The Evidence Speaks Series is a recurring feature highlighting the latest in CHÉOS research. This series features summaries of select publications as well as in-depth features on the latest work from our investigators.
In the early days of CHÉOS, the Centre had a series known as “The Evidence Speaks,” a monograph series to keep media and the research community up-to-date with CHÉOS’ current research results in the health outcomes field.
Bagshaw SM, Wang X, Zygun DA, Zuege D, Dodek P, Garland A, Scales DC, Berthiaume L, Faris P, Chen G, Opgenorth D, Stelfox HT. Association between strained capacity and mortality among patients admitted to intensive care: A path-analysis modeling strategy. J Crit Care. 2018 Feb;43:81-7.
Together with researchers from Alberta, Manitoba, and Ontario, CHÉOS’ Dr. Peter Dodek recently co-authored a study evaluating the connection between patient outcomes and strained intensive care unit (ICU) capacity. Previous research has shown that strain in ICUs (inadequate availability of resources) may be associated with suboptimal care, greater chance of adverse outcomes, mortality, premature discharge, and worsened clinician well-being. In the current study, the direct and indirect effects of strained capacity on patient outcomes, in particular risk of death, were investigated in the health care system of Alberta. Information was collected from a total of nine ICUs in Calgary and Edmonton (12,265 admissions); strain was defined using bed availability and occupancy. At the time of patient admission, there were ≤1 bed, ≤2 beds, and ≤3 beds available in 22.3%, 43.9%, and 63.8% of cases, respectively. Comparably, a bed occupancy of ≥90% was reported in 34.8% of cases and an occupancy of ≥95% occurred in 17.0% of cases — about one in five admissions were during a time of strained capacity. Bed availability of ≤1 was associated with greater illness acuity at time of admission. By integrating both direct and indirect effects, the researchers found that strained capacity was associated with greater illness severity and ICU mortality. Strained capacity was also associated with a reduced length of stay in the ICU. Combining these findings with previous studies, the authors noted that increased strain may result in greater rates of withdrawing life support — resulting in shorter average ICU stay — or in earlier discharge of patients with less acute illnesses. This study demonstrates the consequences of strained ICU capacity and provides valuable insight that may inform the design and implementation of interventions to reduce strain in the ICU.
Dragojlovic N, Elliott AM, Adam S, van Karnebeek C, Lehman A, Mwenifumbo JC, Nelson TN, Souich du C, Friedman JM, Lynd LD. The cost and diagnostic yield of exome sequencing for children with suspected genetic disorders: a benchmarking study. Genet Med. 2018 Jan 4 epub ahead of print.
Exome sequencing (ES), a type of genetic testing that analyzes only those genes that encode proteins, can be a valuable diagnostic tool to identify the root cause of disease in people who may have a genetic disorder. The cost-effectiveness of this type of testing can vary greatly, depending upon the delivery model and at what point the testing is used (i.e. as a last resort or a first-line test). The primary measures used to estimate cost-effectiveness for this type of service are cost, diagnostic yield (the likelihood of a test providing enough information for diagnosis), and cost per positive diagnosis (CPPD), the quotient of the per-patient cost and yield. Dr. Larry Lynd, a CHÉOS Scientist, along with Dr. Nick Dragojlovic of the Collaboration for Outcomes Research and Evaluation (CORE) at UBC, conducted a literature review to estimate the cost-effectiveness of ES. They also used data from the Clinical Assessment of the Utility of Sequencing and Evaluation as a Service (CAUSES) Study at B.C. Children’s and Women’s Hospitals to estimate the effect of changing the service design for ES. The literature review revealed that the cost of ES varied greatly, due partially to a decline in cost over time and variations in costing models (e.g. inclusion of genetic counselling or team-based test interpretation). Diagnostic yield varied depending on reporting criteria and on patient selection criteria. Using the CAUSES Study data, the study team demonstrated the effects of changes to cost and yield on CPPD. This study provides contemporary benchmark estimates of these performance indicators for diagnostic ES that can be used to assess the broader applicability and future cost-effectiveness of this type of testing.
Hall AL, Davies HW, Koehoorn M. Personal light-at-night exposures and components of variability in two common shift work industries: uses and implications for future research. Scand J Work Environ Health. 2018 Jan 1;44(1):80-7.
Shift work that interrupts the natural circadian rhythm may have acute and chronic health effects. Animal studies have shown the negative physiological consequences of light exposure during biological night, however few studies have specifically investigated the effect of light-at-night (LAN) exposure in humans. In order to inform future epidemiological studies, CHÉOS’ Dr. Mieke Koehoorn, with other researchers from the UBC School of Population and Public Health, designed a study to determine levels of and variations in LAN exposure of shift workers. The study recruited emergency health service workers and hospital workers who were working at least one night shift. Each participant was fitted with a light monitoring device at the beginning of each shift; the device measures light intensity, collecting a sample each minute in units of photopic illuminance (lux). Data were collected from 23:00-05:00 over 45 nights in 104 participants for a total of 155 full-shift LAN recordings. In general, health care workers had the highest average exposure; lab workers and care aides had the highest while respiratory therapists and unit clerks had the lowest exposure levels. There was very little variance between repeated measurements in the same worker or within occupation groups. The observed variance was mostly explained by differences between different occupation groups. The information gathered in this study shows that simple, high-level groupings (i.e. occupation) can be utilized to assess LAN exposure in epidemiological studies of shift work.