5 Analytics Innovations in Healthcare
According to the Office of the National Coordinator for Health IT, 83% of doctors use electronic health records (EHRs). EHRs are digital records that present a comprehensive picture of the patient’s history. Some older doctors and smaller healthcare centers resist adopting EHRs because of the cost and complexity of the system, but those who fail to comply face Medicaid and Medicare reimbursement penalties.
Those who haven’t adopted EHRs are missing out on their benefits. The data in EHRs provides a wealth of information about both individual patients and larger at-risk populations. Medical professionals can easily access patient information and rely on its accuracy.
The bad news is EHRs can be a challenge to leverage for insights because much of the information they contain consists of doctor’s notes and scans. Text and image fall into the category of unstructured data, which is particularly hard to analyze. To improve patient care, the healthcare industry has enlisted the help of advanced analytics to conquer the challenge of complex medical data and enhance the security of medical records.
Here Are 5 Ways Analytics Are Transforming Healthcare:
1) Tracking Patient Health Outside of Appointments
To help reduce patient admissions and help patients stay healthier, many hospitals and other medical facilities are starting to use advanced analytics to detect problems in patients outside of the facility. Wearables, such as the Fitbit, and home monitoring devices keep track of vital signs like blood pressure, heart rate, and even activity level. Predictive analytics takes that data and forecasts when trouble is developing. When alerted of a problem, the nurse can contact the patient in time to take preventative action.
2) Identifying At-risk Populations
CrescentCare Health in New Orleans uses analytics to help improve outcomes for patients with the top chronic conditions reported in the area, including HIV and cardiovascular disease. Drawing on clinical and lab data, they used an algorithm to give each patient a score. Based on this score, healthcare professionals can identify at-risk patients and provide them proactive and individualized care.
3) Preventing Drug Abuse
According to the Center for Disease Control, prescription drug abuse is a huge and expensive problem. It costs the U.S. $55 billion every year. This is not to mention the cost of human life. In 2014, over 47,000 people died from prescription and illegal drug overdoses.
Data analytics enables pharmacies, doctor’s offices, and hospitals to track abnormal prescription drug activity so they can be alerted of potential abuse. After all, opioids, which can be found in prescription pain relievers and heroin, are the main driver for overdose deaths. The California Prescription Drug Monitoring Program (PDMP), for example, allows healthcare providers and pharmacists to access patient history information so they can detect patterns of drug abuse.
4) Fighting Healthcare Fraud
In a single year, the Center for Medicare and Medicaid Services (CMS) used predictive analytics to identify or prevent over $210.7 million in healthcare fraud. CMS commissioned Northrup Grumman and IBM to develop a fraud detection prevention system based on predictive modeling. The system is designed to generate alerts based on risk scoring that can stop payment on false claims. Healthcare providers need help detecting fraud because, as the Ponemon Institute reported, 50% of victims of medical identity theft who were surveyed didn’t report the error on an explanation of benefits.
Analytics take advantage of rules-based anomaly detection that can filter insurance claims. Healthcare providers receive an alert when a false claim pattern is identified, like someone having bypass surgery twice in one day.
5) Reducing Data Breaches
After the first half of 2016, the Institute for Critical Infrastructure Technology reported that 47% of Americans suffered a cyberattack on their medical records in the past 12 months. This number includes only the publicly reported breaches that affected 500 or more people. Medical records are a hot commodity on the dark web because they can fetch $60 per record on the black market compared to $15 for Social Security numbers.
While there is no single defense that can protect hospitals and medical centers against every attack, data analytics can add an extra layer of protection to prevent healthcare data breaches. Advanced data analytics like artificial intelligence can monitor system logs and traffic patterns to identify abnormalities such as failed password attempts and large data transfers.
The Future of Healthcare Analytics
With data analytics already improving patient care and protecting patient records for healthcare facilities harnessing its power, the healthcare industry is poised to enter the cognitive era. IDC predicts that by 2018, 30% of the healthcare industry will look to cognitive analytics that can learn and reason to gain the insights needed to personalize healthcare. IBM found that 95% of healthcare leaders who were aware of cognitive systems plan to invest in cognitive capabilities in the future.
By harnessing the power of cognitive analytics, healthcare providers can benefit from the machine learning and natural language processing necessary to understand complex doctor’s notes well enough to make diagnoses and propose treatments. For patients, cognitive analytics means better outcomes for their health.
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