Use of electronic medical records and quality of patient data: different reaction patterns of doctors and nurses to the hospital organization

BMC Med Inform Decis Mak. 2017 Feb 10;17(1):17. doi: 10.1186/s12911-017-0412-x.

Abstract

Background: As the implementation of Electronic Medical Records (EMRs) in hospitals may be challenged by different responses of different user groups, this paper examines the differences between doctors and nurses in their response to the implementation and use of EMRs in their hospital and how this affects the perceived quality of the data in EMRs.

Methods: Questionnaire data of 402 doctors and 512 nurses who had experience with the implementation and the use of EMRs in hospitals was analysed with Multi group Structural equation modelling (SEM). The models included measures of organisational factors, results of the implementation (ease of use and alignment of EMR with daily routine), perceived added value, timeliness of use and perceived quality of patient data.

Results: Doctors and nurses differ in their response to the organisational factors (support of IT, HR and administrative departments) considering the success of the implementation. Nurses respond to culture while doctors do not. Doctors and nurses agree that an EMR that is easier to work with and better aligned with their work has more added value, but for the doctors this is more pronounced. The doctors and nurses perceive that the quality of the patient data is better when EMRs are easier to use and better aligned with their daily routine.

Conclusions: The result of the implementation, in terms of ease of use and alignment with work, seems to affect the perceived quality of patient data more strongly than timeliness of entering patient data. Doctors and nurses value bottom-up communication and support of the IT department for the result of the implementation, and nurses respond to an open and innovative organisational culture.

Keywords: Electronic medical records; Health personnel; Health services; Hospital; Implementation process; Quality of patient data.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Attitude of Health Personnel*
  • Electronic Health Records / standards*
  • Female
  • Humans
  • Male
  • Medical Staff, Hospital / standards*
  • Middle Aged
  • Nursing Staff, Hospital / standards*