Data Analytics for Healthcare
Health data analytics classify into four types — descriptive, predictive, prescriptive and discovery.
This data provides information about what has occurred. It reports concrete statistics and displays them in an easy-to-digest way, such as how many patients sought medical treatment during the previous month and the average patient waiting time. Health technology research is useful in resource planning or identifying opportunities for improvement.
This data forecasts the probability of an event occurring. For health care professionals, leveraging this information requires up-to-date figures and robust interoperability that centralizes data and enhances access. Health care data analysts who incorporate such solutions see better decision-making and proactive care opportunities sooner.
Where Does Health Care Data Come From?
There are many ways to collect health care data, including:
- Patient portals.
- Health-related apps.
- Wearable devices.
- Electronic health records.
- Personal health records.
- Master patient indexes.
- Electronic prescription services.
- Research studies.
- Online tools and databases.
Benefits of Using Data Analytics in Healthcare Organizations
Advantages to collecting and analyzing health data include:
Software applications detect critical patterns to quickly and precisely identify high-risk patients. These methods allow medical professionals to use more proactive treatments and preventive patient care methods.
More Complete Patient Health Records
Robust technology can integrate data from the Internet of Things (IoT) for more insights into patient health. For example, professionals can analyze information from fitness devices to deliver more personalized patient care.
Real-time insights combined with analysis of historical data help clinicians make more informed care decisions. This ability is especially valuable for health professionals treating complex conditions and working in high-stress atmospheres.