Using Electronic Medical Record Systems for Admission Decisions in Emergency Departments: Examining the Crowdedness Effect

Incidence of moral hazards among health care providers in the implementation of social health insurance toward universal health coverage: evidence from rural province hospitals in Indonesia

Objective

To identify the incidence of moral hazards among health care providers and its determinant factors in the implementation of national health insurance in Indonesia.

Methods

Data were derived from 360 inpatient medical records from six types C public and private hospitals in an Indonesian rural province. These data were accumulated from inpatient medical records from four major disciplines: medicine, surgery, obstetrics and gynecology, and pediatrics. The dependent variable was provider moral hazards, which included indicators of up-coding, readmission, and unnecessary admission. The independent variables are Physicians' characteristics (age, gender, and specialization), coders' characteristics (age, gender, education level, number of training, and length of service), and patients' characteristics (age, birth weight, length of stay, the discharge status, and the severity of patient's illness). We use logistic regression to investigate the determinants of moral hazard.

Results

We found that the incidences of possible unnecessary admissions, up-coding, and readmissions were 17.8%, 11.9%, and 2.8%, respectively. Senior physicians, medical specialists, coders with shorter lengths of service, and patients with longer lengths of stay had a significant relationship with the incidence of moral hazard.

Conclusion

Unnecessary admission is the most common form of a provider's moral hazard. The characteristics of physicians and coders significantly contribute to the incidence of moral hazard. Hospitals should implement reward and punishment systems for doctors and coders in order to control moral hazards among the providers.

Epidemiological challenges in pandemic coronavirus disease (COVID-19): Role of artificial intelligence

World is now experiencing a major health calamity due to the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus clade 2. The foremost challenge facing the scientific community is to explore the growth and transmission capability of the virus. Use of artificial intelligence (AI), such as deep learning, in (i) rapid disease detection from x-ray or computed tomography (CT) or high-resolution CT (HRCT) images, (ii) accurate prediction of the epidemic patterns and their saturation throughout the globe, (iii) forecasting the disease and psychological impact on the population from social networking data, and (iv) prediction of drug-protein interactions for repurposing the drugs, has attracted much attention. In the present study, we describe the role of various AI-based technologies for rapid and efficient detection from CT images complementing quantitative real-time polymerase chain reaction and immunodiagnostic assays. AI-based technologies to anticipate the current pandemic pattern, prevent the spread of disease, and face mask detection are also discussed. We inspect how the virus transmits depending on different factors. We investigate the deep learning technique to assess the affinity of the most probable drugs to treat COVID-19. This article is categorized under:Application Areas > Health CareAlgorithmic Development > Biological Data MiningTechnologies > Machine Learning.

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.

Physicians' and pharmacists' use of My Health Record in the emergency department: results from a mixed-methods study

Purpose

This study aimed to explore pharmacists' and physicians' perceptions of use, barriers to use and the healthcare outcomes associated with use of Australia's national personally controlled electronic health record-known as My Health Record-in the emergency department.

Methods

A mixed methods approach was deployed, including surveys and individual semi-structured interviews. All physicians and pharmacists who work in the emergency department at Cabrini Health (a non-for-profit healthcare provider in Victoria, Australia) were invited to participate. Due to the timing of elective blocks, physician trainees were excluded from interviews.

Results

A total of 40 emergency medicine clinicians responded to the survey. Over 50% (n = 22) of all respondents had used My Health Record in the emergency department at least once. A total of 18 clinicians participated in the semi-structured interviews, which led to the identification of three themes with multiple sub-themes regarding My Health Record: (1) benefits; (2) effectiveness; and; (3) barriers.

Conclusion

Participants reported My Health Record use in the emergency department delivers efficiencies for clinicians and has a heightened utility for complex patients, consistent with previous research conducted outside of the Australian setting. Barriers to use were revealed: outdated content, a lack of trust, a low perception of value, no patient record and multiple medical record systems. The participants in this study highlighted that training and awareness raising is needed in order to improve My Health Record use in the emergency department, a need stressed by physician's. Further observational research is required to explores meaningful MHR use at scale.

Exploring overcrowding trends in an inner city emergence department in the UK before and during COVID-19 epidemic

Background

The COVID-19 pandemic and the associated lockdowns have caused significant disruptions across society, including changes in the number of emergency department (ED) visits. This study aims to investigate the impact of three pre-COVID-19 interventions and of the COVID-19 UK-epidemic and the first UK national lockdown on overcrowding within University College London Hospital Emergency Department (UCLH ED). The three interventions: target the influx of patients at ED (A), reduce the pressure on in-patients’ beds (B) and improve ED processes to improve the flow of patents out from ED (C).

Methods

We collected overcrowding metrics (daily attendances, the proportion of people leaving within 4 h of arrival (four-hours target) and the reduction in overall waiting time) during 01/04/2017–31/05/2020. We then performed three different analyses, considering three different timeframes. The first analysis used data 01/04/2017–31/12–2019 to calculate changes over a period of 6 months before and after the start of interventions A-C. The second and third analyses focused on evaluating the impact of the COVID-19 epidemic, comparing the first 10 months in 2020 and 2019, and of the first national lockdown (23/03/2020–31/05/2020).

Results

Pre-COVID-19 all interventions led to small reductions in waiting time (17%, p < 0.001 for A and C; an 9%, p = 0.322 for B) but also to a small decrease in the number of patients leaving within 4 h of arrival (6.6,7.4,6.2% respectively A-C,p < 0.001).

In presence of the COVID-19 pandemic, attendance and waiting time were reduced (40% and 8%; p < 0.001), and the number of people leaving within 4 h of arrival was increased (6%,p < 0.001). During the first lockdown, there was 65% reduction in attendance, 22% reduction in waiting time and 8% increase in number of people leaving within 4 h of arrival (p < 0.001). Crucially, when the lockdown was lifted, there was an increase (6.5%,p < 0.001) in the percentage of people leaving within 4 h, together with a larger (12.5%,p < 0.001) decrease in waiting time. This occurred despite the increase of 49.6%(p < 0.001) in attendance after lockdown ended.

Conclusions

The mixed results pre-COVID-19 (significant improvements in waiting time with some interventions but not improvement in the four-hours target), may be due to indirect impacts of these interventions, where increasing pressure on one part of the ED system affected other parts. This underlines the need for multifaceted interventions and a system-wide approach to improve the pathway of flow through the ED system is necessary.

During 2020 and in presence of the COVID-19 epidemic, a shift in public behaviour with anxiety over attending hospitals and higher use of virtual consultations, led to notable drop in UCLH ED attendance and consequential curbing of overcrowding.

Importantly, once the lockdown was lifted, although there was an increase in arrivals at UCLH ED, overcrowding metrics were reduced. Thus, the combination of shifted public behaviour and the restructuring changes during COVID-19 epidemic, maybe be able to curb future ED overcrowding, but longer timeframe analysis is required to confirm this.

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.

Characteristics and clinical outcomes of index versus non-index hospital readmissions in Australian hospitals: a cohort study

Objective Risk factors and clinical outcomes of non-index hospital readmissions (readmissions to a hospital different from the previous admission) have not been studied in Australia. The present study compared characteristics and clinical outcomes between index and non-index hospital readmissions in the Australian healthcare setting. Methods This retrospective cohort study included medical admissions from 2012 to 2016 across all major public hospitals in South Australia. Readmissions within 30 day to all public hospitals were captured using electronic health information system. In-hospital mortality and readmission length of hospital stay (LOS) were compared, along with 30-day mortality and subsequent readmissions among patients readmitted to index or non-index hospitals. Results Of 114105 index admissions, there were 20539 (18.0%) readmissions. Of these, 17519 (85.3%) were index readmissions and 3020 (14.7%) were non-index readmissions. Compared with index readmissions, patients in the non-index readmissions group had a lower Charlson comorbidity index, shorter LOS and fewer complications during the index admission and were more likely to be readmitted with a different diagnosis to the index admission. No difference in in-hospital mortality was observed, but readmission LOS was shorter and 30-day mortality was higher among patients with non-index readmissions. Conclusion A substantial proportion of patients experienced non-index hospital readmissions. Non-index hospital readmitted patients had no immediate adverse outcomes, but experienced worse 30-day outcomes. What is known about the topic? A significant proportion of unplanned hospital readmissions occur to non-index hospitals. North American studies suggest that non-index hospital readmissions are associated with worse outcomes for patients due to discontinuity of care, medical reconciliation and delayed treatment. Limited studies have determined factors associated with non-index hospital readmissions in Australia, but whether such readmissions lead to adverse clinical outcomes is unknown. What does this paper add? In the Australian healthcare setting, 14.7% of patients were readmitted to non-index hospitals. Compared with index hospital readmissions, patients admitted to non-index hospitals had a lower Charlson comorbidity index, a shorter index LOS and fewer complications during the index admission. At the time of readmission there was no differences in discharge summary completion rates between the two groups. Unlike other studies, the present study found no immediate adverse outcomes for patients readmitted to non-index hospitals, but 30-day outcomes were worse than for patients who had an index hospital readmission. What are the implications for practitioners? Non-index hospital readmissions may not be totally preventable due to factors such as ambulance diversions stemming from emergency department overcrowding and prolonged emergency department waiting times. Patients should be advised to re-present to hospital in case they experience recurrence or relapse of a medical condition, and preferably should be readmitted to the same hospital to prevent discontinuity of care.

Use of natural language processing to improve predictive models for imaging utilization in children presenting to the emergency department

OBJECTIVE

To examine the association between the medical imaging utilization and information related to patients' socioeconomic, demographic and clinical factors during the patients' ED visits; and to develop predictive models using these associated factors including natural language elements to predict the medical imaging utilization at pediatric ED.

METHODS

Pediatric patients' data from the 2012-2016 United States National Hospital Ambulatory Medical Care Survey was included to build the models to predict the use of imaging in children presenting to the ED. Multivariable logistic regression models were built with structured variables such as temperature, heart rate, age, and unstructured variables such as reason for visit, free text nursing notes and combined data available at triage. NLP techniques were used to extract information from the unstructured data.

RESULTS

Of the 27,665 pediatric ED visits included in the study, 8394 (30.3%) received medical imaging in the ED, including 6922 (25.0%) who had an X-ray and 1367 (4.9%) who had a computed tomography (CT) scan. In the predictive model including only structured variables, the c-statistic was 0.71 (95% CI: 0.70-0.71) for any imaging use, 0.69 (95% CI: 0.68-0.70) for X-ray, and 0.77 (95% CI: 0.76-0.78) for CT. Models including only unstructured information had c-statistics of 0.81 (95% CI: 0.81-0.82) for any imaging use, 0.82 (95% CI: 0.82-0.83) for X-ray, and 0.85 (95% CI: 0.83-0.86) for CT scans. When both structured variables and free text variables were included, the c-statistics reached 0.82 (95% CI: 0.82-0.83) for any imaging use, 0.83 (95% CI: 0.83-0.84) for X-ray, and 0.87 (95% CI: 0.86-0.88) for CT.

CONCLUSIONS

Both CT and X-rays are commonly used in the pediatric ED with one third of the visits receiving at least one. Patients' socioeconomic, demographic and clinical factors presented at ED triage period were associated with the medical imaging utilization. Predictive models combining structured and unstructured variables available at triage performed better than models using structured or unstructured variables alone, suggesting the potential for use of NLP in determining resource utilization.

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.

Balancing volume and duration of information consumption by physicians: The case of health information exchange in critical care

BACKGROUND

The realization of the potential benefits of health information exchange systems (HIEs) for emergency departments (EDs) depends on the way these systems are actually used. The attributes of volume of information and duration of information processing are important for the study of HIE use patterns in the ED, as cognitive load and time constraints may result in a trade-off between these attributes. Experts and non-experts often use different problem-solving strategies, which may be consequential for their system use patterns. Little previous research focuses on the trade-off between volume and duration of system use or on the factors that affect it, including user expertise.

OBJECTIVES

This study aims at exploring the trade-off of volume and duration of use, examining whether this relationship differs between experts and non-experts, and identifying factors that are associated with use patterns characterized by volume and duration.

METHODS

The research objectives are pursued in the context of critically-ill patients, treated at a busy ED in the period 2010-2012. The primary source of internal and external data is an HIE linked to 14 hospitals, over 1300 clinics, and other clinical facilities. We define four use profiles based on the attributes of duration and volume: quick and basic, quick and deep, slow and basic, and slow and deep. The volume and duration of use are computed using HIE log files as the number of screens and the time per screen, respectively. Each session is then classified into a specific profile based on distances from predefined profile centroids. Experts are physicians that are board-certified in emergency medicine. We test the distribution of use profiles and their associations with multiple variables that describe the patient, physician, situation, information available in the HIE system, and use dynamics within the encounter.

RESULTS

The quick and basic profile is the most prevalent. While available admission summaries are associated with quick and basic use, lab and imaging results are associated with slower or deeper use. Physicians who are the first to use the system or are sole users during an encounter are less inclined to quick and deep use. These effects are intensified for experts.

DISCUSSION

A trade-off between volume and duration is identified. While system use is overall similar for experts and non-experts, the circumstances in which a certain profile is more likely to be observed vary across these two groups. Information availability and multiple-physician dynamics within the encounter emerge as important for the prediction of use profiles. The findings of this study provide implications for the design, implementation, and research of HIE use.

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.

Cost-Effectiveness Evaluation of EHR: Simulation of an Abdominal Aortic Aneurysm in the Emergency Department

Health care organizations have installed electronic systems to increase efficiency in health care. Empirically assessing the cost-effectiveness of technologies to the health care system is a challenging and complex task. This study examined cost-effectiveness of additional clinical information supplied via an EHR system by simulating a case of abdominal aortic aneurysm devised and acted professionally by the Israel Center of Medical Simulation. We conducted a simulation-based study on physicians who were asked to treat a simulated patient for the prevalent medical scenario of hip and leg pain that actually corresponded to an abdominal aortic aneurysm. Half of the participating physicians from the Department of Emergency Medicine at Tel-Hashomer Hospital - Israel's largest - had access to an EHR system that integrates medical data from multiple health providers (community and hospitals) in addition to the local health record, and half did not. To model medical decision making, the results of the simulation were combined with a Markov Model within a decision tree. Cost-effectiveness was analyzed by comparing the effects of the admission/discharge decision in units of quality adjusted life years (QALYs) to the estimated costs. The results showed that using EHR in the ED increases the QALY of the patient and improves medical decision-making. The expenditure per patient for one QALY unit as a result of using the EHR was $1229, which is very cost-effective according to many accepted threshold values (less than all these values). Thus, using the EHR contributes to making a cost-effective decision in this specific but prevalent case.

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.

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.

Validation of a nurses' views on electronic medical record systems (EMR) questionnaire in Turkish health system

Using of EMR in health services and organizations is steadily increasing for quality improvement, cost effectiveness and performance development. However, no validated national and international instruments (scale, questionnaire, index, and inventory) have assessed the effectiveness, satisfaction, health care savings, patient safety and cost minimization of electronic medical and health systems from the viewpoint and perceptions of nurses in Turkish health services. The perceptions of health care professionals especially physicians and nurses can contribute important information that may predict their acceptance of EMR and desired mode of use for EMR, evaluation performance of EMR thus guiding EMR implementation in hospitals. This article is a report of validation of the instrument to measure nurses' views on the use, quality and user satisfaction with EMR in Turkish health system. Items in the questionnaire were designed and obtained following O.G. Otieno, H. Toyama, M. Asonuma, M. Kanai-Pak, K. Naitoh's questionnaire about Use, Quality and User Satisfaction with EMR systems. Reliability and validity were examined and investigated in terms of responses from 487 nurses from one education hospital in Ankara, Turkey. This study was planned and conducted at a university hospital. The validation process was based on construct validity in this study. The response rate was 74.92%. Cronbach's alphas of three factors (use, quality and satisfaction of EMR) ranged from 0.78 to 0.94. Goodness-of-fit indices from the confirmatory factor analysis showed a reasonable model fit. Results of confirmatory factor analysis showed that χ2 statistic indicated significant result (p < 0.001) and model fit was acceptable according to relative χ2 statistic (χ2/df = 2.8 < 5). Further validation of the instrument could yield positive results in health systems in the different countries. Also further validation and reliability studies could be planned on physicians and other health professionals.

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.

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.

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.

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

BACKGROUND

Many medical organizations have invested heavily in electronic health record (EHR) and health information exchange (HIE) information systems (IS) to improve medical decision-making and increase efficiency. Despite the potential interoperability advantages of such IS, physicians do not always immediately consult electronic health information, and this decision may result in decreased level of quality of care as well as unnecessary costs. This study sought to reveal the effect of EHR IS use on the physicians' admission decisions. It was hypothesizing the using EHR IS will result in more accurate and informed admission decisions, which will manifest through reduction in single-day admissions and in readmissions within seven days.

METHODS

This study used a track log-file analysis of a database containing 281,750 emergency department (ED) referrals in seven main hospitals in Israel. Log-files were generated by the system and provide an objective and unbiased measure of system usage, Thus allowing us to evaluate the contribution of an EHR IS, as well as an HIE network, to decision-makers (physicians). This is done by investigating whether EHR IS lead to improved medical outcomes in the EDs, which are known for their tight time constraints and overcrowding. The impact of EHR IS and HIE network was evaluated by comparing decisions on patients classified by five main differential diagnoses (DDs), made with or without viewing the patients' medical history via the EHR IS.

RESULTS

The results indicate a negative relationship between viewing medical history via EHR systems and the number of possibly redundant admissions. Among the DDs, we found information viewed most impactful for gastroenteritis, abdominal pain, and urinary tract infection in reducing readmissions within seven days, and for gastroenteritis, abdominal pain, and chest pain in reducing the single-day admissions' rate. Both indices are key quality measures in the health system. In addition, we found that interoperability (using external information provided online by health suppliers) contributed more to this reduction than local files, which are available only in the specific hospital. Thus, reducing the rate of redundant admissions by using external information produced larger odds ratios (of the β coefficients; e.g. viewing external information on patients resulted in negative associations of 27.2% regarding readmissions within seven days, and 13% for single-day admissions as compared with viewing local information on patients respectively).

CONCLUSIONS

Viewing medical history via an EHR IS and using HIE network led to a reduction in the number of seven day readmissions and single-day admissions for all patients. Using external medical history may imply a more thorough patient examination that can help eliminate unnecessary admissions. Nevertheless, in most instances physicians did not view medical history at all, probably due to the limited resources available, combined with the stress of rapid turnover in ED units.

Implementing a Monte‐Carlo simulation on admission decisions

Purpose

Although very significant and applicable, there have been no formal justifications for the use of Monte‐Carlo models and Markov chains in evaluating hospital admission decisions or concrete data supporting their use. For these reasons, this research was designed to provide a deeper understanding of these models. The purpose of this paper is to examine the usefulness of a computerized Monte‐Carlo simulation of admission decisions under the constraints of emergency departments.

Design/methodology/approach

The authors construct a simple decision tree using the expected utility method to represent the complex admission decision process terms of quality adjusted life years (QALY) then show the advantages of using a Monte‐Carlo simulation in evaluating admission decisions in a cohort simulation, using a decision tree and a Markov chain.

Findings

After showing that the Monte‐Carlo simulation outperforms an expected utility method without a simulation, the authors develop a decision tree with such a model. real cohort simulation data are used to demonstrate that the integration of a Monte‐Carlo simulation shows which patients should be admitted.

Research limitations/implications

This paper may encourage researchers to use Monte‐Carlo simulation in evaluating admission decision implications. The authors also propose applying the model when using a computer simulation that deals with various CVD symptoms in clinical cohorts.

Originality/value

Aside from demonstrating the value of a Monte‐Carlo simulation as a powerful analysis tool, the paper's findings may prompt researchers to conduct a decision analysis with a Monte‐Carlo simulation in the healthcare environment.