Electronic Health Record Triggers Can Identify Patients With Suspected Lung Cancer, Study Indicates

A “trigger” algorithm in electronic health record (EHR) systems can be used to identify patients who may have cancer for whom follow-up screening was delayed, according to an article and abstract that were published online May 11 in the journal Radiology. The research, supported in part by an AHRQ grant, sought to establish whether an EHR-based trigger notification could identify delays in follow-up of imaging results that suggested lung cancer. Researchers designed the trigger as an alert to notify clinicians when a patient with an abnormal lung imaging result did not receive a follow-up diagnostic evaluation in a timely manner. They tested it in a large health care facility over a one-year period. In that period, 89,168 patients visited the facility, 24,829 had at least one chest image taken and 538 had findings that radiologists flagged as suspicious. The trigger algorithm identified 131 patients, of whom 75 were found to have a delay in follow-up action, which was confirmed through a manual review of records.

2015 May 11:142530. [Epub ahead of print]

Development and Validation of Electronic Health Record-based Triggers to Detect Delays in Follow-up of Abnormal Lung Imaging Findings.

Murphy DR1, Thomas EJ, Meyer AN, Singh H.

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Abstract

Purpose To develop an electronic health record (EHR)-based trigger algorithm to identify delays in follow-up of patients with imaging results that are suggestive of lung cancer and to validate this trigger on retrospective data. Materials and Methods The local institutional review board approved the study. A "trigger" algorithm was developed to automate the detection of delays in diagnostic evaluation of chest computed tomographic (CT) images and conventional radiographs that were electronically flagged by reviewing radiologists as being "suspicious for malignancy." The trigger algorithm was developed through literature review and expert input. It included patients who were alive and 40-70 years old, and it excluded instances in which appropriate timely follow-up (defined as occurring within 30 days) was detected (eg, pulmonary visit) or when follow-up was unnecessary (eg, in patients with a terminal illness). The algorithm was iteratively applied to a retrospective test cohort in an EHR data warehouse at a large Veterans Affairs facility, and manual record reviews were used to validate each individual criterion. The final algorithm aimed at detecting an absence of timely follow-up was retrospectively applied to an independent validation cohort to determine the positive predictive value (PPV). Trigger performance, time to follow-up, reasons for lack of follow-up, and cancer outcomes were analyzed and reported by using descriptive statistics. Results The trigger algorithm was retrospectively applied to the records of 89 168 patients seen between January 1, 2009, and December 31, 2009. Of 538 records with an imaging report that was flagged as suspicious for malignancy, 131 were identified by the trigger as being high risk for delayed diagnostic evaluation. Manual chart reviews confirmed a true absence of follow-up in 75 cases (trigger PPV of 57.3% for detecting evaluation delays), of which four received a diagnosis of primary lung cancer within the subsequent 2 years. Conclusion EHR-based triggers can be used to identify patients with suspicious imaging findings in whom follow-up diagnostic evaluation was delayed. © RSNA, 2015.