Differing Strategies to Meet Information‐Sharing Needs: Publicly Supported Community Health Information Exchanges Versus Health Systems’ Enterprise Health Information Exchanges

POLICY POINTS: Community health information exchanges have the characteristics of a public good, and they support population health initiatives at the state and national levels. However, current policy equally incentivizes health systems to create their own information exchanges covering more narrowly defined populations. Noninteroperable electronic health records and vendors' expensive custom interfaces are hindering health information exchanges. Moreover, vendors are imposing the costs of interoperability on health systems and community health information exchanges. Health systems are creating networks of targeted physicians and facilities by funding connections to their own enterprise health information exchanges. These private networks may change referral patterns and foster more integration with outpatient providers. CONTEXT: The United States has invested billions of dollars to encourage the adoption of and implement the information technologies necessary for health information exchange (HIE), enabling providers to efficiently and effectively share patient information with other providers. Health care providers now have multiple options for obtaining and sharing patient information. Community HIEs facilitate information sharing for a broad group of providers within a region. Enterprise HIEs are operated by health systems and share information among affiliated hospitals and providers. We sought to identify why hospitals and health systems choose either to participate in community HIEs or to establish enterprise HIEs. METHODS: We conducted semistructured interviews with 40 policymakers, community and enterprise HIE leaders, and health care executives from 19 different organizations. Our qualitative analysis used a general inductive and comparative approach to identify factors influencing participation in, and the success of, each approach to HIE. FINDINGS: Enterprise HIEs support health systems' strategic goals through the control of an information technology network consisting of desired trading partners. Community HIEs support obtaining patient information from the broadest set of providers, but with more dispersed benefits to all participants, the community, and patients. Although not an either/or decision, community and enterprise HIEs compete for finite organizational resources like time, skilled staff, and money. Both approaches face challenges due to vendor costs and less-than-interoperable technology. CONCLUSIONS: Both community and enterprise HIEs support aggregating clinical data and following patients across settings. Although they can be complementary, community and enterprise HIEs nonetheless compete for providers' attention and organizational resources. Health policymakers might try to encourage the type of widespread information exchange pursued by community HIEs, but the business case for enterprise HIEs clearly is stronger. The sustainability of a community HIE, potentially a public good, may necessitate ongoing public funding and supportive regulation

The Association Between State-Level Health Information Exchange Laws and Hospital Participation in Community Health Information Organizations

Evidence suggests that health information exchange (HIE) is an effective strategy to improve efficiency and quality of care, as well as reduce costs. A complex patchwork of federal and state legislation has developed over time to encourage HIE activity. Hospitals and health systems have adopted various HIE models to meet the requirements of these statutes and regulations. Given the complexity of HIE laws, it is important to understand how these legal levers influence HIE engagement. We combined data from two unique data sources to examine the association between state-level HIE laws and hospital engagement in community HIEs. Our results identified three legal provisions of state laws (HIE authorization, financial & non-financial incentives, opt-out consent) that increased the likelihood of community HIE engagement. Other provisions decreased the likelihood of engagement. This analysis provides foundational evidence about the utility of HIE laws. More research is needed to determine causal relationships

Variation and disparities in awareness of myocardial infarction symptoms among adults in the United States

Importance: Prompt recognition of myocardial infarction symptoms is critical for timely access to lifesaving emergency cardiac care. However, patients with myocardial infarction continue to have a delayed presentation to the hospital.Objective: To understand the variation and disparities in awareness of myocardial infarction symptoms among adults in the United States.Design, setting, and participants: This cross-sectional study used data from the 2017 National Health Interview Survey among adult residents of the United States, assessing awareness of the 5 following common myocardial infarction symptoms among different sociodemographic subgroups: (1) chest pain or discomfort, (2) shortness of breath, (3) pain or discomfort in arms or shoulders, (4) feeling weak, lightheaded, or faint, and (5) jaw, neck, or back pain. The response to a perceived myocardial infarction (ie, calling emergency medical services vs other) was also assessed.Main outcomes and measures: Prevalence and characteristics of individuals who were unaware of myocardial infarction symptoms and/or chose not to call emergency medical services in response to these symptoms.Results: Among 25 271 individuals (13 820 women [51.6%; 95% CI, 50.8%-52.4%]; 17 910 non-Hispanic white individuals [69.9%; 95% CI, 68.2%-71.6%]; and 21 826 individuals [82.7%; 95% CI, 81.5%-83.8%] born in the United States), 23 383 (91.8%; 95% CI, 91.0%-92.6%) considered chest pain or discomfort a symptom of myocardial infarction; 22 158 (87.0%; 95% CI, 86.1%-87.8%) considered shortness of breath a symptom; 22 064 (85.7%; 95% CI, 84.8%-86.5%) considered pain or discomfort in arm a symptom; 19 760 (77.0%; 95% CI, 76.1%-77.9%) considered feeling weak, lightheaded, or faint a symptom; and 16 567 (62.6%; 95% CI, 61.6%-63.7%) considered jaw, neck, or back pain a symptom. Overall, 14 075 adults (53.0%; 95% CI, 51.9%-54.1%) were aware of all 5 symptoms, whereas 4698 (20.3%; 95% CI, 19.4%-21.3%) were not aware of the 3 most common symptoms and 1295 (5.8%; 95% CI, 5.2%-6.4%) were not aware of any symptoms. Not being aware of any symptoms was associated with male sex (odds ratio [OR], 1.23; 95% CI, 1.05-1.44; P = .01), Hispanic ethnicity (OR, 1.89; 95% CI, 1.47-2.43; P \u3c .001), not having been born in the United States (OR, 1.85; 95% CI, 1.47-2.33; P \u3c .001), and having a lower education level (OR, 1.31; 95% CI, 1.09-1.58; P = .004). Among 294 non-Hispanic black or Hispanic individuals who were not born in the United States, belonged to the low-income or lowest-income subgroup, were uninsured, and had a lower education level, 61 (17.9%; 95% CI, 13.3%-23.6%) were not aware of any symptoms. This group had 6-fold higher odds of not being aware of any symptoms (OR, 6.34; 95% CI, 3.92-10.26; P \u3c .001) compared with individuals without these characteristics. Overall, 1130 individuals (4.5%; 95% CI, 4.0%-5.0%) chose a different response than calling emergency medical services in response to a myocardial infarction.Conclusions and relevance: Many adults in the United States remain unaware of the symptoms of and appropriate response to a myocardial infarction. In this study, several sociodemographic subgroups were associated with a higher risk of not being aware. They may benefit the most from targeted public health initiatives

Leadership, Culture, and Organizational Technologies as Absorptive Capacity for Innovation and Transformation in the Healthcare Sector: A Framework for Research

Organizational transformation, in brief, is the profound reshaping of the organization\u27s and its people\u27s performance. The same transformational initiative might prove effective in one health system yet not another. Variations in success also exist across facilities, departments, or other units within a healthcare organization. Such variations remain relatively unexplored in the literature. We propose that some of these variations might be due to levels of absorptive capacity (ACAP), the ability to discover and exploit innovation, across and within healthcare organizations. The purpose of this article is to provide a research framework and recommend a measurement model for the study of ACAP for transformations in the healthcare setting. To develop a framework for ACAP for transformation, we reviewed 118 peer-reviewed journal articles, 36 books or book sections and two websites related to transformation and ACAP. We also reviewed literature covering related topics, including ACAP measurement models, organizational learning, organizational change, innovation, complex adaptive systems, strategy execution, organizational technologies, leadership, and culture. This comprehensive review of literature covered fields of sociology, organizational theory, management science, and systems theory. The approach sought a parsimonious framework sufficient to capture the significant complexities of ACAP for transformation in healthcare. Our proposed framework of measuring ACAP in healthcare organizations encompasses three dimensions: leadership (L), culture (C), and organizational technologies (OT) that are relevant to transformative change. By applying this LCOT framework in measuring ACAP levels associated with transformation issues, barriers, and outcomes, we propose that constraints can be identified and addressed, and successful implementation of transformational initiatives can be realized. Capturing and tracking the level of ACAP will help healthcare leaders with improving transformation implementation and success, making informed decisions about timing and selection of initiatives, and decisions about continuation or contraction of specific transformations within specific departments, teams or their healthcare system. © Common Ground, Bita Kash, Aaron Spaulding, Larry Gamm, Christopher Johnson, All Rights Reserved

Leadership, culture, and organizational technologies as absorptive capacity for innovation and transformation in the healthcare sector: A framework for research

Organizational transformation, in brief, is the profound reshaping of the organization\u27s and its people\u27s performance. The same transformational initiative might prove effective in one health system yet not another. Variations in success also exist across facilities, departments, or other units within a healthcare organization. Such variations remain relatively unexplored in the literature. We propose that some of these variations might be due to levels of absorptive capacity (ACAP), the ability to discover and exploit innovation, across and within healthcare organizations. The purpose of this article is to provide a research framework and recommend a measurement model for the study of ACAP for transformations in the healthcare setting. To develop a framework for ACAP for transformation, we reviewed 118 peer-reviewed journal articles, 36 books or book sections and two websites related to transformation and ACAP. We also reviewed literature covering related topics, including ACAP measurement models, organizational learning, organizational change, innovation, complex adaptive systems, strategy execution, organizational technologies, leadership, and culture. This comprehensive review of literature covered fields of sociology, organizational theory, management science, and systems theory. The approach sought a parsimonious framework sufficient to capture the significant complexities of ACAP for transformation in healthcare. Our proposed framework of measuring ACAP in healthcare organizations encompasses three dimensions: leadership (L), culture (C), and organizational technologies (OT) that are relevant to transformative change. By applying this LCOT framework in measuring ACAP levels associated with transformation issues, barriers, and outcomes, we propose that constraints can be identified and addressed, and successful implementation of transformational initiatives can be realized. Capturing and tracking the level of ACAP will help healthcare leaders with improving transformation implementation and success, making informed decisions about timing and selection of initiatives, and decisions about continuation or contraction of specific transformations within specific departments, teams or their healthcare system. © Common Ground, Bita Kash, Aaron Spaulding, Larry Gamm, Christopher Johnson, All Rights Reserved

Health care administrators\u27 perspectives on the role of absorptive capacity for strategic change initiatives: A qualitative study

BACKGROUND:: The dimensions of absorptive capacity (ACAP) are defined, and the importance of ACAP is established in the management literature, but the concept has not been applied to health care organizations attempting to implement multiple strategic initiatives. PURPOSE:: The aim of this study was to test the utility of ACAP by analyzing health care administrators\u27 experiences with multiple strategic initiatives within two health systems. METHODOLOGY:: Results are drawn from administrators\u27 assessments of multiple initiatives within two health systems using in-depth personal interviews with a total of 61 health care administrators. Data analysis was performed following deductive qualitative analysis guidelines. Interview transcripts were coded based on the four dimensions of ACAP: acquiring, assimilating, internalizing/transforming, and exploiting knowledge. Furthermore, we link results related to utilization of management resources, including number of key personnel involved and time consumption, to dimensions of ACAP. FINDINGS:: Participants\u27 description of multiple strategic change initiatives confirmed the importance of the four ACAP dimensions. ACAP can be a useful framework to assess organizational capacity with respect to the organization\u27s ability to concurrently implement multiple strategic initiatives. This capacity specifically revolves around human capital requirements from upper management based on the initiatives\u27 location or stage within the ACAP framework. PRACTICE IMPLICATIONS:: Strategic change initiatives in health care can be usefully viewed from an ACAP perspective. There is a tendency for those strategic initiatives ranking higher in priority and time consumption to reflect more advanced dimensions of ACAP (assimilate and transform), whereas few initiatives were identified in the ACAP exploit dimension. This may suggest that health care leaders tend to no longer identify as strategic initiatives those innovations that have moved to the exploitation stage or that less attention is given to the exploitation elements of a strategic initiative than to the earlier stages. © 2013 Wolters Kluwer Health | Lippincott Williams & Wilkins

Measuring Team Effectiveness in the Health Care Setting: An Inventory of Survey Tools

Background: Guidance for measuring team effectiveness in dynamic clinical settings is necessary; however, there are no consensus strategies to help health care organizations achieve optimal teamwork. This systematic review aims to identify validated survey instruments of team effectiveness by clinical settings. Methods: PubMed, MEDLINE, and ISI Web of Knowledge were searched for team effectiveness surveys deployed from 1990 to 2016. Validity and reliability were evaluated using 4 psychometric properties: interrater agreement, internal consistency, content validity, and structural integrity. Two conceptual frameworks, the Donabedian model and the Command Team Effectiveness model, assess conceptual dimensions most measured in each health care setting. Results: The 22 articles focused on surgical, primary care, and other health care settings. Few instruments report the required psychometric properties or feature non-self-reported outcomes. The major conceptual dimensions measured in the survey instruments differed across settings. Team cohesion and overall perceived team effectiveness can be found in all the team effectiveness measurement tools regardless of the health care setting. We found that surgical settings have distinctive conditions for measuring team effectiveness relative to primary or ambulatory care. Discussion: Further development of setting-specific team effectiveness measurement tools can help further enhance continuous quality improvements and clinical outcomes in the future

The Diabetes Management Education Program in South Texas: An Economic and Clinical Impact Analysis

IntroductionDiabetes is a major chronic disease that can lead to serious health problems and high healthcare costs without appropriate disease management and treatment. In the United States, the number of people diagnosed with diabetes and the cost for diabetes treatment has dramatically increased over time. To improve patients’ self-management skills and clinical outcomes, diabetes management education (DME) programs have been developed and operated in various regions.ObjectiveThis community case study explores and calculates the economic and clinical impacts of expanding a model DME program into 26 counties located in South Texas.MethodsThe study sample includes 355 patients with type 2 diabetes and a follow-up hemoglobin A1c level measurement among 1,275 individuals who participated in the DME program between September 2012 and August 2013. We used the Gilmer’s cost differentials model and the United Kingdom Prospective Diabetes Study (UKPDS) Risk Engine methodology to predict 3-year healthcare cost savings and 10-year clinical benefits of implementing a DME program in the selected 26 Texas counties.ResultsChanges in estimated 3-year cost and the estimated treatment effect were based on baseline hemoglobin A1c level. An average 3-year reduction in medical treatment costs per program participant was $2,033 (in 2016 dollars). The total healthcare cost savings for the 26 targeted counties increases as the program participation rate increases. The total projected cost saving ranges from$12 million with 5% participation rate to $185 million with 75% participation rate. A 10-year outlook on additional clinical benefits associated with the implementation and expansion of the DME program at 60% participation is estimated to result in approximately 4,838 avoided coronary heart disease cases and another 392 cases of avoided strokes.ConclusionThe implementation of this model DME program in the selected 26 counties would contribute to substantial healthcare cost savings and clinical benefits. Organizations that provide DME services may benefit from reduction in medical treatment costs and improvement in clinical outcomes for populations with diabetes