TechNet-21 - Forum

This forum provides a place for members to ask questions, share experiences, coordinate activities, and discuss recent developments in immunization.
  1. David Brown
  2. Immunization information systems & coverage monitoring
  3. Thursday, 12 January 2017

Poor decision making due to "poor data quality", meaning data that are ill-fit for the decisions that need to be made, is one of the biggest challenges we confront in our efforts to improve the health and well-being of women and children around the world. Globally, many (though not all) leaders now recognize that poor decision making and poor data quality threaten to stall the progress made over the past 20-25 years. We recognize the problem and have talked at length about it, but now we must tackle these issues with urgency and bold action. Translating current commitments in health systems strengthening and child survival improvement into more visible action presents opportunities to reimagine the future if we collectively seize those opportunities.

The challenges of achieving such transformations is formidable, however. For example, many national immunization programmes continue to struggle to ensure that information systems are appropriately resourced to provide the necessary information to best manage their programmes. Facility-based record systems are ill-suited in many places and fall short of providing data that are fit for purpose. Home-based records, perhaps one of the most under-appreciated tools within immunization delivery and primary healthcare more broadly, are often not available, not adopted and/or appropriately utilized to fulfil their intended purpose.

Unfortunately, the inefficiencies and associated costs of poor decision making — costs that exist as a result of the current state of affairs with regards to our frontline capacities (or lack thereof) for decision making and the data on which those decisions are based — are not well recognized or understood. If they were, I believe, those same global leaders mentioned above would be moving more quickly to identify solutions and mobilize necessary human and financial resources within current investment packages. Again, unfortunately, few seemingly recognize that the long-term investment costs in improving our decision making capacities and the data on which decisions are based will be far less than the costs of the status quo and existing inefficiencies. In the private sector, CEOs would be all over the inefficiencies that exist in our field.

Now, this is not to say that there necessarily needs to be a massive resource mobilization (though in some communities where the immunization information systems have been so severely neglected for years this may indeed be true). It may well be that much can be done with existing programme resources using human centered design approaches to optimize what is already in place (e.g., See as well as through innovative solutions as being done with the MyChildCard approach ( for which early results are promising (;

IF we maintained a greater awareness of the inefficiencies resulting from poor decision making and a desire to reduce resultant inefficiencies, I believe a common sense business case exists for national immunization programmes to more consciously invest in home-based record systems, alongside investments in the facility-based administrative recording and reporting systems, as a critical component of an immunization programme’s overall programmatic intelligence strategy.

I look forward to the views of others on the topic as we champion creative solutions to the existing challenges while ensuring that the path we are choosing will be sustainable in the long-term.

Dr Daudi Manyanga Accepted Answer

The concerns are still valid and will countinue to be an issue in regards to data. I do agree that, health facility data are equally important, like HBR. Nevertheless much investment is being directed to facility-based data. I think this actually depends on how we will aggregate the data for improved decision making at a certain agreed quality and precision levels. My main issue of concern actually is that we are collecting many variables for both facility-based data as well as HBR. I am not sure if time is dedicated at some point to deciding about the purpose and scopes of our M&E systems. The plan on how to collect data and manage the collected data can be easily imitated based on the available technology and experiences. Nevertheless, most countries invest much on tools, transmission devices, but less on data analysis and resources; therefore it is difficult to reap out of the investment. Finally this ends up in a scenario of data being collected and transmitted up to higher level without being used for improved decision making, eventhough it suffices the programme monitoring part.

Narayana Holla Accepted Answer

Dear Sir / Madam

Thanks for the post and the deep concern with which you have reflected.

  1. Facility-based record systems are ill-suited in many places and fall short of providing data that are fit for purpose.

Inappropriateness of facility based recording and reporting, policy decision regarding HMIS reporting, use of HMIS based indicators for reviewing the performance of grass-root level workers we are also facing problem in our country, as I learnt from the service providers of planning units attached to our Medical College.

This has been reflected as “HMIS”o-genic depression – True case and its management, available in Technet-21 for the global viewers - attached for ready reference. Though there is no reciprocation, we only hope the post had some impact in mitigating the agony of ANMs and adopting alternate method. 

  1. Home-based records, perhaps one of the most under-appreciated tools within immunization delivery…

Home-based record especially for vaccination is also very much neglected, especially in the private sector. But currently, there is a revised design provided by the government for the National Immunization Schedule (NIS), though optional vaccines are not included as a constraint. It is really helping in closing the population immunity gap, vaccinating close to the schedule.

Combo-card having both NIS 'as it is' from the government HBR as part A and the country specific optional vaccines as part B can greatly solve the problem of private sector in India. Their vaccination data will be compatible for reporting through HMIS. On sharing the PPT on Combo-Card, senior consultants from Geneva also expressed that if it can be adopted by all the private vaccination service providers, it will be of a great achievement in India.

I have reflected this repeatedly starting from our college in the Academic Society Meeting, local health authority, District, State and the center but with no reciprocation till now.

KVG team proactively communicated to all known RI stakeholders – both private and the government including partner organizations as to what we can do in one day to within one year. [The list is once again attached for ease of reference].

We can definitely solve the HBR issue in just one day at both district and state level provided stakeholders 'order us' do it. Approach and methodology are ready with us. This incurs no extra expenditure to the government, and yet can bring a great name to whoever procatively implements our method and solve the HBR problem.

With regards,

KVG Team   

Attachments (2)

I have been reflecting about this post for some time now. Furthermore, as I am reading Predictably Irrational: The Hidden Forces That Shape Our Decisions by Dan Ariely 2008, this post came back to the forefront of my brain.

How do we make decisions and how should we make decisions? Data we have, and as Xavier stated, we don't know what's the level of quality that makes data usable to, at least, point in the right direction. David - your point is so relevant about to even start thinking how much we are paying for inneficiencies. What can we lean from the private sector, from behavioral economics, even from machine learning? 

What are readers views of being explicit about decision-making, efficiencies and plain economics in the post-2020 immunization program?

1) there is no perfect data; therefore, the questions is not good/bad data but what is the acceptable level of data quality to make sound decisions;

2) the problem, therefore, is not poor data quality, but ignoring the quality of data;

3) decisions are difficult because there is uncertainty; decisions are and can be made under any level of uncertainty;

4) data for decisions is much more than the HMIS; actually, the HMIS is a little part of the data needed for decision making;

5) we need robust evidence to understand how decisions are made and how data is used.

Dr Daudi Manyanga Accepted Answer

Ideally the decision making process needs sufficient information which will be generated from data. In other words, data processing skills cannot change the actual situation if primary data are of inadequate quality. I actually disagree the ideas that,” poor decision making may not be related to the data at all” especially in health programme including immunization. In some instances, one can have negative dropout rates in routine immunization data, negative days in surveillance, over 100% coverages while there are vaccines stock outs, and like information. This can happen, disregard your exile capacities and capabilities in analyzing data to provide informed decision. I think that is why ‘data quality” is an important agenda in any country.

I do agreed that, in most of LMIC the primary level of services may do have inadequate capacities and capabilities in making analysis and use the information for action at that level, however at level 2 (district level) and level 3 (provincial level) there capacities to a certain extent. There is no way if data gathered from health facilities if it is of poor quality can be used to make good decisions at higher level apart from decisions of improving its quality.

In this regard, in designing a system HIS/HMIS one should think mechanisms of capacitating the level one rather than using that level as transmitter of data and will receive information after being analyzed at higher hierarchy. So in summary, the decision making are actually based on the data (quality, completeness and timeliness) and capacity to use data to improve decision from the point of data collection.

David Brown Accepted Answer

Dear David and Nasoor,

Thank you for your comments. Absent from the replies, which is consistent with the current environment in health and immunization information and intelligence systems, is a narrative around the lacking thoughtful consideration of the costs of the counterfactual. It seems critical that there be greater dialogue aroundthe inefficiencies and associated costs of poor decision making. Indeed the poor decision making may not be related to the data at all, but rather to the capacities to analyze and synthesize information from a variety of sources to make an informed decision, particularly at select places along the immunization delivery continuum. My opinion remains that until the leadership at global, regional and national levels begins to consider the costs of the inefficiencies that exist, there will be little meaningful, sustainable movement forward within immunization information and intelligence system investment(s).


nassor Accepted Answer

It is always easier to associate poor decision making with poor data but how many times do people make poor decision based on the poor data?? I do agree that poor data may lead to poor decision but we should also acknowledge that not always decision makers (especially in developing countries) make decision based on the data and that is the source of poor data to be a chronic problem in most developing countries. To me, culture of using data for decision making will resolve the issue of data quality and ultimately people will make decision based on the good quality and reliable data. If the primary aim of collecting data is to report to the higher level, we should not expect good quality data. But if we managed to change the mind-set and all health care workers acknowledge that, the primary aim of collecting data is to help doing proper/evidence based decision then the quality of data will improve and ultimately we will resolve the issue of poor decision making due to poor data quality in a sustainable way.

Another issue which I see that compromises the quality of data is collecting data for no one use or collect data in duplicates. In many developing countries there is acute shortage of Health Care Workers and therefore asking them to collect data for no one use or collecting data in duplicates means adding workload to already overwhelm health care workers and the price for that is poor quality of collected data. We need to be very wise when asking health care workers to collect more data and we should do critical analysis of the system if it can accommodate that additional data collection before asking them to do so. I know sometimes there is a push for data to be collected simply because there is a project need to monitor that set of data but after the project no one look at that data sometimes for years and we still expect the data to be of good quality.

Dr Daudi Manyanga Accepted Answer

Evidence based decision making is very critical for an appropriate and well-functioning management including in health sector. Inadequate decision making can absolutely contributed by inadequate information which also may be in terms of amount of information, quality of information and even duration of such information. In health sector major road block of inadequate decisions can be results from data generated from the Health Information System (HIS) or rather called Health Management Information Systems (HMIS).

Monitoring is defined as a continuing function that aims primarily to provide the management and main stakeholders of an ongoing intervention with early indications of progress, or lack thereof, in the achievement of results. This definition is broader when compared to the traditional which define monitoring as the process of routinely gathering information on all aspects of the project. Taking advantages of the two vas On the other hand, information system can be described as an integrated set of components for collecting, storing, processing, and communicating information. It’s a combination of hardware, software, trained personnel’s engaging in the initiation/designing, planning, executions, controlling and phasing out/closing. For a well-functioning HIS or HMIS, the important thing to be taken on board are the (i) How was the design and set up of the system; (ii) Arrangements made for gathering and managing information; (iii) Critical reflection (based on the information gathered and experience) to improve decision making and; (iv); Communicating and reporting the results. In most cases, especially for the developing Countries there is a weak linkage between the steps and finally in some instances instead of improving health the systems may somehow failed to uncover the reality.

Furthermore, while designing the systems, the scopes for initiating systems can be too ambitious by creating indicators in which the available systems and investment done does not have capacity and ability of gather such information. In most of the projects including health projects, monitoring and evaluation functions are under budgeted in terms of resources (material, finance and human resources), while in actual fact the monitoring and evaluation system is the source of increased evidence based/informed decision making towards success.

In terms of critical reflection capacities is very low, most HIS/ HIMs systems critical reflection is expected at the top instead of being done at the point of data collection to increase quality, efficiency and effectiveness.

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