A.B. Lindberg M.D. was a member of the AAMC Advisory Committee. The U.S. National Library of Medicine (NLM) grants for IAIMS were initiated in 1984 the same year Dr. Lindberg became Director of the NLM. This chapter presents an overview of IAIMS and its progression through three stages with Dr. Lindberg's leadership.

Enabling adoption and use of new health information technology during implementation: Roles and strategies for internal and external support personnel.

OBJECTIVE: Successful technological implementations frequently involve individuals who serve as mediators between end users, management, and technology developers. The goal for this project was to evaluate the structure and activities of such mediators in a large-scale electronic health record implementation. MATERIALS AND METHODS: Field notes from observations taken during implementation beginning in November 2017 were analyzed qualitatively using a thematic analysis framework to examine the relationship between specific types of mediators and the type and level of support to end users. RESULTS: We found that support personnel possessing both contextual knowledge of the institution's workflow and training in the new technology were the most successful in mediation of adoption and use. Those that lacked context of either technology or institutional workflow often displayed barriers in communication, trust, and active problem solving. CONCLUSIONS: These findings suggest that institutional investment in technology training and explicit programs to foster skills in mediation, including roles for professionals with career development opportunities, prior to implementation can be beneficial in easing the pain of system transition.

Organizational diagnostics: a systematic approach to identifying technology and workflow issues in clinical settings.

OBJECTIVES: Healthcare organizations need to rapidly adapt to new technology, policy changes, evolving payment strategies, and other environmental changes. We report on the development and application of a structured methodology to support technology and process improvement in healthcare organizations, Systematic Iterative Organizational Diagnostics (SIOD). SIOD was designed to evaluate clinical work practices, diagnose technology and workflow issues, and recommend potential solutions. MATERIALS AND METHODS: SIOD consists of five stages: (1) Background Scan, (2) Engagement Building, (3) Data Acquisition, (4) Data Analysis, and (5) Reporting and Debriefing. Our team applied the SIOD approach in two ambulatory clinics and an integrated ambulatory care center and used SIOD components during an evaluation of a large-scale health information technology transition. RESULTS: During the initial SIOD application in two ambulatory clinics, five major analysis themes were identified, grounded in the data: putting patients first, reducing the chaos, matching space to function, technology making work harder, and staffing is more than numbers. Additional themes were identified based on SIOD application to a multidisciplinary clinical center. The team also developed contextually grounded recommendations to address issues identified through applying SIOD. DISCUSSION: The SIOD methodology fills a problem identification gap in existing process improvement systems through an emphasis on issue discovery, holistic clinic functionality, and inclusion of diverse perspectives. SIOD can diagnose issues where approaches as Lean, Six Sigma, and other organizational interventions can be applied. CONCLUSION: The complex structure of work and technology in healthcare requires specialized diagnostic strategies to identify and resolve issues, and SIOD fills this need.

Physician Perspectives on Training for an EHR Implementation.

In 2017, a US academic medical center switched to a commercial EHR system using the "specialist training the specialist" model, which combines peer-to-peer training, classroom based training, and web-based training. We conducted semi-structured interviews with physicians at multiple training levels to investigate the impact of this EHR switch and to explore the training experience of physicians and their perception of the training quality pre and post Go-Live. Our team used Grounded Theory methodology to classify the interview information. Themes that emerged from the interviews included stress and anxiety, the desire for more realistic training environments tailored to specialty needs, and concerns about the duration of time between training and implementation. In future implementations, we recommend more data-rich test patients and the demonstration of real-world workflows during training.

Discussion of "Representation of People's Decisions in Health Information Systems: A Complementary Approach for Understanding Health Care Systems and Population Health".

This article is part of a For-Discussion-Section of Methods of Information in Medicine about the paper "Representation of People's Decisions in Health Information Systems: A Complementary Approach for Understanding Health Care Systems and Population Health" written by Fernan Gonzalez Bernaldo de Quiros, Adriana Ruth Dawidowski, and Silvana Figar. It is introduced by an editorial. This article contains the combined commentaries invited to independently comment on the paper of de Quiros, Dawidowski, and Figar. In subsequent issues the discussion can continue through letters to the editor.

Identifying collaborative care teams through electronic medical record utilization patterns.

OBJECTIVE: The goal of this investigation was to determine whether automated approaches can learn patient-oriented care teams via utilization of an electronic medical record (EMR) system. MATERIALS AND METHODS: To perform this investigation, we designed a data-mining framework that relies on a combination of latent topic modeling and network analysis to infer patterns of collaborative teams. We applied the framework to the EMR utilization records of over 10 000 employees and 17 000 inpatients at a large academic medical center during a 4-month window in 2010. Next, we conducted an extrinsic evaluation of the patterns to determine the plausibility of the inferred care teams via surveys with knowledgeable experts. Finally, we conducted an intrinsic evaluation to contextualize each team in terms of collaboration strength (via a cluster coefficient) and clinical credibility (via associations between teams and patient comorbidities). RESULTS: The framework discovered 34 collaborative care teams, 27 (79.4%) of which were confirmed as administratively plausible. Of those, 26 teams depicted strong collaborations, with a cluster coefficient > 0.5. There were 119 diagnostic conditions associated with 34 care teams. Additionally, to provide clarity on how the survey respondents arrived at their determinations, we worked with several oncologists to develop an illustrative example of how a certain team functions in cancer care. DISCUSSION: Inferred collaborative teams are plausible; translating such patterns into optimized collaborative care will require administrative review and integration with management practices. CONCLUSIONS: EMR utilization records can be mined for collaborative care patterns in large complex medical centers.

Machine learning for risk prediction of acute coronary syndrome.

Acute coronary syndrome (ACS) accounts for 1.36 million hospitalizations and billions of dollars in costs in the United States alone. A major challenge to diagnosing and treating patients with suspected ACS is the significant symptom overlap between patients with and without ACS. There is a high cost to over- and under-treatment. Guidelines recommend early risk stratification of patients, but many tools lack sufficient accuracy for use in clinical practice. Prognostic indices often misrepresent clinical populations and rely on curated data. We used random forest and elastic net on 20,078 deidentified records with significant missing and noisy values to develop models that outperform existing ACS risk prediction tools. We found that the random forest (AUC = 0.848) significantly outperformed elastic net (AUC=0.818), ridge regression (AUC = 0.810), and the TIMI (AUC = 0.745) and GRACE (AUC = 0.623) scores. Our findings show that random forest applied to noisy and sparse data can perform on par with previously developed scoring metrics.

Recommendations for the design, implementation and evaluation of social support in online communities, networks, and groups.

A new model of health care is emerging in which individuals can take charge of their health by connecting to online communities and social networks for personalized support and collective knowledge. Web 2.0 technologies expand the traditional notion of online support groups into a broad and evolving range of informational, emotional, as well as community-based concepts of support. In order to apply these technologies to patient-centered care, it is necessary to incorporate more inclusive conceptual frameworks of social support and community-based research methodologies. This paper introduces a conceptualization of online social support, reviews current challenges in online support research, and outlines six recommendations for the design, evaluation, and implementation of social support in online communities, networks, and groups. The six recommendations are illustrated by CanConnect, an online community for cancer survivors in middle Tennessee. These recommendations address the interdependencies between online and real-world support and emphasize an inclusive framework of interpersonal and community-based support. The applications of these six recommendations are illustrated through a discussion of online support for cancer survivors.

Bridging organizational divides in health care: an ecological view of health information exchange.

BACKGROUND: The fragmented nature of health care delivery in the United States leads to fragmented health information and impedes patient care continuity and safety. Technologies to support interorganizational health information exchange (HIE) are becoming more available. Understanding how HIE technology changes health care delivery and affects people and organizations is crucial to long-term successful implementation. OBJECTIVE: Our study investigated the impacts of HIE technology on organizations, health care providers, and patients through a new, context-aware perspective, the Regional Health Information Ecology. METHODS: We conducted more than 180 hours of direct observation, informal interviews during observation, and 9 formal semi-structured interviews. Data collection focused on workflow and information flow among health care team members and patients and on health care provider use of HIE technology. RESULTS: We structured the data analysis around five primary information ecology components: system, locality, diversity, keystone species, and coevolution. Our study identified three main roles, or keystone species, involved in HIE: information consumers, information exchange facilitators, and information repositories. The HIE technology impacted patient care by allowing providers direct access to health information, reducing time to obtain health information, and increasing provider awareness of patient interactions with the health care system. Developing the infrastructure needed to support HIE technology also improved connections among information technology support groups at different health care organizations. Despite the potential of this type of technology to improve continuity of patient care, HIE technology adoption by health care providers was limited. CONCLUSIONS: To successfully build a HIE network, organizations had to shift perspectives from an ownership view of health data to a continuity of care perspective. To successfully integrate external health information into clinical work practices, health care providers had to move toward understanding potential contributions of external health information. Our study provides a foundation for future context-aware development and implementation of HIE technology. Integrating concepts from the Regional Health Information Ecology into design and implementation may lead to wider diffusion and adoption of HIE technology into clinical work.

Effective strategies for implementation and evaluation of public e-health innovations.

The creation of a new public e-health product is no guarantee that it will be used. Developing an implementation strategy is crucial for success. This paper presents a model for both an implementation and an evaluation process. It offers strategies for the multiple phases of an implementation process (foundational concepts, actual implementation, and the on-going use process). It also offers evaluation considerations that parallel each of the implementation phases.

Mediation of adoption and use: a key strategy for mitigating unintended consequences of health IT implementation.

OBJECTIVE: Without careful attention to the work of users, implementation of health IT can produce new risks and inefficiencies in care. This paper uses the technology use mediation framework to examine the work of a group of nurses who serve as mediators of the adoption and use of a barcode medication administration (BCMA) system in an inpatient setting. MATERIALS AND METHODS: The study uses ethnographic methods to explore the mediators' work. Data included field notes from observations, documents, and email communications. This variety of sources enabled triangulation of findings between activities observed, discussed in meetings, and reported in emails. RESULTS: Mediation work integrated the BCMA tool with nursing practice, anticipating and solving implementation problems. Three themes of mediation work include: resolving challenges related to coordination, integrating the physical aspects of BCMA into everyday practice, and advocacy work. DISCUSSION: Previous work suggests the following factors impact mediation effectiveness: proximity to the context of use, understanding of users' practices and norms, credibility with users, and knowledge of the technology and users' technical abilities. We describe three additional factors observed in this case: 'influence on system developers,' 'influence on institutional authorities,' and 'understanding the network of organizational relationships that shape the users' work.' CONCLUSION: Institutionally supported clinicians who facilitate adoption and use of health IT systems can improve the safety and effectiveness of implementation through the management of unintended consequences. Additional research on technology use mediation can advance the science of implementation by providing decision-makers with theoretically durable, empirically grounded evidence for designing implementations.

Registries and evidence-based medicine in craniofacial and plastic surgery.

Evidence-based medicine is a vital process for maintaining and improving quality and value in health care. However, evidence-based practice is most limited by the availability of research and outcomes data. Although randomized controlled trials (RCTs) have been identified by numerous research organizations as the criterion standard for research methodology (eg, "level I evidence"), the execution of well-designed RCTs has proved either challenging or impossible in many surgical fields and with rare disease conditions. In particular, craniofacial and plastic surgery has been noted to be lacking in both the number and quality of RCTs. Many reasons are discussed for this dearth of research including inadequate sample size and challenges in randomization, blinding, and clinical equipoise. Yet, data for outcomes assessment are highly valued by surgeons and by consumers and payers. Therefore, alternative and more practical means for research and data collection must be sought. Observational studies of clinical practice are particularly useful for outcomes assessment despite relegation to a lower tier of evidence (eg, "level II evidence"). Functional databases with well-defined processes for data collection, called medical data registries, are an essential informatics tool to collect and store outcomes data and produce high-quality observational, practice-based research studies. A properly designed and implemented registry can provide surgeons with an abundance of data to perform research and quality improvement projects. In fact, registries may be superior in many ways to RCTs for craniofacial and plastic surgeons both pragmatically and functionally. In this commentary, we discuss the production of such registries in the framework of evidence-based practice and the relevant studies in craniofacial surgery.

Health information exchange technology on the front lines of healthcare: workflow factors and patterns of use.

OBJECTIVE: The goal of this study was to develop an in-depth understanding of how a health information exchange (HIE) fits into clinical workflow at multiple clinical sites. MATERIALS AND METHODS: The ethnographic qualitative study was conducted over a 9-month period in six emergency departments (ED) and eight ambulatory clinics in Memphis, Tennessee, USA. Data were collected using direct observation, informal interviews during observation, and formal semi-structured interviews. The authors observed for over 180 h, during which providers used the exchange 130 times. RESULTS: HIE-related workflow was modeled for each ED site and ambulatory clinic group and substantial site-to-site workflow differences were identified. Common patterns in HIE-related workflow were also identified across all sites, leading to the development of two role-based workflow models: nurse based and physician based. The workflow elements framework was applied to the two role-based patterns. An in-depth description was developed of how providers integrated HIE into existing clinical workflow, including prompts for HIE use. DISCUSSION: Workflow differed substantially among sites, but two general role-based HIE usage models were identified. Although providers used HIE to improve continuity of patient care, patient-provider trust played a significant role. Types of information retrieved related to roles, with nurses seeking to retrieve recent hospitalization data and more open-ended usage by nurse practitioners and physicians. User and role-specific customization to accommodate differences in workflow and information needs may increase the adoption and use of HIE. CONCLUSION: Understanding end users' perspectives towards HIE technology is crucial to the long-term success of HIE. By applying qualitative methods, an in-depth understanding of HIE usage was developed.

Extending nurse practitioner care using the virtual reality world of second life.

The growth of Internet applications has substantially broadened the potential for its use in global telehealth. This pilot project used the virtual reality world of Second Life for diabetic patients to meet with their nurse practitioners for their maintenance visits. Using avatars and the online patient portal, these scheduled visits were designed to meet the needs of the patients as determined by the results from a questionnaire completed by patients prior to the visit. The virtual visits took place in the replicated building where patients typically receive their care, the Eskind Diabetes Clinic. Orientation sessions to Second Life were made available prior to the actual visit, and additional online resources were made available after the visit was over. Although only seven pilot patients have currently completed visits, data illustrate the positive potential use of this treatment modality for future study.

Barriers and facilitators to the use of computer-based intensive insulin therapy.

PURPOSE: Computerized clinical decision support systems (CDSSs) for intensive insulin therapy (IIT) are increasingly common. However, recent studies question IIT's safety and mortality benefit. Researchers have identified factors influencing IIT performance, but little is known about how workflow affects computer-based IIT. We used ethnographic methods to evaluate IIT CDSS with respect to other clinical information systems and care processes. METHODS: We conducted direct observation of and unstructured interviews with nurses using IIT CDSS in the surgical and trauma intensive care units at an academic medical center. We observed 49h of intensive care unit workflow including 49 instances of nurses using IIT CDSS embedded in a provider order entry system. Observations focused on the interaction of people, process, and technology. By analyzing qualitative field note data through an inductive approach, we identified barriers and facilitators to IIT CDSS use. RESULTS: Barriers included (1) workload tradeoffs between computer system use and direct patient care, especially related to electronic nursing documentation, (2) lack of IIT CDSS protocol reminders, (3) inaccurate user interface design assumptions, and (4) potential for error in operating medical devices. Facilitators included (1) nurse trust in IIT CDSS combined with clinical judgment, (2) nurse resilience, and (3) paper serving as an intermediary between patient bedside and IIT CDSS. CONCLUSION: This analysis revealed sociotechnical interactions affecting IIT CDSS that previous studies have not addressed. These issues may influence protocol performance at other institutions. Findings have implications for IIT CDSS user interface design and alerts, and may contribute to nascent general CDSS theory.

Health information exchange usage in emergency departments and clinics: the who, what, and why.

OBJECTIVE: Health information exchange (HIE) systems are being developed across the nation. Understanding approaches taken by existing successful exchanges can help new exchange efforts determine goals and plan implementations. The goal of this study was to explore characteristics of use and users of a successful regional HIE. DESIGN: We used a mixed-method analysis, consisting of cross-sectional audit log data, semi-structured interviews, and direct observation in a sample of emergency departments and ambulatory safety net clinics actively using HIE. For each site, we measured overall usage trends, user logon statistics, and data types accessed by users. We also assessed reasons for use and outcomes of use. RESULTS: Overall, users accessed HIE for 6.8% of all encounters, with higher rates of access for repeat visits, for patients with comorbidities, for patients known to have data in the exchange, and at sites providing HIE access to both nurses and physicians. Discharge summaries and test reports were the most frequently accessed data in the exchange. Providers consistently noted retrieving additional history, preventing repeat tests, comparing new results to retrieved results, and avoiding hospitalizations as a consequence of HIE access. CONCLUSION: HIE use in emergency departments and ambulatory clinics was focused on patients where missing information was believed to be present in the exchange and was related to factors including the roles of people with access, the setting, and other site-specific issues that impacted the overall breadth of routine system use. These data should form an important foundation as other sites embark upon HIE implementation.

Characteristics and effects of nurse dosing over-rides on computer-based intensive insulin therapy protocol performance.

OBJECTIVE: To determine characteristics and effects of nurse dosing over-rides of a clinical decision support system (CDSS) for intensive insulin therapy (IIT) in critical care units. DESIGN: Retrospective analysis of patient database records and ethnographic study of nurses using IIT CDSS. MEASUREMENTS: The authors determined the frequency, direction-greater than recommended (GTR) and less than recommended (LTR)- and magnitude of over-rides, and then compared recommended and over-ride doses' blood glucose (BG) variability and insulin resistance, two measures of IIT CDSS associated with mortality. The authors hypothesized that rates of hypoglycemia and hyperglycemia would be greater for recommended than over-ride doses. Finally, the authors observed and interviewed nurse users. RESULTS: 5.1% (9075) of 179,452 IIT CDSS doses were over-rides. 83.4% of over-ride doses were LTR, and 45.5% of these were ≥ 50% lower than recommended. In contrast, 78.9% of GTR doses were ≤ 25% higher than recommended. When recommended doses were administered, the rate of hypoglycemia was higher than the rate for GTR (p = 0.257) and LTR (p = 0.033) doses. When recommended doses were administered, the rate of hyperglycemia was lower than the rate for GTR (p = 0.003) and LTR (p < 0.001) doses. Estimates of patients' insulin requirements were higher for LTR doses than recommended and GTR doses. Nurses reported trusting IIT CDSS overall but appeared concerned about recommendations when administering LTR doses. CONCLUSION: When over-riding IIT CDSS recommendations, nurses overwhelmingly administered LTR doses, which emphasized prevention of hypoglycemia but interfered with hyperglycemia control, especially when BG was >150 mg/dl. Nurses appeared to consider the amount of a recommended insulin dose, not a patient's trend of insulin resistance, when administering LTR doses overall. Over-rides affected IIT CDSS protocol performance.