Background: The process of screening and/or detection to the actual diagnosis of lung cancer involves multiple specialties and diagnostic testing, which can be quite daunting for an individual and his/her family. A symptomatic patient presents to the hospital emergency department, leading to hospital admission and subsequent diagnosis may also make this time disjointed and confusing for a patient. Three previous patients were noted to have lung nodules on previous CT scans; however, patients did not follow up with emergency department recommendations or were not aware of the nodule. Subsequently, several months later, these patients became symptomatic and were eventually diagnosed with lung cancer.
Objectives: To improve coordination of care of individuals found to have lung nodules leading to a lung cancer diagnosis. To decrease time from lung cancer diagnosis to treatment time.
Methods: Community hospital of a large hospital system instituted artificial intelligence to alert a lung nodule coordinator of incidental findings of lung nodule on CT scans performed in the emergency department. The lung nodule coordinator navigates the patient through the healthcare system, identifying any barriers that may impede the rendering of a cancer diagnosis. Early identification of barriers, including transportation and lack of insurance, are identified by the coordinator. Referrals to resources to obtain healthcare/testing are made. Initiation of Medicaid application and Social Security Disability applications are done. Once diagnosed with lung cancer, the lung nodule coordinator alerts and hands off the patient to the thoracic oncology nurse navigator (ONN) within 2 days.
Results: Since the inception in April 2019, 43 patients have been successfully coordinated from lung nodule to lung cancer diagnosis. The average time from diagnosis to first visit with the oncologist is 7 days, and the average diagnosis to treatment time is 34 days. To date, 7 of 9 uninsured patients have received Medicaid/Medicare and/or Marketplace insurance with assistance of coordination between the lung nodule coordinator and the thoracic ONN. One outmigration was thwarted by the ONN with early intervention.
Conclusion: The lung nodule coordinator is alerted of incidental lung nodules from CT scans performed in the emergency department. The nodule coordinator works to remove barriers to care for patients by ensuring they have the resources and appointments to obtain a cancer diagnosis. The thoracic ONN is then alerted by the coordinator when the patient has an official lung cancer diagnosis. This allows for timely intervention and appointment procurement to the appropriate oncology provider. Patients experience increased coordination and less fragmented care. This results in decreased diagnosis to treatment times. Early identification of barriers helps to ensure that patients adhere to treatment plans. Patients also benefit from having a single point of contact for questions/concerns prior to actual diagnosis and a seamless transition to navigation by the thoracic ONN once a lung cancer diagnosis is obtained.