ArticleBMC medical informatics and decision making2019
Staff expectations for the implementation of an electronic health record system: a qualitative study using normalisation process theory.
Article in BMC medical informatics and decision making, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Practitioner perspectives on implementing a quality improvement intervention for telephone-based therapy in NHS Talking Therapies: a qualitative process evaluation study.BMC health services research · 2026Trial
- Tele-ophthalmology-enabled and artificial intelligence-ready referral pathway for community optometry referrals of retinal disease: HERMES cluster randomised trial with a diagnostic accuracy study.Health technology assessment (Winchester, England) · 2025Trial
- Implementation of electronic medication management systems in hospital settings: a theory-informed systematic review protocol of mechanisms influencing patient safety, operational efficiency and staff experience.BMJ health & care informatics · 2026Article
- Optimised electronic patient records to improve clinical monitoring of people living with HIV (MONART trial) intervention: a qualitative process evaluation.BMC health services research · 2026Article
- Telerehabilitation of patients with stroke: Initial program theories for successful implementation.PM & R : the journal of injury, function, and rehabilitation · 2025Article
- Translational framework for implementation evaluation and research: implementation strategies derived from normalization process theory.Implementation science : IS · 2025Article
- Identifying Influential Theories in Human-Computer Interaction Within Health Informatics: A Systematic Review.Health science reports · 2025Review
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- A new normal in primary care: the rapid normalization of a major eHealth program in public health centers.BMC health services research · 2024Article
- Exploring the implementation of an educational film within antenatal care to reduce the risk of cytomegalovirus infection in pregnancy: A qualitative study.BMC pregnancy and childbirth · 2024Article
- Evaluating the Implementation of the Pediatric Acute Care Education (PACE) Program in Northwestern Tanzania: A Mixed-Methods Study Guided by Normalization Process Theory.Research square · 2024Article
- Readiness for Change in the Implementation of a 3D Printing Initiative in a Catalan Tertiary Hospital Using the Normalization Process Theory: Survey Study.JMIR human factors · 2023Article
- How Safe are Outpatient Electronic Health Records? An Evaluation of Medication-Related Decision Support using the Ambulatory Electronic Health Record Evaluation Tool.Applied clinical informatics · 2023Article
- Impacts of COVID-19 on Drug Treatment Court Operations: Lessons Learned Through Normalization Process Theory.Victims & offenders · 2023Article
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- Satisfied or not satisfied? Electronic health records system implementation in Ghana: Health leaders' perspective.BMC medical informatics and decision making · 2022Article
- Article
- Automated Decision Support For Community Mental Health Services Using National Electronic Health Records: Qualitative Implementation Case Study.JMIR human factors · 2022Article
- Electronic health record implementation and healthcare workers' work characteristics and autonomous motivation-a before-and-after study.BMC medical informatics and decision making · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGlobal evidence suggests a range of benefits for introducing electronic health record (EHR) systems to improve patient care. However, implementing EHR within healthcare organisations is complex and, in the United Kingdom (UK), uptake has been slow. More research is needed to explore factors influencing successful implementation. This study explored staff expectations for change and outcome following procurement of a commercial EHR system by a large academic acute NHS hospital in the UK.
methodsQualitative interviews were conducted with 14 members of hospital staff who represented a variety of user groups across different specialities within the hospital. The four components of Normalisation Process Theory (Coherence, Cognitive participation, Collective action and Reflexive monitoring) provided a theoretical framework to interpret and report study findings.
resultsHealth professionals had a common understanding for the rationale for EHR implementation (Coherence). There was variation in willingness to engage with and invest time into EHR (Cognitive participation) at an individual, professional and organisational level. Collective action (whether staff feel able to use the EHR) was influenced by context and perceived user-involvement in EHR design and planning of the implementation strategy. When appraising EHR (Reflexive monitoring), staff anticipated short and long-term benefits. Staff perceived that quality and safety of patient care would be improved with EHR implementation, but that these benefits may not be immediate. Some staff perceived that use of the system may negatively impact patient care. The findings indicate that preparedness for EHR use could mitigate perceived threats to the quality and safety of care.
conclusionsHealth professionals looked forward to reaping the benefits from EHR use. Variations in level of engagement suggest early components of the implementation strategy were effective, and that more work was needed to involve users in preparing them for use. A clearer understanding as to how staff groups and services differentially interact with the EHR as they go about their daily work was required. The findings may inform other hospitals and healthcare systems on actions that can be taken prior to EHR implementation to reduce concerns for quality and safety of patient care and improve the chance of successful implementation.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.