Simulating Realistic Continuous Glucose Monitor Time Series By Data Augmentation.

BACKGROUND: Simulated data are a powerful tool for research, enabling benchmarking of blood glucose (BG) forecasting and control algorithms. However, expert created models provide an unrealistic view of real-world performance, as they lack the features that make real data challenging, while black-box approaches such as generative adversarial networks do not enable systematic tests to diagnose model performance. METHODS: To address this, we propose a method that learns missingness and error properties of continuous glucose monitor (CGM) data collected from people with type 1 diabetes (OpenAPS, OhioT1DM, RCT, and Racial-Disparity), and then augments simulated BG data with these properties. On the task of BG forecasting, we test how well our method brings performance closer to that of real CGM data compared with current simulation practices for missing data (random dropout) and error (Gaussian noise, CGM error model). RESULTS: Our methods had the smallest performance difference versus real data compared with random dropout and Gaussian noise when individually testing the effects of missing data and error on simulated BG in most cases. When combined, our approach was significantly better than Gaussian noise and random dropout for all data sets except OhioT1DM. Our error model significantly improved results on diverse data sets. CONCLUSIONS: We find a significant gap between BG forecasting performance on simulated and real data, and our method can be used to close this gap. This will enable researchers to rigorously test algorithms and provide realistic estimates of real-world performance without overfitting to real data or at the expense of data collection.

Online Learning and Residents' Acquisition of Mechanical Ventilation Knowledge: Sequencing Matters.

OBJECTIVE: Rapid advancements in medicine and changing standards in medical education require new, efficient educational strategies. We investigated whether an online intervention could increase residents' knowledge and improve knowledge retention in mechanical ventilation when compared with a clinical rotation and whether the timing of intervention had an impact on overall knowledge gains. DESIGN: A prospective, interventional crossover study conducted from October 2015 to December 2017. SETTING: Multicenter study conducted in 33 PICUs across eight countries. SUBJECTS: Pediatric categorical residents rotating through the PICU for the first time. We allocated 483 residents into two arms based on rotation date to use an online intervention either before or after the clinical rotation. INTERVENTIONS: Residents completed an online virtual mechanical ventilation simulator either before or after a 1-month clinical rotation with a 2-month period between interventions. MEASUREMENTS AND MAIN RESULTS: Performance on case-based, multiple-choice question tests before and after each intervention was used to quantify knowledge gains and knowledge retention. Initial knowledge gains in residents who completed the online intervention (average knowledge gain, 6.9%; SD, 18.2) were noninferior compared with those who completed 1 month of a clinical rotation (average knowledge gain, 6.1%; SD, 18.9; difference, 0.8%; 95% CI, -5.05 to 6.47; p = 0.81). Knowledge retention was greater following completion of the online intervention when compared with the clinical rotation when controlling for time (difference, 7.6%; 95% CI, 0.7-14.5; p = 0.03). When the online intervention was sequenced before (average knowledge gain, 14.6%; SD, 15.4) rather than after (average knowledge gain, 7.0%; SD, 19.1) the clinical rotation, residents had superior overall knowledge acquisition (difference, 7.6%; 95% CI, 2.01-12.97;p = 0.008). CONCLUSIONS: Incorporating an interactive online educational intervention prior to a clinical rotation may offer a strategy to prime learners for the upcoming rotation, augmenting clinical learning in graduate medical education.

Computer-Assisted Motivational Interviewing Intervention to Facilitate Teen Pregnancy Prevention and Fitness Behavior Changes: A Randomized Trial for Young Men.

PURPOSE: Despite recent declines, teen unintended pregnancy and sexually transmitted infections in the United States remain at levels higher than comparable nations. Initiatives to prevent teen pregnancy have focused primarily on female adolescents; how to effectively engage young men to reduce their risk of fathering a teen pregnancy has not been well studied. We proposed to adapt an innovative computer-assisted motivational interviewing (CAMI) intervention, originally designed and tested with young women, for use with young men, aged 15-24 years, to reduce their risk of fathering a teen pregnancy. This manuscript describes the design of a CAMI intervention for young men aimed at preventing teen pregnancy and improving fitness. METHODS: This randomized controlled trial will recruit 945 sexually active young men between the ages of 15 and 24 years from three health centers in New York City. Participants will be assigned by permuted block randomization to two study arms: one aimed at reducing involvement in unintended teen pregnancy (CAMI-teen pregnancy prevention) and the other at improving overall fitness (CAMI-Fitness). Except for topic, both intervention arms will provide four sessions of Motivational Interviewing coaching and use a mobile app to track behavior and set goals. We will assess young men's sexual and reproductive health behaviors and fitness at baseline, 12, 24, 36, and 64 weeks using a mobile device app created for the study. RESULTS: Pending ongoing study. CONCLUSIONS: Results from the study are expected to enhance our understanding of the efficacy of CAMI to enhance young men's reproductive health and fitness behaviors.

Impact of an electronic handoff documentation tool on team shared mental models in pediatric critical care.

OBJECTIVE: To examine the impact of the implementation of an electronic handoff tool (the Handoff Tool) on shared mental models (SMM) within patient care teams as measured by content overlap and discrepancies in verbal handoff presentations given by different clinicians caring for the same patient. MATERIALS AND METHODS: Researchers observed, recorded, and transcribed verbal handoffs given by different members of patient care teams in a pediatric intensive care unit. The transcripts were qualitatively coded and analyzed for content overlap scores and the number of discrepancies in handoffs of different team members before and after the implementation of the tool. RESULTS: Content overlap scores did not change post-implementation. The average number of discrepancies nearly doubled following the implementation (from 0.76 discrepancies per handoff group pre-implementation to 1.17 discrepancies per handoff group post-implementation); however, this change was not statistically significant (p=0.37). Discrepancies classified as related to dosage of treatment or procedure and to patients' symptoms increased in frequency post-implementation. DISCUSSION: The results suggest that the Handoff Tool did not have the desired positive impact on SMM within patient care teams. Future electronic tools for facilitating team handoff may need longer implementation times, complementary changes to handoff process and structure, and improved designs that integrate a common core of shared information with discipline-specific records. CONCLUSION: While electronic handoff tools provide great opportunities to improve communication and facilitate the formation of shared mental models within patient care teams, further work is necessary to realize their full potential.

Replicability, Reproducibility, and Agent-based Simulation of Interventions.

Secondary use of medical data and use of observational data for causal inference has been growing. Yet these data bring many challenges such as confounding due to unobserved variables and variation in medical processes across settings. Further, while methods exist to handle some of these problems, researchers lack ground truth to evaluate these methods. When a finding is not replicated across multiple sites, it is unknown whether this is a failure of an algorithm, a genuine difference between populations, or an artifact of structural differences between the sites. We show how agent-based simulation of medical interventions can be used to explore how bias, error, and variation across settings affect inference. Our approach enables users to model not only interventions and outcomes, but also the complex interaction between patients with different risks of mortality and providers with different observed and latent treatment effects. Ultimately we propose that such simulations can be used to better evaluate the behavior of new methods with known ground truth and better calculate sample size for EHR-based studies.

In Search of Social Translucence: An Audit Log Analysis of Handoff Documentation Views and Updates.

Communication and information sharing are critical parts of teamwork in the hospital; however, achieving open and fluid communication can be challenging. Finding specific patient information within documentation can be difficult. Recent studies on handoff documentation tools show that resident handoff notes are increasingly used as an alternative information source by non-physician clinicians. Previous findings also show that residents have become aware of this unintended use. This study investigated the alignment of resident note updating patterns and team note viewing patterns based on usage log data of handoff notes. Qualitative interviews with clinicians were used to triangulate findings based on the log analysis. The study found that notes that were frequently updated were viewed significantly more frequently than notes updated less often (p < 2.2 × 10(-16)). Almost 44% of all notes had aligned frequency of views and updates. The considerable percentage (56%) of mismatched note utilization suggests an opportunity for improvement.

Characterization of a handoff documentation tool through usage log data.

Handoffs are a critical component of coordinated patient care; however, poor handoffs have been associated with near misses and adverse events. To address this, national agencies have recommended standardizing handoffs, for example through the use of handoff documentation tools. Recent research suggests that handoff tools, typically designed for physicians, are often used by non-physician providers as information sources. In this study, we investigated patterns of edits of an electronic handoff tool in a large teaching hospital through examination of its usage log data. Qualitative interviews with clinicians were used to triangulate log data findings. The analysis showed that despite its primary focus on facilitating transitions of care, information in the handoff documentation tool was updated throughout the day. Interviews with residents confirmed that they purposefully updated information to make it available for other members of their patient care teams. This further reiterates the view of electronic handoff tools as facilitators of team communication and coordination. However, the study also showed considerable variability in the frequency of updates between different units and across different patients. Further research is required to understand what factors drive such diversity in the use of electronic handoff tool and whether this diversity can be used to make inferences about patients' conditions.

OpenMDC: an open-source framework for medical device communication.

We have developed an extensible, open source framework for collecting data from bedside medical devices which support RS-232 serial output. The system uses inexpensive hardware to convert RS-232 signals to Universal Serial Bus (USB) format, enabling "plug-and-play" device communication at low cost. A prototype of the system has been created and tested with Puritan-Bennett 840 ventilators.