Big data analysis technology is rapidly developing, becoming an important characteristic of management. For example, IBM develops a super-computer that scans millions of scientific articles and utilizes machine learning to correlate symptoms and predict clinical outcomes (Cozzoli et al., 2022). Predictions have become a necessity; modern healthcare undergoes a transition from methods based on treating symptoms to patient-centric care involving predicting outcomes. With data analysis making it possible to predict dangerous illnesses’ development, lowering costs for all stakeholders by eliminating the need for expensive insurances and hospitalizations (The role of data analytics in Health Care, 2021). Other possible ways to decrease costs are managing supply chains and decreasing fraud. With the Internet being easily available, the launch of big data analytical systems will allow improving organizations’ functionality.
The first step to implementing analytics into healthcare organizations is to identify objectives, procedures, and key performance indicators. These measures should become standard for healthcare managers, allowing them to conduct monitoring and predicting analysis. To this end, they will receive special equipment connected to the main computer, including PDAs, trackers, and monitoring devices for different physical attributes such as temperature. According to Medtronic, such practice can cut costs by up to $535,000 annually via, for example, regular pulse oximetry of high-risk patients (HealthITAnalytics, 2021). For the patients, the technology will provide bedside computers to accumulate data, creating visual maps of infections and viruses spreading. The materials for their conditions they require will be managed better as well, ensuring that they will always have necessary medications on hand.
To collect all the necessary data, I would create a centralized way of storing and collecting all the information. A centralized virtual storage would gather and process data from every manager of the organization and send it to them based not only on their evidence, but their colleagues as well. For example, several managers and their subordinates treat unrelated patients with similar ailments. With their data being remotely analyzed and processed, they will gain more information from the patients to make predictions and prevent outcomes. If a patient still had to be hospitalized, big data systems will process it and mark the patient as prone to serious illnesses, providing them with necessary medications in the future (Miller, 2022). Other than providing income from these medications, this measure may prevent readmission penalties for the hospital.
Other options to increase revenue are marking patients who tend to miss their scheduled procedures, not paying as a result, and replacing their slots with those who do appear. Financial losses from dying patients will be controlled as well, since managers will be able to notice the inflow of patients and direct the staff accordingly, helping patients who need urgent care. The staff will have a say as well, providing feedback to the managers’ work. Thus, the key to increasing revenue through big data analysis is making customers pay while not endangering their health and putting emphasis on their treatment.
Thus, the usage of computer analytics in managing healthcare organizations will assist in the effectiveness of these organizations, providing care based on predictions and preventing serious illnesses. It will decrease costs due to preventing hospitalizations as well, and increase revenue due to replacing non-paying customers with the paying ones. Those patients who tend to arrive late will be directed to arrive in time and receive their treatment. Thus, I would apply computer-based machine analytics as it is a useful and universal tool.
References
Cozzoli, N., Salvatore, F. P., Faccilongo, N., & Milone, M. (2022). How can big data analytics be used for healthcare organization management? Literary framework and future research from a systematic review. BMC Health Services Research, 22(1). Web.
HealthITAnalytics. (2021). Predictive analytics, continuous monitoring cut medical costs by $535K. HealthITAnalytics. Web.
Miller, L. (2022). Data Analytics can improve financial performance and efficiency in Hospitals. VIE Healthcare Consulting. Web.
The role of data analytics in Health Care (2021). School of Health and Rehabilitation Sciences Online – University of Pittsburgh. Web.