Improvement in Stage of Lung Cancer Diagnosis With Incidental Pulmonary Nodules Followed With a Patient Tracking System and Computerized Registry.

Introduction: Given that an incidental pulmonary nodule (IPN) on chest computed tomography (CT) may represent nascent lung cancer, timely follow-up imaging is critical to assess nodule growth and the need for tissue sampling. We previously reported our institution's systematic process to identify and track patients with an IPN associated with improved CT on follow-up. We hypothesized that this improvement may have led to a higher frequency of early-stage lung cancer. To evaluate this, we performed a study to determine whether cases of early-stage lung cancer were more likely to have had our tracking system applied to suspicious findings. Methods: An observational study was performed by identifying cases of lung cancer that were detected as IPNs on chest CT scans performed at our institution, from 2006 to 2016. A total of 314 cases were dichotomized into early-stage (stage 1) or late-stage (stages II to IV) disease. A multivariant regression analysis with modeling was used to determine factors associated with a diagnosis of early-stage disease. Factors included the use of the tracking system and nodule registry. Results: The following factors were independently associated with early-stage lung cancer: index nodule diameter, (OR = 0.971, confidence interval [CI]: 0.948-0.995], p = 0.016), adenocarcinoma histology (OR = 2.930 [CI: 1.695-5.064], p = 0.0001) and use of tracker phrases on CT reports (OR = 1.939 [CI: 1.126-3.339], p = 0.016). Conclusions: The application of a patient tracking system and computerized lung nodule registry lead to an increased frequency in the diagnosis of stage 1 NSCLC from IPNs. This is a meaningful outcome for patients and should be adapted for IPN management.

Improvement in Follow-up Imaging With a Patient Tracking System and Computerized Registry for Lung Nodule Management.

PURPOSE: Despite established guidelines, radiologists' recommendations and timely follow-up of incidental lung nodules remain variable. To improve follow-up of nodules, a system using standardized language (tracker phrases) recommending time-based follow-up in chest CT reports, coupled with a computerized registry, was created. MATERIALS AND METHODS: Data were obtained from the electronic health record and a facility-built electronic lung nodule registry. We evaluated two randomly selected patient cohorts with incidental nodules on chest CT reports: before intervention (September 2008 to March 2011) and after intervention (August 2011 to December 2016). Multivariable logistic regression was used to compare the cohorts for the main outcome of timely follow-up, defined as a subsequent report within 13 months of the initial report. RESULTS: In all, 410 patients were included in the pretracker cohort versus 626 in the tracker cohort. Before system inception, 30% of CT reports lacked an explicit time-based recommendation for nodule follow-up. The proportion of patients with timely follow-up increased from 46% to 55%, and the proportion of those with no documented follow-up or follow-up beyond 24 months decreased from 48% to 31%. The likelihood of timely follow-up increased 41%, adjusted for high risk for lung cancer and age 65 years or older. After system inception, reports missing a tracker phrase for nodule recommendation averaged 6%, without significant interyear variation. CONCLUSIONS: Standardized language added to CT reports combined with a computerized registry designed to identify and track patients with incidental lung nodules was associated with improved likelihood of follow-up imaging.

Predictors of mortality in rheumatoid arthritis-associated interstitial lung disease.

Interstitial lung disease (ILD) is a common pulmonary manifestation of rheumatoid arthritis. There is lack of clarity around predictors of mortality and disease behaviour over time in these patients.We identified rheumatoid arthritis-related interstitial lung disease (RA-ILD) patients evaluated at National Jewish Health (Denver, CO, USA) from 1995 to 2013 whose baseline high-resolution computed tomography (HRCT) scans showed either a nonspecific interstitial pneumonia (NSIP) or a "definite" or "possible" usual interstitial pneumonia (UIP) pattern. We used univariate, multivariate and longitudinal analytical methods to identify clinical predictors of mortality and to model disease behaviour over time.The cohort included 137 subjects; 108 had UIP on HRCT (RA-UIP) and 29 had NSIP on HRCT (RA-NSIP). Those with RA-UIP had a shorter survival time than those with RA-NSIP (log rank p=0.02). In a model controlling for age, sex, smoking and HRCT pattern, a lower baseline % predicted forced vital capacity (FVC % pred) (HR 1.46; p<0.0001) and a 10% decline in FVC % pred from baseline to any time during follow up (HR 2.57; p<0.0001) were independently associated with an increased risk of death.Data from this study suggest that in RA-ILD, disease progression and survival differ between subgroups defined by HRCT pattern; however, when controlling for potentially influential variables, pulmonary physiology, but not HRCT pattern, independently predicts mortality.

Using patient lists to add value to integrated data repositories.

Patient lists are project-specific sets of patients that can be queried in integrated data repositories (IDR's). By allowing a set of patients to be an addition to the qualifying conditions of a query, returned results will refer to, and only to, that set of patients. We report a variety of use cases for such lists, including: restricting retrospective chart review to a defined set of patients; following a set of patients for practice management purposes; distributing "honest-brokered" (deidentified) data; adding phenotypes to biosamples; and enhancing the content of study or registry data. Among the capabilities needed to implement patient lists in an IDR are: capture of patient identifiers from a query and feedback of these into the IDR; the existence of a permanent internal identifier in the IDR that is mappable to external identifiers; the ability to add queryable attributes to the IDR; the ability to merge data from multiple queries; and suitable control over user access and de-identification of results. We implemented patient lists in a custom IDR of our own design. We reviewed capabilities of other published IDRs for focusing on sets of patients. The widely used i2b2 IDR platform has various ways to address patient sets, and it could be modified to add the low-overhead version of patient lists that we describe.