The story below is a preview from our July/August 2018 issue. For more, Subscribe today or view our FREE digital edition.
A careful balance of information and privacy is needed to provide next-generation care.
There is an unseen but critical impact that technology plays in every patient interaction. Within the hospital setting, predictive analytics help decide many aspects of patient care, from ensuring compliance with state and federal laws, budgeting for staffing levels, finding and flagging drug interactions, tracking drug diversion, interfacing interactive wearable medical devices, making well-timed business investments, tracking patients’ vital signs, researching medical breakthroughs, managing costs of care and even the way in which nutritional and laundry services are delivered at the patient’s bedside. A careful balance of information and privacy is needed to provide next-generation care.
Data Security
Preapproved guests enter a large, nondescript building, with limited signage, in a nondescript part of Roanoke city. The exact location is on a need-to-know basis. Razor wire fencing is on one side of the building. Cameras capture every move from the parking lot to inside the front door. Guests, including Carilion employees, are required to bring a valid government ID to gain access into the building.
Once inside the enormous building, a receptionist and security guard greet visitors in a small atrium. This is intentional. The Carilion security officer assists guests by scanning a government ID into a machine not unlike the passport scanners found in airports. According to Keith Perry, Chief Information Officer of Carilion Clinic, over 50 security checks are performed instantly from a government ID, including federal and state law enforcement watch lists, as well as compliance issues with programs such as those with the Centers for Medicare and Medicaid Services (CMS).
With an enormous amount of data shared among internal and external partners, Perry explains the reasoning for decisions regarding our medical information. Perry’s responsibilities are broad. He oversees technology that clinical and operational leaders need to direct patient care, including information systems, health information management and clinical engineering. Perry puts it simply, “People are taking care of people everywhere in the hospital; on the opposite side of that, technology has hopefully enabled them to spend more time on the care and compassion they give.”
Next to ensuring that the technology is always functional, the sacrosanct part of his mission is safeguarding the data. Perry says all 13,000 employees share accountability for safeguarding the information. Carilion has internal systems to monitor who is accessing and using patient information. Audits are also conducted by the Office of Organizational Integrity and Compliance as well as external auditors are engaged for additional risk assessments.
Perry’s goal is to keep the patient at the center of technology, with upgraded, robust data helping patients. “Medication administration has been a huge win with the use of technology. The pharmacy, the patient and medication prep and dispensing, as well as administration of medication, is all systematically checked in real time,” he says.
A patient’s wristband is scanned to ensure the right patient is given the right medication at the right time. Diets and other medications are checked for interactions through the enterprise-wide electronic health record (EHR), Epic. Formulary information by pharmaceutical manufacturers provides up-to-date content, so data is provided in real-time regarding the drug being administered.
Perry works collaboratively with Dr. Stephen Morgan, Chief Medical Information Officer. Morgan and his team of doctors, nurses and analysts are tasked with bringing value and meaning to these large data sets and offering. Morgan and his team use their knowledge of healthcare, information systems, databases and information technology security to gather, store, interpret and manage the massive amount of data generated when care is provided to patients.
“Bringing value and meaning from these large data sets is one of our primary goals,” according to Morgan. Part of this work involves providing clinical decision support to a variety of team members at the point of care, when clinicians are treating patients. “The goal is to not overwhelm practitioners, but to provide the best information at the right time, while providing great care and reducing overall health care costs.”
Big data is the practice of combining many sources of extremely large data sets to reveal patterns, trends and associations, especially relating to human behavior and interactions. Big data within health care is a natural progression, from information collected through electronic medical records beginning in the 1990s, to standardization of medical information through 2008. Now trending is the use of in-house information, along with third party and public information, to make predictive decisions in every aspect of patient care.
As part of the Affordable Care Act, The Centers for Medicare and Medicaid (CMS) began to move toward a value-based model for billing that focused more on quality outcomes. The old model for billing was fee-for-service–meaning the more care one provides, the more one bills. Treating large volumes of patients was a goal during this period. Increasingly, hospitals are now reimbursed for the quality of care and not just quantity. The new model financially ties patient outcomes to reimbursement.
To improve outcomes, it is important to share large amounts of data between health care settings to provide better care for patients. Having a more global view of the patient allows for more in-depth knowledge and improved clinical insight. With the availability of these large data sets, predictive models can be developed to help provide quality care in a less expensive way.
Since the most expensive medical care is provided in the hospital setting, providers can reach out to high-risk patients and communities to help avoid costly hospital stays. Care can be preemptively handled in outpatient clinics, by home health teams or with telemedicine. Predictive analytics can zero in on patient populations not only within the hospital, but also at the zip code level within the community.
Using funding for smarter investments in the business of health care is one way a nonprofit like Carilion can ensure spending is done wisely and can impact those with the greatest or most pressing needs.
Readmissions
CMS has set a national goal of cutting down patient readmissions. Carilion is using big data to determine which patients are at high risk for remission to the hospital once discharged. Teams of medical experts are developing an algorithm, using machine learning in real time, to better flag patients with a higher risk of readmission. Those at a higher risk of readmission will have resources such as patient education, social workers and home health care providers allocated, with the common goal of keeping the patient healthier, better informed and treated within the appropriate setting.
Carilion currently has a major focus on addressing the opioid crisis. Part of this is using modeling with third-party data for patients prescribed opioids. More robust data means a multidisciplinary team; lead by Dr. Robert Trestman, they can use a patient-focused approach targeting problems identified by the data systems, including flagging at-risk behaviors, locating geographical hot spots and enhanced reporting for prescription monitoring. Opioid data is also compiled to assist with research funding. Patients considered at-risk for overutilization of opioids are tracked, with actionable plans provided to their health care provider in real time.
In 2017, the state mandated the Emergency Department Information Exchange (EDID), a standardized system to share patient information between hospital systems. The software is designed to proactively notify Emergency Departments when high-utilization or special needs patients register. This will allow better coordination of care for these patients. Patients frequenting emergency rooms seeking controlled drugs are now tracked with a goal of providing the information in real time and sharing it among all emergency rooms. Given our nationwide opioid crisis, patients seeking narcotics at different locations can be flagged with the goal of decreasing this behavior.
Improving Hospital Care
Predicting which patients are more likely to fall is giving providers better information to educate and assist patients and their caregivers. Combining data points in real time, a patient is assigned a risk score and suggested, proactive measures that can be taken to mitigate the risk of a fall.
Machine learning can also help pick up on subtle patient changes before they become life-threatening. A tool which has been in place for the past year at Carilion Roanoke Memorial Hospital provides real time early warning alerts to staff when a patient’s status is deteriorating. This surveillance sends out easily understood, color-coded graphical charts to medical staff which are monitored on every unit. This intelligence also adds continuity of care and facilitates better communication during shift changes and handoffs.
Community Involvement
Carilion is partnering with multiple schools at Virginia Tech to use data to better understand how to address our community’s health needs. One project involves combining EHR data, publicly available school systems data, economic data and social determinants to develop best practice risk models and treatment plans to target appropriate care for high risk communities. Dr. Morgan states, “Understanding our patients’ social and economic challenges is key to improving the health status of the areas we serve.”
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