groups » Trial Management » Electronic treatment information for healthcare workers, and district surveillance schemes
I am looking for advice on a couple of items. I will be working in Latin America with patients with the genetic disease Huntingdons Chorea (though my questions are not disease specific!). There has been no research in this patient group in this area before so we are starting afresh. For more information on the work we are doing, see: http://factor-h.org and www.chdifoundation.org.
I will be spending 10 days in late Feb visiting the communities, including meetings with the physicians, caregivers, and also the local authorities. I wanted to discuss with them whether having an accessible (web and smart phone-ready) tool to guide caregivers, families etc as to what to do with the care of Huntingdons Chorea affected subjects – eg “in case of a fever, do this”, might be useful to them. It would also provide information as to local contacts nearby, etc.
Have you ever done anything web-based that I can use as a model? Any lessons there?
Another topic relates to both factor-H and CHDI work in LatAm. Both require a ‘census’ of where the patients are and their family structure- any advice you can provide to (a) protect the families, (b) include the local researchers/physicians to get this done promptly would be helpful. Without a census all of our efforts will fail – so this is the first step. Anything else I should be looking out for? Do you have any presentations I can use to start these discussions?
Many thanks in advance.
In regard to the 'app' then there are several options for this. In Kenya we provided fieldworkers with handheld PDA's (these are very cheap there) research teams were able to load these with a simple programmed tool that we used for part data collection and part guidance. This was for malaria and they were visiting kids in their rural village homes. It worked like this; when they went into the programme they were asked 1. Does the child have a fever? And if yes then they had to record the temperature and if higher that 37.5 they had to do a fingerprick test and record the result, and then call one of the team and treat the child. All the data was captured and the programme took them through the care alogrithm. This example used pendragon software for this and it worked well – but it was a low cost solution. Your solution will largely depend on your budget. You need the devices and some form of programming to create what is effectively a decision tree 'app'
There was a discussion on this on Global Health Trials last year http://globalhealthtrials.tghn.org/community/groups/group/data-management-statistics/topics/202/ that talks about some of the issues. It seems your situation is easier because you want it to use a decision tree to guide rather than collect data – is that right? Although I think I would try and use the opportunity to have it capture the answers and thereby provide you with some useful epi data.
Many groups who have used this
In regard to your census then this could use the smartphone / PDA app as above about to collect basic epi data. There is much experience with this with district surveillance systems in Africa where similar to above basic data are collected on handheld devices with GPS included so you can map and locate your participants in your survey. The important elements that you need to think about are data protection, consent and ethics. For all of which there are good strong solutions that others have tried and tested in the field: I am sure the Global Health Trials community will be able to help.
We hope this is of help and encourage others to add their experiences
We have a good deal of experience of this within our network and we would be pleased to help you. As a starting point and I think for a swifter response, the best is to provide the following references as well as the INDEPTH website which has lots of information on starting such research programmes www.indepth-network.org:
1. Yé Y, Kyobutungi C, Ogutu B, Villegas L, Diallo D, Tinto H, Oduro A, Sankoh O (2012)
Malaria Mortality Estimates: Need for Agreeable Approach.
Tropical Medicine & Intl. Health Epub ahead of print doi: 10.1111/tmi.12020.
2. Yé Y, Wamukoya M, Ezeh A, Emina J, Sankoh O (2012)
Health and demographic surveillance systems: a step towards full civil registration and vital statistics system in sub-Sahara Africa?
BMC Public Health 12(1): 741.
3. Sankoh O, Byass P (2012)
The INDEPTH Network: filling vital gaps in global epidemiology.
Int J Epidemiol 41(3):579-88.
4. Sankoh O (2010)
Global health estimates: stronger collaboration needed with low- and middle-income countries.
PLoS Med 7(11):e1001005.
5. Bangha M, Diagne A, Bawah A, Sankoh O (2010) Monitoring the millennium development goals: the potential role of the INDEPTH Network.
Glob Health Action 3 doi: 10.3402/gha.v3i0.5517.
We wish you well and congratulate you on your efforts
This is a long post, and I'm hoping it will provide some help. Its short on answers, but contains a number of questions and issues where you will need to make decisions about the technology. There are many projects that have successfully used mobile technology, some of which are mentioned above. However, I'm also aware of projects where the technology has failed the project - its more difficult to account for these as the results are never published, but I feel the number is not insignificant.
First off, I do not know South America at all (apart from finding it on Google maps) but I'm assuming it is similar to Africa in technology terms - a) pockets of good networks but vast areas of the country where network connectivity is slow and intermittent and b) very low computer literacy levels in general. My background is IT and the mobile phone industry and I'm currently researching (as part of a master's thesis) the use of basic mobile phones for clinical research by community health workers. This document is my own thoughts about use of mobile phones in developing countries, and you could find more information through a local Computer Science department
I see a number of challenges you'll have to overcome to successfully deploy a mobile smart phone for use in your project which I cover under the various headings. There is no particular order of importance, but the first two will be easier to assess as they are based on hard facts while the rest relate to the skills and abilities of the users.
I also see two distinct user communities - the care givers who have a certain level of literacy and can be trained to use the phone apps, and patients and their families who will have a wide range of skills and experience in the use of mobile apps.
I do not know your cost model, but I am guessing that care givers will be provided with smart phones and their network costs will be paid.
The families will be more difficult to subsidise, unless you also plan on giving them a smart phone and paying for its network costs - however, the families could then use the smart phone for their own calls at your expense.
If you want the families to bear the cost, your solution may be too expensive for them to afford. In terms of affordability of the smart phone, I did some affordability calculations last year for another debate which I based on a brief internet search for doctors salaries and cost of phones.
A newly qualified doctor (GP) in the US works less than 3 hours to cover the cost of an iPhone 4. A similar doctor in South Africa works 4.5 days. In Kenya he would have to work for about 18 days while in Malawi the doctor would have to work over 200 days to cover this cost. This is a mind blowing figure. I know there are cheaper smart phones than the iPhone, but the costs are of the same order of magnitude and the results should be similar.
Network costs are also high relative to earnings.
In Africa it is not uncommon for people to have a mobile phone and up to three SIM cards because each operator has different tariff structures. The user will open up his phone and change SIM card when he wants to send an SMS as it is cheaper, or when he wants to call a landline phone, he will use the 3rd SIM. It is only a matter of cents difference between the tariffs, but they are so poor they have to budget every cent.
The point I'm trying to make is to ensure the technology will be affordable to the poorest of your target population.
2) Network capability vs Phone and app capability:
In Africa, many cities (possibly most cities) have a relatively high speed mobile phone network supplied by more than one operator. However, outside the major cities and a few special areas, network speeds are low, and the quality of the connection is often poor, intermittent and in some areas no connection is available.
I have seen more than one solution designed in the developed world that has been thrust on us by funders that just does not work in our context because it relies on high speed always available networks. This is typical of web-based solutions, as well as some other solutions that are designed as if they were to be used in an office.
I suggest very strongly that you use a phone and app combination that can store results on the phone and only upload them when a connection is available. Epihandy mentioned above is one such and another that I am familiar with is openXdata (www.openxdata.org) - however in my research I uncovered more than 35 survey type applications for mobile phones.
3) Application type
You have identified two application types - one for a census and one as an online help facility.
For the census, many of the survey type apps can support your requirements. I suggest that local support/familiarity should influence your decision - openXdata has been used in South America and is available in a Spanish version, and there are probably others.
For the online help, I would stay away from a web based solution (see above). I would rather consider one where the information is stored on a SD card that can be inserted into the phone - medhand (www.medhand.com) is one such I have come across, but I must admit I've never used it.
4) User literacy
I do not mean 'can they read and write', but rather 'are they computer literate' type definition. In my research project I've coined the term 'mobile-phone literate' as I have come across people who are functionally illiterate (never went to school) but they can perform quite complex transactions using their mobile phones (in Kenya you can buy a hamburger from your phone airtime!!). I have also found that people who are used to basic phones struggle to master the virtual keyboard of a smart-phone and vice versa (one of my study participants kept swiping the screen to scroll down on a basic mobile phone handset).
While you will be able to select the care givers who can manage the chosen smart phone and provide them with training, you can't select the patients! Assuming that many of these patients will be from the poorer section of the population and not familiar with smart-phones, you may need to look at a less sophisticated help system for them that can be used on a generic mobile phone (what we call J2ME) and an 'all bells and whistles' one for the care givers.
And that's it for now. Just drop a note here to get more clarity on anything I've mentioned, and anything else you think I may be able to help with.
I hope this is useful and I wish you all success on your project.
Sorry, I forgot another key issue you will need to keep in mind, but have no control over;-( A large issue in remote areas in Africa is lack of power/electricity in rural areas. In many villages, people take their phones to a loacl shop where the owner has a petrol generator and charges them for charging. While phones do not use much power, smart-phones do use much more than the basic handset and some have very limited battery life when using complex apps such as the help facility. This could be a problem for the care givers if they travel to remote villages.
This recent review could also be on interest to those contributing to this thread:
The Effectiveness of Mobile-Health Technologies to Improve Health Care Service Delivery Processes: A Systematic Review and Meta-Analysis
Caroline Free, Gemma Phillips, Louise Watson, Leandro Galli, Lambert Felix, Phil Edwards, Vikram Patel, Andy Haines
Caroline Free and colleagues systematically review controlled trials of mobile technology interventions to improve health care delivery processes and show that current interventions give only modest benefits and that high-quality trials measuring clinical outcomes are needed.
Sorry team, but I do not think the above review is useful here. My criticisms of this are:
1) "...nearly all were undertaken in high-income countries" - there are significant other issues encountered in the developing world.
2) The review is comparing apples and oranges. The applications range from appontment reminders to diagnosis from images!
On the other hand, there are definitely a number of successful 'census' type projects, some mentioned above, but also
a)The use of mobile phones as a data collection tool: a report from a household survey in South Africa
Mark Tomlinson et al
b)Electronic Community Care Giver Study: a formative evaluation of the implementation of an electronic monitoring and evaluation solution for CCG programmes.
Ogumefun C, Mothibe N, Friedman I.
Unfortunately I don't have references to the on-line help type applications at my finger tips, but I know there are successful implementations out there.
Also bear in mind that Ignacio's case is a fairly standard 'census' and a standard 'on-line help facility'. There is no need to limit it to instances for medical research or health in general.
Hope this helps the debate
I have a particular interest in neurology so am interested to hear about your plans, though I am afraid I can't help with the mobile data capture or DSS - but I noticed this recent article in the Lancet, on this this topic, and thought you may be interested (though of course you may already have seen it!):
thank you everyone for your help. A few more useful bits of information here:
http://www.ghdonline.org/tech/discussion/lessons-from-mhealth-projects-tech-is-the-easy-par/ - this article by Sarah Arnquist of Global Health Hub talks about the challenges of mHealth and how to set achievable goals)
In response to Mike's comment above, where he quite rightly points out that the studies mentioned in PLoS are mainly high-income countries, I also wanted to forward this article: http://www.lshtm.ac.uk/newsevents/news/2013/item23074.html - this is from the London School of Tropical Medicine and Hygiene, and mentioned some research from Low Income countries too on the same topic. Unfotunately it is not very extensive but I hope it helps.
And lastly, proving Mike's point further, here is a very imely article from SciDev.Net about the Evidence leacking in mHealth in developing countries! http://www.scidev.net/en/health/news/evidence-lacking-on-mhealth-effectiveness-in-poor-countries.html