Module 9 Part A: Monitoring and Evaluation *Image courtesy of: World Lung Foundation

Describe the difference between monitoring and evaluation Explain why we monitor programmes Explain how to monitor a TB programme –What to monitor –Principles and techniques Describe how to conduct a supervisory visit Learning Objectives

What is M&E? *Image courtesy of: World Lung Foundation

Differences between Monitoring and Evaluation

Why Monitor and Evaluate? 1.Collect accurate information about the TB Programme 2.Use that information to improve the TB Programme

 Management  Reporting  Accountability  Advocacy  Evaluation Monitoring serves several purposes

Episodic assessment of specific indicators –determine effectiveness or impact of services or activities –during a given interval Determine whether goals are being met Assess impact of a specific service or intervention - HIV testing among TB patients Advocacy Why Evaluate?

Determine if staff activities follow BNTP guidelines Measure key indicators related to case detection, quality of diagnosis, and TB treatment Identify problems in implementing TB control activities (e.g., laboratory reporting delays) Inform the annual evaluation of TB Programme Use the findings to modify programme goals and strategies (e.g., implementing RHT) Benefit for BNTP

Surveillance Data and Programme Monitoring within BNTP Clinic-level: TB Suspect and TB Case Registers District-level: District TB Register and ETR National-level: ETR

How should I monitor?

The first step is observation, but talking and analysis help you understand the cause ObserveTalkAnalyse ActionsAttitudesConsistency ProcessesUnderstandingAccuracy ConditionsMoraleEffectiveness

Observe

Take a look around the clinic  Are there signs of disorganization?  Are the patient treatment cards for all registered patients available?  Are the cards in a binder in numerical order?  Are the meds organized?

 Are there IEC materials?  Are there masks for patients and respirators for staff?  Are patients being triaged appropriately?  Is the condom dispenser full? Other Visual Indicators

Communication with Clinic Staff

Find Out More from People Through communicating we can: Test level of knowledge Gauge attitude and morale Seek guidance on priority areas   

DO’s:  Listen and be prepared to learn  Take notes – it’s your job. Don’t be embarassed!  Ask follow-up questions and explore the issues  Compare one story against another! “Triangulate” DONT’s:  Don’t worry if the person knows more than you  Don’t take anything at face value – CHECK all verbal information against the data  Don’t threaten or intimidate the people you speak to Some Communication Tips  

 Level of knowledge:  ‘Who should be entered into this register?’  ‘Explain the process of how the register is used’  Attitude / Perception  ‘Whose job is it to enter the data?’  ‘How important is it that this register is used properly?’  ‘Are you comfortable with using it?’  Seek guidance  ‘What needs to be done to improve how it is used?’ Apply this Approach to Determine How Register is Used

Analysing the Suspect and Sputum Dispatch Register

% of new pulmonary TB (NPTB) suspects who have 3 initial sputums collected consecutively Formula: Number of who have 3 initial sputums collected consecutively Number of NPTB suspects worked up for TB Tip: compare the result you get to last time. You can learn a lot by comparing indicators over time Indicator: Quality of Programme Management

The TB Register

 Use your experience and common sense  Are the entries recorded correctly? –Proper chronological sequence –Proper identification of class and type  Are there signs that the register is being completed in “batches”? –Multiple entries on the same date with different treatment start dates (all in the same pen!) How does the data ‘look’?

Analysing the District TB Register  Recording and reporting  Calculating Indicators

 Use your experience and common sense  Are the entries recorded correctly –Proper chronological sequence –Proper identification of class and type  Are there signs that the register is being completed in “batches” –Multiple entries on the same date with different treatment start dates (all in the same pen!) How does the data ‘look’?

Example: Review of District TB Register  Is there a report for each facility in this quarter?  For cases registered 3 months ago, are there follow-up sputum examination results (that is, for those collected at month 2 / end of the intensive phase?)  For cases registered > 6 months ago, are there more follow-up sputum exam results, or blanks in these columns?  For cases registered 12 months ago, are there treatment outcomes, or gaps in that area of the register?  Are there cases who were registered on the basis of sputum exam results but never started treatment?

Analysing the District TB Register via the ETR  Calculating Indicators  Recording and reporting

Calculating TB Rates Death Rate = deaths / proportion of incident cases that die Case Detection Rate = annual new smear-positive notifications (country) / estimated annual new smear positive incidence (country) Other Useful TB Rates Include: Notification Rate, Cure Rate, Treatment Success Rate, Default Rate, Treatment Failure Rate, Transfer Out Rate

TB Cases Pulmonary EPTotal% Smear +Smear -No SmearTotal New cases % Relapses % After default % After failure % Total * % %35%6%41%83%17%100% * of which children aged 0-7: 6 TB Cases >75Total% All TB Cases M % F % Total % %5%12%40%29%10%3%1%0%100% All Smear + Cases M % F % Total % %1%15%41%30%10%2%0% 100% All Smear + Re-treat M % F % Total % %0%33%67%0% 100% 0 record(s) with missing age Botswana Tuberculosis Programme Case Finding Report Report on New and Retreatment Cases of Tuberculosis (WHO) 15 – GABORONEQuarter 1 of 2004 Formula SS+ cases Registered cases Example 94 = 35% 265 AFB Diagnosis Rate The proportion of notified cases diagnosed with sputum smear microscopy 43%

What can it mean if cases diagnosed through AFB is under 50%? 1.Too many cases being diagnosed through x-ray 2.Too many extra-pulmonary cases 3.In comparison with previous quarters an increase may imply increasing reliance by clinicians on smear microscopy… Is that good or bad? What could have caused the change in District A? Take a look at District C – if you were monitoring this province what would you think if you saw this trend? What about District B? Which is probably the best result?

CategoryOutcome Status No% All TB Cases Treatment completed Smear negative at completion288% Smear positive at completion00% Smear results not available6719% Treatment not completed Died during treatment123% Transferred to another unit267% Defaulted from treatment206% Treatment outcome not evaluated19556% All tuberculosis cases347100% All Smear + New Treatment completed Smear negative at completion2118% Smear positive at completion00% Smear results not available1613% Treatment not completed Died during treatment33% Transferred to another unit119% Defaulted from treatment65% Treatment outcome not evaluated6353% All tuberculosis cases120100% All Smear + Re-treatment Treatment completed Smear negative at completion00% Smear positive at completion00% Smear results not available125% Treatment not completed Died during treatment00% Transferred to another unit00% Defaulted from treatment00% Treatment outcome not evaluated375% All tuberculosis cases4100% Botswana Tuberculosis Programme Treatment Outcome Report Report on the Outcome of Tuberculosis Treatment 15 – GABORONEQuarter 1 of 2004 Formula No of registered cases that default Total no of registered cases Example 20 = 6% 347 Program Default Rate: How many patients are defaulting from treatment. In other words, how many people stop taking their medications. Less than 5%

Something is wrong in the program and needs to be fixed. The patient is quite likely sill sick and contagious. Less than 5% It’s important to understand what ‘default’ means: “A TB Patient is classified as a ‘default’ when their treatment is interrupted for 2 consecutive months or more.” This is an easy indicator to get from the data, but it can be deceptive! Every defaulting patient = a risk of MDR-TB in the community. What do we know for sure if we’re missing the target?

1.Is it to do with the patient? Is it embarassing for the patient? Are patients scared of the side-effects? Does the patient know that you have to KEEP taking the tablets? 2.Is it to do with the nurse? Are nurses doing the DOT? Is it dangerous / difficult to get to the patient? 3.Is it a problem of drug supply? The defaulter rate is an important indicator for measuring quality of treatment. But what are its limitations? Take a closer look at the definition of ‘default’. What does it mean if the program default rate is not on target?

CategorySputum Conversion Status At 2 monthsAt 3 months No% % All Smear + Cases Treatment still ongoing Converted to smear negative2923%4940% Remaining smear positive97%76% Smear results not available7560%5444% Treatment discontinued Died during treatment11%1 Transferred to another unit97%108% Defaulted from treatment11%32% All smear + cases124100%124100% All Smear + New Treatment still ongoing Converted to smear negative2823%4638% Remaining smear positive87%76% Smear results not available7361%5344% Treatment discontinued Died during treatment11%1 Transferred to another unit98%108% Defaulted from treatment11%33% All smear + new cases120100%120100% All Smear + Re-treatment Treatment still ongoing Converted to smear negative125%375% Remaining smear positive125%00% Smear results not available250%125% Treatment discontinued Died during treatment00%0 Transferred to another unit00%0 Defaulted from treatment00%0 All smear + new cases4100%4 Botswana Tuberculosis Programme Sputum Conversion Report Report on Response to Initial Phase Tuberculosis Treatment 15 – GABORONEQuarter 1 of 2004 Formula SS+ converting to smear negative SS+ registered cases Example 29 = 23% 124 The Sputum Conversion Rate Are enough patients converting to smear negative at the end of 2 months of treatment? To do this we use a conversion Rate Equal to or greater than 85%

What can it mean if sputum conversion rate is under 85%? Equal to or greater than 85% 1.The drug treatment regimen may not be working Are the correct regimens being used? Could MDR-TB be an issue? 2.Patients are not taking their TB medications Are the nurses doing their job? Is Directly Observed Treatment actually happening? Are patients scared of taking the tablets? What kind of detective work would you do to find the cause?

Formula No of registered cases with test taken Total no of registered cases Example 6 = 84% 7 Proportion of notified cases tested for HIV: What % of TB cases were tested for HIV? 100% HIV Status Result Date Test 1Test 2 N P N N N N 6 Reg Number Registered Date (mmddyy) 001/0501/01/05 002/0501/02/05 003/0501/03/05 004/0501/04/05 005/0501/05/05 006/0501/06/05 007/0501/07/05 7

What can it mean if less than 100% of patients are tested for HIV? 1.Lack of training among clinical staff 2.Shortage of test kits 3.High refusal rates among patients 4.Other factors requiring consultation with the TBFP or relevant clinical staff 100% Low testing rates may indicate that the policy of routine HIV testing has not been implemented properly in a site or district.

Analysing the treatment card

Patient’s information is complete Patient’s DOT and weights correctly recorded All HIV Status results are correctly recorded For HIV-infected patients –Receipt of ART noted? –Receipt of IPT? Reviewing the Treatment Card

We have:  An understanding of the principles of M&E  Some experience and guidelines you can take away with you on good ways to:  Observe  Communicate  Analyse By now (hopefully)…

Next steps In the next session we will apply these practices to the supervision checklist, which means we have to:  Use the whole supervision checklist  Practice communicating with actual field staff  Interpret actual data to develop indicators  Observe the environment  Develop a list of action-items

Thank you and Good Luck!