Large quantities of clinical data is now being collected and analyzed in order to improve patient care around the world using big data. Big data is paving way for reduction in cost and effort within the healthcare industry. A recent report in Health Care Insights highlights how the use of algorithms to analyze large amounts of data has led to lowering the overall spend within healthcare.
- A large chunk of healthcare budgets are depleted by a small concentration of patients that are likely to be high-cost. Developing algorithms to identify patients that account for high-cost spending and making these predictions available to clinicians will help improve and manage patient care.
- Often readmissions are due to false positive alerts and the use of algorithms to predict whether a patient is likely to be readmitted will help improve healthcare through proper clinical intervention and customized patient care.
- Effective prioritization leads to proper prediction of complications for first-time patients. Integrating an algorithm that integrated triage into the clinical workflow will help with tasks like proper clinical care unit and management of bed resources.
- Decompensation episodes through worsening of symptoms, mental illness, and increasing stress levels can lead to increased patient care costs. Developing algorithms to detect cases of potential decompensation can help reduce costs and increase quality of patient care.
- Adverse drug events are often costly in terms of monetary expenditure and patient well-being. Utilization of big data to prevent adverse drug events will help prevent patient morbidity and mortality.
- Big data can be used to combine various measurements of routine health care to predict the development of a chronic disease that affect multiple organ systems. This leads to optimization of treatment for diseases and thereby, reduces costs.
Are you a healthcare provider looking to reduce costs through the use of big data algorithms? Contact our team and we will help you find the best possible solution.