QIM119-120: Utilizing Technology to Identify Oncology Patients to Impact Patient Care

Abstract

Background: Sarah Cannon has established a standardized nurse navigation program for breast, lung, and Gi cancer patients. Navigators play a significant role in addressing barriers that may adversely impact patient outcomes. Historically, nurse navigators were spending up to 65% of their time data mining to identify new patients for navigation. This lost time compromises a navigator’s ability to effectively support patients. Sarah Cannon implemented a technology solution to address this manual process. Methods: A patient identification software application (patient ID), utilizing natural language processing technology, was developed to identify positive pathology reports across the enterprise in real time. Patient ID instantly routes those reports to a tumor site-specific oncology nurse navigator. The impact of this technology was assessed in 3 Hospital Corporation of America (HCA) markets from December 2016–March 2017. Total patient recall, total volume of reports reviewed, navigated patient volumes, navigator time allocation, and time from diagnosis to first treatment were studied. Results: Patient ID reviewed 47,544 pathology reports during the 4-month pilot, identifying 7,224 potential cancer reports. 2,782 of those represented breast, lung, or Gi cancer patients and were routed to a nurse navigator. Patient ID performed with an overall total patient recall of 98%, respectively. Decreased time spent data mining was observed, and navigator caseload increased by 71%. Time from diagnosis to first treatment decreased by an average of 6 days. Time allocated to direct patient contact and physician interaction increased by 35%. Conclusions: Implementation of a technology solution to rapidly identify new cancer patients for navigation in a community health system is feasible and associated with multiple benefits. Increased navigator patient volumes and navigator productivity were observed. Navigator time spent with patients and physicians increased with a concurrent reduction in data mining time. Timeliness of care metrics improved, suggesting a favorable impact on quality. This technology is now being deployed across the HCA enterprise.