Cost-effectiveness Analysis of Single-Use Duodenoscope Applied to Endoscopic Retrograde Cholangiopancreatography

OBJECTIVES

Secondary infections due to transmission via the duodenoscope have been reported in up to 3% of endoscopic retrograde cholangiopancreatographies. The use of single-use duodenoscopes has been suggested. We investigate the cost-effectiveness of these duodenoscopes use in cholangiopancreatography.

MATERIALS AND METHODS

A cost-effectiveness analysis was implemented to compare the performance of cholangiopancreatographies with reusable duodenoscopes versus single-use duodenoscopes. Effectiveness was analyzed by calculating quality-adjusted life years (QALY) from the perspective of the National Health System. Possibility of crossover from single-use to reusable duodenoscopes was considered. A willingness-to-pay of €25,000/QALY was set, the incremental cost-effectiveness ratio (ICER) was calculated, and deterministic and probabilistic sensitivity analyses were performed.

RESULTS

Considering cholangiopancreatographies with single-use and reusable duodenoscopes at a cost of €2900 and €1333, respectively, and a 10% rate of single-use duodenoscopes, ICER was greater than €3,000,000/QALY. A lower single-use duodenoscope cost of €1211 resulted in an ICER of €23,583/QALY. When the unit cost of the single-use duodenoscope was €1211, a crossover rate of more than 9.5% made the use of the single-use duodenoscope inefficient.

CONCLUSIONS

Single-use duodenoscopes are cost-effective in a proportion of cholangiopancreatographies if its cost is reduced. Increased crossover rate makes single-use duodenoscope use not cost-effective.

Are Estimates of the Health Opportunity Cost Being Used to Draw Conclusions in Published Cost-Effectiveness Analyses? A Scoping Review in Four Countries

BACKGROUND

When healthcare budgets are exogenous, cost-effectiveness thresholds (CETs) used to inform funding decisions should represent the health opportunity cost (HOC) of such funding decisions, but HOC-based CET estimates have not been available until recently. In recent years, empirical HOC-based CETs for multiple countries have been published, but the use of these CETs in the cost-effectiveness analysis (CEA) literature has not been investigated. Analysis of the use of HOC-based CETs by researchers undertaking CEAs in countries with different decision-making contexts will provide valuable insights to further understand barriers and facilitators to the acceptance and use of HOC-based CETs.

OBJECTIVES

We aimed to identify the CET values used to interpret the results of CEAs published in the scientific literature before and after the publication of jurisdiction-specific empirical HOC-based CETs in four countries.

METHODS

We undertook a scoping review of CEAs published in Spain, Australia, the Netherlands and South Africa between 2016 (2014 in Spain) and 2020. CETs used before and after publication of HOC estimates were recorded. We conducted logit regressions exploring factors explaining the use of HOC values in identified studies and linear models exploring the association of the reported CET value with study characteristics and results.

RESULTS

1171 studies were included in this review (870 CEAs and 301 study protocols). HOC values were cited in 28% of CEAs in Spain and in 11% of studies conducted in Australia, but they were not referred to in CEAs undertaken in the Netherlands and South Africa. Regression analyses on Spanish and Australian studies indicate that more recent studies, studies without a conflict of interest and studies estimating an incremental cost-effectiveness ratio (ICER) below the HOC value were more likely to use the HOC as a threshold reference. In addition, we found a small but significant impact indicating that for every dollar increase in the estimated ICER, the reported CET increased by US$0.015. Based on the findings of our review, we discuss the potential factors that might explain the lack of adoption of HOC-based CETs in the empirical CEA literature.

CONCLUSIONS

The adoption of HOC-based CETs by identified published CEAs has been uneven across the four analysed countries, most likely due to underlying differences in their decision-making processes. Our results also reinforce a previous finding indicating that CETs might be endogenously selected to fit authors' conclusions.

Diagnostic accuracy of adenosine deaminase for pleural tuberculosis in a low prevalence setting: A machine learning approach within a 7-year prospective multi-center study

OBJECTIVE

To analyze the performance of adenosine deaminase in pleural fluid combined with other parameters routinely measured in clinical practice and assisted by machine learning algorithms for the diagnosis of pleural tuberculosis in a low prevalence setting, and secondly, to identify effusions that are non-tuberculous and most likely malignant.

PATIENTS AND METHODS

We prospectively analyzed 230 consecutive patients diagnosed with lymphocytic exudative pleural effusion from March 2013 to June 2020. Diagnosis according to the composite reference standard was achieved in all cases. Pre-test probability of pleural tuberculosis was 3.8% throughout the study period. Parameters included were: levels of adenosine deaminase, pH, glucose, proteins, and lactate dehydrogenase, red and white cell counts and lymphocyte percentage in pleural fluid, as well as age. We tested six different machine learning-based classifiers to categorize the patients. Two different classifications were performed: a) tuberculous/non-tuberculous and b) tuberculous/malignant/other.

RESULTS

Out of a total of 230 patients with pleural effusion included in the study, 124 were diagnosed with malignant effusion and 44 with pleural tuberculosis, while 62 were given other diagnoses. In the tuberculous/non-tuberculous classification, and taking into account the validation predictions, the support vector machine yielded the best result: an AUC of 0.98, accuracy of 97%, sensitivity of 91%, and specificity of 98%, whilst in the tuberculous/malignant/other classification, this type of classifier yielded an overall accuracy of 80%. With this three-class classifier, the same sensitivity and specificity was achieved in the tuberculous/other classification, but it also allowed the correct classification of 90% of malignant cases.

CONCLUSION

The level of adenosine deaminase in pleural fluid together with cell count, other routine biochemical parameters and age, combined with a machine-learning approach, is suitable for the diagnosis of pleural tuberculosis in a low prevalence scenario. Secondly, non-tuberculous effusions that are suspected to be malignant may also be identified with adequate accuracy.

Towards the automated economic assessment of newborn screening for rare diseases

OBJECTIVE

Economic assessments of newborn screening programs for rare diseases involve the use of models and require huge efforts to synthesize information from different sources. Sharing and automatically or semi-automatically reusing this information for new assessments would be desirable, but it is not possible nowadays due to the lack of suitable tools.

MATERIAL AND METHODS

We designed and implemented the Rare Diseases Ontology for Simulation (RaDiOS) after performing two reviews, and critically appraising the existing data repositories on rare diseases. The first review involved previous published economic assessments, and served to identify the main parameters required to model newborn screening. The second review aimed at locating existing data repositories potentially available to inform these parameters.

RESULTS

We found key model parameters on epidemiology, screening methods, diagnose methods, pathogenesis, treatment and follow-up tests. We also identified seven data repositories directly related to rare diseases. None of such repositories was well-suited for the automated generation of simulation models. We incorporated the identified parameters as structured classes and properties of the new ontology (RaDiOS). We carefully set the relationships among the parameters so to allow automated inference from the ontology.

CONCLUSIONS

RaDiOS is an ontology that serves as a data repository to automatically build simulation models for the economic assessment of newborn screening for rare diseases.

Cost-effectiveness analysis of real-time continuous monitoring glucose compared to self-monitoring of blood glucose for diabetes mellitus in Spain

RATIONALE, AIMS AND OBJECTIVES

Self-monitoring of blood glucose (SMBG) is recommended to monitor glycaemic levels. The recent development of real-time continuous glucose monitoring (RT-CGM) enables continuous display of glucose concentration alerting patients in the event of relevant glucose fluctuations, potentially avoiding hypoglycaemic events and reducing long-term complications related to glycosylated haemoglobin (HbA1c) levels. This paper aims to evaluate the cost-effectiveness of RT-CGM compared to SMBG in patients with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) which should support decision-making on public funding of RT-CGM in Spain.

METHODS

We performed a systematic review and meta-analyses on the effectiveness of RT-CGM in the reduction of HbA1c levels and severe hypoglycaemic events. A cost-effectiveness analysis was conducted using a Markov model which simulates the costs and health outcomes of individuals treated under these alternatives for a lifetime horizon from the perspective of the Spanish Health Service. The effectiveness measure was quality-adjusted life years (QALYs). We ran extensive sensitivity analyses, including a probabilistic sensitivity analysis.

RESULTS

Real-time continuous glucose monitoring provides a significant reduction of HbA1c for T1DM (13 studies; weighted mean difference (WMD) = -0.23%, 95% CI: -0.35, -0.11) and T2DM (5 studies; WMD = -0.48%, 95% CI: -0.79, -0.17). There were no statistically significant differences in the rate of severe hypoglycaemic events in T1DM (9 studies; OR = 1.16, 95% CI: 0.78, 1.72) or T2DM (no severe hypoglycaemic events were reported in any study). In the base case analysis, RT-CGM led to higher QALYs and health care costs with an estimated incremental cost-effectiveness ratio of €2 554 723 and €180 553 per QALY for T1DM and T2DM patients respectively. Sensitivity analyses revealed that the study results were robust.

CONCLUSIONS

Real-time continuous glucose monitoring is not a cost-effective technology when compared to SMBG in Spain.

Effectiveness and cost-effectiveness of knowledge transfer and behavior modification interventions in type 2 diabetes mellitus patients--the INDICA study: a cluster randomized controlled trial

BACKGROUND

Type 2 diabetes mellitus is a chronic disease whose health outcomes are related to patients and healthcare professionals' decision-making. The Diabetes Intervention study in the Canary Islands (INDICA study) aims to evaluate the effectiveness and cost-effectiveness of educational interventions supported by new technology decision tools for type 2 diabetes patients and primary care professionals in the Canary Islands.

METHODS/DESIGN

The INDICA study is an open, community-based, multicenter, clinical controlled trial with random allocation by clusters to one of three interventions or to usual care. The setting is primary care where physicians and nurses are invited to participate. Patients with diabetes diagnosis, 18-65 years of age, and regular users of mobile phone were randomly selected. Patients with severe comorbidities were excluded. The clusters are primary healthcare practices with enough professionals and available places to provide the intervention. The calculated sample size was 2,300 patients. Patients in group 1 are receiving an educational group program of eight sessions every 3 months led by trained nurses and monitored by means of logs and a web-based platform and tailored semi-automated SMS for continuous support. Primary care professionals in group 2 are receiving a short educational program to update their diabetes knowledge, which includes a decision support tool embedded into the electronic clinical record and a monthly feedback report of patients' results. Group 3 is receiving a combination of the interventions for patients and professionals. The primary endpoint is the change in HbA1c in 2 years. Secondary endpoints are cardiovascular risk factors, macrovascular and microvascular diabetes complications, quality of life, psychological outcomes, diabetes knowledge, and healthcare utilization. Data is being collected from interviews, questionnaires, clinical examinations, and records. Generalized linear mixed models with repeated time measurements will be used to analyze changes in outcomes. The cost-effectiveness analysis, from the healthcare services perspective, involves direct medical costs per quality-adjusted life year gained and two periods, a 'within-trial' period and a lifetime Markov model. Deterministic and probabilistic sensitivity analyses are planned.

DISCUSSION

This ongoing trial aims to set up the implementation of evidence-based programs in the clinical setting for chronic patients.

TRIAL REGISTRATION

Clinical Trial.gov NCT01657227.