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Epic Healthy Planet Increased Patient Adherence to Preventive Care

Epic Healthy Planet used EHR data to determine care gaps for older high-risk patients, resulting in greater patient adherence to preventive care services such as cancer screening and vaccinations.

After piloting the population health tool, Epic Healthy Planet, primary care providers at UC Davis Health were able to directly address care gaps through personalized EHR data reports to significantly upend patient adherence to preventive care.

The study examined how EHR optimizations like population health tools impacted healthcare delivery and decreased the adverse outcomes preventable diseases have on older patients.

“Unfortunately, primary care physicians are inundated with numerous patient health concerns throughout the day, and some screening tests can be forgotten,” Eric Chak, associate professor of gastroenterology and hepatology and lead investigator on the study, stated in the press release. “In California there is currently just a lung cancer screening rate of 1 percent of eligible adults.”

Prior to a patient visit, patient data was used to create custom reports and bundle orders based on patient care gaps for several healthcare maintenance areas such as colon cancer screening, lung cancer screening, tobacco and obesity counseling, age-appropriate vaccines, and hepatitis C screening.

Unlike a traditional clinical care encounter, these reports capture data on a population level to administer appropriate action to multiple patients simultaneously. 

A nonphysician pre-visit planner specializing in prevention education would then access the Epic Healthy Planet Reporting Workbench to view healthcare maintenance reports.

To ensure proper patient engagement, patients were contacted by the pre-visit planners regarding the intervention to prepare patients for preventative services.

The study, “Enhancing Electronic Health Systems to Decrease the Burden of Colon Cancer, Lung Cancer, Obesity, Vaccine-Preventable Illness, and Liver Cancer” (CLOVER), triggered positive results.

From July 2020 to July 2021, patient adherence to lung cancer screening improved by 212 percent through utilizing the population health tool compared to 40 percent in the control clinic.

“The COVID-19 pandemic has created a shift in how we practice medicine, and patients now don't always have the need to see their doctor face-to-face,” stated Chak. “Being proactive and seeking out those people that are at risk opposed to waiting for them to come to the doctor is an effective way to prevent potential illnesses.”

In addition, obesity counseling adherence improved by 126 percent. However, the control clinic only experienced a 6 percent improvement in patient adherence.

During the study, patient adherence to colon cancer screenings only improved by 4 percent at the intervention clinic versus 1 percent at the control clinic.

Researchers noticed more minor improvements in tobacco counseling and pneumonia vaccination.

Ultimately, the use of the electronic population health tool enhanced care coordination for patients 50 years or older and ensured they received the necessary care.

Due to the success of the study, researchers expanded and replicated the model to several clinics and federally qualified health centers.

“With the CLOVER model, we are aspiring to streamline healthcare for patients and in some ways create a one-stop-shop,” explained Moon S. Chen Jr, professor in population sciences and health disparities and one of the principal investigators. “With the aging population in the United States, we have a tremendous opportunity to connect with older patients and actively work towards preventing future illnesses.”

According to a 2021 KLAS research report, Epic was received as one of the most well-rounded leaders in population health management alongside Arcadia and Innovaccer.

Epic’s population health management platform is one of many modules the health IT company offers to help providers in a variety of specialties improve patient care delivery and meet federal requirements.

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