October 05 2016 | 0 Comments | 250 reads Average Rating: 4.5

Sophisticated Analytics: The Key to Ovation-Worthy Results

by Lalithya Yerramilli in Health Analytics

Duke Ellington was widely lauded for his ability to use combinations of instruments, scales and harmonies to move jazz music to new levels of sophistication. In fact, he pushed the envelope so far that he was posthumously awarded a special Pulitzer Prize for music in 1999.

As analytics becomes all the rage in healthcare, leaders are realizing just how important it is to up the level of sophistication as well. By doing so, organizations can transform collected data into useful knowledge that can be acted upon to truly affect change. For example, here’s how increasingly sophisticated analytics can be used to reduce readmissions in hospital settings:

Descriptive analytics can provide an understanding of current patient care scenarios by aggregating clinical, financial, operational and socioeconomic data. With descriptive analytics, leaders can easily determine the facility’s readmissions rates overall as well as for specific clinical procedures or patient diagnoses. Through such analysis, a hospital might realize that a large number of congestive heart failure (CHF) patients are being readmitted while very few joint replacement patients are returning to the hospital. As such, the organization would then put more resources into initiatives that address the quality of care for cardiac patients.

Diagnostic analytics can help healthcare organizations identify why they are achieving various outcomes. For example, diagnostic analysis can identify the root causes of readmissions. The analysis could determine if readmissions are the result of complications or infections arising directly from the initial hospital stay; poorly managed transitions; or a recurrence of the condition. The analysis, for instance, might reveal that a lack of patient education after discharge is leading to CHF patient readmissions.

Predictive analytics can be leveraged to assess what is likely to happen through specific changes. Using advanced statistical analysis, predictive analytics can provide a reliable, data-based glimpse of the future that helps to understand the potential impact of various changes.1 For example, the analysis might reveal that a patient education program would have a greater potential to reduce readmissions with CHF patients who do not suffer from other co-morbidities than with those who are also diabetic. Such analysis can quantify the care-gaps prioritization for patients, as well as the possible cost saving associated with gaps-closure.

Prescriptive analytics pushes the envelope a bit more. With prescriptive analytics, an organization could determine the exact combination of changes that will lead to the most coveted outcomes. In essence, prescriptive analysis can help organizations determine the most cost effective way to reduce readmissions for a particular type of patient who has undergone a specific procedure. For example, with prescriptive analytics organizations could provide a tailor made plan for each CHF patient – ensuring that the treatment would lead to success and prevent the patient from re-entering the hospital.

Readmissions is just one area that is requiring the use of more sophisticated analytics. Can you think of other areas that could benefit from advanced analytics?

Reference

1. Higgins, R. Analytics: Keys to Charting a Strategic Road Map to Healthcare Financial Success. HFM Blog. March 16, 2016. https://www.hfma.org/Content.aspx?id=47191

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Author
Lalithya Yerramilli
Vice President, Analytics

Lalithya Yerramilli has 15 years of experience in analytics in insurance, healthcare, and life sciences industries working with customer info-base, transactional, physician level, patient level, claims and longitudinal datasets.

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