Big Data is widely seen as a major opportunity for progress in the practice of personalized medicine, attracting the attention from medical societies and presidential teams alike as it offers a unique opportunity to enlarge the base of evidence, especially for older patients underrepresented in clinical trials. This study prospectively assessed the real-time availability of clinical cases in the Health & Research Informatics Total Cancer Care™ (TCC) database matching community patients with cancer, and the impact of such a consultation on treatment.
Patients aged 70 and older seen at the Lynn Cancer Institute (LCI) with a documented malignancy were eligible. Geriatric screening information and the oncologist\'s pre-consultation treatment plan were sent to Moffitt. A search for similar patients was done in TCC and additional information retrieved from Electronic Medical Records. A report summarizing the data was sent and the utility of such a consultation was assessed per email after the treatment decision.
Thirty one patients were included. The geriatric screening was positive in 87.1% (27) of them. The oncogeriatric consultation took on average 2.2 working days. It influenced treatment in 38.7% (12), and modified it in 19.4% (6). The consultation was perceived as \"somewhat\" to \"very useful\" in 83.9% (26).
This study establishes a proof of concept of the feasibility of real time use of Big Data for clinical practice. The geriatric screening and the consultation report influenced treatment in 38.7% of cases and modified it in 19.4%, which compares very well with oncogeriatric literature. Additional steps are needed to render it financially and clinically viable.

Epidemiologic study of sarcoidosis utilizing electronic databases has been increasingly popular. However, the accuracy of diagnostic codes for sarcoidosis is unknown.
The medical record-linkage system of the Rochester Epidemiology Project was searched to identify all potential adult cases of sarcoidosis between January 1, 1995 and December 31, 2013 in Olmsted County, Minnesota, using the International Classification of Diseases, Ninth Revision (ICD-9) code 135 (sarcoidosis). Complete medical records of those potential cases were individually reviewed. The diagnosis of sarcoidosis was confirmed by the presence of non-caseating granuloma on histopathology, radiographic findings of intrathoracic sarcoidosis, and compatible clinical presentations. Positive predictive value (PPV) was estimated as the number of patients verified to have sarcoidosis divided by the number of patients with a diagnostic code for sarcoidosis.
The study cohort included 366 patients with at least one code for sarcoidosis. Of these, 224 cases of confirmed sarcoidosis were identified, resulting in PPV of 61.2% (95% CI 56.0-66.2%). A total of 268 patients in the database had a code for sarcoidosis on least two occasions separated by at least 30 days. Of these, there were 205 cases of confirmed sarcoidosis. The PPV for having the code at least twice was 76.5% (95% CI 71.0-81.4%).
The PPV of ICD-9 code for sarcoidosis is relatively low and, thus, further verification is required for studies using electronic databases.