Catching Cancer in Time

Vincenzo Scivittaro, MD, MS-MIS is the Director of Health Informatics and Population Health Solutions at IBM Watson Health.

The Iowa Clinic is the largest physician-owned, multi-specialty group in Central Iowa, with more than 200 physicians and healthcare providers practicing in more than 40 specialties. The organization makes a simple but powerful promise to its patients: “Dedicating our lives to taking care of yours.” Among the many ways that The Iowa Clinic delivers on this promise is how it uses technology in an effort to catch cancer in time.

The Iowa Clinic serves a population area of 1.1 million, averaging 450,000 patient visits each year.

“We use technology to help us personalize care,” said Melissa Linder, Director of Quality and Care Management at The Iowa Clinic. “We don’t have the amount of staff that would be required to make individual calls to thousands of people, but technology helps us identify and reach each person and remind him or her to make important appointments, such as those for cancer screenings.“

Here’s an example of how the The Iowa Clinic used that technology to identify, contact, diagnose and treat three women who are now breast cancer survivors.

FINDING PATIENTS IN NEED OF CARE

The Iowa Clinic uses a software solution from IBM Watson Health that automatically searches through all patient records and identifies patients who have care gaps, such as those who are due or overdue for mammograms.

The Iowa Clinic has programmed its solution to regularly look through its electronic medical records for women ages 40-74 who have not had a mammogram in the previous 12 months and don’t already have one scheduled. (The program excludes women who have been diagnosed or treated for breast cancer and require different kinds of screening.) Physicians can choose the age groups and frequency within each age group for their patients.

“We like the flexibility that this program offers us so physicians remain in control, and we like knowing the automation will help us reach more patients who have care gaps,” said Christi Taylor, MD, Chief Quality Officer at The Iowa Clinic.

REACHING PATIENTS IN NEED OF CARE

Once the solution identifies women in need of mammograms, it automatically calls, emails or texts (depending on patient preference) the women to remind them to make an appointment. If the women don’t respond within 30 days, the system automatically sends them another message. The messages continue until the care gap has been closed.

“We know these automated messages work, and in three particular cases, we see such a strong correlation between the messages and the women taking action to make mammogram appointments, that we believe our technology-driven outreach may have helped us save lives,” said Linder.

MAKING THE CONNECTION BETWEEN TECHNOLOGY AND CARE

The Iowa Clinic can refer to its patient records and see that these three women each made an appointment for a mammogram within a week of receiving an automated message from their doctor’s office. Then the data shows that within weeks the women were diagnosed with breast cancer, subsequently received treatment, and are now, a year later, in remission.

“At the organizational level, The Iowa Clinic appreciates being able to see how automated outreach and reminders are helping us deliver personalized, powerful, and necessary care to our patients,” Dr. Taylor said.

HOW TECHNOLOGY HELPED IOWA CLINIC CATCH CANCER IN TIME

Patient #1:

This patient regularly received mammograms from 2004-2011, but did not book one after the last one in 2011. A programmed algorithm within IBM Phytel Outreach automatically determined that the patient was overdue for a mammogram and did not have any future booked appointments in February of 2012. The patient received an Outreach-generated phone call in February 2012 and booked her mammogram less than two weeks later, closing her care gap. She continued booking regular mammograms on her own through May 2016.  In May 2017, Outreach determined she was again overdue and called her. She booked her appointment on the day of the call, which resulted in a follow up visit about a week later, a biopsy two weeks later, and a breast cancer diagnosis five days after the biopsy, with subsequent follow ups booked beyond that date.

 

Patient #2:

This patient regularly received mammograms from 2004-2015. In March of 2016, the patient had an inpatient hospital stay for cardiology-related issues, with related follow-up care through the rest of 2016. This episode is likely the cause of a missed mammogram in 2016. The patient had another hospitalization from late February through early March of 2017. A programmed algorithm within Outreach found her to be overdue for a mammogram and contacted her in March of 2017. On that same day, the patient booked her appointment for later in March. The mammogram resulted in a follow-up ultrasound in April and biopsy in May, with first diagnosis of breast cancer recorded six days after the biopsy. The patient had multiple follow-up visits in May/June with a cancer-related diagnosis and her next mammogram booked for January 2018.

 

Patient #3:

This patient received mammograms in 2009 and 2010. In March 2011, a programmed algorithm within Outreach found her to be overdue for a mammogram and contacted her via telephone, to which she responded that same day by booking an appointment for her mammogram. That screening took place in April. In 2012, Outreach again determined she was overdue and contacted her, and she responded by having her annual mammogram. The patient proactively booked mammograms without Outreach intervention from 2013-2015. In May 2016, she was again contacted via Outreach to book her annual mammogram and responded by closing that care gap in June 2016 . In July  2016, she had a follow-up ultrasound with an additional MRI follow up later that month. These led to a partial lumpectomy and breast cancer diagnosis in August. The patient had multiple surgical follow ups throughout August and September 2016. She had a follow-up mammogram in March of 2017 and was booked for another mammogram in October 2017.

 

Read this case study to learn how other IBM Watson Health clients are leveraging automated patient engagement solutions.