Ghana Case Study on Ageing Final.Pdf

Table of Contents Page

CHAPTER ONE 2 INTRODUCTION 2 1.1 Background 2 1.2 Objectives 4 1.3 Global Trends in Ageing Populations 4 1.4 Madrid International Plan of Action 5 1.5 Global Strategy and Action Plan on Ageing and Health 5 1.6 Ghana’s Position on the Global Strategy 6 1.7 Review of Policies on Ageing 7 1.8 Review of Ghana’s National Policy on Ageing 7 1.9 National Social Protection Policies for Older People 8 1.10 Understanding Ageing-Related Issues 9 1.11 Methodology for the Case Study 9 CHAPTER TWO 11 EVIDENCE OF EXISTING DATA 11 2.0 Introduction 11 2.1 Study on Global Ageing and Adult Health (SAGE) 11 2.2 Ghana Health Service Data 17 2.3 Social Security and National Insurance Trust Data 19 2.4 National Health Insurance Authority Data 20 2.5 Livelihood Empowerment Against Poverty (LEAP) Programme 22 2.6 Ghana Living Standard Survey 24 2.7 2010 Population and Housing Census Data 26 CHAPTER THREE 30 ASSESSMENT OF EXISTING DATA 30 Introduction 30 CHAPTER FOUR 32 IMPROVING THE USE OF EXISTING DATA 32 4.0 Introduction 32 4.1 Illustration of the Use of SAGE Data: 32

4.2 Illustration of the Use of NHIA Data 33 4.3 Illustration of the Use of SSNIT Data 33 4.4 Illustration of the Use of Census and GLSS6 Data 33 CHAPTER FIVE 35 ENCOURAGING THE USE OF DATA – IN THE FUTURE 35 CHAPTER SIX 36 CONCLUSION AND RECOMMENDATIONS 36 6.0 Introduction 36 6.1 Strength of the Data 36 6.2 Recommendation – Strengthening Capacity for Data Collection and Collation 37 Appendix A 39 Contributors to Ghana's Case Study on Ageing 39 Reviewers of Case Study 39 Appendix B 41 Health Insurance Registration Data 42 References 43

CHAPTER ONE

INTRODUCTION 1.1 Background The population of older adults is increasing in all regions of the world although at a varying pace. The global population of people aged 60 years and older has increased from 382 million in 1980 to 962 million in 2017 (United Nations, 2017). It is projected that the population of older adults (60 years and older) will account for about one-fifth (22%) of the world population by 2050 (World Health Organization, 2018). In the short term, it is estimated that globally the number of older people aged 60 years and older will outnumber the number of children under five by 2020 (World Health Organization, 2018). The absolute and relative increase in the population of older adults has occurred at a varying pace across different regions of the world. Population ageing is more advanced in countries such as Japan (United Nations, 2015). While countries such as France have had nearly 150 years to adjust to changes in the population structure as a result of ageing, developing countries such as India and China will have just about 20 years to make the necessary adjustments (World Health Organization, 2018). The World Health Organization estimates that “in 2050 80 % of older people will be living in low-and middle-income countries”. Although the African region is regarded as a youthful continent, the population of older persons in the region is increasing. The population of older persons in sub-Saharan Africa has doubled between 1990 and 2015, increasing from 23 million to 46 million (United Nations, 2016). It is projected that sub-Saharan Africa will experience a fast growth in the population of older adults (64%) over the next 15 years (United Nations, 2015) with a projected increase to 161 million by 2050 (United Nations, 2016). In spite of the rapid rate of population ageing in the sub-Saharan African region as a whole, the extent of population ageing varies markedly from country to country. While countries such as Mauritius have about 15 % of their population being older adults, in Senegal, older adults constitute about 11 % of the population whereas countries such as Uganda have less than 4 % of the total population being older adults (United Nations, 2016). The population of Ghana, like other African countries has seen an increase in the absolute number of older adults. Data from the 2010 Population and Housing Census indicates that the population of older adults has increased about sevenfold; from 215,258 in 1960 to 1,643,978 in 2010 (National

Population Council, 2014). It is projected that the population of older adults in Ghana will increase to 2.3 million in 2025 and 5.6 million by 2050 (Ghana Statistical Service, 2014) as illustrated in Table 1.

Table 1: Actual and projected population of older adults (60 years and older) in Ghana, 1960 - 2050

While on the one hand, the success of population ageing at the global, regional and national levels can be attributed to increasing longevity, improvement in health and socio-economic conditions, on the other hand, the increasing number of older adults presents challenges for the health and social wellbeing of older adults especially in the sub-Saharan Africa region. Older adults in sub- Saharan Africa face numerous social, economic and health challenges. For example, older adults in many sub-Saharan African countries do not receive social pensions except in a few countries such as South Africa. Additionally, health insurance coverage specifically for older adults is not available in many African countries except Ghana and Senegal (Parmar et al., 2014; Pham, 2017). Furthermore, Ghana has instituted the livelihood empowerment against poverty cash transfer programme that targets households with older adults as eligible beneficiaries (Pham, 2017). In spite of the implementation of the aforementioned social protection programmes for older adults in Ghana, there has not been a holistic assessment of the situation of older adults in the country.

1.2 Objectives This case study seeks to provide empirical evidence in support of identifying and improving national efforts to build and strengthen local and sub-national data collection systems, establish linkages across sectors, and promote co-production, analysis and use of data by a wide range of stakeholders, including older adults themselves.

1.3 Global Trends in Ageing Populations In this current age, most people are expected to live beyond 60 years and by 2050, 1 in 5 people will be 60 years or older (WHO, 2017). Although the growth in the population of older adults is global in nature, it is more prominent in certain regions. Both developed and developing countries populations are ageing, however, the growth is much more evident in developing countries. Between 2000 and 2015, developing countries experienced over 60% growth in the population of older people and the projected growth between 2015 and 2030 stands at 71%. For developed countries, the growth in the population of older adults between 2000 and 2015 stood at 29% and it is expected to grow by 26% between 2015 and 2030. In the sub-Saharan Africa region, the population of older adults 60 years and older doubled between 1990 and 2015 – increasing from 23 million in 1990 to 46 million in 2015 (United Nations, 2016). The population of older adults in sub-Saharan Africa is projected to further increase to 161 million in 2050. The World Health Organization estimates that the projected number of older adults (60 years and older) in Africa in 2050 will constitute about 10% of the population of Africa.

1.4 Madrid International Plan of Action The Madrid International Plan of Action on Ageing (MIPAA) is a United Nation (UN) document on population ageing adopted at the Second World Health Assembly on Ageing in April 2002 to replace the earlier Vienna International Plan of Action on Ageing. The MIPAA was adopted to guide global policies on ageing for the current century. The main feature of the MIPAA was the society for all ages concept and its thematic foundation. The first draft had two parts: the long-term strategy on ageing, as the preamble to the draft Plan of Action; and the main body of the draft revised Plan. The latter identified three priority directions for policy action: (i) sustaining development in an ageing world; (ii) advancing health and well-being into old age; and (iii) ensuring enabling and supportive environments for all ages. The Madrid Action Plan was followed by the development of an African Union Policy framework and Plan of Action on Ageing (AU/HAI, 2003). This is in sharp contrast with the period of the first UN International Plan of Action on Aging. At the time, much of the continent was not aware of the burgeoning demographic revolution (Apt, 2012).

In Ghana, there is considerable interest in ageing. The government has responded to the issue with germane policies and programmes to address ageing-related challenges. Firstly, Ghana has an ageing policy dubbed “Ageing with Security and Dignity” that focuses on challenges spanning housing, health, poverty, and gender dynamics of ageing in Ghana (Ministry of Employment and Social Welfare, 2010). Other policies formulated to address the issue include the National Social Protection Strategy (which includes the Livelihood Empowerment against Poverty (LEAP)), Ghana National Disability and National Health Insurance Scheme (NHIS), albeit not solely directed to older adults. Although Ghana has pockets of policies, initiatives and directions on ageing, there is no harmonization of the various policies, strategies or interventions. Consequently, the full potential of these policies and interventions for the health and wellbeing of older adults is not being realized.

1.5 Global Strategy and Action Plan on Ageing and Health Population ageing is a global phenomenon and all countries including low-and-middle income countries are being entreated to ensure that the health and wellbeing of older adults is addressed in national development plans. The Global Strategy and Action Plan on Ageing envisions “a world in which everyone can live a long and healthy life” and the African Regional Framework on Ageing also envisions a region “in which everyone can live a long, healthy and productive life” (WHO, 2019). The African Regional framework aims to; by 2020, increase awareness and accelerate actions for healthy ageing in the African Region and establish evidence and partnerships necessary to support a Decade of Healthy Ageing from 2020 to 2030. In line with the global and regional action plans aimed at ensuring healthy ageing, the government of Ghana is committed to establishing frameworks for formulating structures geared toward the promotion of; a. an age-friendly environment b. research-based policy initiatives c. enhanced engagement with the ageing community d. awareness creation on healthy ageing e. establishment of systems that align well with the context-specific needs of the older generation f. enduring and sustainable care plans in the long term and

g. efficient feedback loop through research, monitoring and evaluation.

1.6 Ghana’s Position on the Global Strategy As the coordinating agency for Ghana on this “Healthy Ageing Case Study”, the Ghana Statistical Service has adopted a multi-sectoral approach to understanding the phenomena of “Healthy Ageing”. Stakeholders from Academia, Ministries, Departments and Agencies, Civil Society Organizations and Representatives of donor-support agencies, were collectively involved in developing the most reflective strategy that will ensure healthy ageing for all. The case study seeks to take stock of where Ghana is in terms of the situation of older adults, where we want to go with issues regarding older adults and how the intended goals and targets can be achieved. Given the right resources and leverage, Ghana is committed to pursuing these strategies aimed at addressing the needs of older adults. In the national effort to ensure “leaving-no-one-behind” in the implementation of the SDGs and Ghana’s development framework, the multi-stakeholder team is committed to drawing policy makers’ attention through publication of various ageing related statistical products by 2021.

1.7 Review of Policies on Ageing The change in demographics has implications for several sectors of the various world economies and raises challenges for policy makers. Institutions such as the African Development Bank (Governors Consultative Meeting, 2018) describe this situation as a “ticking time bomb” especially for developing economies where policy formulation and implementation continues to lag behind. Governments must therefore rise to the challenge and implement policies that will deal with the situation of population ageing. These policies need to address every aspect of the lives and wellbeing of older adults. Additionally, policies that address population ageing need to consider the impacts of these policies on the larger policy framework of every country targeting areas such as the social, economic, psychological and political dimensions of population ageing. Such a broad policy outlook is important because population ageing is integral to national development. The government of Ghana recognizes the importance of population ageing for national development. Ghana has thus developed national policies and implemented social protection programmes/projects that seek to cater for the needs of older adults. For instance, the 1992 Constitution of Ghana, the Ghana Shared Growth and Development Agenda 2010-2013, the

National Population Policy (Revised Edition, 1994), the National Ageing Policy (2010), the National Health Insurance Act 2003 (Act 650), and the National Social Protection Strategy all seek to address the needs of older adults in Ghana. The enrolment of older adults 70 years and above on the National Health Insurance Scheme and the provision of cash grants to poor households with older adults under the Livelihood Empowerment Against Poverty (LEAP) programme are all examples of the government of Ghana’s commitment towards ensuring the health and wellbeing of older adults.

1.8 Review of Ghana’s National Policy on Ageing Population policies are integral to efforts that influence people’s behaviours and demographic trends (May, 2012). The population structure of any country is influenced by the three components of demographic change, i.e. fertility, mortality and migration (both internal and international). The interplay between these three components of population change has significant consequences for present and future population structure and socio-economic development. For example, after World War II, fertility and mortality were documented to be very high in developing countries and it was realized that reducing fertility levels was essential to improving socio-economic development (Kwankye & Cofie, 2015). This consequently led to the adoption of population policies in some African countries. Ghana was the third country after Mauritius and Kenya to adopt a comprehensive population policy titled “Population Planning for National Progress and Prosperity in 1969 (Republic of Ghana, 1969). The population growth rate in Ghana between 1960 and 1970 was high at 2.4% per annum. The 1969 population policy thus aimed to reduce the population growth rate. However, the implementation of the policy was met with failure as it did not reduce fertility rates as expected. By the early 1990s, the country’s fertility rate had toppled that of the previous rate, reaching almost 3% per annum. Some of the problems encountered in the implementation of the policy included the pervasiveness of cultural beliefs about having many children, lack of commitment from successive governments, overburdened health systems required to provide family planning services, and neglect of men and rural-dwellers in the family planning approach. Therefore, in 1994, the first population policy was replaced by the Revised Population Policy. The revised policy and action plans were formulated within the context of economic growth and sustainable development. It had fourteen goals, summarized into two overarching goals:

i. a national population policy and programme are to be developed as organic parts of the social and economic planning and development and ii. Measures will be undertaken to improve the standards of living and quality of life of the people (Government of Ghana, 1994, p. 25). The specific targets included the reduction of total fertility rate from 5.5 per woman to 5.0 by the year 2000, 4.0 by 2010 and 3.0 by 2020. Additionally, it was projected that the use of contraceptives will reach 15% by 2000, 28% in 2010 and 50% in 2020. So far there have been some gains made: fertility and mortality have declined steadily.

1.9 National Social Protection Policies for Older People Over the last two decades Ghana has implemented a number of social protection policies, some of which target older adults in particular. An example is the social health insurance for older adults implemented under the National Health Insurance Scheme (NHIS). Ghana’s NHIS grants a premium exemption for older adults who are 70 years and older. The exemption allows older adults to register for health insurance under the NHIS without having to pay a premium they are however, required to pay registration and annual renewal fees.

Ghana also operates a national pension scheme which is currently being operated on a three-tier pension system. It involves a voluntary and a non-voluntary component. The involuntary component is the first and second tier while the voluntary component is the third tier. Formal sectors workers are compulsorily enrolled on the tier I and tier II schemes while the tier III is which is voluntary, is open to all. The totality of contributions for the pension scheme is 18.5% (5.5% employee and 13% employer). Out of the total 18.5% contribution, 13.5% goes to tier I and 5% goes tier II. The third tier is the voluntary scheme and is open to all.

1.10 Understanding Ageing-Related Issues Globally, researchers who study ageing have used different research methods to understand the phenomena. Such methods include cohort studies, randomized control trials and systematic reviews and such research have been carried by experts in specific fields including anthropology, gerontology, psychology, sociology, social work, public health and social policy. There has been limited research on population ageing in Ghana and older people have been under-represented in research, policy and discussions on national development discourse. Evidence from existing research on population ageing gives indication of the use of two main research approaches to

understanding ageing; qualitative and quantitative (Apt, 1993; 2016; Mba, 2010). These two approaches are relevant to addressing the multifaceted needs of older people in Ghana. These research approaches help to unearth and understand the social, mental, physical, psychological and economic aspects of the ageing process. To a large extent, research on ageing is at a fledgling state and researchers are progressing toward unravelling what may or may not work in Ghana. In line with Olsen (2004), using qualitative and quantitative approaches together throws light on seemingly new and developing social phenomena. Creswell (2009) mentions that quantitative data in itself provides baseline information and offers researchers the opportunity to appreciate the superficial statistical significance or otherwise of the data. On the other hand, the use of qualitative data aids in understanding a particular phenomenon and offer clarifications for quantitative findings. In chapter two of this report, an attempt is made to highlight available data set in Ghana on Ageing. The data sets are described by underscoring the agency from which data is gathered, the purpose, age bracket of participants of interest, and the method utilized in sourcing respective data.

1.11 Methodology for the Case Study A participatory approach was employed in developing this case study. Different stakeholders were engaged in an inception meeting to develop the case study on data, evidence and information on healthy ageing in Ghana. Subsequently, several meetings were held to better understand the evidence available with each institution and develop a roadmap for the case study. The team continued to engage both physically and virtually to complete the case study. Experts from WHO Headquarters in Geneva and from the Ghana Office participated in the first engagement. The following institutions were represented: Ghana Statistical Service (GSS) - the lead institution Ghana Health Service (GHS) Ministry of Health (MoH) National Population Council (NPC) National Development Planning Commission (NDPC) Ministry of Planning (MoP) Ministry of Gender, Children and Social Protection (MoGCSP) National Health Insurance Authority (NHIA)

Department of Psychology, University of Ghana Regional Institute for Population Studies, University of Ghana (RIPS) Ministry of Local Government and Rural Development (MoLGRD) Social Security and National Insurance Trust (SSNIT) Ministry of Food and Agriculture (MoFA) HelpAge Ghana Rights and Responsibilities Initiatives, Ghana University of Ghana Medical School. Department of Community Health The Center for Ageing studies, University of Ghana

The Ghana Statistical Service provided secretarial support throughout the development of this case study.

CHAPTER TWO

EVIDENCE OF EXISTING DATA 2.0 Introduction The importance of data, information and evidence to optimize healthy ageing cannot be over emphasized. Person-centred information on determinants and levels of intrinsic capacities and functional ability, disaggregated by geographic and socio-economic characteristics of the population, including by age and sex groups, is needed to support action and inform policy and decision making in multiple sectors and with multiple stakeholders.

This chapter explores what data sources are available and to what extent these data sources cover issues of older adults in the country. Particularly, the chapter examines data from Ghana Health Service (GHS), the WHO Study on Global Ageing and Adult Health (SAGE), the National Health Insurance Authority (NHIA), the Social Security and National Insurance Trust (SSNIT), the Ghana National Household Registry and Livelihood (GNHR), the Ghana Living Standards Survey (GLSS) and the Population and Housing Census (PHC).

2.1 Study on Global Ageing and Adult Health (SAGE) Background: The World Health Organization’s Study on Global Ageing and Adult Health (SAGE) aims to address the gap in reliable data and scientific knowledge on ageing and health in low and middle-income countries (Kowal et al., 2012). The study evolved from the 2003 World Health Survey (WHS), otherwise known as wave 0, which was an organized effort of WHO, the Ministries of Health of the various countries involved in the study and the University of Ghana Medical School, through the Department of Community Health, in the case of Ghana. SAGE is a longitudinal study with nationally representative samples of persons aged 50 years and above in China, Ghana, India, Mexico, Russia and South Africa, with a smaller sample of adults aged 18– 49 years in each country for comparisons. Data collection instruments are compatible with other large high-income country longitudinal studies on ageing. Wave 1 was conducted during 2007– 2010 and included a total of 34,124 respondents aged 50 years and older and 8,340 respondents aged 18–49 years. In four countries, a subsample consisting of 8,160 respondents participated in Wave 1 and the World Health Survey (SAGE Wave 0). Wave 2 data collection was conducted in 2012 and 2013, following up all Wave 1 respondents. Wave 2 data is however not publically

available yet. Data collection for Wave 3 of SAGE is currently on-going. SAGE is committed to the public release of study instruments, protocols and meta and micro-data: access is provided upon completion of a user’s Agreement available through the WHO SAGE website (www.who.int/healthinfo/systems/sage) and WHO’s archive using the National Data Archive application: (http://apps.who.int/healthinfo/systems/surveydata). Data from waves 0 and 1 can be accessed via the website on written request.

The SAGE study in Ghana was conducted a collaborative effort between WHO, the Ministry of Health through the National Health Research and the Department of Community Health at the University of Ghana Medical School.

The SAGE study in Ghana uses a longitudinal study design with cohorts derived from the world health survey of 2003. The study has so far been implemented in 6 countries were national samples have been drawn using probabilistic sampling techniques. Study Population: In Ghana, all the 6000 households from the WHS made up of 20 households from the 300 enumeration areas formed the primary sampling units (PSU) Sampling Design: The sampling method used for SAGE Wave 1 was based on the design for the world Health survey. It used a multistage sampling approach, in which the primary sampling units (PSUs) were stratified by region and location (Rural/urban). Selection of the PSUs was based on proportion allocation by size, with each Enumeration Area (EA) independently selected within each stratum. In the WHS/SAGE Wave 0, a total of 6000 households were interviewed and therefore 300 EAs were selected nationwide with twenty households randomly selected in each EA using systematic sampling. The number of EAs per region was based on the population size of the region. For SAGE Wave 1, a total of 5000 older adults (50 years and older) and 1000 young adults (18–49 years) was required. As such 250 EAs out of the 298 EAs of the WHS/ SAGE Wave 0 were used based on the availability of respondents aged 50+ years within the EAs. Enumeration areas with no 50+ individuals were excluded (WHO, 2007). Within each EA, 20 households with one or more 50+ individuals and four households with members aged 18–49 were selected. All respondents aged 50+ within households from the WHS were automatically selected and additional households with members aged 50+ years were randomly selected to make a total of 20 households for each EA. The four households of the 18–

49 years age group were randomly selected from the WHS/SAGE Wave 0 households list per EA. All the 50+ year olds within the selected households were interviewed together with the four identified under-50 respondents. Field work and data entry were undertaken between May 2007 and June 2008. All data in tables are from this period, unless otherwise indicated.

Data Collection Technique: A total of 30 interviewers and supervisors were trained in two phases. Initially, the full survey team was trained for 10 days centrally in Accra with support from WHO Geneva. Three teams were subsequently formed and assigned to regions and then were retrained in the field. Data collection was done manually during face-to-face interviews in respondents’ homes. In urban areas, some respondents were contacted by telephone for re-contacts. A team consisted of four interviewers and one supervisor assigned to one PSU. Each interviewer was to complete interviews with two respondents per day, and was to approach households up to three times to locate respondents. The supervisors conducted editing and also completed the blood sample collection, blood pressure measurements and spirometry. Re-test interviews were to be done within seven days. The location’s GPS data were taken in front of respondents’ houses with a minimum of five satellites available to be accepted for readings to be accurate. These geo-data could be used for future analysis (for example, distance to health care facilities, finding respondents for the next round of data collection, finding respondents for validation studies/ sub- studies). Completed questionnaires were organized and documented centrally before data entry. Two centres were organized in Ghana for data entry and then the final product was transferred to Geneva. Table 1. Description of Households and Individual Questionnaires Questionnaire type Domain Wave1 Measure Household Household identification, Identification and contact contact and sampling details details; structure of households, dwelling characteristics, improved water, sanitation and cooking facilities Transfers and support Family, community and networks Government assistance into

and out of the household; informal personal care provision Assets, income and List of households assets, expenditure sources and amount of household income; improved household expenditure on food, goods and services, health care Household care and health Persons in household needing insurance care; mandatory and voluntary health insurance coverage Individual Socio-demographic Sex, Age, Marital status, characteristics education, Ethnicity, Religion, languages spoken, etc. Work history and Benefits Length of time worked, reason for not working, type of employment, mode of payment, hours worked and retirement Health status and descriptions Anthropometrics, performance tests and biomarkers Risk factors and preventive health behaviours. Chronic conditions and health services coverage. Health care utilization

Social cohesion Subjective wellbeing and quality of life Impact of caregiving

Data Collection Tools: This involved questionnaires, health and biomarker measurements. Questionnaires: Six types of questionnaires were used in the SAGE study: The household questionnaire, individual, proxy, proxy validation, re-test and mortality questionnaires. The respondents were selected in advance and interviewers visited their homes for interviews and measurements. A household questionnaire and individual questionnaire were administered to each respondent. In following up households reporting death(s) in the past two years, a verbal questionnaire was completed. If a respondent was found to be incapable of answering the individual questionnaire, a proxy questionnaire was completed. Within a PSU, two respondents were to be randomly selected for re-test and one for proxy validation. In all, each PSU was to have 20 completed interviews for 50+ years respondents (household and individual), four interviews for the 18-49 years respondents, two re-test questionnaires, one proxy validation questionnaire and verbal autopsy questionnaires where applicable. One of the 251 selected PSUs was not used. This was because the EA which was expected to be located at Korle Bu Teaching hospital could not be traced. The household and individual questionnaires were translated into two dominant local languages (Akan and Ga) and used for training. Back translations were also done before use. However, the questionnaire used for the survey was printed in English. Interviewers were given appendices to illustrate various items, response options and concepts. In addition, instruments for blood pressure, height, weight, waist and hip measurements, spirometry, visual acuity (near and distance using tum-bling E charts), and stopwatches (to time measured walk) were provided. Blood spots were obtained via finger prick, labelled and stored for future analyses. Health and Biomarker Measurements: In addition to self-reports on health and well-being, direct health examination and biomarker measurements (blood samples, anthropometric measurements and performance tests) were included in the survey.

Ethics: Informed consent was obtained from each respondent for interviews, measurements and blood samples. Survey metrics and data quality: for Wave 0, were generated for all 70 participating countries, including Ghana. Survey metrics for the new modules/questions in Wave 1 were generated, along with an assessment of accuracy of age reporting and response rates as a measure of the representativeness of the population of interest. Strengths This is the first longitudinal study on health and ageing in multiple low and middle-income countries. The six surveys including that of Ghana have nationally representative samples yielding results that are comparable to those of similar ageing surveys in high-income countries. Initial response rates were fairly good. GPS coordinates have been taken from all households in order to reduce problems of finding households. The study is a collaboration between the WHO and a leading research institutions in the respective countries, with variable levels of involvement of the national health authorities. In Ghana, the main research institution involved in the study is the community health department of the University of Ghana Medical School. The local research institution is particularly critical to the overall success and strategic use of the results. The collection of a range of biological and clinical markers in addition to a very comprehensive interview is an asset (He et al., 2007). The SAGE collaborations with local health and demographic surveillance studies or systems provide an opportunity to link non-fatal health outcomes data to information from demographic surveillance, such as risk factors, mortality and migration, and track these populations over time. Data from these sites and systems can be compared with SAGE national samples in China, Ghana, India and South Africa to assess plausibility of findings, as well as to generate new hypotheses that can be more intensively studied using surveillance field sites before incorporating these components into future rounds of SAGE in national samples. Weaknesses The major weakness of the study is those related to the potential high attrition rates that often characterize national longitudinal sample surveys. Secondly, possible fatigue of the respondents. The duration of the interview was long (mean time for Wave 1 was 2.5 hours), as multiple dimensions of health and well-being are measured, which may be particularly demanding for both respondents and interviewers. This may affect the data

quality, although no systematic problems have been detected so far. In several countries, urban dwellers more often refused to participate in the survey, as is the case in other population surveys internationally. All countries in future waves of SAGE will use CAPI, which will improve efficiency in terms of sample and data management. Information from earlier waves will be preloaded in the CAPI for respondents who are being followed up and consistency checks will be carried out in future rounds. Data Completeness The SAGE data has a National representativeness based on the regional population and rural- urban population sizes. There is also data on verbal autopsy for all deaths within 24 months in the household. Other household data include household care and health insurance, assets, income and expenditure as well as transfers and supports system.

2.2 Ghana Health Service Data Background of Hosting Agency The Ghana Health Service (GHS) is an autonomous Executive Agency responsible for implementation of national policies under the control of the Minister for Health (MoH) through its governing Council - the Ghana Health Service Council. It was established in 1996 through an Act of Parliamentary (Act 525) and works in liaison with the Ministry of Health. MoH Operates a decentralized system at five levels: National, Regional, District, Sub- District and Community. GHS is authorized by MOH to collect, collate and report on all routine health services including health service data from Mission, Private and Quasi-government health facilities everywhere in the country.

Primary Data All service delivery points generate essential routine service data on health service utilization, morbidity and disease patterns. Such data are very useful to health managers at all levels for planning, budgeting and decision-making. Routine service data also feed into the Health Sectors’ monitoring and evaluation system for analysis and dissemination of results. Thus helping to reflect and judge performance, and highlighting weak areas for strengthening intervention programmes. GHS Collaborated with the University of Oslo to develop a software called the District Health Information Management System (DHIMSII). DHIMSII is a comprehensive HMIS solution for

the reporting and analysis needs of district health administrations and health facilities at every level. It provides a comprehensive HMIS solution based on data warehousing principles and a modular structure which can easily be customized to the needs of different health systems - national, regions, districts, and facilities. Data is collected mainly from people who visit the health facility, as such does not include people who do not access health services. The data may not be the representative of the entire population.

Secondary Data and Relevance The DHIMS data is a comprehensive health data source with varied health conditions data of the population from national, regional and sub-regional levels. Its crosscutting issues allows for programmes and projects to be developed and implemented to address health challenges of people at all levels. A Person-centred information on determinants of health of older adults can be easily achieved with the DHIMSII data. The person centred variables include age, sex, diagnosis, cause of death etc. The proportion of older adults by age can be generated based on total attendance to health facilities for any given period. Additional information on occupation, religion, marital status, place of residence can be obtained from the patients’ registers. However, there is no formal documentation on the process of using data from the DHIMSII for programming or interventions for older adults. Method

The DHIMSII data is an online data system which allows authorized personnel to input directly daily health data collected from health facilities. It is customized to replicate paper forms – to simplify the process of data entry. DHIMSII is accessible in all districts and is being used by health facilities and district health directorates to collect, collate, transmit and analyze routine health service data The DHIMSII captures data on all persons who access services whether they are insured or pay out of pocket. The GHS captures basic client/patient data, as well as data pertaining to their symptoms, conditions, diagnoses etc. when they visit health facilities.

2.3 Social Security and National Insurance Trust Data Introduction The Social Security and National Insurance Trust (SSNIT) or the Trust, is a statutory public Trust charged with the administration of Ghana’s National Pension Scheme. The Trust is currently the largest non-bank financial institution in the country. The primary responsibility of the Scheme is to replace part of lost income due to Old Age (as a result of retirement from active work), Invalidity, or loss of life. The Pension Scheme administered by SSNIT has a registered membership of approximately one million, six hundred and twenty-five thousand, two hundred and fifty-five (1,625, 255) with two hundred and fifteen thousand, eight hundred and fifty (215,850) pensioners who currently collect their monthly pension from SSNIT. These are made up both public and private formal sector works as well a few informal sector workers. The Social Security and National Insurance Trust or the Trust, was established in 1972 under the NRCD 127 to administer the National Social Security Scheme. Prior to 1972, the Scheme was administered jointly by the then Department of Pensions and the State Insurance Corporation from 1965. The Social Security Law (PNDC Law 247) under which the current Social Security Scheme operates was passed in 1991. Until 1991, the Trust administered a provident fund, and was converted into the Pension Scheme. In 2008, a new law which the National Pensions Act, Act 766 was promulgated which brought to being the Three Tier Pension Scheme that started operating in 2010 where SSNIT is mandated to manage only the First Tier.

The Core Functions of SSNIT SSNIT performs a lot of functions but the core ones among them are those listed below: • Registration of employers and employees • Collection of Social Security Revenues • Managing records of members • Managing the funds of the Scheme • Processing and paying benefits to eligible members and declared nominees.

The areas of interest for this exercise are the registration of employees and the management of their records. In the registration of employees, the following information on the employees are collected; • Name, • Date of birth • Place of birth • Date joined scheme or date one commenced working • Name of employer (establishment) • Salary at first point of employment • Parental details • Nominees (next of kin) In managing the records, information such as Name, Employer, Salary and nominees can be updated or changed while the rest cannot change, especially the date of birth. Additional information which is collected throughout the working life of all members of the scheme and managed as well, are the financial data. It must well be emphasized that though, the above mentioned data are collected at the very beginning of the working life of a member, they are not used in any way to monitor their conditions of life as they age. The essence of undertaking the above mentioned set of activities is basically to collect contributions, manage the funds therein and then pay benefits as and when they fall due (being Old Age, Invalidity of Death). Another set of data that is collected usually at the tail end is when a pensioner dies. As a means of verifying the death, the causes of death are also captured and recorded in the database as part of the investigations conducted to confirm the death of a member of the scheme. This information is actually not used for any particular agenda afterwards by SSNIT. At the moment the cause of death data from SSNIT does not inform vital registration.

2.4 National Health Insurance Authority Data Introduction The National Health Insurance Scheme (NHIS) was established by an Act of Parliament in 2003 to provide financial risk protection against the cost of basic health care services. The Scheme is a major social intervention policy of the government to ensure unhindered access to healthcare for all residents especially the poor and vulnerable. The National Health Insurance Authority (NHIA)

is the Agency responsible for the implementation of the NHIS. The objective of NHIA is to attain Universal Health Coverage in relation to persons’ resident in the country and persons who are not resident but who are on a visit to the country. As at 31st December 2019, about 12.3 million Ghanaians, representing 41% of the population had enrolled onto the scheme. The NHIS also has a network of over 4,500 credentialed healthcare providers across the country to improve geographical access to healthcare by members.

Exemption Policy As a major social intervention programme of the government of Ghana, the NHIS exempt over 60% of its members from payment of annual premium. Exempted members include children below the age of 18 years, SSNIT Contributors, SSNIT Pensioners, older adults 70 years and above who are not SSNIT contributors, pregnant women, and the indigent (core poor). Only informal sector workers pay annual premium to the scheme. Benefit Package The NHIS benefit package covers about 95% of all disease conditions in Ghana. This include, Out Patient Department, In – Patient Department, medicines on NHIS medicines list and investigations. Other specialized services such as maternal care, dental cares and eye care are also covered. The benefit is the same for all members irrespective of individual member’s contribution into the NHIS fund. Primary Data and Mandate The NHIA is mandated to register and issue unique membership ID cards to members (including the aged) to enable them access health care. Biometric data on individuals are collected by staff at NHIA district offices before ID cards are issued. Secondary Data Data on health service utilization and claims are generated by credentialed Service Providers and submitted to NHIA on monthly basis for vetting and payment. Claims data are submitted either electronically or manually. Currently about 75% of claims are submitted and vetted manually (partly because some health facilities do not have electronic systems) with the remaining 25% of claims vetted electronically.

Method Membership data collected at the district offices go directly to a central database of the NHIA and is managed by MIS Directorate of NHIA. Also, all claims are sent to NHIA Claims Processing Centers in Accra, Kumasi, Cape Coast and Tamale for vetting and forwarded to Finance for payment to credentialed providers. There are still some health facilities in Ashanti Region yet to be consolidated to CPC Kumasi.

Limitations/Challenges with the Data The NHIA captures data on persons who register with the scheme. The data therefore excludes the aged who are not registered members of the scheme. Even though the scheme is free for older adults 70+ years (they do not pay premium), a person needs to register by paying processing fees to be part of it. In essence, the scheme does not have data on older persons who are not registered.

2.5 Livelihood Empowerment Against Poverty (LEAP) Programme Background The Livelihood Empowerment Against Poverty (LEAP) Programme is both a conditional and unconditional cash transfer. The programme aims to empower the extremely poor, disadvantaged and the vulnerable in society to come out of poverty thereby, fostering long term human capital development. Target beneficiary household include households with Orphans and Vulnerable Children (OVC), older adults aged 65 years and older, pregnant/women with children under one without support and disabled persons without productive capacity). The overall objective of the LEAP Programme is to reduce poverty by increasing consumption and promoting access to services and opportunities among the extreme poor and vulnerable. The LEAP Programme uses categorical targeting. The Common Targeting Mechanism is used to select potential beneficiaries. This mechanism has been agreed to by five (5) other government ministries, specifically Ministry of Gender Children and Social Protection (MoGCSP), Ministry of Health (MoH), Ministry of Education (MoE), Ministry of Finance (MoF) and Ministry of Local Government and Rural Development (MLGRD).

The Common Targeting Mechanism used to select potential beneficiary households employs the following approach;

i. Geographic Selection ii. Public information and communication iii. Proxy Means Testing

The household data is collected on all household members. However, having an older adult aged 65 years and above is one of the eligibility criteria for the extremely poor household to qualify. LEAP data on older adults is collected as part of the general data for all potential beneficiary households. The range of analysis, however covers older adults 60 years and above and this includes other household members who might not be benefiting directing from the LEAP programme.

The LEAP data is not nationally representative of older adults in Ghana although the data is collected in all the 16 regions and 260 districts in the country. This is because, the programs targets extremely poor households, which may or may not include older adults. In so doing, many of the older adults in the LEAP communities may be left out as the baseline criterion for the selection of the house is first extremely poor before the other categories such as having an older adult are considered. The targeting process was guided by annual targets determined by the Ministry of Gender, Children and Social Protection based on available or anticipated resources. Allocations are made to beneficiaries across all sixteen regions using Regional Poverty Quotas. Majority of the older adults in LEAP have been identified to be females who are the caregivers while the males are heads of the households. Analysis of the educational background of the older adults indicates high levels of illiteracy.

One of the strengths of the LEAP data is that, the data can be used to provide information on older adults that receives social interventions and their poverty levels as well. In terms of limitations, the programme is not able to determine the age at death and data from LEAP can only be used for households that have older adults.

2.6 Ghana Living Standard Survey Primary Data and Mandate The Living Standards Measurement Study (LSMS), customized by implementing countries, including Ghana (Ghana Living Standards Survey), is a research project that was initiated in 1980 by the Policy Research Division of the World Bank. The objective of the project is to make relevant data on socio-economic development indicators available for policy makers to measure socio- economic development and analyze their determinants. The Living Standards Survey is conducted every 5-7 years. The 6th round of the survey covered a nationally representative sample of 18,000 households in 1,200 enumeration areas. Of the 18,000 households, 16,772 were successfully enumerated leading to a response rate of 93.2 % (GLSS 6, 2012/13). The 7th round of GLSS was implemented from October 2016 to October 2017. The GLSS 7 survey collected information from 16,000 households with a 93% response rate. Detailed information was collected on the demographic characteristics of households as well as, indicators on education, health, employment, migration and tourism, housing conditions, household agriculture, household expenditure and income (including components such as access to financial services, credit and assets).

Secondary Data and Relevance The GLSS data is a rich source of multidisciplinary data and its application is useful for many areas of study. It covers crosscutting issues and allows for programmes and projects to be developed and implemented to address challenges in the various sectors of the economy. Data from the Living Standards Surveys have, therefore, made it possible to provide valuable insights into the living conditions of developing countries including. Person-centred information on determinants and levels of intrinsic capacities and functional ability, disaggregated by geographic and socio-economic characteristics such as age and sex can be obtained from the GLSS data. Intrinsic capabilities measured in the GLSS data include disability status (in terms of vision, hearing, and mobility) of every household member 3 years or older. Some areas of functional ability covered by the GLSS data is the health status of every household member. Specifically, if any member was sick or injured in the previous two weeks and if they accessed health services, time spent, cost, satisfaction with service; for those who did not access health services, why they did not access healthcare services.

Methods The Ghana Living Standards Surveys (GLSS 6 & 7), was designed to provide nationally and regionally representative indicators. A two-stage probability sampling design was used to select households for the surveys. A representative sample for all regions as well as rural-urban areas was selected to constitute the sample for the survey.

Detailed information was collected on key elements of socio-economic life using the following questionnaires:

o Household Questionnaire o Non-farm Household Questionnaire o Community Questionnaire o Governance, Peace and Security Questionnaire o Prices of Food and Non-food Items Questionnaire

Reflectivity on Ageing The Ghana National Ageing policy sought to among others reduce poverty among older adults, improve health, nutrition and wellbeing of older adults, as well as improve the housing and living environment of older adults. Again, other policy dimensions of the National Ageing Policy are to strengthen family and communities to provide adequate support to older adults and improving income security and enhanced social welfare. The GLSS data through the use of the Household Questionnaire collected information on seven sections namely: demographic characteristics of respondents; education and skills training; health and fertility behaviour; employment; time use (GLSS6 only); migration and tourism; household agriculture; housing and housing conditions. In addition, age and sex data for each member of the household was collected. Therefore, routine information needed on everyone – to promote healthy ageing across the life course and general information – that is needed specifically on older adults, and further disaggregated by single age and sex can be sourced from the GLSS data. Additionally, the GLSS collected detailed information on the health conditions of all household members. Data on health conditions in the two weeks preceding the interview are good sources of information on the health and wellbeing of older adults.

Limitations and Challenges 1. Firstly, although the GLSS data can be disaggregated by several characteristics such as age, sex, disability status, occupation and education among others, some indicators cannot be disaggregated largely due to the fact that data on important variables such as housing, access to financial service are collected at the household rather than the individual level. One major policy dimension of the Ageing policy is to reduce poverty among older adults. However, the Ghana Poverty Profile which is produced out of the GLSS data falls short of measuring poverty among older adults. This is because the lowest unit of disaggregation for all indicators of poverty including the poverty index is at the household, rural/urban, district and regional levels. Other important policy measures of the ageing policy such as housing and income security cannot be measured using the GLSS data because information are collected at the household level and not at the individual level. 2. Secondly, the GLSS survey is a cross sectional survey and therefore does not allow for follow-ups on selected individual. This is very necessary in studying lifelong changes which is important in studying healthy ageing. 3. Thirdly, because the GLSS is cross-sectional, data from other sources cannot be linked to it for further analysis. At best, it can only be compared with previous GLSS data since the GLSS surveys used the same methodology.

2.7 2010 Population and Housing Census Data Primary Data and Mandate (2010 Population and Housing Census) The Population and Housing Census is a complete enumeration of the population of Ghana. The PHC is conducted on a decennial basis and implemented by the Ghana Statistical Service. The population and housing census has been conducted since 1960. The most recent census was conducted in 2010 with 26th September designated as the census night. The census provides benchmark data for policy and planning. Detailed analysis of the census data provides empirical data to enhance our understanding of the effectiveness of the various interventions implemented by the government and its collaborators to improve the lives of Ghanaians in general. Since the census collects data on every individual person in Ghana on the census night, the data can be used to track demographic and social indicators of all persons including older adults 60 year and older.

Secondary Data and Relevance The Census data is a rich source of data and provides indicators multiple dimensions of population and socio-economic development which can measure some indicators of population ageing at the national, regional, district and locality levels. The census data also serves as bench mark data for other surveys. Census data can be used to extrapolate survey data to the lowest unit of the country using small area estimation methods. For instance, the 2015 Poverty Mapping Report used the 2010 census and GLSS6 data to produce district level poverty estimates. The cross cutting nature of the census data allows for programmes and projects to be developed and implemented to address challenges in the various sectors of the economy such as education, economic activities, housing conditions, migration, dependency, mortality as well as social and demographic conditions of older adults among others.

Methods In the 2010 Population and Housing Census (PHC), people were enumerated at where they spent the census night (de facto) and not at where they usually resided (de jure). The de facto count was adopted because it is based on physical presence on a defined date and therefore it is simple, straightforward, and easy to interpret as well as minimizes the risks of under and over enumeration. The reference period, the census night, was fixed for 26th September 2010.

A special operation was carried out by staff of the census secretariat and regional statisticians to identify possible locations of out-door sleepers in major cities such as Accra, Kumasi, Tema, Sekondi-Takoradi and Tamale before the census night. Out-door sleepers (floating population) were enumerated on the census night by regional and district census officials using the census questionnaire (PHC1C). Following the census night on 26th September 2010, enumeration of household populations started on Monday, 27th September 2010 with visits to houses, compounds and structures in enumeration areas for a face-to-face interview with all households.

Reflectivity on Ageing The census questionnaire collected information on seven thematic areas namely: demographic characteristics of every individual; educational attainment, employment and unemployment; migration, disability status, mortality, housing and housing conditions. In addition, age and sex

data for each member of the household was collected. Therefore, routine information needed on everyone – to promote healthy ageing across the life course and general information – that is needed specifically on older ages, from age 50 years onwards disaggregated by age and sex can be sourced from the census data.

Uses of Census Data Census data are used for policy and planning, administration, research, business, electoral boundary delimitation and generating the sampling frame for surveys (United Nations, 2008). For instance, Section 47 (5) of the 1992 Constitution mandates the Electoral Commission to use census data as part of the political process. Institutions such as the Electoral Commission, National Health Insurance Authority and the National Identification Authority use census data to guide their activities. The decentralization policy pursued in the country also demands the use of census data at the lowest administrative level possible. Furthermore, students, researchers, the media and other data users depend on census data for their work.

The 2010 census data have been used to provide in-depth analyses of aspects of the population of Ghana and GSS looks forward to using the 2020 census data to assess progress made in Ghana’s development efforts. The following objectives of the national ageing policy can be measured using the census data; 1. Empower older persons to fully and effectively participate in the economic, social and political lives of their societies, including through income-generating and voluntary work; 2. Ensure commitment to gender equality among older persons through, inter alia, gender- based discrimination 3. Improving the housing and living environment of older persons 4. Achieve secure ageing, which involves reaffirming the goal of eradicating poverty in old age and building on the United Nations Principles for older persons Generally, the census provides bench mark data on several themes covering individuals, households and communities to better understand the environment, the social and economic conditions of the population including older adults.

Limitations and Challenges 1. The Census data is a snapshot cross sectional data gathered in a ten year interval and therefore does not allow for monitoring of the indicators during the inter-censual period.

CHAPTER THREE

ASSESSMENT OF EXISTING DATA Introduction This chapter contains an assessment of the available data sources capture in this case study. The assessment carried out considered both qualitative and quantitative assessment approached. Each data set was assessed using a set of questions and the objective was to ascertain the suitability of the data set in terms of these indicators;

▪ How complete are these data? ▪ Can a person-centered approach to healthy ageing be described, monitored and reported on? ▪ Can data sources from different sectors be linked? ▪ At what level and sub-groups can data be disaggregated? ▪ Do older adults use this information – themselves, or groups that represent them? ▪ Are there projections for the future? The results of the assessment is as contained in Table 1 below.

TABLE 1: SUMMARY: ASSESSMENT OF EXISTING DATA

DATA / COMP APPRO DATA LEVEL USAGE HOST PROJE YEARS LETEN ACH LINKA OF BY INSTIT CTION ESS TO GES DISAG OLDE UTION S AGEIN GREG R FOR G ATION ADUL THE TS FUTUR E SAGE Person Data No Universi A National centered can be Regiona directly ty of longitud ly approac linked l, observe Ghana inal data represen h to data Rural/U d usage Medical and only tative, from rban, by older School be covers NHIA, age, sex, adults compare many SSNIT, income d among variable DHIMS level, waves s of ethnicity measuri Ghana and ng all Health religion aspect Service of healthy ageing HEALTH Data is Person Data Used GHS Limited complet centered can be National CSOs projecti e and link , ons can national with Regiona be done ly NHIA l, Sub- represen data regional tative SNNIT Data is Person Can be Gender, N/A SSNIT Some incompl centered linked Age projecti ete. to Brackets ons can Limited NHIA and be made to only and Locatio but for registere GHS n SSNIT d data internal member use s only only. NHIA Data Person Can be N/A NHIA Limited limited centered linked Regiona projecti to active to l, Sub- on. For registere DHIMs regional internal d data of use only member GHS s of the NHIS only

LEAP/GNH Data is Person Can be Gender, No MoGCS Some R incompl centered linked Age direct P projecti ete to Brackets observat on can NHIA and ion of be made Locatio usage because n by older of its adults linkage to GSS data eg. Poverty data GLSS National Person Data Regiona No GSS No 2005, 2012, ly centered cannot l, directly projecti 2017 represen approac be Rural/U observe ons can tative h linked rban d usage be made but with by older on the limited other adults data in datasets variable because s it is measuri cross- ng all sectiona aspect l data of healthy ageing PHC Person Data No GSS No 2000/2010 National centered cannot Regiona directly projecti ly approac be l, Sub- observe ons can represen h linked Regiona d usage be made tative with l, by older on the but other Rural/U adults data limited datasets rban in because variable it is s cross- measuri sectiona ng all l data aspect of healthy ageing

CHAPTER FOUR

IMPROVING THE USE OF EXISTING DATA 4.0 Introduction This chapters seeks to highlight with illustration how existing data has been utilized by hosting agencies or other institutions/organization in decision making.

4.1 Illustration of the Use of SAGE Data: The SAGE data has been used as a source of secondary data for further analyses in the various aspects of ageing. The Ministry of Health adopted the wave 1 study in 2011 as the main policy on ageing and health for the Ministry and made some few policy changes, especially in the management of age-related health issues.

SAGE fed into or provided policy guide to the 2010 National Ageing with Dignity, with several publications with cogent recommendations for institutional and national use. The SAGE wave 1 affected a lot of policy changes for the aged. Notable amongst them was the subsequent review of the NHIS premium for the aged. This was stated in the Minister’s preface of the wave 1 national report in 2013. “The population of those aged 60 years and above in Ghana is projected to double from 6.0% in 2011 to 11.9% in 2050. Despite the increasing older adult population, the social and health care needs of this segment of the population have not received the attention it deserves” (1, page 4). The Minister added in his policy brief that, “These findings lend support for a specific national multi-sectoral policy on ageing”. He added that, the aged were not benefiting from the NHIS coverage as they should. He therefore advocated for more effort into streamlining the implementation of the NHIS so that the elderly population benefits (1, pages 3 -5)). “The recent passage of the Disability Law provides some social benefits for our aged population. Besides the recent passage of the Patient Charter, the Ministry of Health will continue to work to fill in the quality of care gaps so that health services become friendlier to the elderly populations in particular”. For wave 1, a number of analyses at the household and individual levels were done to inform the above policy recommendations. Analysis such as the income quintiles at household and individual levels were done to determine indicators such as the Human Development Index(HDI), other indicators of quality of life such as DALE, HALE were all estimated from the wave 1.

4.2 Illustration of the Use of NHIA Data The NHIA data on the aged may be used to determine disease conditions that affect older adults and the associated medicines for treatment. Again, the number of the aged enrolled provide valuable information about the extent to which the aged are protected against the cost of ill health. This information will enable policy makers formulate policies to support the aged and other vulnerable groups in the country. The data is used by the academia and other research institutions in conducting research on critical issues affecting the aged in Ghana. Utilization and membership data on the aged was part of data used by National Health Insurance Authority (NHIA) in 2019 to conduct actuarial evaluation of the sustainability of the NHIA. The data was used to analyze the relationship between disease burden and utilization. Based on the results, various scenarios have been developed for consideration by NHIA Board. The report will inform policy direction of the country as Ghana strives towards achieving Universal Health Coverage by 2030.

4.3 Illustration of the Use of SSNIT Data Currently, the data on pensioners (aged) is mainly used internally to monitor pensioners, especially those who are beyond 72/75 years of age (having exceeded the annuity period depending on the scheme type they belong – 72 for PNDCL 247 and 75 for Act 766). If a pensioner hits the aforementioned age(s), it means the pensioner has exhausted his entire annuity and as such when they die, their nominees are paid nothing. It is basically to ensure that pension payments to such deceased pensioners are ceased.

Secondly, pensioners along the line requested for a recreational facility to be built for them which was executed and handed over to them in the year 2011. With the current increase in the number of pensioners, further requests have come to construct similar centres at all regional capitals. The database of pensioners is helping in studying the viability and sustainability of such projects.

4.4 Illustration of the Use of Census and GLSS6 Data The Census data is a rich source of multidisciplinary data which can measure some indicators of the aged at the locality or district level and can be used to bench mark survey data. The 2010 Population and Housing Census collected data on single ages up to age 99. Therefore, the 2020

PHC is a rich database for analysis on older adults. Particularly, 2010 PHC report “the Elderly in Ghana (GSS, 2013) assess the ageing situation in Ghana and its implications for national development. Accordingly, the report examined the characteristics of the elderly in Ghana based on the 2010 Population and Housing Census (PHC). It also used data and other information from the previous post-independence censuses (1960, 1970, 1984 and 2000) and other secondary sources.

The analysis employed the functional age brackets: 60 - 74 (young-old), 75- 84 years (old-old) and 85+ years (very old). The report covered areas including social characteristics of the elderly, literacy and educational attainment, activity status of the elderly, disability and living conditions among others.

The report was a direct response to Ghana’s adoption of the National Ageing Policy for the country in July 2010 and was aimed at making available data on older adult to facilitate the implementation of the Ghana National Ageing policy. Other reports such as 2010 PHC report; Women and Men in Ghana (GSS, 2013), also provide perspectives into the distribution of population in the country and serves as a very useful data source for understanding issues concerning older adults in Ghana.

The Ghana Living Standard Survey, round 7 report (GSS, 2019), is the most current statistical data that can be used to provide analysis on older adults in Ghana. Detailed information on the Demographic characteristics of households, Education, Health, Employment, Migration and Tourism, Housing conditions, Household Agriculture, Household Expenditure, Income and their components and access to Financial Services, Credit and Assets can be analyzed for older adults since age data was collected in single ages.

CHAPTER FIVE

ENCOURAGING THE USE OF DATA – IN THE FUTURE For effective and efficient delivery of services, the health sector has a monitoring system in place to support evidence-based decision making and accountability; effectiveness of the sector responses to abnormalities from expected performance depends on its ability to analyse and use data on time. At the service delivery points, essential routine service data is generated on health service utilization, morbidity and disease patterns which is fed into the District Health Information Management System (DHIMS2).

The DHIMS2 offers a very comprehensive HMIS for reporting and analysis of district and health facilities at every level and can easily be customized to the needs of different health systems - national, regions, districts, and facilities. The DHIMS2 provides a useful source of health data of the population from national, regional and sub-regional levels. The system is such that a person- centered information on determinants of health of older adults can be easily achieved.

Routine health data remain very useful to health managers at all levels; for planning, budgeting, decision-making and collaboration with relevant sectors. Such data continually provide significant basis for the Health Sectors’ programme of work, monitoring and evaluation system for analysis and dissemination of results. Thus facilitating the assessment of the effective the efficient implementation of sector plans.

Evaluation of public health programmes are usually built into the programmes and remain an important part of the planning processes. The aim has always been to carry out a systematic assessment of the processes and/or outcomes of the interventions with the intent of furthering its development and improvement and also accounting for public health actions. Evaluation of the programmes usually provide findings which have enabled immediate, data-driven decisions for improving the interventions for maximum impact. The routine health data can be easily linked with NHIA. We have no clear evidence that older adults themselves utilize available dataset.

CHAPTER SIX

CONCLUSION AND RECOMMENDATIONS 6.0 Introduction This chapter discusses conclusions of the case study and submit some recommendations for consideration to further improve the generation and use of data on older adults. The concluding part focuses on the strength of available data in the country and the extent of use to inform policy formulation and discourse.

6.1 Strength of the Data The SAGE is a longitudinal survey conducted in a number of countries (China, Ghana, India, Mexico, Russian Federation and South Africa) that collect data on the health status of a sampled adult aged 50 years and above. Ghana has been involved in this study and has data from Wave zero to Wave four. This longitudinal survey data on the aged is nationally representative of the country and therefore covers all the indicators on the aged.

However, this data needs to be complimented with other survey data. For instance, the Ghana Living Standard Survey (GLSS) collected by the Ghana Statistical Survey (GSS). The GLSS data have the life cycle of five years from which data on the aged covering both health and demographic indicators can be obtained. This data is also nationally representative.

Ghana conducts a decennial Census and data on the health of the aged can be extracted for analysis and sense making. Given the availability of these three datasets, a comprehensive analysis on the aged can be done.

Furthermore, The National Health Insurance Scheme (NHIS) data has a comprehensive detailed diagnostics health status of the aged as well as data on the full cost of treatment. Also, data on the cause of death of pensioners who died before aged 72 years is currently available with the Social Security and National Insurance Trust. The data cannot give us the mortality rate, the health cost of the aged among others. Nevertheless, it can be supported by administratively gathered data.

6.1.1 Data Use There is evidence of dearth of the use of information contained in this dataset of the aged. This is largely attributed to the non - publication of reports on the aged and also due to lack of knowledge on the existence of the data.

Additionally, administrative data on the aged from Ministries, Agencies, Health care facilities and Departments are mostly used for internal purposes and analysis of the data for macro-level relevance has not been carried out due to lack of capacity among the personnel.

6.2 Recommendation – Strengthening Capacity for Data Collection and Collation All the datasets are sitting with the various Ministries, Departments and Agencies. There is the need to harmonize the database to enable all researchers to link up their datasets to one repository and this should be located within the GSS. This is because GSS already have SDG national reporting platform and will facilitate easy collation.

In addition to harmonization, the following are recommended to help strengthen data collection, collation among data producers

● MDAs producing administrative data be trained to analyze the data and prepare policy briefs for dissemination in the media to create awareness on the issues on ageing ● A technical team should be put together with clear objectives to use these three datasets to generate a report on the aged with derived estimates for the regions and districts.

● Furthermore, there is the need to conduct a qualitative data research on the aged to identify their intrinsic capacity and functional abilities of the aged and also challenges with respect to social integration and exclusion. This should also explore access to financial services to the aged.

● Moreover, a technical team be formed to develop a model on financial services and Information, communication and Technology which should be incorporated in both GLSS and SAGE data.

● Also, Ghana should have a decennial comprehensive survey on the aged after every census. The essence of this data will be to cover the gaps identified in GLSS, Sage and administrative data sets as well as social exclusion, preferably a year after the census. Given that Ghana is due to conduct the next census in 2020, the target year will then be 2021

● Advocacy on the use of the data for policy making is low among decision makers. In view of that, regular presentations be made to parliamentary select committees, cabinet ministers and ministers responsible for matters of keen interest to older adults.

● Ghana Statistical Service should take the lead role to prepare a compendium and Standard Operating Practices (SOPs) on the concepts and analysis of the aged which should be disseminated among all stakeholders.

Appendix A Contributors to Ghana's Case Study on Ageing Name Institution Mr Ebenezer Teye-Mensah Social Security and National Insurance Trust Dept. of Psychology/Centre for Ageing Studies, University of Dr. Collins Badu Agyemang Ghana, Legon Dr. Isaac Adomako School of Public Health, Univ. of Ghana Regional Institute for Population Studies, Dr. Fadilia Dake University of Ghana Dr. Yaa Asante Ghana Health Service Mr Collins Akuamoah National Health Insurance Scheme Mr Francis Soetor-Akatsa National Population Council

Mr Felix Logah Ministry of Gender, Children and Social protection Mr Joshua Addae Ministry of Planning Mr Ebenezer Adjetey- Sorsey HelpAge Ghana Mr Philip Acheampong Ministry of Planning Mr Omar Seidu Ghana Statistical Service Mr Anthony Amuzu Pharin Ghana Statistical Service Mr Jeremiah Sixtus Dery Ghana Statistical Service Mrs Jane Geraldo-Acolatse Ghana Statistical Service Mr Samuel Tetteh Ghana Statistical Service

Reviewers of Case Study Name Institution Dept. of Psychology/Centre for Ageing, University of Ghana, Dr. Collins Badu Agyemang Legon Dr. Isaac Adomako School of Public Health, Univ. of Ghana Regional Institute for Population Studies, Dr. Fadilia Dake University of Ghana Mr Ebenezer Teye-Mensah Social Security and National Insurance Trust Dr. Yaa Asante Ghana health Service Mr Collins Akuamoah National Health Insurance Scheme Mr Omar Seidu Ghana Statistical service Mr Jeremiah Sixtus Dery Ghana Statistical service Jane Geraldo-Acolatse Ghana Statistical service

Appendix B %Age of older adults, 60 years and above, registered onto the National Health Insurance Scheme for 2017 and 2018 2017 2018 Fe male Male Fe male Male Region NHIS Projected NHIS Projected NHIS Projected NHIS Projected Percent Percent Percent Percent Registered Population Registered Population Registered Population Registered Population Ashanti 122,660 175,430 69.9 66,559 144,943 45.9 127,632 179,097 71.3 69,394 148,768 46.6 Brong Ahafo 70,155 86,634 81.0 40,304 74,966 53.8 75,125 88,338 85.0 42,649 76,875 55.5 Central 53,603 104358 51.4 28,226 75956 37.2 54,717 104,981 52.1 28,546 77,287 36.9 Eastern 95,160 130,928 72.7 52,999 107,401 49.3 97,259 133,531 72.8 53,461 110,219 48.5 Greater Accra 88,121 131,610 67.0 54,536 116,562 46.8 89,149 134,687 66.2 54,180 119,748 45.2 Northern 44,136 88,854 49.7 24,965 86,676 28.8 43,453 90,724 47.9 23,789 88,819 26.8 Upper East 45,359 60,308 75.2 18,963 47,285 40.1 46,782 61,589 76.0 19,296 48,410 39.9 Upper West 24,247 36,732 66.0 11,811 29,130 40.5 26,564 37,500 70.8 12,753 29,839 42.7 Volta 69,760 120,159 58.1 35,843 90,582 39.6 71,380 122,504 58.3 36,281 92,897 39.1 Western 46,638 83,611 55.8 30,809 75,442 40.8 48,358 85,433 56.6 31,077 77,487 40.1 Total Country 659,839 1,018,624 64.8 365,015 848,943 43.0 680,419 1,038,384 65.5 371,426 870,349 42.7

Note: At the time of the GLSS7 in 2017 not persons who had registered were covered either due to expired membership or in the process of renewal

Health Insurance Registration Data

References Ghana Statistical Service, 2019. Ghana Living Standard Survey Round 7 Main Report.

Ghana Statistical Service, 2014. Ghana Living Standard Survey Round 6 Main Report.

Ghana Statistical Service, 2013. Population & Housing Census Report.

Ghana Statistical Service, 2013. 2010 Population and Housing Report: The Elderly in Ghana

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