Health Financing - Norway

  • Norway
  • In 2023, the estimated spending on medical products in Norway is €0.98k.
  • The health expenditure in Norway is expected to be 10.73% of GDP by 2023.
  • The healthcare spending per capita in Norway is expected to be €55.11bn by 2023.
  • The medical services spending per capita in Norway is expected to be €147.50 by 2023.
  • The tobacco spending per capita in Norway is expected to be €0.53k of GDP by 2023.
  • The CPI inflation for health-related consumption in Norway is expected to be 116.40 by 2023.

Key regions: Portugal, Saudi Arabia, Thailand, United States, Germany

Comparaison de régions

Analyst Opinion

The health indicators domain encompasses a dynamic landscape with regions and countries at different stages of development. Several regions have shown notable progress in health indicators, including North America, Western Europe, and parts of Asia. These regions benefit from advanced healthcare systems, robust data infrastructure, and significant investments in population health. However, disparities exist, with developing regions facing challenges in data collection and infrastructure development. In terms of its structure, the health systems exhibit a diverse landscape. Numerous organizations and institutions contribute to the development and implementation of health indicators. Collaboration and partnerships among stakeholders are crucial for ensuring comprehensive and standardized health indicator measurements across regions and sectors.

The healthcare sector faces several challenges in relation to health financing, health determinants, and healthcare resources. In terms of health financing, inadequate funding and inefficient allocation pose significant obstacles to ensuring universal access to quality healthcare services. Limited financial resources and competing priorities can hinder investment in healthcare infrastructure, workforce development, and medical technologies. Additionally, healthcare systems often face resource constraints, including shortages of healthcare professionals, limited healthcare infrastructure in rural areas, and affordability challenges in accessing advanced medical technologies. These challenges need to be addressed to optimize the allocation and utilization of healthcare resources.

The COVID-19 pandemic has had a profound impact on the health indicators. The pandemic highlighted the importance of timely and accurate health data in monitoring and responding to public health crises. COVID-19 has influenced health indicators in several ways, including increased focus on infectious disease surveillance, changes in healthcare utilization patterns, and the prioritization of population health management. Future outlooks for the health indicators domain indicate continued growth and innovation. The pandemic has also accelerated the adoption of telehealth and remote monitoring, which are likely to persist beyond the crisis, shaping the future of health indicators and healthcare delivery.


Data coverage:

The dataset encompasses data from 152 countries. The charts depict the situation of each country in six different domains. These domains are socioeconomic indicators, macroeconomic indicators, health indicators, digital and connectivity indicators, consumption indicators, as well as logistics and transport indicators. Within these domains, various segments are covered, including demography, economic measures, economic inequality, employment, consumption, health determinants, and much more.

Modeling approach:

The composition of each domain follows a comprehensive approach that combines both top-down and bottom-up methodologies, with each domain and segment being guided by a specific rationale. To evaluate the situation of these six domains within each country, we rely on pertinent indicators and data from reputable international institutions, local national statistical offices, industry associations, and leading private institutions. Additionally, we undertake data processing procedures to address issues such as missing timelines, outliers, and data inconsistency. Our data processing incorporates advanced statistical techniques, including interpolation, exponential moving weighted average, and the Savitzky-Golay filter. These methods contribute to the refinement and enhancement of data quality.


In our forecasting process, a wide range of statistical techniques is utilized based on the characteristics of the markets. For example, the S-curve function is employed to forecast the adoption of new technology, products, and services, aligning the forecast model with the theory of innovation adoption. Additionally, the data is forecasted using ARIMA with and without seasonality considerations, exponential trend smoothing, and the Compound Annual Growth Rate (CAGR), with the option to incorporate adjustment factors when necessary. These techniques enable accurate and reliable forecast methods tailored to the unique characteristics of the data in each market and country.

Additional notes:

The data is updated twice per year or every time there is a significant change in their dynamics. The impacts of the COVID-19 pandemic and of the Russia/Ukraine war are considered at a country-specific level.

Vue d’ensemble

  • Health Spending
  • Health Inflation
  • Analyst Opinion
  • Methodology
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