Research Methods for Developing Countries EpiHServ 539

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Research Methods for Developing
CountriesEpi/HServ 539

• Health Indicators
• Routine Health Data
• Stephen Gloyd
• January 2007

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WHAT ARE INDICATORS?

• reflection of a given situation (IMR, LE, years
  of educ)
• variables which help measure changes ( attended
  births, immunized)
• indirect and partial measures of a complex
  situation (IMR, U5MR, BRs)
• often a proxy (LBW, food prod)
• USED TO DEMONSTRATE HOW POLICIES CHANGE HEALTH
• yardsticks to measure progress
• measure of quality of life and development

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CHARACTERISTICS

• valid actually measure what supposed to
• objective same answer if measured by
  different people in similar circumstances
• sensitive sensitive to changes in the
  situation
• specific reflect changes only in the
  situation concerned
• In real life, few indicators comply with these
  criteria
• The feasibility (organizational, technical, and
  financial) of collecting and analyzing the
  information is the decisive factor

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Millennium Development Goals 1-4
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Millennium Development Goals 5-6

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Millennium Development Goal 7
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4 Categories of Indicators HFA 2000

• 1) Health Policy
• political commitment to HFA
• resource allocation
• degree of equity of distribution of health
  resources
• community involvement in attaining HFA
• organizational framework and managerial process
• 2) Socioeconomic
• rate of pop increase
• GNP/capita
• income distribution Gini coefficient
• work conditions
• adult literacy
• housing
• food avaiability
• 3) Health Care
• coverage by PHC
• coverave by referral system

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WHO GLOBAL INDICATORS

• HFA/MDG/PHC/IMAC as a policy endorsed at highest
  official level
• of national budget (or GDP) on health care
  (target 14)
• of health care spent on primary health care
• Equitable distribution of health facilities and
  staff
• Sustained support from affluent countries

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WHO GLOBAL INDICATORS (2)

• PHC available to the whole population, including
• safe water within 15 minutes from home
• immunization coverage gt 80 DPT3 by 12mo age
• local health care with gt20 essential drugs within
  one hour's walk
• trained personnel for attending pregnancy,
  childbirth, and for children up to one year
• The nutritional status of children is such that
• at least 90 of newborns weigh 2500g
• at least 90 of children have WFA over reference
• IMR for all subgroups is below 50/1000
• Life expectatcy gt 60
• Adult literacy for both men and women exceeds 70
• GNP/capita exceeds (US)500

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Indicators that I like

• of (estimated) pregnant women attending
  prenatal care
• births attended by trained personnel
  (institutional births)
• children 12-24 mo immunized against
  measles/DPT3
• children lt -2z Wt/Age, Ht/Age, Wt/Ht
• women of married women aged 15-49 currently
  using modern contraception
• TB patients who complete treatment
• children enrolled in primary (secondary) school
  (net or gross)

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UN indicators website

• WHO Indicators http//www.who.int/whosis/whostat20
  06DefinitionsAndMetadata.pdf
• MDG Indicators
• http//mdgs.un.org/unsd/mdg
• Others Unicef, UNDP, World Bank annual reports

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Obtaining data - trade-Offs

• Between what is relatively simple and cheap to
  collect and the degree of precision of the
  information and its validity.
• Remembering, the countries that most need
  information are usually those that are least able
  to obtain the information precisely
• Thus, a balance has to be struck between
• the allocation of resources to information
  collection for making priority decisions about
  alternative strategies and action
• and the allocation of resources to the programmes
  themselves.

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WHAT DEGREE OF PRECISION IS NECESSARY?

• varies by the indicator
• examples
• IMR - general magnitude
• Vaccine rates - to measure change (/- 10?)
• HIV-TB - measure changes and service burden

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WHAT DATA CAN YOU TRUST?

• Some characteristics which increase validity
• -based on 2 or more well-conducted studies
• big demographic studies (fertility studies
  are good and often available)
• published research
• -consistent with generally accepted data
• IMR, U5MR, Birth Rates
• Nutrition data (not easy to get)
• -consistency between routine service data and
  community collected data

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Other data characteristics

• Doesnt help much
• -consistent over time
• -formally presented
• Should make you suspicious
• -substantial differences from other published
  data
• -inconsistencies (time, between collectors,
  units)
• -sensitive information (regarding sexuality,
  religion, etc)
• -data from which someone may benefit

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SOURCES OF HEALTH DATA

• Vital events registers (continuous)
• Census housing and population (q 10 yrs)
• Sample surveys (e.g., DHS q 5 yrs)
• Administrative Data
• Epidemiologic surveillance systems (weekly)
• Disease registers
• Monthly reports (outpatient, inpatient, admin)

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VITAL EVENTS REGISTERS

• data births, deaths, marriages, adoptions
• individual - age/sex/ms/occ/res/natl
• event - date/time/place/cause/cer
  tified
• purpose administrative, e.g., disposal of
  bodies, inheritance, life insurance
• characteristics
• passive, continuous
• under or non-reporting
• lack of incentive, high cost to
  individual
• guilt, sensitivity to event
• don't know age, diagnosis, date, etc
  
• urban better than rural
• Latin America better, Africa worse
• few active systems(e.g., headman, teachers)
• sample registration systems - India
• limited areas
• cross check of reporting, HH surveys
• problem with size, migration,
  crosschecking

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CENSUS - POPULATION AND HOUSING

• data tot population, age structure,
  geographical dist
• complete survey
• purpose administrative, allocation of
  resources
• baseline data for all sectors
• characteristics
• usually censuses not from health sector
• once every 10 yrs
• migration, pop changes
• enumerators - training, time,
  incentives
• poor less visible

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SAMPLE SURVEYS

• data HH SES, environment information
• disease/death recall
• health service utilization
• purpose defined by surveyor
• characteristics
• most frequently resorted to when other sources
  are absent
• complement health service information
• usually household survey
• can be done by members of the community, school
  vacations

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World Health Survey (WHO)

• 70 countries
• HH, SES, Health status, Health Systems
  utilization information
• Data available end 2006

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DHS Surveys Demographic Health
Survey(Measure DHS - USAID)

• Focus on MCH, KAP, SES
• 70 countries (USAID Countries) rounds every 5
  years
• Over 200 surveys done
• Data available in reports data files for SPSS
• Newer surveys
• SPA service provision assessment
• AIS AIDS indicator surveys
• Qualitative surveys

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POPULATION SURVEILLANCE SYSTEMS

• purpose small area research/service projects
• varying purpose
• characteristics
• often are big studies
• often research emphasis
• fixed time period can be a problem
• periodic HH surveys, complementary Health
  System info
• often foreign dominated
• huge personnel, transportation costs
• precludes expansion to MOH
• OTHER SOURCES (including other sectors)
• members of the community to collect (CHW,
  TBA)
• schoolteachers, leaders, womens orgs

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Disease Registers

• Examples Cancer, Maternal Mortality, TB, HIV,
  Diabetes
• Usually hospital based, thus misses non-referred
  cases
• Good data on individual cases
• Useful for trends if methods and utilization
  patterns are consistent

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Routine Health System Data

• Purpose depends on activities
• to plan, evaluate (personnel and programs)
• Characteristics and concerns
• cheap, easy to collect
• utilization dependent
• big variation between facilities
• disease specific (diarrhea vs. malaria)

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Types of health system information

• examples
• a) patient charts (hospital, clinic, prenatal,
  wcc)
• clinical data, ommissions, legibility,
  organization
• info on clinical functioning of services,
  mortality
• b) routine monthly reports
• numbers visits, inpatients, services
• some diagnoses
• staffing
• c) routine epidemiologic surveillance data
• weekly, sporadic
• limited number of specific diseases
• endemic disease patterns, control measures
• needs to be representative to be useful
• d) inventory, accounting records
• staffing, transportation, structures
• pharmaceuticals
• financing
• e) disease registers
• underreporting

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Characteristics and concerns re Health Systems
Information

• Differences between govt/non-govt/traditional
  sectors
• referral difficulties - where to list people
• training, motivation dependent
• collection, aggregation, forwarding
• personnel changes, time limitation
• importance of supervision, feedback, relevance
• numerator-denominator mismatch
• under-reports morbidity and mortality
• over-reports health service activities

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Using routine data

• Compare with usually reliable data
• Institutional births, deaths
• Special studies
• Look for inconsistencies, surprises
• Usually related to data collection
• Dont invoke unusual theories without checking
  validity
• Avoid missed counts, double counting
• Sequential annual reports help
• Record monthly reports received

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Using routine data (2)

• Cross check
• e.g., births LBW, health cards prenatal care
  registers
• Disaggregate!
• Identify whether trends are with all facilities
  or just a few outliers
• Look for long term trends in disaggregates sites
• Clarify and validate denominators
• 1st Prenatal care is useful vs registries
• Identify community based denominators (e.g., EPI)

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Using routine data (3)

• Examine assumptions
• e.g., births LBW, health cards prenatal care
  registers
• When reporting
• Identify sources of data
• nutritional assessment Wt/Ht vs MUAC
• access to health care
• Explain your assessment of validity (accuracy and
  reliablity)