Effectiveness of clinical decision support in controlling inappropriate red blood cell and platelet transfusions, speciality specific responses and behavioural change

Jolene Atia, Felicity Evison, Suzy Gallier, Sophie Pettler, Mark Garrick, Simon Ball, Will Lester, Suzanne Morton, Jamie Coleman, Tanya Pankhurst*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

BACKGROUND: Electronic clinical decision support (CDS) within Electronic Health Records has been used to improve patient safety, including reducing unnecessary blood product transfusions. We assessed the effectiveness of CDS in controlling inappropriate red blood cell (RBC) and platelet transfusion in a large acute hospital and how speciality specific behaviours changed in response.

METHODS: We used segmented linear regression of interrupted time series models to analyse the instantaneous and long term effect of introducing blood product electronic warnings to prescribers. We studied the impact on transfusions for patients in critical care (CC), haematology/oncology (HO) and elsewhere.

RESULTS: In non-CC or HO, there was significant and sustained decrease in the numbers of RBC transfusions after introduction of alerts. In CC the alerts reduced transfusions but this was not sustained, and in HO there was no impact on RBC transfusion. For platelet transfusions outside of CC and HO, the introduction of alerts stopped a rising trend of administration of platelets above recommended targets. In CC, alerts reduced platelet transfusions, but in HO alerts had little impact on clinician prescribing.

CONCLUSION: The findings suggest that CDS can result in immediate change in user behaviour which is more obvious outside specialist settings of CC and HO. It is important that this is then sustained. In CC and HO, blood transfusion practices differ. CDS thus needs to take specific circumstances into account. In this case there are acceptable reasons to transfuse outside of these crude targets and CDS should take these into account.

Original languageEnglish
Article number342
Number of pages12
JournalBMC Medical Informatics and Decision Making
Volume22
Issue number1
DOIs
Publication statusPublished - 29 Dec 2022

Bibliographical note

© 2022. The Author(s).

Keywords

  • Humans
  • Platelet Transfusion
  • Decision Support Systems, Clinical
  • Blood Transfusion
  • Erythrocyte Transfusion
  • Erythrocytes
  • Red blood cells
  • Platelets
  • Haemoglobin
  • Transfusion
  • Clinical decision support
  • CDS
  • Electronic health records
  • EHR
  • e-Alerts
  • Segmented linear regression of interrupted time series

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