Principles for Constrained Optimisation Across Health Promotion, Prevention and Care Settings
To enable budget constrained optimisation across health prevention and promotion, diagnostic, curative, rehabilitative and palliative settings health economics needs robust principles and unbiased while flexible methods to inform societal decision making across joint research, reimbursement and regulatory decisions.
In identifying robust and principled health economic methods for constrained maximisation across these health care setting and joint decisions, we bring together:
- (i) The seminal research of Bernie O’Brien and colleagues (Andy Willan, Andy Briggs and others) in highlighting the need to move beyond partial clinical and economic consideration to jointly consider costs and effects (O’Brien 1996; Briggs and O’Brien 2001; Briggs et al. 2002; Willan and Briggs 2006).
- (ii) Decision analytic principles of coverage and comparability shown as more generally required to avoid biases and inferential fallacies in evidence synthesis, translation and extrapolation to inform societal decision making in any given jurisdiction(s) of interest (Eckermann et al. 2009, 2011).
- (iii) Methods for robustly evaluating health promotion strategies in community settings, where following Shiell and Hawe’s research, community-level social capital and network multiplier impacts of strategies in practice (Hawe and Shiell 2000; Shiell et al. 2008; Hawe et al. 2009) are key.
- (iv) Value of information methods enabling optimisation of joint research and reimbursement decisions allowing for key decision contexts (Eckermann and Willan 2007, 2008a, b, 2009, 2011, 2013; Eckermann et al. 2010; Willan and Eckermann 2010, 2012).
- (v) Robust methods for regulating to create appropriate economic incentives for net benefit maximisation with multiple provider efficiency (Eckermann and Coelli 2013) as well as multiple strategy (Eckermann et al. 2008; Eckermann and Willan 2011) and multiple outcome (McCaffrey et al. 2015) comparisons.
- (vi) Budget-constrained threshold values for effects reflecting opportunity cost of adopting and financing new technologies given alternative research and reim?bursement options and decision contexts faced in any jurisdiction of interest, highlighting the health shadow price research of Pekarsky (Pekarsky 2012, 2015; Eckermann and Pekarsky 2014).
The principles and research methods developed for the Health Economics from Theory to Practice course underlying this text have been aimed at providing a robust framework to jointly address these six areas. The process of bringing these areas together explicitly addresses structural issues of who and what health systems should serve and reflect - community objectives and values - to underlie processes of evidence-based societal decision making. The political economy of health systems, their institutions and decision making and actions are hence central to health economics principles and practice in optimising societal decision making. This is particularly important given the characteristics of health-care transactions and health systems and the importance of appropriate community values and objectives in achieving both equity and efficiency across health systems. Characteristic asymmetry of information (Akerlof 1970; McGuire et al. 1988) between providers and patient populations with associated bounded rationality (Simon 1957) of patients in complex decision making under uncertainty (Arrow 1963) arises in agency relationships with health care. These characteristics are prevalent across health systems and settings.
In many health-care settings, information asymmetries are often extreme between provider and patient agents in health-care interactions. They are also likely to be present ex post (after treatment) as well as ex ante (before treatment) given the incremental impact of any actual strategy or pathway is relative to counterfactual alternative strategies or pathways (McGuire et al. 1988: 43-44). These information conditions in turn lead to the need for health-care providers to act as agents for patients in enabling efficient decision making in these settings. However, they also create the conditions for supplier-induced demand to arise (and associated detrimental cost and health outcomes from overtreatment) where providers have incentives (financial and/or professional) to induce such demand. Understanding these characteristics and the need for appropriate incentives for health-care providers in practice is key to establishing policy and regulatory frameworks for efficiency as well as equity in health-care institutions and their performance monitoring and funding arrangements. The theoretical underpinnings of these factors for the health economics discipline point to the need for universal public health-care provision on equity but also population health, health system cost and efficiency grounds in providing appropriate incentives for providers, as Chap. 12 highlights.
Empirically, there is ample evidence for the importance of universal health care and payment arrangements and provider incentives for appropriate care, rather than perverse incentives for supplier-induced demand in populations able to access care, in order to enable health system efficiency as well as equity of access. This is particularly borne out in contrasting the joint cost and outcomes of the US health system relative to universal access systems in places such as Canada, the UK, France, Australia and indeed the vast majority of Organisation for Economic Co-operation and Development (OECD) countries. In 2013 the US health system cost on average double the proportion of GDP of universal publicly provided systems in the OECD
(18 vs. 9%) at $8505 per capita, in spite of the US systems’ lack of universal access to health care. Further, despite this much higher health expenditure, the USA had some of the worst population-level health outcomes in the OECD, with life expectancy in 2013 lower than any country with annual health expenditure of more than US$2000 per capita, as well as the worst performing country in terms of health improvements over the past 50 years (OECD 2013). Such clear health system inefficiency with higher costs and worse health outcomes as well as inequity in the absence of universal health-care access (Davis et al. 2014) in large part arises as those who have access; the highest income quintile(s) are over-serviced, while those who don’t have access or have very limited access, are underserviced. Over-servicing of those with access in the USA is reinforced by defensive medicine under threat of litigation and can be extreme, manifesting in unnecessary tests and subsequent unnecessary treatment of false positives (particularly for rare conditions) as well as cascading use of polypharmacy with symptom chasing of side effects.
Another related reason costs are significantly higher in the USA is due to increased complexity in administering a health system without universal access. This leads to higher costs in monitoring and assessing access and exclusion criteria and maintaining property rights across multiple systems and care provision (privately insured, Medicare for the elderly and Medicaid for some disadvantaged populations). There are also costs of the ‘paper trails’ between health-care providers, insurers and other funders. Historically, about one quarter of current US health-care system costs are associated with administration of their systems compared with approximately one tenth of health-care costs in universal access systems (Woolhandler et al. 2003). Further, for those with private insurance in the USA, alongside being over-serviced if they gain access to treatment, denial of treatment by health maintenance organisations (HMOs) simultaneously arose prior to Obamacare for necessary treatment of conditions which existed prior to insurance (pre-existing conditions required to be declared). Where pre-existing conditions are excluded, large administrative costs also arise in attempting to identify pre-existing conditions and associated litigation costs to patients and insurers, alongside leading to worse health outcomes from needed treatment not being provided for pre-existing conditions.
The bottom line is that publicly funded universal access health systems are both theoretically expected to be, and with empirical evidence observed to be, less costly while having better access and population-level health outcomes, and hence more efficient, than privately funded systems (OECD 2013; Davis et al. 2014). However, the equity and efficiency advantages of publicly provided universal health-care systems still depend on such systems providing appropriate incentives for providers and reflecting the objectives of the community they serve. If public health systems are to optimise outcomes for community benefit with constrained budgets and resources, then community objectives need to be reflected in decision making and robustly regulated to reflect health system level opportunity costs for those objectives. This is particularly the case in research and assessment of the types of strategies available with existing and new technology that are appropriate to use in different parts of the health system. Naturally this is also the case in the way therapies and strategies are used in practice, in coordinating between parts of the system and across populations over time. These are important health economic questions this text aims to shed some light across, highlighting common biases and problems of often partial and silo-based approaches while identifying simple methods to jointly, robustly and efficiently address research, reimbursement and regulation decisions.
In combining these areas of health economic research, we will be drawing on many sources, attempting to bring together best approaches from the west (evidence-based medicine in diagnosis and treatment) with the east (preventative medicine and health promotion allowing for sociological and societal determinants) in addressing the full spectrum of options across health settings. HTA infrastructure focussed on assessing patentable medications, devices and diagnosis and testing strategies to the exclusion of unpatentable options acts to create distinct barriers to appropriate research into and adoption of unpatentable options and best expansion and contraction of existing programs. Such a system denies appropriate consideration of better use of existing programs and non-patentable alternative strategies (Pekarsky 2012, 2015; Eckermann and Pekarsky 2014), for example, community health promotion, rehabilitation or function decline prevention programs, investing in better infrastructure for information flows and care coordination, overcoming barriers and supporting enablers for better implementation of strategies and modifying methods of care. Systems focused on new patentable interventions delay or completely stall the evidence for, and ability to appropriately compare and defend, current programs and non-patentable options against their displacement in areas including:
- (i) Expanding use of ‘off-patent’ medication and its better use in indicated populations, e.g. use of existing statins.
- (ii) Non-patentable alternative modality areas such as rehabilitative care in coronary heart disease (CHD) and chronic obstructive pulmonary disease (COPD) population or palliative care support at home or in institutional settings as alternatives to therapies such as radiotherapy and chemotherapy and associated medications in cancer populations.
- (iii) Health promotion and primary prevention measure community-based approaches in community settings such as community gardens and kitchens in schools (Eckermann et al. 2014) or other community settings, walking paths and more generally age- and dementia-friendly facilities, programs and policies (Kalache 2013).
- (iv) The use of natural plant varieties and extracts at factor costs in treatment of common conditions. For example, medicinal cannabis exploiting entourage benefits of CHD-, terpene- and THC-rich varieties (Wagner and Ulrich- Merzenich 2009; Russo 2011; Gallily et al. 2015) titrated up to individual patient needs and tolerance in palliative pain management populations (Johnson et al. 2010; Carter 2011).
Such options are explored at length in Chap. 12 considering promising policy, research, reimbursement, pricing and practice options, in response to the health, aged care and wider social system challenges of baby boomer ageing. Historical evidence-based medicine and HTA approaches to research, reimbursement and pricing do not facilitate optimisation of health outcomes from constrained budgets until such non-patentable options are appropriately explored and compared alongside patentable technologies. Indeed, unless such options are adequately explored, HTA and EBM processes can be rightly accused of creating institutional barriers that promote selection bias in alternatives considered, which unduly privilege allocation of constrained research and reimbursement funding to new patentable technology. This lack of appropriate coverage of options leads to ill inform societal decision making in relation to reimbursement (adoption and financing) of new technology without appropriate consideration of opportunity costs (best alternative adoption and financing actions) associated with current programs and technology and budget constraints. That is, comparison with best alternative actions in adoption, namely the most cost effective expansion of existing programs and technology, and best alternative action in financing, contraction of least cost effective programs as the research of Pekarsky (Pekarsky 2012, 2015; Eckermann and Pekarsky 2014) highlights, and as explored at length in Chap. 11.
Note that this does not imply that unexplained or anecdotal evidence of benefits from practice of health promotion and preventative strategies, herbal medicine or other eastern approaches and therapies such as tai chi, iridology, foot reflexology and acupuncture should be accepted on face value. It points to the need to undertake research to trial and test in practice whether and why such benefits arise in order to advance the health system toolkit and appropriate use. Rather than ignore such strategies and therapies, they should be researched where appropriate as promising approaches in the same way that promising new patentable therapies are - ideally with globally optimal trials. As Chaps. 6 and 7 highlight, explicitly allowing for evidence translation in optimising global trial design provides a first best option globally for translatable evidence as part of expected net gain maximisation, but also the ability to adopt and trial in optimising joint research and reimbursement decisions. Until promising non-patentable options have research which is resourced to compare with that of promising patentable options, a systemic institutional bias arises in processes of EBM. As Pekarsky (2015: 34) notes, both Arrow (1963) and Tirole (1988) conclude that the failure of the market to provide an incentive to invest in innovation for non-patentable strategies provides the economic case for public sector investment in researching and adopting such non-patentable strategies.
These fundamental coverage issues for avoiding selection bias in optimisation are further explored in developing methods which facilitate robust evidence generation and consideration of appropriate comparators and multiple modalities in:
- (i) Chapter 4, highlighting methods for appropriate cost effectiveness evaluation of health promotion and prevention strategies.
- (ii) Chapters 6 and 7, identifying method for optimal global trial design which enable feasible evidence collection for adopting and trialling with existing or promising new strategies while maximising global value relative to cost of trial designs and decision making.
- (iii) Chapters 8 and 10, highlighting robust multiple strategy and outcome comparison methods on the cost disutility plane with expected net loss and frontier methods to best summarise cost effectiveness analysis in informing reimbursement and later research decisions.
- (iv) Chapter 9, illustrating the net benefit correspondence theorem method for practice comparisons (Eckermann 2004; Eckermann and Coelli 2013), uniquely enabling comparison of the efficiency of providers in practice consistent with maximising net benefit, which in making coverage and comparability conditions explicit also provide a robust framework to avoid cost-shifting and cream-skimming incentives.
- (v) Chapter 11, where health shadow price methods developed by Pekarsky (2012, 2015; Eckermann and Pekarsky 2014) are shown to provide appropriate incentives to collect evidence on best expansion and contraction of existing programs and technology alongside evidence of new technology. The health shadow price is also shown as key to establishing appropriate pricing of new technology and a pathway to allocative efficiency and budget-constrained optimisation with related research, reimbursement and regulation decisions.
In joining together these parts, and key principles and appropriate methods for individual and community approaches across settings, it is also important to note that in each case, as well as in combination, they require a longer-term attention span and wider perspective than short-term political or market-based reductionist approaches typically allow. We trust that those readers who stay the course will understand why partial and reductionist approaches are dangerous and obtain the fullest picture we can muster for key links between principles and methods for optimising research, reimbursement and regulation decisions. As a result, this text is not a cookery book telling you what to do in the next part of the recipe; however, the following mud map of chapters may aid those wanting to dive into a particular area to have some understanding of the whole. Figure 1.1 provides a map of the big picture, depicting decision making cycles for optimal joint research, reimbursement and regulation of practice and pricing decisions locally and globally, referencing related book chapters.
The robust process of problem definition, synthesis of cost, effects and costs effectiveness evidence and translation to inform net benefit estimation in jurisdictions of interest and assessment of optimal joint research and reimbursement decisions locally and globally allowing for relevant opportunity costs is iterative. Note that locally there are absorbing states for decision making cycles with rejection of strategies where the incremental net benefit (INB) is negative at the relevant jurisdiction shadow price for effects or sufficient evidence with adoption now optimal if INB is positive, while expected net gain from feasible research is not. Monitoring and regulation in practice is nevertheless indicated with adoption, while a lower price or changed evidence or conditions have potential to allow a strategy to become potentially optimal where INB is currently negative. More generally, the potential arises at the end of each research cycle to redefine questions in light of changing factors such as additional appropriate comparators and target populations in addition to updating evidence of relative treatment effects, baseline risks in translating evidence. Local factor prices and the health shadow price and associated INB and expected net gain
Fig. 1.1 Optimal decision making cycles for joint research, reimbursement and regulatory processes locally and globally
(ENG) measures can also change to reflect local conditions. The appropriate health shadow price for any given set of decision contexts flowing through to appropriate threshold values for effects also clarifies that research into best use of existing programs and technologies is a priority for appropriate pricing of new technology as well as its own sake in optimising budget-constrained decision making.