Browsing by Author "Kaufman, Jaime"

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    Exploring data reduction strategies in the analysis of continuous pressure imaging technology
    (2023-03-01) Peng, Mingkai; Southern, Danielle A.; Ocampo, Wrechelle; Kaufman, Jaime; Hogan, David B.; Conly, John; Baylis, Barry W.; Stelfox, Henry T.; Ho, Chester; Ghali, William A.
    Abstract Background Science is becoming increasingly data intensive as digital innovations bring new capacity for continuous data generation and storage. This progress also brings challenges, as many scientific initiatives are challenged by the shear volumes of data produced. Here we present a case study of a data intensive randomized clinical trial assessing the utility of continuous pressure imaging (CPI) for reducing pressure injuries. Objective To explore an approach to reducing the amount of CPI data required for analyses to a manageable size without loss of critical information using a nested subset of pressure data. Methods Data from four enrolled study participants excluded from the analytical phase of the study were used to develop an approach to data reduction. A two-step data strategy was used. First, raw data were sampled at different frequencies (5, 30, 60, 120, and 240 s) to identify optimal measurement frequency. Second, similarity between adjacent frames was evaluated using correlation coefficients to identify position changes of enrolled study participants. Data strategy performance was evaluated through visual inspection using heat maps and time series plots. Results A sampling frequency of every 60 s provided reasonable representation of changes in interface pressure over time. This approach translated to using only 1.7% of the collected data in analyses. In the second step it was found that 160 frames within 24 h represented the pressure states of study participants. In total, only 480 frames from the 72 h of collected data would be needed for analyses without loss of information. Only ~ 0.2% of the raw data collected would be required for assessment of the primary trial outcome. Conclusions Data reduction is an important component of big data analytics. Our two-step strategy markedly reduced the amount of data required for analyses without loss of information. This data reduction strategy, if validated, could be used in other CPI and other settings where large amounts of both temporal and spatial data must be analysed.
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    Implementation strategies for hospital-based probiotic administration in a stepped-wedge cluster randomized trial design for preventing hospital-acquired Clostridioides difficile infection
    (2023-12-11) Bresee, Lauren C.; Lamont, Nicole; Ocampo, Wrechelle; Holroyd-Leduc, Jayna; Sabuda, Deana; Leal, Jenine; Dalton, Bruce; Kaufman, Jaime; Missaghi, Bayan; Kim, Joseph; Larios, Oscar E.; Henderson, Elizabeth; Raman, Maitreyi; Fletcher, Jared R.; Faris, Peter; Kraft, Scott; Shen, Ye; Louie, Thomas; Conly, John M.
    Abstract Background Clostridioides difficile infection (CDI) is associated with considerable morbidity and mortality in hospitalized patients, especially among older adults. Probiotics have been evaluated to prevent hospital-acquired (HA) CDI in patients who are receiving systemic antibiotics, but the implementation of timely probiotic administration remains a challenge. We evaluated methods for effective probiotic implementation across a large health region as part of a study to assess the real-world effectiveness of a probiotic to prevent HA-CDI (Prevent CDI-55 +). Methods We used a stepped-wedge cluster-randomized controlled trial across four acute-care adult hospitals (n = 2,490 beds) to implement the use of the probiotic Bio-K + ® (Lactobacillus acidophilus CL1285®, L. casei LBC80R® and L. rhamnosus CLR2®; Laval, Quebec, Canada) in patients 55 years and older receiving systemic antimicrobials. The multifaceted probiotic implementation strategy included electronic clinical decision support, local site champions, and both health care provider and patient educational interventions. Focus groups were conducted during study implementation to identify ongoing barriers and facilitators to probiotic implementation, guiding needed adaptations of the implementation strategy. Focus groups were thematically analyzed using the Theoretical Domains Framework and the Consolidated Framework of Implementation Research. Results A total of 340 education sessions with over 1,800 key partners and participants occurred before and during implementation in each of the four hospitals. Site champions were identified for each included hospital, and both electronic clinical decision support and printed educational resources were available to health care providers and patients. A total of 15 individuals participated in 2 focus group and 7 interviews. Key barriers identified from the focus groups resulted in adaptation of the electronic clinical decision support and the addition of nursing education related to probiotic administration. As a result of modifying implementation strategies for identified behaviour change barriers, probiotic adherence rates were from 66.7 to 75.8% at 72 h of starting antibiotic therapy across the four participating acute care hospitals. Conclusions Use of a barrier-targeted multifaceted approach, including electronic clinical decision support, education, focus groups to guide the adaptation of the implementation plan, and local site champions, resulted in a high probiotic adherence rate in the Prevent CDI-55 + study.