DNP 805 How could the EHR database facilitate this type of integration between clinical and administration systems

DNP 805 How could the EHR database facilitate this type of integration between clinical and administration systems

DNP 805 How could the EHR database facilitate this type of integration between clinical and administration systems

Electronic Health Record (EHR) are used in our healthcare organization and widely used to research as well. The validity of the results is dependent upon the assumptions of the healthcare system. EHR based data have challenges and some threats to validity and includes target population, availability and interpretability of clinical and non-clinical data. EHR includes socioeconomic status, race, and ethnicity that can be compared. Availability of data for fundamental markers of health are important for identifying inequities. The data has the ability to capture individuals clinical trials , data sets and measures the outcome that has potential risk factors. The EHR can be robust, informative and important to the understanding of health and disease in the population.

The Veterans Health Administration is a unique healthcare organization that provides good insight into the implementation of a population health approach to vaccine acceptance. I work at the VA and I can say that we cater to a special population in the community. The COVID-19 pandemic and vaccine hesitancy, and has been a threat in public health. Population health approach to vaccine acceptance using EHR-based tools can greatly impact vaccination rates in the healthcare system. Vaccine hesitancy—“the reluctance or refusal to vaccinate despite the availability of vaccines”—was identified as a “top 10” threat to global health in the years leading up to the COVID-19 pandemic. Vaccine hesitancy on a large scale focuses in voices of authority, engaging health care workers, scientists and strategies are addressed. The size and scope of the Veterans Health Administration, the characteristics of EHR primary focuses in health population, record of high quality preventive care and implementation of an evidenced-based framework to address vaccine hesitancy. The goal is to improve clinical and operational vaccine uptake. Steps that improve vaccine acceptance includes the identification of education for clinicians and veterans. Development of vaccine acceptance tools and application of population health approach will readily available.




Centers for Disease Control and Prevention. COVID Data tracker. Available at: Accessed September 1, 2021.


Ni K, Chu H, Zeng L, et al. Barriers and facilitators to data quality of electronic health records used for clinical research in China: a qualitative study. BMJ Open. 2019;9(7):e029314. doi: 10.1136/bmjopen-2019-029314. [PMC free article] [PubMed] [CrossRef] [Google Scholar]


Verheij RA, Curcin V, Delaney BC, et al. Possible sources of bias in primary care electronic health record data use and reuse. J Med Internet Res. 2018;20(5):e185. doi: 10.2196/jmir.9134. [PMC free article] [PubMed] [CrossRef] [Google Scholar]


World Health Organization. Ten threats to global health in 2019. Available at: Accessed September 1, 2021.

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The electronic health record EHR or the electronic medical record (EMR) is one of the most important sources for data analysis. It can be used today to drive decision-making in public health, identify risk factors for infectious diseases and treat them, and provide the continuity of care among various medical institutions while improving the quality of healthcare and continue to push forward medical and scientific research (Wang, 2019). Data Integration is the process of collecting a cluster of raw data from different sources and combining them into one source and it is stored and distributed to various applications from the storage place as new data. So, data mining would yield great knowledge of information needed to provide useful insights for research that would enable the compatibility of the EMR with different hospitals. It is the process of merging the systems from two different companies into one centralized data set. So, the integration and interoperability of healthcare data from different sources of information and communication technology (ICT) in a region or a country is of the utmost necessity for care and treatments in hospitals (Sreemathy, Naveen Durai, Lakshmi Priya, Deebika, Suganthi, & Aisshwarya, 2021), (Wang, 2019).

Integration is often times looked upon as easy and just inputting data into a system but it is beyond that. The systems that have targeted only the technical aspects has led to many failures because the two systems are not built the same and may have different levels, and vendor policies, so there is a need to include the social factors as well and the broader context in the integration process (Bjørnstad, & Ellingsen, 2019).

The patient population that I would like to integrate their data information would be the chronic heart failure (CHF)

DNP 805 How could the EHR database facilitate this type of integration between clinical and administration systems
DNP 805 How could the EHR database facilitate this type of integration between clinical and administration systems

patients. It is a chronic debilitating disease with a very high mortality rate and severe symptom burden for a long duration. The physical symptoms of CHF are shortness of breath (SOB), Dyspnea, pain, fatigue, decreased physical activity, anxiety and depression because of the declining quality of life (QoL), (Siouta, Heylen, Aertgeerts, Clement, Janssens, Van Cleemput, & Menten, 2021). The integration data from this population would be the patient demographic which includes the age, gender, allergies, weight, admitting symptoms, prior diagnosis, history and physical with any chronic symptoms such as dyspnea, lower extremity edema, any use of oxygen, medications, laboratories, diagnostics, procedures, treatment care plans, and any tolerable physical activity. For there to be an integration between the clinical and the administrative systems, the integration process has to comply with the ethical and legal standards of the facilities and the regulators. For all the clinical and administrative systems to integrate, there are integrative systems in place like the enterprise resource planning systems, enterprise application integration, component ware, and middleware. Also, the standardization of systems is also necessary with integration and many more. The most recent being the open EHR standard 17 and international initiative to structure and standardize clinical knowledge by global consensus (Bjørnstad, & Ellingsen, 2019).

IT systems in hospitals support cooperative work. Schmidt and Simone28 argue that cooperative work interleaves distributed tasks; articulation work manages the consequences of the distributed nature of the work. Hence, information technology (IT) systems in hospitals need coordination and articulation work to function (Bjørnstad, & Ellingsen, 2019).

Improving the processes for patients and providers with the policy approaches must be evaluated to make sure that they remove unnecessary steps and complications for patients, while decreasing administrative burdens for providers. Standards and approaches must reflect how information flows through the health care system, the technical systems that are needed, and the crucial role of health information professionals play in translating across clinical and administrative domains. Also, the sharing of health information across payers and providers requires consideration of privacy policies, to ensure that only the minimum necessary information is shared, and they are not used beyond the specific transaction limited (American Health Information Management Association (AHIMA), 2020)


American Health Information Management Association (AHIMA). (2020, February). AHIMA Policy Statement on Integrating Clinical and Administrative Health Data. AHIMA Home.

Bjørnstad, C., & Ellingsen, G. (2019). Data work: A condition for integrations in health care. Health Informatics Journal25(3), 526-535.

Siouta, N., Heylen, A., Aertgeerts, B., Clement, P., Janssens, W., Van Cleemput, J., & Menten, J. (2021). Quality of life and quality of care in patients with advanced chronic heart failure (CHF) and advanced chronic obstructive pulmonary disease (COPD): Implication for palliative care from a prospective observational study. Progress in Palliative Care29(1), 11-19.

Sreemathy, J., Naveen Durai, K., Lakshmi Priya, E., Deebika, R., Suganthi, K., & Aisshwarya, P. (2021). Data integration and ETL: A theoretical perspective. 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS)

Wang, Z. (2019). Data integration of electronic medical record under administrative decentralization of medical insurance and healthcare in China: A case study. Israel Journal of Health Policy Research8(1).