An Algorithm Using Medical Record Data Predicts Risk for Parkinson ' s Disease

We are entering an era when algorithms will be used to analyze data in the LIS and EHR databases and predict the risk of a patient developing various disease(s) in the future. This field is often referred to aspredictive healthcare analytics. A recent article discussed this process in terms of predicting the onset of Parkinson's disease (see:Algorithm scans medical records for higher Parkinson ’s risk), Below is an excerpt from it:Researchers have developed an algorithm that could check patients ’ medical histories to find signs of increased risk for developing Parkinson’s disease and alert doctors to evaluate patients at greater risk. Before symptoms become pronounced, there is no reliable way to identify who is on track to develop Parkinson’s disease....The algorithm relies on information in patients ’ medical records, such as tests and diagnoses of various medical conditions....One of the most interesting findings is that people who are going to develop Parkinson’s have medical histories that are notably different from those who don’t develop the disease.....[The authors of a paper on this topic] analyzed de-identified medical claims data for Medicare beneficiaries nationwide, ages 66 to 90. They found 89,790 people who had been diagnosed with Parkinson ’s in 2009, and matched them with 118,095 people in the same age range who had not been diagnosed with Parkinson’s in 2009 or prior years. Then, the researchers sifted through each person â...
Source: Lab Soft News - Category: Laboratory Medicine Authors: Tags: Clinical Lab Industry News Clinical Lab Testing Electronic Health Record (EHR) Healthcare Delivery Healthcare Information Technology Lab Industry Trends Medical Consumerism Medical Ethics Medical Research Source Type: blogs