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<h2 class="hd hd-2 unit-title">Introduction</h2>
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<h4>Introduction</h4>
<p>Before the term "mHealth" was coined to mean the use of mobile technology in the health setting, pioneers were trying to utilize the earliest of such computers to collect health data in the field. The first paper referencing this appears to be "Revolutionising health data capture: use of hand-held computers" by K.C. Lun et al, and written twenty-five years ago, in 1989. </p>
<p>These early attempts at mobile electronic data collection (MEDC) were based on newly available pocket organizer computers like the Psion Organizer II XP (Figure.1), and by the late 1990's on more advanced, touch-screen devices like the Palm Pilot and the Apple Newton. Despite the limitations of these devices, numerous attempts were made, and numerous articles published extolling the benefit of this approach when compared with paper.</p>
<p><b>Figure.1</b> Psion Organizer II, circa 1986. (Credit: Boris Cornet)</p>
<p><img src="/assets/courseware/v1/55dc405f85ccfb1a47eaabc9c6df965b/asset-v1:MITx+HST.936x+1T2019+type@asset+block/Screen_Shot_2016-08-29_at_1.21.12_PM.png" width="245" height="366" /></p>
<p>For all the promise of those early experiments, widespread adoption of mobile technology for data collection remained elusive and newsworthy, because both hardware and software suffered from limitations of complexity and expense – and two decades after K.C. Lun’s pioneering work, the vast majority of health data in poor countries is still collected laboriously on paper.</p>
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<h2 class="hd hd-2 unit-title">Overcoming early limitations</h2>
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<h4>Overcoming early limitations</h4>
<p>As an example, in poor countries, a typical example of data collection might be a household survey done for the purpose of determining the rate of malnutrition in a child population in, say, Southeast Asia. This would typically involve a form consisting of 30 or more questions printed on several sheets of paper. A sample of several thousand households would be selected for inclusion in the survey and then the survey team would go to each household with a paper copy of the form and fill it out based on the information provided by the residents of the household. After collecting the thousands of completed forms, someone would be tasked with then typing all the collected information from the paper forms into a computer database – a laborious and error-prone process.</p>
<p>More recently, however, two major technological developments – the mobile phone, representing widespread, affordable computing hardware, and the World Wide Web, representing widespread, affordable access to information – have provided the means to overcome these two limitations (Table.1).</p>
<p><b>Table. 1</b>Overcoming early limitations</p>
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<p></p>
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<p> Limitation</p>
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<p> Solution</p>
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<p></p>
<p>hardware</p>
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<p>Pocket organizers never reached the level of popularity, particularly in poor countries, that would have driven the price down and allowed greater scale</p>
</td>
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<p>The explosion of mobile phones has driven mobile computing costs down to the point that devices are now commonplace even in poor countries</p>
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<p>software</p>
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<p>Software for early devices was always too complex for the non-technologist, requiring expensive personnel to configure</p>
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<p>The Web has provided a platform for distribution of inexpensive and easy-to-use software – and lots of examples to emulate</p>
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<p>Now the average person in Nairobi, Kenya has a computing device in their pocket that cost less than $50 but which has orders of magnitude more computing power than NASA did when they put men on the moon in the 1960s. And though few pieces of software can rival Facebook for complexity and functionality, a ten-year-old can set up their page in minutes. </p>
<p>Affordable, ubiquitous hardware and simple, self-service (i.e. configure-it-yourself, without programmers or consultants or special training) software are now – finally – revolutionizing health data collection in the field on a larger scale.</p>
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<p><span style="font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif; line-height: 25.6px;">Andrew Kanter MD MPH</span><br style="text-rendering: optimizeLegibility; line-height: 1.4em; font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif;" /><span style="font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif; line-height: 25.6px;">Chief Medical Officer</span><br style="text-rendering: optimizeLegibility; line-height: 1.4em; font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif;" /><span style="font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif; line-height: 25.6px;">Integrated Medical Objects</span></p>
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<h3 class="hd hd-2">The Real Burden of Disease</h3>
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<legend id="7f011b4d03474ca5b2143f68d2b5d629_2_1-legend" class="response-fieldset-legend field-group-hd">What were the two major technological developments which have provided the means to overcome the early limitations in mobile electronic surveys and data collections?</legend>
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<h2 class="hd hd-2 unit-title">Key points for mobile data collection</h2>
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<h4>Key points for mobile data collection</h4>
<p>Mobile data collection is finally becoming more common, after more than two decades of gestation. Increasing prosperity in developing countries, the spread of the internet, and new business and technology models are all creating new opportunities that make it feasible for almost any organization or individual to consider this approach. Every day it seems there are more software and hardware possibilities, and this has the potential to vastly increase available data, improve data quality, and save enormous amounts of money currently spent on paper-based activities.</p>
<p>As described, there are currently many options for mobile electronic data collection that make it practical and affordable. Prior to implementing a mobile electronic data collection system, there are some key points for anyone contemplating this approach to keep in mind:</p>
<ol>
<li><b>Cost</b> – When determining the cost of using a system, it’s important to include <i>all</i> costs in your calculations. Some systems charge per interview conducted, others per data collector. Others charge nothing for the software but require expensive programmers or other consultants in order to configure it. Sometimes, those programmers and consultants may need to be traveled to the field, another large budget item. A planning budget should compare the costs for hardware, software, personnel (trainers, programmers, consultants), travel, per diem and daily rates, data transmission costs in-country, etc.</li>
<li><b>Hardware selection</b> – there are now a very wide variety of mobile devices at a range of prices. Any Android or iOS device can be used with a variety of systems, and as of this writing it is possible to get a very functional Android device (including GPS capability) for as little as $75 (and that price is gradually but consistently declining). If SMS data collection is planned, then any mobile phone at all can be used, with units available for as little as $10. Regardless of the device, it will be important to test its operation in the field, preferably by purchasing and testing only one or two, prior to buying in large numbers. It is also good practice to read online reviews, paying close attention to reports of battery life, screen quality, and durability.</li>
<li><b>Preparation</b> – With any technology field work, it’s important to plan for delays and technology issues: delays in form design, delays in training, delays in fieldwork, poor internet connectivity, loss of electrical power, etc. Those with experience of any mobile data collection activity will know to build time into the schedule to allow some flexibility, and to always have a Plan B in case Plan A fails (e.g. even if you’ve planned to have your data collectors upload data from the field, train them what to do if they do not encounter an adequate cellular signal in the field).</li>
<li><b>Motivation</b> – When thinking of using mobile devices for a pre-existing paper-based data collection activity, remember that if data collectors on the ground are not collecting data on paper it is unlikely that they will collect it using a mobile phone or tablet. Failure to collect data may reflect poor pay, lack of supervision, lack of security in the field, lack of fuel for vehicles, or many other factors – and bringing in mobile devices will not, by itself, solve any of them. Any successful data collection will need to consider the existing, and the possible, incentives and disincentives required to ensure that the data collectors will, in fact, use the technology.</li>
</ol>
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<h2 class="hd hd-2 unit-title">Example: Open Data Kit</h2>
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<p>Andrew Kanter MD MPD<br />Chief Medical Officer<br />Integrated Medical Objects</p>
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