Care Transitions: A Mixed Methods Study Using a Complexity Science Lens

Research studies on care transitions from hospital to nursing home are few and heterogeneous, offering an inadequate characterization to support practice. The purpose of this study was to characterize multiple care transitions among hospitalized older adults with advanced chronic disease who were discharged to a nursing home. This prospective, mixed methods study used multiple case studies with an embedded quantitative strand and multiple sources of information. Four cases included an index patient (an older hospitalized adult with advanced chronic illness), his or her informal caregiver, if available, and healthcare providers involved in the index patient’s care. Two hospitals and two nursing homes participated. Healthcare providers, expert in care transitions within those facilities, were interviewed for facility context. Care transitions occurred in two contexts: the facilities’ organizational context and the patients’ ongoing life transitions. While care transitions were time-bounded healthcare provider-centered processes, life transitions were ongoing and principal-centered. Defined care transition processes were complicated. However, dynamic interactions between patients, family caregivers, and healthcare providers occurred in multiple complex systems. Dynamic interactions within the complex systems were affected by the alignment of the familial approach to patient support with the patient’s needs and the availability of a stable core. Symptom distress and quality of life trajectories did not illuminate differences in principal experiences. However, patterns of dynamic interactions were different between patients experiencing unplanned utilization and those who did not. Fragmented processes and lack of feedback loops were the norm. This fragmentation limited information flow. Simple outcome measures did not reflect the complexity of care transitions. While quality of life measures and symptom distress did reflect the patients’ situation at a moment in time, they did little to explain the patient’s experience of care transitions. Implications for practice relate to the complexity within care transitions. Limited information flow due to role fragmentation and lack of feedback loops hamper learning and adaptation both within individual cases and across facilities. Care transitions from hospital to skilled nursing facility occurred within complex systems. As such, future research must consider not only the processes, but also the relationships and dynamic interactions within the systems

Evaluation of Biomedical Informatics Component of NIGMS Funded IDeA-CTR programs

We believe the NIGMS IDeA-CTR programs would benefit from adopting many of the CTSA innovations. We sought to determine current informatics practices of IDeA-CTR programs through a qualitative study of BMI activity and organization. We recommend possible convergence of NIGMS IDeA-CTR BMI activity towards NCATS CTSA BMI functionality.https://digitalcommons.unmc.edu/com_emerg_pres/1002/thumbnail.jp

Beyond Safe Harbor: Risk of Exposing Location in De-Identified Clinical Data

The use of de-identified EHR data for clinical and translational research has increased significantly since the HIPAA Privacy Rule De-Identification standards went into effect -Inclusion of SDOH measures in de-identified research is increasing as well, which presents an inherent risk of re-identifying PHI (primarily location units smaller than the state) -Data warehouse architecture and institutional policies need to recognize the risk associated with providing multiple location-based indices -Research interests are secondary to privacy concerns throughout biomedical research, but particularly in de-identified research, which is intended to promote more secure access to EHR data while allowing for expedient access (fewer institutional barriers to entry)https://digitalcommons.unmc.edu/com_neuro_pres/1000/thumbnail.jp

Concentrations of perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) and their associations with human semen quality measurements

A total of 256 men were studied to evaluate whether serum concentrations of perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS) impacted semen quality or reproductive hormones. Blood and semen were collected and analyzed for perfluorochemicals and reproductive and thyroid hormones. Semen quality was assessed using standard clinical methods. Linear and logistic modeling was performed with semen profile measurements as outcomes and PFOS and PFOA in semen and plasma as explanatory variables. Adjusting for age, abstinence, and tobacco use, there was no indication that PFOA or PFOS was significantly associated with volume, sperm concentration, percent motility, swim-up motility and concentration, and directional motility (a function of motility and modal progression.) Follicle stimulating hormone was not associated with either PFOA or PFOS. Luteinizing hormone was positively correlated with plasma PFOA and PFOS, but not semen PFOS. Important methodological concerns included the lack of multiple hormonal measurements necessary to address circadian rhythms

Risk stratification for arrhythmic death in an emergency department cohort: a new method of nonlinear PD2i analysis of the ECG

Heart rate variability (HRV) reflects both cardiac autonomic function and risk of sudden arrhythmic death (AD). Indices of HRV based on linear stochastic models are independent risk factors for AD in postmyocardial infarction (MI) cohorts. Indices based on nonlinear deterministic models have a higher sensitivity and specificity for predicting AD in retrospective data. A new nonlinear deterministic model, the automated Point Correlation Dimension (PD2i), was prospectively evaluated for prediction of AD. Patients were enrolled (N = 918) in 6 emergency departments (EDs) upon presentation with chest pain and being determined to be at risk of acute MI (AMI) >7%. Brief digital ECGs (>1000 heartbeats, ∼15 min) were recorded and automated PD2i results obtained. Out-of-hospital AD was determined by modified Hinkle-Thaler criteria. All-cause mortality at 1 year was 6.2%, with 3.5% being ADs. Of the AD fatalities, 34% were without previous history of MI or diagnosis of AMI. The PD2i prediction of AD had sensitivity = 96%, specificity = 85%, negative predictive value = 99%, and relative risk >24.2 (p ≤ 0.001). HRV analysis by the time-dependent nonlinear PD2i algorithm can accurately predict risk of AD in an ED cohort and may have both life-saving and resource-saving implications for individual risk assessment

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

2017 Research & Innovation Day Program

A one day showcase of applied research, social innovation, scholarship projects and activities.https://first.fanshawec.ca/cri_cripublications/1004/thumbnail.jp

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease