DATA SOURCES BY DR. DC TSHIBANGU

1. DATA SOURCESBYDR. DC TSHIBANGU

2. SESSION OBJECTIVES • Define what is a health information system (HIS) and understand its components • Define routine health data/information • Discuss routine data collection methods • Define non-routine data • Discuss methods of collection for non-routine data

3. SESSION OBJECTIVES To help M & E OFFICERS to: • Appreciate the varied sources & forms of information on specific project/program/service • Develop a toolkit for thinking about the complexity of information and its uses • Assess the completeness, accuracy, relevance and timeliness of available information • Decide which types of information are most appropriate for a particular activity within a project/program • Make optimal use of information which is not ideal, and assess the effects of its departure from perfection

4. FROM REALITY TO ACTION Real world (Collection, coding) Data (Processing, interpretation, presentation) Information (Politics, commitment) Action Source: Oxford Handbook of Public Health Practice December 21, 2019 4

5. USE OF WORDS ‘DATA’ & ‘INFORMATION’ • DATUM(singular) or DATA(plural) refers to raw numbers or other measures, usually discrete and gives objective facts about events. • INFORMATIONrefers to what emerges whendata are processed, analyzed, interpreted and presented. Information isdata transformed (contextualized, categorized, corrected, calculated, condensed) into a message

6. WHEN TRANSFORMING DATA Always bear in mind the issues that affect the quality of the data: • Validity - are the data capturing the concept or quantity you intended? • Selection bias – where the data mislead because they are not representative of the population • Classification bias – where there is a non-random effect on putting data into groupings (non-blind assessments of any outcome)

7. KINDS OF DATA SOURCES In most countries, there are many different sources of information on any Specific project/program/service and different types of information vary in their C.A.R.T: • Completeness • Accuracy • Relevance and/or Representativeness • Timeliness DATA SOURCES also vary in the ease with which a base population can be identified, for use in the denominator, for calculating rates.

8. WHAT DOES THE DATA SOURCEDESCRIBE? This depends on the goals/ objectives of program and may include information such as: • Demographic & Socioeconomic features of the study-population:age, sex, education, occupation, mobility and geographical distribution. • Health status: health service use data(diagnoses, interventions, procedures, health outcomes of interventions), morbidity, mortality (TB, Malnutrition, HIV/AIDS, co-infections and OIs) • Programmatic:inputs, process, outputs, outcome & impact

9. HOW IS THE INFORMATION COLLECTED? Information can be Routineor Specially collected • Routine refers to collected, assembled, and made available regularly, according to well-defined protocols and standards. Such data are usually available at regular intervals They intend to allow tracking over time They are codified using national or international standards (ICD)

10. HOW IS THE INFORMATION COLLECTED? • Speciallycollected refers to collection for a particular purpose, without the intention of regular repetition or adherence to standards (other than those needed for the specific study or tasks); such data are usually: - aimed at a specific , time-limited study or tasks; - codified according to the goals in hand and the wishes of the investigators.

11. CLASSIFICATION OF INTRINSIC TYPES OF DATA Sometimes data are categorized as hard or soft: Hard data:are precise (or intend to be precise): They are often numerical; if not, then coded according to a protocol; They are reproducible, and likely to be similar even if the data collectors are varied.

12. CLASSIFICATION OF INTRINSIC TYPES OF DATA Soft data:tend to be: - qualitative, attempting to capture some of the subtlety of human experience; - often narrative or textual form, at least as they are collected; - Imbued with some subjectivity, due to the complexity of the personalities of the data collectors and the individuals studied.

13. THE UTILITY OF THE INFORMATION Neither hard nor softdata are intrinsically better than the other. The utility of the information (in terms of better decision making) often comes from combining the two: • Harder data usually allow more precise analysis and comparisons, but may fail to capture subtleties. • Softer data usually capture more of the ‘truth’ about the world, but often at the expense of emphasizing the uniqueness of the circumstances, and are less likely to allow comparisons and conclusions.

14. DATAWISE WHAT DO YOU NEED TO ASSESS? You need to assess ‘the fitness for purpose’ by asking the following question: Are the existing or proposed sources of data fit for the purpose for which they are intended, the conclusion to be drawn or the decision to be made?

15. KEY ISSUES FOR ASSESSING APPROPRIATENESSAND USEFULNESS OF DATA & DATA SOURCES Here are some guiding issues but none is absolute, and the balance of advantage & disadvantage must be assessed using judgment. • Technical issues - Are the definitions clear and appropriate? - Are the target and study population clear? - Are the data collection methods clear and sound? - How complete, accurate, relevant, and timely are the data? How much does this matter?

16. KEY ISSUES FOR ASSESSING APPROPRIATENESSAND USEFULNESS OF DATA & DATA SOURCES • Issues relating to outcome or decision involved - Is the study population sufficiently representative of the target population for the purpose of the decision? - Do you need absolute or relative estimates, to make the best decision ? - Would existing data source suffice, by using comparative data or by extrapolating with care? - Would qualitative information suffice, when habit automatically suggests quantitative data?

17. Health Information Systems (HIS) • Health system • All resources, organizations and actors that are involved in the regulation, financing, and provision of actions whose primary intent is to protect, promote or improve health.” (WHO, 2000) • Health Information System (HIS): • A system that provides specific information support to the decision-making process at each level of an organization (Hurtubise, 1984) • Similar to a health management information system (HMIS)

18. What is the problem with many existing routine health information systems (RHIS)? • Irrelevance and poor quality of the data collected • Fragmentation into “program- oriented” information systems: duplication and waste • Centralization of information management without feedback to lower levels • Poor and inadequately used health information system infrastructure

19. As a result… • Poor use of information by users at all levels: care providers as well as managers • “Block” between facility and community health information systems • Reliance on more expensive survey data collection methods

20. What characterizes a good HIS? • Regular production of good quality data • Continued use of health data for improving health system operations and health status.

21. What influences data quality and use? • Standard indicators • Data collection forms • Appropriate IT • Data presentation • Trained people Technical factors

22. What influences data quality and use? • Resources • Structure of the health system • Roles, and responsibilities • Organizational culture System and environment factors

23. What influences data quality and use? • Motivation • Attitudes and values • Confidence • Sense of responsibility Behavioral factors

24. SYNOPSIS OF SOME HEALTH & SOCIAL PROGRAMS • Malaria Program • TB Program • HIV Program • Nutrition Program • Family Planning Program • Immunization Program • Tobacco Prevention Program • Poverty Alleviation Program

25. M & E MANAGERS • Are likely to get involved in all or some of these programs • The selection/choice of appropriate Data Sources depends upon the type of program one is involved in. • Some selected examples are provided below:

26. M & E HIV/AIDS MANAGERS Are likely to get involved in • Preventive Programs and/or • Care & ART Programs and/or • Support Programs and The selection/choice of appropriate Data Sources is dictated by the type of HIV programs.

27. M & E POVERTY PROJECT MANAGERS Are likely to get involved in Designing and Implementing Poverty-targeted programs and The selection/choice of appropriate Data Sources depends on whether one needs to determine who should qualify for services and who should not. December 21, 2019 28

28. FIVE MINUTE EXERCISE • Choose any population/health/nutrition program • Define one objective of that program • List 3 data sources and 3 reasons why you have selected them

29. DATA SYSTEMS • TWO TYPES OF DATA SYSTEMS: • ROUTINE: Health information systems • NON-ROUTINE: - Surveys - Research programs

30. ROUTINE DATA SOURCES • Such as HIS (Health Information System) and its subsystems that are collected as part of an ongoing system

31. CHARACTERISTICS OF HIS • A health system is not a static phenomena. It is in a continuous process of change due to pressures from both outside and within the system • HIS is an integral part of the health system • HIS generates the data to measure the change of a health system

32. NON-ROUTINE DATA SOURCES Such as • DHS • Special Surveys • Program or Project Evaluation • Clinical trials • Epidemiological Surveys (Descriptive/Analytical)

33. Non-Routine Data Sources by Levels • Policy or program level • Facility/Service delivery point level • Client level • Population level

34. LEVELS OF INFORMATION WITHIN THE IDENTIFIED DATA SOURCES The next quest is to identified the level of information one is interested in within identified the Data sources • FIVE LEVELS OF DATA: 1. Policy or Program level 2. Population level 3. Service Environment level 4. Client level 5. Spatial/Geographic level

35. POLICY/PROGRAM LEVEL • This is policy/legislation formulation level, Sources of: - Official legislative & administrative documents - National budgets or other related data - Policy inquiries - Reputational rankings (program efforts scores) • Tools: - Indexing questionnaires (for country specialists and rankings) - Special/contract studies

36. FACILITY LEVEL • Facilities-services, infrastructure, etc. • Audits/inventories • Facility surveys • Health care providers, other staff • Performance reviews, competency measures • Training records

37. POPULATION LEVEL Where you need to know the size/composition of a population. Sources such as: - Population census bureau; - Sentinel surveillance systems - Vital statistics system (birth & death certificates) - Sample households or individuals; - Special population samples (demographic/occupational group, or geographic sector) Tools: - Birth/Death certificates - Census questionnaires - Household/Individual Special Surveys

38. SERVICE ENVIRONMENT LEVEL This is a complex level requiring different types of data from Sources such as: • Administrative records (service stats, HMIS data, financial & transport data) • Service delivery point information (audit information, inventories, facility survey data) • Staff information (performance assessments, training records, provider data, quality of care data) - Client visit registers Tools: • Health Service Information Systems; - Facility Sample Surveys; - Facility records; - Performance Monitoring Reports

39. INDIVIDUAL LEVEL “Individual” in this context refers to a client, participant, patient or documents related to a single person as can be obtained from • Sources such as: - Medical records; - Interview data; - Case Surveillance (epidemiology of disease) - Provider-Client interactions Tools: - Case reports; - Survey questionnaire; - Client register analysis - Patient flow analysis; - Direct observation

40. INDIVIDUAL LEVEL Can measure “program exposure” represented by utilization, as well as service experience, quality of care/service delivery, disease surveillance • Is the volume increasing? • What is the service mix? • Who are the clients? • How does it vary by public/private sector? • What are their consultation experiences? • Would they return/recommend the service? Other questions?

41. INDIVIDUAL LEVEL 1. Client Exit Interviews 2. Case surveillance (epidemiology) 3. Provider-client observation • Service Delivery Point records and registers • Patient-flow analysis • Others?

42. MEASUREMENTTOOLS • Facility audits, Inventories • Facility surveys • Provider interviews • Provider-client observation • Provider training records • Situation analysis • Others

43. Some Strengths and Weaknesses of Facility Surveys as a Source of M&E Data • Strengths • Can cover both public and private health facilities • Timing can coincide with program implementation • Can combine with population survey for outcome monitoring and impact evaluation • Limitations • Survey sampling design and analysis may be complex • Expensive, time-consuming • Information rapidly outdated, unless repeated • Others??

44. Surveys: When are they appropriate? • Surveys especially useful- • when other data are not available or inadequate • when they can be tailored to fit specific measurement objectives • Yield cost-efficient data on population and services • Good sampling techniques produce representative results for facilities, providers and clients • Surveys are expensive, but versatile and widely used

45. Rapid Appraisal / Qualitative Methods • Key Informant Interviews • Focus Group Discussions • Community Interviews • Direct Observation

46. COMPONENTS OF DATA SYSTEM • A sound Data System is likely to have: 1. Multiple, operationally defined indicators 2. A variety of Appropriate Data Sources 3. Baseline and Target Values 4. Feasible Data Collection Plan and Budget: - Specified Frequency - Identified Responsibility

47. GEOGRAPHIC LEVEL These are modern and specialized sources that include: - Cadastral maps (land ownership) - Land Demarcation Department with: - Satellite Imagery and Area Photography - Digital Line Graphs and Elevation Models Tools: - Global Positioning System - Computer Software Programs (GIS)

48. CONCLUSION: DATA SOURCES and YOUR M&E PLAN • Assess the type of information your program/project needs • Assess what information is already available and from what sources and levels • Use those sources to help developing your M&E Plan • Decide what gaps need to be filled and plan accordingly • Diagram the flow of data through the M&E system (collection to analysis)

49. THANK YOU