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Data mining: health care must look to adopt predictive analytics

November 29, 2016
Health IT
From the November 2016 issue of HealthCare Business News magazine

By Levi Thatcher

Hospital leaders agree — nearly 80 percent of them — that predictive analytics can solve a host of persistent problems for health care.That’s according to the results from an August survey of 136 hospital and health system executives by Health Catalyst, which would seem to confirm that widespread adoption of analytics is here, or close to it.

Yet the same survey revealed that only 31 percent of hospitals have used the technology for more than a year, although 38 percent said they plan to adopt predictive analytics within the next three years. What’s preventing these organizations from using a powerful tool, right now, that can help curb preventable readmissions, develop precision treatments for diseases such as cancer, and renegotiate contracts with insurers that pay less than the cost of providing care, just to name some of the longstanding challenges that predictive analytics can tackle?

It turns out that while there’s certainly a demand for predictive analytics, the necessary infrastructure and ready access to data are lacking. That’s the verdict of 32 percent of respondents in the above-cited survey, and it’s not a surprising one. Producing reliable predictions of future probabilities or trends does require an accessible, trusted source of data, aggregated from multiple IT systems such as the hospital’s EHR and financial systems. When asked to list the top sources of data for making predictions, respondents cited clinical data from the EHR, claims data and patient outcomes data, financial data and non-medical patient demographics and patient satisfaction data.

Predictive analytics also requires analytic applications to drive the predictions and make them easy for front-line staff to use. But, according to a sizable number of survey respondents, 26 percent, a lack of people and skills were preventing use of predictive analytics in their organization. Even among those who plan to adopt predictive analytics, few said they have the budget to allocate significant resources to the effort. Thirty-seven percent are tip-toeing into the space with commitments or planned commitments of one to three people devoted to the task of leveraging analytics for predictions. Only 8 percent said they would allocate more than four people to that role. Thirty-four percent of respondents said they were unsure how many people they would have work in the area.

Pent-up demand?
Few seem to question the effectiveness of the technology. Only one respondent said past efforts had failed to show results. And despite the relative youth of predictive analytics technology, confidence in its accuracy ranged from neutral to very strong among respondents. Only 2 percent said the technology produces inaccurate results. Apparently driven by faith in predictive analytics’ ability to deliver meaningful results, demand for the technology appears to be strong among hospital leaders. Of the 38 percent who said they plan to adopt predictive analytics within the next three years, 14 percent of that group said they will adopt it in the next 12 months.

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