1. Running head: DATA QUALITY AND INTEROPERABILITY IN EHRS THE US 1
Data Quality and Interoperability in Electronic Health Records in the U.S.
Courtney Quinlan
Metropolitan State University of Denver

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“In 2013, 78% of office-based physicians used any type of electronic health record
(EHR) system, up from 18% in 2001” (Hsiao C-J, & Hing E, 2014). Figure 1 below shows just
how much the use of EHRs has increased for 2001 to 2013.
Figure 1. Percentage of office-based physicians with EHR systems: United States, 2001–2013.
(Hsiao C-J, & Hing E, 2014)
This statistic from the Centers for Disease Control and Prevention (CDC) shows how big of a
role EHRs have become in health care. Many people, whether it be those working in health care
or patients receiving care, question the benefits of EHRs. Data quality seems to be one of the
larger issues on the health care end of using EHRs. Part of the problem with identifying high
quality data is that in order to be considered as high quality, it must conform to a unified
standard which is something the U.S. does not currently have (Wager, Lee, & Glaser, 2009).
Interoperability is another large issue in addition to data quality. Interoperability is defined as,
“the extent to which systems and devices can exchange data, and interpret that shared data”
which includes internal and external data transfer (himss.org/library). Though the U.S. does not
possess data or interoperability standards, it does have national and state organizations and laws
to help with this issue. Data quality and interoperability in EHRs can be improved by the use of

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the American Health Information Management Association’s (AHIMA) data quality
management model, adhering to Health Information Technology for Economic and Clinical
Health Act (HITECH), and practicing the facilitation of health information exchange through
agencies such as Colorado Regional Health Information Organization (CORHIO). This paper
will further explore the above mentioned organizations’ roles in bridging the gap in data quality
and interoperability in EHRs.
The American Health Information Management Association (AHMIA) is an organization
that is the leader in health information management (HIM) and is “working to advance the
implementation of electronic health records (EHRs) by leading key industry initiatives and
advocating high and consistent standards” (our story, ahima.org). AHIMA’s data quality
management model is helpful in that it sets a base for creating data quality standards by
indicating typical elements of health care data that should be continuously present no matter
what the use of the data or resulting information are for. See Figure 2 (Data quality
management, ahima.org). Figure 2 shows 10 characteristics of data quality and Table 1 gives
Figure 2. AHIMA Data Quality Management Model. (Data quality management, ahima.org).
Data Quality Management Domains
Application: The purpose for the data collection
Collection: The processes by which data elements are
accumulated
Warehousing: Processes and systems used to archive data and
data journals
Analysis: The process of translating data into information utilized
for an application

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brief explanation of the roles each data characteristic play in achieving quality data with
examples.
Data Type Role in Data Quality Example
Accuracy Has correct, valid values. Discharge summaries free of typographical
errors.
Accessibility Must be available to decision makers. Better insures accurate analysis.
Comprehensiveness Must be present and available to user. Relevant data may not be useful when
incomplete.
Consistency Must be consistent. No abbreviations with two different meanings.
Currency Data can become obsolete. Admitting and discharge diagnosis are different.
Definition Clear definitions must be provided so both
users have understanding.
Use of data dictionaries are good for this
purpose.
Granularity Data elements cannot be subdivided. Patients name should be stored as three data
elements.
Precision Relates to numerical data. Data must be
precise.
Figuring drug dosage,no rounding.
Relevancy Must be relevant to purpose for which
collected.
Patient's color preference is not relevant to care.
Timeliness Critical dimension in quality. Lab values must be available in timely manner.
Table 1. AHIMA Data Quality Characteristics (Wager, et. al., 2009, pgs. 47-48, 54).
As one can see, all of these characteristics tie directly into data quality and patient care. The
AHIMA library mentions that the initial point of capture of data for an EHR is the most crucial
because any further use of the data in the EHR will be based off this initial information
(assessing and improving, ahima.org). It is also noted in AHIMA’s library that, “quality data is
critical for patient care and safety, reimbursement, accreditation, quality initiatives, and
research” (assessing and improving, ahima.org). If more organizations followed a data standard
such as this for their EHRs, the U.S. would see a higher quality in health care which leads to
higher patient satisfaction leading to lower cost of care. To add, health information exchange
(HIE) is affected by poor quality data which in return affects interoperability. Interoperability is
not successful and is irrelevant if the data being shared are inaccurate. Unfortunately, there are
not many laws in place currently that force health care organizations to conform to a uniformed

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standard. Although, the Health Information Technology for Economic and Clinical Health Act
(HITECH) that was passed in 2009 is a good foundation to start on.
HealthIT.gov states that the HITECH Act of 2009, “provides HHS (U.S. Department of
Health and Human Services) with the authority to establish programs to improve health care
quality, safety, and efficiency through the promotion of health IT, including EHRs and private
and secure electronic health information exchange” (health it legislation, healthit.gov). To go a
bit further in detail, “the HITECH act calls for the implementation of a nationwide health
information technology infrastructure as well as a processes for evaluation, adoption, and
implementation of endorsed standards, implementation specifications, and certification criteria
for health IT” (select portions of, healthit.gov). Though the act promotes the above mentioned
ideas for enhancing data quality and consistency in EHRs and their interoperability, there has yet
to come an official standard for health care organizations to live up to. However, this act does
relate to and support the work of the Office of the National Coordinator for Health Information
Technology (ONC) and the 2015 Interoperability Standards Advisory. The ONC holds the
responsibility of advancing interoperability and connectivity of health IT with the goal of
electronic information having the ability to follow a patient wherever they may be
(interoperability roadmap, healthit.gov). The ONC will use the 2015 Interoperability Standards
Advisory as a model to help facilitate the identification, assess, and then determine what will be
the best standards for interoperability and how implementation should be carried out for the
health care industry to use for specific purposes (interoperability roadmap, healthit.gov). This
advisory will be what is considered an “open draft” since the process will be interactive with
both the public and the health care industry to create a discussion on what the best available
standards and overview the agreements and disagreements on the subject matter in order to make

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a solid decision when the time comes (interoperability roadmap, healthit.gov). Implementations
that the 2015 Interoperability Standards Advisory discover and use will help conform a data
standard for EHRs and health IT in general thus leading to higher data quality and improved
interoperability. The HITECH Act will help ensure these standards are adhered to. The
information here is focused on a national level which leads to the question of how things work
on the state level. Colorado has an excellent and rapid growing system in place for facilitating
health information exchange (HIE).
The organization in Colorado that is primarily used in HIE is called CORHIO, Colorado
Regional Health Information Organization. CORHIO is a nonprofit, public-private partnership
that is working towards the improvement of health care for Colorado state residents by using cost
effective and secure implementation of HIE (about, corhio.org). The organization has three
specific goals to achieve by this year, 2015, which are: “health information exchange deployed in
every community, 85% of all primary care providers and safety-net providers are meaningful
users of electronic health records (EHRs), and 85% of all providers statewide are meaningful
users of EHRs” (about, corhio.org). The Health Resources and Services Administration (HRSA)
defines meaningful use through three main components specified by the American Recovery and
Reinvestment Act which are: “1.) the use of a certified EHR in a meaningful manner, 2.) the
electronic exchange of health information to improve quality of health care, and 3.) the use of
certified EHR technology to submit clinical quality and other measure” (what is meaningful use,
hrsa.gov). Meaningful use directly ties into the data quality of an EHR in that; if information is
falsified for any benefit, i.e. reimbursement for personal gain, then the quality and validity of the
data are compromised and are unusable. There are four major areas in which CORHIO helps

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with data quality and interoperability in EHRs in the about section on CORHIO’s website which
are:
1. Time saving through faster access to information regarding patients and less of a need for
phone calls and faxes to obtain patient information.
2. Improving care through accuracy and standardized data transmission leaving less margin
of error and delays in treatment.
3. Reducing cost via streaming information exchange, less errors, i.e. unnecessary
medications, treatments, hospitalizations , and more efficient use of resources thus
increasing efficiency in IT spending.
4. Enhancing privacy by controlling access to health IT which leaves less of a paper trail
and one less possibility for an information security breach.
(about, corhio.org)
According to CORHIO’s website, the organization has seen growth in triple digits in 2014 along
with connecting to Denver, Colorado’s largest health system which was a huge feat for the
organization (facilitating health, corhio.org). This is one of the fastest growing state based HIEs
out there. CORHIO is a great organization that the U.S. should use as an example and starting
base for an international standard in determining quality and interoperability of EHRs due to its
immense success.
The last three paragraphs all discussed the benefits of quality data of EHRs and their
interoperability. An issue that needs to be address that was mentioned several times throughout
this paper was the security of information. Passing information electronically has many benefits
as listed above, but a major concern is this information being stolen. This information is highly
sensitive in that EHRs often include full patient names, addresses, birth dates, and social security
numbers. Pretty much all the information a dishonest person needs to commit identity theft and
other heinous crimes. According to an article on the Healthcare IT News’ website, “29.3 million
patient health records were compromised in a HIPAA data breach since 2009 and there was a
138 percent jump in the number of health records breached just from 2012” (McCann, 2014).

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This is staggering news for anyone to hear and raises the question, what is being done to prevent
breaches of patient information? Another article on Healthcare IT News’ website lists five ways
to avoid data breaches in health care. According to Healthcare IT News, these five ways are stes
toward avoiding breaches of data:
1. Conduct an annual HIPAA security risk analysis. This is already part of a requirement
per HIPAA, but it is suggested that organizations plan and budget in advance for it.
2. Inoculate yourself by encrypting data-at-rest. List encryption on all portable devices to
prevent data breach if an item, such as a laptop, is lost or stolen.
3. Conduct more frequent vulnerability assessments and penetration testing. Use good
antivirus and malware software to protect data and set monthly tests to ensure that
security issues are being fixed and new issues are detected sooner rather than later.
4. Invest in the security awareness of your workforce. Educate your employees on data
safety and also monitor them to be sure there are not any in house breaches occurring.
5. Engage with your business associates. You and your vendors are equally responsible for
the safeguarding of information.
(Manos, 2014)
I believe that even though patient data is at risk now more than ever, protecting such information
is far from impossible. The more organizations adhere to HIPAA, Health Insurance Portability
and Accountability Act, standards along with setting high standards for themselves, the more
safe patient information will be.
In conclusion, it is apparent that there is a great need for the U.S. to develop a national
standard for data quality and interoperability in EHRs. Use of AHIMA’s data quality
management model, complying with the HITECH Act, and using organizations such as CORHIO
for a base model, will help the nation take a step forward in attempts to achieve this standard.
An article on TechTarget.com titled CIOs Call for Interoperability at HIMSS 2015 gives a huge
call to action to Congress in regards to interoperability of health care information. Martin
Slominis, vice president for management information services and deputy CIO of the Wayne
State University Physician Group, states, “Congressional intervention is imperative to allow

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providers, patients and insurers to share health data and that we want the vendors to help us solve
problems, not compete with us, so data can go anywhere it could be used" (source 11). This
alone shows that many people in health care are seeking a unified data and interoperability
standard.

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References
American Health Information Management Association. (n.d.). Assessing and improving ehr
data quality (updated). Retrieved April 19, 2015, from
http://library.ahima.org/xpedio/groups/public/documents/ahima/bok1_050085.hcsp?dDoc
Name=bok1_050085
American Health Information Management Association. (n.d.). Data quality management model
(updated). Retrieved April 19, 2015, from
http://library.ahima.org/xpedio/groups/public/documents/ahima/bok1_049664.hcsp?dDoc
Name=bok1_049664
American Health Information Management Association. (n.d.). Our story: Get to know ahima.
Retrieved April 19, 2015, from http://www.ahima.org/about/aboutahima?tab id=story
Colorado Regional Health Information Organization. (n.d.). About. Retrieved April 19, 2015
from http://www.corhio.org/about.aspx
Colorado Regional Health Information Organization. (n.d.). Facilitation health information
exchange. Retrieve April 19, 2015, from http://www.corhio.org/
Health Resources and Services Administration. (n.d.) What is “meaningful use”?. Retrieved
April 19, 2015, from
http://www.hrsa.gov/healthit/meaningfuluse/MU%20Stage1%20CQM/whatis.html
Healthcare Information and Management Systems Society. (n.d.). What is interoperability?.
Retrieved April 19, 2015, from http://www.himss.org/library/interoperability-
standards/what-is-interoperability
HealthIT.gov. (n.d.). Health it legislation and regulations. Retrieved April 19, 2015, from
http://www.healthit.gov/policy-researchers-implementers/health-it-legislation
HealthIT.gov. (n.d.). Interoperability roadmap. Retrieved April 19, 2015, from
http://www.healthit.gov/policy-researchers-implementers/interoperability
HealthIT.gov. (n.d.). Select portions of the hitech act and relationship to onc work. Retrieved
April 19, 2015, from http://www.healthit.gov/policy-researchers-implementers/select-
portions-hitech-act-and-relationship-onc-work
Hsiao C-J, & Hing E. (2014). Use and characteristics of electronic health record systems among
office-based physician practices: United States, 2001–2013. NCHS data brief, no 143.
Hyattsville, MD: National Center for Health Statistics. 2014. Retrieved April 19, 2015,
from http://www.cdc.gov/nchs/data/databriefs/db143.htm
Manos, D. (2014). 5 ways to avoid health data breaches. Retrieved April 19, 2015, from
http://www.healthcareitnews.com/news/5-ways-avoid-health-data-breaches?page=1
McCann, E. (2014). Hipaa data breaches climb 138 percent. Retrieved April 19, 2015, from
http://www.healthcareitnews.com/news/hipaa-data-breaches-climb-138-percent

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Sutner, S. (2015). Cios call for interoperability at himss 2015. Retrieved April 19, 2015, from
http://searchhealthit.techtarget.com/news/4500244284/CIOs-call-for-interoperability-at-
HIMSS-2015
Wager, K.A, Lee, F. W., & Glaser, J.P. (2009). Health care information systems: A practical
approach for health care management. (2nd ed.). San Francisco, CA: Jossey-Bass.
Wager text