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Background A shareable repository of clinical notes is critical for advancing natural language processing (NLP) research, and therefore a goal of many NLP researchers is to create a shareable repository of clinical notes, that has breadth (from multiple institutions) as well as depth (as much individual data as possible). Methods We aimed to assess the degree to which individuals would be willing to contribute their health data to such a repository. A compact e-survey probed willingness to share demographic and clinical data categories. Participants were faculty, staff, and students in two geographically diverse major medical centers (Utah and New York). Such a sample could be expected to respond like a typical potential participant from the general public who is given complete and fully informed consent about the pros and cons of participating in a research study. Results Two thousand one hundred forty respondents completed the surveys. 56% of respondents were “somewhat/definitely willing” to share clinical data with identifiers, while 89% of respondents were “somewhat (17%)/definitely willing (72%)” to share without identifiers. Results were consistent across gender, age, and education, but there were some differences by geographical region. Individuals were most reluctant (50–74%) sharing mental health, substance abuse, and domestic violence data. Conclusions We conclude that a substantial fraction of potential patient participants, once educated about risks and benefits, would be willing to donate de-identified clinical data to a shared research repository. A slight majority even would be willing to share absent de-identification, suggesting that perceptions about data misuse are not a major concern. Such a repository of clinical notes should be invaluable for clinical NLP research and advancement.

Published guidelines have helped to standardize the care of patients with traumatic brain injury; however, there remains substantial variation in the decision to pursue or withhold aggressive care. The International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) prognostic calculator offers the opportunity to study and decrease variability in physician aggressiveness. The authors wish to understand how IMPACT’s prognostic calculations currently influence patient care and to better understand physician aggressiveness. The authors conducted an anonymous international, multidisciplinary survey of practitioners who provide care to patients with traumatic brain injury. Questions were designed to determine current use rates of the IMPACT prognostic calculator and thresholds of age and risk for death or poor outcome that might cause practitioners to consider withholding aggressive care. Correlations between physician aggressiveness, putative predictors of aggressiveness, and demographics were examined. One hundred fifty-four responses were received, half of which were from physicians who were familiar with the IMPACT calculator. The most frequent use of the calculator was to improve communication with patients and their families. On average, respondents indicated that in patients older than 76 years or those with a >85% chance of death or poor outcome it might be reasonable to pursue non-aggressive care. These thresholds were robust and were not influenced by provider or institutional characteristics. This study demonstrates the need to educate physicians about the IMPACT prognostic calculator. The consensus values for age and prognosis identified in our study may be explored in future studies aimed at reducing variability in physician aggressiveness and should not serve as a basis for withdrawing care.

Clinical decision support interventions are typically heterogeneous in nature, making it difficult to identify why some interventions succeed while others do not. One approach to identify factors important to the success of health information systems is the use of meta-regression techniques, in which potential explanatory factors are correlated with the outcome of interest. This approach, however, can result in misleading conclusions due to several issues. In this manuscript, we present a cautionary case study in the context of clinical decision support systems to illustrate the limitations of this type of analysis. We then discuss implications and recommendations for future work aimed at identifying success factors of medical informatics interventions. In particular, we identify the need for head-to-head trials in which the importance of system features is directly evaluated in a prospective manner.

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