Big Data and Healthcare

2 min read
Curated from insidebigdata.com →

The ability to track patient data is instrumental to a doctor, hospital, nursing facility or even substance rehab center. But today, what do we do with  our ability to predict that  data? As providers continue to collect huge amounts of data from financial, clinical, demographic,  and socioeconomic inputs, the need to sift through and interpret that data is critical.

Where electronic health records (EHRs) fall short, a predictive patient relationship management can make up in value. EHRs were not designed to serve as predictive channels for their stored data. Providers need a solution that not only enables them to manage no-show and cancellation rates but also addresses questions like:

Providers genuinely want to spend more time doing what they do best: caring for their patients, not sift through volumes of unclassified, unstructured data. When relying on EHRs for patient engagement, physicians and nurse practitioners face many challenges indeed. What doctors and physicians seek is a tool that not only gives back lost time from using EHRs but a tool that enables two-way patient communication even when patients leave their care clinic, hospital or center. This calls for a communication medium to be put in place dedicated to engaging patients and helping doctors get what patients need when they need it.

It’s becoming more difficult for doctors to focus solely on their patients.

 

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Yves Mulkers

Yves Mulkers is the founder of 7wData and a widely followed voice in the data and AI community. He curates the 7wData and AI Beat newsletters, reaching hundreds of thousands of data and AI professionals, and writes on data strategy, analytics, AI, and the evolving data ecosystem.