Community-acquired pneumonia (CAP) is a serious acute infection of the lower respiratory system in patients with limited to no previous healthcare exposures.1,2 When CAP is caused by bacterial pathogens, CAP is classified as community-acquired bacterial pneumonia (CABP). Pathogens causing significant CABP morbidity and mortality include pneumococci, Klebsiella spp, Haemophilus influenzae, and Staphylococcus aureus.1,3 Treatment of patients with CAP is usually empiric.2,4 Currently, ceftriaxone with azithromycin combination therapy or fluoroquinolone levofloxacin monotherapy are the most frequently prescribed regimens for the treatment of hospitalized, non–intensive care unit (ICU) adult patients with suspected or documented CABP.5
Despite the availability of vaccines and antibiotics, the incidence of CAP remains high and is associated with considerable morbidity and mortality.1,2 Pneumonia is the third leading cause of death worldwide and the sixth leading cause of death in the United States.2 The risk of CAP-related mortality is greatest among elderly patients and those with comorbidities. As such, CAP places a considerable burden on healthcare systems, particularly if hospitalization is required.6,7 In 2010, the costs associated with CAP were greater than $17 billion annually.7
Omadacycline is an oral and intravenous (IV), once-daily aminomethylcycline antibiotic that has activity against the most common CABP pathogens, including multidrug resistant Staphylococcus pneumoniae, and is approved by the US Food and Drug Administration (FDA) for the treatment of adult patients with CABP.8-11 To date, omadacycline has been shown to be noninferior to moxifloxacin for patients with CABP in 1 phase 3 registrational clinical trial (NCT02531438).10 Rates of adverse events (AEs) such as nausea and vomiting, diarrhea, infusion-site extravasation, and headache were comparable between treatment groups, with the exception of the incidence of Clostridium difficile infections, which occurred in 8 (2%) patients who received moxifloxacin but not in patients who received omadacycline.10
As hospital reimbursement and antimicrobial stewardship programs are both increasingly tied to quality, efficiency, and cost of care, economic assessments of new drugs and therapies are often required to determine their costs and benefits relative to currently available therapies. The objective of this analysis was to estimate the budget impact of omadacycline compared with relevant comparators in the treatment of adult patients with suspected or documented CABP from the hospital perspective using a de novo budget impact analysis. Sensitivity analyses were conducted to assess the impact of key parameters on the model results, and scenario analyses were explored to analyze the budget impact of avoiding hospitalization and reducing hospital length of stay (LOS) with omadacycline relative to current treatments. Data suggest that using an antibiotic like omadacycline that has therapeutically equivalent IV and oral formulations may avoid hospitalization or reduce hospital LOS when patients need to be hospitalized. Based on this hypothesis, scenarios were designed to assess the potential cost impact of these premises (ie, hospital avoidance, hospital LOS reduction). Of note, there are no actual data to support these scenarios for omadacycline at this time, and it was not evaluated in the omadacycline clinical trials.
The model was developed to estimate the cost of introducing omadacycline to hospitals as a treatment for suspected or documented CABP over a 3-year time frame. The model is based on a theoretical cohort of 1 million Medicare members in the United States, and is consistent with guidance from the International Society for Pharmacoeconomics and Outcomes Research on good practices for budget impact modeling.12
Model Description and Structure
The budget impact model (BIM) was developed in Microsoft Excel® 2010. The analyses were conducted from a US hospital perspective. All patients were assumed to present to the emergency department (ED). Patients could then transition to the observation unit or directly to the inpatient or outpatient setting.
Model Inputs and Assumptions
The incidence rate for pneumonia ED visits was estimated to be 5.3 per 1000 people.13 Treatment pathway assumptions for patients with CABP who presented to the ED are shown in Table 1. Of the 5300 hypothetical patients who presented to the ED, 23% received care in the observation unit and 40% were assumed to be admitted from either the ED or observation unit (2106 patients).
Market Share Assumptions
Market share assumptions are provided in Supplementary Table 1. Market share estimates for scenario analyses without omadacycline were derived from an analysis of the Arlington Medical Resources (now part of Decision Resources Group) database (see Appendix). Market share assumptions for omadacycline were 0.03% in year 1, 0.11% in year 2, and 0.25% in year 3. Default market share projections in the analysis were set conservatively based on observation of the utilization of other new antibiotics, such as tedizolid and ceftaroline; these estimates were also based on the analysis of the Arlington Medical Resources database (see Appendix). There has not been an IV/oral antibiotic indicated for CABP introduced in many years (moxifloxacin received FDA approval in December 1999).14
Clinical Inputs and Assumptions
Base-case treatment response rates and treatment discontinuations due to AEs are shown in Table 2.10,15-19 Successful treatment response was defined as the total number of patients receiving treatment minus the total number of patients who had therapy discontinued due to treatment failure (ie, lack of efficacy) or to AEs. Treatment failure was defined as the proportion of patients who discontinued treatment due to lack of efficacy. Efficacy inputs and assumptions for omadacycline were based on 1 phase 3 trial (OPTIC) that assessed the safety and efficacy among patients with CABP who received once-daily IV to oral omadacycline compared with patients who received IV to oral moxifloxacin.10 The assumption was that all comparators, including omadacycline, have equal treatment responses (ie, efficacy) based on the results of historical noninferiority clinical trials for all comparators in the model. The incidence of AEs leading to discontinuation for antibiotics included in the model were obtained from phase 3 clinical trials.
The average times in the ED and observation unit were set at 0.29 and 0.71 days, respectively. The total treatment duration for the base-case analysis for “treatment successes” was 5 inpatient days. The assumption for hospital LOS was derived from an analysis of the Vizient® Health System Hospital Database (Appendix) and was applied for omadacycline and all comparators to allow a fair comparison among all antibiotics in the BIM.20 Time to treatment failure due to lack of efficacy was assumed to be 3 days; this was based on the FDA guidelines for assessment of early clinical response and inappropriate response to treatment.21 The duration of subsequent inpatient treatment of 5 days (8 total inpatient days) was applied (assumption). Assumptions regarding treatment discontinuation due to AEs included a time to event of 2 days and a duration of subsequent inpatient treatment of 6 days. Day 2 of therapy was selected as the day of treatment discontinuation, because most AEs occur early during the course of therapy.22-24 Although we could have selected a later day during the course of therapy for AEs leading to discontinuation, we conservatively selected day 2 as the discontinuation day for AEs as a measure to have identical total hospital LOS (8 days) for treatment discontinuations due to lack of efficacy and AEs.
Cost Inputs and Assumptions
Treatment acquisition costs used in the BIM are summarized in Supplementary Table 2. Wholesale acquisition costs were obtained from the Medi-Span Price Rx® database in 2017.25 To provide a conservative estimate of budget impact, the model used the lowest price per milligram to derive total acquisition costs. Wholesale costs for omadacycline were provided by Paratek Pharmaceuticals, Inc.
ED, observation, and inpatient hospitalization costs are shown in Supplementary Table 3.20,26 EDs and observational units were assumed to be hospital-owned and were included in the analyses (cost derived from an analysis of the Vizient® database, Appendix). Per diem hospital costs were assumed to be $2273.27 It was assumed that per diem costs would incorporate administrative and monitoring costs. For patients who had treatment discontinued due to treatment failure or an AE, only the additional hospital day costs were considered.
Model Analyses and Outputs
Model outputs for scenarios with and without omadacycline included:
- Total and disaggregated costs by category
- Categorized by location as ED, inpatient, outpatient, or observation
Treatment acquisition cost
- ED, inpatient, outpatient, or observation
Total and incremental budget impact per year, presented as:
- Total per year
- Cumulative over the entire time horizon
- Cost per member
- Cost per member per month
- Cost per member treated (cost per case)
- Cost per member treated (cost per case) per month.
Sensitivity and Scenario Analyses
One-way sensitivity analysis. To test the uncertainty of the model inputs, one-way sensitivity analyses were performed. The sensitivity of the model to changes in individual parameter estimates was assessed via the impact of changing parameter values when the input was varied by ±20%.
Scenario analyses. The first set of scenario analyses examined potential reductions in hospital LOS (1- and 2-day LOS reductions) associated with IV-to-oral omadacycline relative to the current inpatient standard of care. For the second scenario analysis, the directed use of outpatient omadacycline to suitable patients in the ED was explored. All other base-case settings were applied to the scenario analyses.
Distribution of the suspected or documented CABP study population for the base-case scenario with and without omadacycline is shown in Table 3. Base-case analyses results are presented in Table 4A. Over the span of 3 years, the addition of omadacycline increased the budget impact by $1568 in year 1, $5805 in year 2, and $13,271 in year 3, resulting in a cumulative impact of $20,644. The increased costs with omadacycline were largely due to increased drug acquisition costs in the ED and inpatient settings (Table 4A). This resulted in an incremental increase in the cost per member treated of $0.30 in year 1, $1.10 in year 2, and $2.50 in year 3.
One-Way Sensitivity Analysis for Omadacycline as First-Line Treatment
The most influential parameter on budget impact was inpatient LOS (Figure). Other impactful parameters included the omadacycline success rate, cost of omadacycline, failure cost of omadacycline, and success rates of comparator treatments.
Results of the hospital scenario analyses are shown in Table 4B, Table 4C, and Table 4D. With 1 hospital day saved with omadacycline, the cumulative incremental cost for the addition of omadacycline was $2384. A decrease of 2 hospital days with omadacycline resulted in cumulative 3-year savings of $15,875. Shifting inpatient care to the outpatient setting with omadacycline resulted in 3-year cumulative cost-savings of $112,843.
The aim of this study was to estimate the budget impact of omadacycline following its introduction as a treatment option for patients with CABP. Overall, the base-case analyses indicated that the introduction of omadacycline results in a modest increase in the total budget as a treatment over a 3-year period. Not surprisingly, the main cost driver of the budget increase was treatment acquisition costs. Although increased overall costs with omadacycline were noted in the base-case analysis, it is possible this could be offset by costs associated with current treatments that were not varied between treatments in this model. In the one-way sensitivity analyses, a parameter that heavily influenced the total budget beyond omadacycline drug acquisition costs was the input treatment success rates of therapies included in the model. In the base-case analysis, we assumed these to be the same across all treatments due to lack of comparator data in a comparative-effectiveness trial. The 2 major comparators in the BIM were ceftriaxone with a macrolide and fluoroquinolone monotherapy. Data suggest that upwards of 40% of hospitalized, non-ICU patients with CABP who receive ceftriaxone and macrolide therapy do not achieve clinical response by day 4 of hospitalization, and time to clinical response has been associated with the total length of time spent in the hospital.28,29 Studies indicate that fluoroquinolones may result in more AEs relative to other antibiotics, and these safety concerns prompted the FDA to update the labeling of all fluoroquinolones to better describe the serious risk of multiple disabling and potentially irreversible adverse reactions associated with their use.30 Although we did not alter the base-case assumptions in light of these data, the budgetary impact of adding omadacycline to the formulary should be revisited as more phase 4, real-world comparator data become available.
Hospital LOS was also found to profoundly influence the total budget impact of CABP treatment. This was not surprising, as hospitalization is estimated to account for 80% of CABP-associated healthcare costs.31,32 Even for low-risk patients with CABP, the average cost of a hospitalization was found to exceed $15,000 in a recent large US hospital administrative database study.32 Whereas omadacycline is available in therapeutically equivalent IV and oral formulations, and existing literature supports the earlier discharge of patients as soon as they can safely be transitioned to self-administered oral drugs,33-35 the model was used to explore the budget impact of shorter inpatient hospital stays with omadacycline. Overall, the budget impact was reduced with omadacycline in the “hospital LOS reduction” scenarios, especially if omadacycline-associated hospital stays were reduced by 2 days. Although a variety of costs were considered in the hospital LOS reduction scenario analyses, the collective results suggest that it may be advisable to consider using omadacycline as a measure to shorten hospital stay and reduce overall costs due to its comparable IV and oral formulations in appropriate patients when other oral antibiotics may not be an appropriate option for them, although this concept must be further explored clinically.
As part of this analysis, the budget impact of shifting inpatient care to the outpatient setting with omadacycline (IV transitioned to oral) was explored. Consensus CABP treatment guidelines recommend that clinicians use site-of-care severity of illness indicators and prognostic models to identify patients with CABP who may be candidates for outpatient treatment, given the substantially lower costs associated with outpatient management of patients with CABP relative to inpatient care.2 Despite this level 1 guideline recommendation, data suggest that clinicians still tend to hospitalize a substantial proportion of low-risk patients with CABP, leading to unnecessary and costly hospital admissions. Consistent with the hospital LOS reduction scenario analyses, shifting the site of care to the outpatient setting with targeted use of omadacycline (IV transitioned to oral) among suitable patients may also potentially result in a reduction in the overall budget impact of patients with CABP from the hospital perspective.
It is important to recognize that the interpretation of the results may be limited by assumptions made within the BIM. Like all BIMs, construction of the BIM required us to make a number of assumptions. Whenever possible, published data were used to inform the BIM. Many required inputs, however, were not available in the peer-reviewed literature. This required us to conduct analyses with 2 different healthcare databases (Vizient and Arlington) to generate the data necessary for the BIM (Appendix). In certain cases, assumptions had to be made because of lack of data. As an example, it was assumed that clinical efficacy and hospital LOS were the same for omadacycline and all comparators. To date, nearly all trials establishing antibiotic effectiveness rates were conducted in phase 3 noninferiority trials. Because of this, we believed it was advisable to assume these 2 critical inputs were the same across treatments due to lack of head-to-head, real-world comparative-effectiveness data. Assumptions about market uptake of omadacycline also may not have been accurate. Projected market share estimates for omadacycline were intentionally modest, as is expected for newly approved antimicrobials. Patterns of antibiotic resistance were not included in the model, which may affect treatment choice and length of inpatient hospital stays. Along these lines, resistance rates for omadacycline are not currently known. For now, the results of the BIM analyses should be viewed as conservative estimates of the impact of adding omadacycline to formularies in substitution of other therapies. As additional data become published on the assumption-based inputs, the BIM should be considered and assessed.
Based on this BIM, the introduction of omadacycline as treatment for CABP would result in a net modest increase in costs over a 3-year period. Although the results presented here indicate a modest overall impact to the budget, the results of the scenario analyses suggest that it may be worthwhile to consider using omadacycline as a potential measure to shorten or avoid hospital stay, and thus reduce hospital costs, due to its therapeutically equivalent IV and oral formulations in appropriate patients when other oral antibiotics may not be an appropriate option for them. These additional scenarios should be considered by formularies, despite the projected budgetary increase, when drawing comparisons to currently prescribed treatment options. As with all BIM analyses, it is important to recognize that it is a modeling exercise. All the findings must be validated in the clinical arena before drawing definitive conclusions.
The authors would like to thank Robert Adamson, PharmD, FASHP, for his thoughtful contributions and perspectives during the development of this manuscript. Kate Young, PhD (PAREXEL Access), contributed to its budget impact model development. Medical writing and editing support were provided by Melanie Jardim, PhD (Evidera, Raleigh, NC).
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Author Disclosure Statement
Dr LaPensee is an employee of Paratek Pharmaceuticals, Inc; Mr Mistry has received consulting payments from Paratek Pharmaceuticals, Inc; Dr Lodise has received consulting payments from Paratek Pharmaceuticals, Inc.
Dr LaPensee is Director, Health Economics and Outcomes Research, Paratek Pharmaceuticals, Inc, King of Prussia, PA; Mr Mistry is Senior Associate, Health Economics, PAREXEL Access Consulting, PAREXEL International, London, UK; Dr Lodise is Professor, Albany College of Pharmacy and Health Sciences, NY.
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