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I. Introduction
Te bene ts o electronic nursing record (ENR) systems in-clude
reduced errors, improved quality o care, and loweredcost. hese bene
its can be maximized by using a standard
nursing terminology, which improves data quality, data shar-ing,
and decision support. In Korea, an ENR system basedon standard
nursing terminology was introduced or the rsttime at Seoul National
University Bundang Hospital in 2003[1]. For nursing documentation,
nurses at Bundang Hospi-tal use nursing statements that were
created by combiningconcepts rom the International Classi ication
or NursingPractice. he data gathered by this system have been
usedor decision-making and research [2,3].However, the current
system has some limitations in ensur-
ing ull semantic interoperability because nursing statements
Integration of Evidence into a Detailed ClinicalModel-based
Electronic Nursing Record SystemHyeoun-Ae Park, PhD, RN 1, Yul Ha
Min, MS, RN 1,2 , Eunjoo Jeon, RN 1, Eunja Chung, RN 31Seoul
National University College of Nursing, Seoul;2Research Institute
of Nursing Science, Seoul National University, Seoul;3Department of
Nursing, SeoulNational University Bundang Hospital, Seongnam,
Korea
Objectives: Te purpose o this study was to test the easibility o
an electronic nursing record system or perinatal care thatis based
on detailed clinical models and clinical practice guidelines in
perinatal care. Methods: Tis study was carried out in
ve phases: 1) generating nursing statements using detailed
clinical models; 2) identi ying the relevant evidence; 3)
linkingnursing statements with the evidence; 4) developing a
prototype electronic nursing record system based on detailed
clini-cal models and clinical practice guidelines; and 5)
evaluating the prototype system. Results: We rst generated 799
nursingstatements describing nursing assessments, diagnoses,
interventions, and outcomes using entities, attributes, and value
sets o detailed clinical models or perinatal care which we
developed in a previous study. We then extracted 506
recommendationsrom nine clinical practice guidelines and created
sets o nursing statements to be used or nursing documentation by
group-ing nursing statements according to these recommendations.
Finally, we developed and evaluated a prototype electronicnursing
record system that can provide nurses with recommendations or
nursing practice and sets o nursing statementsbased on the
recommendations or guiding nursing documentation. Conclusions: he
prototype system was ound to besufciently complete, relevant, use
ul, and applicable in terms o content, and easy to use and use ul
in terms o system userinter ace. Tis study has revealed the
easibility o developing such an ENR system.
Keywords: Computerized Medical Record Systems, Nursing Records,
Evidence-Based Practice, Concept Formation, Semantics
Healthc Inform Res. 2012
June;18(2):136-144.http://dx.doi.org/10.4258/hir.2012.18.2.136pISSN
2093-3681 eISSN 2093-369X
Original Article
Submitted: May 8, 2012Revised: June 27, 2012
Accepted: June 28, 2012
Corresponding Author Yul Ha Min, MS, RNSeoul National University
College of Nursing, 103 Daehak-ro,Jongno-gu, Seoul 110-799, Korea.
Tel: +82-2-740-8827, Fax: +82-2-766-1852, E-mail:
[email protected]
This is an OpenAccess article distributed under the terms of the
Creative Com-mons Attribution Non-Commercial License
(http://creativecommons.org/licenses/by-nc/3.0/) whichpermits
unrestrictednon-commercial use, distribution, and reproduc-tion in
any medium, provided theoriginal work isproperly cited.
2012 The Korean Society of Medical Informatics
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Evidence and DCM-based Electronic Nursing Records
used or documentation have di erent levels o granularity with di
erent quali ers and value sets. Te current ENR sys-tem also has not
yet incorporated the available evidence onclinical practice
guidelines (CPGs) and clinical pathways.
A data model is proposed to ensure the ull semantic
in-teroperability o a terminology-based ENR system. A data
model expresses the classes o in ormation required and
theproperties o those classes, including attributes,
relation-ships, and states [4,5]. One such data model is a
detailedclinical model (DCM) consisting o
entity-attribute-valuetriplets. In a DCM, an entity is a core or
ocus concept o adata element. An attribute is a quali er that
represents a dataentity in more detail. A value set represents a
uniquely iden-ti able set o valid concept representations o an
attribute.
Tere have been several di erent research projects to devel-op
data models in health care or a national-level minimumdata set,
electronic health records, a decision support system,and data
analysis. Examples are IMH Clinical Elements romIntermountain
Healthcare, ISO 13606 Archetypes, Clinicalemplates Scotland,
Clinical Contents Models, Health Level 7templates, and the DCM
developed in the Netherlands [4-10].
However, the e orts in these approaches have been limitedto the
domain o medical knowledge. While the importanceo developing a data
model or nursing has been addressedby nurse in ormaticists [7],
there is only one report on thistopic in nursing literature by
Goossen [11], other than re-search results published by the authors
o this paper [12-16]. hese research projects were only pilot
studies whichshowed the possibility o model development in a
limitednursing domain. Nursing statements generated using the
en-tities, attributes, and value sets o the data models o er new
possibilities to provide semantic interoperability or
nursingrecords.
Limited use o evidence rom research is one o the prob-lems
encountered in clinical practice. ranslating researchoutcomes as
evidence or clinical practice is necessary orensuring patient sa
ety and advancing the quality o health-care. Evidence-based
practice (EBP) is de ned as a problem-
solving approach to practice that involves the conscientioususe
o current best evidence in making decisions aboutpatient care in
order to promote the selection and imple-mentation o the most
appropriate intervention [17]. CPGwith appraised summaries o
research and recommendationsor health care is one strategy with
which to use the currentbest evidence [17,18]. As in ormation
technology is used toimprove adherence to guidelines, there were
several researchprojects integrating clinical guidelines or
pathways into theclinical decision support system or pain, pressure
ulcers,and obesity management in nursing [19-22].
However, these evidence-based clinical decision supportsystems
were not linked to an ENR system. Tere ore, nursesadditionally have
to document the nursing activities per-ormed ollowing
recommendations. hus, an ENR systemlinking EBP is proposed to solve
these problems. An ENR system integrated with EBP not only guides
nurses or best
practice, but also helps them document nursing practicearound
best practice. o our knowledge, there has been noprevious work on
this topic.
here ore, an ENR system based on DCMs and CPGs isproposed in
this study. he purpose o this study is to testthe easibility o this
system in perinatal care.
II. Methods
his study was carried out in ive phases: 1) generatingnursing
statements using DCMs; 2) identi ying the relevantevidence; 3)
linking nursing statements with the evidence;4) developing a
prototype electronic nursing record systembased on DCMs and CPGs;
and 5) evaluating the prototypesystem (Figure 1).
1. Generating Nursing Statements Using DCMsNursing statements
describing nursing assessments, diagno-ses, interventions, and
outcomes in perinatal care were gen-erated using the entities,
attributes, and value sets o DCMsdeveloped [12,13] by the authors o
this paper.
2. Identifying EvidenceWe searched and reviewed published CPGs
related to the as-sessment and management o perinatal care. Te
guidelineswere searched or in the National Guideline
Clearinghouse(www.guideline.gov), the Guidelines International
Network (www.g-i-n.net), the New Zealand Guidelines Group
(www.nzgg.org.nz), and the National Institute or Health and
Clin-ical Excellence (NICE; www.nice.org.uk). Te search termsused
included labor, pregnancy, management o labor, anddelivery
care.
We extracted recommendations relevant to nursing carerom these
CPGs. Tese recommendations were rearrangedby stage o labor and
patient problems in each stage. We validated this arrangement
internally by consulting threedomain experts who were nurses with
more than 10 years o clinical nursing experience in maternal care.
Each recom-mendation was re ned through repeated consultation
withthese domain experts.
3. Linking Nursing Statements with EvidenceWe organized a set o
nursing statements around the recom-
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140 http://dx.doi.org/10.4258/hir.2012.18.2.136www.e-hir.org
Hyeoun-Ae Park et al
Table 1. Clinical guidelines related to delivery care
Title Developer (date released) Guideline in this study
Antenatal care: routine or the healthy pregnant woman
National Collaborating Centre or Womensand Childrens Health (Oct
2003)
Antenatal care or normal pregnancy
Intrapartum care: care o healthy wom-en and their babies during
childbirth
National Collaborating Centre or Womensand Childrens Health (Sep
2007)
Intrapartum care or vaginal delivery
Routine postnatal care o women andtheir babies
National Collaborating Centre or Primary Care (Jul 2006)
Postpartum care or vaginal delivery
Induction o labor National Collaborating Centre or Primary Care
(Jul 2008)
Intrapartum care or caesarean sec-tion (CS)
Nursing care and management o thesecond labor
Association o Women's Health, Obstetricand Neonatal Nurses (Jan
2000)
Intrapartum care or vaginal delivery
Caesarean section: summary o e ectsand procedural aspects
National Collaborating Centre or Womensand Childrens Health (Apr
2004)
Intrapartum care or CS and post-partum care or CS
Gestational diabetes mellitus: evidence-based nutrition practice
guideline
American Dietetic Association (Sep 2001) Gestational diabetes
mellitus
Te management o severe pre-eclamp-sia/eclampsia
Royal College o Obstetricians and Gynaeco-logists (Mar 2006)
Pre-eclampsia
Hypertension in pregnancy: the man-agement o hypertensive
disordersduring pregnancy
National Collaborating Centre or Women'sand Children's Health
(Aug 2010)
Pre-eclampsia
Figure 3. Nursing statement set of intrapartum care for vaginal
delivery.
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Hyeoun-Ae Park et al
5. Evaluating the Prototype ENR SystemTe mean scores given or
completeness, relevancy, use ul-ness, and applicability were 4.7,
4.7, 4.8, and 4.8 out o 5.0,respectively. Eight recommendations
were rated as either1 or 2. Five recommendations were rated as
irrelevant andthree recommendations as inapplicable. Tese
recommenda-
tions were modi ied and re ined. One example rated as
ir-relevant was the per orm post-void residual
catheterizationrecommendation in the rst stage o labor, because
checkingpost-void residual urine is not necessary during the
intra-partal care o a normal pregnancy. Tis was modi ed to as-sess
urine including requency and characteristics. Anotherexample rated
as inapplicable was the recommendation in-struct patient to report
danger signs, because observing any changes in etal activity during
delivery and reporting thedanger signs to nurses might cause the
patients discom ort.his was modi ied to instruct caregiver to
report dangersigns.
Te domain experts commented that the system was easy to use and
use ul in displaying sets o nursing statements a -ter grouping them
according to recommendation by stage o labor, type o delivery, and
pregnancy risk level, and allow-ing nurses to search appropriate
statements according to thecare process. In addition, the new
system user inter ace (UI)was not much di erent rom that o the
current ENR system.However, they pointed out that the statements
were unnatu-ral and that it took them too much time to select an
appro-priate value or each attribute. For example, a statement
suchas labor pain presents (interval, 5 minutes; duration, 1
min-ute) does not have a natural sentence structure, and nursesneed
to pick values or the interval and duration attributes inorder to
document the labor pain completely.
IV. Discussion
his study is one o the irst attempts to develop an ENR system
based on data models and CPGs to support nursingpractice and
nursing documentation. Te prototype system
was ound to be sufciently complete, relevant, use ul,
andapplicable in terms o content, and easy to use and use ul
interms o the system UI. Tis study has revealed that develop-ing
such an ENR system is easible.
he nursing statements describing patient problems vary more than
nursing statements describing nursing interven-tions and nursing
activities by the nursing units and diseasetypes. Further, nursing
statements describing the same pa-tient status and problem have di
erent levels o granularity with di erent quali ers and value sets
[23,24]. For example,the presence o pain or the intensity o pain is
an impor-
tant piece o in ormation in one nursing unit, whereas
thecharacter o the pain, the quality o the pain, and the clini-cal
course o the pain are more important in another nurs-ing unit. For
this reason, it is necessary to provide nursingstatements with di
erent levels o granularity with di erentquali iers and value sets
to nurses at the point o nursing
documentation. It was possible or us to generate
nursingstatements with di erent levels o granularity in the
proto-type ENR system developed in this study. For example, 41di
erent nursing statements were generated using the laborpain
DCM.
In this study, the nursing statements were generated by
combining the entity-attribute-value set triplets o DCMs
toacilitate structured data entry. However, these statementswere
very structured and not natural to human language,and it took more
time to select an appropriate value roma pick-list or each
attribute than already pre-coordinatedstatements. o solve this
problem, we re ined these state-ments manually to mimic natural
sentences, such as romlabor pain (duration, 1 minute; interval, 5
minutes) to laborpain presents or 1 minute at 5-minute intervals.
Tere ore, anursing statement generating system using natural
languagegeneration technology needs to be developed to
automati-cally create more user- riendly, readable, and natural
nursingstatements in the uture.
In this study, we used only published CPGs as clinicalevidence.
Although there is no lack o nursing-orientedguidelines [17,18],
most o these guidelines are ocused onchronic nursing care or speci
ic nursing problems such aspain, pressure ulcers, and breast
eeding. Nursing-orientedguidelines or acute care are still scarce.
In order to developa CPGs-based ENR system, relevant
recommendations needto be extracted rom various guidelines
considering di erenttarget groups and context.
CPGs are promising tools or closing the gap betweenresearch and
practice, yet the e ective and timely imple-mentation o evidence
into practice remains ragmentedand inconsistent [25,26]. One
barrier is the limited integra-
tion o guidelines into the care process or the point o care.We
categorized guidelines by stages o labor, di erent typeso delivery,
and pregnancy risk levels, and arranged andgrouped recommendations
according to the stages o laborand patient problems. Tus,
recommendations provided inthis prototype ENR system were more
customized or di er-ent stages o labor and patient problems.A
CPGs-based ENR system will acilitate advanced nursing
practice and the accumulation o key in ormation gener-ated
during patient care. here ore, individual patient datagathered with
DCMs- and CPGs-based ENR systems will
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Evidence and DCM-based Electronic Nursing Records
improve data quality, which in turn will provide a ounda-tion or
generating urther evidence and measuring clinicaloutcomes.
However, this study has a ew limitations. First, the
imple-mentation scope o CPGs was limited to perinatal care.Second,
the evaluation o the ENR system was limited to
the quality o its content by mainly limited domain experts.Tere
ore, urther studies on the CPGs-based ENR system inother areas o
nursing and evaluation o the system in termso quality improvement
in nursing documentation and nurs-ing practice are recommended.
Con icts of Interest
No potential con lict o interest relevant to this article
wasreported.
Acknowledgments
Tis research was supported by the Basic Science ResearchProgram
through the National Research Foundation o Ko-rea (NRF) unded by
the Ministry o Education, Science andechnology (No. 2010-0010468
& 2012-0000998).
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