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2-2 Short Paper: Technology and Data Extraction Techniques
HIM 350
SNHU
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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
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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 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 m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m
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(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 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. m 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.
HIE m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m
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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%2
0healthcare%20organization.&text=An%20EMPI%20ensures%20that%20every,all%20sys
tems%20of%20hospital%20data.
Ehrenstein, V., Kharrazi, H., Lehmann, H., & Taylor, C. O. (2019). Obtaining Data From
Electronic Health Records. In Tools 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. Journal of
medical Internet research, 21(6), e14184.
HIE m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m m
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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.
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/.
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