2 Approach

On this page: 2.1 The options being considered by the Medicines Scheduling Delegate | 2.2 The regulatory model | 2.3 The health economic model | 2.4 Conclusion

2.1 The options being considered by the Medicines Scheduling Delegate

Table 1 details the regulatory options (or combinations of regulatory options) being considered by the Medicines Scheduling Delegate.

Source: TGA RFI documentation (TGA2016-325)

As discussed above, it was confirmed at the planning workshop between KPMG and relevant TGA internal stakeholders that, while these implementation options are separated out into individual scheduling changes for clarity, in practice, they are necessarily grouped. For example, both Options 4 and 6 reflect the Interim Decision. The following scenarios were agreed in the workshop to reflect the most likely practical groupings and were used to inform subsequent analysis.

Source: TGA and KPMG workshop 4 August 2016

2.2 The regulatory model

Overview

The development of the regulatory model was undertaken in accordance with OBPR Guidance Note: 'Regulatory Burden Measurement Framework' dated February 2016. In accordance with this framework, regulatory costs were estimated for administrative compliance costs and substantive compliance costs only. The labour cost formula (price x quantity) (or in its more expanded version: (Time required × Labour cost) × (Times performed × Number of businesses or community organisations × Number of staff)) was used to determine these costs. It is important to note the interrelationship between the inputs in this formula as this explains the variation in the calculated regulatory costs for various compliance activities.

Delay costs (application and approval delays) were determined to be out of scope as it was envisaged that any changes to scheduling for codeine products would incorporate sufficient time for industry to respond with only minimal stock-outs (which occur when existing pharmaceutical stock is withdrawn or exhausted prior to new stock being available) being experienced.

As detailed earlier in this report, a workshop was held with TGA staff to identify the key regulatory compliance processes that would arise from the implementation of each option. Component elements of each of the identified regulatory processes were then broken down into their respective time, cost and frequency components and the value of the respective inputs sourced from previous RISs prepared by TGA, as well as information provided via consultations with industry and peak bodies. As agreed, cost models were developed in Microsoft Excel with the summary for each option also presented in the standard Regulatory Burden Measure (RBM) format.

Consultations

The development of the regulatory cost estimates was informed by targeted consultation with sponsors who currently produce codeine-based products in the OTC market. The target sponsors were Sandoz Pty Ltd, Sanofi-Aventis Australia Pty Ltd, GlaxoSmithKline Consumer Healthcare Pty Ltd, Soul Pattinson Manufacturing Pty Ltd and Johnson & Johnson Pacific. These companies occupy both distinct and overlapping segments of the OTC and prescription market and were able to provide a range of perspectives given the different incentives and risks that are intrinsic to their respective business models.

Sponsors were provided with a list of questions in Attachment G which were subsequently used to structure conversations in meetings and focus on issues directly related to the modelling and implementation implication of different options.

Broadly, the interviews were structured around six topics outlined in the questionnaire:

• product strategy;
• market response;
• labelling;
• packaging;
• updated listing and regulatory approvals; and
• implementation.

A high level summary of industry responses are provided here without direct attribution to specific stakeholders. This is intended to provide an overall picture of the feedback and the key themes that emerged from the meetings and informed the modelling.

Topic 1 - Product Strategy

Sponsors were asked about how they would respond to up-scheduling decisions and what factors would be considered in determining their product strategy. There was a high level of concern by S2 and S3 sponsors about the impact of up-scheduling on their business. Sponsors identified a number of issues that undermine the commercial viability of up-scheduled codeine products. The issues were fundamentally connected to the different distribution and market access models associated with S3 and S4 arrangements, and uncertainty about the level of demand for lower dosage codeine products given the current prescribing habits of GPs.

Key points were:

• S2 sponsors are unlikely to migrate products to S4. It is likely that most S2 sponsors would migrate products to S3 but would materially rationalise their product portfolio and range with generic brands to be most impacted by the reduced range behind the pharmacists counter.
• S3 sponsors would evaluate the commercial viability of moving products to S4, however this would be largely contingent on their expectations about demand and confidence that GPs would change their prescribing habits to account for different dosage options.
• Sponsors with branded products highlighted concerns about the impact of discontinuing products on brand equity and the regulatory barriers to redeploying or reformulating well known and trusted brands which are a source of value for these companies.

Topic 2 - Market Response

Sponsors were asked to provide views on what impact different options would have on the behavior of customers (across different segments) and the level of demand and substitution they would expect to see in the market.

Key themes were as follows:

• The introduction of warning labels and reduced pack sizes would reduce overall revenue slightly, however, overall demand for codeine would largely remain.
• The up-scheduling of S2 to S3 would reduce demand but there would still be a market for codeine-based cough and cold products. However consumers would be presented with less choice and range as products move behind the counter. This would necessitate some degree of product rationalisation.
• The up-scheduling of S2 to S4 would effectively see these product lines discontinued.
• The up-scheduling of S3 to S4 would reduce overall demand for medium dosage codeine products, but that a sizable segment of these existing customers would continue to seek out codeine products and visit a GP to obtain a prescription. Sponsors all considered it was likely that some consumers would visit their GP and receive access to higher dosage products with larger pack sizes which could lead to perverse outcomes (note this factor is specifically addressed in the economic model).
• The S3 market is essentially entirely made up of consumers - hospitals and other institutions do not bulk purchase OTC codeine products (tending to use paracetamol and/or ibuprofen or move to higher strength opioids).

Topic 3 Reduced Pack Size

Sponsors were asked whether they have existing products or manufacturing arrangements that would readily accommodate the change to a 3-day pack (outer pack and the inner blister packs). There was a mixed response regarding this question, with about half of the sponsors indicating they already produced a 3-day pack or had production lines that could be used to do so, and thus they could accommodate this at essentially no cost. Others would incur costs for retooling machinery to modify the depth of the outer pack or the length of the inner blister pack.

The sponsors interviewed stated that costs appeared to depend on whether the manufacturing was done in Australia or overseas. Retooling in Australia was more expensive (and potentially cost prohibitive) and ranged between $30,000 and $150,000. Retooling overseas is cheaper and ranges from between $10,000 and $30,000. The sponsors also expressed an opinion that implementation in local facilities could be executed more quickly (6 months) whilst changes to overseas facilities would take longer (12 months).

Topic 4 New Warning Labels

Sponsors were asked to describe the steps involved in adding new labels, and the costs associated with these steps. Broadly, the steps identified were the development of artwork and design, internal review, quality assurance and implementation. The range of costs provided by sponsors was between $2,000 and $6,500.

Sponsors noted they would look for opportunities to roll label updates into others which were already in the pipeline. Updates would typically occur once every 3 years.

Implementation timeframes were between 6 and 12 months. Similar to packaging, overseas production arrangements required longer lead-times as there was less flexibility in scheduling updates into manufacturing change windows.

Topic 5 Updated listings

Sponsors were asked to comment on time or cost of regulatory forms and other compliance processes connected to the various options. Key points were

• C1/C2 forms were considered relatively straight forward. With sponsors indicating time required to complete, undertake internal review and submit forms being between 4 - 10 hours of effort.
• Sponsors indicated updating Product Information (PI)/Consumer Medicine Information (CMI) documents would also be straightforward. In the event a new PI/CMI had to be created (such as S2 up-scheduling to S3) sponsors would not seek to create one from scratch but leverage a model PI already being used in that schedule.
• Sponsors did not anticipate up-scheduling to S4 (if they were currently in S2 or S3) would cause any difficulties with respect to GMP conformity. The sponsors consulted were all confident their facilities were GMP compliant and also noted those facilities were already manufacturing other S4 products.
• In their responses, sponsors indicated that based on precedent, they would expect the TGA to grandfather S2 and S3 products into S4. They cited the standard registration process for a prescription medicine as a material cost and time delay that could require up to 24 months subject to the scope of the application requirements.

Topic 6 Implementation timeframes

Implementation timeframes were discussed with sponsors throughout each of the topics to understand the minimum and ideal timeframes connected with different change processes. The purpose of this topic was to understand any other implementation considerations pertinent to industry.

Several sponsors expressed concerns about the lack of certainty concerning the implementation timeline and arrangements that would accompany a decision to up-schedule. They noted the critical importance of implementation timeframes in enabling business to reposition themselves in the event of an adverse outcome. They also noted that a short implementation timeframe would potentially increase costs and also make it difficult to reposition themselves in the market without significant losses in revenue. In this respect, sponsors emphasized the engagement of the TGA would be critical towards assisting their planning.

Broadly, sponsors indicated a reasonable end-to-end implementation timeframe would at a minimum be between 18 to 24 months.

Sponsors noted their concerns that an 18 to 24 month timeframe may be perceived as being at odds with the safety/risk rationale of the interim decision and that the TGA would be presented with a moral dilemma in balancing the two.

Other key themes were as follows:

• Pharmacies generally hold between 1 to 2 month(s) worth of stock depending on their location.
• Most manufacturers do not hold large amounts of produced stock but make to order. However they do make bulk purchases of components and materials and these can take between 4 and 9 months to turn over.
• Shelf life of codeine products is 24 months. Sponsors were concerned a short implementation timeframe may require some residual products to be recalled from shelves which would be a costly exercise and involve reverse logistics and associated costs.
• The minimum timeframes to comply with an up-scheduling decision appears to be around 9 months. However sponsors noted this assumes that there is no business case development or evaluation of commercial viability to up-schedule which they considered to be unreasonable. They further expressed a view that a longer timeframe is needed to enable this to be undertaken in an orderly way.
• Sponsors indicated time is also needed for GPs to be educated about the changes (in the event of an up-scheduling) to ensure their prescribing habits adapt to the new situation, and that medium dosage codeine products (at 12.5mg) are prescribed when appropriate. Sponsors also sought clarity as to whether Government or industry would be expected to fund the costs of GP education.

2.3 The health economic model

Data limitations and key assumptions

The health economic model sought to project the changes to a range of costs to the Commonwealth and individual consumers, deaths prevented and changes in quality of life as a consequence of all three scenarios; only Scenario 4 was expected to have quality of life benefits. Most of the parameters that could influence the projected results were identified during consultation and review of available materials. The model sought to include as many of these parameters as possible. Where input data was available and/or the parameter was assessed as potentially influencing the results, it was included in the model. There were a number of key assumptions regarding both baseline parameters (e.g. the proportion of consumers who are dependent on low dose codeine medicines) and projection parameters (the proportion of dependent users whose health outcomes will improve)) that have limited supporting evidence. There were many other parameters for which minimal data and information was available. By using the most appropriate model structure, conservative assumptions and sensitivity analysis it was possible to generate robust results relating to the direction of any net effect of the projected costs and benefits of each scenario.

The only OTC low dose codeine medicines specific data available to use as an economic model input was IMS data (volume data) for sales of codeine-based products (24 months to September 2013). This data needed to be extrapolated for the base year of sales (2017). Some externally sourced inputs (such as categorisation and fee structure for MBS GP consultations and the discount rate) were not specific to the options being modelled but rather relate to the broader health system or to specific requirements of this regulatory assessment process. Initial assumptions were formed for the remaining inputs and then, in the absence of data or relevant literature, they were 'sense-checked' in interviews with peak bodies (i.e. expert opinion was sought). The key assumptions underpinning the economic analysis are:

• 99% of people who used low dose codeine medicines at least once are using it for therapeutic purposes (the remaining 1% is for non-therapeutic use).
  • Of all users, 80% are using it therapeutically for acute conditions.
  • Of the 19% using it therapeutically for chronic conditions, 20% are dependent on low dose codeine medicines.
  • In the absence of reliable data to inform these parameters, these reasonable values were selected and tested in the sensitivity analyses.
• If S2 low dose codeine medicines are up-scheduled to S4 then the prescribing behaviour of GPs will be to provide zero repeats as appropriate for cough and cold medicines. Only 20% of consumers will continue to use this option and for only 30% of these patients will the visit they make to the GP be in addition to visits they would have made anyway in the absence of the regulatory change. Some consumers will switch to cough and cold medicines without codeine.
• If S3 low dose codeine medicines are up-scheduled to S4 then the model assumes the prescribing behaviour of GPs will be to provide up to 5 repeats if they assess that it is appropriate for this patient to continue with this pharmacotherapy, given the patient's symptomology and medical history. Not all patients are expected to continue and this is accommodated in the model.
• Of current therapeutic acute users of S3 low dose codeine medicines, 25% are assumed in the base case to continue to use low dose codeine medicines. In the absence of reliable data to inform these parameters, this reasonable value was selected and tested in the sensitivity analyses. Some will switch to OTC ibuprofen and/or paracetamol and others to cough and cold medicines without codeine.
• Chronic therapeutic users are assumed in the base case projections to follow one of a number of potential pathways, only one of which is ongoing use of low dose codeine medicines. The potential pathways were identified through stakeholder consultations and a review of the available literature. In the absence of reliable data to inform these proportions of consumers who would follow potential, reasonable 'base case' assumptions were made in the model and then tested in the sensitivity analyses.
• The projected number of prevented deaths per year from up-scheduling S2/S3 low dose codeine medicines to S4 is 5 per year. This is a conservative estimate based on the cited 229 codeine related deaths in which OTC codeine products were recorded over the 14 year period of the study.^[18] These deaths are not necessarily entirely attributable to OTC codeine medicine use and hence a very conservative estimate of the deaths prevented was used in the base case assumptions of the model.
• Health benefits as shown in the model will only be realised from improved therapeutic pathways taken by patients who would otherwise be chronic therapeutic users of S3 low dose codeine medicines. For this improved therapeutic pathway to be realized the key enabler was a visit to a GP, which will not be likely to occur under options that keep low dose codeine medicines as an OTC medicine, regardless of pack size or whether up-scheduled from S2 to S3. The potential pathways were identified through stakeholder consultations and a review of the available literature. In the absence of reliable data to inform these proportions of consumers who would follow potential, reasonable 'base case' assumptions were made in the model and then tested in the sensitivity analyses.
• Most current higher dose codeine medicines are limited in the number of repeats that can be provided, often to no repeats if this prescription is dispensed under PBS. This limit does not apply to current users of high dose codeine medicines if they use a private rather than PBS script. Stakeholders indicated that many current users of high dose prescription codeine medicines use private scripts and have up to 5 repeats. The assumption used in this model is that a patient will be provided up to 5 repeats of low dose codeine medicines, if the prescriber assesses this is appropriate. This assumption is considered reasonable for the following reasons.
  • Stakeholders indicated that pharmaceutical companies are unlikely to seek PBAC approval for PBS listing of low dose codeine medicines; the cost of listing could be high compared to potential impact on the volume of sales.
  • If they were to be listed, the option for patent to use private scripts with up to 5 repeats would remain available if the prescriber assessed that this was an appropriate number of repeats.
  • There would be no incentive for a general beneficiary (non-concessional) patient to seek a PBS script rather than a private script because the price of low dose codeine medicines is currently below the general beneficiary co-payment.
• Concessional patients are already purchasing OTC low dose codeine medicines at a price that is only a few dollars above the concessional copayment. If a concessional patient is currently using more than two packs a year then there is little incentive to save a few dollars on each script if it requires one GP consultation for every script.
• Paracetamol and/or ibuprofen medicines as alternative to low dose codeine medicines are cheaper than existing S2 and S3 low dose codeine medicines and are also available at supermarkets (which introduces further price competition).

The baseline case

The economic modelling for all options uses a baseline case (current use) that was developed for five groups of patients. Characteristics of these patients groups, including their annual pattern of codeine use (low/high dose, packs and expenditure) are detailed in Annex E, which provides a discussion of the economic model. A key distinction is that all use of Schedule 2 products is assumed to be for acute use, whereas Schedule 3 product use is spread across all five patient groups.

How the economic model works

The economic model works in five main steps, as follows:

Step 1: Simulation. The simulation is based on holding constant the total amount of codeine currently used by the five groups of consumers (though possibly in different pack sizes) and then adjusting the following variables to reflect the post-regulatory change environment:

• packs of low dose codeine medicines;
• out of pocket cost;
• pharmacy purchases; and
• GP consultations.

Step 2: Plausibility analysis. The next step assesses for each consumer group the plausibility that this change in resource use will occur (holding the consumption of low dose codeine medicines constant) relative to alternative pathways and models accordingly. Each of these alternative pathways have different uses of resources and health outcomes associated with them. Scenario 4 does not add pathways; it removes one and hence changes which of the existing pathways that patients will take. These alternative pathways will often incorporate discussions with both GPs and pharmacists, and include options such as:

• use of paracetamol and/or ibuprofen without codeine;
• non-pharmacotherapy;
• prescribed low or high dose codeine;
• alternative prescribed pharmacotherapy;
• GP or self-referrals to allied health providers; and
• GP referrals to specialist pain clinics.

Step 3. Allocation of population across pathways. This step entails identifying the proportion of consumers in each group (cohort) that will pursue each pathway. This proportion varies across groups and also depends on factors such as the capacity for the existing pain clinics to see additional patients, including those who are referred by their GP and are eligible for a Medicare rebate.

Step 4. Determination of resource use and health outcomes. This step assigns changes in resource use to each cohort, where these changes in resource use and health outcomes are a consequence of changes in behaviour.

Step 5. Project changes over time. The final step projects these changes over the specified ten-year period, taking into account changes in cohorts, the ongoing needs for additional services and the longer term impact on health outcomes.

The benefits: their sources and drivers

The benefits are of three types: (1) deaths prevented; (2) health gains (Quality of Life Year - QALY- gain); and (3) financial savings. Deaths are prevented in option 6 and are a consequence of the removal of access to OTC low dose codeine medicines.^[20] Financial savings are a benefit in options 4 and 6, where patients substitute their use of low dose codeine medicines with OTC painkillers such as ibuprofen and paracetamol, which are cheaper.

The net health gain requires further explanation. There are several options (of the five specified options to be modelled) where there are no realised health benefits because either (1) there is no change in behaviour or (2) the consumer switches to an alternative therapy that brings the same level of pain relief and might be available at the same or lower cost. For many consumers, clinical trials have demonstrated that they will experience no loss in pain relief if they switch from low dose codeine medicines with paracetamol and/or ibuprofen to either of these two medicines alone.23 However, stakeholders stated that some patients do benefit from low dose codeine medicines compared to paracetamol or ibuprofen alone, although no references were provided. Stakeholders also stated that while some patients benefit from paracetamol and ibuprofen combination medicines relative to either product alone, this combination product might be contraindicated for use in some patients, for example those with an active gastrointestinal bleed^[21]. A small group of patients were assumed to have a loss in pain relief (QALY decrement) which partly offset the QALY gain for patients who participate in improved therapeutic pathways as a consequence of up-scheduling from S3 to S4. While this up-scheduling is expected to result in an increase in the use of paracetamol and/or ibuprofen medicines, it is not expected to result in an increase in the deaths associated with their use compared to the deaths that would otherwise have occurred in the absence of Scenario 4 being enacted. The reason is that consumers who would otherwise have a codeine dependency and used above the maximum recommended daily dose of paracetamol and/or ibuprofen (due to their presence in combination drugs with codeine), are now instead using these medicines for pain relief only and are not consuming above the maximum recommend daily dose.

In summary, the potential health impacts are of the following kinds:

• a reduced level for pain relief for some patients who substitute low dose codeine medicines with OTC paracetamol or/and ibuprofen;
• improved quality of life if the patient would benefit more from other pain treatment options that would not otherwise have been used by these patients and they commence using these options;
• prevention of adverse events related to unintentional overdose of paracetamol and/or ibuprofen in combination products also containing codeine; and
• reduced dependence and risk of dependency.

Only the first two of these potential impacts were quantified in the model. The last two are not quantified in the model as there was insufficient information to form initial assumptions.

The costs: their sources and drivers

The main additional costs relate to:

• net out-of-pocket costs to consumer;
• additional costs to MBS due to additional GP and pain consultations; and
• additional costs to the PBS due to additional scripts for PBS listed pain medications.

The additional costs to the MBS are the primary driver of additional costs to government.

Model uncertainty

Modelling has two main types of uncertainty, those associated with inputs (input uncertainty) and structure (systematic uncertainty). Each uncertainty is described below.

Input uncertainty

There is a paucity of data in relation to many of the inputs needed for this model, particularly in relation to the projected health benefits. The main drivers of input uncertainty related to the benefits in this model are:

• the proportion of consumers that could potentially benefit from changing their pathway;
• the proportion of consumers who will change their pathway in an optimal way;
• the additional health benefits that will be achieved if consumers with the potential to benefit, in fact change their pathway and receive improved treatment; and
• the time period that the benefits are maintained without the need for additional investments in treatment and therapy.

For a discussion of these inputs, as well as the methods that were used to resolve the paucity of data, please see Annex E. The broad options for acute and chronic users of S3 under option 6 are illustrated in Figure 1. Acute users are the only group who are expected to have some users who continue to use low dose codeine medicines at the same rate over the ten years of the model (Outcome 1.1). This assumption is based on discussions with stakeholders, some of whom indicated that it was unlikely that GPs would continue to prescribe low dose codeine medicines for chronic users and instead prescribe higher dose codeine or, more likely, a range of other therapeutic options, including those that arise from diagnoses that would not have been made had the customer continue do use OTC low dose codeine medicines (Outcome 2.2).

Figure 1. Option 6, S3→S4, options for acute and chronic users of S3

As a general principle, the economic model sought to take conservative approaches to the estimation of health gains, for two reasons.

The first reason for taking a conservative approach was that the health gains arising from the improved therapeutic pathways taken by patients who would otherwise be chronic users of low dose codeine medicines were the primary driver of benefits in the model but also the most contested benefit. There was wide disagreement across the range of stakeholders as to the proportion of current chronic or acute users who would benefit from using different therapeutic pathways, and the extent of this benefit. Stakeholders who were supportive of the up-scheduling highlighted the benefits in terms of patients who would have an improved diagnosis of chronic or acute pain and also a shift to high dose codeine to reduce the risks related to paracetamol and/or ibuprofen use. These stakeholders also referred to the evidence from the Cochrane^[22] systematic reviews regarding the evidence of limited effectiveness of low doses of codeine compared to paracetamol and/or ibuprofen alone. However, no stakeholder provided supporting evidence or data, other than the Cochrane reviews, and instead gave specific examples. Stakeholders in favour gave specific examples of patients who was treated by anti-migraine medications or saw their GP and then was referred for non-pharmacotherapy options (hip replacement, weight management clinic). Stakeholders who were not supportive of the up-scheduling gave examples of patients who could not tolerate ibuprofen and would now have no pharmacotherapy options available to them.

The second reason for taking a conservative approach was that the protocol^[23] to be applied to the valuation of a statistical life year is the use of an unconstrained willingness to pay $182,000. This statistical life year is intended to be a year at full health and therefore is also the value of a Quality Adjusted Life Year (QALY). The unconstrained willingness to pay approach is the preferred option under this protocol; however, it results in a much higher value being placed on a QALY compared to that used in health economics and health technology assessment in Australia and internationally.^[24]

Avoided deaths were an additional benefit. It was not possible to estimate deaths that could be prevented as a consequence of Option 6, partly because the deaths attributable specifically to low dose codeine could not be estimated. When deaths involving low dose codeine medicine abuse occurred, it was likely that there were multiple influencing factors and changed access to low dose codeine would not necessarily prevent these deaths.^[25] The base case assumed five deaths a year would be prevented. Financial saving to patients due to less expenditure on low dose codeine medicines in options 4 and 6 was also included as a benefit.

This approach of taking a conservative estimate of the benefit generates confidence that the true net benefit is unlikely to be lower than that generated by the model. However, the base case of this model will be more likely to underestimate the true net benefit compared to other approaches that use a larger QALY gain for some patients. In the context of this decision, where only the up-scheduling of S2 and S3 low dose codeine medicines to S4 results in health benefits, this approach will not impact on the ranking of options. Given that the decision rule is to prefer the option with the highest net benefit, and options 4 and 6, which are not mutually exclusive, are the only options that result in a net benefit (from the economic model), then having strong confidence that the net benefit is greater than zero is a more appropriate strategy than having a base case net benefit which might be closer to the true net benefit but includes substantive uncertainty. In simple terms, the lower net benefit results in the same ranking of options, but there is less controversy in the assumptions underlying the net benefit.

Systematic uncertainty

Systematic uncertainty can lead to the wrong model structure being adopted and the results might be incorrect (biased), even if all the inputs are clearly correct. The KPMG model was designed to reduce the systematic bias that is inherent in some existing economic models on this issue. The main method to reduce systematic bias was to use five groups of consumers rather than base the model entirely on the 'average' consumer. Refer to Annex E for a discussion of how this reduction in systematic bias was achieved, despite the uncertainty in the inputs.

2.4 Conclusion

As discussed, although annexes C and D present the calculation of the regulatory cost structured along the specified six options for the purpose of inclusion in the RIS, there is a logical grouping of options. Essentially, modification of the regulatory control mechanisms for both S2 and S3 codeine medicines is required simultaneously, otherwise the desired outcomes would largely be negated by consumers shifting from either S2 to S3 (or vice versa) if a single regulatory option was enacted. Regulatory costs projected over ten years are summed (without discounting) and then summarised and reported as an average annual impact (total divided by ten). In contrast, economic costs for a cost-benefit analysis have their impact over the life of the proposed regulation (set at 10 years in this case) monetised and discounted at 7% per annum to obtain present value of the ten years of costs. Noting these differences in calculation methods, Table 3 sums the results of the regulatory costs (the undiscounted ten years summed) and economic modelling (ten years discounted to obtain a predicted net benefit). As discussed in further detail throughout the annexes, only the implementation of Scenario 4 results in a net benefit to society

The economic benefits include the gain in quality of life for additional people who improve treatment, deaths prevented and net financial savings due to the reduction in expenditure on low dose codeine medicines. The economic costs include the additional costs to consumers, MPS and PBS of additional medications, GP consultations and specialist consultations. The gains in quality of life (measured as QALYs) and deaths prevented are monetised at the rates recommended by the OBPR.

Note: the regulatory costs are undiscounted and the economic costs discounted, as is consistent with OBPR guidelines.

Source: KPMG