Predicting a way to better health

Was the cause too much spicy food or a life-threatening irregular heart rhythm? For a patient recently released from the hospital following a heart attack, that isn’t a trivial question when she returns in discomfort. If it is after hours, an expensive trip to the emergency room would be the only way to know for sure.

Geneia would like to change that. The health care technology and consulting company is working with clinical information, medical records and wearable device data to better understand when a trip to the hospital is absolutely necessary – even before the patient realizes it. The company’s goal is to help health care organizations deliver better care at a lower cost. It currently serves 750,000 individuals through health care payers, hospital systems and employer organizations.

The company’s premise is simple: Wearable medical devices (such as those that can unobtrusively record an EKG reading) are the future, but not unless medical information can be analyzed quickly to accurately predict when intervention is necessary. For the analytical component of its business, Geneia uses SAS®.

“The home is going to be where care is delivered both physically and virtually,” notes Mark Caron, Geneia’s Chief Executive Officer. “We want to be the leader in that marketplace.”

Starting with data fundamentals

Before Geneia can reach the point of determining whether a patient is about to have another heart attack – or just ate too many burritos – it needed to grapple with the data streaming in from medical records. Health organizations have struggled with this in the past. By the time the data is pulled into one file to analyze, months would pass. “There were just these islands of data out there,” Caron says, adding that he believes it is the key reason highly touted care management programs have failed to deliver on the promise of lowering the costs of treating the chronically ill. If it takes months to figure out that a certain person with diabetes is at risk to be re-hospitalized, that person has already been back in the hospital. “SAS Analytics helps us to accurately predict a patient’s likelihood to follow treatment, select a plan or develop complications,” Caron explains.

Geneia uses SAS in building its Theon platform, an all-source data and analytics platform that helps identify and care for patients and populations in accountable care organizations (ACOs) – groups of providers who band together to deliver coordinated high-quality care to Medicare patients, patient-centered medical homes and pay-for-performance arrangements. Theon’s analytics are customized to the role of the care team member and personalized for patients.

Theon sits on top of electronic medical record files, sifting through data not only to snap a picture of the patient’s health at that point, but also to predict what will happen next and make suggestions to counteract potential problems. Data is mined in multiple ways to better recommend a next-best course of treatment. For an older individual living alone with little social support, it might recommend more intensive care management, at home nurse visits or a prescription medicine review. For the otherwise healthy young mom with asthma, it might simply put a note in the chart to make sure the physician reviews medications at the next visit.

“We’re looking to build in learning engines to solve complex population and individual health problems,” Caron says.

The home is going to be where care is delivered both physically and virtually.
Mark Caron

Mark Caron
Chief Executive Officer

Making wearable devices meaningful to managing care

With a platform to analyze data, Geneia is making wearable medical devices meaningful to preventive health. Geneia is using these constant streams of data to look for the subtle, early signs of trouble that must be checked. Otherwise, wearable devices will simply be expensive gadgets that could create unnecessary anxiety or added cost. “We can bring all this data in the Theon application and begin to sense earlier than ever before when health might start to fail,” explains Heather Lavoie, President and Chief Operating Officer of Geneia. Theon is showing early success. An ACO adopted the platform to improve patient care and drive down costs. In less than 20 minutes on the platform, this client found:

  • A list of patients discharged from the hospital in the past 10 days along with a smaller, targeted list of those who would benefit from home monitoring to avoid future emergency room visits and potential readmission.
  • One patient currently in the hospital who had 13 prior admissions as well as more than 200 specialty visits and 150 prescriptions.
  • Ten patients with more than $100,000 in medical costs who had not been seen by their primary care physician in more than 12 months.
  • Two physician practices with significantly higher prescription costs than their peers, along with the information needed to remedy the situation.

Broadening the use of analytics

The information from analytics (with and without wearables) has multiple uses beyond high-yield wins like reducing readmissions. Health insurers and employers can study data to better understand which hospital systems provide the best care, and an employer can understand what types of wellness programs actually pay dividends and then customize the marketing of those plans. Rather than everyone getting a brochure for a 5K race, for instance, employees who have run them, or are in the demographic to run one, would get a brochure. And individual patients can get customized information on what types of tests they need or behaviors they should change to optimize their health. “Theon helps to support all of this on one platform,” Lavoie says.

Geneia Logo

Challenge

Use data effectively to make meaningful decisions about using wearable devices to monitor health and timely intervention for patients at risk of serious illness.

Solution

SAS® Analytics

Benefits

  • Better target care management resources to the patients most in need and most likely to participate.
  • Reduce readmission rates.
  • Reduce care gaps.
  • Help customers manage overall costs.

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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