Statistics refers to both quantitative data, and the classification of such data in accordance with probability theory and the application to them of methods such as hypothesis testing. Health statistics include both empirical data and estimates related to health, such as mortality, morbidity, risk factors, health service coverage, and health systems. Health statistics are numbers about some aspect of health. Statistics about births, deaths, marriages, and divorces are sometimes called “vital statistics.” Researchers use statistics to see patterns of diseases in groups of people. This can help in figuring out who is at risk for certain diseases, finding ways to control diseases and deciding which diseases should be studied. Health Statistics is a branch of official statistics that is mainly meant to cater to the needs of statisticians, professional and institutional users of official statistics.
Apart from administrative data on health related parameters, it also covers measures, estimates and counts derived from survey and census results. Health statistics are crucial for decision making at all levels of health care systems. It facilitates better decisions in policy design, health planning, management, monitoring and evaluation of programmes and services including patient care and facilitate improvements in overall health services performance and outcome. Health management information incorporates all the data needed by policy makers, clinicians and health service users to improve and protect population health. Health statistics measure health

⦁ Correlates
⦁ Conditions
⦁ Care
⦁ Consequences

International organizations like WHO considers health statistics as an important aspect in improving policies for life quality and health level
intervention. The production and dissemination of health statistics is a core WHO activity mandated to WHO by its Member States in its Constitution. WHO programmes compile and disseminate a broad range of statistics that play a key role in advocacy for health issues, monitoring and evaluation of health programmes and provision of technical assistance to countries

The World Health Organization has also duly emphasized that investment in Health Management Information Systems (HMIS) could reap multiple benefits such as:

⦁ helping decision makers to detect and control emerging and endemic health
problems, monitor progress towards health goals , and promote equity;
⦁ empowering individuals and communities with timely and understandable health related information, and drive improvements in quality of services;
· strengthening the evidence base for effective health policies , permitting evaluation of scale -up efforts , and enabling innovation through research and;
⦁ improving governance, mobilizing new resources and ensuring accountability in the way they are used

Health Statistics provide information for understanding, monitoring, improving and planning the use of resources to improve the lives of people, provide services and promote their well being.

The Importance of Health Data

Health statistics and data are important because they measure a wide range of health indicators for a community. A community can be ann entire nation, a region, state, county, or city. Health data provide comparisons for clinical studies, can be used to assess costs of health care, can help identify needed prevention targets for programs, and are important for programplanning and evaluation by finding a baseline against which to measure in the evaluation phase.

The Context of Health Statistics

Health statistics are influenced by an organization’s perspective and bias. These biases can affect the collection device and eventual outcomes that are reported. They also can determine what data are collected and how the data are collected. The populations covered by different data collections systems may not be the same. Some information is collected in more than one survey and estimates of the same statistic may vary among surveys.

Key Features of Health Statistics

Health statistics are population based, and many are collected and analyzed over time. Statistics often use geographic regions for determining health care coverage and comparisons of specific disease occurrences. Most studies focus on variation over time, space, and social group. Health statistics come from diverse sources. Many studies use administrative data which include enrollment or eligibility information, claims information, and managed care encounters. Surveys are designed to collect specific data and are often conducted by trained personnels.

Data Incorporated in Health Statistics

Health statistics incorporate a variety of data types. The most common statistics reported are vital (birth, death, marriage, divorce rates), morbidity (incidence of disease in a population) and mortality (the number of people who die of a certain disease compared with the total number of people). Other common statistical data reported are health care costs, the demographic distribution of disease based on geographic, ethnic, and gender variables, and data on the socioeconomic status and education of health care professionals.

Difficulties in Data Collection

⦁ Numerous state and local agencies in additional to not-for-profit organizations are involved in the collection and dissemination of health related data. As a result, there may be little to no data in some areas and duplication of data in others. There may also be variations between how data is collected and described between these various agencies.
⦁ Data collection on a national level takes money and staff to compile.
⦁ Absence of strict systematic scales and indexes might also posit problems.

Health indicators

Health indicators are quantifiable characteristics of a population which researchers use as supporting evidence for describing the health of a population. Typically, researchers will use a survey methodology to gather information about certain people, use statistics in an attempt to generalize the information collected to the entire population, then use the statistical analysis to make a statement about the health of the population. Health indicators are often used by governments to guide health care policy. A common example of a health indicator is life expectancy. A government might have a system for collecting information on each citizen’s age at the time of death. This data about age at death can be used to support statements about the national life expectancy, in which case life expectancy would be a health indicator. Life expectancy may be one of many health indicators which collectively researchers would use to describe the health of the population of the country.

Characteristics of Health Indicators

A health indicator which will be used internationally to describe global health should have the following characteristics:
1. It should be defined in such a way that it can be measured uniformly internationally.
2. It must have 2. statistical validity.
3. The indicator must be data which can feasibly be collected.
4. The analysis of the data must result in a recommendation on which people can make changes to improve health

List of Health Indicators
1. Mortality indicators

_Crude death rate
_Life expectancy
_Infant mortality rate
_Maternal mortality rate
_ Proportional mortality rate

2. Morbidity indicators

⦁ Prevalence
⦁ Incidence
⦁ Others

3. Health status(conditions)

Incidence counts of any of the following in a population may be health indicators:
⦁ Low ⦁ birth weight
_High blood pressure
_Cancer incidence
_Chronic pain
⦁ hospital visits due to ⦁ injury
⦁ reports of ⦁ waterborne diseases or ⦁ foodborne illness

4. Disability indicators

⦁ Disability adjusted life years (DALY)
⦁ Others: Activities of daily living (ADL), Musculoskeletal disability (MSD) score etc.

5. Nutritional indicators

⦁ Proportion of low birth weight
⦁ Prevalence of anaemia
⦁ Proportion of overweight individuals
⦁ Nutritional intake assessments

6. Social and mental health indicators

⦁ Alcohol related indicators
⦁ Injury rates

7. Health system indicators

⦁ Healthcare delivery related
⦁ Health policy indicators

8. Health Determinant

_Smoking habits
_alcohol consumption habits
_Physical exercise habits

Mortality and Morbidity as Key Health Indicators

Death is a unique and universal event. Age at death and cause provide an instant depiction of health status. In high mortality settings, information on trends of death (by causes) substantiate the progress of health programs. As survival improves with modernization and populations age, mortality measures do not give an adequate picture of a population’s health status. Indicators of morbidity such as the prevalence of chronic diseases and disabilities become more important. Major Sources of Mortality Information are National vital registration systems – a major source in developed countries, Sample registration systems (e.g., in China and India), Household surveys – to estimate infant and child mortality, Special longitudinal investigations (e.g., maternal mortality studies).

Morbidity data are widely used by epidemiologists in the analysis of ill-health within human populations. There are two major types of morbidity rate: the prevalence rate and the incidence rate. The prevalence rate gives an indication of the number of individuals in a population suffering from a particular condition at any time, while the incidence rate shows how many individuals develop a condition within a particular period of time, usually one year.

Morbidity rates are generally presented for specific conditions rather than as a general rate, and may be reported as absolute numbers within a year (for example 200 cases of rabies), or as incidence rates per thousand population, to facilitate comparisons between different sub-populations (such as sexes, age-groups, or occupations).

Major Sources of Mortality Data

a. Vital Registration or Vital Statistics Systems

Vital statistics are statistics on live births, deaths, fetal deaths, marriages and divorces. The most common way of collecting information on these events is through civil registration, an administrative system used by governments to record vital events which occur in their populations. It has a universal coverage of the population and has continuous operation. Data Collection for Vital Registration is usually done by a local registration office, usually a government agency.

Special Problems of Vital Registration in Developing Countries

⦁ Laws vary dramatically across the countries
⦁ Public compliance poor
⦁ Definitions of vital events varies
⦁ Inadequate resources
⦁ Lack of trained personnel to collect data
⦁ Data infrequently analyzed
⦁ Under utilization of data

b. National Sample Registration Systems

Systematic national household sample surveys to collect data on population and health began during early 1960’s to measure the demographic impact of family planning programs Family planning and population surveys are still the largest sources of data for health in developing countries sIn India data is collected through Sample Registration System (SRS) which began in 1964-65. A dual registration system for births and deaths exists. It also provides fertility and mortality estimates for every state and territory .

Measures of Mortality

a. Crude Death Rates
b. Age-Specific Death Rates
c. Life Table Estimates
–Life expectancy
–Survivorship (by age)
d. Cause-Specific Death Rates
e. Special Indicators
–Infant and maternal mortality rates

a. Crude Mortality Rate

It is defined as the number of deaths in a given year per 1000 mid-year population i.e.
No of deaths/year *1000
Mid-year population

b. Age Specific Death Rates

It is the number of deaths per year in a specific age (group) per 1000 persons in the age group is given as:
(Da/Pa) 1000

Where Da= Number of deaths in age group ‘a’
Pa= Midyear population in age group ‘a’

c. Life Tables

It is a powerful demographic tool used to simulate the lifetime mortality experience of a population, by taking that population’s age-specific death rates and applying them to a hypothetical population of 100,000 people born at the same time.

i. Life Expectancy

Estimate of the average number of additional years a person could expect to live if the age-specific death rates for a given year prevailed for rest of his or her life.

d. Cause Specific Deaths

It is defined as the number of deaths attributable to a particular cause c divided by population at risk , usually expressed in deaths per 100,000.

(Dc/P) * 100,000

e. Special Indicators

i. Infant Mortality Rate

It is defined as the number of deaths of infants under age 1 per year per 1000 live births in the same year.

No. of deaths of infants in a year * 1000
Total live births in that year
ii. Maternal Mortality Rate

Is is defined as the number of women who die as a result of complications of pregnancy or childbearing in a given year per 100,000 women of childbearing age in the population.

No of maternal deaths *100,00Is0

No of women aging 15-49

Sources of Morbidity Data

The main sources of disease-specific incidence and prevalence data are as follows:

i. Health interview surveys

– Cross-sectional population surveys
– Panel/cohort surveys

ii. Medical records / administrative statistics

– Hospital records
– Disease-specific registers
– Death registers
– General Practice (GP) records
– Administrative notifications

i. Survey data

Survey data tend to be used for producing estimates of prevalence rather than of incidence; Egidi (1996) argues that the sample size is usually too low for calculations of incidence to be made. Disease-specific morbidity data can be collected by different types of surveys, including health interview surveys (HIS), health and lifestyle surveys, multi-purpose surveys which include a health module, and surveys focusing on particular topics such as psychiatric morbidity, or disability.

ii. Medical records / administrative statistics

Medical records and administrative statistics provide information about the numbers of people with certain diseases/disorders. To calculate incidence and prevalence, all these sources must be supplemented with information about the base population, e.g. the numbers of people in a range of age and sex groups resident in a specified geographical area. These estimates may be derived, and updated, from sources such as censuses or population registers.

Uses of Morbidity and Mortality Data

I. Uses of Mortality Data
i. Population forecasting

Mortality is one of the three factors, the others being of life and, through links between morbidity and and migration, that determine changes in population size, distribution and structure. For most countries, mortality is the second most important factor after fertility in determining such changes at the national level. Population forecasting is essential for all long-term planning, and for much short-term and medium-term planning as well. Mortality rate data provides essential details to help in this process.

ii. Social description

Mortality levels are correctly regarded as indicators of the general welfare of a national population and its subgroups (they are clearly indicators of the quantity of life and, through links between morbidity and mortality, and reflect the quality of life within quantity). Summary measures of mortality conditions, such as life expectancy at birth or the infant mortality rate, are routinely included in indices of the quality of life – indices that are useful for charting socio-economic needs and for making international comparisons.

iii. Planning and Development

The first use of mortality information in the health sector is to identify high-mortality areas and high-risk groups within areas, so that health sector resources can be directed where they are needed and are likely to have most effect. It can further improve the efficiency of resource allocation in the health sector, particularly concerning causes of death.

iv. Evaluation of health services and programmes

The efficacy of general health services and of specific health programmes can be evaluated in terms of observed changes in mortality.

II. Uses of Morbidity Data
Uses of incidence-based statistics

⦁ Monitoring the distribution of new cases (or of all episodes) among different groups in a population, including monitoring progress towards targets
⦁ Identifying possible causes of a disease/disorder (etiological studies)
⦁ Studies of age at onset, and disease-free life expectancy
⦁ Evaluation of screening programmes
⦁ Analysis of alternative treatment/care regimes, and recovery rates

Uses of prevalence statistics

⦁ Monitoring the burden of disease on different groups of the population including monitoring progress towards targets.
⦁ Estimating the need for and use of care services