Budget impact and pharmacy costs with targeted use of oliceridine for postsurgical pain in patients at high risk of opioid-related adverse events

ABSTRACT

Background

Oliceridine, a new class of μ-opioid receptor agonist, may be associated with fewer opioid-related adverse events (ORAEs) due to its unique mechanism of action. Thus, it may provide a cost-effective alternative to conventional opioids such as morphine.

Patients and Methods

Using a decision tree with a 24-hour time horizon, we calculated costs for medication and management of the three most common AEs (oxygen saturation <90%, vomiting, somnolence) following postoperative oliceridine or morphine in high-risk patients. Costs were enumerated as differences in cost of analgesics and resource utilization in the first 24 hours post-surgery. An economic model compared expected AEs and costs in a blended cohort where elderly/obese patients at higher risk for ORAEs received oliceridine while those presumed to be at lower risk received morphine with a cohort that received morphine alone.

Results

In high-risk patients, use of oliceridine resulted in overall savings of $363,944 (in 1,000 patients). Implementing a targeted approach of oliceridine utilization in patients with high risk for ORAEs can save a typical hospital system $122,296 in total cost of care.

Conclusion

Use of oliceridine in postoperative care among patients at high risk provides a favorable health economic benefit compared to the use of morphine.

PLAIN LANGUAGE SUMMARY

Oliceridine, a new class of opioid analgesics, administered directly into a vein, is a unique medication in that it provides pain relief equivalent to morphine and may have less costly side effects. It is given in a hospital/clinic or surgery center for the treatment of postoperative pain and can reduce costs compared to other opioid analgesics, possibly due to less side effects. An economic model was developed that compares morphine to oliceridine in patients more likely to experience sides effects due to traditional pain medications, comparing common side effects and pain relief following surgery. Although oliceridine costs more than morphine, in our economic model, the use of oliceridine resulted in cost savings ($363,944 US 2020 Dollars in 1,000 patients), and a positive return of investment of over 7 times, when compared to morphine.

KEYWORDS:

• Acute pain
• cost of care
• elderly
• morphine
• obese
• oliceridine
• postoperative

1. Introduction

Management of postsurgical pain is a critical component of perioperative care. Inadequate treatment of postsurgical pain has been linked to substantial clinical and economic adverse consequences, including reduced quality of life, surgical complications, prolonged rehabilitation, and development of chronic pain [1,2]. In many surgical procedures, the availability of intravenous (IV) opioids is an important component of a comprehensive strategy to manage acute postsurgical pain [3]. However, this class of pharmaceutical analgesics is generally characterized by a relatively narrow therapeutic window due to the development of a range of medically significant adverse events (AEs) [4]. Shafi et al [5] estimated that the incidence of International Classification of Diseases, Ninth Revision (ICD-9) code-based opioid-related adverse events (ORAEs) among surgical patients range from 1.8% to 13.6%, and also reported that patients with such events experienced prolonged lengths of stay (LOS) and higher hospital costs. These investigators also noted that patients who experienced ORAEs had $8,225 higher mean cost per admission ($25,599 per admission compared to $17,374 for patients with no ORAEs) after controlling for patient demographics, clinical risk factors, and surgery type. In addition, mean LOS in the hospital was 1.6 days longer for patients reporting ORAEs (6.8 days compared to 5.2 days for patients without events) [5].

The clinical challenge is heightened further in the setting of clinical and demographic factors that place patients at higher risk for the development of ORAEs, including advanced age or patients who are overweight. Given the reality that the surgical patient population is aging [6], coupled with the increasing prevalence of obesity, which independently can be a critical factor affecting surgical outcomes [7], there is an obvious medical need for innovation in opioid analgesics. New medication options that may widen the therapeutic window for analgesic effect, with an improved safety profile, especially in patients at higher risk for the development of ORAEs would be a welcome addition to available therapeutics.

Oliceridine IV was recently approved by the US FDA as an opioid analgesic indicated in adults for the management of acute pain severe enough to require an IV opioid analgesic and for whom alternative treatments are inadequate [11]. While all opioid medications bind to the µ-opioid receptor, oliceridine differs from conventional opioid analgesics in its pattern of post-receptor signaling within the cell. Specifically, oliceridine preferentially engages the G-protein signaling pathway, with relatively little engagement of the β-arrestin signaling pathway within the cell [12]. This pharmacologic innovation framed the scientific rationale for the discovery and development of oliceridine, since it had been theorized that the G-protein signaling pathway is responsible for the analgesic effects of µ-opioid receptor activation, while the β-arrestin pathway contributes to the development of adverse outcomes characteristic of opioid medications [13,14]. Among the most troubling ORAEs are respiratory depression, gastrointestinal (GI) complications, and central nervous system depression. These potential differences in adverse outcomes were studied in detail in the Phase 3 clinical trials which were used to support the approval of oliceridine. These studies included two large, multisite, Phase 3 randomized placebo- and active (morphine)-controlled clinical trials in hard and soft tissue surgical models (APOLLO-1: orthopedic surgery–bunionectomy study; NCT02815709 and APOLLO-2: plastic surgery–abdominoplasty study; NCT02820324) [9,10]. In addition, the safety and effectiveness of oliceridine as a first-line pain medication for surgical patients was examined in a pragmatic, real-world, prospective, Phase 3 observational study, among a clinically diverse population of surgical patients studied in a variety of clinical practice settings, including hospital inpatient units, ambulatory surgery centers, and hospital emergency departments (ATHENA; NCT02820324) [15].

Previously we have reported a health economic model that was developed using the published Phase 3 clinical evidence for oliceridine and that examined the cost-effectiveness of oliceridine when utilized as a substitute for morphine in the management of acute postsurgical pain [8]. Results of that analysis demonstrated that the use of oliceridine, while associated with a modest increase in pharmacy costs, provided a substantially favorable economic benefit on the total cost of care. These results were largely due to the differences in the incidence of adverse outcomes observed between oliceridine and morphine in the clinical trial data from the randomized controlled Phase 3 clinical studies. Here we extend these economic observations by providing an analysis of the specific health economic consequences when either oliceridine or morphine is used among a population of higher risk, including the elderly/obese patients, during their postsurgical care. We also provide an accompanying budget impact model, from the hospital perspective, based on these health economic outputs. Additionally, a return-on-investment (ROI) calculation was performed based on the cost savings realized. This analysis and the previously published base model, referred to within this study, followed the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) recommended for economic modeling studies [16].

2. Patients and methods

2.1. Source data

Clinical efficacy and adverse outcome data were obtained from the published Phase 3 studies of oliceridine for the treatment of acute pain in the postoperative setting (Table 1). Oliceridine was studied in two pivotal Phase 3 placebo- and active-controlled multisite clinical trials [9,10]. Study 1 examined the efficacy and safety of oliceridine for the treatment of postoperative pain following hard tissue orthopedic surgery in 389 patients undergoing first metatarsal bunionectomy with regional anesthesia [9]. Patients included in the study had reported at least moderate pain, as measured on a categorical scale (none, mild, moderate, and severe) and on an 11-point numeric rating scale ([NRS] ≥4) within 9 hours after discontinuation of regional anesthesia. Mean baseline pain scores based on an 11-point NRS (0 = no pain, 10 = worst pain) were − placebo: 7.0 (1.5), oliceridine 0.35 mg: 6.6 (1.9), oliceridine 0.5 mg: 6.5 (1.7), and morphine: 6.7 (1.6). Study 2 examined the efficacy and safety of oliceridine for the treatment of postoperative pain following soft tissue plastic surgery in 401 patients undergoing an abdominoplasty procedure under general anesthesia [10]. Patients included in this study had reported moderate or severe pain both on a categorical scale (none, mild, moderate, or severe) and on an NRS (score ≥5, range: 0 = no pain to 10 = worst pain imaginable) within 4 hours post-surgery. Mean baseline pain NRS scores were − placebo: 7.2 (1.4), oliceridine 0.35 mg: 7.4 (1.6), oliceridine 0.5 mg: 7.5 (1.6), and morphine: 7.3 (1.5). In addition to the controlled clinical studies, a third study (Study 3) examined the safety and tolerability of oliceridine in an open-label, real-world study among 768 patients treated for a broad range of postoperative and post-procedural clinical care requiring the use of a parenteral opioid for the management of acute pain [15]. The study included adult patients with moderate to severe pain (NRS ≥4 on an 11-point rating scale, range: 0 = no pain to 10 = worst pain) as noted 30 minutes prior to receiving the first dose of oliceridine. Mean baseline NRS score was 6.3 (2.1).

Table 1. Summary of efficacy outcomes, rescue analgesic, and rescue antiemetic medication use in the health economic analysis [8]

Input parameter	Treatment allocation	Value
Efficacy (% Responder)
	Oliceridine 0.35 mg demand dose initial responders	66.1%
	Oliceridine 0.5 mg demand dose incremental proportion of responders	19.4%
	Morphine 1 mg demand dose	73.6%
Rescue analgesic medication Use (%)
	Oliceridine 0.35 mg demand dose	17.0%
	Oliceridine 0.5 mg demand dose	14.5%
	Morphine 1 mg demand dose	12.0%
Rescue antiemetic medication Use (%)
	Oliceridine 0.35 mg demand dose	45.3%
	Oliceridine 0.5 mg demand dose	51.1%
	Morphine 1 mg demand dose	62.9%

The data shown here are obtained from the two randomized placebo- and morphine-controlled Phase 3 studies (pivotal) in patients with moderate to severe acute pain following either orthopedic surgery–bunionectomy (APOLLO-1, Study 1) [9], or plastic surgery–abdominoplasty (APOLLO-2, Study 2) [10]. The pre-specified primary clinical efficacy outcome in the pivotal Phase 3 studies was the categorical outcome of response defined as patients who met the following criteria: 1) at least a 30% improvement in final time-weighted sum of the pain intensity differences (SPID) from baseline at 48 hours (SPID-48) for orthopedic surgery–bunionectomy or at 24 hours (SPID-24) for plastic surgery–abdominoplasty; 2) without use of rescue pain medication during the randomized treatment period; 3) without early discontinuation of study medication for any reason; and 4) without reaching the study medication volume-based dosing limit. Prophylactic antiemetics were not allowed and patients enrolled had a high risk of postoperative nausea and vomiting (PONV), based on their Apfel scores at baseline (≥3) [9,10].

Details of the study designs, patient demographic and clinical information, and study outcomes are reported elsewhere [9,10,15]. The pre-specified primary clinical efficacy outcome in the pivotal randomized controlled Phase 3 studies was the categorical outcome of response defined as patients who met the following criteria: 1) at least a 30% improvement in final time-weighted Summed Pain Intensity Differences (SPID) from baseline at 48 hours (SPID-48) for orthopedic surgery–bunionectomy or at 24 hours (SPID-24) for plastic surgery–abdominoplasty; 2) without use of rescue pain medication during the randomized treatment period; 3) without early discontinuation of study medication for any reason; and 4) without reaching the study medication volume-based dosing limit.

ORAEs of interest for the health economic analysis were those directly observed in the pivotal clinical trials and included: 1) oxygen desaturation defined as a measured oxygen saturation reaching an SpO₂ < 90%; 2) vomiting; and 3) somnolence, the latter two outcomes both reported as Medical Dictionary for Regulatory Activities (MedDRA)-coded AEs. These are shown in Table 2. Opioid-induced respiratory depression (OIRD) events were pre-specified, as defined in the original study protocols, for all patients based on verbatim clinical terms coded using AE methodologies defined in MedDRA (version 19.0). These included terms for hypoventilation, hypoxia, respiratory depression, and respiratory failure categories and over 100 possible MedDRA-coded terms. Terms for sedation/somnolence included: groggy and sluggish, drowsy on awakening, tranquilization excessive, dullness, less alert on arising, daytime sleepiness, sedation excessive, dopiness, sleepiness, somnolence neonatal, druggedness, hard to awaken, fuzzy, sluggishness, oversedation, overtranquilization, narcolepsy, lethargy, relaxed, groggy on awakening, groggy, drowsiness.

Table 2. Adverse event incidence and risk-ratio computation from pooled pivotal randomized controlled Phase 3 RCTs (orthopedic surgery–bunionectomy study and plastic surgery–abdominoplasty study) [Modified from 8]

Adverse Event	Treatment Allocation
	Oliceridine 0.35 mg demand dose	Oliceridine 0.5 mg demand dose	Morphine 1 mg demand dose
Low O2 Saturation
Value (%)	14.6	17.0	22.2
Risk-ratio applied	1.52	1.16	–
Vomiting
Value (%)	30.3	41.5	51.9
Risk-ratio applied	1.71	1.37	–
Somnolence/Sedation
Value (%)	19.0	15.1	23.5
Risk-ratio applied	1.24	0.8	–

The incidence rates of the 3 opioid-related adverse events (ORAEs): O₂ saturation <90%, vomiting and somnolence (and sedation) shown here are derived from the pooled APOLLO–1 & −2 studies. Risk ratios for oliceridine compared to morphine were then calculated.

RCTs = randomized controlled trials.

Constipation, although a commonly occurring ORAE with chronic use of opioids, was not included in this analysis because of a) its lower incidence compared to other GI effects in our pivotal clinical trials conducted in the acute setting; and b) the lack of availability of data related to other severe post-operative GI symptoms such as ileus. Thus, constipation was not included as a cost-driver in this particular model.

2.2. Cost inputs and estimation methods

In the clinical management of postoperative pain, implementation of Enhanced Recovery After Surgery (ERAS) protocols is rapidly evolving, and it can therefore be expected that today the observed rate of ORAEs using these protocols may be even lower than those reported in the recent published literature. Correspondingly, it can be reasonably presumed that the cost of managing these adverse outcomes will be less than what is reported in the existing literature [17]. In order to avoid an overestimation of the costs of ORAEs in the health economic model described here, the most recent representative national data were used to estimate costs, and the mean marginal cost per day was selected as the analytical parameter of interest, because this is the most conservative statistical approach that could be employed. Further, since the most recent nationally representative data available are for 2017, cost estimates were inflated to reflect projected 2020 actual costs using the May 2020 medical care consumer price index (CPI) factor of 1.09647 (US Bureau of Labor and Statistics accessed at https://www.bls.gov/cpi).

The mean cost and LOS for a group of eight surgical procedures highly likely to require the use of parenteral opioids for postoperative pain management were estimated using the 2017 National Inpatient Sample (NIS) data set from the Healthcare Cost and Utilization Program (HCUP) [18]. All records for patients aged 18 and older were extracted from the sample. Surgical admissions were identified by the International Classification of Diseases, Tenth Revision (ICD-10) procedure codes. These codes included surgical phenotype specifications for the following procedures: gastrectomy, gastric bypass, colon-rectal resection, knee arthroplasty, coronary artery bypass graft (CABG), spinal fusion, cholecystectomy, and abdominal repairs. This restricted dataset included 467,796 adult admissions, which constitutes a representative sample of 2,338,979 US surgeries performed in 2017. Females comprised 56.6% of the total sample population. Racial distribution was 75.3% White, 10.0% Black, and 9.5% Hispanic, with the balance of the sample distributed across Other, Mixed, or Undeclared race categories. Less than 1% of patients died during the surgical admission (0.84%). Mean patient age was 61.0 years [standard deviation(SD): 16.7, range: 18 to 90]. Mean LOS in hospital was 4.54 days (SD: 6.9, range: 0 to 334 days). The cost per admission was estimated by applying each hospital’s cost-to-charge ratio to the total charges for the admission, a standard approach for summarizing HCUP data. The estimated mean cost per admission was $24,168 (median: $16,618, SD: $27,286, range: $19 to $2,466,577). NIS sample weighted and unweighted values were identical, so the unweighted means were used for calculation of the marginal cost for model events. The result of this analysis is provided in Supplementary Table 1.

The presence of respiratory depression after surgery has a well-documented association with LOS, increased cost, and unplanned admission to the intensive care unit [19–21]. In the recently reported multisite PRediction of Opioid-induced respiratory Depression In patients monitored by capnoGraphY (PRODIGY) trial (NCT02811302), mean LOS was 7.7 days (SD: 7.8 days) for patients without episodes of OIRD, compared to 10.5 days (SD: 10.8 days) for patients with an OIRD episode [19]. This represents an increase of 36.4% in hospital LOS. Further, an economic analysis of US cost data in PRODIGY for 148 patients with OIRD reported a 16% higher cost per admission when compared to 272 propensity-score matched patients from the study sample who did not have an episode of OIRD [22].

Thus, based on the PRODIGY analysis, the cost of OIRD may be estimated as either 15% (the calculation as reported in the abstract previously presented at the American Society of Anesthesiology Annual Meeting in 2019) of the mean cost per surgery, or as the cost associated with an increase of 36.4% in hospital LOS [23]. Fifteen percent was utilized in the analysis as the abstract of the PRODIGY study, at the time the model was contracted, was noted as 15%. However, the actual cost data from that trial may be assumed to be biased upward because they reflect costs in selected hospitals capable of undertaking such a large multisite clinical trial utilizing continuous monitoring. This assumption is supported by the relatively longer LOS reported for PRODIGY trial patients (LOS 7.7 vs. 10.5 days for non-OIRD and OIRD admissions respectively). Therefore, to avoid bias in the estimation of OIRD-associated event costs, the health economic model reported here used the mean costs and LOS from a representative sample of US surgical admissions (as listed in Supplementary Table 2). The cost of an OIRD event is then calculated as 15% of the cost of an admission. Thus, the most conservative cost weight used in the model is $24,168*15% = $3,625. This is equivalent to an increase of approximately 1.08 days in the hospital for patients with a median LOS of 3 days. If the PRODIGY estimate of 36.4% increase in LOS was used as the cost basis, the estimated cost per OIRD is mean LOS 4.54*36.4 = 1.65 days. At a median cost of $3,365 per day, an OIRD event would add $5,552 to an admission. The mean low and high estimated cost weights for OIRD events for selected types of surgeries are provided in Supplementary Table 3.

Postoperative nausea and vomiting (PONV), especially vomiting, has been identified as a significant contributor to increased morbidity and LOS, and decreased satisfaction with care among surgical patients [24,25]. The lowest reported marginal cost of PONV in the Premier Database study [20] showed a marginal cost increase for patients who experienced an episode of PONV of $1,698 and higher LOS of 1.6 days. However, as noted above, since current practice recommends the use of ERAS protocols, which almost universally include the use of prophylactic antiemetic medication, and a focus on multimodal pain management, the health economic model reported here anticipated that the risk of PONV in current practice has been consequently reduced, and thus, data from earlier studies may overstate the effect of vomiting on LOS and cost of care. To avoid over-estimating the cost of vomiting in the model, the marginal cost of vomiting used was based on the values in the NIS 2017 surgical admissions data set. ICD-10 codes for vomiting with and without nausea (R11.0, R11.11, R11.12, and K91) were used to identify an episode of vomiting. A multivariable model with a gamma-distributed log-link transformation was used to estimate the marginal cost increase for patients with a vomiting diagnosis. Episodes were controlled for age, sex, and type of surgery in the model. The mean cost per admission for patients with a vomiting diagnosis was $23,382, compared to $22,410 for patients without the condition (p < 0.0001). Thus, the marginal cost of a vomiting episode is estimated at $972. This may be expected to be a low estimate because vomiting tends to be under-reported in discharge summaries, and vomiting will therefore be under-coded in billing data. When the effect of a vomiting diagnosis on LOS was examined, an increase of 0.51 days in LOS was estimated. Using the median cost per day estimated from the HCUP dataset (see Supplementary Table 3), a mean increase of 0.51 day in LOS would result in an estimated marginal cost of vomiting of $3,365*0.51, or a cost of $1,716. Based on these analyses, $1,344 (the median value between $972 and $1,716 for the two costing results) was used as the cost weight for vomiting in the model.

Finally, the cost of somnolence or sedation was calculated for the health economic model. Somnolence or sedation was recorded as a MedDRA-coded AE among 19.9% of oliceridine-treated and 23.4% of morphine-treated patients in the pooled data from the pivotal controlled Phase 3 studies [26]. However, the recorded rate of somnolence as an AE in the large, multisite Phase 3 open-label safety study was 1.8% [8]. Rates of somnolence as an AE in archival records are much lower than rates recorded in clinical trials, making it difficult to identify the cost of these AEs under routine practice conditions. Using the ICD-10 code of R40.0, somnolence was coded among only 0.8% of the surgeries in the NIS 2017 data set, and patients with this code had 1.33 days longer LOS and $6,353 higher cost per admission than patients without a somnolence code after controlling for age, sex, and surgery type. However, given the very low prevalence of recorded somnolence, this marginal cost estimate for somnolence is most likely biased upwards because only the most severe cases were recorded. Thus, the use of this estimate in the economic model would likely bias results against morphine. As an additional observation, it is noted that Barra et al [27] estimated the cost of somnolence as an AE at 93% of the cost of a vomiting AE. Using the 2017 cost data from the NIS surgical data set, this would result in a median cost of $1,344*93% = $1,250. Based on this calculation, the more conservative cost weight of $1,250 per somnolence event was included in the health economic model to capture the economic effect of this condition. The most conservative cost weights included in the Supplementary Table 2 were adopted as the economic estimates in the analysis.

Overall costs were calculated as differences in the cost of pain medication and differences in resource use required to manage the three aforementioned adverse outcomes during the first 24 hours after surgery. Costs of pain medication, rescue therapy, and antiemetic drugs were tabulated based on utilization rates observed in the randomized controlled Phase 3 studies. Other model parameters are derived from the published literature and observational cost data and are discussed in the sections that follow.

2.3. Approach and economic model framework

Using the clinical trial and real-world data noted above, and integrating regional and national cost data, a cost-effectiveness hospital-based prospective cost beneficial analysis and ROI model was developed, comparing the costs and ORAEs. Details of the economic model framework were previously reported and described the base model economic outputs [8]. A brief summary of the model framework is presented below for clarity.

The High-Risk Patient economic model used the analysis structure defined in the base model [8] but with the model parameters modified to reflect the rates of ORAEs of interest (defined in the base model above) as reported among a clinically challenging, high-risk patient subgroup in the Phase 3 real-world pragmatic safety study (Study 3). In this model, high-risk patients were defined as those patients aged 65 years or greater and having a body mass index (BMI) of 30 kg/m² or more. As in the base model, a decision analysis tree was used to structure the data, using a 24-hour time horizon because the greatest contribution of the marginal costs and benefits of postsurgical pain management are expected to materialize within this time period. Patients were grouped on the branches of the decision analysis tree by the observed efficacy response outcomes recorded in the randomized controlled Phase 3 pivotal studies (Studies 1 and 2), by the presence or absence of adverse outcomes of interest, and by the clinical need for rescue pain medication due to lack of efficacy of the assigned treatment. As discussed earlier (Source data), the primary outcome was the percentage of patients in each oliceridine group who met the pre-specified response criteria at the end of the randomized 48-hour (Study 1) or 24-hour (Study 2) treatment period. In both studies, patients in each of the oliceridine regimens showed a statistically superior responder outcome compared to those receiving placebo (p < 0.0001; all with Hochberg adjustment). No formal non-inferiority assessments were conducted between oliceridine and morphine response rates because the predefined statistical analysis failed to show significance at the second gating assessment (i.e. respiratory safety burden or RSB). However, exploratory analyses (not corrected for multiplicity) indicated that the oliceridine 0.35 mg and 0.5 mg regimens were non-inferior to morphine (both p < 0.01) in both Study 1 and Study 2. Failure of oliceridine at the initial 0.35 mg demand dosing was assumed to lead to escalation of dosing to 0.5 mg, and then to the use of rescue analgesic medication if patients failed this higher dose. Failure to benefit among patients assigned to morphine was assumed to lead directly to use of rescue analgesic medication, as occurred in the controlled Phase 3 studies.

The differential marginal costs focused on the presence of three common and costly ORAEs associated with the use of parenteral opioid pain medication, namely, oxygen desaturation, based on observed oxygen saturation levels [SpO₂] <90%, vomiting and somnolence. These adverse outcomes were selected as the focus in the model since they have been well-characterized in the literature to be substantial post-anesthesia economic contributors to the costs associated with the use of parenteral opioids in the postsurgical setting [20,27].

The Phase 3 pivotal trials (Studies 1 and 2) were designed to test the efficacy and safety of the treatments in a controlled research setting, and by design these studies did not permit the use of multimodal analgesia. Therefore, in order to prevent the economic model from using an excessively high estimation of the true incidence of the AEs of interest likely to be seen in actual clinical practice, risk ratios for oliceridine compared to morphine were derived from the pivotal randomized controlled Phase 3 studies and then applied to the AE rates observed in the large multisite Phase 3 open-label safety study (Study 3). This latter study provided a more accurate representation of the tolerability and safety of oliceridine in a real-world practice setting under conditions of routine clinical care, where use of oliceridine in conjunction with clinician-directed multimodal analgesia was the norm. In the base model [8], the risk ratios were applied to the entire population of patients treated with oliceridine in Study 3. In the High-Risk Patient model reported here, the risk ratios were applied to the subset of patients who met age and weight criteria for inclusion in the high-risk patient stratum of Study 3.

An overview of the approach and methodology used in the economic model is shown in Figure 1. The data inputs used in the construction of the health economic model are shown in Tables 1, 2, and 3.

Table 3. Estimation of expected adverse event incidence in real-world conditions derived from Phase 3 open-label safety study data [8]

Adverse Event	Treatment Allocation
	Oliceridine 0.35 mg demand dose	Oliceridine 0.5 mg demand dose	Morphine 1 mg demand dose
Low O2 Saturation
Value (%)	13.7%	15.9%	24.2%
Vomiting
Value (%)	10.1%	13.8%	23.7%
Somnolence/Sedation
Value (%)	1.9%	1.5%	2.4%

Data shown for all treatment groups are derived from the pivotal randomized Phase 3 studies (APOLLO-1 and −2 as shown in Table 2) [9,10] and then applied to the AE rates observed in the large multisite Phase 3 open-label safety study (Study 3) [9,10]. This large study was an open-label safety study of oliceridine conducted in 768 patients following a wide range of surgical procedures or non-surgical medical conditions. All patients in the study had at least one medical comorbidity. Almost half of all patients (46%) were obese with a BMI ≥30 kg/m² and 32% were aged 65 years or older. For the model, the ORAE risk ratios were applied to the high-risk patients defined as elderly and obese.

AE = adverse event; BMI = body mass index; ORAE = opioid-related adverse event.

Figure 1. Overview of the economic model methodology [Modified from 8].

The model focused on specific AEs: 1) oxygen desaturation defined as measured oxygen saturation with an SpO₂ <90%; 2) vomiting as a reported MedDRA-coded AE; and 3) somnolence, as a reported MedDRA-coded AE directly measured in the Phase 3 studies. Estimates of the risks (risk ratios) of these AE outcomes were derived directly from the safety data measures reported in the Phase 3 orthopedic surgery–bunionectomy (APOLLO-1) [9,10] and plastic surgery plastic surgery–abdominoplasty abdominoplasty (APOLLO-2) [9,10] studies. The risk ratios were then applied to AE rates observed in high-risk patients (age ≥65 years a BMI ≥30 kg/m²) from the Phase 3 open-label safety study of oliceridine [9,10] to estimate the rates of AEs reported among a medically complex, real-world patient sample. Other model parameters are derived from the published literature and observational costs data.AE = adverse event; BMI = body mass index; MedRA = Medical Dictionary for Regulatory Activities; SpO₂ = peripheral oxygen saturation.

2.4. Budget impact model structure

The framework for the budget impact model is shown in Figure 2. The model was designed to compare expected adverse outcomes and costs among a cohort of patients who received only morphine for their postoperative pain management to a blended cohort of patients within which a subset of patients at higher risk for ORAEs (of interest as mentioned above) received oliceridine while the balance of the patients (i.e. those presumed to be at lower risk) received morphine for their postoperative acute pain management. To do this, the budget impact model assumed that only patients aged ≥65 years and who also have a BMI ≥30 kg/m² received oliceridine and that the balance of lower risk patients in that allocated group were treated with morphine. Based on the demographic and clinical features directly observed in the population of patients in Study 3 [15], this subset of higher risk patients is estimated to represent 16.6% of the overall population studied.

Figure 2. Analysis framework for budget impact model. The Budget Impact Model assumes that only high-risk patients (age ≥65 years who have a BMI ≥30 kg/m²) will receive oliceridine and that the balance of lower risk patients in that allocated group will be treated with morphine. Based on the population demographics directly observed in the ATHENA study population [9,10], this subset of higher risk patients is estimated to represent 16.6% of the overall population studied. The Budget Impact Model also assumes a total annual sample of 1,132 eligible surgeries per year, with a distribution of surgical cases as observed on average for hospitals in Florida in 2017 [18]. The Budget Impact Model estimated the total cost for pain medication, the total number of adverse outcomes, and the total number of adverse outcomes averted by using oliceridine for the high-risk patients and morphine for all others, compared to having used only morphine for all patients. A return on investment (ROI) is calculated as the ratio of the total cost of AEs averted divided by the total additional cost of pain medications.AE = adverse event; BMI = body mass index; CABG = coronary artery bypass graft.

The model estimates are based on the events and costs observed during the first 24 hours of postsurgical care. The budget impact model presumed identical patterns and amounts of use of prophylactic antiemetics, and that ERAS and other clinical protocols were implemented in a similar manner across the two treatment groups (i.e. morphine only, or a blended use of oliceridine for higher risk patients and morphine for all others). The budget impact model estimated differences in adverse outcomes, the total cost of pain medications, the total cost of adverse outcomes averted, and the total net cost savings (or increases) for the blended treatment condition compared to the treatment condition using only morphine. An ROI was also calculated as the ratio of the total cost of AEs averted divided by the total additional cost of pain medications.

In order to approximate the economic impact on a typical regional hospital system, the budget impact model assumed a total sample of 1,132 eligible surgeries per year, which was derived from the distribution of a targeted subset of surgical cases observed on average for hospitals in Florida in 2017 [18]. This reflects a case volume of an acute care hospital with approximately 275 beds. The surgical procedures included in this estimate were the following: gastrectomy, gastric bypass, knee arthroplasty, CABG, spinal fusion, cholecystectomy, and abdominal repairs.

Figure 3 shows the relationships between the main inputs from the clinical study results, the approach to calculation of risk ratios for the two treatments considered in the model, the cost inputs applied, and the resulting model parameters and outputs for the health economic model. All calculations for the decision analysis tree and economic model were programmed in Excel (Microsoft Corporation, Redmond, WA). Approaches used for issues related to skewed, missing, or censored data are described in the published reports of the clinical trials. The study parameters were weighed for appropriate representation in the cost calculations by the proportion of patients contributing to the study’s contribution to the overall model parameter.

Figure 3. Summary of the analytic framework and methodology used to design the oliceridine health economic model [8]. The analytic framework for the overall economic model was structured as a decision tree with two major branches representing treatment with oliceridine or morphine over a 24-hour time period. Treatment response parameters were derived from pooled data from the Phase 3 orthopedic surgery–bunionectomy and Phase 3 plastic surgery–abdominoplasty studies. Risk ratios for oliceridine versus morphine adverse events (AEs) were derived from these pivotal randomized Phase 3 studies and applied to the mean AE rates observed in the ATHENA observational study. This approach was used to prevent the model from using the excessively high rates observed for both treatments in the pivotal Phase 3 trials due to protocol specifications that did not permit the use of multimodal analgesia. Failure of oliceridine 0.35 mg dosing was assumed to lead to escalation of dosing to oliceridine 0.5 mg, and to use of rescue analgesic medication if patients failed this higher dose. Failure of the morphine medication was assumed to lead directly to use of rescue analgesic medication, as used in the trials. Costs of pain medication, rescue therapy and antiemetic drugs were tabulated based on rates observed in the pivotal Phase 3 studies. The decision tree was ‘rolled back’ and population numbers for each condition were calculated. Standard cost weights for AEs were estimated for each arm of the decision tree.ROI = return on investment; RR = risk ratio.

2.5. Sensitivity analysis

Two approaches were used to test the sensitivity of the original model published previously [8]. Generally, the two sensitivity methodologies executed a one-way approach to document the model’s response to changes in various model parameters and reported changes in a Monte Carlo methodology conducted in Excel using Crystal Ball software for estimation (Oracle Crystal Ball v 11.1.2.4, Oracle Software, 2017).

3. Results

3.1. High-risk model economic outputs

Utilizing an n of 1,000 high-risk patients in both treatment groups, use of oliceridine resulted in 200 fewer AEs, $459,495 lower cost of AEs, and $96,623 greater expenditures for pain medications. Overall savings were estimated at $363,944. The estimates calculated from the high-risk patient model are shown in Table 4.

Table 4. High-risk model: inputs and estimates for the comparative cost of care for 1,000 surgical patients treated on-demand with either oliceridine or morphine

	Oliceridine [0.35 mg with escalation to 0.5 mg for nonresponse] (N = 1,000)	Morphine 1 mg (N = 1,000)	Difference (Oliceridine – morphine)
Cost of pain medication for 24 hours/patient	$108.14	$15.00	($93.14)
Response rate (%)	66.1%	73.6%	(7.5%)
% Escalated to 0.5 mg	19.4%	N/A	N/A
Total number of AEs	309	509	(200)
Respiratory depression (Low O2 saturation)	157	242	(85)
Vomiting	128	237	(109)
Somnolence	24	30	(6)
Cost of pain medication	$127,181	$30,558	$96,623
Cost of AEs	$778,764	$1,238,259	($459,495)
Total Cost	$907,115	$1,271,059	($363,944)

The model results shown here are based on an assumed average daily cost of oliceridine of $100.

The total cost also includes the cost of antiemetics: $1,170 in the oliceridine arm and $2,242 in the morphine arm.

AE = adverse event.

3.2. Budget impact model output

Table 5 shows the results of the model, assuming that 16.6% of the allocated patients annually use oliceridine along with the remaining 83.4% who use morphine alone (Policy B), among a sample surgical population of 1,132 surgeries per year compared to the same population of 1,132 surgeries where only morphine was available for postoperative pain management when a parenteral opioid was required (Policy A).

Table 5. Budget impact model: inputs and estimates for the comparative cost of care among 1,132 surgical patients treated on-demand with Policy B (blended use of oliceridine and morphine) compared to Policy A (use of morphine only)

	Treatment Policy A [Use of Morphine Only] (N = 1,132)	Treatment Policy B [Blended Use of Oliceridine and Morphine] (N = 1,132)	Difference* (Policy A – Policy B)
% Population at higher risk of adverse outcomes	16.6%	16.6%	NA
Adverse outcomes
Vomiting	269	237	31
O2 desaturation	166	140	26
Somnolence	27	24	3
Total number of adverse outcomes	461	401	60
Total cost of pain medication	$34,591	$52,748	$18,157
Total cost of adverse outcomes	$964,950	$824,699	($140,251)
Total Cost of Care	$1,002,079	$879,784	($122,296)
Return on Investment			7.7

Policy B utilized blended use of oliceridine for higher-risk patients and morphine for all other low-risk patients.

For results shown here, the cost of oliceridine was set at $100 per day and morphine at $15 per day. The total cost also includes the cost of antiemetics: $1,170 in the oliceridine arm and $2,242 in the morphine arm.

*Any sum differences are due to rounding.

For Policy B, where oliceridine use is reserved for the patients at highest risk for the emergence of ORAEs, the budget impact model estimated the net savings in total cost of care to be $122,296 compared to Policy A, where morphine was used for all patients. Specifically, the savings from the use of blended oliceridine and morphine, Policy A, resulted from avoidance of ORAEs ($140,251) versus the use of morphine only, Policy B. Utilizing the formula; [ROI = gain from investment divided by the cost of investment], we calculated the ROI in this analysis as $140,251 divided by $18,157 for a total ROI of 7.7.

4. Discussion

In our economic model based on the events and costs observed during the first 24 hours of postsurgical care, oliceridine demonstrates a favorable health economic advantage for the treatment of acute pain in the postoperative setting compared to the conventional opioid, morphine. The economic advantage offered by oliceridine is especially apparent when its use is focused on those patients anticipated to be at the highest risk for the emergence of opioid-related AEs. Results of the base model were estimated for a sample population of 1,000 surgeries assigned to each treatment arm and were previously reported [8]. Briefly, in those results, patients allocated to oliceridine experienced fewer adverse outcomes, resulting in $324,005 less total cost for these adverse outcomes. While the overall hospital costs decreased, use of oliceridine resulted in $96,623 greater expenditures for pain medications. Nevertheless, these costs were more than offset by the cost savings associated with the reduced incidence of adverse outcomes and reductions in the associated cost of care and hospital LOS ($228,454). Because oliceridine was the economically dominant treatment, an incremental cost-effectiveness ratio (ICER) could not be calculated. One-way sensitivity analyses and a Monte Carlo simulation demonstrated that base model economic outputs were robust and relatively insensitive to variations in the mean model parameters [8].

In the health economic analysis reported here, when used in a high-risk patient population, oliceridine was estimated to result in a total cost savings to the hospital system of $363,944. This is an additional savings of $135,490 over the estimates obtained in the base model, which presumed that oliceridine was simply substituted for the use of morphine in all patients. Thus, when the use of oliceridine is restricted only for use among patients anticipated to be at higher risk for the emergence of ORAEs, it may be expected to further increase the overall cost savings from the perspective of the hospital. In either analysis, oliceridine was the economically dominant treatment in comparison with a conventional IV opioid medication. As in the base model analysis, an ICER could not be calculated because oliceridine was the economically dominant treatment.

In an accompanying budget impact model based on these health economic model outputs, oliceridine can be expected to save a typical hospital system $122,296 in total cost of care, when used in a targeted manner in surgical patients who are at high risk for the development of ORAEs. Across an average annual surgical population, this represents a return on investment of approximately 8-fold in return for the incremental cost of adding oliceridine to the pharmacy budget.

In recent years, the introduction of ERAS protocols has shifted focus from opioid-minimization to opioid elimination, including opioid-free analgesia [28]. However, findings show that utilization of non-opioid strategies do not necessarily eliminate use of opioids [29,30]; and few recent studies also report increased AEs associated with the use of non-opioid strategies [31,32]. In the management of moderate to severe acute postoperative pain, opioids are the most efficacious agents and an important part of pharmacotherapy [3,5,33], and use of non-opioids alone as a part of multimodal regimen is usually insufficient [33]. Conventional opioids have a narrow therapeutic index, potentially fatal concentration-dependent toxicity, and wide interindividual variability, making them relatively challenging to use when balancing the analgesic efficacy to the serious AEs associated with these agents [4,34]. Thus there is a need for defining regimens using ‘optimal analgesia’ and tailoring to specific needs of individual patients [33]. Oliceridine is an IV opioid agonist that is relatively selective to the µ-opioid receptor. Oliceridine is selective to the G-protein signaling pathway (providing analgesia) with less recruitment of β-arrestin (responsible for the AEs) [12]. Nonclinical studies show that oliceridine is potently analgesic while causing less GI dysfunction and respiratory depression than morphine at equianalgesic doses [12]. Although in the placebo and morphine controlled clinical studies, no statistically significant differences were seen between oliceridine demand doses and morphine in the respiratory safety endpoint, there were numerical differences in the respiratory safety events and a trend toward improved safety with oliceridine [9,10]. Likewise, the frequency of dosing interruption due to a respiratory safety event as well as the cumulative duration of dosing interruptions were numerically lower with oliceridine than with morphine [35]. The incidence of nausea, in particular vomiting, was lower for oliceridine regimens than morphine in the controlled clinical studies. Furthermore, an exploratory analysis that evaluated complete GI response, defined as ‘no vomiting and no use of rescue antiemetics,’ showed that at equianalgesic conditions, i.e. at the same levels of SPID, the odds of achieving complete GI response were 2–3 times higher with oliceridine (combined demand doses of 0.1, 0.35, or 0.5 mg) than with morphine (1 mg) [36].

The strengths of this health economic analysis include the fact that it is based on direct observations of the head-to-head comparison of oliceridine and morphine in two large, Phase 3 randomized, placebo-controlled clinical trials. These data were strengthened by an accompanying large, multisite open-label safety study examining the tolerability of oliceridine in a real-world patient sample. The base model was also shown to be robust to sensitivity analyses.

4.1. Limitations

Decision analysis models are simplifications of the many factors that affect clinical outcomes and cost under real practice conditions. However, our model was designed for maximal transparency in its structure, was populated with the most conservative parameters, and our report clearly describes the origin of the data and the assumptions imbedded in the model. Thus, we are confident that the estimates produced are as conservative and unbiased as it is possible to achieve with the available data.

Among other limitations, the studies utilized in the models compared oliceridine only to morphine and not to any other opioids. In addition, the AEs were limited to those observed with study medications and do not delineate events related to procedural complications. Further, in the model, we focused only on three ORAEs that are known to contribute to increased cost (respiratory depression, vomiting, and sedation), and not all ORAEs observed in the clinical studies. Although constipation is a commonly occurring ORAE, it has been more frequently associated with longer-term use of opioids. Its incidence in our pivotal trials was low and therefore considered to be less of a cost driver in our model for use in a postoperative setting. Of note, we used the 24-hour time horizon for our model because the greatest contribution of the marginal costs and benefits of postsurgical pain management are expected to materialize within this time frame. However, as noted in our previous publication of the base model, this short time perspective may tend to underestimate the savings associated with very complex procedures for patients with numerous comorbid conditions, and those with longer postoperative recuperation paths [8]. Future research and economic modeling should include other ORAEs, such as postoperative ileus and the use of concurrent medications to treat this AE.

Lastly, oliceridine IV is approved for use only in the United States (US) and this cost benefit/budget impact analysis was based on the US Health care system and is relevant for use only in the US.

4.2. Expert Opinion

Pain management post-surgery is changing rapidly as a result of insights gained from the opioid epidemic and detailed analysis of patient LOS. The value of new therapeutic modalities is important from the perspecctive of the payer. In the case of an institution, such as a hospital, the cost of a medication to treat any condition may be lower than the cost of treatment of AEs and subsequent increase in LOS [37]. New pain medication with fewer ORAEs may have important roles in the evolving pain management protocols both because of their efficacy against pain, and because medications with fewer side effects may facilitate faster mobilization, earlier feeding, and more rapid discharge to home. Economic modeling studies can provide important and useful information to ensure that decision makers and payers consider the value of new therapeutic modalities in terms of benefits, direct protocol costs, and savings associated with decreased AEs and earlier discharges. Therapeutic modalities may affect patient health outcomes after discharge from the facilities. Further research is needed to confirm the nature and extent of these effects. Negative outcomes can affect the institution’s reimbursement and quality ratings from government agencies for patients participating in United States Medicaid and Medicare programs. Approaching the evaluations of a treatment modality’s value in a holistic manner may provide for better patient outcomes and lower total costs of therapy.

5. Conclusion

In patients at high risk of developing opioid-related adverse outcomes, oliceridine has a favorable overall expected impact on the total cost of postoperative care compared to the use of the conventional opioid morphine, despite a modest increase in pharmacy costs.

Author contributions

K N Simpson developed the model described in this manuscript. M A Demitrack drafted the manuscript. All other authors were involved in revising it critically for intellectual content. All authors approved the final draft that was submitted. All authors had access to the data included in the economic model.

Declaration of interest

K N Simpson is a consultant for Trevena, Inc. M J Fossler, L Wase, M A Demitrack and T Wandstrat declare employment at Trevena, Inc. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Ethical conduct of research

No institutional review was required as the data included in the model described here was of previously published, de-identified data. The studies adhered to the principles outlined in the Declaration of Helsinki.

Further information

Some of the data discussed in this paper were presented at the Virtual ISPOR 2021 (May 17-20, 2021) and AMCP 2021 Virtual (April 12-16, 2021) meetings.

Reviewer disclosures

One peer reviewer acted in a speaker’s bureau for Astra Zeneca/Daiichi - breast cancer series. Peer reviewers on this manuscript have no other relevant financial relationships or otherwise to disclose.

Acknowledgments

The authors would like to thank K Sridharan, MS, employee at Trevena, Inc. for providing editorial assistance during development of the manuscript. S Parthasarathy of Innovation Communications Group helped with the logistics of submission to the journal, funding for which was provided by Trevena, Inc.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This research project was funded by Trevena, Inc.