Cost-Effectiveness Analysis of a Transparent Antimicrobial Dressing for Managing Central Venous and Arterial Catheters in Intensive Care Units

<div><p>Objective</p><p>To model the cost-effectiveness impact of routine use of an antimicrobial chlorhexidine gluconate-containing securement dressing compared to non-antimicrobial transparent dressings for the protection of central vascular lines in intensive care unit patients.</p><p>Design</p><p>This study uses a novel health economic model to estimate the cost-effectiveness of using the chlorhexidine gluconate dressing versus transparent dressings in a French intensive care unit scenario. The 30-day time non-homogeneous markovian model comprises eight health states. The probabilities of events derive from a multicentre (12 French intensive care units) randomized controlled trial. 1,000 Monte Carlo simulations of 1,000 patients per dressing strategy are used for probabilistic sensitivity analysis and 95% confidence intervals calculations. The outcome is the number of catheter-related bloodstream infections avoided. Costs of intensive care unit stay are based on a recent French multicentre study and the cost-effectiveness criterion is the cost per catheter-related bloodstream infections avoided. The incremental net monetary benefit per patient is also estimated.</p><p>Patients</p><p>1000 patients per group simulated based on the source randomized controlled trial involving 1,879 adults expected to require intravascular catheterization for 48 hours.</p><p>Intervention</p><p>Chlorhexidine Gluconate-containing securement dressing compared to non-antimicrobial transparent dressings.</p><p>Results</p><p>The chlorhexidine gluconate dressing prevents 11.8 infections /1,000 patients (95% confidence interval: [3.85; 19.64]) with a number needed to treat of 85 patients. The mean cost difference per patient of €141 is not statistically significant (95% confidence interval: [€-975; €1,258]). The incremental cost-effectiveness ratio is of €12,046 per catheter-related bloodstream infection prevented, and the incremental net monetary benefit per patient is of €344.88.</p><p>Conclusions</p><p>According to the base case scenario, the chlorhexidine gluconate dressing is more cost-effective than the reference dressing.</p><p>Trial Registration</p><p>This model is based on the data from the RCT registered with <a href="http://www.clinicaltrials.gov" target="_blank">www.clinicaltrials.gov</a> (<a href="https://clinicaltrials.gov/ct2/show/NCT01189682" target="_blank">NCT01189682</a>).</p></div

Health states defined from a multicentre randomized controlled trial [13].

<p>* New CT needed can mean either the replacement of the existing catheter, or the need for an additional catheter at a new site.</p><p>CRBSI, Catheter-related Bloodstream Infections; CT, Catheter (Central venous or radial / femoral arterial).</p><p>Health states defined from a multicentre randomized controlled trial [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0130439#pone.0130439.ref013" target="_blank">13</a>].</p

Structure of the Markov Model showing the possible transition between health states from one Markov cycle to the next cycle.

<p>The costs per patient for each health state were calculated in both CHG and No-CHG dressing as respectively: State 1: €1,270 and €1,266; State 2: €1,364 and €1,361; State 3: €13,661 and €13,658; State 4: €13,756 and €13,752; State 5: €1,388 and €1,385; State 6: €1,266 and €1,266; State 7: €0 for both groups; State 8: €0 for both groups; CHG: chlorhexidine gluconate; CRBSI: catheter-related bloodstream infection; CT: catheter.</p

Occurrences per 1,000 patients as generated through 1,000 NH-MCMC of 1,000 patients in each dressing group, according to the base case scenario.

<p>CHG, Chlorhexidine Gluconate; CI, Confidence Interval; CRBSI, Catheter-related bloodstream infection; CT, Catheter; ICU, Intensive Care Unit; NH-MCMC, Non-Homogeneous Markov Chain Monte Carlo.</p><p>Occurrences per 1,000 patients as generated through 1,000 NH-MCMC of 1,000 patients in each dressing group, according to the base case scenario.</p

Cost-effectiveness results for the probabilistic sensitivity analysis.

<p>The analysis uses 1,000 non-homogeneous Markov-Chain Monte Carlo simulations of 1,000 patients for each dressing strategy. The x axis represents the difference in effectiveness (number of CRBSI events in CHG versus non CHG dressing) and the y axis represents the difference in cost (mean cost per patient with CHG versus non CHG dressing) in €2013. The (0,0)-point indicates the reference dressing strategy (Non-CHG group). Each point in the graph represents the Incremental Cost-Effectiveness Ratio (ICER) of CHG-dressing strategy versus reference dressing. All but three points are at the left side of the graph, showing that CHG dressing strategy was 99.7% more effective than the comparator at the same costs per patient. The squared point in the center of the cloud represents the average CE ratio of all 1,000 simulations. CHG: chlorhexidine gluconate; CRBSI: catheter-related bloodstream infection.</p

Mean Cost for one patient in each dressing group.

<p>Time Horizon: 30-days ICU—1,000 NH-MCMC simulations of 1,000 patients (€2013).</p><p>CHG: Chlorhexidine Gluconate; CI: Confidence Interval; ICU: Intensive Care Unit; NH-MCMC: Non-Homogeneous Markov-Chain Monte Carlo simulation</p><p>Mean Cost for one patient in each dressing group.</p

Patient flow chart, management, and 28-day follow-up in 21 patients enrolled in the study.

<p>Patient flow chart, management, and 28-day follow-up in 21 patients enrolled in the study.</p

Non-homogeneous Semi-Markov Chain simulation from observed data (CLEAN)–simulated global patient—ICU-time horizon: 100 days.

<p>Non-homogeneous Semi-Markov Chain simulation from observed data (CLEAN)–simulated global patient—ICU-time horizon: 100 days.</p

Cost-effectiveness results from observed data (CLEAN database)–Observed global patient—ICU-Time Horizon: 100 days.

<p>Cost-effectiveness results from observed data (CLEAN database)–Observed global patient—ICU-Time Horizon: 100 days.</p

Patient characteristics (n = 21).

<p>Patient characteristics (n = 21).</p