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BackgroundMany 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.MethodsThis 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.ResultsThe 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).ConclusionsViewing 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.

Many medical organizations have deployed electronic medical record (EMR) information systems (IS) to improve medical decision-making and increase efficiency. Despite their advantages, however, EMR IS may make less of a contribution in the stressful environment of an emergency department (ED) that operates under tight time constraints. The high level of crowdedness in the EDs itself can cause physicians to make medical decisions resulting in more unnecessary admissions and fewer necessary admissions. Thus this study evaluated the contribution of an EMR IS to physicians by investigating whether EMR IS leads to improved medical outcomes in points of care in EDs under different levels of crowdedness. For this purpose a track log-file analysis of a database containing 3.2 million ED referrals in seven main hospitals in Israel (the whole population in these hospitals) was conducted. The findings suggest that viewing medical history via the EMR IS leads to better admission decisions, and reduces the number of possibly avoidable single-day admissions. Furthermore, although the ED can be very stressful especially on crowded days, physicians used EMR IS more on crowded days than on non-crowded days. These results have implications as regards the viability of EMR IS in complex, fast-paced environments.

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.

Diagnostic complexity is an important contextual factor affecting a variety of medical outcomes. Existing measurements of diagnosis complexity either rely on crude proxies or use fine-grained measures that employ indicators from proprietary data that are not readily available. Hence, the study of this important construct in fields such as medical informatics has been hampered by the difficulty of measuring diagnostic complexity. This article presents a novel approach for conceptualizing and operationalizing diagnostic task complexity as a multi-dimensional construct, which employs the readily available International Classification of Diseases codes from medical encounters in hospitals and uses Analytic Hierarchical Process methodology. We demonstrate the reliability of the proposed approach and show that despite using a relatively simple procedure, it is able to predict readmission rates just as well as (or even better) than some of the sophisticated measures that have been used in recent studies (namely, the LaCE score index).