DNP 825 How can large aggregated databases be used to improve population health?  Re: Topic 3 DQ 1

The adoption of electronic health records (EHRs) in healthcare systems as mandated by the US Department of Health and Human Services (HHS and some other great sources of healthcare data such as wireless health monitoring devices and behavioral social media sources the healthcare professionals can easily access abundant amounts of patient data that provide more significant insights of the patient health information. This wealth of databases form big data (Batarseh and Latif, 2016). Hernandez and Yuting Zhang (2017) define big data as notably large and complex databases that aggregate information of different types and scales, collecting data across time and distance from multiple sources, often requiring complex data processing applications. Further describing those big data that are used in the healthcare system as HER, administrative claims, clinical trial data, and data collected from smartphone applications, wearable devices, social media, and personal genomics services. Batarseh and Latif (2016) in their article explained how using big data helped to establish the vast majority of US citizens estimating up to 30 million individuals were diagnosed with the chronic diseases of diabetes and hypertension in 2010. This accounted for more than 80% of health system costs. As these chronic conditions are linked with other health-threatening complications, engaging these patients in preventative health education to empower them on how to take charge in improving their illnesses like lifestyle modification and follow-ups will not only improve the patient’s overall health but when health is improved, less medication is prescribed and subsequently reduce waste. Using the home blood pressure monitor that can report to the clinician’s office and some of the newer technological diabetes monitors like the Dexcom G6 pools data and aid in data aggregating.

References

Batarseh, F. A., & Latif, E. A. (2016). Assessing the quality of service using big data analytics: with application to healthcare. Big Data Research, 4, 13-24.

Hernandez, I., & Yuting Zhang. (2017). Using predictive analytics and big data to optimize pharmaceutical outcomes. American Journal of Health-System Pharmacy, 74(18), 1494–1500. https://doi-org.lopes.idm.oclc.org/10.2146/ajhp161011 https://lopes.idm.oclc.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=a2h&AN=125112221&site=ehost-live&scope=site