title: The impact of EHR and HIE on reducing avoidable admissions: controlling main differential diagnoses.
abstract: 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.
authors.affiliation: Faculty of Business Administration, Ono Academic College, Zahal Street, Kiryat Ono, IL, Israel. ofir.benassuli@gmail.com
authors.forename: Ofir
authors.initials: O
authors.lastname: Ben-Assuli
authors.forename: Itamar
authors.initials: I
authors.lastname: Shabtai
authors.forename: Moshe
authors.initials: M
authors.lastname: Leshno
mesh_terms: D000328:Adult; D019033:Delivery of Health Care, Integrated / Q000379:methods; D003937:Diagnosis, Differential; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D005260:Female; D006279:Health Maintenance Organizations / Q000706:statistics & numerical data; D006300:Health Services Misuse / Q000517:prevention & control*; D006751:Hospital Information Systems / Q000706:statistics & numerical data*; D006801:Humans; D038801:International Classification of Diseases / Q000706:statistics & numerical data; D007557:Israel; D008297:Male; D008875:Middle Aged; D010043:Outcome and Process Assessment, Health Care; D010343:Patient Admission / Q000706:statistics & numerical data*; D010359:Patient Readmission / Q000706:statistics & numerical data*; D010820:Physicians / Q000523:psychology* / Q000706:statistics & numerical data; D012017:Referral and Consultation / Q000706:statistics & numerical data; D012044:Regression Analysis