NETIMIS: Dynamic Simulation of Health Economics Outcomes Using Big Data

Many healthcare organizations are now making good use of electronic health record (EHR) systems to record clinical information about their patients and the details of their healthcare. Electronic data in EHRs is generated by people engaged in complex processes within complex environments, and their human input, albeit shaped by computer systems, is compromised by many human factors. These data are potentially valuable to health economists and outcomes researchers but are sufficiently large and complex enough to be considered part of the new frontier of ‘big data’. This paper describes emerging methods that draw together data mining, process modelling, activity-based costing and dynamic simulation models. Our research infrastructure includes safe links to Leeds hospital’s EHRs with 3 million secondary and tertiary care patients. We created a multidisciplinary team of health economists, clinical specialists, and data and computer scientists, and developed a dynamic simulation tool called NETIMIS (Network Tools for Intervention Modelling with Intelligent Simulation; http://www.netimis.com) suitable for visualization of both human-designed and data-mined processes which can then be used for ‘what-if’ analysis by stakeholders interested in costing, designing and evaluating healthcare interventions. We present two examples of model development to illustrate how dynamic simulation can be informed by big data from an EHR. We found the tool provided a focal point for multidisciplinary team work to help them iteratively and collaboratively ‘deep dive’ into big data

Ambulatory EMR Adoption in the USA: A Longitudinal Study

Based on a longitudinal national survey, this study examines the adoption of electronic medical records (EMR) by clinics in the USA between 2004 and 2014. A trend analysis suggests that government incentive, technological breakthrough and patient-centered care push the diffusion forward. The interaction among policy, technology and practice is likely to affect the decision-making of practitioners regarding EMR adoption. This study identifies clinic-, patient- and visit-related variables from the survey, and uses them to predict EMR adoption intention and usage in each year. The explanatory power of different variables changed over time in different ways, revealing how policy, technology, and practice influence EMR adoption together. The findings yield implications for the strategies and best practices of health IT diffusion

J Am Geriatr Soc

Background:Disparities in healthcare access and delivery caused by transportation and health workforce difficulties negatively impact individuals living in rural areas. These challenges are especially prominent in older adults.Design:We systematically evaluated the feasibility, acceptability and effectiveness in providing telemedicine searching the English-language literature for studies (January 2012 to July 2018) in the following databases: Medline (PubMed); Cochrane Library (Wiley); Web of Science; CINAHL; EMBASE (Ovid); and PsycINFO (EBSCO).Participants:Older adults (mean age 6565 and none were less than 60 years)Interventions:Interventions consisted of live, synchronous, two-way video-conferencing communication in non-hospital settings. All medical interventions were included.Measurements:Quality assessment using the Cochrane Collaboration\u2019s Risk of Bias Tool was applied on all included articles, including a qualitative summary of all articles.Results:Of 6,616 citations, we reviewed the full text of 1,173 articles, excluding 1,047 that did not meet criteria. Of the 17 randomized controlled trials, the United States was the country with the most trials (6 [35%]) with cohort sizes ranging from 3\u2013844 (median 35) participants. Risk of bias among included studies varied from low to high. Our qualitative analysis suggests that telemedicine can improve health outcomes in older adults and that it could be used in this population.Conclusions:Telemedicine is feasible and acceptable in delivering care to older adults. Research should focus on well-designed randomized trials to overcome the high degree of bias observed in our synthesis. Clinicians should consider using telemedicine in routine practice to overcome barriers of distance and access to care.NCATS UL1TR001086/AG/NIA NIH HHS/United StatesP30 CA023108/CA/NCI NIH HHS/United StatesUL1 TR001086/TR/NCATS NIH HHS/United StatesP30 DA029926/DA/NIDA NIH HHS/United StatesCDC U48DP005018/AG/NIA NIH HHS/United StatesU48DP005018/ACL/ACL HHS/United StatesK23AG051681/AG/NIA NIH HHS/United StatesK23 AG051681/AG/NIA NIH HHS/United StatesNCI P30CA023108-37/AG/NIA NIH HHS/United StatesNIDA P30DA029926/AG/NIA NIH HHS/United States2020-08-01T00:00:00Z31066916PMC66844098081vault:3367

How useful are patient portals for hospitals in rural areas?

Electronic medical records (EMR) are a relatively new development and the move away from paper records is incentivized by allocating funds to hospitals who undertake this change. In part, the funds are allocated as part of Meaningful Use, which also sets quantitative goals for hospitals in conjunction with the move towards EMR. Hospitals in poor, rural areas of North Carolina with a high percentage of Medicaid patients must meet Meaningful Use requirements in order to receive maximum funding under these federal guidelines. As part of my internship, I focused on the usage of the patient portal at Halifax Regional Medical Center (HRMC), a hospital in one of the poorest counties in North Carolina. The results indicated that the poor and aging population in the area was ill prepared to handle electronic communications with providers through a portal, yet HRMC would still be subject to the requirement under the proposed MU Stage 3 to enroll 25% of patients in the portal. While these numbers seem reasonable for counties with a highly educated workforce and availability of high education institutions, Halifax County is struggling to educate adults about computer usage and use of email as a means of secure communication. In addition, HRMC is competing with primary care practices, where many patients regular visit physicians, for portal usage since some physicians outsource lab testing to HRMC, but will use their own portal to make the results available to patients. HRMC is used as an example of the effort undertaken by rural hospitals in poor counties within North Carolina to meet Meaningful Use Requirements; this effort is not only taking up significant resources in developing and administrating the portal, but also effort in getting patients to enroll in the portal and providing sufficient security for the patient data housed in the portal. This paper attempts to determine how useful resources spent towards enrolling patients in portals are for rural hospitals and whether the funds spent on a portal may not be better used towards getting the population ready for the use of a portal and securing the information in the portal. Using studies about what prerequisites must be met for an effective use of a patient portal, this paper aims at determining whether portal usage should be priority for rural hospitals. Or whether funds should be better spent on securing EMR and delay portal usage in favor of securing electronic records first.Master of Public Healt

Health Information Technology in US Hospitals: Analysis of Current Status and Development of Future Strategies

Adopting Electronic Health Records (EHR) improves the efficiency and quality of health care systems. However, recent studies reported a slow rate of adoption or conflicting study results regarding EHR implementation in the United States. Even though there appears to be a substantial difference in terms of EHRs implementation and adoption among hospitals with different organizational characteristics and by end-users in different job categories, little has been studied about the relationship between EHR implementation and different organizational and end-users’ characteristics. To evaluate the current status of EHRs implementation and adoption and to compare how differences in organizational and end-user characteristics relate to EHR adoption and implementation, we analyzed secondary data from HIMSS Analytics® annual survey of 2013 and primary data from end-user surveys using various statistical analysis techniques including multivariable regression analysis, multinomial logistic regression analysis, and information theoretic analysis using normalized mutual information (NMI). This study was based on various theories including an organizational learning theory, a theory of organizational readiness for change, the Technology Acceptance Model (TAM) and Andersen and Aday’s behavioral model. We found discernable differences in EHR implementation and adoption among hospitals with different organizational contextual factors. Most notable was a strong link between hospital location and EHR implementation. Rural hospitals lagged behind urban hospitals in terms of EHRs implementation demonstrating a lower level of readiness for meaningful use attainment. Hospitals in different locations selected and used different EHR vendors based upon location specific evidence related to attaining meaningful use. We also found that EHR end-users across different job categories had different perceptions toward EHRs, which ultimately influenced their satisfaction with EHRs. For successful EHR implementation and adoption, health care managers need to develop and customize EHR implementation strategies. Instead of applying one uniform strategy, health care managers need to prioritize their resources and focus their efforts according to different organizational contexts and different end-user expectations toward EHRs. As rural areas will be disadvantaged in terms of quality and efficiency if rural hospitals continue to struggle with EHR implementation, we need to pay special attention to EHRs implementation in rural hospitals

Health Care Leaders\u27 Experiences of Electronic Medical Record Adoption and Use

Adoption of electronic medical record (EMR) technology systems of meaningful use has been slow despite the mandate by the U.S. government. The purpose of this single case study was to explore strategies used by health care leaders to implement EMR technology systems of meaningful use to take advantage of federal incentive payments. Diffusion of innovation theory provided the conceptual framework for the study. Semistructured interviews were conducted with 6 health care leaders from a military installation in the Southeast United States. Data were analyzed using software, coding, and inductive analyses. The 3 prominent themes were patient, provider, and champion. Alerts from an EMR technology system can increase providers\u27 awareness and improve patient safety. Providers\u27 involvement in every phase of an EMR system\u27s implementation can improve the adoption rate. Champions play a critical role in successful adoption and implementation of EMR systems. Results of this study may assist health care leaders in implementing EMR systems to take advantage of federal incentive payments. Implications for positive social change include enhanced delivery of safe, high-quality health care

Two Essays on Analytical Capabilities: Antecedents and Consequences

Although organizations are rapidly embracing business analytics (BA) to enhance organizational performance, only a small proportion have managed to build analytical capabilities. While BA continues to draw attention from academics and practitioners, theoretical understanding of antecedents and consequences of analytical capabilities remain limited and lack a systematic view. In order to address the research gap, the two essays investigate: (a) the impact of organization’s core information processing mechanisms and its impact on analytical capabilities, (b) the sequential approach to integration of IT-enabled business processes and its impact on analytical capabilities, and (c) network position and its impact on analytical capabilities. Drawing upon the Information Processing Theory (IPT), the first essay investigates the relationship between organization’s core information processing mechanisms–i.e., electronic health record (EHRs), clinical information standards (CIS), and collaborative information exchange (CIE)–and its impact on analytical capabilities. We use data from two sources (HIMSS Analytics 2013 and AHA IT Survey 2013) to test the theorized relationships in the healthcare context empirically. Using the competitive progression theory, the second essay investigates whether organizations sequential approach to the integration of IT-enabled business processes is associated with increased analytical capabilities. We use data from three sources (HIMSS Analytics 2013, AHA IT Survey 2013, and CMS 2014) to test if sequential integration of EHRs –i.e., reflecting the unique organizational path of integration–has a significant impact on hospital’s analytical capability. Together the two essays advance our understanding of the factors that underlie enabling of firm’s analytical capabilities. We discuss in detail the theoretical and practical implications of the findings and the opportunities for future research

Health Information Exchange Use in Primary Care

Indiana University-Purdue University Indianapolis (IUPUI)The United States has invested over $40 billion in digitizing the health care system, yet the anticipated gains in improved care coordination, quality, and cost savings remain largely unrealized. This is due in part to limited interoperability and low rates of health information exchange (HIE) use, which can support care coordination and improve provider decision-making. Primary care providers are central to the US health care delivery system and frequently function as care coordinators, yet capability and HIE use gaps among these providers limit the potential of these digital systems to achieve their intended goals. I study HIE use in the context of primary care to examine 1) factors associated with provider HIE use, 2) the extent and nature of team-based HIE use, and 3) differences in HIE system use patterns across discrete groups of system users. First, I use a national sample of primary care providers to analyze market and practice factors related to HIE use for patient referrals. Overall, I find that only 43% of primary care provider referrals used HIE. Furthermore, I find substantial variation in HIE use rates across electronic health record (EHR) vendors. Second, I use HIE system log data to understand the breadth and depth of HIE use among teams, a care model underpinning primary care delivery reform efforts. I find that although use of HIE systems remains low, in primary care settings it overwhelmingly takes place in a manner consistent with team-based care workflows. Furthermore, team-based use does not differ in breadth from single provider HIE use, but illustrates less depth before and after visits. Third, I apply cluster analysis to 16 HIE use measures representing 7 use attributes, and identify 5 discrete user groups. I then compare two of these user groups and find user-level variation in volume and efficiency of use, both of which have implications for HIE system design and usability improvements. Ultimately, these findings help to inform how HIE use can be increased and improved in primary care, moving the US health care system closer to realizing the coordination, quality, and cost savings made possible by a digitized delivery system