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Am J Med Sci ; 351(6): 576-81, 2016 Jun.
Article in English | MEDLINE | ID: mdl-27238919

ABSTRACT

BACKGROUND: Electronic health records (EHR) with computerized physician order entry have become exceedingly common and government incentives have urged implementation. The purpose of this study was to ascertain the effect of EHR implementation on medical intensive care unit (MICU) mortality, length of stay (LOS), hospital LOS and medication errors. MATERIALS AND METHODS: Prospective, observational study from July 2010-June 2011 in MICU at an urban teaching hospital in Atlanta, Georgia of 797 patients admitted to the MICU; 281 patients before the EHR implementation and 516 patients post-EHR implementation. RESULTS: Compared with the preimplementation period (N = 43 per 281), the mortality risk at 4 months post-EHR implementation (N = 41 per 247) and at 8 months post-EHR implementation (N = 26 per 269) significantly decreased (P < 0.001). In addition, the mean MICU LOS statistically decreased from 4.03 ± 1.06 days pre-EHR to 3.26 ± 1.06 days 4 months post-EHR and to 3.12 ± 1.05 days 8 months post-EHR (P = 0.002). However, the mean hospital LOS was not statistically decreased. Although medication errors increased after implementation (P = 0.002), this was attributable to less severe errors and there was actually a decrease in the number of severe medication errors (both P < 0.001). CONCLUSIONS: We report a survival benefit following the implementation of EHR with computerized physician order entry in a critical care setting and a concomitant decrease in the number of severe medication errors. Although overall hospital LOS was not shortened, this study proposes that EHR implementation in a busy urban hospital was associated with improved ICU outcomes.


Subject(s)
Critical Care , Electronic Health Records , Length of Stay/statistics & numerical data , Medical Order Entry Systems , Medication Errors/statistics & numerical data , Mortality , Adult , Aged , Female , Georgia , Hospitals, Teaching , Hospitals, Urban , Humans , Intensive Care Units , Interrupted Time Series Analysis , Male , Middle Aged , Prospective Studies
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