Introduction and objectives
of the handbook
In recent years, significant progress has been achieved in delivering health-related interventions that are
designed to achieve goals relating to improving maternal and child health, and reducing mortality and illhealth
due to HIV/AIDS, tuberculosis and malaria. It is increasingly apparent, however, that the gains have been
neither universal nor sufficiently broad-based and sustainable. Progress at the national level has not necessarily
resulted in gains for most vulnerable population groups; in some instances, progress has stagnated or been
reversed. There is mounting evidence that health systems that can deliver services equitably and efficiently are
critical for achieving improved health status. Thus, many global health initiatives now incorporate attention to
health systems strengthening in the support they provide to countries.
While this increased attention to the strengthening of health systems is welcome, it would not be sustainable
in the absence of a sound monitoring strategy that enables decision-makers to accurately track health progress
and performance, evaluate impact, and ensure accountability at country and global levels. Moreover, the use
of results-based financing mechanisms by major global donors has created a further demand for timely and
reliable data. There is also increasing in-country demand for data in the context of annual health sector reviews.
Information is needed to track how health systems respond to increased inputs and improved processes, and
the impact they have on improved health indicators. This implies the need to define core indicators of health
system performance while developing and implementing appropriate sustainable measurement strategies to
generate the required data. However, on the supply side, there are major gaps in data availability and quality.
Few developing countries are able to produce data of sufficient quality to permit the regular tracking of progress
in scaling-up health interventions and
strengthening health systems. Data gaps
span the range of “input”, “process”,
“output”, “outcome” and “impact”
indicators: e.g. few countries carry out
regular national health accounts studies;
data on the availability and distribution
of health workers are often incomplete,
inaccurate and out of date; few countries
have systems that can monitor service
delivery; and data on population access
to essential services are limited.