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Evidence Review case study: SolidarMed

An evidence review for a housing program in rural Zambia helped the nonprofit SolidarMed

a) understand the strengths and weaknesses in its theory of change, b)identify areas for further investigation through a monitoring, evaluation, and learning system, c) create a database in which to enter new research pertinent to its program.

Background

Delivery of health services in rural Zambia is critical; over half the Zambian population lives in these areas and they shoulder a heavy burden of disease. However, a shortage of healthcare workers willing to work in rural areas hampers delivery of health services and, ultimately, positive health and health systems outcomes. Rural areas struggle to attract and retain healthcare workers, in part because of inadequate housing options. To address this challenge, SolidarMed runs a program to construct and renovate housing for healthcare workers in rural areas. By improving the quantity and quality of housing for healthcare workers, SolidarMed aims to alleviate staff shortages, with the hypothesis that this will translate into improved health outcomes in rural Zambia.

Question

SolidarMed sought to clarify its pathway to impact – what conditions needed to hold for the housing program to lead to improved health outcomes? To answer this question, IDinsight:

  1. Produced a theory of change for the housing program
  2. Conducted an evidence review to understand whether and in what ways research supported the pathway to impact laid out in the theory of change, as well as to identify gaps in the existing literature

The rest of this case study focusses on the evidence review for SolidarMed’s housing program. For more information on the process of creating the theory of change for this program, please click here.

Approach

Reviewing the literature helped us a) develop the theory of change (below), and b) assess the likelihood that the theory of change would hold.

Searching for evidence 
We first looked for studies linking superior housing for healthcare workers to health outcomes. Unfortunately, no such evidence was available, mainly because few large-scale programs had been implemented and evaluated. We thus decided to explore the evidence for critical assumptions in the theory of change, specifically:

  1. How superior housing influences the attraction and retention of healthcare workers to rural areas
  2. How general housing influences the attraction and retention of healthcare workers to rural areas
  3. How superior housing affects the well-being of occupants
  4. How attraction and retention of healthcare workers leads to improved health outcomes. More specifically, we investigated how improved performance by healthcare workers could lead to improved health outcomes
  5. How health facilities and rural infrastructure lead to improved health outcomes

We primarily used Google Scholar to search for keywords relevant to each link in the theory of change.

Overview of evidence found

  1. Evidence suggested that poor housing dissuades healthcare workers from moving to and staying in rural areas
  2. There is also compelling evidence that a sufficient rural health workforce can contribute to improved rural health outcomes
  3. Although there is no evidence on the isolated effect that improved housing has on health systems outcomes, there is evidence supporting some of the linkages between superior housing and improved health outcomes.These pathways include the link between improved housing and healthcare worker living conditions.
  4. However, there is little to no evidence for other potential linkages between superior housing and improved health outcomes. For example, at the time of this review there was little evidence on whether an increased number of healthcare workers in a rural area will consistently lead to increased availability of healthcare staff in the relevant clinic

Synthesizing the evidence 
Based on the evidence, we assessed the likelihood (high/medium/low) that each assumption held. We also noted the assumptions for which there was no evidence from the literature.

Results

A simplified version of SolidarMed’s theory of change is given below.

The evidence substantiating the first link in this theory of change is relatively strong. It is logical to conclude that SolidarMed’s housing program may have a positive impact on retention of healthcare workers, which could lead to more health staff on-site for longer periods of time.

The evidence in support of superior housing affecting patient health outcomes is weaker. This pathway to impact operates through multiple channels. Evidence suggests that some of the ways housing could lead to improved health outcomes (for example, through increased availability of healthcare workers and reduced workloads) may hold, but other pathways like increased diversity of the cadre of healthcare workers may not hold or are relatively unexamined. In other words, housing may impact patient health outcomes through some channels and not others.

Overall, the theory for SolidarMed’s housing program is convincing. Given the evidence, it is reasonable to conclude that superior housing likely has an impact on the number of on-site health staff (mostly through retention). An increased number of on-site health staff may lead to improved patient health outcomes through one of many impact pathways, if the corresponding assumptions hold.
In order to confidently conclude whether superior housing leads to improved health outcomes, we recommended that SolidarMed test key assumptions and linkages in its theory of change, through the development of a monitoring, evaluation, and learning system. This is a key step towards eventually measuring the causal impact of the housing program with an impact evaluation.
The evidence review continues to serve as a ready reference for literature relevant to the program. It also provides a structured database that SolidarMed can easily update with new research relevant to its program.
Explore more examples from IDinsight projects

Guide

Not sure where to go from here? 
Use our guide to frame a question and match it to the right method.

Evidence review?

Want to learn more about evidence reviews, Click here to find out more.

Create your theory of change

Use our drag-and-drop tool to create a theory of change diagram

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Types of impact evaluations

Impact evaluations compare the people who receive your program to a similar group of people who did not receive your program. Based on how this similar group is chosen, impact evaluations can be randomized controlled trials or quasi-experimental.

A randomized controlled trial (RCT) is considered the gold standard of impact evaluation. In an RCT, the program is randomly assigned among a target population. Those who receive the program are called the treatment group; those who do not receive the program are called the control group. We consider the outcomes from the control group to represent what would have happened to the treatment group in the absence of the program. By comparing outcomes among those who receive the program (the treatment group) to those who don’t (the control group), we can rigorously estimate the impact of the program. The random assignment of the program to the treatment and control group provides the rigor, as it ensures that the selection of people is not based on biased criteria that could affect the results.

When a randomized design is not feasible, there are other, “quasi-experimental,” ways of constructing a valid comparison group. 

  • In a matched design we would match individuals who receive the program to individuals who don’t receive the program based on some observable characteristics (such as age, gender, number of years of schooling, etc.), and compare outcomes across these groups. 
  • Another common technique is regression discontinuity design, in which you create a cutoff based on which individuals are eligible to receive the program, and then compare outcomes from groups just below and just above the cutoff to estimate impact. 

Matched designs and regression discontinuity designs are just two of many quasi-experimental techniques. J-PAL provides an overview of common methods of conducting an impact evaluation. All such methods seek to identify what would have happened to your target population if they had never received the program, and their success relies on the strength of the assumptions they make about whether the comparison group is a credible stand-in for your program’s target population. 

Recommendation: Theory of Change

A theory of change is a narrative about how and why a program will lead to social impact. Every development program rests on a theory of change – it’s a crucial first step that helps you remain focused on impact and plan your program better.

You can use diagrams.net to create your Theory of Change.

Learn more about the theory of change ->
Go to the next state of the decision guide

Recommendation: Needs assessment

A needs assessment describes the context in which your program will operate (or is already operating). It can help you understand the scope and urgency of the problems you identified in the theory of change. It can also help you identify the specific communities that can benefit from your program and how you can reach them.

Build your theory of change ->

Once you’re satisfied that your program can be implemented as expected:

Go to the next state of the decision guide

Your program's theory of change

You have a written plan for how your program will improve lives – great! Make sure to refer to it as you explore the different sections in the Impact Measurement Guide, as it is the foundation for any other method you’ll use.

Learn more about the theory of change ->
Go to the next state of the decision guide

Recommendation: Process Evaluation

A process evaluation can tell you whether your program is being implemented as expected, and if assumptions in your theory of change hold. It is an in-depth, one-time exercise that can help identify gaps in your program.

Learn about process evaluations ->

Once you are satisfied that your program can be implemented as expected:

Go to the next state of the decision guide

Recommendation: Evidence Review

An evidence review summarizes findings from research related to your program. It can help you make informed decisions about what’s likely to work in your context, and can provide ideas for program features.

Learn about evidence reviews ->

Once you are satisfied with your evidence review:

Go to the next state of the decision guide

Recommendation: Monitoring

A monitoring system provides continuous real-time information about how your program is being implemented and how you’re progressing toward your goals. Once you set up a monitoring system, you would receive regular information on program implementation to track how your program is performing on specific indicators.

Learn more about monitoring ->

Once you are satisfied with your monitoring system:

Go to the next state of the decision guide

Recommendation: Monitoring

A monitoring system provides continuous real-time information about how your program is being implemented and how you’re progressing toward your goals. Once you set up a monitoring system, you would receive regular information on program implementation to track how your program is performing on specific indicators.

Learn more about monitoring ->

Once you are satisfied with your monitoring system:

Go to the next state of the decision guide

How to compile evidence, method 2

You’re on this page because you want to search for evidence relevant to your program.

Here are some academic sources where you can search for relevant research:

  • Google Scholar is a search engine for academic papers – enter the keywords relevant to your program, and you’ll find useful papers in the top links
  • Once you identify some useful papers, you can consult their literature review and bibliography sections to find other papers that might be relevant
  • Speaking to a sector expert can guide you to useful literature

 However, don’t include only academic studies in your review! You should also consult:

  • Policy reports
  • Websites of organizations involved in this issue, such as think tanks, NGOs, or the World Bank
  • Public datasets
  • Your program archives – data and reports from earlier iterations of the program can be very valuable!

 The free Zotero plug-in provides an easy way to save, organize, and format citations collected during internet research. Note that Zotero can help you start your annotated bibliography, but it is not a substitute since it does not include any summary or interpretation of each study’s findings.

How to compile evidence, method 1

Start with the 3ie Development Evidence Portal, which has compiled over 3,700 evaluations and over 700 systematic evidence reviews. Steps 2-7 of this example are specific to locating evidence on the 3ie website, but you can also consider looking for a review by J-PAL or Campbell Collaborations or the Cochrane.

For example, suppose your goal is to increase immunization rates in India. Type “immunization vaccination” or other related terms into the search box, and click the magnification lens to search.

The search results include individual studies, which are usually about a single program in a single location, as well as “systematic reviews”, which is what we are looking for because they are more comprehensive. To show only the systematic reviews, on the left of the screen under Filter Results, click on PRODUCTS and check the Systematic Reviews box. We’re now left with 17 evidence reviews related to immunization.

Now you might want to further narrow your search by region or country. In our example, suppose we want to see only those evidence reviews that contain at least one study from India. Click on COUNTRY and scroll down to click on India.

There are still 9 evidence reviews! Now read the titles of each review and start going through the ones that seem applicable to you.

  • Note that they are sorted with the most recent first, which is helpful as newer reviews tend to be more comprehensive.
  • 3ie has made the hardest part – assessing how strong the evidence is – easy for us. They use a 3-star scale to indicate the level of confidence in the systematic review.
  • In this example, the most recent review, Interventions For Improving Coverage Of Childhood Immunisation In Low- And Middle-Income Countries, is also the only one rated 3 stars (high quality). Click on its title.

The next page gives you an overview of the study. If it is “Open access”, this means you can read it for free – click “Go to source” below the star rating. If it isn’t open access, you can try some of the strategies in Step 9 to see if you can find the study for free elsewhere.

Clicking on “Go to source” opens a new tab with a PDF of the article. Don’t be intimidated by the length and technical terminology, and start with the summary – these articles usually include an “abstract” and sometimes a “plain language summary” and/or “summary of findings”.

The summary will likely be useful but too vague – dig into the review and look for details about which programs were tried and where, and how well they worked.

  • Keep track of which programs and studies seem particularly relevant, so that you can look them up later.
  • Consider the conclusions of the authors of the systematic review – are there trends that emerge across countries and contexts that are relevant for you? Overall, what are the main lessons from this review that you take away?
  • Be sure to read with a skeptical mindset – just because something worked in Japan doesn’t mean it will work in India – nor does it mean it won’t. And just because something worked in India before doesn’t mean it will continue to work – context is more complicated than country! Think about the evidence you find as well-documented ideas, but not the last word.
  • You can skip the parts about the methodology followed by the authors of the systematic review.
  • If the systematic review was helpful, add it to the bibliography.
  • Copy the citation from the references section and paste it into a search engine.
  • Usually, the first result will be the full paper on a journal’s website. If it is open access, you can read it directly. A lot of academic literature is not open access, unfortunately. Here are some tricks you can try if the article is not available:

a) Go back to your search and see if you can find a PDF posted on one of the authors’ websites – authors often share “working papers”, which might differ only slightly from the final paper, for free on their site.

b) Email the paper’s authors if you can’t find it elsewhere – many researchers are happy to share a copy with people looking to learn from their experience.

  • Read the paper. You probably don’t need to read all of it – the abstract, introduction, a description of the program, the results, and the conclusion are probably enough, whereas sections on technical methods can be skipped. This paper may also include references to other literature that could be relevant to your program. Keep track of these references so you can look into them later.
  • Add the paper to the annotated bibliography if it seems relevant.
  •  

For each piece of evidence that you find, there should be a clear justification for including it in the bibliography, such as: it is a landmark study in the topic (i.e. it has a large number of citations or is cited by many other studies in your review), it is relevant to specific aspects of this evaluation (such as measuring similar outcomes, being conducted in a similar context, or evaluating a similar intervention), etc. However, there are no absolute standards for inclusion, and since not all studies will be used in writing up the review, it is better to err on the side of including a study in the annotated bibliography.

Repeat step 9 for every paper from the systematic review that you found relevant!

  • If an organization ran the program that was evaluated, you might be able to find information on the organization’s website. If not, try emailing the organization.
  • Sometimes people share program details elsewhere – blogs, policy briefs, videos, etc. Try searching more about the program and you might find something.
  • In our example, we found a review from 2016, which is quite recent. However, keep in mind it can take 1-2 years to write and publish a review – and since the review is citing only published literature, the cited articles would be a year or two old as well. This means that it is likely that this review is missing anything done since 2014 or 2013, and hopefully the world has learned a lot about how to address your problem since then. While this shortcut helped you find relevant evidence, you might still want to use Method 2 so that you can see what has been learned since 2014.

 

  • This method used only academic sources. Non-academic sources are also a very useful source of information, and you should look into them. In Method 2, we have included a list of non-academic sources to consult.

Process evaluation vs monitoring: Which one do you need?

Process evaluations and monitoring both provide information on how your program is running and whether it is meeting expectations. The key difference is that process evaluations are a one-off activity, while monitoring is ongoing. That means that process evaluations are often more intensive exercises to collect more data and dive deeper into the theory of change. In contrast, ongoing monitoring must not overburden program staff and often tracks just a few high-priority indicators that are critical to program success.  

Consider the following questions to help you decide between conducting a process evaluation and building a monitoring system:  

1.     Are you interested in identifying specific problems or general problems? 

Process evaluations typically identify general or systemic problems along the theory of change, whereas monitoring typically identifies specific entities (e.g. service providers or locations)that need more attention.    

2.     Are you looking to hold program staff accountable?   

Both process evaluations and monitoring are implemented for learning – is our program being implemented as planned? If not, at which steps is it breaking down? However, if you are seeking an accountability system, monitoring is better-suited as it is continuous, whereas a process evaluation is a one-time exercise.  

3.     Do you need ongoing data on how your program is performing?  

A process evaluation typically offers a snapshot in time, whereas monitoring involves ongoing data collection and analysis for the entire duration of the program. For example, a process evaluation may do in-depth interviews with program participants on their experiences, whereas a monitoring system might collect data on just a few questions related to beneficiary satisfaction.  

4.     Do you need comprehensive data?

‍A process evaluation is typically based on a sample, while monitoring is usually comprehensive. For example, in a teacher training program, you would monitor the training of all teachers (because it is useful to know exactly which teachers did not attend the training), whereas in a process evaluation, you would interview a subset of teachers to understand the reasons why they did not attend the training.