Appraising Drugs Based on Cost-effectiveness and Severity of Disease in Norwegian Drug Coverage Decisions.

Importance: Rising health care costs are a major health policy challenge globally. Norway has implemented a priority-setting system intended to balance cost-effectiveness and concerns for fair distribution, but little is known about this strategy and whether it works in practice. Objective: To present and evaluate a systematic drug appraisal method that uses the severity of disease to account for a fair distribution of health in cost-effectiveness analysis, forming the basis for price negotiations and coverage decisions. Design, Setting, and Participants: This cross-sectional study uses confidential drug price information and publicly available data from health technology assessments and logistic and linear regression analyses to evaluate drug coverage decisions for the Norwegian specialized health care sector from 2014 to 2019. Main Outcomes and Measures: Drug coverage decisions by Norwegian authorities and incremental cost-effectiveness and severity of disease measured as absolute shortfall of quality adjusted life years. Results: Between 2014 and 2019, a total of 188 drugs were appraised, of which 113 were cancer drugs. The overall coverage rate was 73% (138 of 188). The number of annual appraisals increased during the observation period. Based on 83 chosen decisions, regression analysis showed that incremental cost-effectiveness ratios (ICER) based on negotiated drug prices, adjusted for severity-differentiated cost-effectiveness thresholds, was the variable that best projected drug approvals (OR, 0.60; 95% CI, 0.42-0.86). An increase in the ICER by $10 000 was associated with a reduction in the odds for approval of 40% for drugs assessed from 2018 to 2019. Conclusions and Relevance: This cross-sectional study demonstrated how concerns for efficiency and fair distribution of health can be implemented systematically into drug appraisals and reimbursement decisions. New, expensive drugs are expected to escalate health care costs in the years to come, and it may be feasible to control costs by negotiating the prices of new drugs while appraising both their cost-effectiveness and how their health benefits are distributed.

Attitudes towards priority setting in the norwegian health care system: a general population survey.

BACKGROUND: In an ideal world, everyone would receive medical resources in accordance with their needs. In reality, resources are often scarce and have an alternative use. Thus, we are forced to prioritize. Although Norway is one of the leading countries in normative priority setting work, few descriptive studies have been conducted in the country. To increase legitimacy in priority setting, knowledge about laypeople's attitudes is central. The aim of the study is therefore to assess the general population's attitudes towards a broad spectrum of issues pertinent to priority setting in the Norwegian publicly financed health care system. METHODS: We developed an electronic questionnaire that was distributed to a representative sample of 2 540 Norwegians regarding their attitudes towards priority setting in Norway. A total of 1 035 responded (response rate 40.7%). Data were analyzed with descriptive statistics and binary logistic regression. RESULTS: A majority (73.0%) of respondents preferred increased funding of publicly financed health services at the expense of other sectors in society. Moreover, a larger share of the respondents suggested either increased taxes (37.0%) or drawing from the Government Pension Fund Global (31.0%) as sources of funding. However, the respondents were divided on whether it was acceptable to say "no" to new cancer drugs when the effect is low and the price is high: 38.6% somewhat or fully disagreed that this was acceptable, while 46.5% somewhat or fully agreed. Lastly, 84.0% of the respondents did not find it acceptable that the Norwegian municipalities have different standards for providing care services. CONCLUSION: Although the survey suggests support for priority setting among Norwegian laypeople, it has also revealed that a significant minority are reluctant to accept it.

Precision medicine and the principle of equal treatment: a conjoint analysis.

BACKGROUND: In precision medicine biomarkers stratify patients into groups that are offered different treatments, but this may conflict with the principle of equal treatment. While some patient characteristics are seen as relevant for unequal treatment and others not, it is known that they all may influence treatment decisions. How biomarkers influence these decisions is not known, nor is their ethical relevance well discussed. METHODS: We distributed an email survey designed to elicit treatment preferences from Norwegian doctors working with cancer patients. In a forced-choice conjoint analysis pairs of hypothetical patients were presented, and we calculated the average marginal component effect of seven individual patient characteristics, to estimate how each of them influence doctors' priority-setting decisions. RESULTS: A positive biomarker status increased the probability of being allocated the new drug, while older age, severe comorbidity and reduced physical function reduced the probability. Importantly, sex, education level and smoking status had no significant influence on the decision. CONCLUSION: Biomarker status is perceived as relevant for priority setting decisions, alongside more well-known patient characteristics like age, physical function and comorbidity. Based on our results, we discuss a framework that can help clarify whether biomarker status should be seen as an ethically acceptable factor for providing unequal treatment to patients with the same disease.

Clinical decision making in cancer care: a review of current and future roles of patient age.

BACKGROUND: Patient age is among the most controversial patient characteristics in clinical decision making. In personalized cancer medicine it is important to understand how individual characteristics do affect practice and how to appropriately incorporate such factors into decision making. Some argue that using age in decision making is unethical, and how patient age should guide cancer care is unsettled. This article provides an overview of the use of age in clinical decision making and discusses how age can be relevant in the context of personalized medicine. METHODS: We conducted a scoping review, searching Pubmed for English references published between 1985 and May 2017. References concerning cancer, with patients above the age of 18 and that discussed age in relation to diagnostic or treatment decisions were included. References that were non-medical or concerning patients below the age of 18, and references that were case reports, ongoing studies or opinion pieces were excluded. Additional references were collected through snowballing and from selected reports, guidelines and articles. RESULTS: Three hundred and forty-seven relevant references were identified. Patient age can have many and diverse roles in clinical decision making: Contextual roles linked to access (age influences how fast patients are referred to specialized care) and incidence (association between increasing age and increasing incidence rates for cancer); patient-relevant roles linked to physiology (age-related changes in drug metabolism) and comorbidity (association between increasing age and increasing number of comorbidities); and roles related to interventions, such as treatment (older patients receive substandard care) and outcome (survival varies by age). CONCLUSIONS: Patient age is integrated into cancer care decision making in a range of ways that makes it difficult to claim age-neutrality. Acknowledging this and being more transparent about the use of age in decision making are likely to promote better clinical decisions, irrespective of one's normative viewpoint. This overview also provides a starting point for future discussions on the appropriate role of age in cancer care decision making, which we see as crucial for harnessing the full potential of personalized medicine.

Health inequalities in Ethiopia: modeling inequalities in length of life within and between population groups.

BACKGROUND AND OBJECTIVES: Most studies on health inequalities use average measures, but describing the distribution of health can also provide valuable knowledge. In this paper, we estimate and compare within-group and between-group inequalities in length of life for population groups in Ethiopia in 2000 and 2011. METHODS: We used data from the 2011 and 2000 Ethiopia Demographic and Health Survey and the Global Burden of Disease study 2010, and the MODMATCH modified logit life table system developed by the World Health Organization to model mortality rates, life expectancy, and length of life for Ethiopian population groups stratified by wealth quintiles, gender and residence. We then estimated and compared within-group and between-group inequality in length of life using the Gini index and absolute length of life inequality. RESULTS: Length of life inequality has decreased and life expectancy has increased for all population groups between 2000 and 2011. Length of life inequality within wealth quintiles is about three times larger than the between-group inequality of 9 years. Total length of life inequality in Ethiopia was 27.6 years in 2011. CONCLUSION: Longevity has increased and the distribution of health in Ethiopia is more equal in 2011 than 2000, with length of life inequality reduced for all population groups. Still there is considerable potential for further improvement. In the Ethiopian context with a poor and highly rural population, inequality in length of life within wealth quintiles is considerably larger than between them. This suggests that other factors than wealth substantially contribute to total health inequality in Ethiopia and that identification and quantification of these factors will be important for identifying proper measures to further reduce length of life inequality.