Weekly OHDSI Digest - 25Apr2016

MauraBeaton · April 25, 2016, 8:19pm

This week’s working group meetings:

Patient Visualization Meeting - Tuesday at 2pm ET

Webex: https://jjconferencing.webex.com/mw0401lsp13/mywebex/default.do?service=1&main_url=%2Fmc0901lsp13%2Fe.do%3Fsiteurl%3Djjconferencing%26AT%3DMI%26EventID%3D386219722%26MTID%3Dmcad14cd8ab3f94c3de90668079be00a5%26Host%3DQUhTSwAAAAJd77Hph5wmiTcw5DyZad3saBWVNVnAd48fjuvGU6KntDs88bph8v3eweBVX8O65Q_aiUEL41pKeZyoTpm8qZ_70%26FrameSet%3D2&siteurl=jjconferencing&nomenu=true
Teleconference: 1-877-5659999 (US)
Access Code: 881 735 36

Population-Level Estimation Meeting - Wednesday at 12pm ET

Webex: https://meetings.webex.com/collabs/meetings/join?uuid=MAAQGCTZMYBUAS6MFSXWO42087-D1JL
Dial in: +1-415-655-0001 US TOLL
Access code: 195 413 955

Community Publications

Quantifying and Mitigating the Effect of Preferential Sampling on Phylodynamic Inference.

ncbi.nlm.nih.gov

Quantifying and Mitigating the Effect of Preferential Sampling on Phylodynamic Inference.

MD Karcher, JA Palacios, T Bedford, MA Suchard and VN Minin, PLoS computational biology, Mar 2016

Phylodynamics seeks to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. One way to accomplish this task formulates an observed sequence data likelihood exploiting a coalescent model for the sampled individuals' genealogy and then integrating over all possible genealogies via Monte Carlo or, less efficiently, by conditioning on one genealogy estimated from the sequence data. However, when analyzing sequences sampled serially through time, current methods implicitly assume either that sampling times are fixed deterministically by the data collection protocol or that their distribution does not depend on the size of the population. Through simulation, we first show that, when sampling times do probabilistically depend on effective population size, estimation methods may be systematically biased. To correct for this deficiency, we propose a new model that explicitly accounts for preferential sampling by modeling the sampling times as an inhomogeneous Poisson process dependent on effective population size. We demonstrate that in the presence of preferential sampling our new model not only reduces bias, but also improves estimation precision. Finally, we compare the performance of the currently used phylodynamic methods with our proposed model through clinically-relevant, seasonal human influenza examples.

Seasonality in acute liver injury? Findings in two health care claims databases.

ncbi.nlm.nih.gov

Seasonality in acute liver injury? Findings in two health care claims databases.

RB Weinstein, MJ Schuemie, PB Ryan and PE Stang, Drug, healthcare and patient safety, 2016

Presumed seasonal use of acetaminophen-containing products for relief of cold/influenza ("flu") symptoms suggests that there might also be a corresponding seasonal pattern for acute liver injury (ALI), a known clinical consequence of acetaminophen overdose.The objective of this study was to determine whether there were any temporal patterns in hospitalizations for ALI that would correspond to assumed acetaminophen use in cold/flu season.In the period 2002-2010, monthly hospitalization rates for ALI using a variety of case definitions were calculated. Data sources included Truven MarketScan(®) Commercial Claims and Encounters (CCAE) and Medicare Supplemental and Coordination of Benefits (MDCR) databases. We performed a statistical test for seasonality of diagnoses using the periodic generalized linear model. To validate that the test can distinguish seasonal from nonseasonal patterns, we included two positive controls (ie, diagnoses of the common cold [acute nasopharyngitis] and influenza), believed to change with seasons, and two negative controls (female breast cancer and diabetes), believed to be insensitive to season.A seasonal pattern was observed in monthly rates for common cold and influenza diagnoses, but this pattern was not observed for monthly rates of ALI, with or without comorbidities (cirrhosis or hepatitis), breast cancer, or diabetes. The statistical test for seasonality was significant for positive controls (P<0.001 for each diagnosis in both databases) and nonsignificant for ALI and negative controls.No seasonal pattern was observed in the diagnosis of ALI. The positive and negative controls showed the expected patterns, strengthening the validity of the statistical and visual tests used for detecting seasonality.

Revealing Structures in Narratives: a Mixed-Methods Approach to Studying Interdisciplinary Handoff in Critical Care.

ncbi.nlm.nih.gov

Revealing structures in narratives: A mixed-methods approach to studying interdisciplinary handoff in critical care.

L Mamykina, S Jiang, SA Collins, B Twohig, J Hirsh, G Hripcsak, R Stanley Hum and DR Kaufman, Journal of biomedical informatics, 2016 08

To examine a novel mixed-methods approach for studying patterns of clinical communication that could inform future informatics solutions, with a specific focus on handoff within interdisciplinary teams.Researchers observed, recorded, and transcribed verbal handoff discussions of different members of critical care teams. The transcripts were coded qualitatively, and then analyzed quantitatively for emerging structural patterns using categorical cluster analysis, and for degree of shared mental models (SMM) using the modified Pyramid method.An empirical study using the proposed mixed-methods approach suggested emerging patterns of communication among clinicians. For example, the temporal focus of handoff was often determined by the role of the clinician giving the handoff; the clinical content of handoff was consistent between clinicians, but varied between patients. The SMM index ranged from 0.065 (with the maximum possible overlap score of 1) to 0.007 with a median of 0.026; the overlap was higher in statements concerned with patient presentation (23.6% of these had overlap) and referring to the past (24% overlapped). This calculated SMM index was correlated with the assessment of coherence within the participating teams by independent physicians (r=0.63, p=0.038).The proposed novel mixed-methods approach helped to reveal emerging patterns in content and structure of handoff communication and highlight differences due to the clinical context, and to the different priorities of clinicians on interdisciplinary patient care teams. The approach for calculating SMM is more ecologically sensitive as it relies on naturally occurring discourse and less intrusive than traditional ways of assessing SMM, and takes initial steps toward establishing empirical foundation for the design of electronic tools to support handoff in interdisciplinary teams.

Leveraging Dialog Systems Research to Assist Biomedical Researchers’ Interrogation of Big Clinical Data

ncbi.nlm.nih.gov

Leveraging dialog systems research to assist biomedical researchers' interrogation of Big Clinical Data.

J Hoxha and C Weng, Journal of biomedical informatics, 2016 06

The worldwide adoption of electronic health records (EHR) promises to accelerate clinical research, which lies at the heart of medical advances. However, the interrogation of such Big Data by clinical researchers can be laborious and error-prone, involving iterative and ineffective communication of data requests to data analysts. Research on this communication process is rare. There also exists no contemporary system that offers intelligent solutions to assist clinical researchers in their quest for clinical data. In this article, we first provide a detailed characterization of the challenges encountered in this communication space. Second, we identify promising synergies between fields studying human-to-human and human-machine communication that can shed light on biomedical data query mediation. We propose a mixed-initiative dialog-based approach to support autonomous clinical data access and recommend needed technology development and communication study for accelerating clinical research.