A presentation during the recent RIMS 2016 Annual Conference demonstrated the results of using predictive analysis to help reduce workers’ compensation risks and costs.
“Predictive analytics is a critical tool to identify potential high-cost claims, ensure early intervention, and deploy the right treatments throughout the course of a claim,” notes Michelle Despres, PT, CEAS II, vice president and national product leader at Align Networks, a division of One Call Care Management and a provider of workers’ compensation physical medicine programs, during her presentation.
“With these insights, we can make more accurate decisions, get more timely care for the injured worker, and head off potential problems before they impact both the cost and outcome of a claim,” she adds, according to a media release.
According to the release, predictive analytics involves overlaying algorithms onto claim and managed care data to identify patterns, gain insights on claims and patient populations, identify the need to take specific actions, and even change the clinical pathways for injured workers.
During the presentation, Despres and her co-presenter, JJ Schmidt, senior vice president at York Risk Services Group, shared examples of results from the use of predictive analytics, suggesting that by identifying “at risk” claims early, managers may be able to lower costs for surgery, medical equipment, and other treatments.
Key measures of success in predictive analytics, they advise, include: average claim costs; average medical costs; average number of disability/lost time days; and average number of days for claim, open to close.
Additional data points that may be included in the analysis, according to the release, include: therapy benchmarks, length of time between medical treatments, types of medication, duration of treatment or disability, equipment or supply cost thresholds, and psychosocial factors.
[Source(s): Align Networks, Business Wire]