Jim needs to have his knee replaced. He is a 52-year-old former long-distance runner who has recently picked up on CrossFit and often wears a Fitbit. To schedule the surgery, he goes online and coordinates his family's calendar with the calendars of his surgeon and the pre- and post-operation nursing teams. He is asked a few personal questions: In the past year, did he ever have trouble covering co-payments? Does he have friends or family who can transport him to rehabilitation therapy? Does he have to climb stairs to reach his bedroom?
After a short wait he receives his Quality and Risk Report Card. The report card says he is an excellent candidate for total knee arthroplasty (TKA). However, his recent trip to the urologist for kidney stones and urinary tract infection (UTI) suggests prophylactic antibiotic therapy prior to the surgery to reduce the risk of surgical site infection. And, because of his lack of adherence to prior clinical treatment plans, a post-discharge care coordination team will be engaged before he leaves the hospital.
If all of this sounds worlds apart from the kind of surgery your father might have experienced, it is. I spoke with Randy Salisbury, chief marketing officer of Streamline Health Solutions, about how healthcare is rapidly moving from relatively subjective decision-making based on isolated incidents to more evidence-based medicine; becoming connected, predictive and personalized. The days of the trip to the doctor resulting in referrals followed by the same tests and questions repeated over and over are nearing an end. Patients are taking a more active role in their own care. With relevant historical information about the patient and the experiences of patients like them, care teams can avoid undesired outcomes such as surgical site infections, ongoing pain, stiffness and poor physical function. This can save thousands of dollars in unreimbursed follow-up care costs for hospitals and health systems and can help keep patient satisfaction high.
How is all this possible?
Although hospitals and health systems have long monitored financial and operational data, the difference comes with tracking clinical data. This includes information such as a patient's diagnosis, treatments, prescriptions, lab tests and hospitalizations.
Clinical data is extracted from a variety of sources, including electronic health records, information exchanges, disease registries, and even personal health devices and direct patient surveys. Examining clinical data completes a 360-degree view, enabling providers to analyze their patient populations, understand which individuals need the most help and proactively reach out to give them the care they need. When intelligently applied, clinical analytics help not only support a hospital's bottom line, but also improve patient outcomes and reduce avoidable readmissions.
What's behind the drive toward analytics?
For one, it's you, me and everyone else who waits to get help for a medical condition until they are sweating and complaining of chest pain and shortness of breath. It is no secret that "reactive" healthcare is more costly than preventive care designed to keep patients out of high-cost settings such as the emergency room.
Encouraging "wellness," in fact, lies at the heart of healthcare reform initiatives that move away from fee-for-service reimbursement and toward value-based, accountable care models that tie together cost and quality of care. For hospitals, this shift means that future success depends on the ability to use data and analytics to improve both financial and clinical performance.
How it works
In the past, evidence-based treatment has meant following well-studied care protocols. With increased access to clinical data and advances in computing power, however, predictive analytics can provide a new kind of evidence to drive action. Aggregating and analyzing information about a broad population of patients over extended periods of time can help care managers understand -- and therefore facilitate -- the root causes of good outcomes for individual patients and for patient populations.
Predictive modeling helps care managers identify patterns in a population's health in order to prospectively determine individual risk scores. These scores can then be used to triage the work of a care team, allowing them to focus first on patients at highest risk. In the earlier example of Jim, the TKA patient, predictive analytics helped identify him as a high risk for surgical site infection -- and therefore in need of prophylactic antibiotics -- or it might identify him as being inexperienced with physical therapy, which is a critical component of post surgery success.
Predictive modeling, whether based on claims data, medical records or patient-supplied risk assessments, can segment individuals prior to service and address a myriad of concerns before they turn into problems. This can be done through:
- preventive care and wellness activities
- chronic disease management programs that teach patients how to care for themselves, such as when to take their medications
- better care coordination, for example, making sure medical records are sent to a skilled nursing facility prior to a patient's transfer from the hospital
Clinical analytics can quantify everything from patient outcomes to readmissions and emergency department visits, to wait times and utilization of high-cost services. This new level of insight and transparency is good for both clinical outcomes and for business. In addition to setting internal benchmarks to measure cost and quality performance, for instance, clinical analytics also can help an organization compare how well it stacks up against its competitors and use that data to negotiate better payer contracts. It gives hospitals the ability to quickly make strategic decisions to improve clinical quality, reduce costs, optimize resources and enhance their competitive positions.
The benefits to patients are equally strong. By providing a holistic understanding of patients, analytics ushers in a new era of personalized healthcare. Clinical analytics have the power to arm individuals with timely, relevant information to help them make good health choices. This 360-degree view helps doctors predict risk for disease and response to treatment, supporting better diagnoses, safer drug prescribing and more effective treatments. Over the years, both as a patient and in his role as an executive for a leading healthcare analytics solution provider, Randy has witnessed this evolution first hand.
Forward-looking hospitals have already begun to embrace clinical analytics -- and that means their patients can enjoy a life well-examined. With that will come lower costs, reduced readmissions, improved outcomes, and a better overall patient experience.
This post was co-authored with Randy Salisbury, chief marketing officer of Streamline Health Solutions, Inc.