Currently, Poindexter calculates care gaps and predicts the likelihood of hospital admissions, as well as readmissions, 6 to 12 months in advance for any given patient population — typically covered lives in a self-insured employer's health plan. The tool also examines data from claims, pharmacy and clinical sources, benchmarking against real-world health data adjusted for comparable demographics, geography and industry of the employer.

Poindexter assigns risk scores to individuals within that population – identifying people whose health profile suggests elevated risk. Case managers can improve outcomes and lower costs when they help patients avoid catastrophic events by improving their health through timely interventions.

"As data science and predictive analytics technologies get sharper every year, we hardwire new innovations into Poindexter so self-insured employers can mine actionable data and help their employees live healthier lives," said Neil Godbey, CEO, Advanced Plan for Health. "This upgrade represents one of the biggest leaps forward we've seen in some time."

New Condition-Specific Predictive Modeling Capabilities

Poindexter's newest release pushes the boundaries of predictive modeling by determining the likelihood of an occurrence of coronary events, neurological events, orthopedic events and chronic kidney disease. In addition, Poindexter now has the ability to predict hospital length of stay and general likelihood of an ER visit for any member of a patient population.  

Third-Party Administrators (TPAs) and brokers can leverage Poindexter's new functionality to better identify at-risk individuals in their customers' insured population. Employers with self-funded health plans can directly benefit, too.

"Five to seven percent of health plan participants account for 60 to 70 percent of spending," said Barbara Rutkowski, Vice President, Clinical Operations, Advanced Plan for Health. "These folks can benefit from early intervention and receiving needed guidance in navigating the healthcare maze. Having a user-friendly data analytics tool gives case managers more time to focus on their patients and less time combing through data to find patients who need interventions. Poindexter's predictive model finds these targeted cases and tracks results."

"We use Poindexter to meet with our TPA, broker, PBM, senior leadership and medical management team, including physicians, to review our monthly dashboard," said Debby Neel, RN, BSN, Director of System Wellness and Community Health at Memorial University Medical Center in Savannah, Georgia. "We use the data to develop interventions that address specific individual risks, as well as financial and quality variances identified in the population. Advanced Plan for Health provides the information we need to meet our clinical and financial goals, and its new predictive analytics capabilities will be great in helping us continue our aggressive, proactive approach." 

Maiken Himmel, RN, BSN, Employee Nurse Navigator at Baptist Health Floyd in New Albany, Indiana echoes these sentiments: "Hospitals are under pressure to avoid readmissions, and decrease preventable use of the emergency department and inpatient services. Poindexter helps me manage our associates and their families, direct them to appropriate care settings and work proactively to create a health culture that decreases expensive facility care. Its data supported the addition of a Nurse Practitioner, and provided evidence of how our diabetic members have improved. The new functionality will only be more useful."

Learn more at APH-online.com and MyPoindexter.com.