Essay on Big Data Analytics in Healthcare

Financial Condition

Based on Joslin Diabetes Center's 2012 and 2013 financial statements, the healthcare facility is in a viable financial condition. In essence, the health facility reported increased total unrestricted revenue and gains of 80,116,904, 85,030,025, and 85,291,074 in 2011, 2012, and 2013 respectively signifying that the facility is doing better regarding obtaining new contracts and providing patient services among other investments. Besides, the facility has managed to increase the unrestricted net assets over the three years, from a decrease of $2,990,602 in 2011 to an increase of $1,743,181 and $3,436,016 in 2012 and 2013 respectively. Also, the health facility has made increased revenue from research contracts and grants in 2013 and 2012, which is approximated as $3,070,000 and $3,296,000 respectively. The increase in assets also signifies the betterment of the financial condition of the facility as it has increased from 2011 to 2013. For instance, in 2011, the total assets were $124,736,435, which the facility improved to $136,118,108 and $137,737,362 in 2012 and 2013 respectively. As such, the increase in revenues and total assets signifies an improvement of financial condition.

Healthcare Trends

There are various healthcare trends that can impact Joslin Diabetes Center. For instance, there is an increasing trend of capitalizing on big data and technology in the hospital settings. In fact, the advent of big data and technology are revolutionizing healthcare delivery in a variety of ways that were not foreseen before, notably in personalized care (Chawla & Davis, 2013). Through bid data and technology, Joslin Diabetes Center can utilize computer-generated pathways in delivering optimal care to individuals, which will improve the healthcare delivery (Kaufman et al., 2017). In addition, to capitalize on the trend of increased diversity, the facility needs to align its workforce to diversity by employing diverse staff in terms of culture, ethnicity, gender, socioeconomic factors, and race so as to ensure that the personnel can attend to the needs of the diverse population (Kaufman et al., 2017).

Opportunities and Challenges

The trends of increased technology and bid data provides Joslin Diabetes Center with an opportunity to adopt technologies that will support care management, as well as implement IT systems that will allow for effective decision-making among healthcare personnel. Besides, from big data, healthcare leaders have an opportunity to capture patient data via in-home monitoring devices, as well as utilize wearables remotely (Kaufman et al., 2017). Regarding diversity, Joslin has the opportunity to capitalize on the strengths of a diverse workforce as they can support the needs of a diverse population. The challenges however for implementing technology and capitalize on big data will mean that the facility will require additional finances, which the organization needs to plan. According to Raghupathi and Raghupathi (2014), there needs to be additional finances to capitalize on big data owing to technological implementation costs. It also requires competent personnel, as well as training the available workforce on how to use the technologies. Diversity challenges include resistance to change, communication, and ineffective policies for implementing diversity in the workplace.

Potential Implications for the Mission

Joslins mission is researching and finding a cure for diabetes, as well as ensuring that patients with diabetes live long and healthy lives. The trends of increased technology and use of bid data, as well as capitalizing diversity, has implication on the mission. For instance, big data will allow for effective research on diabetes, which when coupled with information technology can help monitor patients remotely. Besides, it will allow the facility to analyze diabetes patterns and improve health surveillance, which will ensure that Joslin achieves its mission of ensuring that diabetic patients live a long and healthy life. Diversity, on the other hand, will allow Joslin to take care of all diabetic patients efficiently regardless of their race, gender, socioeconomic status, ethnicity, and culture. Most importantly, it will allow for effective communications between the medical practitioners and the patients.

References

Chawla, N. V., & Davis, D. A. (2013). Bringing big data to personalized healthcare: a patient-centered framework. Journal of general internal medicine, 28(3), 660-665.

Kaufman, K., Chernew, M.E., Ehadollahi, S., Grant, H.R., Bisognano, M.A., Angood, P.B., Moore, R.S., Diamandis, P.H. (2017). Futurescan 20172022: The building blocks of transformation. Society for Healthcare Strategy & Market Development. Retrieved from http://trustees.aha.org/envtrends/Futurescan%20PPT%20for%20Trustees.pdf

Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: promise and potential. Health information science and systems, 2(1), 3.