Health Informatics for Paediatric Ophthalmology
Designing Useful, Usable Information Systems
Maria S. Cross
1,2,3,4
, George W. Aylward
4
and Jugnoo S. Rahi
1,2,3,4,5
1
UCL Great Ormond Street Institute of Child Health, London, United Kingdom
2
Ulverscroft Vision Research Group, London, United Kingdom
3
Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom
4
Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
5
Institute of Ophthalmology, University College London, London, United Kingdom
maria.cross.11@ucl.ac.uk
1 RESEARCH PROBLEM
Electronic medical records (EMRs) are at the core of
a recent movement towards evidence-based
healthcare in many countries (European Commision
2012, Bluemnthal 2010). In the United Kingdom,
there is a target to have a paperless National Health
Service (NHS) by 2020 (NHS England 2014). The
uptake of EMRs in ophthalmology, however, has
been found to lag behind other medical specialties
(Chiang et al. 2008, Boland et al. 2013).
Chiang et al. described the features of general
ophthalmology that impose unique EMR design
requirements and challenge adoption within the field
(2011). These include the high throughput nature of
routine care, and a heavy reliance on imaging and
graphical representation of findings (Chiang et al.
2011). As a subspecialty, paediatric ophthalmology
is anticipated to encounter these in addition to
specific difficulties that reflect its interface with
paediatrics and child health (Redd et al. 2014).
To facilitate EMR adoption, many have
proposed the implementation of a user-centred
design (UCD) approach to health information
technology development (Texeira, Ferreira and
Santos 2012, Martikainen et al. 2010). In the United
States, all certified EMRs are now required to have
been developed following a UCD approach and
undergone usability testing
(US Department of
Health and Human Services 2014). In UCD, the
needs of the user and the use environment drive the
development of the system
(International
Organisation for Standardisation 2010). For health
information technology, this requires an
understanding of clinical information flows and how
patient consultations are conducted and documented
within medical records. Recent research suggests
there are particular challenges in participant
recruitment and the conduct of sufficiently in depth
research into clinical workflows to support the UCD
of EMR development (Ratwani et al. 2015). A
paucity of literature exploring information flows
within NHS paediatric ophthalmology means the
application of UCD to EMR development will be
particularly challenging for this context of use.
2 OUTLINE OF OBJECTIVES
Broadly, this doctoral research applies and evaluates
a user-centred approach to health information
technology development within NHS paediatric
ophthalmology.
The specific objectives are to: (i) identify how
medical record data are and could be used within
routine paediatric ophthalmic NHS care and medical
research; (ii) define data and EMR design
requirements imposed by the identified uses, users
and use environments; and (iii) develop and test data
capture tools that address these requirements.
3 STATE OF THE ART
Initially, health information technology development
was restricted by the technological limitations.
However, recent advances mean that, as with other
domains, health information technology systems can
now adapt to the needs of the user. Design strategies
are therefore shifting towards a user-centred
approach, to create products that are both useful and
usable.
Usability, as defined by the International
Organisation for Standardisation (ISO), is the ‘extent
to which a product can be used by specified users to
achieve specified goals with effectiveness,
efficiency and satisfaction in a specified context of
use’ (International Organisation for Standardisation
1998). Thus, in order to achieve true EMR-usability,
Cross, M., Aylward, G. and Rahi, J.
Health Informatics for Paediatric Ophthalmology - Designing Useful, Usable Information Systems.
In Doctoral Consortium (DCBIOSTEC 2017), pages 11-15
11
an understanding must be gained of who the users of
health data are, and for what purposes and where
these data will be used, through a user-centred
approach.
The ISO standard on ergonomics of human
system interaction describes six principles that
underpin successful UCD (International
Organisation for Standardisation 2010):
The design is based upon an explicit
understanding of users, tasks and
environments.
Users are involved throughout design
and development.
The design is driven and refined by user-
centred evaluation.
The process is iterative.
The design addresses the whole user
experience.
The design team draws upon
multidisciplinary skills and perspectives.
3.1 Users of Electronic Medical
Records
The user, as defined by ISO, is any ‘person who
interacts with the product (International
Organisation for Standardisation 2010). Within this
doctoral work, in order to satisfy the fifth UCD
principle and ensure the whole user experience is
appropriately addressed, both the EMR system and
the health data it contains are considered part of the
product. The definition of an EMR-user is therefore
extended to include any person who interacts with
the technology or with the resulting health data.
Typically, a variety of qualitative research
methods are used to profile potential users and any
experience-influencing factors. Within the
healthcare setting, informal non-structured
interviews can initially identify clinical requirements
of an EMR system (Teixeira, Ferreira and Santos
2012, Greenhalgh et al. 2010). Additional non-
participatory observation can validate these self-
reported needs, and help identify those that may not
be apparent to the individual users studied (Saleem
et al. 2015).
There are few examples of such qualitative
studies undertaken within paediatric ophthalmology,
and thus little literature defining EMR users or
specific user requirements. Surveys conducted in the
United States have identified clinical priorities of
both paediatricians and ophthalmologists (Chiang et
al. 2013, Leu et al. 2012, Spooner 2007). However
as usability is defined to depend upon the context of
use, it cannot be assumed the findings generalise to
practices within the NHS, or indeed to paediatric
ophthalmology as a subspecialty.
Further research is needed to understand the
exact nature of EMR-user requirements and
limitations within NHS paediatric ophthalmology.
4 METHODOLOGY
The multifaceted aims of this doctoral research
require consideration of a great range of use contexts
and end users. In order to include and explore all
user perspectives, a mixed methods approach is
applied. The research is divided into three phases:
exploratory, to elicit user requirements of a
paediatric ophthalmology EMR; a design phase, to
iteratively develop software inline with these
requirements; and a validation phase, to test the
performance of the software against the
requirements and assess the suitability of the
methods employed.
4.1 Exploratory Phase
4.1.1 National Survey
An online questionnaire has been devised to
understand paediatric ophthalmic clinicians’
experiences and perceptions of EMR adoption
within the NHS. All members (189) listed in the
United Kingdom Paediatric Ophthalmology email
group are invited to participate in the online survey.
Questions consider routine clinical documentation
practices, participants’ perceived benefits and
barriers of EMR use, and, if appropriate, experiences
of use. Responses are collected during a two-month
period, and subject to univariate statistical analyses
using SPSS 23.0.0.0.
4.1.2 Interviews
Paediatric ophthalmic clinicians and researchers are
invited to participate in semi structured interviews to
further investigate perceptions of the existing health
information technology landscape and the
information flows between academic and clinical
communities. Interviews then explore the user-
defined requirements of a paediatric ophthalmic
EMR system. Using the nVivo software, qualitative
thematic analyses are applied to identify themes in
the responses and any differences between user
groups.
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4.1.3 Time-Motion Study
Qualitative observational data on what medical
records are used for, and by whom, are collected in
parallel to quantitative time stamps for various
predefined clinical activities (for example reading
notes, writing notes, talking to patient, examination)
in a representative sample of paediaitric
ophthalmology outpatient clinics at Great Ormond
Street Hospital, London. At the end of each
observational session, - following a single clinician
for a whole clinic these data are linked to
anonymised demographic and diagnostic data for the
patients observed.
Thematic and statistical analyses are used to
compare documentation behaviours between the
different clinical user groups and the patient groups
included in the study.
4.1.4 Medical Record Review
During a three-week period, the paper-based medical
notes produced within Great Ormond Street Hospital
paediatric ophthalmology outpatient clinics are
reviewed. The individual data items written in the
notes are identified and grouped into sets, defined as
the list of items documented by a single clinician
during a single patient consultation. Diagrams are
recorded as one data item, for example ‘fundus
diagram’. Items documented for each eye are
recorded as two sequential items; items within each
set are ordered as they appear in the medical notes.
Similarities between sets are calculated using
pairwise sequence alignment techniques, adapted
from the Needleman-Wunsch algorithm (Needleman
and Wunsch 1970), traditionally applied in genetic
sequence analyses. The resulting similarity scores
are used to drive the sequence-dependent clustering
of sets. A principle component analysis is then
performed on cluster membership information,
considering the documenting clinician’s role and
demographic data, and patient demographic and
disease data, to explore the factors influencing
variations in clinical documentation patterns.
The resulting maximal data set is then aligned
with data sets or protocols from existing research
studies, to consider the suitability of EMR data for
secondary research purposes.
4.2 Design Phase
To apply and test the EMR requirements elicited
within this PhD research, a series of data collection
tools are being developed as case studies. Software
design work focuses on integrating a flexible range
of data capture methods, including drawing tools
and more standardised drop down menus, text entry
or tick boxes, to create electronic forms for the case
study scenarios.
4.2.1 Software Development
Software is coded to create web based data capture
tools, utilising HTML form and canvas objects,
building on existing work within the JavaScript-
based open source medical drawing software
repository, EyeDraw, from the OpenEyes
Foundation (2015). Separate JavaScript modules for
each drawing element are written and then compiled,
following the EyeDraw workflow.
Working groups, consisting of six to eight
clinical experts working within the field, are
established via email to review the data capture
tools. Feedback is requested on individual tool
elements, or complete forms as necessary.
Participant opinions are shared amongst the group to
encourage discussion and reach consensus on design
elements.
4.3 Validation Phase
4.3.1 User Acceptability Testing
The final phase of this research involves users
assessing the usability the effectiveness,
efficiency, and user satisfaction, as previously
defined of the data capture tools. Testing is
completed online; potential users from across the
NHS are invited to undertake tasks using the
software. Tasks are designed to replicate real word
clinical activities, and the uses of the software
prioritised by users, as defined during the
exploratory phase of this research. Participants’
ability to complete the task is recorded, in addition
to the position of every mouse click the click
flow” during each task, to measure the
effectiveness and efficiency of the software.
Participant feedback is invited upon task completion
via a combination of Likert items to quantify user
satisfaction against the requirements identified by
potential users in previous stages of this research,
and open-ended free text questions for qualitative
comments on the overall suitability of the software.
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5 EXPECTED OUTCOME
Upon completion of this doctoral research we hope
to have developed and tested a series of software
applications suitable, as defined by potential users,
for use within NHS paediatric ophthalmic care.
Although we hypothesise the chosen user-
centred methodology will produce both useful and
useable software, further work will be required upon
completion of this research to assess the suitability
of the outputs when integrated into the “real world”
NHS information system. Hence a secondary
outcome of this research will be the provision of an
evidence base to guide future software development
within the field. This evidence base will provide a
description of current clinical practices within
paediatric ophthalmology to which comparisons and
suitable evaluations may be drawn following health
information technology implementation in this
environment.
6 STAGE OF RESEARCH
Our national survey identified 7.8% of the paediatric
ophthalmic clinicians who responded (N=7 of 90)
used EMRs for the majority of their paediatric
patients. However, 64.4% reported prior experience
using an EMR. These individuals with previous
experience (N=58) were significantly more like to
identify ‘difficult-to-navigate system designs’
(69.0% vs 41.4%, P=0.013), ‘poor user interface’
(62.1% vs 34.5%, P=0.015) and ‘inability to
integrate EMR with other clinical IT systems’
(67.2% vs 31.0%, P=0.002) as barriers but
‘improved communications with patients’ (43.1% vs
18.8%, P=0.020) as a benefit of routine EMR use.
Overall, participants most frequently identified
‘software functionalities not meeting clinical needs’
as the biggest barrier (25.3%) with the biggest
benefit cited being ‘increased document legibility’
(23.2%), whilst 3.33% perceived no benefit at all.
Therefore, despite the movement to universal
EMR-adoption in the NHS, routine use within
paediatric ophthalmology is uncommon and more in
keeping with uptake in paediatrics (Leu 2012) than
general ophthalmology (Boland et al. 2013) in other
countries.
This initial research indicates there is a great
need for a user-centred approach, to identify and
align EMR software with clinical needs, overcoming
the largest perceived barrier of users. Accounting
for such user perceptions throughout the subsequent
design phase of this research is more likely to ensure
the product overcomes barriers challenging use and
delivers the benefits valued by paediatric ophthalmic
clinicians.
Additional, more in depth insights from
interview and clinical observational data will be
combined with these results to define EMR
requirements for paediatric ophthalmology,
considering both user-defined and user-observed
factors as is important in successful UCD
(International Organisation for Standardisation
2010). This will complete the first, exploratory
phase of the doctoral research. Next software will be
iteratively developed and tested against the user-
centric requirements, to assess the success of the
methodology for EMR development within
paediatric ophthalmology set in the NHS
information system.
REFERENCES
Blumenthal D. Launching HITECH. The New England
Journal of Medicine. 2010; 362:382-5.
Boland MV, Chiang MF, Lim MC, Wedemeyer L, Epley
KD, McCannel CA, et al. Adoption of electronic
health records and preparations for demonstrating
meaningful use: an American Academy of
Ophthalmology survey. Ophthalmology. 2013;
120:1702-10.
Chiang MF, Boland MV, Brewer A, Epley KD, Horton
MB, Lim MC, et al. Special requirements for
electronic health record systems in ophthalmology.
Ophthalmology. 2011; 118:1681-7.
Chiang MF, Boland MV, Margolis JW, Lum F, Abramoff
MD, Hildebrand PL, et al. Adoption and perceptions
of electronic health record systems by
ophthalmologists: an American Academy of
Ophthalmology survey. Ophthalmology. 2008;
115:1591-7.
Chiang MF, Read-Brown S, Tu DC, Choi D, Sanders DS,
Hwang TS, et al. Evaluation of electronic health
record implementation in ophthalmology at an
academic medical center (an American
Ophthalmological Society thesis). Transactions of the
American Ophthalmological Society. 2013; 111:70-
92.
European Commission. eHealth Action Plan 2012-2020 -
Innovative healthcare for the 21st century Brussels
2012. Available from: http://ec.europa.eu/
information_society/newsroom/cf/dae/document.cfm?
doc_id=4188. Accessed April 20 2015.
Greenhalgh T, Stramer K, Bratan T, Byrne E, Russell J,
Potts HW. Adoption and non-adoption of a shared
electronic summary record in England: a mixed-
method case study. BMJ. 2010; 340:c3111.
DCBIOSTEC 2017 - Doctoral Consortium on Biomedical Engineering Systems and Technologies
14
International Organisation for Standardisation. ISO 9241-
11: Guidance on Usability. Geneva, Swizterland.
1998.
International Organisation for Standardisation. ISO 9241-
210: Ergonomics of human-system interaction. Part
210: Human-centred design for interactive systems.
Geneva, Swizterland. 2010.
Leu MG, O'Connor KG, Marshall R, Price DT, Klein JD.
Pediatricians' use of health information technology: a
national survey. Pediatrics. 2012; 130:1441-6.
Martikainen S, Ikävalko P, Korpela M. Participatory
interaction design in user requirements specification in
healthcare. Studies in health technology and
informatics. 2010; 160:304-8.
Needlemann S B, Wunsch C D. A general method
applicable to search for similarities in the amino acid
sequence of two proteins. Journal of Molecular
Biology. 1970; 48:443-53.
NHS England. Five year forward view 2014. Available
from: http://www.england.nhs.uk/wp-content/uploads/
2014/10/5yfv-web.pdf.
OpenEyes Foundation. The EyeDraw code repository.
2015 [accessed 9 September 2015]. Available from:
https://github.com/openeyes/eyedraw.
Ratwani RM, Fairbanks RJ, Hettinger AZ, Benda NC.
Electronic health record usability: analysis of the user-
centered design processes of eleven electronic health
record vendors. Journal of the American Medical
Informatics Association : JAMIA. 2015; 22:1179-82.
Redd TK, Read-Brown S, Choi D, Choi D, Yackel TR, Tu
DC, Chiang MF. Electronic health record impact on
productivity and efficiency in an academic pediatric
ophthalmology practice. J AAPOS. 2014; 18:584-9.
Saleem JJ, Plew WR, Speir RC, Herout J, Wilck NR,
Ryan DM, et al. Understanding barriers and
facilitators to the use of Clinical Information Systems
for intensive care units and Anesthesia Record
Keeping: A rapid ethnography. International journal of
medical informatics. 2015.
Spooner SA. Special requirements of electronic health
record systems in pediatrics. Pediatrics.
2007;119(3):631-7.
Teixeira L, Ferreira C, Santos BS. User-centered
requirements engineering in health information
systems: a study in the hemophilia field. Computer
Methods And Programs In Biomedicine.
2012;106:160-74.
US Department of Health and Human Services. Health
information technology: standards, implementation
specifications, and certification criteria for electronic
health record technology, 2014 edition; revisions to
the permanent certification program for health
information technology. 45 CFR 170. 2012. Available
from: https://federalregister.gov/a/2012-20982.
Accessed January 6 2016.
Health Informatics for Paediatric Ophthalmology - Designing Useful, Usable Information Systems
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