on 21 September 18
Medicine in many ways is a data-driven business. The numbers collected during office visits or as results of lab tests or imaging scans drive the decision-making and treatment plans.
Until recently, most of those numbers went into a patient's paper file. The information couldn't easily be shared or analyzed because it wasn't in a structured or digital format. The increased use of electronic medical records, mandated by the government, changes this.
As a subset of business intelligence, healthcare analytics applies statistical techniques, quantitative methods, and computer models to create a decision support system that enables health professionals to make better-informed decisions. The analytics fall into several categories, including descriptive analytics, which focus on past events; predictive analytics, which use the data to support what-if analyses; prescriptive analytics, which attempt to support proactive decision-making; and discovery analytics, to support the identification of unknown illnesses and develop medications to treat them.
These different techniques will have a major impact on the way modern medicine delivers care. Here are 5 examples of the impact:
1. Manufacturing Medicine
Medical and pharmaceutical research will use analytics to identify new drugs, analyze data collected while testing safety and effectiveness, and help refine the manufacturing process. Analytics can identify correlations between drugs and side effects, or discover new drugs through simulations and what-if analysis.
2. Better Insurance Coverage
Health insurance companies will use predictive analytics to understand their new customer base. Insurance companies will understand better how medicines work and also which individuals are vulnerable to health costs. Analytics will also be used to manage costs and detect fraud.
3. Tailored Health Care
Health care providers will use analytics to track their patient care. Clinical Decision Support systems provide real-time analysis of data to help physicians define the treatment plan. Analytics will enable analysis of outcomes as well to suggest improvements in treatment protocols. Predictive analytics will let hospitals identify patients most likely to require readmission and provide additional support services upon their discharge to ensure a better outcome.
4. Smarter Public Health Policy
Government will use analytics to combine clinical and administrative data to determine if public health spending is having the desired impact of improved public health outcomes. Since government is the source of many health dollars, analytics to identify fraud will be important here as they are for the insurance companies. Analytics can also let government plan for medications to stockpile for any anticipated epidemic.
5. Smarter Business Solutions
Employers will use health care analytics to reduce their healthcare expenditures. By understanding the health and wellness of their employees, wellness programs can be tailored to the needs of the population.
Interested in a career in this growing field? Get a RHIA degree from the University of Cincinnati to get into the field of Health Information Management.
This blog is listed under Data & Information Management Community