Category Archives: Service Provision Assessment (SPA)

10 Sep 2019

Nutrition in the Health System: Linking SPA and DHS Surveys

Global momentum on quality of care in the health system continues to expand. The United Nations Decade of Action on Nutrition (2016-2025) recognizes that the health system is a key pillar in providing universal coverage of essential nutrition actions. Reliable data for monitoring is central to understanding and improving the health system for nutrition. In addition to data from Health Management Information Systems, Service Provision Assessment (SPA) surveys also provide nationally representative facility information that can be used to explore the quality of facility-based health services.

­SPA surveys are a rich source of nutrition information providing insight on the availability and quality of services. Similarly, DHS surveys provide a significant amount of information about nutrition behaviors of populations. By linking SPA and DHS surveys, users can examine how the health facility environment contributes to these behaviors.

Two recently released DHS Working Papers examine the health service environment for key nutrition interventions: breastfeeding counseling and iron folic acid supplementation. The papers use Haiti and Malawi as case studies to describe the facility readiness, such as the availability of trained providers and essential medicines (see infographics below), and service delivery including observations of provider-client consultations of the two interventions in the context of antenatal care. The papers go on further to link SPA and DHS surveys to examine relationships between the health service environment and the nutrition behaviors.

The papers illustrate how linking SPA and DHS surveys can be useful for enhancing essential nutrition actions at the facility by identifying key programmatic gaps that can be strengthened to improve effective intervention coverage.

Download Working Papers 160 and 161 to find out more about the results in each country and their implications. And now, Analytical Briefs are available for DHS Program Analytical Reports. Download the Analytical Briefs for a shorter, more concise summary of these working papers.

Facility readiness to provide iron folic acid supplements
and counseling during antenatal care.



12 Jun 2019

Luminare: The Senegal Continuous Survey

This blog post is part of Luminare, our new blog series exploring innovative solutions to data collection, quality assurance, biomarker measurement, data use, and further analysis.


Two needs are often expressed by both DHS host countries and donors: 1) for data to be made available more frequently, and 2) for the continued strengthening of implementing agencies’ capacity to conduct surveys. Among various innovations that The DHS Program has pursued to respond to these needs is the Continuous Survey (CS) model.

What is a Continuous Survey?

In a CS, data are collected and reported annually by a permanently maintained office and field staff.  A smaller sample size is designed to provide estimates at the national level and for urban/rural residence every year. For regional-level estimates, data are pooled over multiple consecutive phases. Through both the smaller sample and continuously maintained staff, the model can lower costs and institutionalize the implementing agency’s ability to conduct a DHS survey. In 2004, Peru became the first country to conduct a CS, and the effort is still ongoing.

How did Senegal implement a Continuous Survey?

Inspired by the Peru experience, USAID and The DHS Program piloted the CS model in Africa. Senegal was chosen for its long survey history and the capacity of the local implementing agency, Agence Nationale de la Statistique et la Démographie (ANSD). The Senegal Continuous Survey (SCS) expanded on the original model to include an annual facility-based Continuous Service Provision Assessment (C-SPA), in addition to the household-based Continuous Demographic and Health Survey (C-DHS). The SCS was conducted in five phases, spanning the period from 2012 to 2018.

Covers from final reports from each of the five phases of the SCS.

What were the successes and challenges of the SCS?

ANSD partnered with Le Soleil newspaper to create an 8-page spread highlighting results from the 2016 SCS.

The SCS demonstrated many successes. Senegal is the only country in Africa to annually collect nationally representative demographic and health data, allowing Senegal to monitor progress towards the SDGs every year. This was also the first time a country releases both facility and household data at the same time. This model of releasing C-SPA data annually and in conjunction with the C-DHS resulted in flourishing data use for both surveys.

The SCS greatly strengthened capacity in Senegal. ANSD is now capable of conducting DHS and SPA surveys with only limited technical assistance. ANSD has the initiative to move beyond the pilot to implement the 2018 SCS with limited technical assistance and is already continuing the annual surveys.

Most surveys encounter challenges, and, in the Senegal experience, CS-specific design challenges emerged. Some stakeholders were concerned about the approach of pooling two consecutive years of CS data to generate a large enough sample size for regional-level estimates. Additionally, a census and an updated health facility master list in Senegal during the SCS pilot period resulted in new sampling frames for both the C-DHS and the C-SPA, and subsequent challenges in data interpretation. Finally, survey dissemination activities overlapped with the next phase’s design and implementation activities, increasing the burden on ANSD.

The CS model demands an overlap of activities. While one phase moves toward dissemination, planning is already occurring for the next phase of data collection, as evidenced in the SCS pilot experience.

Lessons learned from the SCS experience will inform The DHS Program’s continued efforts to innovate in the areas of data collection and use.

04 Apr 2019

Spotlight on Implementing Agencies: Democratic Republic of the Congo

In January 2019, The DHS Program welcomed visitors from the Democratic Republic of the Congo. This post is one in a series of interviews with visitors to DHS headquarters.

Don’t read French? You can use the translate feature at the top of the page!

Nom : Didine K. Kaba

Pays d’origine :  RĂ©publique DĂ©mocratique du Congo

Titre et organisation : Professeur (MD, PhD), DĂ©partement d’EpidĂ©miologie et Bio statistiques, Ecole de SantĂ© Publique de l’UniversitĂ© de Kinshasa

RĂŽle dans l’EPSS RDC 2017-2018 : Co-Investigateur de l’enquĂȘte


Vous pouvez nous raconter un peu sur votre expĂ©rience avec l’EPSS RDC 2017-2018 ?

C’est une enquĂȘte intĂ©ressante qui nous a permis d’auto Ă©valuer nos compĂ©tences dans la rĂ©alisation d’une enquĂȘte de grande envergure. Dans l’EPSS, il s’est agi d’un Ă©chantillon des formations sanitaires dissĂ©minĂ©es partout en RDC.

Le pays Ă©tant grand (26 provinces), les donnĂ©es ont Ă©tĂ© collectĂ©es par vague, qui a Ă©tĂ© dĂ©cidĂ©e afin de diminuer les sites de formation, permettre une bonne supervision des formations, et assurer ainsi la qualitĂ© des donnĂ©es.

Une autre chose que nous avons expĂ©rimentĂ©, c’est l’appropriation de l’enquĂȘte par le MinistĂšre de la SantĂ© Publique, prĂ©sent de l’adaptation des questionnaires jusqu’à la rĂ©daction du premier draft du rapport de l’enquĂȘte. Son implication Ă  tous les niveaux a facilitĂ© la tĂąche Ă  nos diffĂ©rentes Ă©quipes, plus particuliĂšrement Ă  celles chargĂ©es de la collecte des donnĂ©es.

L’EPSS RDC 2017-2018 est la premiĂšre EPSS en RDC. Vous pouvez commenter sur quelques dĂ©fis ou succĂšs spĂ©cifiques Ă  une telle enquĂȘte, surtout Ă©tant la premiĂšre expĂ©rience ?

Un dĂ©fi c’est l’immensitĂ© du pays, avec accĂšs trĂšs difficile dans l’arriĂšre-pays, sans compter le fait que des conflits armĂ©s Ă©taient encours dans le pays pendant la collecte des donnĂ©es. Au sein d’une mĂȘme province, le transport aĂ©rien Ă©tait parfois nĂ©cessaire pour accĂ©der Ă  des formations sanitaires soit sĂ©parĂ©es des autres par des champs de guerre ou alors d’accĂšs difficile par route. Nous disposions Ă©galement dans l’échantillon des formations sanitaires qui ne pouvaient ĂȘtre atteintes que par pirogue ou hors-bord. Ainsi, nous devrions d’une part respecter l’échantillon des formations sanitaires pour assurer la reprĂ©sentativitĂ© et d’autre part veiller Ă  la sĂ©curitĂ© des agents de collecte des donnĂ©es. Ce dĂ©fi a Ă©galement Ă©tĂ© relevĂ©. En effet, nous avons collectĂ© les donnĂ©es dans 1380 formations sanitaires sur les 1412, seuls deux pourcents de formations sanitaires n’ont pas Ă©tĂ© enquĂȘtĂ©es.

Comment espĂ©rez-vous que les donnĂ©es de l’EPSS RDC 2017-2018 soient utilisĂ©es ?

Ces donnĂ©es sont trĂšs importantes et trĂšs attendues dans le pays. Chaque programme s’intĂ©ressera aux donnĂ©es en lien avec son domaine d’intervention. Les donnĂ©es de cette Ă©valuation serviront Ă  l’identification des problĂšmes Ă  rĂ©soudre en vue de l’amĂ©lioration de la qualitĂ© de l’offre de service des soins en RDC.

Quelles sont d’autres leçons apprises ou pensĂ©es que vous aimeriez partager ?

  • Une autre procĂ©dure de rĂ©daction d’un rapport d’enquĂȘte : informations clĂ©s pour chaque chapitre, encadrĂ©s pour dĂ©finir chaque indicateur et commentaires par caractĂ©ristique de base ;
  • Maitrise de la formation des adultes/Andragogie : utilisĂ© dans la formation des agents de collecte des donnĂ©es ;
  • Analyse des Ă©ditions secondaires des donnĂ©es et des tableaux de qualitĂ© avec feedback vers les agents de terrain pour l’amĂ©lioration de la qualitĂ© des donnĂ©es collectĂ©es ;
  • La collaboration entre institutions et le fait d’avoir de la considĂ©ration des uns envers les autres au sein de l’équipe de recherche ont Ă©tĂ© le gage de la rĂ©ussite de l’EPSS RDC 2017-2018. Chaque membre de l’équipe de recherche (agent de collecte des donnĂ©es, facilitateurs/superviseurs, agent de saisie, Ă©quipe informatique, Ă©quipe de coordination, etc.) avait fait de cette enquĂȘte son affaire. Notre motivation Ă©tait la satisfaction de voir l’enquĂȘte se dĂ©rouler avec succĂšs. Oui, c’était ça la clĂ© de notre rĂ©ussite.

The 2017-18  Democratic Republic of the Congo SPA  was released on March 22, 2019.

Download the final report here.

© ICF

21 Mar 2019

DHS Data Users: Insights on Health System Quality from the Service Provision Assessments

© 2017 Magali Rochat/VectorWorks, Courtesy of Photoshare

This new blog series, DHS Data Users, captures examples of how you, the data user, have incorporated data from DHS, MIS, and/or SPA surveys into your analyses, at your institution, or to influence policies or programs. If you are interested in being featured in the ‘DHS Data Users’ blog series, let us know here by submitting your example of DHS Program data use. 


The year 2018 saw an upswell of interest in health system quality with the publication of three global reports highlighting critical deficits in quality in health systems in low- and middle-income countries [1,2,3]. Much of the empirical basis for these reports was drawn from the Service Provision Assessments (SPA), the lesser-known surveys conducted by The Demographic and Health Surveys (DHS) Program, which provide comprehensive assessments of health systems in low-resource settings from Haiti to Nepal.

These surveys include a detailed audit of facility resources, provider interviews, direct observations of primary care services, and exit interviews with patients or caretakers. Each assessment is a sample of the complete health system (public and private) or in some cases a complete census. The resulting wealth of data enables assessment of structural inputs to quality of care, the care process – both competent care and user experience – and some outcomes from care, primarily user confidence in the health system. A small but increasing number of researchers is delving into all the SPA data have to offer. Among the insights the SPA surveys have yielded just from my own research are:

  • Most health systems assessed are not fully prepared for basic health care.
    A comparative study of 8,443 facilities in 9 countries based on SPA surveys between 2007 and 2015 found that hospitals averaged between 69% (Senegal 2012-2014) and 82% (Tanzania 2015, Namibia 2009) on the service readiness index defined by the World Health Organization for primary health facilities. Non-hospitals achieved at best 68% readiness (Namibia 2009) and at worst only 41% (Uganda 2007, Bangladesh 2014) [4]. Within primary care services – antenatal care, family planning, and sick child care – service-specific service readiness is not highly predictive of competent care being delivered.
  • Across facilities with a similar level of readiness, provider adherence to clinical guidelines varied widely. Correlation between readiness and observed clinical quality was more consistent for observations of labor and delivery, though only two SPA surveys include these data [5].
  • In Kenya, where the 2010 SPA did include direct observation of labor and delivery, both structural quality of maternity care and observed clinical quality was higher in facilities in wealthier areas than facilities in poorer areas, with women in the poorest areas receiving care that complied with only half of recommended clinical guidelines on average [6].
  • Across 8 countries, adherence to clinical guidelines was lower in sick child care, where providers completed only 38% of the standard Integrated Management of Childhood Illness (IMCI) items, than in family planning (46%) and antenatal care (57%) [7]. The median sick child consultation lasted only 8 minutes [8]. Focusing specifically on Malawi, where the survey team conducted a limited re-examination of sick children, providers diagnosed pneumonia in only 1 in 5 children who showed symptoms of pneumonia per the IMCI guidelines [9].
  • Analysis of the 2013-2014 Malawi SPA survey with a simultaneous household survey suggested that poor quality care may contribute to avertable neonatal mortality, with a predicted prevalence of neonatal mortality of 28.3 deaths per 1,000 in lower quality facilities and 5.2 deaths per 1,000 in higher quality facilities, among women who would choose higher quality if it were more accessible to them [10].

As attention shifts from describing health system quality to improving it at scale, robust and ongoing measurement will be an essential tool for governments and researchers alike, particularly the direct observation of care delivery and perspective from patients themselves that makes the SPA such a unique and valuable resource.

References


Written by Dr. Hannah Leslie

Dr. Hannah Leslie is a Research Associate at the Harvard Chan School of Public Health; she served as the Measurement Research Lead for the Lancet Global Health Commission on High-Quality Health Systems in the SDG Era. She received her MPH and Ph.D. in Epidemiology from the University of California, Berkeley. Her research has made extensive use of the Service Provision Assessment surveys to 1) develop metrics of structure and process quality in LMICs, 2) describe current quality of care, and 3) assess predictors and effects of poor quality. Her recent work focuses on effective coverage calculations, patient experience measurement, and quality of care as a driver of HIV testing and treatment retention.

07 Apr 2016

Measuring health care: The Service Provision Assessment Survey

http://dhsprogram.com/publications/publication-SPA22-SPA-Final-Reports.cfm

When DHS and other population-based surveys indicate potential problems with a country’s health care systems, such questions are raised:

“Are certain services available in health facilities?”
“What is the quality of those services?”
“Are there factors at the service delivery level that could be contributing to the problems?”

The Service Provision Assessment (or SPA) survey attempts to bridge this gap while fulfilling the need to monitor health systems strengthening in surveyed countries.

Let’s say a national strategy is initiated to address a growing obesity problem and its associated issues, diabetes and hypertension. A component of the strategy may focus on improving a country’s health facilities by increasing the number that have diabetes services available.

2014-15 Tanzania SPA Key Findings

2014-15 Tanzania SPA Key Findings

It may also strengthen readiness of those facilities to provide quality services – more staff who are up-to-date on trainings for provision of diabetes services, more equipment (such as blood pressure apparatuses, adult weighing scales, and height boards), improved diagnostic capacity (the ability to conduct blood glucose and urine protein tests), and increased availability of medicines to manage diabetes. These are all indicators a SPA survey provides.

The improvements in service availability and readiness may lead to early identification of risk factors, early diagnosis and initiation of management, and, perhaps, a gradual decline in unmanaged diabetes.

2014-15 Tanzania SPA Key Findings video series
The SPA survey is designed to collect information from a sample of functioning health facilities in a country on the availability of services, readiness of facilities to provide health services in many areas, and measures of quality of care. Four different questionnaires are used to collect data at the facility, provider, and client levels. Survey data collection is done by teams of health workers.

If the DHS is a snapshot of a population’s health, the SPA is a snapshot of the service environment and those who provide and receive services, which drives population health. Though it can be challenging to directly link health facility data with population data, the SPA is useful in providing support and context to the DHS.

The first SPA surveys took place in Guatemala, Kenya, and Bangladesh in the late 1990’s, and continue to be implemented today. To date, 22 SPA surveys have been conducted, the latest being the 2014 Bangladesh Health Facilities Survey and 2014-15 Tanzania SPA. Ongoing surveys include the 2015 Nepal SPA and Senegal Continuous SPA. Be the first to know when those will be available (along with all other surveys) by signing up for email alerts, or by following us on Facebook and Twitter! 

The information provided on this Web site is not official U.S. Government information and does not represent the views or positions of the U.S. Agency for International Development or the U.S. Government.

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