Existence of designated mechanisms charged with analysis of RH statistics

Existence of designated mechanisms charged with analysis of RH statistics

Existence of designated mechanisms charged with analysis of RH statistics

There is a designated and functioning institutional mechanism charged with analysis of reproductive health (RH) statistics, synthesis of data from different sources and validation of data from population-based and facility-based sources (WHO, 2010). The body charged with these functions should be administratively separate from programs responsible for delivery of interventions and should adhere to fundamental principles of handling official statistics.

This indicator is a subset for RH of one of the core indicators for general health statistics in the WHO Health System Strengthening (HSS) Handbook and is also one of 26 indicators in the Health Information Systems Performance Index (HISPIX), which can be summed into a composite score (WHO, 2010). For more background on the process and criteria used in developing the WHO Handbook of Indicators for HSS and for details on this and related indicators, see WHO (2010); USAID (2009); and WHO (2007).

Data Requirement(s):

Reviews of ministry of health (MOH) and national health sector reports on designated infrastructure, staff, and procedural guidelines for health statistics analysis and reporting.  A number of tools have been developed for assessing information systems including: the HIS indicators in the WHO HSS Handbook and the HISPIX (WHO, 2010); the self-assessment indicators in the WHO Health Metrics Network (HMN) toolkit (WHO, 2007); the Organization for Economic Cooperation and Development (OECD, 2003) statistical standards, guidelines and best practices on development indicators; and the United Nations Fundamental Principles of Official Statistics (UN, 1994), which is often used as a general framework to assess the performance of national statistics offices.

The HMN toolkit recommends scoring the responses for this and related indicators on a four-level scale: highly adequate; adequate; present but not adequate; and not adequate at all. The crucial difference between the HISPIX approach and the HMN self-assessment tool is that the HISPIX indicators and summary score can be assessed on the basis of information that is largely available in the public domain.

National MOH and health sector reports

This indicator reflects the national capacity for synthesis, analysis and validation of health data, specifically RH data, and can be used to establish a baseline and to monitor progress. A well-functioning national health information system (HIS) that provides sound and reliable information is the foundation of decision-making across all aspects of the health system.  The HIS collects data from health and other relevant sectors, analyses the data, ensures overall quality, relevance and timeliness, and converts the data into information for decision-making and planning. Quality health statistics analysis and reporting are essential for all aspects of HSS, from health system policy development and implementation, governance and regulation, health research, human resources development, health education and training, to service delivery and financing.  Few developing countries have sufficiently strong and effective health information systems to meet all the varied needs for health information. New technologies can contribute to improving data generation, compilation and information exchange, however, these technologies also require detailed quality standards to be of optimal value. Strengthening national HIS capacity and RH health data quality and utilization are fundamental to the achievement of the health-related Millennium Development Goals: #4 reduce child mortality; #5 improve maternal health; and # 6 combat HIV/AIDS, tuberculosis and malaria.

The existence of a mechanism for RH data analysis does not necessarily mean that the body charged with the task is operating effectively and efficiently. In many countries, health sector reform and decentralization have brought about shifts in functions between the central, district and local levels that have created new information needs with changing requirements for data collection, processing, analysis and dissemination. Moreover, health sector reforms can increase the need for standardization and quality information.

management

Organization for Economic Cooperation and Development (OECD), 2003, Quality dimensions, core values for OECD statistics and procedures for planning and evaluating statistical activities. Paris: OECD. http://www.oecd.org/dataoecd/26/38/21687665.pdf (accessed 1 April 2010).

United Nations Statistics Division. Fundamental principles of official statistics. New York: United Nations, 1994. http://unstats.un.org/unsd/dnss/gp/fundprinciples.aspx

USAID, 2009, Measuring the Impact of Health Systems Strengthening, A Review of the Literature, Washington, DC: USAID. https://www.researchgate.net/publication/274064201_Measuring_the_Impact_of_Health_Systems_Strengthening_A_Review_of_the_Literature

WHO, 2010, Monitoring the building blocks of health systems: a handbook of indicators and their measurement strategies, Geneva: WHO. http://www.who.int/healthinfo/systems/WHO_MBHSS_2010_full_web.pdf

WHO, 2007, Strengthening Country Health Information Systems: Assessment and Monitoring Tool Version 2.0, Geneva: WHO Health Metrics Network http://www.hrhresourcecenter.org/node/747

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