Outcomes-based managed entry agreements (MEAs) can enable patient access to promising high cost therapies when there is uncertainty in the clinical data
In 2016, The National Institute for Health and Care Excellence (NICE) undertook a health technology assessment (HTA) exercise for a hypothetical CAR T-cell therapy for late-stage ALL, and demonstrated how an outcomes-based, staged payment approach (such as ‘lifetime leasing’ whereby payments would be made in instalments over the period of time that therapy benefits are sustained) can reduce the uncertainty in the cost-effectiveness results, and thereby improve its chances of being recommended for reimbursement in the National Health Service (NHS). Such MEAs are a much-debated topic among scholars and healthcare stakeholders, as they can be particularly useful in situations where a new and therapy, which has the potential to deliver long-term patient benefits, is launching with a less mature data set.
Despite the potential of outcomes-based reimbursement schemes to reduce decision-uncertainty, their use in practice is commonly hampered by concerns over the administrative cost of implementation. While these concerns are well-founded, they are rarely quantified, and a clearly described methodology for detailing the administrative cost of implementation is lacking.
Building on NICE’s HTA exercise in ALL described above, we sought to investigate this matter further, and the our research objectives were therefore to
- Provide a methodological framework for exploring the costs associated with setting up and implementing an outcomes-based MEA
- Quantify the administrative burden of introducing an outcomes-based MEA for the hypothetical CAR T-cell therapy for late-stage ALL, using a staged payment approach over a 10-year time horizon
This research is unique and a first of its kind in terms of quantifying the administrative burden of an outcomes-based MEA. The outputs are intended to inform healthcare system stakeholders and pharmaceutical manufacturers about the administrative burden associated with implementing an MEA for an advanced therapy medicinal product (ATMP) in ALL specifically, as well as providing a methodological approach to assess the incremental burden of activity and cost for introducing a performance-based MEA in other therapy areas.
The methodological framework and study design was developed with input from a Project Advisory Group (PAG) of NHS stakeholders. The PAG consisted of:
- Senior NHS pharmacy representatives
- Clinical oncology representatives
- Representatives from NICE
Input data was gathered from representatives from key NHS trusts relevant to the treatment of ALL. Research participants included chief pharmacists, haematology pharmacists and oncology pharmacists who were recruited from five NHS trusts that met one of the following criteria:
- Accredited for stem cell transplantation through the Joint Accreditation Committee-ISCT & EBMT (JACIE), or
- Actively treating paediatric ALL, or
- A centre of excellence in oncology
Respondents were asked to detail the task and activity levels for administrative activities related to three therapeutic scenarios, and across four distinct implementation phases, as shown in Table 1 below.
Although both CAR T-cell therapy scenarios (with and without MEA) relate to the same hypothetical therapy, the former is associated with a less mature data set, which is the driver of the implementation of the performance-based MEA. In the scenario where the CAR T-cell is introduced without an MEA, the therapy is assumed to have a more mature data set at launch that enables reimbursement through a one-off payment at the time of administration. The time horizon of the analysis is 10 years, and 50 new patients were assumed to be treated each year in each therapeutic scenario.
In the case of the therapy with MEA, participants were asked to detail also the expected capital investment needed for the operation of the MEA. The cost of the therapies and associated patient management were excluded from the analysis, as the focus is exclusively on administrative burden.
The research participants completed Excel sheets with qualitative descriptions of tasks and quantitative data (time and cost) for each phase. Following completion of research questionnaires, a semi-structured follow-up telephone interview was performed to explore and clarify the data, before all responses were entered into a central Excel spreadsheet, and subjected to a series of quality assurance tests, including:
- Validation against original entry
- Identification of:
- potential duplicated tasks
- tasks with unknown detail i.e. job band entries missing
- Calculation of a minimum, maximum and variance value
- Variance analysis to check for erroneous entries
Clarification of erroneous entries with the participants was undertaken (where needed), before a clean database of raw data was finalised. Data was then categorised by task, personnel time required to complete the task, job band, and capital investment, before grouping by hospital departments i.e. Pharmacy, Clinical, Finance, HR and Training, Information Technology (IT) and Other. Participants provided their respective job bands, and the time required to complete tasks was costed using the mid-point salary detailed in the latest NHS Employers Agenda for Change Pay Scales.
The results were reported as cost (£s) and time; per implementation phase; total and incremental; as well as direct1 and indirect2 (as validated through the PAG).
Quantifying the administrative burden of an outcomes-based managed entry agreement
A key finding became apparent when respondents were asked to identify and quantify any significant one-off capital investment associated with implementing the MEA. Respondents believed that the data collection infrastructure used for oncology in England (the Systemic Anti-Cancer Treatment [SACT] database) would be sufficient accommodate the MEAs; for this reason, they considered the capital and infrastructure investments needed in the context of the oncology MEA exemplar in England to be negligible.
The estimated total 10-year costs to an English NHS Trust (50 new patients treated per annum), is presented in Table 1 below.
* Monitoring visits per year
** UKALL R3, UKALL 2011 protocol
The incremental cost of implementing an MEA for the hypothetical CAR T-cell therapy (treating 50 new patients per annum over 10 years) was estimated at £871,707 and £669,671 as compared to CAR T-cell therapy without MEA and the SoC respectively (as shown in Figure 1 below)
The total number of personnel working days required for the different therapeutic scenarios at an English NHS hospital trust (treating 50 new patients per annum over 10 years), is estimated at:
- 1,444 working days for hypothetical CAR T-cell therapy without an MEA
- 7,845 working days for hypothetical CAR T-cell therapy with an MEA
- 2,799 working days for existing SoC
This translates to an incremental cost of implementing an MEA for the hypothetical CAR T-cell therapy as detailed in Figure 2 below.
We also detailed the incremental administrative burden per patient of introducing the CAR T-cell therapy with an MEA, as shown in Table 3.
It is worth noting that the SoC represents a considerable baseline administrative burden, which stems from the repeated activity for the payment of numerous chemotherapy administrations and the associated requirement for oncology treatments to enter data into the SACT database, and the use of the BlueTeq interface for Payment by Results excluded products. This baseline administrative burden for the SoC was quantified for the first time in our research, specifically for ALL.
CAR T-cell therapy without MEA is less resource-intensive than the SOC because it only requires an upfront, one-off payment upon a single administration. The CAR T-cell therapy with an MEA presents the greatest burden of the three options analysed, and a key driver for this is the increased frequency of Minimal Residual Disease (MRD) blood testing in year one (due to greater uncertainty around the safety and efficacy data and in order to inform the performance-based reimbursement mechanism), but also greater patient numbers over time (as compared to the SoC) due to improved survival. The increase in resource costs is mainly attributable to the increase in pharmacy personnel time and higher banding of the personnel involved. The indirect costs, e.g. set up costs and infrastructure that would be required for the system to run, are negligible (less than 1%), as a data collection infrastructure is already in place for oncology therapies (through SACT and BlueTeq). From an NHS perspective, this also means that the incremental cost of adopting the CAR T-cell therapy with an MEA at multiple hospitals would be relatively low.
It should be noted that the costs communicated in this study are based on treating 50 patients per annum and over a 10-year horizon and leveraging the existing oncology data infrastructure for enabling the operation of the MEA. However, if a similar MEA arrangement was to be implemented for a larger therapy area in terms of target patient population, then the total administrative burden and associated cost would increase proportionately to the number of patients treated. Furthermore, if the target therapy area lacks an existing data collection infrastructure, the total MEA implementation burden would further increase due to the capital investment required to create the appropriate infrastructure for the operation of the MEA.
While the total costs are considerable, the incremental cost per patient of adopting the hypothetical CAR T-cell therapy with an MEA equates to an annual cost per patient of £240. For products with a list price into the hundreds of thousands of pounds (as illustrated by the list price of Kymriah in paediatric ALL at £282,000 per patient), this might be considered a viable “annual insurance premium” to underwrite the potential reimbursement should the drug fail.
Our research has provided for the first time a detailed estimate of the administrative resources required for reimbursement purposes for the existing standard of care in ALL at the NHS trust level in England, as well as the resource implications of adopting a CAR T-cell therapy with or without an MEA. We have also developed a methodological framework that can be used to undertake similar analyses in other therapy areas where MEAs are considered as a means to reduce the decision uncertainty in HTAs and improve the chances of being reimbursed.