Healthcare environment is complex and dynamic thus an analytics platform is required to aid the CXO’s to keep pace with it. An ideal analytics platform will help in taking informed decisions by providing real-time actionable information at finger tips.
The insights starts with Descriptive Reporting and these are few general uses cases that we address:
Deeper insights by leveraging Advanced Machine Learning algorithms.
Find if any patient is getting re-admitted or coming back to hospital within 30 days of discharge, identify the reason for it and find ways to avoid it.
Identify the main reasons for claims denial by insurance companies, resolve issues and increase the cash inflow.
Identify which all patients can be contacted for follow-ups after surgery, routine checkups etc. thus increase the revenue. Find a treatment pathway that any patient should undergo to keep them healthy and enable physicians to detect any major disease before it happens. Physician can define proactive treatment pathways for upkeep of patient’s health.
Rank the physicians based on multiple criteria models. Gives insight into most productive/efficient physicians and also determine the profitability based on multiple factors.
Identify the number of patients who only visited a department and did not go to any other department, number of patients who initially visited a department and then went to another department. This helps in: Identifying departments which are most referred to in the facility
Provide enhanced care to a patient by monitoring the vital statistics in real-time using wearable devices. Physicians gets alerted virtually in real time to provide medical assistance as and when required.
Provide the best treatment by incorporating big data and data sciences to integrate and analyze internal and external data sources.
Simulate possible decisions to identify its impact and evaluate risk to reach the optimal next step. For e.g., what happens if 1 more physician / specialist is added and how will it impact the revenue and expenses.
Use predictive analysis to determine how many patients will be there at a given point of time and decide on the optimum staff required to provide quality care and reduced waiting time for patients.
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