Like to do is take you to Georgia and facts look, focusing on the policy.
It's a tuberculosis policy.
They are still in the process of redefining and it will give us plenty of angles to look at its release evaluation and how you actually do it.
But I focus on the number of challenges. Not all of it, of course, but if things are not clear, if you want to resolve things, as I said, just ask me.
So I don't think I should repeat much this kind of mantras. I think the starting point for our use of healers in Georgia was that there is
this promise of redistribution that you can do it in a very participatory way,
that you can start from a program theory that you develop together with the stakeholders, in this case with policy makers.
And the idea was actually to use the whole released cycle to at the same time, in fact, develop a research program on this policy,
kind of find out how we could check and test effectiveness costs and the processes of implementation,
but also actually informing the policy making process by engaging policymakers in the whole exercise.
And so this kind of a double promise is actually what we started out with here.
And in this project, seven principles or eight or nine.
There's a number of lists out there. I'm again, I'm not going to go very deep in that.
I know you are into this. I think just to say that at some point you will have some questions.
So the configuration analysis part is to make sure that you link up your policy implementation to outcomes.
This black box of mechanisms and contexts and the people in it and that all of that
makes sense and that you do the analysis not in segmentations or by by segments,
but really kind of tied up at the end.
We use an this just kind of a cycle or kind of a diagram to to structure things a bit to make our students see how we go about designing the study,
but also for funding proposals, that kind of stuff.
So the whole thing starts with research questions or your research objectives, your evaluation questions if you want.
You know, by now the programme chief is a starting point, his end point, but also the starting point of any released cycle.
Study design, data collection, data analysis will be in fact decided upon by your actual programme theory,
the programme, which is of course responding to these kind of questions.
And then at the end of the whole empirical cycle,
you try to summarise synthesise kind of pull your CMO so those into the programme trigger and you design that and then you know,
the cycle can go on as long as your funding actually takes. And quite often that's not very long.
Of course, at some point then we'll have recommendations for policymakers or for any kind of commissioners of the evaluation.
So that's basically two steps, and we'll focus a lot now here on the programme to resist for a large extent.
To a large extent, because this and that hasn't been done as well.
But we're not yet in this phase, which we had to introduce, which we'll come back to at the end of the presentation.
So the starting point is this programme theory, which is perhaps easily understood as kind of the assumptions, the ideas that underlie a policy,
and that should explain why that policy would be expected to lead to particular outcomes for the target population.
Because basically the idea here and one of so is not only actually evolution stream using these
kind of principles to reduce evaluation of change largely stems from the same principles,
the idea that if you develop that programme from the beginning, which people involved in the programme or in the intervention,
there's a high chance that you would get a common understanding of what's happening
because you identify critical issues and you might also actually push people to,
to develop or better. Actually, the policy did not develop and we see that actually happening in Georgia.
If you go into the causal pathways from the very start, it allows for a better evaluation design.
And so if you develop this programme theory from the beginning with the policy makers but also with the research team,
and in this case we had economists there, public health people, health systems people, some psychologists and a number of different disciplines.
Basically, if you want them to contribute to your thing, it helps to have something to work on and doesn't disclose the causal pathways,
which then actually leads to a better design of the evaluation because you will see that also you can actually start mapping
out on your program theory the kind of data points you need and the methods you will actually use to collect the data.
By now, this should be non-use nature.
If you the assumption somehow is that we all have ideas about why things work, we don't necessarily make that explicit.
Definitely not.
When you are policy developers, a programme designer, there's a lot of hidden assumptions quite often that it's good to to understand that because.
It still is to a large extent actually what would be implemented and why. Okay.
Now, there are a number of ways to to come to that initial program theory for theories which are programmed to use held by the designers,
the people, beneficiaries, the actors involved. Of course, there's a lot of existing knowledge.
I think probably everything we kind of look at in medicine or in public health has been done somewhere.
There's lots of research that's very relevant for our kind of policy implementation
problems that have been developed in disciplines like public administration,
psychology, economics. So it's helps to to find out how you can get into that knowledge and then if nothing would, exists, exist.
There's always a possibility to start with exploratory research.
So that's kind of basically three categories of who is, let's say, that helps you to to continue your initial program theory.
Now, Georgia, on a bad day, actually, it was quite sunny at that stage, but cloudy.
This is about to me. I don't know if you know where Georgia lies. It's not the American Georgia, of course.
We're into ex-U.S. desert between the Black Sea and the Caspian Sea.
It's in the middle of the Caucasus Mountains. It's a highly political area.
You can see this large chunk of the world, which is the Soviet Russia,
the Soviet Union, Russia, they are still quite involved at the northern borders.
It's a relatively big country, but it has only 6 million people. It's going to have sparsely populated and highly mountainous.
Now from ITB is that it is for it's better now because if you look at the incidents maps, the dark green areas are the worse off.
That's basically to certain parts of Africa.
And that has to a large extent to do with HIV, AIDS infections, with also quite still some in South East Asia.
The excuse is that republics hold quite high levels.
When the USSR broke up, a lot of the systems collapsed.
Georgia kind of picked up, but they're still in the high range here.
So they're kind of this light greenish kind of thing.
But as we see at the upper limit of that, so and so, 92 people out of 100,000 will get TB every year.
The problem is not only that, but actually the success rates are not very good and there's a huge variation geographically in the country.
So in the big cities where the clinics are good, you'll find for drug sensitive routes through sensitive TB patients that has 100% success rates,
but only less than half in a number of other places.
There's quite some multidrug resistant tuberculosis as well, which is quite problematic, of course,
with these people will not get cured and this resistance is also occurring in people never treated.
So in that sense, the multidrug resistant and the and the extreme resistance case is really what concerns policymakers.
And they had to explanations when they looked into the policy in around 2015, 2016.
So one was adherence of patients to the treatment is not good.
And as you know, it's a long treatment. We'll come back to that in a second.
But also a lot of people actually opt out of the treatments.
So when started, they actually had a lot of side effects or didn't feel very, very well cared for and did drop out.
And that was initial analysis.
It has to do to a large extent to the huge wave of privatisation that happens after the collapse of the Soviet Union in 91.
Now it took a bit of time for them to get the rules revolution and then Shevardnadze and a lot of the old apparatchiks were kicked out.
And in that period from in fact already here it was a very wild privatisation going on.
So one of the stories is that they actually gave for symbolic ruble, almost huge hospital complexes in the middle of Tbilisi as a kind of lease,
a five year lease to private companies who wouldn't where they were just supposed to render services for five years for the symbolic one ruble,
and then they could do whatever they wanted to just put them down. And they built shopping malls.
And so it's a bit the spirit of this wild capitalism that really is quite, quite strong in Georgia.
So it led to what we call the provider split, a complete separation of the states functions and the provision of health care.
It was completely privatised. And in fact, for TB, it's the private sector that actually does the queues, the cash, but also preventive activities.
So there's very little left at the centre level.
There's the Russian tuberculosis program. They do the policymaking.
They're supposed to do some in supervision, supervision and guidance over the private practices as well.
The private sector is also very heterogeneous.
There's a small companies running a number of clinics in the few cities that are mega companies running kind of chains all over the country.
They're private practitioners still there, nurses operating small clinics. So it's a very kind of diverse picture, but it's not really priority for.
Because there's not much money in it physically unless we see patients who need to be observed every day.
In fact, when taking the pills or every 2 to 3 days, it's a huge workload for, in fact, very little money.
Now, government foresaw that already, of course, and they had a TB service agreement which forced the private sector to offer a private I mean,
TB programme activities within private companies. But that agreement was supposed to end by 2018.
And so policymakers said you need to to kind of incentivise the private sector now to really take on and continue the treatments.
But besides that, they also saw quite some problems between this primary health care or first care and first level of care,
in fact, and the TB services in the big cities.
So they had a number of problems there. Just to give you an idea, that was a not so directly observed treatment regimen for TB in Georgia,
which is kind of an international protocol it takes. And that's a bit strange.
People had to be hospitalised for six weeks and four months initially, in both cases drug sensitive and drug resistant TB patients.
But it's even takes six months.
And so in some cases, they went to see somebody by the patient would come twice a week to the clinic, take the drugs under supervision,
swallow and actually almost check, and then take some pills home for the next two days,
come back to the clinic to be seen actually taking two tablets.
It's a very from a political perspective, I can see the point, but from a from a human perspective,
this kind of direct observed treatment that I can't understand that you ever did,
that I mean, that you forced people to come and show that they swallow tablets.
It's crazy. And so you can imagine for patients, it's not the nicest of kind of experience.
But for private providers, actually, they couldn't care less almost.
That's not to say that there are not good clinics in Georgia because there is a not all that bad, but it's a problem.
So what they said is, okay, if we need to make sure now that the private providers properly take care of their TV patients and can motivate
them to come every 2 to 3 days and make sure that is sit out the whole treatment we need to incentivise them.
It's a market system. It's a it's a purely private for profit system.
So what you do, you just dangle them a carrot and you hope you have some sticks to beat them if they don't.
But there are not many sticks in Georgia. It's the country that's really the the policy option taken.
So that kind of a decision was taken in around 2015.
Policymakers said we need to do something about the situation. We are going to incentivise them.
And they asked actually a local research centre, the Grassroots Fund International Foundation in Tbilisi,
to set up a program to help them actually to develop the policy and at the same time to evaluate it.
And that was part of the grants they got from the Global Fund to actually roll out a three
year pilot project testing disincentives so that there's a whole set of the projects.
And it got funded at some points by the Health Systems Research Initiative of the MRC.
So what we then did was in fact put together the whole consortium, health economists, health systems, people, some TB guys.
The idea was we have a three pronged approach in terms of evaluation, the impact assessments,
the cost analysis and a process evaluation or a policy implementation assessment, but then based on the release approach.
Now that's kind of common. That's what you see in a lot of situations.
Of course, you have kind of any kind of trial combined with cross evaluations, whatever.
What you did here was to set out to kind of bring all these strands together from the very beginning and based on the program theory.
So here to set up is to try from the very beginning actually to come together with the policymakers, but also the researchers,
and to have one program theory that would help us set up the three other elements of the research
actual data collection to see and to have then one common framework not only to guide the process,
but also to help us with the analysis at the end. So that and at the same time, because we would engage with the policymakers,
the whole monitoring system as well as implementation would be easier to follow up.
That was kind of the promise. So program two here deals with the intended policy will have a combination of designs.
We'll have an integrated data collection tool basically that maps out all kinds of studies that we need or subseries to answer the big questions,
a much more integrated data analysis, a more parsimonious analysis, a more parsimonious data collection also.
And that should help us and to inform the scaling of this.
Now, it's been we had actually been doing that more or less in another project before this one from Health,
which focussed on the exemption of maternal care fees or exemption of fees for maternal health services in West Africa,
which was a huge policy thing like five, ten years ago here in this project.
We did not do it from the very start.
So what we did was kind of halfway tried to figure out how new units of maternal mortality is kind of influenced by biological complications,
but also by a number of health system factors that you then can start mapping out and to colour things.
I'm not going to go in detail. Bit of colour things are basically subsidies were packages that were focusing on
documenting particular elements of the ocean and this was a study done in four countries.
So it helped us to have kind of an overall strategy and some standardisation of tools, but also to make sure that there would not be too much overlap,
not too many gaps, in fact, and a much more integrated analysis that was more or less what we achieved in females.
But here we did not set out to the whole thing. We didn't start from the program theory.
So as we said already, for theorists literally to use it for research that could be used to to formulate your initial program theory here,
we actually did the teachings on top and then the kind of reef system.
If you once we started formulating the initial program, cheering on the basis of policy documents,
of course, had been quite sometimes written on the policy in Georgia as well,
but also internationally, literature reviews on policy implementation, on TB,
programs on the problems of the Caucasus, and then interviews with the program managers.
So that was the very start to kind of a basic starting point.
We took this initial program to read into a stakeholder a kind of a concept mapping workshop,
if you want, or a stakeholder workshop where we brought together a lot of people.
Then that led us to the initial program to number one, there will be holding an additional document review, again,
discussion with policymakers because of political context that changed and then a new kind of program theory that was taken to the second workshop.
And we see there was a slight difference in focus there.
We ended up with the third one and then that one actually was taken up by both researchers and led to a research strategy,
if you want, and with the policy makers to new TB policy.
So we did this process over a period of four months, almost two workshops in similar time.
Some have a few months here and a few months on the outside.
Okay. What is, of course, the importance, if you want to engage stakeholders, is to find the right ones.
And what is quite often not happening is providers and and patients.
In this case we did not have patients, but we had representatives of patients organisations,
but there was a quite good mobilisation of about 45 participants.
The effect of all these levels here. So policymakers, the program managers, of course from the national system, but also the funders,
researchers and then nurses, doctors actually from all regions of Georgia.
Because it's one thing easy, in fact, to get to the people working in the big cities.
You can actually get them and know them. But we had, in fact, quite a number of providers from far away and more much more rural areas.
And that's, as we'll see, actually changed quite, quite strongly the dynamics of the group, but also led to quite some new insights.
Now, if you want to set your program theory, you have this kind of very diverse public.
It helps to have a starting point somehow. And so here this is so an advisor.
Is the health economist involved with one of them? She had been working on the TV programs and cost effectiveness analysis.
They had been working on a kind of reframe. What we did is kind of simply take out the central part of that framework,
which is nothing more than setting out the different steps people would go through from onset of symptoms to being treated.
That's kind of we call that in Antwerp. And operation analysis kind of tool is pure model of TB implementation program evaluation, if you want.
It's nothing new there, but it's helped a lot for this public.
That's a public that's really geared towards TB and program management, doctors and nurses to have something quite tangible and relatively simple.
So we did not use the full blown thing here. We just told them, look, in the first workshop, try to figure out in this kind of a chain,
where are the big problems, where are the bottlenecks, why are people dropping out?
So it's it was used as a first workshop, actually, as a way to to analyse the problem by bringing the different stakeholders together,
but also in the second spheres of that same workshop to make them think about solutions and then prioritise solutions.
Because key policy is about, of course,
priorities and a lot of discussions and interactive small group meetings to try to come to not a consensus, but to actually find rival theories.
So again, the problem with program driven or theory driven evaluation methods is that you
start out with a program theory and that there might be a tendency to confirm that,
as we always do. You have ideas the. My mind is kind of set up, too, to confirm what we think.
To avoid that kind of tunnel vision, you really need to continuously push people to look for alternative explanations.
So that actually happens because we are facilitated, of course, for each of the groups.
So what it actually did was discover not really, of course, because we knew that I mean, the very, very starting point.
Why would you simply incentivise private providers and hope that that would change the situation in Georgia?
Of course, we know there's a whole systemic set of factors that you need to tackle at the same time,
for TB patients actually to be conformable to accept the care and to actually sit out the whole thing,
you know that it is not simply providers actually needing an incentive to change their attitudes,
but the policymakers who are not much convinced of much else. And so they were actually involved in this workshop.
And for them, these kind of contextual factors and system factors,
service related factors and related factors were quite, quite shocking to some extent.
So it led not only to identify these constraints much better, but also to considering,
in fact, a broader package of interventions to be in the policy.
Now, again, no need to reduce your risk.
So this is one way to summarise the findings of that first workshop.
You remember vividly this central pattern of the patient.
We kind of expanded it a bit. Uh, it went up to the organisational settings, this kind of facility level issues, management strategy,
then providers on this side again geographical accessibility, acceptability,
financial accessibility of service related factor that you could factor in.
And then that chain was also developed further with a number of other things.
Don't worry about that. It helped us to somehow keep track of the discussions.
First points for step taken workshops. So we're at this level here now, more or less.
There's also a bit of a narrative, uh, program theory version if you want.
And that was actually done discussed with, again, policymakers. So bit of a strange thing there.
One of the people of the foundation was a member of Parliament,
was the head of the medical commission in or the Health Commission in parliament was closely involved with policymakers,
had a lot of inside information.
Actually, it allowed it allowed for a lot of discussions at high level through this kind of dual position researcher, policy politician, actually.
But these discussions actually were quite important because they led to a number of changes in the policy design, basically.
And then we did some additional document review because what I come back to that later actually started
with this and gets into the policymakers first thing here in a number of these people changed.
And in the process of this program since about 2017, I think we've had three Minister of Health to a different Secretary-General's,
a number of different heads of departments as well. So there's quite a fast turnover of politicians and policy makers there.
That complicates matters. They come. It's different ideas.
They need to be briefed. You need to kind of see what's happening.
We need to understand what they want, actually. So that that was an important phase here.
And what that actually did was where initially the whole policy was about incentives to individual providers.
It was a much more comprehensive package developed. And again, I could have told you that that's what we need from the very start.
But of course it doesn't work that way.
It's not us going to deliver the needs people need to discover what they actually need to do and and the engagement,
the kind of ownership that as a result of this this kind of approach process, I think it was an important outcome.
What you then did in terms of having this discussion with policymakers and the previous response was to go a bit further into
into policy implementation and especially kind of theories and mechanisms which were not identified by the participants.
So when you engage with stakeholders, they are not really they're not looking necessarily for mechanisms.
They might not even have a clue about what the mechanism is for them.
They look at bottlenecks and problems. They see very kind of anecdotal evidence you need to bring them to come to to substantiate their claims.
And that's the process of in the workshops, actually making them argue why they think there's a problem, why that could be a solution.
But they don't go necessarily into the deep, deep analysis and definitely not the level of mechanism.
So at that stage we put in the literature reviews and some other things we had done in the past on adherence.
And then a number of these of course, exist quite soon.
We have taken this information motivation behavioural skills model, which is quite used in HIV research,
where it's used to explain adherence to treatments and self-determination theory,
which is a motivation theory quite well developed since the 1970s and also applied to the motivation of patients in taking drugs.
So it was a quite useful tool that helps us to to model things.
So we had kind of simple models, let's say, to to think through again why people in this case,
women with children who needed drugs would be initiated on the team or not maintain and keep taking the drugs.
And okay, this was a very simple starting point of that, that previous study.
So you can combine, of course, insights from the stakeholders workshops with existing evidence, with the notice that is already out there,
with evaluations from programs and previous studies and kind of accumulate gradually the knowledge and specified.
See whether this explains the situation in Georgia, as you know.
So it's a bit about the possibility of this kind of middle range theory elements, if you want.
We also try to find out a way to summarise these programs using causal diagrams.
We are not going to don't worry, because it's not a terrible thing.
This thing this is the simple one. Let's say there are a number of layers in this thing.
So, of course, loop diagrams allow you graphically to map out relationships between different elements,
if you want of your causal chain is of course, much more advanced than simple drawing program.
You can actually use this to model the whole thing and to run particular changes in the thing.
But we are not into modelling outcomes or predicting policy changes.
This was useful for us to kind of represent in much more detailed way the feedback loops and at some point we are stuck here.
I mean it was not for for a number of reasons, but also because of the the sheer kind of complicated ness of this thing.
Actually. Anyway, just to say that the discussions and that's always the thing.
With modelling, you can believe in modelling or you can be very sceptical.
But develop models actually allows you to again put your hypotheses and assumptions on the
table and to discuss them and to confront people or at least each other's assumptions.
So it helps us to get a much better understanding of the policy as a research group.
And because it made us different kind of assumptions, very so in our group there were people working on PBF,
on performance based financing from health economics perspective, really believing in it, others quite sceptical.
There were people working on tuberculosis, they had lots of knowledge on the TB pathways,
then some epidemiologists from Georgia, some sociologists, some health systems.
Now if you want to kind of have a detailed map, you need to bring all of that together somehow or not, and have a rival explanations.
Okay. But what they did, at least for us, is, again, a see much better which kind of data collection tools we would need to documents,
not the whole map here, but the specific pathways we would be interested in.
And I'll come back to that at the end of its second workshop.
So we had a bit of a program. Now it was a policy decision taken.
We wanted to bring it back now to again the same group of stakeholders to see how far they were actually agreeing with that or not.
Because again, now the politicians or the policy makers had taken back the initiative and they had developed a new package.
I wanted to see an effort that would make sense if discussed with the actual stakeholders.
Here at Fairless participants, about half of the group did not come.
This time we had about 27. But you have the same mix or the same kind of representation of different groups.
So here the idea was, okay, if this is the policy package, what will it achieve?
So you could call it the action model from the policy to the beneficiaries to the expected effects petition side effects.
And in the second step, then we wanted them to think about, okay, but do you think it will work for which reason, why and which kind of conditions?
So action model, causal model is something that's not really used much in realist that comes from program,
from theory driven evaluation, but it basically does the same thing. So the idea was, where are we in the whole process?
We have at some point the policymakers now have an idea that the package should be much larger than they initially thought.
But then and the researchers, of course, kind of steer that to some extent.
And then this politician, researcher guy also.
So at the end, to make to make sure that that's what they would decide and it would make sense for people in the faraway regions.
You said, okay, let's use this opportunity and the dynamics of engaging with the stakeholders a second time to kind of test back.
In fact, the hypothesis underlying the new policy, which are policymakers, of course, did not make very much explicit.
They don't think in terms of program to use, even if they're involved in these workshops, at some point they revert back to type.
So that's quite normal. Of course, it's not their business. So here we said, okay, let's do two things.
Let's first. So the policy was presented to packages and the way the politicians thought it would work.
And then we said, okay, let's now go a bit deeper into that policy.
And as the participants to think about the action model, which is the link between the policy,
how it will play out the intermediate effects and then the ultimate effects,
which is basically health status or adherence to treatment,
but also not forget about potential side effects because politicians always only see positive effects of things, of course.
But we know that a lot of these what is basically systemic interventions will have some negative effects as well.
Okay, second step was, once you have done that kind of action model thinking, explain why you would think it will work or why not to.
Again, kind of find out whether it be not rival theories or rival explanations or better solutions to to the problem.
So it was kind of a test, again, of the hypothesis underlying the policy and that actually did not lead to much results.
So we're not sure. I mean, we didn't go very deep into the analysis.
Is it because the people were tired at some point, because this was no second workshop or because they actually did not see prompts?
But okay, that's where it was. So other is a result of this.
There were very few modifications of the program during the one we had presented to them actually was more realism intense.
But the package of the policy was again refined a bit.
So where it was initially in the very first step, just incentives to individual providers.
After the first workshop, we went to this package. So you will not be incentives to individual doctors, nurses, managers, but to the whole team.
So one of the critiques was that a lot of people are involved in TB care.
You cannot incentivise individuals, you'll get gaming, you get lots of problems.
There will be a lack of team spirit and collaboration. We know, in fact, that is incentivising of individual providers.
Sequential problems if you don't control it. So here too, I said, listen, have the whole team paid in terms of their performance as a team.
And at the same time, make sure that the team can function better.
So it was it was found out in a lot of these private clinics.
The task distribution, the way people coordinated their work was not optimal between laboratory and the clinicians,
between the reception and divisions that required some gaps. And then the other thing which was lacking was an integrated patient management tool.
They call it a plan.
You would call it a patient file, probably, where you keep, in fact, the whole records of the patient, including the treatment plan,
and use that as a kind of integrated data management tool that would help to provide, but also to facilitate, to better manage care for patients.
And something which might not have been super important but which was felt to be important was the side effects.
So the hypothesis was of a lot of providers that because of the side effects, a lot of people drop out.
And of course, TB drugs are not innocent because quite some problems.
So training for specialists to identify the side effects and to do something about it was deemed important.
So that was before the second workshop and the next kind of package did not change much.
They went into a bit of more details now in terms of TB case management and the bonus system also was fine tuned.
Okay. So we are not going to go into evidence of whole TB scores, if you want, if not more.
But the way you are going to make sure that the team actually gets the money and how you are going to decide how to kick is cut up is quite critical.
Who is playing which role into the performance? How much are you going to want to give to the receptionist?
How much to the doctor? How much to the I don't know, the drive. Who takes the samples to the region hospital?
Each of these people plays a role in the whole systemic thing that you need.
But how much do you need to pay them to motivate them to do better?
So it's a quite a messy intervention if you want.
So we were more or less at the end of the second step here where some of the but not so much of the policy package was again, refined and well,
some examples it is that now we need and that has to ensure good in between
because these are kind of dates from last year but they were no more kind of
standard operating procedures let's say or guidelines developed for how an
integrated care team should should function with a clear distribution of the roles,
with some additional training, with guidelines, with supervision tools developed for that.
Okay. They wanted a patient centred approach. Now, that was a huge discussion.
It means 25,000 things to two different people. Of course, I was surprised.
Yeah, okay. But that was an option. I mean, a problem still. And then, okay, as I said to the bonus payment system was also somehow changed.
This is very much technical discussion in performance based financing.
So I kept out of that's what you also did is now because you remember vaguely this huge complex of the the
the loop diagrams that was too difficult to to capture to understand we reduce it to the essential personnel.
And so that's another problem we have, which is really is quite often this.
How do you focus on your complex chain of causality?
Where do you can you capture everything? Then you have to sealed diagrams and of course not.
Our human brain is relatively limited in what it can can deal with.
You need to somehow reduce it and huge. I'll explain that later.
Also, we went into a much more kind of focussed set of hypothesis or a simple computation if you want,
but I'll come to that in seconds and because it's about is basically if you want to focus on this huge,
let's say the chain from people at the political level identifying a problem to the health outcomes,
that basically depends on how patients with TB deal with their disease and how they feel about the disease,
how they perceive it, how they linked up to their community and local situation and then to the health system.
Do we want to identify mechanisms and causal explanations?
At which level? And we talk about out in terms of ladder of mechanisms in released or the number of
ways of conceptualising that you might imagine levels of mechanism at the micro-level.
So at the bottom to see what it is about individuals, people, patients, why would they be motivated now under this policy to take their drugs?
Why would providers actually be more I don't know what difference in their
behaviour towards patients to make sure that people would swallow the drugs.
Why would managers of facilities actually go with this policy?
Why would a supervisor from the TB crew program do that or why with politicians continue to push for funding?
You can imagine in fact mechanisms happening of the number of different places and of course, they all are linked somehow to one to the next to.
There's another example of one of my students now where we look at how, again, that was a feminist example,
a continuation of that, that a particular policy at national level, it could translate into a national program.
It comes down to hospitals. Managers need to adopt it or not.
They will actually have a number of options to to go with the program or not to capture it actually for their own benefits or perhaps to improve it.
So these are kind of street level bureaucracy notions here.
But then it's not because managers decide to go with the program that actually the providers will do so.
You can imagine, in fact, that each level of the system,
a number of hoops and barriers or levers actually need to be kind of taken for the policy to work.
And you cannot just focus probably on just the providers or the facility manager
or a successful policy will need to take into account the whole system,
of course. But okay, that's a discussion you can have at some point.
So where do we want to focus your your efforts? So our way of focusing on things was to say, let's focus back on your initial question.
That is, why are patients not adhering to the policies or how does the policy increase adherence if there is an outcome of better or worse adherence,
how do we explain that by focusing at providers and different kinds of providers, different kinds of private institutions and different logics.
You may have do the facility managers and then also the people at the service level adopted and implemented.
In what kind of context do they do that? And what about patients?
Of course, because they are the people supposed to take the drugs and supposed to get better.
And so that's how we try to kind of to kind of focus the things.
No, there's a slide missing here that what happened to these groups after this is not one of the major problems we have,
and that's not necessarily due to release, is that it's kind of a natural experiment.
This is a policy where you're kind of prospectively involved in the whole thing.
You never know how it's going to end and not even if it's going to continue in the first place.
So one of the major delays we had was changes in the political system due to elections program managers changing, politicians changing.
Initially in the first wave of change, nothing much happened in terms of the policy preference.
They still went for PBF, but the second government came in and they said, well, let's let's drop that idea.
Let's go for primary health care and free care and a kind of a different way of looking at things.
And then the question was very much from a research perspective, okay, I would make my position was let's go with the flow.
So if the policy changes,
let's just adopt the policy question we have and see how that change actually happens and if that new policy will be implemented or not.
But the kind of hardcore economists and the other said, no, no, no, no, we have this program, we have our design, our child is ready.
Let's just do it. And then you have a very strange situation whereby the cross,
your team tries to convince the Global Fund to still get some money there, even if government is not fully in line with.
And it's a quite strange situation. But okay, that explains a bit.
Also again, the delays it's now after, let's say one year and three months of a kind of go between phase.
Don't you begin to really testing the tools now,
starting to data collection piloting and probably implementing the pilot phase in a few months from now.
And it may be that by that stage, again, the political favour will be proposed, but perhaps it will not.
So it's kind of ask, I mean, and that's with any kind of policy research, of course,
to what extent do you need to steer your research in function of politicians and national priorities,
or do you want to stick to your initial fixed design and the finish commitment that whatever?
I yeah, that's a bit dubious.
Okay. So, you know, this was one of the clinics in about to me kind of swamping the office with five,
six, seven people actually asking questions to two nurses.
This was not the way we usually do research. Of course, this was during one of the kind of introduction visits.
Other questions. No, I thank you for forcing here.
Absolutely.