Adoption Of Health Information Technology Research Articles

Health Information Technology in the Era of Care Delivery Reform

THE PROPER USE OF INFORMATION TECHNOLOGY IN health care remains widely debated. The notion that health information technology (HIT) can improve care is not new: since the 1960s, HIT has been examined as a tool to aid diagnosis and archive medical records. Half a century later, academics and policy makers continue to debate whether HIT tools such as electronic health records (EHRs) will save money or improve care. Advocates point to many studies demonstrating the benefits of EHRs. Critics argue that the best data come from a few leading institutions with locally developed systems, whereas data from commercial products in nonleading institutions are equivocal. This debate is anachronistic and misses the current issues facing the transition toward greater use of HIT. The urgency to focus on key issues in HIT adoption has increased since the passage of the Health Information Technology for Economic and Clinical Health (HITECH) Act, which provides nearly $30 billion in incentives for physicians and hospitals to adopt EHRs. The question is no longer whether information technology will be used in health care. It will be. The HITECH Act creates a mix of incentives and penalties that will induce a large proportion of physicians and hospitals to move toward EHR systems by the end of this decade. The discussion should now focus on whether HIT will support the models of care delivery that will help achieve broader policy goals: safer, more effective, and more efficient care. The inspiration for a better approach to HIT can best be described by the concept popularized by the Bauhaus school of architecture: “form ever follows function.” Applied to HIT, this suggests beginning with the “function” of integrated, efficient, team-oriented care and following with the “form,” or design of the IT. However, much of HIT today is designed to track billable episodes of care and focuses on maximizing revenue under fee-for-service payment systems. These EHR systems generally do not facilitate integrated, team-oriented, cost-conscious care. System Needs for HIT Applications That Can Drive Accountability

Including emergency departments in hospitals’ bar-code-assisted medication administration system

ASHP’s Pharmacy Practice Model Initiative is a call to action for health systems to change their practice model while promoting safety and efficiency; this may be accomplished by adopting health information technology.[1][1] Bar-code-assisted medication administration (BCMA) is a technology

The future of health IT innovation and informatics: a report from AMIA's 2010 policy meeting

While much attention has been paid to the short-term impact that widespread adoption of health information technology (health IT) will have on the healthcare system, there is a corresponding need to look at the long-term effects that extant policies may have on health IT system resilience, innovation, and related ethical, social/legal issues. The American Medical Informatics Association's 2010 Health Policy Conference was convened to further the national discourse on the issues surrounding these longer-term considerations. Conference participants self-selected into three broad categories: resilience in healthcare and health IT; ethical, legal, and social challenges; and innovation, adoption, and sustainability. The discussions about problem areas lead to findings focusing on the lack of encouragement for long-term IT innovation that may result from current health IT policies; the potential impact of uneven adoption of health IT based on the exclusions of the current financial incentives; the weaknesses of contingency and risk mitigation planning that threaten system resilience; and evolving standards developed in response to challenges relating to the security, integrity, and availability of electronic health information. This paper discusses these findings and also offers recommendations that address the interwoven topics of innovation, resilience, and adoption. The goal of this paper is to encourage public and private sector organizations that have a role in shaping health information policy to increase attention to developing a national strategy that assures that health IT innovation and resilience are not impeded by shorter-term efforts to implement current approaches emphasizing adoption and meaningful use of electronic health records.

Sharing Clinical Data Electronically

THE UNITED STATES IS UNDERTAKING AN AMBITIOUS EFfort to wire the health care system. The goal is to build a nationwide information infrastructure to serve as the foundation for large and sustained improvements in performance. Widespread adoption of health information technology will support new care delivery models, such as patient-centered medical homes, alongside broader initiatives, such as performance reporting and public health surveillance. To enable the health information technology revolution, Congress allocated nearly $30 billion focused on 2 main goals: transitioning physicians and hospitals from paper-based to electronic systems and enabling these systems to interoperate, allowing clinical data to flow between health care organizations. The vision of complete patient information available across care delivery settings is compelling and central to a highfunctioning health care system. However, the vision is deceptively simple: there are enormous challenges to enabling clinical data to flow across organizations. These challenges are substantially greater than those associated with transitioning physicians and hospitals to electronic health records. Health information exchange (HIE) is the act of sharing clinical data among health care practitioners and practice settings (physicians, hospitals, nursing homes, etc) who are not part of the same organizational entity. Although most electronic health records make clinical data sharing within the same organization relatively easy, sharing across organizations is difficult. Before passage of the 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act, policy makers primarily focused on regional health information organizations (RHIOs) to promote HIE. RHIOs brought together physicians, hospitals, and other health care stakeholders in the local community to establish core principles for how they could exchange data with each other. Despite substantial funding from state and federal governments, these organizations have made slow progress in enabling broad exchange and finding sustainable business models. Under HITECH, policy makers are pursuing a more flexible multipronged approach to HIE. First, they included the ability to engage in HIE (ie, share clinical data electronically with others) in the criterion for “meaningful use,” the federal standard for incentives to health care practitioners and hospitals for using an electronic health record. In the future, meaningful use will likely require that clinicians actually engage in HIE, not just demonstrate the ability. Part of the motivation for beginning with less stringent requirements is that even for clinicians and health care organizations with an electronic health record, there are few accessible, affordable options for sending and receiving data electronically across organizations. Therefore, a second part of the federal approach is to engage states in creating such options. In 2010, the US Department of Health and Human Services awarded more than $548 million through the State HIE Cooperative Agreement Program. Over the 4-year program period, states are responsible for ensuring adequate infrastructure to allow for sharing clinical data across care settings. States are in the early stages of implementing their plans and are pursuing a variety of strategies. A third facet of the federal approach is to promote the Direct Project, a set of services that rely on the Internet to securely push data from one authorized user to another. The Direct Project essentially operates like an e-mail inbox, with added security and authorization, and is a relatively simple and inexpensive approach to HIE. The long-term plan is to evolve from clinicians pushing data (ie, sending an e-mail) to searching for individual patients and retrieving their data, with the hope that HIE will be seamless and will require little work by the clinician to search for information outside of the electronic health record. Whether these efforts will successfully result in broadbased HIE is unclear. According to Blumenthal, the Obama Administration’s former point person on health information technology, HIE is one of the “major challenges in delivering on the ambitious agenda of the HITECH Act.” There are at least 5 major barriers, 3 of which seem under federal policy makers’ control. The first is data privacy and security. There remains uncertainty among clinicians about the legal ramifications of a data breach or unauthorized access through HIE. Second, the Direct Project promotes point-

Obtaining Providers’ ‘Buy-In’ And Establishing Effective Means Of Information Exchange Will Be Critical To HITECH’s Success

In enacting the Health Information Technology for Economic and Clinical Health (HITECH) provisions of the American Recovery and Reinvestment Act, Congress set ambitious goals for the nation to integrate information technology into health care delivery. The provisions called for the electronic exchange of health information and the adoption and meaningful use of health information technology in health care practices and hospitals. We examined the marketplace and regulatory forces that influence HITECH's success and identify outstanding challenges, some beyond the provisions' control. To reach HITECH's goals, providers and patients must be persuaded of the value of health information exchange and support its implementation. Privacy concerns and remaining technical challenges must also be overcome. Achieving HITECH's goals will require well-aligned incentives, both visionary and practical pursuit of exchange infrastructure, and realistic assumptions about how quickly such wholesale change can be accomplished. The use of metrics to show adoption proceeding at a reasonable pace, increased flow of data across parties, and evidence that care is improving, at least in areas with robust systems, will be essential to persuade stakeholders that the initiative is progressing well and warrants continued investment.

Giving Office-Based Physicians Electronic Access To Patients’ Prior Imaging And Lab Results Did Not Deter Ordering Of Tests

Policy-based incentives for health care providers to adopt health information technology are predicated on the assumption that, among other things, electronic access to patient test results and medical records will reduce diagnostic testing and save money. To test the generalizability of findings that support this assumption, we analyzed the records of 28,741 patient visits to a nationally representative sample of 1,187 office-based physicians in 2008. Physicians' access to computerized imaging results (sometimes, but not necessarily, through an electronic health record) was associated with a 40-70 percent greater likelihood of an imaging test being ordered. The electronic availability of lab test results was also associated with ordering of additional blood tests. The availability of an electronic health record in itself had no apparent impact on ordering; the electronic access to test results appears to have been the key. These findings raise the possibility that, as currently implemented, electronic access does not decrease test ordering in the office setting and may even increase it, possibly because of system features that are enticements to ordering. We conclude that use of these health information technologies, whatever their other benefits, remains unproven as an effective cost-control strategy with respect to reducing the ordering of unnecessary tests.

Hospitals Ineligible For Federal Meaningful-Use Incentives Have Dismally Low Rates Of Adoption Of Electronic Health Records

The US government has dedicated substantial resources to help certain providers, such as short-term acute care hospitals and physicians, adopt and meaningfully use electronic health record (EHR) systems. We used national data to determine adoption rates of EHR systems among all types of inpatient providers that were ineligible for these same federal meaningful-use incentives: long-term acute care hospitals, rehabilitation hospitals, and psychiatric hospitals. Adoption rates for these institutions were dismally low: less than half of the rate among short-term acute care hospitals. Specifically, 12 percent of short-term acute care hospitals have at least a basic EHR system, compared with 6 percent of long-term acute care hospitals, 4 percent of rehabilitation hospitals, and 2 percent of psychiatric hospitals. To advance the creation of a nationwide health information technology infrastructure, federal and state policy makers should consider additional measures, such as adopting health information technology standards and EHR system certification criteria appropriate for these ineligible hospitals; including such hospitals in state health information exchange programs; and establishing low-interest loan programs for the acquisition and use of certified EHR systems by ineligible providers.

Informatics Technology Mimics Ecology: Dense, Mutualistic Collaboration Networks Are Associated with Higher Publication Rates

Information technology (IT) adoption enables biomedical research. Publications are an accepted measure of research output, and network models can describe the collaborative nature of publication. In particular, ecological networks can serve as analogies for publication and technology adoption. We constructed network models of adoption of bioinformatics programming languages and health IT (HIT) from the literature.We selected seven programming languages and four types of HIT. We performed PubMed searches to identify publications since 2001. We calculated summary statistics and analyzed spatiotemporal relationships. Then, we assessed ecological models of specialization, cooperativity, competition, evolution, biodiversity, and stability associated with publications.Adoption of HIT has been variable, while scripting languages have experienced rapid adoption. Hospital systems had the largest HIT research corpus, while Perl had the largest language corpus. Scripting languages represented the largest connected network components. The relationship between edges and nodes was linear, though Bioconductor had more edges than expected and Perl had fewer. Spatiotemporal relationships were weak. Most languages shared a bioinformatics specialization and appeared mutualistic or competitive. HIT specializations varied. Specialization was highest for Bioconductor and radiology systems. Specialization and cooperativity were positively correlated among languages but negatively correlated among HIT. Rates of language evolution were similar. Biodiversity among languages grew in the first half of the decade and stabilized, while diversity among HIT was variable but flat. Compared with publications in 2001, correlation with publications one year later was positive while correlation after ten years was weak and negative.Adoption of new technologies can be unpredictable. Spatiotemporal relationships facilitate adoption but are not sufficient. As with ecosystems, dense, mutualistic, specialized co-habitation is associated with faster growth. There are rapidly changing trends in external technological and macroeconomic influences. We propose that a better understanding of how technologies are adopted can facilitate their development.

The US Food and Drug Administration's Sentinel Initiative: Expanding the horizons of medical product safety

The US Food and Drug Administration's Sentinel Initiative: Expanding the horizons of medical product safety

Standards and Guidelines for Personal Health Records in the United States: Finding Consensus in a Rapidly Evolving and Divided Environment

Health care spending in the U.S. over the past decade has dramatically increased over the past decade and is expected to rise to 20% of GDP in the United States by the end of the decade. In 2010, the U.S. Congress approved the Health Care Reform Act with a critical component of this legislation being the adoption of health information technologies (i.e. EMRs, EHRs, PHRs, etc.) aimed at transforming the health care system. Consumer-driven health care models are seen as essential to control the escalating costs of health care. The objective of this research is to canvas the landscape of existing standards and guidelines relating to electronic personal health records (PHRs) and to evaluate the level of adoption of these standards and guidelines amongst current vendors. Through this effort, we propose a consensus standard for PHRs consisting of 14 data components, 11 of which should be essential for all PHRs and 3 additional recommended data components. Through a survey of existing PHR vendors, we observe a low level of adoption of existing standards in commercially available PHR products and note a wide variation (36-73%) of inclusion of critical and desired data components. Further, we propose 4 key features and services based upon a review of the existing literature to facilitate consumer adoption and to improve usefulness of PHRs. By proposing a consensus standard for PHR data components and features, we seek to provide clarity to developers and vendors of HIT products to facilitate product development, interoperability, and integration and data exchange with existing EMR/EHR products

Health Services Research Evaluation Principles

Our forthcoming national experiment in increased health information technology (HIT) adoption funded by the American Recovery and Reinvestment Act of 2009 will require a comprehensive approach to evaluating HIT. The quality of evaluation studies of HIT to date reveals a need for broader evaluation frameworks that limits the generalizability of findings and the depth of lessons learned. Develop an informatics evaluation framework for health information technology (HIT) integrating components of health services research (HSR) evaluation and informatics evaluation to address identified shortcomings in available HIT evaluation frameworks. A systematic literature review updated and expanded the exhaustive review by Ammenwerth and deKeizer (AdK). From retained studies, criteria were elicited and organized into classes within a framework. The resulting Health Information Technology Research-based Evaluation Framework (HITREF) was used to guide clinician satisfaction survey construction, multi-dimensional analysis of data, and interpretation of findings in an evaluation of a vanguard community health care EHR. The updated review identified 128 electronic health record (EHR) evaluation studies and seven evaluation criteria not in AdK: EHR Selection/Development/Training; Patient Privacy Concerns; Unintended Consequences/ Benefits; Functionality; Patient Satisfaction with EHR; Barriers/Facilitators to Adoption; and Patient Satisfaction with Care. HITREF was used productively and was a complete evaluation framework which included all themes that emerged. We can recommend to future EHR evaluators that they consider adding a complete, research-based HIT evaluation framework, such as HITREF, to their evaluation tools suite to monitor HIT challenges as the federal government strives to increase HIT adoption.

Evaluation of a wireless handheld medication management device in the prevention of drug-drug interactions in a Medicaid population.

With the passage of the Health Information Technology for Economic and Clinical Health (HITECH) Act, widespread adoption of certain health information technologies, such as electronic health records (EHRs) and electronic prescribing (e-prescribing), is imminent. Drug-drug interaction (DDI) screening and medication history information are commonly incorporated into health information exchange systems to improve medical decision making, safety, and quality of care, but the value of these features is unclear. To evaluate the effect of providing access to an early generation electronic medication management program with medication history accessible to prescribers via a wireless handheld personal digital assistant (PDA) device on the incidence of potential DDIs (i.e., DDIs that may or may not cause patient harm). This study employed a retrospective pre-intervention/post-intervention study design with a comparison group to evaluate the effectiveness of a wireless handheld medication management program in preventing serious potential DDIs. Licensed prescribers in a state Medicaid program who wrote prescriptions during the period from August 2003 through June 2006 were included in this study. The intervention (PDA) group consisted of clinicians who requested and were granted access to the wireless handheld device containing prescription drug history between August 1, 2004, and June 30, 2005. Initially the device contained 100-day patient-specific medication history, but other functionalities were added during the study period including the ability to check for drug-drug interactions and e-prescribing. The comparison group consisted of prescribers who sent a request to obtain, but did not receive, the wireless handheld device during the same time period. Baseline prescribing patterns of 25 previously identified clinically important potential DDIs were assessed over two 12-month periods, one period prior to (baseline) and one period after (follow-up) an index date (date of device deployment for PDA group; date of request for comparison group). A random-effects negative binomial model was used to analyze the primary outcome, the number of potential DDIs per prescriber per 12-month time period. A secondary outcome of interest, the likelihood that a prescriber would prescribe at least 1 potentially interacting medication pair during the baseline and follow-up periods, was analyzed using a random-effects logistic model. A total of 1,615 prescribers constituted the PDA group, and 600 prescribers made up the comparison group. Prescribers in the 2 groups were significantly different in their specialty practice areas (P less than 0.001), number of pharmacy claims at baseline (P less than 0.001), and the likelihood of prescribing at least 1 potential DDI combination during the 1-year baseline period (P=0.003). However, the prescriber groups were similar in their average age (P=0.241) and geographic location (P=0.181). The most widely prescribed potential DDIs included those involving warfarin with nonsteroidal anti-inflammatory drugs (NSAIDs) and thyroid hormones. The median number of patient medication history updates requested per PDA group prescriber during follow-up was 24 (range 0 to 1,073). At baseline, 1,104 (68.4%) of the PDA group and 449 (74.8%) of the comparison group had no potential DDIs. During the next year, 1,131 (70.0%) and 462 (77.0%) of the PDA group and comparison group, respectively, had no DDIs. The incidence rate ratio was 1.01 (95% CI=0.87-1.17) for the PDA group relative to the comparison group for change in number of potential DDIs. In the logistic regression model, the odds of prescribing at least 1 potential DDI did not significantly differ by group (odds ratio=1.26, 95% CI=0.96-1.66). These results indicate that there was no significant difference between the intervention and comparison group with regard to the change in the rate of potential DDIs between the baseline and follow-up periods. A stand-alone medication management program in a wireless PDA device was not frequently used by most prescribers to update patient medication histories and was not associated with a reduction in the rate of prescribing potentially clinically important DDIs.

Drivers and Barriers in Health IT Adoption

Despite near (and rare) consensus that the adoption and diffusion of health information technology (health IT) will bolster outcomes for organizations, individuals, and the healthcare system as a whole, there has been surprisingly little consideration of the structures and processes within organizations that might drive the adoption and effective use of the technology. Management research provides a useful lens through which to analyze both the determinants of investment and the benefits that can ultimately be derived from these investments. This paper provides a conceptual framework for understanding health IT adoption. In doing so, this paper highlights specific organizational barriers or enablers at different stages of the adoption process - investment, implementation, and use - and at different levels of organizational decision-making - strategic, operational, and frontline. This framework will aid both policymakers and organizational actors as they make sense of the transition from paper-based to electronic systems.

Adoption and Diffusion of Health Information Technology - The Case of Primary Care Clinics

We empirically examine the determinants of adoption of information technology by primary healthcare clinics using a large sample of physician clinics from several States in the U.S. Ours is one of the first studies to intensively investigate primary care clinics. These clinics are important as they represent the frontlines in the delivery of services in this large and complex market. Our study generates several interesting results related to the adoption and diffusion of Health Information Technology (HIT), including: (1) the adoption probabilities vary considerably by the specific type of clinic; (2) in contrast to numerous studies in the broader technology adoption literature, we find little evidence to suggest a relationship between firm (clinic) size and the likelihood of adoption; (3) there appears to be no definitive relationship between the age of a clinic and the likelihood of adoption; (4) there is a strong effect of geographic location, as measured by specific types of urban and rural counties, on the likelihood of adoption; (5) market competitive forces appear to have a mixed influence on adoption; (6) there is a distinct State-specific effect suggesting that information privacy, medical malpractice laws and State initiatives may play an important role in adoption; and (7) HIT is diffusing at a faster rate over time. Our findings have the potential to provide a better understanding of the longer-run effectiveness and efficiency in the provision of healthcare, and crafting appropriate policy responses. We note some future extensions of our work.

Closing the Gap: Eliminating Health Care Disparities among Latinos with Diabetes Using Health Information Technology Tools and Patient Navigators

Latinos have higher rates of diabetes and diabetes-related complications compared to non-Latinos. Clinical diabetes self-management tools that rely on innovative health information technology (HIT) may not be widely used by Latinos, particularly those that have low literacy or numeracy, low income, and/or limited English proficiency. Prior work has shown that tailored diabetes self-management educational interventions are feasible and effective in improving diabetes knowledge and physiological measures among Latinos, especially those interventions that utilize tailored coaching and navigator programs. In this article, we discuss the role of HIT for diabetes management in Latinos and describe a novel "eNavigator" role that we are developing to increase HIT adoption and thereby reduce health care disparities.

Implementation of the Federal Health Information Technology Initiative

The 2009 HITECH Act allocated $29 billion to support the adoption of health information technology. The author reviews the accomplishments to date and the challenges ahead in creating a nationwide, interoperable, and secure electronic health information system.

Creating a Survey to Assess Physicians’ Adoption of Health Information Technology

Information on state-level health information technology (HIT) adoption will become increasingly important with the implementation of incentive payments to accelerate uptake. Recognizing this, the Rhode Island Department of Health selected physician HIT adoption as a subject for its legislatively mandated quality reporting program. This article discusses the state's process for developing HIT adoption measures, including the importance of stakeholder involvement in the development of a survey and the difficulty of accurately defining electronic medical record (EMR) adoption. This article describes the challenges in defining "true" EMRs, which may be addressed, in part, by ensuring local consensus about EMR measures and by piloting the survey and measures, prior to public reporting or the calculation of a statewide baseline. It also presents results from the 2009 administration of this survey to all 3,883 Rhode Island-licensed physicians providing direct patient care.

Health Information Systems in Small Practices: Improving the Delivery of Clinical Preventive Services

Despite strong evidence that clinical preventive services (CPS) reduce morbidity and mortality, CPS performance has not improved in adult primary care. In addition to implementing electronic health records (EHRs), key factors for improving CPS include providing actionable information at the point of care, technical support staff, and quality-improvement assistance. These resources are not typically available in small practices. Estimate the impact on CPS delivery after a software upgrade to embed a clinical decision support system and practice-level quality-improvement support services. Practices were recruited from the Primary Care Information Project, a citywide initiative assisting practices adopt health information technology. Data were collected in 2009 and 2010, and analyses were conducted in 2010 and 2011. Across two time periods, receipt of CPS was calculated for 56 practices. Period 1 measured CPS delivery 2-37 months following implementation of an EHR. Period 2 measured CPS delivery within the first 6 months after an EHR software upgrade. Substantial increases in the delivery of selected CPS were observed after the EHR software upgrades. Blood pressure control for patients with hypertension increased from 46.0% to 54.8%. Breast cancer screening, recorded BMI, and HbA1c testing for patients with diabetes also increased. More than half of the practices increased their patients' blood pressure control, recorded BMI, breast cancer screening, and HbA1c screening by ≥5 percentage points. Delivery of CPS can increase in small primary care practices that implement an EHR that includes comprehensive quality-improvement support.

U.S. hospital efficiency and adoption of health information technology

This study empirically examines the association between hospital inefficiency and the decision to introduce electronic medical records (EMR) and computerized physician order entry (CPOE) in a national sample of U.S. general hospitals in urban areas in 2006. The main research question is whether the presence of hospital cost inefficiency or other factors driving inefficiency in the production process of a hospital explain low adoption rates of health information technology (HIT) in a hospital setting. We estimated a logistic regression of HIT adoption as a function of hospital cost inefficiency scores obtained using a stochastic frontier analysis. The results demonstrate that hospitals with a greater degree of cost inefficiency were more likely to introduce EMR, suggesting that the benefits of EMR implementation in terms of improved efficiency were likely to outweigh the costs of adoption compared to hospitals that are more efficient. The results showed no association between cost inefficiency and the CPOE adoption decision.

Research Forecasting for Health Information Technology (HIT), using technology intelligence

Due to the rapid pace of change in technology and its impact on society, there is an increasing demand for use of Technology Forecasting methods to improve policy planning and implementation. One such area is the field of Health Care and the impact of Health Information Technology (HIT) on this field. Using HIT has shown to be associated with reduced cost, improved quality, and better patient experience; yet HIT adoption has been slow. Therefore, there is a need to better understand the HIT adoption processes in order to meet the evolving requirements for health care delivery.We propose collecting Technology Intelligence for use in Research Forecasting as part of the larger HIT Technology Forecasting efforts. In this study, we systematically probed for HIT-related technology intelligence in the fields of Information Systems, Engineering Management, and Medical Informatics. Results of our analysis show that all three fields are active in Health IT research, but could benefit from further collaboration. We were also able to identify instances of emerging journals and emerging topics in Health IT research. We conclude that it is indeed plausible and meaningful to collect technology intelligence on HIT adoption, to support the overall goal of improving healthcare delivery.