Active Pregnancy, Children & Inherited Conditions NIHR-supported project Public Health & Healthcare

Stakeholder survey: views on electronic maternity notes

In plain English

AI plain-English summary

Midwives and expectant mothers in England are typing notes into two different electronic record systems, and researchers want to know which one works better for maternity care. This matters because paper maternity notes are being replaced by electronic systems, yet no studies have checked whether these digital records actually improve the completeness of the data entered. Without that evidence, hospitals may adopt systems that miss critical information or frustrate the people who use them. The two systems in question—one used in many hospitals but poorly integrated with other services, the other a hospital-wide system with less built-in decision support—offer contrasting approaches, and stakeholders have direct experience of their strengths and weaknesses. If this research succeeds, it will give NHS trusts clear, user-informed guidance on what features matter most in an electronic maternity record. That could lead to systems that are easier for midwives to use, more helpful for clinical decision-making, and better at capturing the full picture of a woman’s pregnancy and birth. The immediate impact is on hospital infrastructure and clinical workflows, not on patients’ daily lives directly—but better records mean safer, more coordinated care.

View original technical description
What is the problem? Electronic Medical Records (EMRs) have been used in primary care for many years and have recently been introduced into maternity care. A recent systematic review (Hawley et al. 2014) evaluated EMRs versus paper handheld records in maternity care, focussed on the completeness of the entered data, user experiences, and process improvements. The review found no studies evaluating the effect of electronic records on data set completeness. What we will do In England, Badgernet has the predominant market share as a provider of a maternity EPR and is used in 47 (40%) hospitals. Epic is an all-inclusive EPR with a built-in maternity module (Stork) with the maternity module used in only six hospitals in England. These two systems have different features that might have influenced stakeholder perceptions. First, Badgernet has limited integration with non-maternity systems in an institution (for example- lack of electronic prescribing, imaging requests). Epic is a hospital wide system incorporating many services such as pharmacy, laboratories, imaging and neo-natal wards. Second, Badgernet comes with extensive in-built decision support while any decision support in Epic must be generated by individual providers at their discretion. We selected these Badgernet and EPIC EMN systems to explore stakeholder views of the relative strengths and weaknesses of these and other potential differences between the two systems. We will conduct an exploratory qualitative evaluation of Electronic Maternity Notes (EMNs) in England with the following objectives: • Assess opportunities and problems experienced by EMN stakeholders (service providers and users) in maternity care • Elicit stakeholders' views on potential alterations or extensions to the EMN system • Evaluate users’ views on decision support within the EMNs.

Researchers

Richard Lilford (Principal Investigator)

Related Research

Grants with similar aims, by meaning.

Measuring the experience of maternity and neonatal service users - development of a maternity Patient Reported Experience Measure (PREM)
Defining, Recognising and Escalating Maternal Early Deterioration (DREaMED): Decreasing inequality through improved outcomes
Defining, Recognising and Escalating Maternal Early Deterioration (DREaMED):Decreasing inequality through improved outcomes
Preliminary research and preparation of outcomes related to pregnancy for developing an NIHR Programme Grant for Applied Research application
The Future of Maternity Care: challenges and opportunities to achieve person- centred care in the NHS

Original classification

Maternal health

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.