HEALTHCARE ENTERPRISE: Great Expectations: Medalogix Redefines Predictive Modeling Possibilities for Home Health Providers
HEALTHCARE ENTERPRISE: Great Expectations: Medalogix Redefines Predictive Modeling Possibilities for Home Health Providers | Medalogix, Dan Hogan, Gerry Andrady, Predictive Modeling, Alternate Solutions HomeCare, Home Health Software, Hospital Readmissions

Dan Hogan
The crystal ball of rehospitalization just got a whole lot clearer, thanks to an innovative newcomer in Nashville’s healthcare technology market. Through their predictive modeling technology, Medalogix is reducing hospitalizations and costs for post-acute home health providers.

 

Medalogix Takes Flight

Founded by home health veteran Dan Hogan and chief technology officer Gerry Andrady, Medalogix was created with the goal of reducing hospitalization among home health patients — a population at high risk of falling through the cracks due to multiple doctors, medications and diagnoses.

Medalogix then partnered with Ohio-based Alternate Solutions HomeCare to develop a pilot program involving 11 agencies and some 2,500 home health patients in three states. The results? Alternate Solutions HomeCare has doubled the accuracy with which it can identify new patients most likely to require rehospitalization. The recent findings exceeded promising results from Medalogix’s initial beta testing.

“We found some remarkable success early on during testing,” said Hogan, who was able to predict just under 74 percent of hospitalizations. Real world results showed accuracy at predicting which patients were most at risk of rehospitalization — that is, those in the top 10 percent of all at-risk patients — increased by 90 percent, more than 16 percent above beta testing. That means Medalogix was 80 percent more likely than a random selection of at-risk patients to predict which would necessitate inpatient care.

 

How It Works

Tessie Ganzsarto, Alternate Solutions president and co-founder, partnered with Medalogix to better manage a large patient population that is frequently sick and hospitalized.

“The information given to us by Medalogix each day allows us to look at patients differently,” Ganzsarto said. “To know that much about your patients and their critical areas so soon means we can be proactive and react much faster.”

The process starts with a 20-page questionnaire filled out during an in-home visit with a home health nurse.

“The survey is remarkably detailed and generates numeric answers from 200 questions,” Hogan said. “From there, we balance medication and clinical risks with utilization, mesh that together and assign each patient a risk score. The real value is not just the number it assigns but the rank, or risk of patients going into the hospital under care of that agency.”

Medalogix pulls the client’s patient information into a databank and, using customized criteria, ranks risk of readmission for each patient on a scale of one to 10. Each morning, Alternate Solutions has data needed to help prevent serious health problems in their most critical patients. The process used to take weeks, or even months. Now, those results are updated every 24 hours.

“What happens is we say, ‘We need to do things differently for this patient, or be more attentive to that patient,’” Ganzsarto said. “That may mean extra phone calls, home visits, therapy, or a call to the doctor to discuss care.”

Medalogix doesn’t make treatment or medication recommendations, but issues risk of hospitalization based solely on critical data.

 

Finding Their Algorithm

A leading indicator for rehospitalization is the total number of prescriptions a patient is taking, Hogan said. In fact, data shows the type of medication a person takes is less indicative than the overall number of drugs taken. A patient on 10 medications is 25 percent more likely to reenter the hospital within 30 days than a patient on two.

Medalogix uses factors such as geography to customize a unique algorithm for each client. According to Hogan, patients in a rural Tennessee community will have different predictive elements for hospitalization than those in an Oregon suburb. And while predictive modeling isn’t a new concept in healthcare, customization of the technology is. 

“Others are doing this as an aggregate of all data, but the weak point in that approach is what can be predicted on a local basis,” Hogan said. “We’re finding better and more accurate ways to do that.”

It takes approximately 30 days to begin using Medalogix data for daily risk protocol, and the service costs a few dollars per patient per month.

 

Medalogix and the Affordable Care Act

While Medalogix got its wings in home health, the company is positioned to soar across the healthcare continuum.

Medalogix was founded in 2009, shortly before introduction of the Affordable Care Act. When healthcare reform sent leaders and policymakers dabbling in data analytics, Medalogix pivoted into predicting rehospitalization based on clinical records for home health agencies and nursing homes.

From 2010 until the Supreme Court’s recent decision to uphold healthcare reform, Medalogix has seen increasing partnerships between acute providers and hospitals, as each has a financial stake in keeping patients out of the hospital. Effective October 2012, the first large-scale Hospital Value-Based Purchasing Program will pay more than 3,500 hospitals according to whether they meet performance standards. At that time, the ACA’s Readmission Reduction Program also will require CMS to reduce payments to hospitals with excess readmissions.

“If hospitals discharge patients to home care, they have two financial areas of exposure,” Hogan said. “If that patient comes back in 30 days, home care loses out on revenue, and the hospital is penalized.”

Increased accountability also gives hospitals more incentive to consolidate discharges to skilled patient providers doing the best work. Physicians also are increasingly aware of the need to streamline processes involving CMS patients and medication management, Hogan said. The technology also is helping hospitals pinpoint doctors and agencies with the highest readmission rates, and compare their own providers to those in the next town.

“The benefit is a whole world of quality improvement opportunities for clients and the patients they work with,” Hogan said. “Research proves that patients in homecare see better outcomes if they remain at home. Cost benefit aside, our ultimate goal is to provide better care for people, and we’re very excited about what we’re able to offer.”