By John Palmer
Editor’s note: One of the biggest healthcare revolutions in the last 10 years has been the advent of analytics. By leveraging large data pools, improving patient care, and using new data analysis technologies, healthcare providers have been able to find innovative ways to harness analytics to ensure effective patient care and proper recordkeeping.
The following is a Q&A with Christopher Rafter, chief operating officer of Tampa-based Inzata Analytics, a company that provides a data analytics platform powered by artificial intelligence (AI). Here, he speaks about the future of data analytics in healthcare and how they can improve the effectiveness of patient care.
Q: What benefits can a healthcare organization enjoy from increased use of data analytics?
Christopher Rafter: Big data analytics strategies are maturing quickly in healthcare, outpacing numerous other industries. The reasons for this are the numerous visible and immediate benefits these technologies bring about, measurable benefits that can appear within weeks of adoption. Organizations are maturing their big data analytics strategies as they rise to the challenges of value-based care. This takes the form of collecting and analyzing more diverse data sets by combining multiple, physically separate data sources. Healthcare organizations are also taking advantage of technologies such as the internet of things (IoT) and robotic process automation (RPA) to collect and monitor more data than ever before.
The benefits fall under two major themes everyone can get behind: improving patient outcomes and reducing the cost of healthcare delivery.
Improving clinical outcomes is the top driver for big data analytics investment, said participants in a 2019 survey conducted by Deloitte Center for Health Solutions. Improved outcomes drives 89% of organizations to invest in analytics now, [and it’s] expected to increase to 93% in three years’ time. The percentage of respondents who rank analytics as “extremely important” jumps from 36% in 2019 to 84% by 2022.
Other top priorities include growing revenue for the organization, transitioning to innovative payment models, and supporting research and precision medicine.
Q: What roles do you foresee these technologies playing in the patient care field, and how will data analytics play a part in that?
Rafter: The most visible changes are set to occur in the frequency and methods by which healthcare is administered and delivered. Traditionally, healthcare delivery has been largely episodic for most people, centering around detection of symptoms by the patient or during checkup, followed by the decision to seek care. New technologies allow for a more holistic “early warning” monitoring and ongoing analysis of patient health data. Being able to predict health conditions based on population characteristics combined with personalized monitoring, and take preventive actions to avoid costly emergency visits, is a major cost saver for the entire system. Wearable health monitors, smart pill bottles, and virtual patient consultations provide physicians with better data about how their patients are doing and give them an opportunity to spot and treat patients before physical symptoms appear.
Q: What products are available to help hospitals benefit from data analytics? So-called “digital dashboards” help facilities collect data from multiple points of analysis.
Rafter: Digital dashboards are just the end product of a healthcare data integration strategy where different data sources are indexed and blended, most often in a data warehouse. This data warehouse product is the heart of any healthcare data analytics capability. It is where data from multiple systems is collected, blended, and enriched to produce holistic reports and dashboards. Having a single, simple platform that does all of this at once is the fastest way to start realizing benefits from data analytics and AI in healthcare. It gives human analysts as well as AI an ability to identify causes and correlating factors that drive healthcare outcomes.
We’ve all seen the headlines such as “XYZ linked to increased rate of heart disease” or “ABC ruled a factor in cancer diagnosis.” By connecting these social determinants with real-time patient data collected through monitoring, physicians have a better ability to predict patient progress and conditions, and can deliver more timely and precise diagnosis and treatment.
For deeper data analysis on big data populations, automated data mining tools that integrate data to detect patterns and correlations within large volumes of healthcare data are essential. After their primary role of monitoring individual data, the data collected serves a secondary purpose in population analysis and the training of predictive algorithms.
Having data-driven, real-time insights accessible to the entire organization through analytics is a competitive necessity for healthcare these days. Larger players and patients have come to expect these capabilities from organizations of all sizes.
Organizations that do not yet have a strategic plan for data analytics should consider launching a strategy as soon as possible. The environment is highly competitive and fast-moving; falling behind your competition by even six months can sometimes be impossible to recover from.
Q: Can you give some examples of how these products can increase patient safety, reduce errors, control infection, etc.?
Rafter: Technologies that engage patients in the home, workplace, or other convenient locations first can dramatically reduce the severity of symptoms by allowing healthcare professionals to get involved earlier. These practices improve safety for patients and allow professionals to intervene before physical symptoms might prompt a patient to seek emergency medical care.
The guidance given at this point on the right place to seek medical care can dramatically reduce the drastic overuse of an emergency room, which is arguably the most costly and inconvenient healthcare point of treatment.
Better access to digital health records and the monitoring of vulnerable populations can greatly reduce medical errors in care delivery. Certain patients and populations are statistically at greater risk, including the following:
> Patients in isolated locations or with limited access to healthcare professionals
> Patients with limited English proficiency, or who have difficulty explaining symptoms or interpreting complex medical instructions
> Patients with low health literacy who may struggle to adequately communicate with members of the healthcare team, fill out complex forms, and understand concepts related to risk and probability
Using combinations of digital health records, biometric identification, and monitoring tools for these risk-prone populations can greatly reduce the incidence of medical errors by improving the reliability and accuracy of patient information prior to treatment.
Q: What benefits do physicians and caregivers gain from improved data analytics?
Rafter: Historical outpatient claims data suggests that about 43% of outpatient visits could be addressed through a virtual care visit, according to Forrester. Telehealth contact methods, combined with sound wellness management, is an option healthcare and hospital CIOs should look at to improve quality and reduce costs associated with care delivery.
Reduction in errors and improvements in physician efficiency through better patient scheduling is another area of benefit. By understanding how long a physician will need to spend with each patient based on known factors, much more efficient schedules can be developed, keeping the physician well utilized and their patients waiting less.
For physicians who divide their time between multiple locations, improvements in virtual consultations and having a better understanding of where their patients are most likely to go help them prioritize their schedules and work locations.
Finally, since individual caregivers are often the major source for collection of primary patient data, digitization of patient data and digital sharing of health and pharmacy records means shorter patient interview times, fewer paper forms, and less documentation to key in and maintain at the local doctor’s office.
Q: Can technology be used to improve communications between primary care doctors and specialists, for instance, and reduce the number of people who need to be involved in a patient’s care?
Rafter: Yes, but in a slightly different way. You often want that specialist involved in patient care, if their expertise is required, but you want to reduce the inefficiency of accessing specialist knowledge such as having to send the patient on multiple office visits and making sure their medical records follow them.
Improving and streamlining communication among links in the patient care chain (e.g., monitoring handoffs in communication) is an important but often underutilized way of reducing medical error rates.
For example, in many hospitals, pharmacists—critical allies in the prevention of medical errors—are relegated to pharmacy operations, in primarily a fulfillment role. They have limited interactions with their colleagues in other departments, and almost never with the patients they’re helping to treat.
Decentralizing the pharmacy, posting pharmacists as permanent resources in particularly vulnerable hospital departments such as the ER, and rotating them between these departments on a regular basis opens up lines of communication.
John Palmer is a freelance writer who has covered healthcare safety for numerous publications. Palmer can be reached at email@example.com.