Achieving Universal Health Coverage: We Can’t Improve What We Don’t Measure

Accordingly, Universal Health Coverage became a target for the United Nations Sustainable Development Goals, SDG 3.8, and is an opportunity to realize the human right to health worldwide by 2030. Universal Health Coverage (UHC), “access to key promotive, preventive, curative and rehabilitative health interventions for all at an affordable cost, thereby achieving equity in access,” is one of the World Health Organization (WHO) Director General’s top priorities.

At the same time, having an SDG-specific UHC target reinforces the urgent need for consensus on how to define and track UHC meaningfully.

HFI’s CEO and founder, Dr. Andrea Feigl, and Fabian Moser Charité-Universitätsmedizin Berlin conducted a systematic review of major global health databases to assess the current state of data on UHC progress around the world. Their findings exposed concerning shortcomings.

In 2015, the WHO and World Bank (WB) jointly published a report entitled Tracking Universal Health Coverage which proposed 13 service coverage indicators and two financial protection indicators to measure global progress toward UHC. Dr. Feigl and Mr. Moser searched nine commonly used and cited public databases including the WHO Global Health Observatory (GHO), WHO Global Health Expenditure Database, WHO PCT databank, WB World Development Indicators (WDI), United Nations Department of Economic and Social Affairs Population Division, International Labor Organization (ILO) Social Protection database, OECD Health Statistics, and the IHME database to find available data on these indicators. They also included a reference search and reached out to key individuals at WHO, World Bank, and ILO for additional data sources, then recorded disaggregated data on the indicators whenever available. The search covered the years 2010–2015 and included all 194 WHO member states.

The graph below displays these 15 indicators and the corresponding percentages of the WHO Member States that were found to have data available for each indicator.

As the graph demonstrates, the availability of data varies widely per indicator. Though more than half of WHO Member States have some data available on most indicators, serious gaps remain.

There is a concerning dearth of data, for example, on catastrophic or impoverishing health expenditures — less than 10% of WHO members had data on either. These financial indicators are key to achieving UHC, as the WHO’s definition of UHC explicitly stipulates these services be accessible “at an affordable cost.” Out-of-pocket healthcare spending still accounts for 35% of global health expenditures and pushes tens of millions, if not more, into poverty annually. Full access to essential health services doesn’t count for much if those services are catastrophically unaffordable, so tracking this indicator is crucial.

Even more alarming, though, is the complete lack of any data on NCD treatment coverage — the percentage of non-smoking adults was the only indicator even remotely related to NCDs with robust data. In the absence of precise data on NCD indicators, UHC progress reports have used proxy indicators like NCD prevalence data or imputation methods like interpolation or extrapolation.

These workarounds, however, may be problematic in and of themselves. Using proxy data can obscure the real gaps in the SDG indicator data, and even worse, can give a false sense of progress. For example, using prevalence data on hypertension in lieu of data on actual service coverage could give the impression that hypertension rates in LMICs are similar to those in HICs (31.5% versus 28.5%). But in reality, though cases of hypertension are not much more prevalent in LMICs, they tend to be much more severe: hypertension control rates among hypertension patients in HICs are four times higher than in LMICs. This disparity points to gaps in actual hypertension care in LMICs (beyond simple diagnostics) that require more precise data to create effective solutions and achieve UHC.

Even for the indicators where the vast majority of countries have reported data, such as TB treatments, the data lacks the nuance that would be necessary for more in-depth analysis. Some indicators have reported data that can be broken down into urban versus rural access, a few have the breakdown by wealth quintile, and only the DTP3 indicator had any reported data that could be categorized by sex. These distinctions may be critical. We might expect urban areas to have easier access to some services for example, and most likely those in the higher wealth quintiles will achieve universal coverage than those in the lower quintiles, and these disparities will be crucial in informing where and how resources should be allocated to make progress toward UHC. But we simply have no way of informing those important decisions without more robust data.

While most WHO Member States had data on most of the indicators, relatively few had data on all 15, even when allowing for proxy data in place of direct data on the NCD indicators. In fact, less than 30% of all member states had data on all the indicators, as shown in the graph below. This makes it exceedingly difficult for researchers, governments, and other global health stakeholders to see the full picture of progress toward UHC.

LICs were most likely to have full data available on all 15 indicators (41% of these countries did have complete data), and HICs were least likely (just 19% did). This may be due to a particular emphasis from the WHO and other global health organizations on increasing health coverage in LICs — and rightfully so, as the disease burden in those countries is highest and access to essential services is lowest. Still, the fact remains that in no income category did even half of the countries have complete data on the proposed UHC indicators, showing the severe gaps in data necessary for monitoring and progressing toward true UHC.

Questions about how UHC can be meaningfully tracked and compared across countries despite the highlighted data scarcity in key areas of service and financial protection coverage will likely persist in the near future. The lacunae of data for several key UHC indicators under the SDG framework highlight that increased data sharing and coordination will be vital to proficiently monitor and accelerate progress towards UHC. At the global level, existing initiatives such as the Health Data Collaborative, or IHME’s tracking of health-related SDGs, represent promising vehicles for such efforts. Regardless of the global body entrusted with monitoring SDG-UHC progress, streamlining of data collection efforts, indicator definitions, and milestone dates will be critical and must be standardized across the wide range of stakeholders working to achieve global UHC.

By Andrea Feigl, Thomas Roades, and Fabian Moser

--

--

--

Heart of a non-profit. Engine of an investment bank. We use economic data to facilitate investments to prevent diseases.

Love podcasts or audiobooks? Learn on the go with our new app.

Recommended from Medium

4 Patient Retention Strategies to Reduce Leakage

My Corona Virus Experience

Corona Virus (COVID19): Customer Updates & Relief Efforts

23andMe Thinks Polygenic Risk Scores Are Ready for the Masses, But Experts Aren’t So Sure

How Mosquitos Have Shaped What We Eat and Drink

A mosquito about to fly onto a person’s hand.

Download In *!PDF BCPS Bullets Read #book %ePub

Marijuana and Opioids: An Unknown Connection

50 Wonderful Health Benefits of Grass - Prospective Health Benefits of Bud and Its…

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Health Finance Institute

Health Finance Institute

Heart of a non-profit. Engine of an investment bank. We use economic data to facilitate investments to prevent diseases.

More from Medium

How to use iMaps like a developer

Ukrainian-Russian Negotiations:A Non-Aligned Perspective

A Long Drive To Memory Lane

What does the Dress Code of Steve Jobs tell you about Decision Fatigue?

steve jobs outfit and decision fatigue