The impact of EHR and HIE on reducing avoidable admissions: controlling main differential diagnoses

The role of information systems in emergency department decision-making-a literature review

OBJECTIVES

Healthcare providers employ heuristic and analytical decision-making to navigate the high-stakes environment of the emergency department (ED). Despite the increasing integration of information systems (ISs), research on their efficacy is conflicting. Drawing on related fields, we investigate how timing and mode of delivery influence IS effectiveness. Our objective is to reconcile previous contradictory findings, shedding light on optimal IS design in the ED.

MATERIALS AND METHODS

We conducted a systematic review following PRISMA across PubMed, Scopus, and Web of Science. We coded the ISs' timing as heuristic or analytical, their mode of delivery as active for automatic alerts and passive when requiring user-initiated information retrieval, and their effect on process, economic, and clinical outcomes.

RESULTS

Our analysis included 83 studies. During early heuristic decision-making, most active interventions were ineffective, while passive interventions generally improved outcomes. In the analytical phase, the effects were reversed. Passive interventions that facilitate information extraction consistently improved outcomes.

DISCUSSION

Our findings suggest that the effectiveness of active interventions negatively correlates with the amount of information received during delivery. During early heuristic decision-making, when information overload is high, physicians are unresponsive to alerts and proactively consult passive resources. In the later analytical phases, physicians show increased receptivity to alerts due to decreased diagnostic uncertainty and information quantity. Interventions that limit information lead to positive outcomes, supporting our interpretation.

CONCLUSION

We synthesize our findings into an integrated model that reveals the underlying reasons for conflicting findings from previous reviews and can guide practitioners in designing ISs in the ED.

Diagnosing an overcrowded emergency department from its Electronic Health Records

Emergency department overcrowding is a complex problem that persists globally. Data of visits constitute an opportunity to understand its dynamics. However, the gap between the collected information and the real-life clinical processes, and the lack of a whole-system perspective, still constitute a relevant limitation. An analytical pipeline was developed to analyse one-year of production data following the patients that came from the ED (n = 49,938) at Uppsala University Hospital (Uppsala, Sweden) by involving clinical experts in all the steps of the analysis. The key internal issues to the ED were the high volume of generic or non-specific diagnoses from non-urgent visits, and the delayed decision regarding hospital admission caused by several imaging assessments and lack of hospital beds. Furthermore, the external pressure of high frequent re-visits of geriatric, psychiatric, and patients with unspecified diagnoses dramatically contributed to the overcrowding. Our work demonstrates that through analysis of production data of the ED patient flow and participation of clinical experts in the pipeline, it was possible to identify systemic issues and directions for solutions. A critical factor was to take a whole systems perspective, as it opened the scope to the boundary effects of inflow and outflow in the whole healthcare system.

From "wading through treacle" to "making haste slowly": A comprehensive yet parsimonious model of drivers and challenges to implementing patient data sharing projects based on an EPaCCS evaluation and four pre-existing literature reviews

Conceptually, this study aimed to 1) identify the challenges and drivers encountered by England's Electronic Palliative Care Coordination System (EPaCCS) projects in the context of challenges and drivers in other projects on data sharing for individual care (also referred to as Health Information Exchange, HIE) and 2) organise them in a comprehensive yet parsimonious framework. The study also had a strong applied goal: to derive specific and non-trivial recommendations for advancing data sharing projects, particularly ones in early stages of development and implementation. Primary data comprised 40 in-depth interviews with 44 healthcare professionals, patients, carers, project team members and decision makers in Cambridgeshire, UK. Secondary data were extracted from four pre-existing literature reviews on Health Information Exchange and Health Information Technology implementation covering 135 studies. Thematic and framework analysis underpinned by "pluralist" coding were the main analytical approaches used. We reduced an initial set of >1,800 parameters into >500 challenges and >300 drivers to implementing EPaCCS and other data sharing projects. Less than a quarter of the 800+ parameters were associated primarily with the IT solution. These challenges and drivers were further condensed into an action-guiding, strategy-informing framework of nine types of "pure challenges", four types of "pure drivers", and nine types of "oppositional or ambivalent forces". The pure challenges draw parallels between patient data sharing and other broad and complex domains of sociotechnical or social practice. The pure drivers differ in how internal or external to the IT solution and project team they are, and thus in the level of control a project team has over them. The oppositional forces comprise pairs of challenges and drivers where the driver is a factor serving to resolve or counteract the challenge. The ambivalent forces are factors perceived simultaneously as a challenge and a driver depending on context, goals and perspective. The framework is distinctive in its emphasis on: 1) the form of challenges and drivers; 2) ambivalence, ambiguity and persistent tensions as fundamental forces in the field of innovation implementation; and 3) the parallels it draws with a variety of non-IT, non-health domains of practice as a source of fruitful learning. Teams working on data sharing projects need to prioritise further the shaping of social interactions and structural and contextual parameters in the midst of which their IT tools are implemented. The high number of "ambivalent forces" speaks of the vital importance for data sharing projects of skills in eliciting stakeholders' assumptions; managing conflict; and navigating multiple needs, interests and worldviews.

Value of Electronic Health Records Measured Using Financial and Clinical Outcomes: Quantitative Study

BACKGROUND

The Health Information Technology for Economic and Clinical Health Act of 2009 was legislated to reduce health care costs, improve quality, and increase patient safety. Providers and organizations were incentivized to exhibit meaningful use of certified electronic health record (EHR) systems in order to achieve this objective. EHR adoption is an expensive investment, given the resources and capital that are invested. Due to the cost of the investment, a return on the EHR adoption investment is expected.

OBJECTIVE

This study performed a value analysis of EHRs. The objective of this study was to investigate the relationship between EHR adoption levels and financial and clinical outcomes by combining both financial and clinical outcomes into one conceptual model.

METHODS

We examined the multivariate relationships between different levels of EHR adoption and financial and clinical outcomes, along with the time variant control variables, using moderation analysis with a longitudinal fixed effects model. Since it is unknown as to when hospitals begin experiencing improvements in financial outcomes, additional analysis was conducted using a 1- or 2-year lag for profit margin ratios.

RESULTS

A total of 5768 hospital-year observations were analyzed over the course of 4 years. According to the results of the moderation analysis, as the readmission rate increases by 1 unit, the effect of a 1-unit increase in EHR adoption level on the operating margin decreases by 5.38%. Hospitals with higher readmission payment adjustment factors have lower penalties.

CONCLUSIONS

This study fills the gap in the literature by evaluating individual relationships between EHR adoption levels and financial and clinical outcomes, in addition to evaluating the relationship between EHR adoption level and financial outcomes, with clinical outcomes as moderators. This study provided statistically significant evidence (P<.05), indicating that there is a relationship between EHR adoption level and operating margins when this relationship is moderated by readmission rates, meaning hospitals that have adopted EHRs could see a reduction in their readmission rates and an increase in operating margins. This finding could further be supported by evaluating more recent data to analyze whether hospitals increasing their level of EHR adoption would decrease readmission rates, resulting in an increase in operating margins. Hospitals would incur lower penalties as a result of improved readmission rates, which would contribute toward improved operating margins.

Understanding the perceived role of electronic health records and workflow fragmentation on clinician documentation burden in emergency departments

OBJECTIVE

Understand the perceived role of electronic health records (EHR) and workflow fragmentation on clinician documentation burden in the emergency department (ED).

METHODS

From February to June 2022, we conducted semistructured interviews among a national sample of US prescribing providers and registered nurses who actively practice in the adult ED setting and use Epic Systems' EHR. We recruited participants through professional listservs, social media, and email invitations sent to healthcare professionals. We analyzed interview transcripts using inductive thematic analysis and interviewed participants until we achieved thematic saturation. We finalized themes through a consensus-building process.

RESULTS

We conducted interviews with 12 prescribing providers and 12 registered nurses. Six themes were identified related to EHR factors perceived to contribute to documentation burden including lack of advanced EHR capabilities, absence of EHR optimization for clinicians, poor user interface design, hindered communication, increased manual work, and added workflow blockages, and five themes associated with cognitive load. Two themes emerged in the relationship between workflow fragmentation and EHR documentation burden: underlying sources and adverse consequences.

DISCUSSION

Obtaining further stakeholder input and consensus is essential to determine whether these perceived burdensome EHR factors could be extended to broader contexts and addressed through optimizing existing EHR systems alone or through a broad overhaul of the EHR's architecture and primary purpose.

CONCLUSION

While most clinicians perceived that the EHR added value to patient care and care quality, our findings underscore the importance of designing EHRs that are in harmony with ED clinical workflows to alleviate the clinician documentation burden.

Evaluating the Impact of a Point-of-Care Cardiometabolic Clinical Decision Support Tool on Clinical Efficiency Using Electronic Health Record Audit Log Data: Algorithm Development and Validation

Background

Electronic health record (EHR) systems are becoming increasingly complicated, leading to concerns about rising physician burnout, particularly for primary care physicians (PCPs). Managing the most common cardiometabolic chronic conditions by PCPs during a limited clinical time with a patient is challenging.

Objective

This study aimed to evaluate a Cardiometabolic Sutter Health Advanced Reengineered Encounter (CM-SHARE), a web-based application to visualize key EHR data, on the EHR use efficiency.

Methods

We developed algorithms to identify key clinic workflow measures (eg, total encounter time, total physician time in the examination room, and physician EHR time in the examination room) using audit data, and we validated and calibrated the measures with time-motion data. We used a pre-post parallel design to identify propensity score–matched CM-SHARE users (cases), nonusers (controls), and nested-matched patients. Cardiometabolic encounters from matched case and control patients were used for the workflow evaluation. Outcome measures were compared between the cases and controls. We applied this approach separately to both the CM-SHARE pilot and spread phases.

Results

Time-motion observation was conducted on 101 primary care encounters for 9 PCPs in 3 clinics. There was little difference (<0.8 minutes) between the audit data–derived workflow measures and the time-motion observation. Two key unobservable times from audit data, physician entry into and exiting the examination room, were imputed based on time-motion studies. CM-SHARE was launched with 6 pilot PCPs in April 2016. During the prestudy period (April 1, 2015, to April 1, 2016), 870 control patients with 2845 encounters were matched with 870 case patients and encounters, and 727 case patients with 852 encounters were matched with 727 control patients and 3754 encounters in the poststudy period (June 1, 2016, to June 30, 2017). Total encounter time was slightly shorter (mean −2.7, SD 1.4 minutes, 95% CI −4.7 to −0.9; mean –1.6, SD 1.1 minutes, 95% CI −3.2 to −0.1) for cases than controls for both periods. CM-SHARE saves physicians approximately 2 minutes EHR time in the examination room (mean −2.0, SD 1.3, 95% CI −3.4 to −0.9) compared with prestudy period and poststudy period controls (mean −1.9, SD 0.9, 95% CI −3.8 to −0.5). In the spread phase, 48 CM-SHARE spread PCPs were matched with 84 control PCPs and 1272 cases with 3412 control patients, having 1119 and 4240 encounters, respectively. A significant reduction in total encounter time for the CM-SHARE group was observed for short appointments (≤20 minutes; 5.3-minute reduction on average) only. Total physician EHR time was significantly reduced for both longer and shorter appointments (17%-33% reductions).

Conclusions

Combining EHR audit log files and clinical information, our approach offers an innovative and scalable method and new measures that can be used to evaluate clinical EHR efficiency of digital tools used in clinical settings.

Use of My Health Record by Clinicians in the Emergency Department: An Analysis of Log Data

Objectives: Leverage log data to explore access to My Health Record (MHR), the national electronic health record of Australia, by clinicians in the emergency department. Materials and Methods: A retrospective analysis was conducted using secondary routinely-collected data. Log data pertaining to all patients who presented to the emergency department between 2019 and 2021 of a not-for-profit hospital (that annually observes 23,000 emergency department presentations) were included in this research. Attendance data and human resources data were linked with MHR log data. The primary outcome was a dichotomous variable that indicated whether the MHR of a patient was accessed. Logistic regression facilitated the exploration of factors (user role, day of the week, and month) associated with access. Results: My Health Record was accessed by a pharmacist, doctor, or nurse in 19.60% (n = 9,262) of all emergency department presentations. Access was dominated by pharmacists (18.31%, n = 8,656). All users demonstrated a small, yet significant, increase in access every month (odds ratio = 1.07, 95% Confidence interval: 1.06-1.07, p ≤ 0.001). Discussion: Doctors, pharmacists, and nurses are increasingly accessing MHR. Based on this research, substantially more pharmacists appear to be accessing MHR, compared to other user groups. However, only one in every five patients who present to the emergency department have their MHR accessed, thereby indicating a need to accelerate and encourage the adoption and access of MHR by clinicians.

Association between 30-day readmission rates and health information technology capabilities in US hospitals

Health information technology (IT) is often proposed as a solution to fragmentation of care, and has been hypothesized to reduce readmission risk through better information flow. However, there are numerous distinct health IT capabilities, and it is unclear which, if any, are associated with lower readmission risk.To identify the specific health IT capabilities adopted by hospitals that are associated with hospital-level risk-standardized readmission rates (RSRRs) through path analyses using structural equation modeling.This STROBE-compliant retrospective cross-sectional study included non-federal U.S. acute care hospitals, based on their adoption of specific types of health IT capabilities self-reported in a 2013 American Hospital Association IT survey as independent variables. The outcome measure included the 2014 RSRRs reported on Hospital Compare website.A 54-indicator 7-factor structure of hospital health IT capabilities was identified by exploratory factor analysis, and corroborated by confirmatory factor analysis. Subsequent path analysis using Structural equation modeling revealed that a one-point increase in the hospital adoption of patient engagement capability latent scores (median path coefficient ß = -0.086; 95% Confidence Interval, -0.162 to -0.008), including functionalities like direct access to the electronic health records, would generally lead to a decrease in RSRRs by 0.086%. However, computerized hospital discharge and information exchange capabilities with other inpatient and outpatient providers were not associated with readmission rates.These findings suggest that improving patient access to and use of their electronic health records may be helpful in improving hospital performance on readmission; however, computerized hospital discharge and information exchange among clinicians did not seem as beneficial - perhaps because of the quality or timeliness of information transmitted. Future research should use more recent data to study, not just adoption of health IT capabilities, but also whether their usage is associated with lower readmission risk. Understanding which capabilities impact readmission risk can help policymakers and clinical stakeholders better focus their scarce resources as they invest in health IT to improve care delivery.

Health systems' use of enterprise health information exchange vs single electronic health record vendor environments and unplanned readmissions

OBJECTIVE

Enterprise health information exchange (HIE) and a single electronic health record (EHR) vendor solution are 2 information exchange approaches to improve performance and increase the quality of care. This study sought to determine the association between adoption of enterprise HIE vs a single vendor environment and changes in unplanned readmissions.

MATERIALS AND METHODS

The association between unplanned 30-day readmissions among adult patients and adoption of enterprise HIE or a single vendor environment was measured in a panel of 211 system-member hospitals from 2010 through 2014 using fixed-effects regression models. Sample hospitals were members of health systems in 7 states. Enterprise HIE was defined as self-reported ability to exchange information with other members of the same health system who used different EHR vendors. A single EHR vendor environment reported exchanging information with other health system members, but all using the same EHR vendor.

RESULTS

Enterprise HIE adoption was more common among the study sample than EHR (75% vs 24%). However, adoption of a single EHR vendor environment was associated with a 0.8% reduction in the probability of a readmission within 30 days of discharge. The estimated impact of adopting an enterprise HIE strategy on readmissions was smaller and not statically significant.

CONCLUSION

Reductions in the probability of an unplanned readmission after a hospital adopts a single vendor environment suggests that HIE technologies can better support the aim of higher quality care. Additionally, health systems may benefit more from a single vendor environment approach than attempting to foster exchange across multiple EHR vendors.

Using electronic health record audit logs to study clinical activity: a systematic review of aims, measures, and methods

OBJECTIVE

To systematically review published literature and identify consistency and variation in the aims, measures, and methods of studies using electronic health record (EHR) audit logs to observe clinical activities.

MATERIALS AND METHODS

In July 2019, we searched PubMed for articles using EHR audit logs to study clinical activities. We coded and clustered the aims, measures, and methods of each article into recurring categories. We likewise extracted and summarized the methods used to validate measures derived from audit logs and limitations discussed of using audit logs for research.

RESULTS

Eighty-five articles met inclusion criteria. Study aims included examining EHR use, care team dynamics, and clinical workflows. Studies employed 6 key audit log measures: counts of actions captured by audit logs (eg, problem list viewed), counts of higher-level activities imputed by researchers (eg, chart review), activity durations, activity sequences, activity clusters, and EHR user networks. Methods used to preprocess audit logs varied, including how authors filtered extraneous actions, mapped actions to higher-level activities, and interpreted repeated actions or gaps in activity. Nineteen studies validated results (22%), but only 9 (11%) through direct observation, demonstrating varying levels of measure accuracy.

DISCUSSION

While originally designed to aid access control, EHR audit logs have been used to observe diverse clinical activities. However, most studies lack sufficient discussion of measure definition, calculation, and validation to support replication, comparison, and cross-study synthesis.

CONCLUSION

EHR audit logs have potential to scale observational research but the complexity of audit log measures necessitates greater methodological transparency and validated standards.

Health Outcomes and Healthcare Efficiencies Associated with the Use of Electronic Health Records in Hospital Emergency Departments: a Systematic Review

Healthcare organisations and governments have invested heavily in electronic health records in anticipation that they will deliver improved health outcomes for consumers and efficiencies across emergency departments. Despite such investment, electronic health records designed to support emergency care have been poorly evaluated. Given the accelerated development and adoption of information technology across healthcare, it is timely that a systematic review of this evidence base is updated in order to drive improvements to design, interoperability and overall clinical utility of electronic health record systems implemented in emergency departments. To assess the impact of electronic health records on healthcare outcomes and efficiencies in the emergency department we carried out a systematic review of published studies on this topic. This is the first review to summarise the cost efficiencies associated with electronic health record use outside of just the United States of America. A systematic search was performed in three scientific databases (MEDLINE, EMcare and EMBASE), of literature published between January 2000 and September 2019. Studies were included in this review if they evaluated electronic health records or health information exchanges (and synonyms for these terms), reported patient outcome and/or healthcare efficiency benefits, were peer-reviewed and published in English. Out of 6635 articles, 23 studies met our inclusion criteria. Wide variation regarding electronic health record access in the emergency department was reported (1.46-56.6%), yet was most frequently reported as less than 20%. Seven different types of health outcomes and three different types of efficiency improvements associated with electronic health record use in the emergency department were identified. The most frequently reported findings were efficiencies, including reductions in diagnostic tests, imaging and costs. This review is the first to report moderate to significant increases in admission rates are associated with electronic health record use in the emergency department, contrasting the findings of previous reviews. Diversity in the methodology employed across the included studies emphasises the need for further research to examine the impact of electronic health record implementation and system design on the findings reported, in order to ensure return on investment for stakeholders and optimised consumer care.

Elucidating system-level interdependence in electronic health record data: What are the ramifications for trainee assessment?

CONTEXT

The electronic health record (EHR) has been identified as a potential site for gathering data about trainees' clinical performance, but these data are not collected or organised for this purpose. Therefore, a careful and rigorous approach is required to explore how EHR data could be meaningfully used for assessment purposes. The purpose of this study was to identify EHR performance metrics that represent both the independent and interdependent clinical performance of emergency medicine (EM) trainees and explore how they might be meaningfully used for assessment and feedback.

METHODS

Using constructivist grounded theory, we conducted 21 semi-structured interviews with EM faculty members and residents. Participants were asked to identify the clinical actions of trainees that would be valuable for assessment and feedback and describe how those activities are represented in the EHR. Data collection and analysis, which consisted of three stages of coding, occurred iteratively.

RESULTS

When faculty members and trainees in EM were asked to reflect on the usefulness of using EHR performance metrics for resident assessment and feedback they expressed both widespread support for the idea in principle and hesitation that aspects of clinical performance captured in the data would not be representative of residents' individual performance, but would rather reflect their interdependence with other team members and the systems in which they work. We highlight three categorisations of system-level interdependence - medical directives, technological systems and organisational systems - identified by our participants, and discuss strategies participants employed to navigate these forms of interdependence within the health care system.

CONCLUSIONS

System-level interdependence shapes physicians' performances, and yet, this impact is rarely corrected for or noted within clinical performance data. Educators have a responsibility to recognise system-level interdependence when teaching and consider system-level interdependence when assessing the performance of trainees in order to most effectively and fairly utilise the EHR as a source of assessment data.

Usage of query-based health information exchange after event notifications

Objectives

This study sought to quantify the association between event notifications and subsequent query-based health information exchange (HIE) use among end users of three different community health information organizations.

Materials and Methods

Using system-log data merged with user characteristics, regression-adjusted estimates were used to describe the association between event notifications and subsequent query-based HIE usage.

Results

Approximately 5% of event notifications were associated with query-based HIE usage within 30 days. In adjusted models, odds of query-based HIE usage following an event notification were higher for older patients and for alerts triggered by a discharge event. Query-based HIE usage was more common among specialty clinics and Federally Qualified Health Centers than primary care organizations.

Discussion and Conclusion

In this novel combination of data, 1 in 20 event notifications resulted in subsequent query-based HIE usage. Results from this study suggest that event notifications and query-based HIE can be applied together to address clinical and population health use cases.

How Does Electronic Health Information Exchange Affect Hospital Performance Efficiency? The Effects of Breadth and Depth of Information Sharing

EXECUTIVE SUMMARY

This research was motivated by the large investment in health information technology (IT) by hospitals and the inconsistent findings related to the effects of health IT adoption on hospital performance. Building on resource orchestration theory and the information systems literature, the authors developed a research model to investigate how the configuration strategies for sharing information under health IT systems affect hospital efficiency. The hypotheses were tested using data from the 2010 annual and IT surveys of the American Hospital Association, Centers for Medicare & Medicaid Services case mix index, and U.S. Census Bureau's small-area income and poverty estimates. The study revealed that in health IT systems, the breadth (extent) and depth (level of detail) of digital information sharing among stakeholders each has a curvilinear relationship with hospital efficiency. In addition, breadth and depth reinforce each other's positive effects and attenuate each other's negative effects, and their balance has a positive effect on hospital efficiency. The results of this research have the potential to enrich the literature on the value of adopting health IT systems as well as in providing practitioner guidelines for meaningful use.

Strategies to Reduce Hospital Readmission Rates in a Non-Medicaid-Expansion State

On October 1, 2012, as part of the Affordable Care Act, the Centers for Medicare and Medicaid Services began to reduce payments to hospitals with excessive rehospitalization rates through the Hospital Readmissions Reduction Program. These financial penalties have intensified hospital leaders' efforts to implement strategies to reduce readmission rates. The purpose of this multiple case study was to explore organizational strategies that leaders use to reduce readmission rates in hospitals located in a non-Medicaid-expansion state. The data collection included semistructured interviews with 15 hospital leaders located in five metropolitan and rural hospitals in southwest Missouri. Consistent with prior research, the use of predictive analytics stratified by patient population was acknowledged as a key strategy to help reduce avoidable rehospitalization. Study findings suggest that leveraging data from the electronic health records to identify at-risk patients provides comprehensive health information to reduce readmissions. Hospital leaders also revealed the need to understand and address the health needs of their local population, including social determinants such as lack of access to transportation as well as food and housing.

The associations between query-based and directed health information exchange with potentially avoidable use of health care services

OBJECTIVE

To quantify the impact of two approaches (directed and query-based) to health information exchange (HIE) on potentially avoidable use of health care services.

DATA SOURCES/STUDY SETTING

Data on ambulatory care providers' adoption of HIE were merged with Medicare fee-for-service claims from 2008 to 2014. Providers were from 13 counties in New York served by the Rochester Regional Health Information Organization (RHIO).

STUDY DESIGN

Linear regression models with provider and year fixed effects were used to estimate changes in the probability of utilization outcomes for Medicare beneficiaries attributed to providers adopting directed and/or query-based HIE compared with beneficiaries attributed to providers who had not adopted HIE.

DATA COLLECTION

Providers' HIE adoption status was determined through Rochester RHIO registration records. RHIO and claims data were linked via National Provider Identifiers.

PRINCIPAL FINDINGS

Query-based HIE adoption was associated with a 0.2 percentage point reduction in the probability of an ambulatory care sensitive hospitalization and a 1.1 percentage point decrease in the likelihood of an unplanned readmission. Directed HIE adoption was not associated with any outcome.

CONCLUSIONS

The Centers for Medicare & Medicaid Services' (CMS) EHR certification criteria includes requirements for directed HIE, but not query-based HIE. Pending further research, certification criteria should place equal weight on facilitating query-based and directed exchange.

Analysing repeated hospital readmissions using data mining techniques

Few studies have examined how to identify future readmission of patients with a large number of repeat emergency department (ED) visits. We explore 30-day readmission risk prediction using Microsoft's AZURE machine learning software and compare five classification methods: Logistic Regression, Boosted Decision Trees (BDTs), Support Vector Machine (SVM), Bayes Point Machine (BPM), and Two-Class Neural Network (TCNN). We predict the last readmission visit of frequent ED patients extracted from the electronic health records of their 8455 penultimate visits. The methods show differential improvement, with the BDT indicating marginally better AUC (area under the ROC curve) than logistic regression and BPM, followed by the TCNN and SVM. A comparison of BDT and Logistic Regression results for correct and incorrect classification highlights the similarities and differences in the significant predictors identified by each method. Future research may incorporate time-varying covariates to identify other longitudinal factors that can lead to readmission risk reduction.

The impact of health information exchange on healthcare quality and cost-effectiveness: A systematic literature review

BACKGROUND AND OBJECTIVE

Health Information Exchange (HIE) is known as a technology that electronically shares all clinical and administrative data throughout healthcare settings. Despite this technology has a great potential in the healthcare industry, there is a limited and sparse evidence of articles which illustrated the impact of HIE on quality of care and cost-effectiveness. This work presents a systematic review that evaluates the impact of HIE on quality and cost-effectiveness, and the rates of HIE adoption and participation in healthcare organizations.

METHODS

We systematically searched all English papers that were indexed in four major databases (Science Direct, PubMed, IEEE and Web of Science) between 2005 and 2016. Consequently, 32 identified papers appeared in 21 international journals and conferences. Eligible studies independently were critically appraised, collected within data extraction form and then thematically analyzed by two reviewers and if necessary, the third author. The selected papers have been classified based on 11 main categories including publication year, journal and conference names, country and study design, types of data exchanged, healthcare levels, disease or disorder, participants in organizations and individuals, settings characteristics and HIE types, the impact of HIE on quality and cost-effectiveness, and the rates of HIE adoption and participation.

RESULTS

Of the 32 articles, 25 studies investigated the financial and clinical impact of HIE. Overwhelmingly, HIE studies have reported positive findings for quality and cost-effectiveness of care. 15 of HIE studies (60%) demonstrated positive financial effects and 16 studies (64%) reported positive effects on quality improvement of patient care. However, the overall quality of the evidences was low. In this regard, cohort study (59.38%) was the most common used study design. Nine studies presented the rates of HIE adoption and participation. The lowest and highest participation rates were 15.7% and 79%, respectively.

CONCLUSIONS

HIE can be considered as a superior potential for healthcare information system, resulting to promote patient care quality and reduce costs related to resource utilization. However, further researches are needed in order to provide a better understanding of this domain and accordingly attain new opportunities to increase users' participation and motivation for successfully adopting this technology.

Predictive modeling in urgent care: a comparative study of machine learning approaches

OBJECTIVE

The growing availability of rich clinical data such as patients' electronic health records provide great opportunities to address a broad range of real-world questions in medicine. At the same time, artificial intelligence and machine learning (ML)-based approaches have shown great premise on extracting insights from those data and helping with various clinical problems. The goal of this study is to conduct a systematic comparative study of different ML algorithms for several predictive modeling problems in urgent care.

DESIGN

We assess the performance of 4 benchmark prediction tasks (eg mortality and prediction, differential diagnostics, and disease marker discovery) using medical histories, physiological time-series, and demographics data from the Medical Information Mart for Intensive Care (MIMIC-III) database.

MEASUREMENTS

For each given task, performance was estimated using standard measures including the area under the receiver operating characteristic (AUC) curve, F-1 score, sensitivity, and specificity. Microaveraged AUC was used for multiclass classification models.

RESULTS AND DISCUSSION

Our results suggest that recurrent neural networks show the most promise in mortality prediction where temporal patterns in physiologic features alone can capture in-hospital mortality risk (AUC > 0.90). Temporal models did not provide additional benefit compared to deep models in differential diagnostics. When comparing the training-testing behaviors of readmission and mortality models, we illustrate that readmission risk may be independent of patient stability at discharge. We also introduce a multiclass prediction scheme for length of stay which preserves sensitivity and AUC with outliers of increasing duration despite decrease in sample size.

Can a collaborative healthcare network improve the care of people with epilepsy?

New opportunities are now available to improve care in ways not possible previously. Information contained in electronic medical records can now be shared without identifying patients. With network collaboration, large numbers of medical records can be searched to identify patients most like the one whose complex medical situation challenges the physician. The clinical effectiveness of different treatment strategies can be assessed rapidly to help the clinician decide on the best treatment for this patient. Other capabilities from different components of the network can prompt the recognition of what is the best available option and encourage the sharing of information about programs and electronic tools. Difficulties related to privacy, harmonization, integration, and costs are expected, but these are currently being addressed successfully by groups of organizations led by those who recognize the benefits.

Health Information Technology Continues to Show Positive Effect on Medical Outcomes: Systematic Review

Background

Health information technology (HIT) has been introduced into the health care industry since the 1960s when mainframes assisted with financial transactions, but questions remained about HIT’s contribution to medical outcomes. Several systematic reviews since the 1990s have focused on this relationship. This review updates the literature.

Objective

The purpose of this review was to analyze the current literature for the impact of HIT on medical outcomes. We hypothesized that there is a positive association between the adoption of HIT and medical outcomes.

Methods

We queried the Cumulative Index of Nursing and Allied Health Literature (CINAHL) and Medical Literature Analysis and Retrieval System Online (MEDLINE) by PubMed databases for peer-reviewed publications in the last 5 years that defined an HIT intervention and an effect on medical outcomes in terms of efficiency or effectiveness. We structured the review from the Primary Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), and we conducted the review in accordance with the Assessment for Multiple Systematic Reviews (AMSTAR).

Results

We narrowed our search from 3636 papers to 37 for final analysis. At least one improved medical outcome as a result of HIT adoption was identified in 81% (25/37) of research studies that met inclusion criteria, thus strongly supporting our hypothesis. No statistical difference in outcomes was identified as a result of HIT in 19% of included studies. Twelve categories of HIT and three categories of outcomes occurred 38 and 65 times, respectively.

Conclusions

A strong majority of the literature shows positive effects of HIT on the effectiveness of medical outcomes, which positively supports efforts that prepare for stage 3 of meaningful use. This aligns with previous reviews in other time frames.

Analysing repeated hospital readmissions using data mining techniques

Few studies have examined how to identify future readmission of patients with a large number of repeat emergency department (ED) visits. We explore 30-day readmission risk prediction using Microsoft's AZURE machine learning software and compare five classification methods: Logistic Regression, Boosted Decision Trees (BDTs), Support Vector Machine (SVM), Bayes Point Machine (BPM), and Two-Class Neural Network (TCNN). We predict the last readmission visit of frequent ED patients extracted from the electronic health records of their 8455 penultimate visits. The methods show differential improvement, with the BDT indicating marginally better AUC (area under the ROC curve) than logistic regression and BPM, followed by the TCNN and SVM. A comparison of BDT and Logistic Regression results for correct and incorrect classification highlights the similarities and differences in the significant predictors identified by each method. Future research may incorporate time-varying covariates to identify other longitudinal factors that can lead to readmission risk reduction.

The role and benefits of accessing primary care patient records during unscheduled care: a systematic review

Background

The purpose of this study was to assess the impact of accessing primary care records on unscheduled care. Unscheduled care is typically delivered in hospital Emergency Departments. Studies published to December 2014 reporting on primary care record access during unscheduled care were retrieved.

Results

Twenty-two articles met inclusion criteria from a pool of 192. Many shared electronic health records (SEHRs) were large in scale, servicing many millions of patients. Reported utilization rates by clinicians was variable, with rates >20% amongst health management organizations but much lower in nation-scale systems. No study reported on clinical outcomes or patient safety, and no economic studies of SEHR access during unscheduled care were available. Design factors that may affect utilization included consent and access models, SEHR content, and system usability and reliability.

Conclusions

Despite their size and expense, SEHRs designed to support unscheduled care have been poorly evaluated, and it is not possible to draw conclusions about any likely benefits associated with their use. Heterogeneity across the systems and the populations they serve make generalization about system design or performance difficult. None of the reviewed studies used a theoretical model to guide evaluation. Value of Information models may be a useful theoretical approach to design evaluation metrics, facilitating comparison across systems in future studies. Well-designed SEHRs should in principle be capable of improving the efficiency, quality and safety of unscheduled care, but at present the evidence for such benefits is weak, largely because it has not been sought.

Between "the best way to deliver patient care" and "chaos and low clinical value": General Practitioners' and Practice Managers' views on data sharing

OBJECTIVE

In the UK, General Practitioners and Practice Managers are key to enabling health information exchange (typically referred to as 'data sharing'). This study aimed to survey GPs and PMs for familiarity, engagement with and perceptions of patient data sharing.

METHODS

Cross-sectional survey. All 107 general practices in England's second largest Clinical Commissioning Group, Cambridgeshire & Peterborough CCG. Descriptive statistics; hierarchical logistic regression; thematic analysis.

RESULTS

405 (64%) responses were received - from 338 (62%) GPs and 67 (71%) PMs. Familiarity and engagement were highest for local frail elderly and end of life care projects (>76% had used). The greatest difference in use concerned the now suspended national care.data initiative: PMs had odds of reporting use 75 times higher than GP partners (95% CI 27-211). Patient confusion was the most pronounced challenge and improved coordination the most pronounced expected benefit. Frequency of discussions with patients varied with IT competence (OR 4.2 for most competent users relative to least, 95% CI 1.7-10.7) and clinical system (OR 0.3, 95% CI 0.1-0.5). Patient reservations were reported more frequently by respondents who rated their IT competence as highest (OR 3.3, 95% CI 1.5-7.6), perceived more data sharing challenges (OR for a 1-point increase in challenges perception score 3.4, 95% CI 2.1-5.6) and by PMs (relative to GP partners, OR 18.0, 95% CI 7.9-41.3).

CONCLUSIONS

Familiarity with and use of data sharing projects was high among GPs and PMs. Both their individual and organisational characteristics were associated with the reported frequency of discussions and patients' responses. Improved awareness of the impact of provider characteristics and attitudes on patients' decisions about data sharing may enhance the equity and autonomy of those decisions.

The implications and impact of 3 approaches to health information exchange: community, enterprise, and vendor-mediated health information exchange

INTRODUCTION

Electronic health information exchange (HIE) is considered essential to establishing a learning health system, reducing medical errors, and improving efficiency, but establishment of widespread, high functioning HIE has been challenging. Healthcare organizations now have considerable flexibility in selecting among several HIE strategies, most prominently community HIE, enterprise HIE (led by a healthcare organization), and electronic health record vendor-mediated HIE. Each of these strategies is characterized by different conveners, capabilities, and motivations and may have different abilities to facilitate improved patient care.

METHODS

I reviewed the available scholarly literature to draw conceptual distinctions between these types of HIE, to assess the current evidence on each type of HIE, and to indicate important areas of future research.

RESULTS

While community HIE seems to offer the most open approach to HIE allowing for high levels of connectivity, both enterprise HIE and vendor-mediated HIE face lower barriers to formation and sustainability. Most existing evidence is focused on community HIE and points towards low overall use, challenges to usability, and ambiguous impact. To better guide organizational leaders and policymakers in the expansion of beneficial HIE and anticipate future trends, future research should work to better capture the prevalence of other forms of HIE, and to adopt common methods to allow comparisons of rate of use, usability, and impact on patient care across studies and types of HIE.

CONCLUSIONS

Healthcare organizations' choice of HIE strategy influences the set of partners the organization is connected to and may influence the benefit that efforts supported by HIE can offer to patients. Current research is not fully capturing the diversity of approaches to HIE and their potentially varying impact on providers and patients.

When Should ED Physicians Use an HIE? Predicting Presence of Patient Data in an HIE

OBJECTIVES

Health information exchanges (HIEs) make possible the construction of databases to characterize patients as multisystem users (MSUs), those visiting emergency departments (EDs) of more than one hospital system within a region during a 1-year period. HIE data can inform an algorithm highlighting patients for whom information is more likely to be present in the HIE, leading to a higher yield HIE experience for ED clinicians and incentivizing their adoption of HIE. Our objective was to describe patient characteristics that determine which ED patients are likely to be MSUs and therefore have information in an HIE, thereby improving the efficacy of HIE use and increasing ED clinician perception of HIE benefit.

METHODS

Data were extracted from a regional HIE involving four hospital systems (11 EDs) in the Charleston, South Carolina area. We used univariate and multivariable regression analyses to develop a predictive model for MSU status.

RESULTS

Factors associated with MSUs included younger age groups, dual-payer insurance status, living in counties that are more rural, and one of at least six specific diagnoses: mental disorders; symptoms, signs, and ill-defined conditions; complications of pregnancy, childbirth, and puerperium; diseases of the musculoskeletal system; injury and poisoning; and diseases of the blood and blood-forming organs. For patients with multiple ED visits during 1 year, 43.8% of MSUs had ≥4 visits, compared with 18.0% of non-MSUs (P < 0.0001).

CONCLUSIONS

This predictive model accurately identified patients cared for at multiple hospital systems and can be used to increase the likelihood that time spent logging on to the HIE will be a value-added effort for emergency physicians.

Health information exchange systems and length of stay in readmissions to a different hospital

BACKGROUND

Readmission to a different hospital than the original discharge hospital may result in breakdowns in continuity of care. In different-hospital readmissions (DHRs), continuity can be maintained when hospitals are connected through health information exchange (HIE) systems.

OBJECTIVE

To examine whether length of readmission stay (LORS) differs between same-hospital readmissions and DHRs, and whether in DHRs the LORS differs by the availability of HIE.

DESIGN

A retrospective cohort study of all internal medicine 30-day readmissions in 27 Israeli hospitals between January 1, 2010 and December 31, 2010.

SETTING

Clalit Health Services-Israel's largest integrated healthcare provider and payer.

POPULATION

Adult Clalit members (aged 18 and older) with at least 1 readmission during the study period.

METHODS

A multivariate marginal Cox model tested the likelihood for discharge during each readmission day in same-hospital readmissions (SHRs), DHRs with HIE, and DHRs without HIE.

RESULTS

Of the 27,057 readmissions, 3130 (11.6%) were DHRs and 792 where DHRs with HIE in both the index and readmitting hospital. Partial continuity (DHRs with HIE) was associated with decreased likelihood of discharge on any given day compared with full continuity (SHRs) (hazard ratio [HR] = 0.85, 95% confidence interval [CI]: 0.79-0.91). Similar results were obtained for no continuity (DHRs without HIE) versus full continuity (HR = 0.90, 95% CI: 0.86-0.94). The difference between DHRs with and without HIE was not significant.

CONCLUSIONS

The prolonged LORS in DHRs versus SHRs was not mitigated by the existence of HIE systems. Future research is needed to further elucidate the effects of actual use of HIE on length of DHRs. Journal of Hospital Medicine 2016;11:401-406. © 2015 Society of Hospital Medicine.

Health information exchange and information gaps in referrals to a pediatric emergency department

OBJECTIVE

to assess the extent of information gaps between three information sources available at admission to a pediatric Emergency Department (ED): Health Information Exchange (HIE) system, physicians' referral letters and information collected from patients/parents at admission to the ED (patient's medical history).

MATERIALS AND METHODS

A retrospective cohort study of 170 medical records of children aged 6 months to 18 years referred to a pediatric ED for a common childhood disease. Each record was reviewed for information on lab and imaging tests, vaccinations, allergies, previous diagnoses, recent and chronic medical treatment in the HIE system and referral letter, or from the patient's medical history taken on admission to the ED. The percent overlap between information sources and information gaps was assessed.

RESULTS

The most informative source, in terms of addressing all key areas, was the patient's medical history, with an average of 73.5% indication of each information key area. Next was the HIE system, with 54.1% indication of each key area; the least informative was the referral letter (43.9%). The overall overlap in data availability among all information sources occurred on average in 23% of the cases. HIE's ability to provide data missing from other routinely available sources was mainly in the area of chronic medication dosages (37% of cases).

CONCLUSIONS

Each of the three major information sources available at admission to a pediatric ED lack important data and each makes its own unique contribution. Improving documentation in electronic health records, on which HIE systems feed from can narrow significant information gaps at the most critical time-point-admission to a pediatric ED.

Outcomes From Health Information Exchange: Systematic Review and Future Research Needs

BACKGROUND

Health information exchange (HIE), the electronic sharing of clinical information across the boundaries of health care organizations, has been promoted to improve the efficiency, cost-effectiveness, quality, and safety of health care delivery.

OBJECTIVE

To systematically review the available research on HIE outcomes and analyze future research needs.

METHODS

Data sources included citations from selected databases from January 1990 to February 2015. We included English-language studies of HIE in clinical or public health settings in any country. Data were extracted using dual review with adjudication of disagreements.

RESULTS

We identified 34 studies on outcomes of HIE. No studies reported on clinical outcomes (eg, mortality and morbidity) or identified harms. Low-quality evidence generally finds that HIE reduces duplicative laboratory and radiology testing, emergency department costs, hospital admissions (less so for readmissions), and improves public health reporting, ambulatory quality of care, and disability claims processing. Most clinicians attributed positive changes in care coordination, communication, and knowledge about patients to HIE.

CONCLUSIONS

Although the evidence supports benefits of HIE in reducing the use of specific resources and improving the quality of care, the full impact of HIE on clinical outcomes and potential harms are inadequately studied. Future studies must address comprehensive questions, use more rigorous designs, and employ a standard for describing types of HIE.

TRIAL REGISTRATION

PROSPERO Registry No CRD42014013285; http://www.crd.york.ac.uk/PROSPERO/ display_record.asp?ID=CRD42014013285 (Archived by WebCite at http://www.webcitation.org/6dZhqDM8t).

Assessing electronic health record systems in emergency departments: Using a decision analytic Bayesian model

In the last decade, health providers have implemented information systems to improve accuracy in medical diagnosis and decision-making. This article evaluates the impact of an electronic health record on emergency department physicians' diagnosis and admission decisions. A decision analytic approach using a decision tree was constructed to model the admission decision process to assess the added value of medical information retrieved from the electronic health record. Using a Bayesian statistical model, this method was evaluated on two coronary artery disease scenarios. The results show that the cases of coronary artery disease were better diagnosed when the electronic health record was consulted and led to more informed admission decisions. Furthermore, the value of medical information required for a specific admission decision in emergency departments could be quantified. The findings support the notion that physicians and patient healthcare can benefit from implementing electronic health record systems in emergency departments.

Achieving regionalization through rural interhospital transfer

Regionalization of emergency medical care aims to provide consistent and efficient high-quality care leading to optimal clinical outcomes by matching patient needs with appropriate resources at a network of hospitals. Regionalized care has been shown to improve outcomes in trauma, myocardial infarction, stroke, cardiac arrest, and acute respiratory distress syndrome. In rural areas, effective regionalization often requires interhospital transfer. The decision to transfer is complex and includes such factors as capabilities of the presenting hospital; capacity at the receiving hospital; and financial, geographic, and patient-preference considerations. Although transfer to a comprehensive center has proven benefits for some conditions, the transfer process is not without risk. These risks include clinical deterioration, limited resource availability during transport, vehicular crashes, time delays for time-sensitive care, poor communication between providers, and neglect of patient preferences. This article reviews the transfer decision, financial implications, risks, and considerations for patients undergoing rural interhospital transfer. We identify several strategies that should be considered for development of the regionalized emergency health care system of the future and identify areas where further research is necessary.

Improving diagnostic accuracy using EHR in emergency departments: A simulation-based study

It is widely believed that Electronic Health Records (EHR) improve medical decision-making by enabling medical staff to access medical information stored in the system. It remains unclear, however, whether EHR indeed fulfills this claim under the severe time constraints of Emergency Departments (EDs). We assessed whether accessing EHR in an ED actually improves decision-making by clinicians. A simulated ED environment was created at the Israel Center for Medical Simulation (MSR). Four different actors were trained to simulate four specific complaints and behavior and 'consulted' 26 volunteer ED physicians. Each physician treated half of the cases (randomly) with access to EHR, and their medical decisions were compared to those where the physicians had no access to EHR. Comparison of diagnostic accuracy with and without access showed that accessing the EHR led to an increase in the quality of the clinical decisions. Physicians accessing EHR were more highly informed and thus made more accurate decisions. The percentage of correct diagnoses was higher and these physicians were more confident in their diagnoses and made their decisions faster.

The visit-data warehouse: enabling novel secondary use of health information exchange data

INTRODUCTION/OBJECTIVES

Health Information Exchange (HIE) efforts face challenges with data quality and performance, and this becomes especially problematic when data is leveraged for uses beyond primary clinical use. We describe a secondary data infrastructure focusing on patient-encounter, nonclinical data that was built on top of a functioning HIE platform to support novel secondary data uses and prevent potentially negative impacts these uses might have otherwise had on HIE system performance.

BACKGROUND

HIE efforts have generally formed for the primary clinical use of individual clinical providers searching for data on individual patients under their care, but many secondary uses have been proposed and are being piloted to support care management, quality improvement, and public health.

DESCRIPTION OF THE HIE AND BASE INFRASTRUCTURE

This infrastructure review describes a module built into the Healthix HIE. Healthix, based in the New York metropolitan region, comprises 107 participating organizations with 29,946 acute-care beds in 383 facilities, and includes more than 9.2 million unique patients. The primary infrastructure is based on the InterSystems proprietary Caché data model distributed across servers in multiple locations, and uses a master patient index to link individual patients' records across multiple sites. We built a parallel platform, the "visit data warehouse," of patient encounter data (demographics, date, time, and type of visit) using a relational database model to allow accessibility using standard database tools and flexibility for developing secondary data use cases. These four secondary use cases include the following: (1) tracking encounter-based metrics in a newly established geriatric emergency department (ED), (2) creating a dashboard to provide a visual display as well as a tabular output of near-real-time de-identified encounter data from the data warehouse, (3) tracking frequent ED users as part of a regional-approach to case management intervention, and (4) improving an existing quality improvement program that analyzes patients with return visits to EDs within 72 hours of discharge.

RESULTS/LESSONS LEARNED

Setting up a separate, near-real-time, encounters-based relational database to complement an HIE built on a hierarchical database is feasible, and may be necessary to support many secondary uses of HIE data. As of November 2014, the visit-data warehouse (VDW) built by Healthix is undergoing technical validation testing and updates on an hourly basis. We had to address data integrity issues with both nonstandard and missing HL7 messages because of varied HL7 implementation across the HIE. Also, given our HIEs federated structure, some sites expressed concerns regarding data centralization for the VDW. An established and stable HIE governance structure was critical in overcoming this initial reluctance.

CONCLUSIONS

As secondary use of HIE data becomes more prevalent, it may be increasingly necessary to build separate infrastructure to support secondary use without compromising performance. More research is needed to determine optimal ways of building such infrastructure and validating its use for secondary purposes.

Electronic health records, adoption, quality of care, legal and privacy issues and their implementation in emergency departments

Recently, the healthcare sector has shown a growing interest in information technologies. Two popular health IT (HIT) products are the electronic health record (EHR) and health information exchange (HIE) networks. The introduction of these tools is believed to improve care, but has also raised some important questions and legal and privacy issues. The implementation of these systems has not gone smoothly, and still faces some considerable barriers. This article reviews EHR and HIE to address these obstacles, and analyzes the current state of development and adoption in various countries around the world. Moreover, legal and ethical concerns that may be encountered by EHR users and purchasers are reviewed. Finally, links and interrelations between EHR and HIE and several quality of care issues in today's healthcare domain are examined with a focus on EHR and HIE in the emergency department (ED), whose unique characteristics makes it an environment in which the implementation of such technology may be a major contributor to health, but also faces substantial challenges. The paper ends with a discussion of specific policy implications and recommendations based on an examination of the current limitations of these systems.

Is the readmission rate a valid quality indicator? A review of the evidence

INTRODUCTION

Hospital readmission rates are increasingly used for both quality improvement and cost control. However, the validity of readmission rates as a measure of quality of hospital care is not evident. We aimed to give an overview of the different methodological aspects in the definition and measurement of readmission rates that need to be considered when interpreting readmission rates as a reflection of quality of care.

METHODS

We conducted a systematic literature review, using the bibliographic databases Embase, Medline OvidSP, Web-of-Science, Cochrane central and PubMed for the period of January 2001 to May 2013.

RESULTS

The search resulted in 102 included papers. We found that definition of the context in which readmissions are used as a quality indicator is crucial. This context includes the patient group and the specific aspects of care of which the quality is aimed to be assessed. Methodological flaws like unreliable data and insufficient case-mix correction may confound the comparison of readmission rates between hospitals. Another problem occurs when the basic distinction between planned and unplanned readmissions cannot be made. Finally, the multi-faceted nature of quality of care and the correlation between readmissions and other outcomes limit the indicator's validity.

CONCLUSIONS

Although readmission rates are a promising quality indicator, several methodological concerns identified in this study need to be addressed, especially when the indicator is intended for accountability or pay for performance. We recommend investing resources in accurate data registration, improved indicator description, and bundling outcome measures to provide a more complete picture of hospital care.

Barriers over time to full implementation of health information exchange in the United States

BACKGROUND

Although health information exchanges (HIE) have existed since their introduction by President Bush in his 2004 State of the Union Address, and despite monetary incentives earmarked in 2009 by the health information technology for economic and clinical health (HITECH) Act, adoption of HIE has been sparse in the United States. Research has been conducted to explore the concept of HIE and its benefit to patients, but viable business plans for their existence are rare, and so far, no research has been conducted on the dynamic nature of barriers over time.

OBJECTIVE

The aim of this study is to map the barriers mentioned in the literature to illustrate the effect, if any, of barriers discussed with respect to the HITECH Act from 2009 to the early months of 2014.

METHODS

We conducted a systematic literature review from CINAHL, PubMed, and Google Scholar. The search criteria primarily focused on studies. Each article was read by at least two of the authors, and a final set was established for evaluation (n=28).

RESULTS

The 28 articles identified 16 barriers. Cost and efficiency/workflow were identified 15% and 13% of all instances of barriers mentioned in literature, respectively. The years 2010 and 2011 were the most plentiful years when barriers were discussed, with 75% and 69% of all barriers listed, respectively.

CONCLUSIONS

The frequency of barriers mentioned in literature demonstrates the mindfulness of users, developers, and both local and national government. The broad conclusion is that public policy masks the effects of some barriers, while revealing others. However, a deleterious effect can be inferred when the public funds are exhausted. Public policy will need to lever incentives to overcome many of the barriers such as cost and impediments to competition. Process improvement managers need to optimize the efficiency of current practices at the point of care. Developers will need to work with users to ensure tools that use HIE resources work into existing workflows.

Impact of a health information exchange on resource use and Medicare-allowable reimbursements at 11 emergency departments in a midsized city

INTRODUCTION

Use clinician perceptions to estimate the impact of a health information exchange (HIE) on emergency department (ED) care at four major hospital systems (HS) within a region. Use survey data provided by ED clinicians to estimate reduction in Medicare-allowable reimbursements (MARs) resulting from use of an HIE.

METHODS

We conducted the study during a one-year period beginning in February 2012. Study sites included eleven EDs operated by four major HS in the region of a mid-sized Southeastern city, including one academic ED, five community hospital EDs, four free-standing EDs and 1 ED/Chest Pain Center (CPC) all of which participated in an HIE. The study design was observational, prospective using a voluntary, anonymous, online survey. Eligible participants included attending emergency physicians, residents, and mid-level providers (PA & NP). Survey items asked clinicians whether information obtained from the HIE changed resource use while caring for patients at the study sites and used branching logic to ascertain specific types of services avoided including laboratory/microbiology, radiology, consultations, and hospital admissions. Additional items asked how use of the HIE affected quality of care and length of stay. The survey was automated using a survey construction tool (REDCap Survey Software © 2010 Vanderbilt University). We calculated avoided MARs by multiplying the numbers and types of services reported to have been avoided. Average cost of an admission from the ED was based on direct cost trends for ED admissions within the region.

RESULTS

During the 12-month study period we had 325,740 patient encounters and 7,525 logons to the HIE (utilization rate of 2.3%) by 231 ED clinicians practicing at the study sites. We collected 621 surveys representing 8.25% of logons of which 532 (85.7% of surveys) reported on patients who had information available in the HIE. Within this group the following services and MARs were reported to have been avoided [type of service: number of services; MARs]: Laboratory/Microbiology:187; $2,073, Radiology: 298; $475,840, Consultations: 61; $6,461, Hospital Admissions: 56; $551,282. Grand total of MARs avoided: $1,035,654; average $1,947 per patient who had information available in the HIE (Range: $1,491 - $2,395 between HS). Changes in management other than avoidance of a service were reported by 32.2% of participants. Participants stated that quality of care was improved for 89% of patients with information in the HIE. Eighty-two percent of participants reported that valuable time was saved with a mean time saved of 105 minutes.

CONCLUSION

Observational data provided by ED clinicians practicing at eleven EDs in a mid-sized Southeastern city showed an average reduction in MARs of $1,947 per patient who had information available in an HIE. The majority of reduced MARs were due to avoided radiology studies and hospital admissions. Over 80% of participants reported that quality of care was improved and valuable time was saved.

Enhancing a geriatric emergency department care coordination intervention using automated health information exchange-based clinical event notifications

Purpose:

In a health care system where patients often have numerous providers and multiple chronic medical conditions, interoperability of health information technology (HIT) is of paramount importance. Regional health information organizations (RHIO) often provide a health information exchange (HIE) as a solution, which gives stakeholders access to clinical data that they otherwise would not otherwise have. A secondary use of preexisting HIE infrastructure is clinical event notification (CEN) services, which send automated notifications to stakeholders. This paper describes the development and implementation of a CEN service enabled by a RHIO in the New York metropolitan area to improve care coordination for patients enrolled in a geriatric emergency department care coordination program.

Innovation:

This operational CEN system incorporates several innovations that to our knowledge have not been implemented previously. They include the near real-time notifications and the delivery of notifications via multiple pathways: electronic health record (EHR) “in-baskets,” email, text message to internet protocol-based “zone” phones, and automated encounter entry into the EHR. Based on these alerts the geriatric care coordination team contacts the facility where the patient is being seen and offers additional information or assistance with disposition planning with the goal of decreasing potentially avoidable admissions and duplicate testing.

Findings:

During the nearly one-year study period, the CEN program enrolled 5722 patients and sent 497 unique notifications regarding 206 patients. Of these notifications, 219 (44%) were for emergency department (ED) visits; 121 (55%) of those notifications were received during normal business hours when the care coordination team was available to contact the ED where the patient was receiving care. Hospital admissions resulted from 45% of ED visits 17.8% of these admissions lasted 48 hours or less, suggesting some might potentially be avoidable.

Conclusions and Discussion:

This study demonstrates the potential of CEN systems to improve care coordination by notifying providers of the occurrence of specific events. Although it could not directly be demonstrated here, we believe that widespread use of CEN systems have potential to reduce potentially avoidable admissions and duplicate testing, likely leading to decreased costs.

The potential for community-based health information exchange systems to reduce hospital readmissions

Background Hospital readmissions are common, costly, and offer opportunities for utilization reduction. Electronic health information exchange (HIE) systems may help prevent readmissions by improving access to clinical data by ambulatory providers after discharge from the hospital.

Objective We sought to determine the association between HIE system usage and 30-day same-cause hospital readmissions among patients who consented and participated in an operational community-wide HIE during a 6-month period in 2009–2010.

Methods We identified a retrospective cohort of hospital readmissions among adult patients in the Rochester, New York area. We analyzed claims files from two health plans that insure more than 60% of the area population. To be included in the dataset, patients needed to be continuously enrolled in the health plan with at least one encounter with a participating provider in the 6 months following consent to be included in the HIE system. Each patient appeared in the dataset only once and each discharge could be followed for at least 30 days.

Results We found that accessing patient information in the HIE system in the 30 days after discharge was associated with a 57% lower adjusted odds of readmission (OR 0.43; 95% CI 0.27 to 0.70). The estimated annual savings in the sample from averted readmissions associated with HIE usage was $605 000.

Conclusions These findings indicate that usage of an electronic HIE system in the ambulatory setting within 30 days after hospital discharge may effectively prevent hospital readmissions, thereby supporting the need for ongoing HIE efforts.

Using electronic health record systems to optimize admission decisions: the Creatinine case study

Many medical organizations have implemented electronic health record (EHR) and health information exchange (HIE) networks to improve medical decision-making. This study evaluated the contribution of EHR and HIE networks to physicians by investigating whether health information technology can lead to more efficient admission decisions by reducing redundant admissions in the stressful environment of emergency. Log-files were retrieved from an integrative and interoperable EHR that serves seven main Israeli hospitals. The analysis was restricted to a group of patients seen in the emergency departments who were administered a Creatinine test. The assessment of the contribution of EHR to admission decisions used various statistical analyses and track log-file analysis. We showed that using the EHR contributes to more efficient admission decisions and reduces the number of avoidable admissions. In particular, there was a reduction in readmissions when patient history was viewed. Using EHR can help respond to the international problem of avoidable hospital readmissions.

EHR in emergency rooms: exploring the effect of key information components on main complaints

This study characterizes the information components associated with improved medical decision-making in the emergency room (ER). We looked at doctors' decisions to use or not to use information available to them on an electronic health record (EHR) and a Health Information Exchange (HIE) network, and tested for associations between their decision and parameters related to healthcare outcomes and processes. Using information components from the EHR and HIE was significantly related to improved quality of healthcare processes. Specifically, it was associated with both a reduction in potentially avoidable admissions as well as a reduction in rapid readmissions. Overall, the three information components; namely, previous encounters, imaging, and lab results emerged as having the strongest relationship with physicians' decisions to admit or discharge. Certain information components, however, presented an association between the diagnosis and the admission decisions (blood pressure was the most strongly associated parameter in cases of chest pain complaints and a previous surgical record for abdominal pain). These findings show that the ability to access patients' medical history and their long term health conditions (via the EHR), including information about medications, diagnoses, recent procedures and laboratory tests is critical to forming an appropriate plan of care and eventually making more accurate admission decisions.

Association between use of a health information exchange system and hospital admissions

OBJECTIVE

Relevant patient information is frequently difficult to obtain in emergency department (ED) visits. Improved provider access to previously inaccessible patient information may improve the quality of care and reduce hospital admissions. Health information exchange (HIE) systems enable access to longitudinal, community-wide patient information at the point of care. However, the ability of HIE to avert admissions is not well demonstrated. We sought to determine if HIE system usage is correlated with a reduction in admissions via the ED.

METHODS

We identified 15,645 adults from New York State with an ED visit during a 6-month period, all of whom consented to have their information accessible in the HIE system, and were continuously enrolled in two area health plans. Using claims we determined if the ED encounter resulted in an admission. We used the HIE's system log files to determine usage during the encounter. We determined the association between HIE system use and the likelihood of admission to the hospital from the ED and potential cost savings.

RESULTS

The HIE system was accessed during 2.4% of encounters. The odds of an admission were 30% lower when the system was accessed after controlling for confounding (odds ratio = 0.70; 95%C I= 0.52, 0.95). The annual savings in the sample was $357,000.

CONCLUSION

These findings suggest that the use of an HIE system may reduce hospitalizations from the ED with resultant cost savings. This is an important outcome given the substantial financial investment in interventions designed to improve provider access to patient information in the US.