Managerial practices that promote voice and taking charge among frontline workers

Process-improvement ideas often come from frontline workers who speak up by voicing concerns about problems and by taking charge to resolve them. We hypothesize that organization-wide process-improvement campaigns encourage both forms of speaking up, especially voicing concern. We also hypothesize that the effectiveness of such campaigns depends on the prior responsiveness of line managers. We test our hypotheses in the healthcare setting, in which problems are frequent. We use data on nearly 7,500 reported incidents extracted from an incident-reporting system that is similar to those used by many organizations to encourage employees to communicate about operational problems. We find that process-improvement campaigns prompt employees to speak up and that campaigns increase the frequency of voicing concern to a greater extent than they increase taking charge. We also find that campaigns are particularly effective in eliciting taking charge among employees whose managers have been relatively unresponsive to previous instances of speaking up. Our results therefore indicate that organization-wide campaigns can encourage voicing concerns and taking charge, two important forms of speaking up. These results can enable managers to solicit ideas from frontline workers that lead to performance improvement.

Operational Failures and Problem Solving: An Empirical Study of Incident Reporting

Operational failures occur in all industries with consequences that range from minor inconveniences to major catastrophes. Many organizations have implemented incident reporting systems to highlight actual and potential operational failures in order to encourage problem solving and prevent subsequent failures. Our study is among the first to develop and empirically test theory regarding which reported operational failures are likely to spur problem solving. We hypothesize that problem solving activities are especially likely to follow reported operational failures that provoke financial and legal liability risks. We also hypothesize that management commitment to problem solving, enacted through managers' communication and engagement practices, can encourage frontline workers to conduct problem solving. We test our hypotheses in the health care context, in which the use of incident reporting systems to highlight operational failures is widespread. Using data on nearly 7,500 reported incidents from a single hospital, we find support for our hypotheses. Our findings suggest that frontline workers' participation in problem solving is motivated by some inherent characteristics of the problems as well as by particular management practices.

Preparing healthcare delivery organizations for managing computable knowledge

IntroductionThe growth of data science has led to an explosion in new knowledge alongside various approaches to representing and sharing biomedical knowledge in computable form. These changes have not been matched by an understanding of what healthcare delivery organizations need to do to adapt and continuously deploy computable knowledge. It is therefore important to begin to conceptualize such changes in order to facilitate routine and systematic application of knowledge that improves the health of individuals and populations.MethodsAn AHRQâ funded conference convened a group of experts from a range of fields to analyze the current state of knowledge management in healthcare delivery organizations and describe how it needs to evolve to enable computable knowledge management. Presentations and discussions were recorded and analyzed by the author team to identify foundational concepts and new domains of healthcare delivery organization knowledge management capabilities.ResultsThree foundational concepts include 1) the current state of knowledge management in healthcare delivery organizations relies on an outdated biomedical library model, and only a small number of organizations have developed enterpriseâ scale knowledge management approaches that â pushâ knowledge in computable form to frontline decisions, 2) the concept of Learning Health Systems creates an imperative for scalable computable knowledge management approaches, and 3) the ability to represent data science discoveries in computable form that is FAIR (findable, accessible, interoperable, reusable) is fundamental to spread knowledge at scale. For healthcare delivery organizations to engage with computable knowledge management at scale, they will need new organizational capabilities across three domains: policies and processes, technology, and people. Examples of specific capabilities were developed.ConclusionsHealthcare delivery organizations need to substantially scale up and retool their knowledge management approaches in order to benefit from computable biomedical knowledge.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149202/1/lrh210070.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149202/2/lrh210070_am.pd

Comparing methods of grouping hospitals

ObjectiveTo compare the performance of widely used approaches for defining groups of hospitals and a new approach based on network analysis of shared patient volume.Study SettingNonâ federal acute care hospitals in the United States.Study DesignWe assessed the measurement properties of four methods of grouping hospitals: hospital referral regions (HRRs), metropolitan statistical areas (MSAs), coreâ based statistical areas (CBSAs), and community detection algorithms (CDAs).Data Extraction MethodsWe combined data from the 2014 American Hospital Association Annual Survey, the Census Bureau, the Dartmouth Atlas, and Medicare data on interhospital patient travel patterns. We then evaluated the distinctiveness of each grouping, reliability over time, and generalizability across populations.Principle FindingsHospital groups defined by CDAs were the most distinctive (modularity = 0.86 compared to 0.75 for HRRs and 0.83 for MSAs; 0.72 for CBSA), were reliable to alternative specifications, and had greater generalizability than HRRs, MSAs, or CBSAs. CDAs had lower reliability over time than MSAs or CBSAs (normalized mutual information between 2012 and 2014 CDAs = 0.93).ConclusionsCommunity detection algorithmâ defined hospital groups offer high validity, reliability to different specifications, and generalizability to many uses when compared to approaches in widespread use today. They may, therefore, offer a better choice for efforts seeking to analyze the behaviors and dynamics of groups of hospitals. Measures of modularity, shared information, inclusivity, and shared behavior can be used to evaluate different approaches to grouping providers.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151847/1/hesr13188-sup-0001-AuthorMatrix.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151847/2/hesr13188_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151847/3/hesr13188.pd

Barriers to Hospital Electronic Public Health Reporting and Implications for the COVID-19 Pandemic

We sought to identify barriers to hospital reporting of electronic surveillance data to local, state, and federal public health agencies and the impact on areas projected to be overwhelmed by the COVID-19 pandemic. Using 2018 American Hospital Association data, we identified barriers to surveillance data reporting and combined this with data on the projected impact of the COVID-19 pandemic on hospital capacity at the hospital referral region level. Our results find the most common barrier was public health agencies lacked the capacity to electronically receive data, with 41.2% of all hospitals reporting it. We also identified 31 hospital referral regions in the top quartile of projected bed capacity needed for COVID-19 patients in which over half of hospitals in the area reported that the relevant public health agency was unable to receive electronic data. Public health agencies’ inability to receive electronic data is the most prominent hospital-reported barrier to effective syndromic surveillance. This reflects the policy commitment of investing in information technology for hospitals without a concomitant investment in IT infrastructure for state and local public health agencies

The relationship between hospital and ehr vendor market dynamics on health information organization presence and participation

Abstract Background Health Information Organizations (HIOs) are third party organizations that facilitate electronic health information exchange (HIE) between providers in a geographic area. Despite benefits from HIE, HIOs have struggled to form and subsequently gain broad provider participation. We sought to assess whether market-level hospital and EHR vendor dynamics are associated with presence and level of hospital participation in HIOs. Methods 2014 data on 4523 hospitals and their EHR vendors were aggregated to the market level. We used multivariate OLS regression to analyze the relationship between hospital and vendor dynamics and (1) probability of HIO presence and (2) percent of hospitals participating in an HIO. Results 298 of 469 markets (64%) had HIO presence, and in those markets, 47% of hospitals participated in an HIO on average. In multivariate analysis, four characteristics were associated with HIO presence. Markets with more hospitals, markets with more EHR vendors, and markets with an EHR vendor-led HIE approach were more likely to have an HIO. Compared to markets with low hospital competition, markets with high hospital competition had a 25 percentage point lower probability of HIO presence. Two characteristics were associated with level of hospital HIO participation. Markets with more hospitals as well as markets with high vendor competition (compared to low competition) had lower participation. Conclusion Both hospital and EHR vendor dynamics are associated with whether a market has an HIO as well as the level of hospital participation in HIOs.https://deepblue.lib.umich.edu/bitstream/2027.42/143537/1/12911_2018_Article_605.pd

Patient characteristics associated with objective measures of digital health tool use in the United States: A literature review.

The study sought to determine which patient characteristics are associated with the use of patient-facing digital health tools in the United States.We conducted a literature review of studies of patient-facing digital health tools that objectively evaluated use (eg, system/platform data representing frequency of use) by patient characteristics (eg, age, race or ethnicity, income, digital literacy). We included any type of patient-facing digital health tool except patient portals. We reran results using the subset of studies identified as having robust methodology to detect differences in patient characteristics.We included 29 studies; 13 had robust methodology. Most studies examined smartphone apps and text messaging programs for chronic disease management and evaluated only 1-3 patient characteristics, primarily age and gender. Overall, the majority of studies found no association between patient characteristics and use. Among the subset with robust methodology, white race and poor health status appeared to be associated with higher use.Given the substantial investment in digital health tools, it is surprising how little is known about the types of patients who use them. Strategies that engage diverse populations in digital health tool use appear to be needed.Few studies evaluate objective measures of digital health tool use by patient characteristics, and those that do include a narrow range of characteristics. Evidence suggests that resources and need drive use

The Value of Information Technology-Enabled Diabetes Management

Reviews different technologies used in diabetes disease management, as well as the costs, benefits, and quality implications of technology-enabled diabetes management programs in the United States

International health IT benchmarking:learning from cross-country comparisons

Objective, to pilot benchmark measures of health information and communication technology (ICT) availability and use to facilitate cross-country learning. Materials and Methods, a prior Organization for Economic Cooperation and Development-led effort involving 30 countries selected and defined functionality-based measures for availability and use of electronic health records, health information exchange, personal health records, and telehealth. In this pilot, an Organization for Economic Cooperation and Development Working Group compiled results for 38 countries for a subset of measures with broad coverage using new and/or adapted country-specific or multinational surveys and other sources from 2012 to 2015. We also synthesized country learnings to inform future benchmarking. Results, while electronic records are widely used to store and manage patient information at the point of care- all but 2 pilot countries reported use by at least half of primary care physicians; many had rates above 75%- patient information exchange across organizations/settings is less common. Large variations in the availability and use of telehealth and personal health records also exist. Discussion, pilot participation demonstrated interest in cross-national benchmarking. Using the most comparable measures available to date, it showed substantial diversity in health ICT availability and use in all domains. The project also identified methodological considerations (e.g., structural and health systems issues that can affect measurement) important for future comparisons. Conclusion, while health policies and priorities differ, many nations aim to increase access, quality, and/or efficiency of care through effective ICT use. By identifying variations and describing key contextual factors, benchmarking offers the potential to facilitate cross-national learning and accelerate the progress of individual countries