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Registry-based trials have emerged as a potentially cost-saving study methodology. Early estimates of cost savings, however, conflated the benefits associated with registry utilisation and those associated with other aspects of pragmatic trial designs, which might not all be as broadly applicable. In this study, we sought to build a practical tool that investigators could use across disciplines to estimate the ranges of potential cost differences associated with implementing registry-based trials versus standard clinical trials.
We built simulation Markov models to compare unique costs associated with data acquisition, cleaning, and linkage under a registry-based trial design versus a standard clinical trial. We conducted one-way, two-way, and probabilistic sensitivity analyses, varying study characteristics over broad ranges, to determine thresholds at which investigators might optimally select each trial design.
Registry-based trials were more cost effective than standard clinical trials 98.6% of the time. Data-related cost savings ranged from $4300 to $600,000 with variation in study characteristics. Cost differences were most reactive to the number of patients in a study, the number of data elements per patient available in a registry, and the speed with which research coordinators could manually abstract data. Registry incorporation resulted in cost savings when as few as 3768 independent data elements were available and when manual data abstraction took as little as 3.4 seconds per data field.
Registries offer important resources for investigators. When available, their broad incorporation may help the scientific community reduce the costs of clinical investigation. We offer here a practical tool for investigators to assess potential costs savings.
The goal of pharmacological treatment is a desired response, known as the target effect (e.g. bispectral index of 50). An understanding of the concentration–response relationship (i.e. pharmacodynamics (PD)) can be used to predict the target concentration (e.g. propofol 4 mg/L) required to achieve this target effect in a typical individual . Pharmacokinetic (PK) knowledge (e.g. clearance, volume) then determines the dose that will achieve the target concentration. Each individual, however, is somewhat different and there is variability associated with all parameters used in PK and PD equations (known as models). Covariate information (e.g. weight, age, pathology, drug interactions, pharmacogenomics) can be used to help predict the dose in a specific patient. The Holy Grail of clinical pharmacology is prediction of drug PK and PD in the individual patient (Fig. 4.1) and this requires knowledge of the covariates that contribute to variability .
Indications for TIVA in children are essentially the same as adults with the additional benefit of reducing emergence delirium and possibly cognitive dysfunction.[1,2] Fears that children may develop propofol infusion syndrome during routine anaesthesia have not eventuated.
Obesity is a chronic disease characterised by the presence of excessive body fat that increases the risk of health problems. Traditionally, the administration of TIVA and TCI in the obese has been done using dose schemes extrapolated from non-obese patients. The use of such schemes has proven inadequate in the obese and they are commonly associated with overdose.[1,2] Dosing strategies of IV anaesthetics in heavy weight patients requires approaches that differ from those used in lean patients due to physiological and pharmacological changes associated with obesity. This chapter is intended to be a practical guide for anaesthetists who wish to undertake TIVA and TCI in obese patients.
Recent years have seen an exponential increase in the variety of healthcare data captured across numerous sources. However, mechanisms to leverage these data sources to support scientific investigation have remained limited. In 2013 the Pediatric Heart Network (PHN), funded by the National Heart, Lung, and Blood Institute, developed the Integrated CARdiac Data and Outcomes (iCARD) Collaborative with the goals of leveraging available data sources to aid in efficiently planning and conducting PHN studies; supporting integration of PHN data with other sources to foster novel research otherwise not possible; and mentoring young investigators in these areas. This review describes lessons learned through the development of iCARD, initial efforts and scientific output, challenges, and future directions. This information can aid in the use and optimisation of data integration methodologies across other research networks and organisations.
Objective: Concussion in children and adolescents is a prevalent problem with implications for subsequent physical, cognitive, behavioral, and psychological functioning, as well as quality of life. While these consequences warrant attention, most concussed children recover well. This study aimed to determine what pre-injury, demographic, and injury-related factors are associated with optimal outcome (“wellness”) after pediatric concussion. Method: A total of 311 children 6–18 years of age with concussion participated in a longitudinal, prospective cohort study. Pre-morbid conditions and acute injury variables, including post-concussive symptoms (PCS) and cognitive screening (Standardized Assessment of Concussion, SAC), were collected in the emergency department, and a neuropsychological assessment was performed at 4 and 12 weeks post-injury. Wellness, defined by the absence of PCS and cognitive inefficiency and the presence of good quality of life, was the main outcome. Stepwise logistic regression was performed using 19 predictor variables. Results: 41.5% and 52.2% of participants were classified as being well at 4 and 12 weeks post-injury, respectively. The final model indicated that children who were younger, who sustained sports/recreational injuries (vs. other types), who did not have a history of developmental problems, and who had better acute working memory (SAC concentration score) were significantly more likely to be well. Conclusions: Determining the variables associated with wellness after pediatric concussion has the potential to clarify which children are likely to show optimal recovery. Future work focusing on wellness and concussion should include appropriate control groups and document more extensively pre-injury and injury-related factors that could additionally contribute to wellness. (JINS, 2019, 25, 375–389)
We evaluated whether a diagnostic stewardship initiative consisting of ASP preauthorization paired with education could reduce false-positive hospital-onset (HO) Clostridioides difficile infection (CDI).
Single center, quasi-experimental study.
Tertiary academic medical center in Chicago, Illinois.
Adult inpatients were included in the intervention if they were admitted between October 1, 2016, and April 30, 2018, and were eligible for C. difficile preauthorization review. Patients admitted to the stem cell transplant (SCT) unit were not included in the intervention and were therefore considered a contemporaneous noninterventional control group.
The intervention consisted of requiring prescriber attestation that diarrhea has met CDI clinical criteria, ASP preauthorization, and verbal clinician feedback. Data were compared 33 months before and 19 months after implementation. Facility-wide HO-CDI incidence rates (IR) per 10,000 patient days (PD) and standardized infection ratios (SIR) were extracted from hospital infection prevention reports.
During the entire 52 month period, the mean facility-wide HO-CDI-IR was 7.8 per 10,000 PD and the SIR was 0.9 overall. The mean ± SD HO-CDI-IR (8.5 ± 2.0 vs 6.5 ± 2.3; P < .001) and SIR (0.97 ± 0.23 vs 0.78 ± 0.26; P = .015) decreased from baseline during the intervention. Segmented regression models identified significant decreases in HO-CDI-IR (Pstep = .06; Ptrend = .008) and SIR (Pstep = .1; Ptrend = .017) trends concurrent with decreases in oral vancomycin (Pstep < .001; Ptrend < .001). HO-CDI-IR within a noninterventional control unit did not change (Pstep = .125; Ptrend = .115).
A multidisciplinary, multifaceted intervention leveraging clinician education and feedback reduced the HO-CDI-IR and the SIR in select populations. Institutions may consider interventions like ours to reduce false-positive C. difficile NAAT tests.
As referrals to specialist palliative care (PC) grow in volume and diversity, an evidence-based triage method is needed to enable services to manage waiting lists in a transparent, efficient, and equitable manner. Discrete choice experiments (DCEs) have not to date been used among PC clinicians, but may serve as a rigorous and efficient method to explore and inform the complex decision-making involved in PC triage. This article presents the protocol for a novel application of an international DCE as part of a mixed-method research program, ultimately aiming to develop a clinical decision-making tool for PC triage.
Five stages of protocol development were undertaken: (1) identification of attributes of interest; (2) creation and (3) execution of a pilot DCE; and (4) refinement and (5) planned execution of the final DCE.
Six attributes of interest to PC triage were identified and included in a DCE that was piloted with 10 palliative care practitioners. The pilot was found to be feasible, with an acceptable cognitive burden, but refinements were made, including the creation of an additional attribute to allow independent analysis of concepts involved. Strategies for recruitment, data collection, analysis, and modeling were confirmed for the final planned DCE.
Significance of results
This DCE protocol serves as an example of how the sophisticated DCE methodology can be applied to health services research in PC. Discussion of key elements that improved the utility, integrity, and feasibility of the DCE provide valuable insights.