Running Head: HIE 1
2-2 Short Paper: Technology and Data Extraction Techniques
Lauretta Krakue
HIM 350
SNHU
HIE 2
Technology lies in the central position of Health Information Exchange systems and
ensures that these systems effectively serve the intended purpose in healthcare settings. One of
the main technical requirements of HIE is related to architectural models and data source
integration. The architecture that is adopted mainly influences how data and information flow
within the system and meets the needs of the users. Repositories and registries also serve as
important technologies that ensure that the involved organizations are able to share health-related
data in an efficient and convenient manner. An Enterprise Master Patient Index (EMPI) acts as a
key technology that helps to maintain data about each and every patient in an accurate and
consistent manner (DelVecchio & Holman, 2017). Another important technology that would be
required while working on the new HIE system is Record Locator Service (RLS). Its main
function would be to provide the ability to identify the location where records are situated, based
on criteria like person ID, and/or record data type. There is also the need to focus on
technologies relating to the security and privacy aspects relating to the new HIE system. As the
HIE system would be connected to diverse source systems, the adoption of a robust
cybersecurity framework would be integral. Thus, antivirus software, firewalls, and/or intrusion
detection and prevention systems could be integrated so that the possibility of malicious actors to
violate and invade the network could be restricted considerably (Health Information Exchange
functionality and technology, 2014). Apart from these security tools, blockchain technology,
could also be incorporated so that the level of security, privacy, and interoperability of the
healthcare data could be further strengthened (Esmaeilzadeh & Mirzaei, 2019).
Extraction of data from the technologies using the Hybrid HIE model
The Hybrid HIE model would play a cardinal role by impacting the data extraction
process from the identified HIE technologies. The hybrid architecture would influence the data
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extraction by mainly relying on the use of care coordination as well as population health
management instruments (Bresnick, 2015). For example, a matching engine such as a master
patient index would be used that would help to not only extract data from a centralized data
warehouse but to also manage admission, discharge as well as transfer-related data. All the data
under this HIE model would be interconnected with the centralized infrastructural elements. The
data would be mainly extracted from the central repositories, and the information would be
added to the Electronic Health Records (EHR) data so that it could be effectively and
strategically used by member hospitals belonging to the network. Both the centralized and
decentralized attributes of the new HIW model would come into play and influence the
extraction of health-related data. The specific data types that would be extracted from the
centralized infrastructural components include patient identifiers, diagnoses, procedures and
protocols, details relating to medication, laboratory results, etc. (Ehrenstein et al., 2019). The
coordination aspect of the hybrid HIE model would also ensure that the physicians and doctors
are able to use the Record Locator Service for locating as well as accessing patient information
that has been shared by member hospitals within the network.
Analysis of data
The proper analysis of data from the identified technologies would be of cardinal
importance so that it could be transformed into insightful and useful information. In order to
make sure the new HIE system is able to function optimally, the focus on advanced analytics at
diverse levels would be integral. In fact, it would have a direct implication on the improved
health outcome of the patients as well as the core objectives of the healthcare organization (HIE
data and an analytics platform: A key to PHM Goals. Health Catalyst, 2021). While performing
the data analysis, the role of centralized components of the model would play a key role as it
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would help to get a comprehensive insight into the information that is available within the
system. An important aspect that must be taken into consideration while analyzing the data is
high-quality data quality reporting. Suitable reporting quality measures would have to be
established so that the input from all the players from within the network, which form a part of
the centralized component, is able to function in a streamlined manner. The application of Master
Patient Indexes (MPI), as well as integrated terminology management tools, would be vital to
clean and normalize health data for the purpose of analytics and reporting. In order to analyze
the health data comprehensively, the data analysis process must be conducted at the source, in
the network, and at the end-point as well. Such a comprehensive analysis could strengthen the
role of the HIE system in the healthcare setting.
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References
Bresnick, J. (2015, February 19). How Health Information Exchange Models Impact Data
Analytics. HealthITAnalytics. Retrieved November 8, 2021, from
https://healthitanalytics.com/news/how-health-information-exchange-models-impact-data-
analytics.
DelVecchio, A., & Holman, T. (2017, August 10). What is Enterprise master patient index
(EMPI)? - definition from whatis.com. SearchHealthIT. Retrieved November 8, 2021, from
https://searchhealthit.techtarget.com/definition/master-patient-index-MPI#:~:text=An
%20enterprise%20master%20patient%20index,registered%20by%20a%20healthcare
%20organization.&text=An%20EMPI%20ensures%20that%20every,all%20systems%20of
%20hospital%20data.
Ehrenstein, V., Kharrazi, H., Lehmann, H., & Taylor, C. O. (2019). Obtaining Data From
Electronic Health Records. InETools and Technologies for Registry Interoperability,
Registries for Evaluating Patient Outcomes: A User’s Guide, 3rd Edition, Addendum 2
[Internet]. Agency for Healthcare Research and Quality (US).
Esmaeilzadeh, P., & Mirzaei, T. (2019). The potential of blockchain technology for health
information exchange: experimental study from patients’ perspectives.EJournal of medical
Internet research,E21(6), e14184.
Health Information Exchange functionality and technology. (2014). Retrieved November 8,
2021, from https://chimecentral.org/wp-content/uploads/2014/11/Health-Information-
Exchange-Functionality-and-Technology-Selection-Crite....pdf.
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HIE data and an analytics platform: A key to PHM Goals. Health Catalyst. (2021, August 3).
Retrieved November 8, 2021, from https://www.healthcatalyst.com/insights/HIE-data-
analytics-platform-key-phm-goals/.