http://www.biomedcentral.com/1472-6963/15/230
Research article
A concise, health service coverage index for monitoring progress towards universal health coverage
Anthony Leegwater1, Wendy Wong2 and Carlos Avila1*
• *Corresponding author: Carlos Avila Carlos_Avila@abtassoc.com
Author Affiliations
1Abt Associates, 4550 Montgomery Ave, Suite 800 North, Bethesda 20814, MD, USA
2University of Chicago (formerly Analyst at Abt Associates), Chicago, USA
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BMC Health Services Research 2015, 15:230 doi:10.1186/s12913-015-0859-3
The electronic version of this article is the complete one and can be found online at:http://www.biomedcentral.com/1472-6963/15/230
Received: 18 August 2014
Accepted: 5 May 2015
Published: 12 June 2015
© 2015 Leegwater et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Abstract
Background
There is a growing international commitment to universal health coverage (UHC), but limited means to determine progress towards that goal. We developed a practical index for capturing health service coverage – a critical dimension of UHC -- that was more inclusive than previous methods.
Methods
Our data included publicly-available, indicators reflecting health service delivery, infrastructure, human resources, and health expenditures for 103 countries. We selected a set of internally-consistent indicators and performed principal component analysis. Multiple imputation was used to address missing values. We extracted and rotated four components related to health service coverage and developed a composite index for each country for 2009.
Results
Explaining cumulatively almost 80% of the total variance, the four extracted components were characterized as: 1) provision of services, 2) infrastructure and human resources, 3) immunization (provision of services), and 4) financial resources. The health service coverage index developed from these components demonstrated strong correlation with health outcome measures such as infant mortality and life expectancy, supporting its validity. Index values also appeared generally consistent with published reports and the regional distribution of health coverage.
Conclusions
Our approach moved beyond common indicators of service coverage focused on infectious diseases and maternal and child health, to include information on necessary health inputs. The resulting, balanced, composite index of health service coverage demonstrated promise as a metric, likely to discriminate coverage levels between countries and regions. An important number of service provision indicators were correlated, therefore a reduced set of services performed well as a proxy for the full set of available indicators. This parsimonious index is a start toward simplifying the task of policy-makers monitoring progress on a key domain of universal health coverage.
Keywords:
Health service coverage; Universal health coverage; Index; Principal component analysis
Background
A growing share of countries across the globe are declaring a commitment to pursuing Universal Health Coverage (UHC) and introducing policies and approaches to advance toward that goal. International donors and multilateral organizations are supporting these initiatives, with UHC under serious consideration for the post-2015 development agenda [1]. Such attention raises the issue of the most appropriate metrics for progress towards universal health coverage. Individual indicators currently used to capture aspects of UHC are myriad. There is however no existing measure that captures multiple dimensions of UHC. Even the composite indicators that have been developed in this area are focused on service coverage. Such composite measures are limited in how they are constructed and what health services are covered. Therefore, existing approaches do not appear to meet the current and future needs of policy makers, who need concise metrics to monitor whether countries are advancing in covering their health needs.
The 2010 World Health Report provides the most commonly-referenced definition of universal health coverage, describing it as a goal where all people have access to health services when needed and avoid financial hardship in paying for those services [2]. This influential report features a conceptual framework with three dimensions of UHC: service coverage, financial coverage, and population coverage. Although a persuasive conceptual framework, additional effort is needed to operationalize measurable indicators for tracking coverage in practice, especially as each dimension has its own measurement complexities [3]. We focus here on the service coverage dimension as a critical element, while acknowledging that the other dimensions of UHC are also important but data constrained.
Health service coverage has traditionally been measured by type of disease and type of treatment. Given the profusion of disease conditions and treatments, there have been some efforts to create composite indicators. For example, Millennium Development Goals (MDG) Countdown Research Group constructed composite indices by compiling a selection of service coverage indicators representing various strengths or intervention areas of the maternal and child health (MCH) service delivery system [4], [5]. However, this approach was limited not only by focusing on maternal and child health services but also by giving the same, arbitrary, equal weight to each indicator. Save the Children recently published a Health Access Index that ranked 75 countries with high maternal and child mortality according to health services access [6]. Their approach included six indicators, including four that match with our approach, but also included a measure of equity and an outcome measure for newborn mortality. However, like the MDG Countdown group, the indicators were equally weighted across categories. In addition, the inclusion of an outcome measure in the index risked conflating a goal of improved health services with the means by which it could occur.
Other studies offered in-depth assessments of health coverage in a small group of countries that have instituted specific health insurance or social health protection schemes. Available indicators related to financial coverage (or risk protection) measure household out-of-pocket (OOP) spending and identify when households have exceeded certain levels of spending deemed catastrophic [7]. However, household consumption data require large, expensive survey efforts and are thus typically conducted only every five years or so in most developing countries. This leaves insufficient data at present to include catastrophic measures across countries in our analysis.
A key consideration in measuring progress towards UHC practically is the availability and use of existing data from current systems, to avoid duplicating monitoring systems and imposing additional reporting burden on countries. Current indicators of service provision are dominated by maternal, child and infectious diseases, leaving many other services under-represented. Adding complementary factors – indicators such as infrastructure, human resources, and financial resources -- in the production of overall health services to service provision indicators is a step toward alleviating MCH over-representation in prior estimates. Indeed, our view is that the coverage of services should respond to the health needs of the broad population, the services must be physically available, and financial resources should be available to prevent financial risk when using health care services. These elements should therefore be included to improve the measurement of service coverage.
The objective of this study was to develop a practical index to monitor countries as they expand health coverage by using widely available information from domestic and international sources. Our specific focus here given the data available is service coverage, developing a measure that overcomes some of the shortcomings of other measures and doing so for a large group of countries.
Methods
Our data included indicators reflecting health service delivery, health infrastructure, human resources for health and health expenditures for 2000 to 2010 from publicly-available global databases. The data sources included World Development Indicators and the World Health Organization’s Global Health Observatory. Data analysis was conducted using Stata 12 unless otherwise noted.
We excluded indicators with more than 85% missing data and dropped country observations with more than 50% missing values over that time period, resulting in a database with 19 indicators for 103 countries. For the years 2000 to 2010, 41% of all indicator values were missing. However, policy makers and other interested parties would likely prefer an approach that is focused on a recent year for potential use for benchmarking. Thus, we selected 2009 as a recent year with a more reasonable level of missing values (Additional file 1: Table S1).
We imputed for missing values in 2009 using the broader 2000–2010 dataset (Fig. 1) utilizing a multiple imputation package with time series and cross-sectional capabilities [8]. As a result of this process, we had 30 complete data sets containing imputed values across 19 indicators and 103 countries (Additional file 1: Table S2.)
Fig. 1. Overview of missing imputation and analysis process. (Source: authors. Description of missing value imputation and analysis process)
Internal consistency
To explore relationships in the data and to examine whether they are suitable for such a princ