1. 1 Interpretation and use

2. 2 The walls inside are plastered with laboriously made graphs…

3. 3 Outside, people have been queuing for hours…

5. Appropriate interpretations  facilitate knowledge sharing & feedback  are context sensitive (population, health, service status)  identify plausible linkages (logical, sensible)  depend on quality data  should be base on clear data definitions  result in action!

6. 6 Preparing for interpretation  Accuracy checks – 3 C’s and 1 T, includes:  Routine validation and trends checked over time  Data checked per month, per facility, per district  Local / contextual knowledge on:  Population data: ethnicity, lifestyle, occupation  Health data: common diseases  Service data: types of facilities, proficiency of staff

7. Avoid gathering large number of data elements Avoid data elements without contexts and without denominators –eg. 4,32,345 children given Vitamin A. –34567 women had institutional delivery. –No idea whether this is 5% achievement or 105% achievement. Avoid data elements that cannot be used for indicators Avoid indicators for which there are no data elements

8. 8 Practical questions in interpretation 1. Why have you produced this indicator? 2. What does the indicator measure? 3. Has the indicator been accurately measured? 4. What is the target value OR action trigger value?

9. 9 Practical questions in interpretation 6. What is the normal range? In your country: - urban - rural In the world: - best in the world - worst in the world 7. How does it fit in with other information? 8. What is the local context? 9. What should you do about the situation? 10. How could you implement that? Temporal & Spatial comparisons

10. 10 The manager of a clinic in a peri-urban area was surprised by the very low numbers of male patients attending the OPD with urethral discharge. She was sure that the facility reporting system worked well. What could be the cause? An Exercise

11. Low PHU Deliveries TBAs holding on clients Low community sensitization High fees for deliveries Staff attitude Can’t afford fees Men not involved No proper orientation Low educational level Staff shortage Staff not motivated Cultural beliefs Family trust in the TBAs Community norms Laws not instituted Patients refusal to go to PHU Long distance Irregular supervision Difficult terrain Root Cause Analysis

12. 12 TB Exercise You are presented with a graph for a district in Uganda showing 3 indicators on the Overall TB Cure Rate, Overall TB Success Rate and DOTS (Directly Observed Treatment Shortcourse) for each quarter of 2003. How would you interpret the information contained in the graph?

14. 14 To interpret this information you may need to ask the following questions What are the definitions of the indicators that are used? What does the graph show? What else do you need to know? Is it enough to make a decision? Is this the best way to present this information?

15. 15 USE -> Assessing coverage and quality of health services WHO GETS SICK ? WHAT HEALTH SERVICES EXIST ?

16. 16 Assessment of coverage who gets sick?  Description of people who attend health services: age and gender breakdown community distribution  Use of individual patient data to construct aggregated routine data  Definition of population catchment target for specific services at risk

17. 17 Assessment of quality what services exist ? For whom?  Accessibility –Catchment population –Target population –Utilization What?  Appropriateness –Type and range – Continuity Why?  Political vs functional When?  Acceptability –Convenience to clients and staff Where?  Distribution  Integration How ?  Affordability  Resources –Staff –Materials –Money

18. 18 From Data to Health Input ….Raw Data  quantity and quality of data elements ( Essential Data Sets! )  data collection tools (tally sheets, registers, client cards) Process …Analysis  turning raw data into useful information  planning tools (targets, indicators) Output …Information  used for effective decision-making  assessment tools (aggregation, graphs, reports) Outcome …Coverage and quality of health services + efficiency  management  planning (strategic & operational)  monitoring & evaluation Impact: Health status

19. Challenges to Information Use HMIS often used: –for reporting NOT analysis –as a form of control and reprimand NOT used for –planning and local action –cross checking data with other sources –strengthening supervision processes –improving quality of care

20. Multiple Perspectives on HMIS Organization Management HMIS Public Health Service Delivery Technological determinism Discussion of different interpretations and exploration of different views --> improved and mutual understanding