Cost-effectiveness of noninvasive fetal RhD blood group genotyping in nonalloimmunized and alloimmunized pregnancies.

BACKGROUND: We sought to determine the cost-effectiveness of noninvasive fetal RhD blood group genotyping in nonalloimmunized and alloimmunized pregnancies in Canada. STUDY DESIGN AND METHODS: We developed two probabilistic state-transition (Markov) microsimulation models to compare fetal genotyping followed by targeted management versus usual care (i.e., universal Rh immunoglobulin [RhIG] prophylaxis in nonalloimmunized RhD-negative pregnancies, or universal intensive monitoring in alloimmunized pregnancies). The reference case considered a healthcare payer perspective and a 10-year time horizon. Sensitivity analysis examined assumptions related to test cost, paternal screening, subsequent pregnancies, other alloantibodies (e.g., K, Rh c/C/E), societal perspective, and lifetime horizon. RESULTS: Fetal genotyping in nonalloimmunized pregnancies (at per-sample test cost of C$247/US$311) was associated with a slightly higher probability of maternal alloimmunization (22 vs. 21 per 10,000) and a reduced number of RhIG injections (1.427 vs. 1.795) than usual care. It was more expensive (C$154/US$194, 95% Credible Interval [CrI]: C$139/US$175-C$169/US$213) and had little impact on QALYs (0.0007, 95%CrI: -0.01-0.01). These results were sensitive to the test cost (threshold achieved at C$88/US$111), and inclusion of paternal screening. Fetal genotyping in alloimmunized pregnancies (at test cost of C$328/US$413) was less expensive (-C$6280/US$7903, 95% CrI: -C$6325/US$7959 to -C$6229/US$7838) and more effective (0.19 QALYs, 95% CrI 0.17-0.20) than usual care. These cost savings remained robust in sensitivity analyses. DISCUSSION: Noninvasive fetal RhD genotyping saves resources and represents good value for the management of alloimmunized pregnancies. If the cost of genotyping is substantially decreased, the targeted intervention can become a viable option for nonalloimmunized pregnancies.

Noninvasive Fetal RhD Blood Group Genotyping: A Systematic Review of Economic Evaluations.

OBJECTIVE: Noninvasive fetal rhesus D (RhD) blood group genotyping may prevent unnecessary use of anti-D immunoglobulin (RhIG) in non-alloimmunized RhD-negative pregnancies and can guide management of alloimmunized pregnancies. We conducted a systematic review of the economic literature to determine the cost-effectiveness of this intervention over usual care. DATA SOURCES: Systematic literature searches of bibliographic databases (Ovid MEDLINE, Embase, and Cochrane) until February 26, 2019, and auto-alerts until October 30, 2020, and of grey literature sources were performed to retrieve all English-language studies. STUDY SELECTION: We included studies done in serologically confirmed non-alloimmunized or alloimmunized RhD-negative pregnancies, comparing costs and effectiveness of the intervention versus usual care. DATA EXTRACTION AND SYNTHESIS: Two reviewers extracted data from the eligible studies and assessed their methodological quality (risk of bias) using the Quality of Health Economic Studies (QHES) and Drummond tools. We narratively synthesized findings. Our review included 8 economic studies that evaluated non-invasive fetal RhD genotyping followed by targeted RhIG prophylaxis in non-alloimmunized pregnancies. Five studies further considered a subsequent alloimmunized pregnancy. The cost-effectiveness of the intervention versus usual care (e.g., universal RhIG or prophylaxis conditional on results of paternal testing) for non-alloiummunized pregnancies was inconsistent. Two studies indicated greater benefits and lower costs for the intervention, and another 2 suggested a trade-off. In 4 studies, the intervention was less effective and costlier than alternatives. Three studies were determined to be of high quality by both tools. Two of these studies favoured the intervention, and one assessed benefits in quality-adjusted life-years. No study clearly examined the cost-effectiveness of repetitive use of fetal genotyping in multiple non-alloimmunized or alloimmunized pregnancies. The cost of genotyping was the most influential parameter. CONCLUSION: The cost-effectiveness of noninvasive fetal RhD genotyping for non-alloimmunized pregnancies varies between studies. Potential savings from targeted management of alloimmunized pregnancies requires further research.

Cost-Effectiveness of Magnetic Resonance-Guided Focused Ultrasound for Essential Tremor.

BACKGROUND: Radiofrequency thalamotomy and deep brain stimulation are current treatments for moderate to severe medication-refractory essential tremor. However, they are invasive and thus carry risks. Magnetic resonance-guided focused ultrasound is a new, less invasive surgical option. The objective of the present study was to determine the cost-effectiveness of magnetic resonance-guided focused ultrasound compared with standard treatments in Canada. METHODS: We conducted a cost-utility analysis using a Markov cohort model. We compared magnetic resonance-guided focused ultrasound with no surgery in people ineligible for invasive neurosurgery and with radiofrequency thalamotomy and deep brain stimulation in people eligible for invasive neurosurgery. In the reference case analysis, we used a 5-year time horizon and a public payer perspective and discounted costs and benefits at 1.5% per year. RESULTS: Compared with no surgery in people ineligible for invasive neurosurgery, magnetic resonance-guided focused ultrasound cost $21,438 more but yielded 0.47 additional quality-adjusted life years, producing an incremental cost-effectiveness ratio of $45,817 per quality-adjusted life year gained. In people eligible for invasive neurosurgery, magnetic resonance-guided focused ultrasound was slightly less effective but much less expensive compared with the current standard of care, deep brain stimulation. The results were sensitive to assumptions regarding the time horizon, cost of magnetic resonance-guided focused ultrasound, and probability of recurrence. CONCLUSIONS: In people ineligible for invasive neurosurgery, the incremental cost-effectiveness ratio of magnetic resonance-guided focused ultrasound versus no surgery is comparable to many other tests and treatments that are widely adopted in high-income countries. In people eligible for invasive neurosurgery, magnetic resonance-guided focused ultrasound is also a reasonable option. © 2018 International Parkinson and Movement Disorder Society.

Mechanical Thrombectomy in Acute Ischemic Stroke: A Systematic Review.

Although intravenous thrombolysis increases the probability of a good functional outcome in carefully selected patients with acute ischemic stroke, a substantial proportion of patients who receive thrombolysis do not have a good outcome. Several recent trials of mechanical thrombectomy appear to indicate that this treatment may be superior to thrombolysis. We therefore conducted a systematic review and meta-analysis to evaluate the clinical effectiveness and safety of new-generation mechanical thrombectomy devices with intravenous thrombolysis (if eligible) compared with intravenous thrombolysis (if eligible) in patients with acute ischemic stroke caused by a proximal intracranial occlusion. We systematically searched seven databases for randomized controlled trials published between January 2005 and March 2015 comparing stent retrievers or thromboaspiration devices with best medical therapy (with or without intravenous thrombolysis) in adults with acute ischemic stroke. We assessed risk of bias and overall quality of the included trials. We combined the data using a fixed or random effects meta-analysis, where appropriate. We identified 1579 studies; of these, we evaluated 122 full-text papers and included five randomized control trials (n=1287). Compared with patients treated medically, patients who received mechanical thrombectomy were more likely to be functionally independent as measured by a modified Rankin score of 0-2 (odds ratio, 2.39; 95% confidence interval, 1.88-3.04; I2=0%). This finding was robust to subgroup analysis. Mortality and symptomatic intracerebral hemorrhage were not significantly different between the two groups. Mechanical thrombectomy significantly improves functional independence in appropriately selected patients with acute ischemic stroke.

Simplified Methods for Modelling Dependent Parameters in Health Economic Evaluations: A Tutorial.

BACKGROUND: In health economic evaluations, model parameters are often dependent on other model parameters. Although methods exist to simulate multivariate normal (MVN) distribution data and estimate transition probabilities in Markov models while considering competing risks, they are technically challenging for health economic modellers to implement. This tutorial introduces easily implementable applications for handling dependent parameters in modelling. METHODS: Analytical proofs and proposed simplified methods for handling dependent parameters in typical health economic modelling scenarios are provided, and implementation of these methods are illustrated in seven examples along with the SAS and R code. RESULTS: Methods to quantify the covariance and correlation coefficients of correlated variables based on published summary statistics and generation of MVN distribution data are demonstrated using examples of physician visits data and cost component data. The use of univariate normal distribution data instead of MVN distribution data to capture population heterogeneity is illustrated based on the results from multiple regression models with linear predictors, and two examples are provided (linear fixed-effects model and Cox proportional hazards model). A conditional probability method is introduced to handle two or more state transitions in a single Markov model cycle and applied in examples of one- and two-way state transitions. CONCLUSIONS: This tutorial proposes an extension of routinely used methods along with several examples. These simplified methods may be easily applied by health economic modellers with varied statistical backgrounds.

The care delivery experience of hospitalized patients with complex chronic disease.

OBJECTIVE: This study investigated what is important in care delivery from the perspective of hospital inpatients with complex chronic disease, a currently understudied population. PARTICIPANTS AND SETTING: One-on-one semi-structured interviews were conducted with inpatients at a continuing care/rehabilitation hospital (n = 116) in Canada between February and July 2011. DESIGN: The study design was mixed methods and reports on patient characteristics and care delivery experiences. Basic descriptive statistics were run using SPSS version 17, and thematic analysis on the transcripts was conducted using NVivo9 software. RESULTS: Patients had an average of 5 morbidities and several illness symptoms including activity of daily living impairments, physical pain and emotional disturbance. Three broad themes (each with one or more subthemes) were generated from the data representing important components of care delivery: components of the care plan (a comprehensive assessment, supported transitions and a bio-psycho-social care package); care capacity and quality (optimal staff to patient ratios, quicker response times, better patient-provider communication and consistency between providers) and the patient-provider relationships (characterized by respect and dignity). CONCLUSIONS: As health systems throughout the industrialized world move to sustain health budgets while optimizing quality of care, it is critical to better understand this population, so that appropriate metrics, services and policies can be developed. The study has generated a body of evidence on the important components of care delivery from the perspectives of a diverse group of chronically ill individuals who have spent a considerable amount of time in the health-care system. Moving forward, exploration around the appropriate funding models and skill mix is needed to move the evidence into changed practice.

Understanding bias in probabilistic analysis in model-based health economic evaluation.

Guidelines of economic evaluations suggest that probabilistic analysis (using probability distributions as inputs) provides less biased estimates than deterministic analysis (using point estimates) owing to the non-linear relationship of model inputs and model outputs. However, other factors can also impact the magnitude of bias for model results. We evaluate bias in probabilistic analysis and deterministic analysis through three simulation studies. The simulation studies illustrate that in some cases, compared with deterministic analyses, probabilistic analyses may be associated with greater biases in model inputs (risk ratios and mean cost estimates using the smearing estimator), as well as model outputs (life-years in a Markov model). Point estimates often represent the most likely value of the parameter in the population, given the observed data. When model parameters have wide, asymmetric confidence intervals, model inputs with larger likelihoods (e.g., point estimates) may result in less bias in model outputs (e.g., costs and life-years) than inputs with lower likelihoods (e.g., probability distributions). Further, when the variance of a parameter is large, simulations from probabilistic analyses may yield extreme values that tend to bias the results of some non-linear models. Deterministic analysis can avoid extreme values that probabilistic analysis may encounter. We conclude that there is no definitive answer on which analytical approach (probabilistic or deterministic) is associated with a less-biased estimate in non-linear models. Health economists should consider the bias of probabilistic analysis and select the most suitable approach for their analyses.

Evaluating the correlations of cost and utility parameters from summary statistics for probabilistic analysis in economic evaluations.

OBJECTIVES: The correlations between economic modeling input parameters directly impact the variance and may impact the expected values of model outputs. However, correlation coefficients are not often reported in the literature. We aim to understand the correlations between model inputs for probabilistic analysis from summary statistics. METHODS: We provide proof that for correlated random variables X and Y (e.g. inpatient visits and outpatient visits), the Pearson correlation coefficients of sample means and samples are equal to each other (corrX,Y=corrX-,Y-). Therefore, when studies report summary statistics of correlated parameters, we can quantify the correlation coefficient between parameters. RESULTS: We use examples to illustrate how to estimate the correlation coefficient between the incidence rates of non-severe and severe hypoglycemia events, and the common coefficient of five cost components for patients with diabetic foot ulcers. We further introduce three types of correlations for utilities and provide two examples to estimate the correlations for utilities based on published data. We also evaluate how correlations between cost parameters and utility parameters impact the cost-effectiveness results using a Markov model for major depression. CONCLUSION: Incorporation of the correlations can improve the precision of cost-effectiveness results and increase confidence in evidence-based decision-making. Further empirical evidence is warranted.

A scoping review and thematic classification of patient complexity: offering a unifying framework.

The path to improving healthcare quality for individuals with complex health conditions is complicated by a lack of common understanding of complexity. Modern medicine, together with social and environmental factors, has extended life, leading to a growing population of patients with chronic conditions. In many cases, there are social and psychological factors that impact treatment, health outcomes, and quality of life. This is the face of complexity. Care challenges, burden, and cost have positioned complexity as an important health issue. Complex chronic conditions are now being discussed by clinicians, researchers, and policy-makers around such issues as quantification, payment schemes, transitions, management models, clinical practice, and improved patient experience. We conducted a scoping review of the literature for definitions and descriptions of complexity. We provide an overview of complex chronic conditions, and what is known about complexity, and describe variations in how it is understood. We developed a Complexity Framework from these findings to guide our approach to understanding patient complexity. It is critical to use common vernacular and conceptualization of complexity to improve service and outcomes for patients with complex chronic conditions. Many questions still persist about how to develop this work with a health and social care lens; our framework offers a foundation to structure thinking about complex patients. Further insight into patient complexity can inform treatment models and goals of care, and identify required services and barriers to the management of complexity. Journal of Comorbidity 2012;2:1-9.