Advancing analytics to improve the patient journey

The healthcare system is swimming in data, but providers sometimes struggle to harness that firehose of information to deliver more patient-centric care.

As providers begin to see a gradual uptick in patient volumes after the initial wave of the COVID-19 pandemic, they are grappling with care delivery models that have been upended. In some cases, the pandemic has changed the ways patients schedule appointments, engage in clinician encounters, conduct post-visit follow-ups, and pay their bills.

Most practices don’t need more data; they already have more data than they know what to do with in electronic medical records, scheduling and care coordination systems, virtual health apps, and patient surveys. What they need is actionable, predictive insights from their existing data that improve engagement, quality and consistency at each phase of the patient journey.

While this notion of leveraging data to enhance the consumer experience has lagged in healthcare, other industries, like entertainment and e-commerce, have long recognized the benefits of advanced analytics. For instance, Netflix and Amazon use analytics to gain insights into users’ viewing and buying history and habits. With this intelligence, they predict what the user may be interested in watching or buying next, recommend television series or products, and ultimately keep the user satisfied and engaged. It’s without question that the physician practice setting could benefit from similar analytical methods.

In an industry as notoriously siloed and fragmented as healthcare, obtaining data-driven insights for the right patient at the right time in a clinician’s workflow can represent a significant challenge; however, it is important to keep in mind that data and analytics are not the be-all, end-all. They are valuable tools that enable physicians to make better treatment decisions within the right context. With that caveat, the following are several practical ways that providers can leverage advanced analytics to deliver more patient-centered care at various points along the patient journey.

Appointment scheduling

The patient journey begins before patients engage with clinicians during visits and extends into follow-up care and the management of chronic conditions. At the start of the journey, providers can make a number of key decisions during the appointment-scheduling process based on previously collected demographic, financial and clinical data, in addition to information gathered from the patient during the appointment request. For example, analytics can help providers prioritize patient appointments, determine the appropriate pathways for patients’ care journeys, identify the best clinician for a patient to see, suggest the most convenient times for visits, and determine the best channel for communicating with the patient.

Further, some patients may have difficulty showing up on time for appointments due to work responsibilities or transportation limitations. By leveraging demographic and social determinants of health data, practices can ascertain which patients are the best candidates for virtual visits.

The physician-patient encounter

Dashboards in electronic health record systems are infamous for information overload and complex navigation that frustrate physicians and divert their attention from patient visits. And physicians can’t be expected to read through all the previous notes detailing patients’ histories. Practices can use advanced analytics to make sense of the mess by bringing together massive amounts of disparate information and providing insights that map to succinct metrics, such as a risk score that quantifies the likelihood of future complications from a certain condition or “5 key factors to know about this patient.”

Techniques like Natural Language Processing (NLP) and text analytics can extract insights like Social Determinants of Health (SDoH) from physician and patient contact notes. Contextual understanding of patient conditions and risks are enhanced by these insights, thereby helping clinicians identify and focus on the highest priorities during each patient encounter.

Post-visit follow-up

Given the siloed nature of U.S. healthcare, primary care physicians sometimes lack awareness of whether patients have followed-up on post-visit recommendations such as scheduling specialist visits or filling prescriptions. Practices can capture the full picture of a patient’s care and predict possible next actions with advanced analytics, enabling better-informed decisions when developing care plans. Delivering these insights back to primary care physicians improves and simplifies the post-visit follow-up process.

Billing

The billing process is sometimes fraught with errors and delays, posing a challenge for small practices as they seek to collect payment for services they have provided, while also optimizing the patient experience. Practices can move claims through the system faster with advanced analytics, allowing them to identify anomalies in coding, billing, and payments, and quickly move to resolving these issues and collecting appropriate payment.

Physician practices have plenty of data. They just need to figure out how to incorporate it into their workflows and leverage it to improve patient care and outcomes. Insights enabled by and enriched with SDOH factors can provide significant improvements at every patient touchpoint. Advanced analytics can pave the way for evidence-based decision-making and should not be overlooked as a key step to improving the patient journey.

_{About the Author}

_{Balu Nair is a techno-business leader with over 20 years of strategy, design, and execution experience. As the CTO for Gray Matter Analytics, Mr. Nair leads engagements in strategy, transformation and information management. Read his full bio here.}