Automated Care Coordination Tool Improves Timeliness of Liver Cancer Care

A new study published in PLOS Digital Health shows that an automated care coordination tool can successfully identify and track cases of hepatocellular carcinoma (HCC), a type of liver cancer, which results in improved timeliness of diagnosis and treatment.

According to the Centers for Disease Control and Prevention (CDC), about 25,000 men and 11,000 women get liver cancer each year in the US. Roughly 19,000 men and 9,000 women die from the disease annually.

Globally, liver cancer is the sixth most diagnosed cancer and the fourth leading cause of cancer mortality, the study authors stated. The disease causes 782,000 deaths each year worldwide, and 75 percent of all liver cancer cases are HCC-related.

HCC usually occurs in patients with chronic liver disease, making it complex to treat. HCC prognosis is determined by both the stage at diagnosis and severity of the underlying liver disease, making timely detection and treatment critical. The researchers further noted that HCC incidence is growing the fastest out of all cancers in the US, having tripled in the past 30 years, making research in this area crucial.

The research team began by implementing an EMR-linked abnormal imaging identification and tracking system at Veterans Affairs (VA) Connecticut Healthcare System. The tool was designed to review all liver radiology reports, generate a queue of abnormal cases for review, and maintain a queue of cancer care events with due dates and automated reminders.

This allowed the system to flag abnormal imaging that raised suspicions of liver cancer by using diagnostic codes and natural language processing. It also enabled the system to send reminders for follow-up testing and treatment.

The researchers evaluated the system’s impact on the timeliness of HCC care by measuring the time between stages of care pre- and post-implementation, including time between HCC diagnosis and treatment and time between the first liver image that indicated HCC, specialty care, diagnosis, and treatment. A total of 60 patients diagnosed with HCC three years before system implementation were compared to 127 diagnosed nearly six years after its implementation.

Overall, the average time from diagnosis to treatment was 36 days shorter, time from imaging to diagnosis 51 days shorter, and time from imaging to treatment 87 days shorter for those in the post-implementation group. This group also had a greater proportion of HCC patients diagnosed at earlier clinical stages.

From these results, the authors concluded that an automated care coordination system might have the potential for improving HCC care timeliness and delivery, including in health systems that already utilize HCC-specific screening.

Further, such a tool may systematically address care gaps in at-risk populations, they noted.

Amid growing HCC incidence, some stakeholders are developing technology to prevent and accurately diagnose the disease.

In a recent interview with PharmaNewsIntelligence, leaders from software company Oncoustics revealed that the company has developed new AI software to improve liver disease diagnosis and prevention using ultrasound technology.

The tool is designed to be less invasive than traditional diagnostics, which rely on blood tests, medical imaging, and biopsies, while being cost-effective and accessible for providers and patients.