IMPROVING THE QUALITY OF PRIMARY CARE DATA
WITH INTEROPERABLE STANDARDS
Wilfred Bonney
School of Business and Technology, Capella University, Minneapolis, Minnesota, U.S.A.
Keywords: Data quality, Primary care data, Secondary uses of data, Standards.
Abstract: The quest to improve the quality and safety of healthcare delivery has resulted in the development of many
interoperable standards. Most of these standards are developed so as to ensure that primary care data are
captured, represented and conveyed appropriately in integrated healthcare information systems. Appropriate
representation of primary care data will facilitate the secondary uses of the health data. Secondary uses of
primary care data have the potential to not only support the clinical decision-making process by healthcare
providers but also provide an evidence-based practice. In this paper, a literature review methodology is used
to explore how the quality of primary care data can be improved using interoperable standards.
1 INTRODUCTION
The use of healthcare information systems to record
primary care clinical data is significantly variable
among general practitioners (GPs) (S. de Lusignan
et al., 2004; Rollason, Khunti, & de Lusignan,
2009). In a study conducted in the UK to examine
the accuracy of primary care data reporting by GPs,
Gormley et al. (2008) found that “when GPs were
asked to record basic clinical information, for the
purposes of a primary care-based study, there was a
significant level of inaccurate reporting” (p. 209).
This variability could be attributed to lack of
interoperable standards and no standardized
approach to recording clinical encounters in
information systems at the primary care level.
Acknowledging the fact that lack of training and
support in using healthcare information systems
contribute to the incomplete and inaccuracies in
primary care data, S. de Lusignan, Hague, Brown, &
Majeed (2004) noted that there is little publication
on initiatives to improve data quality in primary
care. It is, therefore, essential that good quality data
is captured and stored in primary care computer
records (S. de Lusignan, 2006). Even though what
constitutes data quality and what interventions
promote high-quality data remains open to debate,
there is a general consensus among healthcare
providers that data quality should be characterized
by completeness, accuracy, currency, relevance,
accessibility and ‘fit for purpose’ (S. de Lusignan,
2006).
Improving data quality of diagnoses, procedures,
and medications is of great importance in healthcare
delivery. These data are used throughout the
healthcare system to prompt for other interventions
within the individual consultation (S. de Lusignan,
2006). Interoperable standards hold the promise of
improving clinical data quality, thereby, improving
the quality of data reporting by general practitioners.
The objective of this paper is to explore the best
practices for integrating interoperable standards with
primary care data so as to maximize its usefulness in
healthcare delivery. The first part of the paper gives
an overview of primary care data and secondary uses
of primary care data. In the second part, the focus is
on the key components of interoperable standards.
The third part focuses on the best practices for
integrating interoperable standards with primary care
data.
2 PRIMARY CARE DATA
The term primary care, as distinguished from
primary health care, is commonly reserved for
clinical activity that is primarily focussed on the
individual (Lee et al., 2009). Primary care data are
usually obtained when healthcare practitioners
record clinical encounters in healthcare information
446
Bonney W..
IMPROVING THE QUALITY OF PRIMARY CARE DATA WITH INTEROPERABLE STANDARDS .
DOI: 10.5220/0003119704460450
In Proceedings of the International Conference on Health Informatics (HEALTHINF-2011), pages 446-450
ISBN: 978-989-8425-34-8
Copyright
c
 2011 SCITEPRESS (Science and Technology Publications, Lda.)

systems. Most healthcare practitioners now use
electronic health records and/or electronic medical
records during consultation, both to guide and record
clinical care (Teasdale, Bates, Kmetik, Suzewits, &
Bainbridge, 2007). According to Teasdale et al.
(2007), the main driving force for the “ubiquitous
primary care uptake of clinical computer systems is
that they support both the clinical and business
processes of general practice” (p. 157).
Primary care data are used not only to support
direct clinical care but also to support a broad range
of secondary uses of health data including “support
of preventive care and health promotion; clinical
audit and clinical governance; national screening
and preventive campaigns; audits against national
standards; payment; national statistics; planning
future services; and resource allocation” (Teasdale et
al., 2007, p. 158).
Moreover, the increasing threat of bioterrorism
and emerging infections with pandemic potential
such as influenza has made primary care data very
crucial and a necessary product that cannot be
simply ignored by healthcare providers. This is
because primary care data will be needed at both
national and local level to inform and help those
managing a pandemic and bioterrorism (Smith et al.,
2007). These properties of primary care data has
contributed to the increasing movement in the
healthcare IT domain to “operationalize” primary
care data to support secondary uses of data such as
clinical decision support and evidence-based
practices.
3 SECONDARY USES
OF PRIMARY CARE DATA
Secondary uses of primary care data have the
potential to not only support the clinical decision-
making process by healthcare providers but also
provide an evidence-based practice. As clinicians
continue to adopt interoperable standards such as
electronic health records (EHRs) and electronic
medical records (EMRs) as the standard for clinical
practice, there is an expectation by healthcare
providers that new sources of detailed clinical
information will be created and stored. Those data,
combined with any existing clinical data, will
dramatically increase the breadth and depth of
information available for non-clinical applications
(Safran et al., 2007).
The secondary uses of primary care data is very
important because it “can enhance individuals’
health care experiences, expand knowledge about
diseases and treatments, strengthen understanding of
health care systems’ effectiveness and efficiency,
support public health and security goals, and aid
businesses in meeting customers’ need” (Safran et
al., 2007, p. 2). Health studies and research based on
the secondary use of health data contributes to our
present level of knowledge of the causes, trends and
natural history of diseases and symptoms (Safran et
al., 2007).
While many healthcare providers consider the
secondary uses of primary care data as a threat to the
integrity and confidentiality of individual health
information, the widespread use of personal health
information “outside of the primary care setting
often occurs with commercial intent as employers,
payers, and insurers attempt to fulfill business and
proprietary-oriented goals and objectives” (Safran et
al., 2007, p. 7). The migration of the primary care
data to support secondary uses of health data such as
clinical decision support and evidence-based
practices will ultimately require data mining
techniques and high computational resources that
might grow exponentially in the coming years.
4 INTEROPERABLE
STANDARDS
Interoperable standards aim to achieve semantic
interoperability by providing and satisfying the
information-sharing needs across care settings,
providers, patients, and population health care
environments (Halley, Sensmeier, & Brokel, 2009a).
The goal of using interoperable standards is to
minimize the technical barriers to adoption while
providing a migration pathway toward progressively
richer computer-processable content of clinical
information (Dolin, Alschuler, Boyer, & Beebe,
2006). Most of the available interoperable standards
could be categorized into three themes: functional
systems; classification and terminology; and
messaging and document standards.
The functional systems are made up of standards
such as Electronic Health Record (EHR); Electronic
Medical Records (EMR) and Personal Health
Record (PHR). Interoperable standards such as
EHR, EMR and PHR are gaining popularity in the
healthcare industry because of their ability to
support interoperability of integrated healthcare
information systems. These functional systems
provides a platform for clinicians to capture primary
care data in a standardized format while eliminating
IMPROVING THE QUALITY OF PRIMARY CARE DATA WITH INTEROPERABLE STANDARDS
447

the healthcare problems associated with paper charts
and human errors (Adler-Milstein & Bates, 2010;
Reti, Feldman, & Safran, 2009). EHR, EMR, and
PHR offer the promise of reducing medical errors,
improving disease management, and reducing the
overall costs of healthcare delivery (Reti et al.,
2009).
The classification and terminology standards are
made up of Systemized Nomenclature of Medicine -
Clinical Terms (SNOMED-CT); International
Classification of Diseases: Tenth Revision (ICD-10);
and Logical Observation Identifiers Names and
Codes (LOINC) (International Health Terminology
Standards Development Organization (IHTSDO),
2010; Logical Observation Identifiers Names and
Codes (LOINC), 2010; World Health Organization
(WHO), 2010). These classification and terminology
standards are very useful and provide the words and
phrases needed to consistently define and document
patient care and clinical encounters (Watkins et al.,
2009). For example, the ICD-10 code for Diabetes
insipidus is E23.2; the SNOMED-CT code for
Hepatitis B vaccination is 16584000 and the LOINC
code for Body mass index is 39156-5.
The messaging and document standards are made
up of standards such as Health Level Seven (HL7)
Version 3 Messaging and HL7 Clinical Document
Architecture (CDA). For example, the HL7 CDA
leverages XML technology and coded terminologies
to support a clinical document that can be
“transferred within a message, and can exist
independently, outside the transferring message”
(Dolin et al., 2006, p. 31). The HL7 CDA standard is
very effective in documenting clinical encounters at
the primary care level. On the other hand, the HL7
V3 messaging standard is very useful in transmitting
healthcare information across different healthcare
providers.
5 INTEGRATING PRIMARY
CARE DATA WITH
INTEROPERABLE
STANDARDS
The idea of integrating primary care data with
interoperable standards is of great necessity in the
healthcare IT community. The integration of
interoperable standards with primary care data is
very crucial in ensuring that primary care data are
captured, represented and conveyed appropriately in
integrated healthcare information systems.
Healthcare information systems record health da-
ta in two ways: coded or structured data; and free
text or narrative (unstructured data) (S. de Lusignan
& van Weel, 2006). Recognizing the fact that natural
language processing (NLP) has not yet developed to
the point to replace ‘coded’ clinical data, S. de
Lusignan and van Weel (2006) emphasized that
“coded data are needed because there are so many
ways that a clinical concept can be represented” (p.
255). There is an increasing consensus among
healthcare providers that the use of classifications
and terminology standards are very useful in
capturing structured data (S. de Lusignan et al.,
2004; Watkins et al., 2009).
Similarly, Rollason et al. (2009) found that
migrating general practitioners’ computer systems to
SNOMED-CT or to another more limited coding
system which would map to ICD-10 would enable
primary care systems to better support improved
standards of care. There is an expectation that the
use of SNOMED-CT in healthcare information
systems will provide an “opportunity to standardise
the use of codes across clinical computer systems,
removing the difficulties associated with the use of
different variants of the same coding system” (S. de
Lusignan et al., 2004, p. 154). This expectation has
contributed to the reason why clinical terminologies
such as SNOMED-CT and LOINC are getting larger
and popular, enabling clinicians to code a wider
range of clinical concepts (S. de Lusignan et al.,
2004).
According to Rollason et al. (2009) the
inconsistent data across GP practices could be
reduced in two ways: “first, the use of a code-set
with fewer diagnostic codes whilst still maintaining
an appropriate degree of granularity; and second, a
more standardised software for entering the data” (p.
117). The first requirement could be met using
terminology and classification standards such as
SNOMED-CT, LOINC and ICD-10 (IHTSDO,
2010; LOINC, 2010; WHO, 2010).
The standardized software requirement could
also be met with the use of interoperable functional
systems such as the EHR, EMR and PHR (Detmer,
Bloomrosen, Raymond, & Tang, 2008; Diamond &
Shirky, 2008; Follen et al., 2007; Jamal, McKenzie,
& Clark, 2009). The ability for functional systems to
“communicate with each other, share information,
and understand what is being shared is the
fundamental interoperability notion” (Halley et al.,
2009, p. 310). Both EHR and EMR can assist
physicians and practitioners in eliminating the
inconsistency of data collection at the primary care
level during consultations. Halley et al. (2009)
indicated that “it is through the interoperable
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exchange of health information that expected
decreases in costs will be realized, such as
eliminating duplicate tests, improving administrative
efficiencies, increasing access to patient clinical
results, and providing information to decrease
repetitive input” (p. 310).
6 CONCLUSIONS
This paper has discussed the importance of
improving the quality of primary care with
interoperable standards. There is no doubt that as
EHRs, EMRs, and PHRs continue to evolve and the
adoption of health information technology increases,
more health data will become readily available, with
predictable increased efforts to access and use these
data for various non-patient care purposes (Safran et
al., 2007). These secondary uses of primary care
data are very essential in preventing bio-terrorism;
monitoring diseases and ensuring health protection
surveillance. For example, a study conducted by
Smith et al. (2007) established the potential of using
electronic coded records from general practice for
health protection surveillance.
Using electronic coded primary care data will not
only help healthcare providers in the development of
clinical decision support systems and surveillance
systems but also provide the platform for primary
care researchers to conduct evidence-based research
(Gormley et al., 2008; Patel et al., 2005; Smith et al.,
2007).
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