To overcome the limitations of FFS reimbursement schemes, various pay-for-performance (P4P) models have been implemented in a number of LMIC countries. These models are usually based on special financial payments for a dedicated performance. However, both the structure of the financial rewards as well as the definition of performance (including its quantification and measurement) differs significantly between the models. It is therefore difficult to compare and transfer results between different countries. In general, P4P programs need to acknowledge that incentives have to be valuable enough to stimulate investment in improving cancer care. Their impact relies exquisitely on high-powered incentives that directly target improved cancer care processes and enhanced patient experience, as well as on the availability of achievable benchmarks for improved outcomes.
It is important to recognize that the value of an incentive has to be seen from the perspective of its receiver, which is not necessarily the same as the perception of those who design the respective incentivizing framework. In addition, the perception of incentives can vary over time, as well as between age groups, generations and different professional groups. This necessitates the continuous adaptation of the underlying schemes. P4P incentives need to focus on a limited number of reliable performance indicators to motivate cancer care providers into changing delivery processes, and require a design that enables clinical and organizational leaders to sustainably use the system for performance improvement. This is a highly challenging task, particularly in the context of cancer care. Furthermore, adequate risk adjustment, such as for differences in underlying patient populations (for example, curable cancer stages versus palliative care situations) or catchment structures (for example urban versus fare remote areas), are important design aspects. High impact performance indicators will motivate providers to develop better cancer care and reorganize efficient delivery processes. However, there is always the inherent danger of stimulating untargeted effects, such as the avoidance of patients with clinically complex conditions or economically less attractive care seekers, such as individuals with metastatic cancer stages. Overall, the effective implementation of P4P for patients with cancer, and particularly those with advanced stages, remains an enormous unsolved task, and therefore is currently not recommended for LMIC, as considerable public health research into the implementation P4P in the cancer care arena needs to be carried out.
Classic P4P models may be modified or combined with incentives, and applied across entire delivery processes that are mainly used for chronic diseases. For example, disease management programs (DMP) with standardized care for certain cancer entities are a combination of FFS and P4P, which commonly integrate structural, process and outcome parameters. If these programs are used for cancer preventive strategies, such as HPV immunization, population coverage and outreach can be improved. In addition, these short-term treatment programs may achieve economic effectivity and positive cost–benefit ratios . However, their success is exquisitely related to the availability of resources and the motivation of healthcare providers. Furthermore, the effects achieved by incentivization are determined in part by patients’ acceptance of and participation in cancer care structures, and on the cultural and religious environment in which the cancer care is embedded. In addition, the education of both the health care providers (in terms of their professional knowledge) and patients (in terms of their understanding of the provider and access models) impacts on the efficacy of incentivization. Accordingly, counterproductive effects of DMP that worsen inequalities in healthcare delivery may occur, especially in remote regions.
Implementation of DMP and other P4P models is frequently impeded by a variety of barriers. Clinical care processes need to be clearly defined that have a limited need for individualization of care. This means that these models are only suitable for a small number of diseases or medical conditions that require highly standardized and comparable medical approaches, which is not usually the case for cancer. Mechanisms are also required that allow for the dynamic adaptation of care plans based on recent innovations and new clinical evidence, especially if care plans are legally regulated. Furthermore, these models demand high management, reporting and controlling efforts, as well as the definition of reliable and measurable quality indicators. Accordingly, poor availability of the high data quality and data management processes that are required limit implementation of these models.
Overall, implementation of DMP in LMIC for specific chronic diseases and acute intervention programs may provide an opportunity to improve the quality of care through standardization of delivery processes and performance feedback, if implemented as part of the DMP. However, there is also a high risk that quality improvement will fail, and that enhanced accessibility for patients will not materialize. Reasons for this include the complexity of DMP, the need to intensively integrate patients into the program, the high requirements for education of involved staff and patients, as well as the requirement for adequate reporting structures. These issues can also be accompanied by unexpected increased costs. In summary, when the potential risks and benefits for cancer care offered by P4P models are weighed against each other, such approaches cannot be recommended for LMIC.
In addition to the frequently used economically-driven performance parameters incorporated into typical P4P designs, there is increasing interest in the advantages offered by value-based financing. The primary goal of value-based payment in the management of cancer patients is to achieve improved care that is not immediately measured as an increased delivery performance by cancer care providers, but rather as a better cancer patient experience, improved clinical quality and health outcomes, or lower overall costs of cancer care. In contrast to performance-based financing, the theoretical background of value-based financing includes a less restrictive perspective on achievable advantages, fewer constraints on management decisions, as well as a reduced need for measurement and reporting. Various forms of value-based financing (such as shared savings and risk, reference pricing, and bundled payment), combined with adjunct incentives for quality and efficiency may be tailored according to the prevailing market conditions and organizational frameworks. However, translation of broadly accepted and comparable values into economic categories and reimbursement schemes is highly controversial. For example, there are a number of ethical considerations due to the great potential of value-based financing to increase inequality in population coverage especially for poor people, to worsen cancer care availability in underserved regions, and to impair its acceptability for certain population groups. In addition, assessment of values such as “health outcomes” is widely used, but significant differences in understanding the meaning of such terms exist between healthcare professionals and managers, making universal applicability challenging. To date, little evidence is available concerning the relative effectiveness and underlying mechanisms of value-based purchasing designs compared to other financing systems, including for LMIC. The very limited current experience suggests that value-based systems require complex management, infrastructure and human resources, as well as functioning referral and effective reporting pathways, if adequate UHC is to be achieved. These observations appear to exclude the use of value-based models for cancer care in LMIC, at least in the near future.
Healthcare economists have advocated the use of cost-effectiveness analysis (CEA) in several (mainly industrial) countries. The principle of CEA is to rank healthcare interventions on the basis of their incremental costs relative to their incremental benefits. This approach invariably leads to the prioritization of treatments, resulting in inequality of healthcare coverage based on criteria such as age, chronic conditions or treatment costs. In CEA systems, benefits are predominantly considered from the economic view of the society as a whole, and the individual patient’s interests are more or less excluded from financial evaluations. The authors share many of the political and ethical concerns regarding CEA approaches, especially for cancer care, under the conditions and healthcare frameworks that prevail in LMIC.