Data Analytics: Maximizing Its Power by Focusing on Simplicity

By Tara Vail

The current and future prospects for patient care data analytics are exciting and powerful. Data is available in many forms from many sources, but it needs to be collected and organized in a way that turns it into actionable information. That is the challenge and the opportunity for healthcare IT and providers: to collaboratively assemble the right, easy-to-use systems for data collection and analysis while maximizing benefits and minimizing the headaches of manual processes. If we can rise to that challenge, we can find new or emerging health trends, draw conclusions more confidently, and identify improvement potential for individual patient care instances or general population care approaches.

Five key considerations can guide our thinking about the use of data and the appropriate role of data analytics as we move forward:

  1. Make the tools easy to use. Healthcare providers are already overwhelmed with a host of data entry requirements for billing and regulatory compliance. We hear about physician burnout stemming from the administrative burdens that have clouded their passion for direct patient care. There have been calls for a “revolution of usability” to improve the data entry systems that often inundate healthcare workers. So health IT companies must ensure their innovative tools are simple, fast, and user friendly. They need to provide more efficiency, not more hoops to jump through. Getting this right means that data collection will provide insights on outliers and trends, showcasing information in a dashboard that all care providers can easily access and update in real time.
  2. To make data useful, normalize it across providers and sites of care. Data lives in electronic health records, patient portals, health apps, e-prescribing systems, clinic management software, patient accounting systems, monitors and devices, and more. The Institute of Medicine (IOM) has long been elevating the conversation on how this amount of information is both powerful and perplexing: “Understanding the scale of this potential and of the missed opportunities to improve health and health care due to gaps in data collection or barriers to their use requires an overview of existing healthcare data—the sources, types, accessibility, and uses,” according to the IOM’s Clinical Data as the Basic Staple of Health Learning: Creating and Protecting a Public Good: Workshop Summary. Health IT must be able to translate all this information into a common language, combine disparate data points, and help ensure it all makes sense. Giant gaps of information undermine the power of data analysis, so interoperability should be a key priority for health facilities as they put in place new systems. Don’t create an island of information; instead, look for ways to plug into the existing highways of communication and allow new data streams to be normalized into a language that can be understood and leveraged.
  3. Measure outcomes consistently. In the spirit of interoperability and normalizing data, it’s important to consistently measure the same outcomes across facilities and providers so that baselines and trends are easily identifiable and actionable.
  4. Harness data with patients, not just about patients. Patients must be an integral part of the process for providing data input. This shouldn’t stop at gathering information about their health history and medication use, either. As we shift toward value-based care and work to reduce hospital readmissions and improve outcomes, we need to know how patients are handling their recovery and symptoms. Health IT systems should include user-friendly tools that make it easy for patients to directly enter their own feedback. Easy-to-use tools increase the likelihood that patients will take the time to report or answer questions. Patient-reported outcome measures are a high priority for CMS and should be on the radar of every patient in the U.S. who wants to be involved in the improvement of their health. In addition to the technology consideration, gathering feedback from patients relies on carefully worded questions, consistent scales, and narrowing down to the essential questions. Patient-sourced information will make outcomes reports more accurate and more valuable.
  5. Leverage data analytics thoroughly for better patient care. We live in an information age where we can track and organize information in ways that were unimaginable in the 20th century—so data analytics must take advantage of all this information to actually improve patient care. The right tools that gather and normalize data will result in information that offers key insights for preop preparation, postop compliance, surgical quality indicators like infection rates, patient-reported outcomes, and any other clinical challenges that might inform patient safety and care quality.

Even with all this data streaming through the cloud, patients are human beings, and they are complicated. Sometimes trends do or don’t apply. In general, data analytics can offer trend information that allows providers to chart the general course of care; after that, providers must use specific patient data to determine the exact changes of sail. Through the combination of data and hands-on observations, providers can improve their diagnostic and clinical care. The result will be better diagnoses, more tailored patient care plans, and more confidence in care decisions. That’s good for individual patients and can drive population care improvement as well.

Tara Vail is the chief customer officer for HST Pathways.