“We reduced our hospitalization rate from 11.6% to 8.2% when we were using Kinnser RiskPoint. That’s a 29.7% reduction," said Jonathan Wohlgemuth, Chief Operating Officer of Community Home Health, Inc.
Austin, TX (PRWEB) May 10, 2016
Kinnser Software today launched Kinnser RiskPoint, a predictive analytics software solution to help home health agencies reduce hospitalizations, and presented strong results from agencies that have been using the solution in a pre-release trial since January 2016.
Kinnser RiskPoint utilizes a cutting-edge, predictive algorithm based on real-world data from the largest dataset in home health––more than 3 million patient episodes in Kinnser Agency Manager™, the most widely used software in home health. Every day, Kinnser RiskPoint automatically analyzes hundreds of data points in the medical record of each patient of a home health agency to accurately assess his or her current risk of hospitalization. The results are displayed for clinical staff on an easy to use dashboard that lets them click into details and communicate with their clinical team to take preventative action. The Center for Health Information and Analysis Improved has identified communication with patients, colleagues and other providers as a key factor in reducing readmission.
Designed to tackle one of healthcare’s toughest and most costly problems––
Hospitalization of home health care patients is a multi billion-dollar challenge in the US. Of the 6.7 million home health care patient episodes that occurred in 2015, over 1,025,000 (15.3%) resulted in the patient going to the hospital. At an average cost of $11,200 per patient hospitalization, this represents more than $11 billion in total healthcare system costs. The Medicare Payment Advisory Commission (MedPAC) estimates that 76% of patient hospitalizations are preventable. Kinnser RiskPoint is designed to significantly reduce these preventable hospitalizations.
“Preventable hospital admissions represent a significant opportunity for home health care and for our country,” said Chris Hester, president and founder of Kinnser Software. “Kinnser RiskPoint puts the tremendous power of data science and machine-learning technology into the hands of all home health providers for the first time--and the results thus far have been truly amazing. With this solution as their competitive advantage, our agencies will be able grow their businesses while also improving the lives of their patients.”
Agencies already experiencing dramatic results––
Kinnser also announced early results reported by agencies that participated in the pre-release trial of Kinnser RiskPoint. “We saw a large reduction in hospitalization,” said Jonathan Wohlgemuth, Chief Operating Officer of Community Home Health, Inc. “Comparing February 1 to March 31 of 2016 to the same period last year in 2015, we reduced our hospitalization rate from 11.6% to 8.2% when we were using Kinnser RiskPoint. That’s a 29.7% reduction.”
Gayla Anderson, RN, BSN, MHR Community Home Health’s Director of Nursing believes the new software is helping her patients receive better care. “Kinnser RiskPoint helps you be a better nurse,” says Anderson. “It prompts you to dig deeper, look harder, and listen more closely… not just to keep patients out of the hospital, but to ensure they have better outcomes.” Community Home Health, Inc. serves an average of 380 patients in Claremore, Oklahoma.
A marketing boon for home health agencies––
Another agency that has already been using Kinnser RiskPoint is Custom Home Health, which serves an average of more than 300 patients in Royal Oak, Michigan. Agency president Chris Tillotson sees a marketing value in Kinnser RiskPoint and says that the new solution was a significant factor in his agency earning new business with an Accountable Care Organization (ACO). “Every ACO in the country cares about hospitalization,” says Tillotson. “Kinnser RiskPoint is absolutely a differentiator––a golden nugget in our pocket. It’s a tool that Custom Home Health will use with every referral source.”
Predicting the future by using the past––
Kinnser’s team of data scientists spent over a year developing Kinnser RiskPoint, analyzing over 2,100 data points for more than 3 million past patients in the Kinnser EHR to better understand the most powerful underlying predictors of hospital admissions. The Kinnser RiskPoint algorithm is strengthened by information from a patient’s Comprehensive Assessment and Plan of Care and updated daily with new vital sign information. Due to this deep and real-time data set, Kinnser’s admission prediction algorithm is the most powerful and accurate of its kind ever introduced.
Kinnser RiskPoint is available now to home health agencies using the Kinnser Agency Manager EHR. More info at http://www.kinnser.com/riskpoint.