Researchers at the University of California, San Francisco, used previously untapped data buried in EHRs to pinpoint the source of a particularly nagging hospital-acquired infection.
The culprit? A CT scanner in the emergency department.
The UCSF researchers used time and location stamps in the system’s EHR to track the movements of more than 86,000 hospitalized patients over a three-year period. The results, published in JAMA Internal Medicine, showed patients who passed through the emergency department’s CT scanner within 24 hours after a patient with Clostridium difficile (C. diff), were twice as likely to become infected. Nearly 4% of patients who were exposed in the scanner became infected within two months.
Although previous studies tracking C. diff transmission have focused on a single hospital floor or even a hospital bed recently vacated by an infected patient, the UCSF study tracked nearly 435,000 patient movements throughout the entire hospital, which helped them build a comprehensive map of potential hotspots.
“If we just look at transmission in their room, we’re missing potential opportunities for disease transmission,” Russ Cucina, M.D., senior author on the study and chief health information officer at UCSF, said in a release. The researchers plan to continue exploring EHR data to track patient movements.
Time stamps in EHRs have shown to be increasingly valuable to researchers. A recent study out of Oregon Health and Science University found that time-stamp data can be helpful in evaluating physician workflows.
Providers have also leaned on EHRs to prevent infections like sepsis, although some experts have voiced concern that relying on electronic screenings could actually increase resistant superbugs by leading to increased use of broad-spectrum antibiotics.
Big data is growing and offering increasing promise for improved clinical and organizational decision-making. The analytics capability to access that data for decision-making, however, is not keeping pace. According to UC Berkeley health policy professor Stefano Bertozzi, “Healthcare data is constantly getting bigger, and that means hospitals have the opportunity to improve not only care delivery, but also, enterprise performance — but the analytic capability is the biggest bottleneck hospitals wrangle with today.”
When Aaron Levitt, PhD, wrote, “Unlocking the value of EHR through analytics,” he spoke of the promise of analytics:
“The application of analytics to EHR data holds great promise for helping organizations identify opportunities to improve the quality of care and preserve financial stability…. Many large health systems and academic institutions already have the manpower and analytics tools in place to perform this type of analysis, but often smaller organizations lack both the required technology and the in-house expertise.”
How analytics provide value to healthcare systems
For example, the Carolinas HealthCare System has seen analytics provide the ability to identify, measure and improve care and quality outcomes. They have also found, among other outcomes, that data can now be used in predictive analytics to help predict disease outbreaks and population health measures.
Other ways in which analytics is offering value to healthcare systems appears in the HIMSS Health IT Value Collection. Here, we find story after story of ways in which analytics is being used to advance the quality of care, population health, and organizational performance. For example:
• Children’s Hospital of Pittsburgh of UPMC found that the EHR generates predictive and preventive analysis reports that prevent patient decline and improve patient outcomes.
• For the Cleveland Clinic, predictive analytics provides the ability to predict length of stay for patients anticipating surgery, which patients will be higher-acuity, and what the hospital occupancy and census will be up to 8 weeks in advance.
• At Kaiser Permanente of Northern California, predictive analytics uses a mother's clinical data and the condition of her baby immediately after birth to predict the risk of severe neonatal infection to determine which babies need antibiotics.
• For Lancaster General Health in Lancaster, Penn., the EHR's clinical data allows analysts to conduct risk stratification of patient populations.
• Analytic capability at Parkland Health and Hospital System in Dallas supports the timely identification of diabetes patients through population surveillance and helps predict readmission risk in patients with heart failure, thus enabling more-informed clinical decisions.
• With a focus on improved performance, Legacy Health (Portland, Ore.) finds that data analytics tools enable clinicians to view their outcomes via comparison to other clinicians from over 200 hospitals.
• The disease registry system stratified 1.1 million patients into various disease states to identify gaps in care at Meridian Health in Neptune, NJ.
• The Stanford Cancer Center found that with the use of analytics, they were able to reduce patient wait times at infusion centers by 30% at peak times, and the centers have been able to see 25% more patients with 15% lower costs.
The importance of analytics to the future of healthcare
These are only a few examples of how analytics, using data in the EHR, has been able to improve care, access, performance and costs at a few major health systems that have implemented and used analytics. As analytics capabilities become ubiquitous, and more professionals train in the use of those capabilities, organizational performance and the quality of care will continue to increase nationally and locally. The importance of analytics to the future of healthcare cannot be overstated.
Electronic medical records (EMRs) provide healthcare professionals with vital patient medical information that can help them choose the proper course of treatment and avoid unnecessary tests or procedures.
Not surprisingly, the widespread adoption of EMRs over the past decade has increased patient safety and led to better outcomes while reducing costs. In an article published in Harvard Business Review, two medical professionals at Virginia Mason Medical Center (VMMC) explain how EMRs are making an even bigger impact on healthcare.
“Just as the cell phone, originally designed as a mobile communication device, has been adapted to an unimagined array of additional functions, the EMR is serving as a platform for innovation and creativity,” write A. James Bender, medical director for clinical informatics, and Robert S. Mecklenburg, medical director of the Center for Health Care Solutions. “Some of these innovations include 1) detailed prompts and reminders to avoid omissions in care, 2) transparency to engage patients and families in spotting lapses in care, and 3) adding medical intelligence to computer programs.”
The authors vividly describe how VMMC uses EMRs to increase transparency:
“In the intensive care unit at Virginia Mason, electronic scoreboards in public areas display with red or green highlights the current treatment status of every patient receiving therapy to prevent the formation of dangerous blood clots in the legs. These highly visible screens enable patients and family members to join doctors, nurses and support staff in rapid identification and correction of incomplete care. Virginia Mason now experiences 100% compliance with interventions to prevent blood clots for these patients.”
Benson and Mecklenburg argue that providers best able to leverage the functionality of EMRs will improve their competitive position.
“Most important,” they conclude, “the best doctors will use the EMR to add the deep knowledge and protection of digital mistake-proofing to the art of medicine that they bring to each of their patients.”
Digital disruption is the new normal. We use video conferencing in global business meetings, summon car rides through our phones using GPS, and snap or tweet our lives to friends and followers.
For its part, healthcare is breaking down traditional hospital walls, and it’s not just the developed world leading this disruption. Indeed, the healthcare model for billions of people in the developing world has always been different. Lacking the massive and complicated hospital infrastructure of other regions, medical care in many parts of the world travels to the patient in the form of a visit from a local doctor or a stop at a rural clinic.
This “last mile of care” – where the hospital finds the patient, not the other way around – is made possible as medical innovation across the globe becomes increasingly mobile, digital, personal and accessible.
Healthcare solutions are becoming more digitally connected, affordable and convenient for both the patient and caregiver. A Journal of Hospital Librarianship study found that 85 percent of health care providers were already using smartphones and/or tablets in their daily work. One-third of health information exchange data is already in the cloud, according to a white paper from Cisco.
Digital health, in other words, is here. Data from remote monitoring devices, such as smart scales and blood pressure cuffs, are being transmitted to doctors around the world to improve patient outcomes. In remote areas across Latin America, cloud technology allows doctors to share ultrasound images with their patients and distant colleagues with the simple click of a button. Similarly, pocket-sized ultrasound technology is helping midwives in Africa determine if expectant mothers can deliver babies safely or need to go to the nearest hospital.
Big data, analytics and artificial intelligence enable health care to be more personalized and precise – a fact with which patients appear increasingly comfortable. Virtual assistants on our phones or kitchen counters are dispensing medical advice from WebMD, and a recent global PwC survey across 12 countries showed that nearly 40 percent of people trusted AI and robotics to administer a heart rhythm test and then make clinical recommendations. That hypothetical is already becoming a reality. A new algorithm server is helping medical professionals read patients’ ECGs remotely and AI is helping doctors diagnose lung cancer in China.
In emergency rooms and operating rooms across the world, machines are generating millions of data points, but only a small fraction are harvested and saved in hospitals’ electronic medical record systems. Gathering, analyzing and acting on this deluge of data is the next step. For instance, clinicians can now use cloud-based, algorithm-powered apps to pull hundreds of data points directly from anesthesia machines with every patient breath. These apps unlock actionable insights that can help clinicians with clinical, operational and economic improvements.
Mobile digital health is revolutionizing not just how and what care people get, but where they can receive it. Already, 70 percent of U.S. employers offer telehealth services, and a World Health Organization survey found that 87 percent of countries worldwide had at least one massive mobile health program underway.
While most acute care will continue to take place inside brick-and-mortar medical facilities, future generations will likely receive care virtually, and participate in their own care to greater degrees. For instance, subtle stick-on monitors that look like digital Band-Aids are being developed right now to help doctors remotely monitor key vital signs, from heart rate and blood pressure to sweat and oxygen levels.
Disruption is indeed the new normal for healthcare. By pairing new thinking with new technology in new clinical areas, we can make sure that future healthcare solutions are at once more personal, more digital and more globally connected. In a future where hospitals are everywhere and nowhere, and data is ubiquitous, care must and will come to the patient.
EHR timestamps can track productivity
Medical clinics looking to identify efficiency and productivity shortcomings should look no further than their EHR system.
Researchers at the Oregon Health and Science University discovered timestamps within EHRs can provide valuable information regarding workflow inefficiencies. By observing workflow at four outpatient ophthalmology clinics and comparing that to EHR timestamps, the researchers found the data buried in medical records offer an accurate portrayal of workflow that can be used to create simulation models and analyze EHR use. (JAMIA study)
Patient data ownership will drive transformation
A trio of digital health researchers says healthcare is “poised for transformation,” but only if patients have broader access and control over their health data.
Specifically, the researchers say this can be accomplished by creating common data elements, providing patients with a “patient encounter data receipt” that is automatically pushed to their complete digital record and drawing up an explicit contract in which providers and vendors turn over control of health data to the patient. (JAMA Viewpoint)
Geisinger partners with pharma to create prediction model for diabetes patients
Pennsylvania-based Geisinger Health announced a partnership with Boehringer Ingelheim and Eli Lilly that will tap the health system’s EHR data to build a risk prediction model that can identify diabetes patients at risk for cardiovascular disease, kidney failure and heart failure. The predictive model could help physicians provide more targeted treatments for people with type 2 diabetes and improve long-term health outcomes. (Announcement)
Indiana University to build "data commons" for genetic information
Indiana University and the Regenstrief Institute have announced a partnership with an Indianapolis-based company called LifeOmic to build a “data commons,” a single repository to store genetic information for millions of patients that can be analyzed by researchers. The databank will allow the system to develop personalized treatment plans by clinicians with new information to support diagnosis and treatment. (Announcement)