Insights into temporal patterns of hospital patient safety from routinely collected electronic data

  • Gallego B
  • Magrabi F
  • Concha O
  • et al.
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Abstract

BACKGROUND: The last two decades have seen an unprecedented growth in initiatives aimed to improve patient safety. For the most part, however, evidence of their impact remains controversial. At the same time, the healthcare industry has experienced an also unprecedented growth in the amount and variety of available electronic data.METHODS: In this paper, we provide a review of the use of routinely collected electronic data in the identification, analysis and surveillance of temporal patterns of patient safety.RESULTS: Two important temporal patterns of the safety of hospitalised patients were identified and discussed: long-term trends related to changes in clinical practice and healthcare policy; and shorter term patterns related to variations in workforce and resources. We found that consistency in reporting is intrinsically related to availability of large-scale, fit-for-purpose data. Consistent reported trends of patient harms included an increase in the incidence of post-operative sepsis and a decrease in central-line associated bloodstream infections. Improvement in the treatment of specific diseases, such as cardiac conditions, has also been demonstrated. Linkage of hospital data with other datasets provides essential temporal information about errors, as well as information about unsuspected system deficiencies. It has played an important role in the measurement and analysis of the effects of off-hours hospital operation.CONCLUSIONS: Measuring temporal patterns of patient safety is still inadequate with electronic health records not yet playing an important role. Patient safety interventions should not be implemented without a strategy for continuous monitoring of their effect.

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Gallego, B., Magrabi, F., Concha, O. P., Wang, Y., & Coiera, E. (2015). Insights into temporal patterns of hospital patient safety from routinely collected electronic data. Health Information Science and Systems, 3(S1). https://doi.org/10.1186/2047-2501-3-s1-s2

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