Data to Help Elderly Patients

A new company and tool called “Patient Pattern” founded by Steven Buslovich MD developed by a start-up program in New York was developed in the Jacobs School of Medicine and Biomedical Sciences at the University of Buffalo (UB) The tool has a cloud-based solution called “LivePAC” to not allow inappropriate treatments to be given to elderly patients in nursing homes.

The cloud-based solution uses data taken when a patient is admitted to a nursing home or a hospital and is able to compare their medical information with thousands of previous cases to assess the patient’s risks.

Patient Pattern is not a tool for day-to-day care, but rather to use to determine the broader assessment of the risks a patient faces and how to handle the risks. For example, some patients receive too much medicine or receive unnecessary tests.

In the case of a frail person, the risk is raised for a poorer outcome. By reducing hospital readmissions and reducing the use of expensive low yield therapies, patient outcomes can rapidly improve as well as improve the finances and overall operations in facilities.

In another project connected with UB, a research team is developing a software tool called Vizier to be released as free open source software to help people try to draw conclusions from raw data. This project backed by a $2.7 million National Science Foundation (NSF) grant was launched in January to enable users to interactively work with data sets.

Vizier will help people explore, clean, curate, and visualize data in meaningful ways as well as spot efforts and offer solutions. However, unlike spreadsheet software, Vizier will allow users to interactively work with datasets and is intended to be used with much larger datasets to make it possible to examine millions of billions of data points, as opposed to hundreds or thousands typically plugged into spreadsheet software.

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