The health care industry produces large amounts of data on a daily basis. Most of these data used to be hard copies but, now organizations are gathering data electronically.
Healthcare analytics is the process of analyzing current and historical industry data to predict trends, improve outreach, and even better manage the spread of diseases. The field covers a broad range of businesses and offers insights on both the macro and micro level. It can reveal paths to improvement in patient care quality, clinical data, diagnosis, and business management.
When combined with business intelligence suites and data visualization tools, healthcare analytics help managers operate better by providing real-time information that can support decisions and deliver actionable insights.
There are mainly 7 data sources that produce the bulk of the data.
- Electronic Health Records (EHR): Clinical records with patient details.
- Laboratory Information Management system (LIMS): Contains lab results
- Monitoring and diagnostic instruments: Data from instruments like MRI.
- Pharmacy: Medication details of the patient
- Instruments and human tracking system: Data contains location information of instruments and people.
- Insurance claim and billing: Contains insurance claims and billing details
- Hospital Resources: Employee list and hospital supply chain details.
Areas where big data analytics has a huge impact:
Pre-adjudication and fraud analysis: Hospitals receives large numbers of insurance claims on a daily basis. Big data analytics can be employed to process large numbers of claims to reduce fraud and abuse.
Cost and Effectiveness: Data analytics can be used to compare the cost and effectiveness of treatments, public policies etc. Organizations can use cost and outcome data to check the effectiveness of medicines and stop prescribing medicines that are not effective.
Disaster planning: Both natural and manmade disasters will put tremendous pressure on the health care systems in that area. During a disaster, the demand for a particular service will increase way beyond its capacity. For example, during a flu outbreak, demand for ventilators will increase. Knowing the real-time location and availability of such facilities will be very helpful for the authorities in managing such disasters. Using data analytics, it is also possible to predict the outbreaks of some diseases and thus putting the authorities in a better position to manage it.
Effective resource management: Location tracking technologies like RFIDs are used to provide real-time management, identification, and tracking of instruments within an organization. Along with tracking instruments, now such technologies are increasingly being used to track and manage patients and staffs. Data from such services can be used to improve patient care, resource utilization, and staff management.
Patient Flow: Healthcare is a time critical service and data analytics plays a crucial role in ensuring smooth patient flow and reducing waiting period. Predicting patient surge will help the authorities take the necessary step to reduce patient waiting time thereby giving timely treatment.
Better Coordinated Care
Data analytics will revolutionize the healthcare industry through this type of streamlining, whether it is reducing administrative waste or facilitating coordination for nurses, doctors, and other medical professionals to take a holistic view of each individual patient’s health. This provides the ability for medical practitioners to coordinate care effectively and efficiently due to their access to shared data. Data analytics can reveal hidden patterns in quantitative information that can help medical professionals suss out ways to provide the best possible care.
The improvement to care coordination that data analytics provide also goes beyond caring for individual patients. Medicare-accountable care organizations are also implementing the use of data analytics to improve overall population health, though they tend to struggle with incomplete data sets.
Analysis of disease patterns and records of outbreaks can help medical professionals quickly react to or even prevent viral outbreaks that affect public health. The ability to predict outbreaks before they occur can help improve the overall quality of care provided as medical professionals will not have to expend huge amounts of resources to combat disease on a large scale.