Predicting Patient Experience with Narrative Data: A Healthcare Goldmine healthcare industry in the United States is going through a major transformation and is becoming much more consumer friendly. This process of “consumerization” will drive healthcare executives to pay close attention to what patients feel and think about healthcare organizations and services – something the industry has ignored for decades. This trend should continue and be accelerated as we all start paying more out of pocket for healthcare services.

Going forward, the success of healthcare organizations will depend on internalizing patient sentiment insights into everyday decision-making, just as it is for nearly every other industry. By its recent introduction of the “Health Star Rating” system [1] for hospitals, the Centers for Medicare and Medicaid Services (CMS) sent a strong and clear signal about the huge transformation of the patient experience and associated ratings, and its impact on the healthcare industry – an impact the industry can no longer ignore.

Patient Experience: An Overview

Patients today provide valuable information about their personal experiences with hospitals, clinics, doctors and nursing staff. Patients share their experiences in a variety of mediums, e.g., social media, patient discussion forums and surveys. In addition, key insights are gathered when patients engage with care delivery organizations via call centers and interactive in-room TV apps. When we bring all of these different data sets together along with key hospital objective metrics and CMS data, the insights derived can have a huge impact on the decisions that today’s healthcare executives have to make. These “narrative data assets” provide new perspectives and complete story lines never before available to the healthcare industry.

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Healthcare Data Landscape

The data landscape – a key to understanding patient behaviors – has dramatically changed over the last few years. Narrative data – ready for processing – is now available from patients before, during and after an encounter.

The medium through which patients are communicating during various touch points has to be understood holistically in order to generate insights to act upon. A holistic program gathers patient data from hospital systems as well as third-party surveys and social websites. Using the new data landscape that is available, a set of patient experience indicators can be generated .

Insights from Data

Once the new data landscape explained above is accessed and understood, we have a wealth of information available to analyze. For example, the narratives from social media sites and surveys can be analyzed using Bayesian interference [2] to find out emotional attachment of patients to a hospital’s brand and services. A typical patient encounter may leave the patient in an overall satisfied state, but they might have felt “anger” at the billing errors. Advanced data science algorithms can analyze this range of emotions.

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Insights to Intervention Programs

We have seen some methods that hospitals can use to track the leading indicators such as patient sentiment from narrative data assets and analyzing their impact on few of the key performance indicators. As noted, the approach presented here is more comprehensive and faster, thus enabling hospitals to generate insights from patient experiences across touch-points.

The real value of the insights from these narrative data assets is when hospitals use them to define intervention programs, thus potentially generating a desired state of outcomes. Using data science methods, a model can be built that can analyze the impact of changing the set of forcing variables on the outcome of a selected target value. For example, a key set of variables that are forcing a patient to switch hospitals can be identified from the test data, and the model can predict the outcome of patient switch based on changing values. Read more…

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