Session: Clinical Settings
CHI 2013: Changing Perspectives, Paris, France
A Matter of Life and Death: Practical and Ethical
Constraints in the Development of a Mobile Verbal
Autopsy Tool
Jon Bird1, Peter Byass2,3,4, Kathleen Kahn2,3,4, Paul Mee2,3,4 and Edward Fottrell2,5
1
UCL Interaction Centre, University College London, UK, jon.bird@ucl.ac.uk
Umeå Centre for Global Health Research, Umeå University, Sweden, peter.byass@epiph.umu.se
3
MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health,
Faculty of Health Sciences, University of the Witwatersrand, South Africa, kathleen.kahn@wits.ac.za
4
INDEPTH Network, Accra, Ghana, paul.mee@agincourt.co.za
5
UCL Institute for Global Health, University College London, UK, e.fottrell@ucl.ac.uk
2
ABSTRACT
Verbal autopsy (VA) involves interviewing relatives of the
deceased to identify the probable cause of death and is typically used in settings where there is no official system for
recording deaths or their causes. Following the interview,
physician assessment to determine probable cause can take
several years to complete. The World Health Organization
(WHO) recognizes that there is a pressing need for a mobile
device that combines direct data capture and analysis if this
technique is to become part of routine health surveillance.
We conducted a field test in rural South Africa to evaluate a
mobile system that we designed to meet WHO requirements
(namely, simplicity, feasibility, adaptability to local contexts, cost-effectiveness and program relevance). If desired,
this system can provide immediate feedback to respondents
about the probable cause of death at the end of a VA interview. We assessed the ethical implications of this technological development by interviewing all the stakeholders in
the VA process (respondents, fieldworkers, physicians,
population scientists, data managers and community engagement managers) and highlight the issues that this
community needs to debate and resolve.
Author Keywords
Verbal autopsy; mobile devices; ethics; HCI4D.
ACM Classification Keywords
H.5.m. Information interfaces and presentation (e.g., HCI):
Miscellaneous.
INTRODUCTION
Currently, the causes of two thirds of the world’s deaths are
not recorded [13] and the World Health Organization
(WHO) receives reliable cause of death statistics from only
31 of its 193 member states. This lack of knowledge about
mortality patterns is not only a concern for academic popuPermission to make digital or hard copies of all or part of this work for
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CHI 2013, April 27–May 2, 2013, Paris, France.
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lation health scientists: national and local health managers
also recognise that this information deficit impacts on their
ability to plan and evaluate public health interventions and
prioritize resources [3].
Verbal autopsy (VA) [15] is the process of interviewing
relatives or other close caregivers of a deceased person to
elicit the symptoms and circumstances of their death. At
present, trained VA fieldworkers use paper-based questionnaires to ask respondents questions about the signs and
symptoms of the terminal illness, typically including an
‘open history’ in which the respondent describes in their
own words the circumstances and sequence of events leading to death. These data are later assessed by two or three
physicians to identify the probable cause of death in a process known as physician-coded verbal autopsy (PCVA).
VA remains the best available approach for assessing causes of death in communities in which most deaths occur at
home [16].
PCVA is usually the most time consuming step in the VA
process. Although in simple cases it might only take a few
minutes for a physician to identify the probable cause of
death from a VA questionnaire, they typically do the analysis in their spare time rather than as a full-time job. For example, in Agincourt, South Africa, which was the location
of the field study described in this paper, it takes at least
one year and occasionally several years from the respondent
interview to the completion of a PCVA. InterVA
(http://www.interva.net) is well-established software that
can automatically and rapidly assign probable causes of
death to VA data that have been converted into a digital
format. Based on the answers to a series of yes/no questions
(with relevant skip patterns depending on the age of the
deceased and responses to filter questions), InterVA uses
Bayesian principles to identify probable causes of death.
Not only is the software significantly quicker than PCVA at
identifying probable causes of death (seconds compared to
years), there is some evidence that physician death certification can be highly variable and imprecise [11]. This is in
contrast to InterVA which, like any mathematical model, is
consistent and reproducible enabling causes of death from
different times and locations to be compared. To date, VA
Session: Clinical Settings
CHI 2013: Changing Perspectives, Paris, France
has predominantly been applied in research settings by
population health scientists. However, there is a strong desire from WHO, the Health Metrics Network, the US Centers for Disease Control and other major health organizations to extend VA methods to routine health surveillance,
outside of research settings [16]. This has led to WHO recently revising the standard VA questionnaires and a short
but useful list of diagnoses that can realistically be ascertained by a limited number of questions. InterVA-4 has
been designed to align with these new WHO instruments
and has integrated insights from previous versions of InterVA with expert consensus. Coinciding with these developments in automated interpretation, WHO further recognizes
the pressing need to develop mobile devices that facilitate
the application of VA for the routine registration of deaths:
“Users of VA have identified the need for simpler data collection instruments coupled with IT (e.g. mobile phones or
hand-held devices). These large scale users of VA have a
perspective different from that (sic) one of researchers,
giving priority to the VA instrument’s simplicity, feasibility
and adaptability to local contexts, cost-effectiveness and
program relevance. A simplified VA instrument coupled
with automated methods to ascertain causes of death can be
a stepping-stone to increase the coverage of operational
and representative civil and vital registration systems.”
[13]
Combining the ability to record, analyse and store VA data
in a mobile device has a number of potential benefits, including significantly reducing the time taken to collect and
analyse and present it. This is primarily because using analysis software to automatically assign probable cause of
death means that the typically lengthy and unstandardized
PCVA stage is no longer required. Moving away from paper questionnaires to direct electronic data capture also obviates the need to convert paper-based VA questionnaires
into a digital form, further reducing data processing time
and cost as well as removing the potential for transcription
errors to be introduced at this stage. Data collection can also
be standardized and errors reduced by automatically ensuring that all and only the appropriate questions are asked. A
final potential benefit is that it is no longer necessary to
store large numbers of paper questionnaires (which can be a
significant overhead).
The development of a mobile, automated VA system also
creates unique opportunities for the feedback of probable
diagnoses to respondents in what are traditionally one-way
encounters. VA data collected during an interview are typically recorded on paper at the respondent’s home and then
taken back to an office where they are entered into a computer and later analysed. The results of the analysis are not
usually fed back to respondents although community-level
communication of aggregated results does occur [8]. A mobile VA system incorporating analysis software could compute the probable cause of death at the end of the interview.
It would then be possible for fieldworkers to feed this back
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to respondents and also provide them with relevant health
information where appropriate. For example, if the probable
cause of death of a respondent’s spouse indicated a lifestyle
disease, such as type 2 diabetes or chronic obstructive pulmonary disease (COPD), then the respondent could potentially benefit from information about a healthy diet or the
risks of smoking, assuming that they share a similar lifestyle to the deceased. The complexities of providing such
information need considerable thought, however, in particular when the information may be sensitive or cause the respondent distress. For example, this could occur if the probable cause of death is stigmatized, such as HIV, or when the
probable cause of death is an infectious disease, such as TB,
and a respondent could be worried that they too were infected. The precise means and ethics of providing respondents with the probable cause of death and health information have had very little consideration in the population
health research community. This is partly because scientists
collecting population mortality statistics typically see their
role as one of measurement rather than public health intervention. Another reason, as mentioned above, is that the
current VA process can take a year or more to determine the
probable cause of death after the interview. As a result,
providing immediate cause of death and health information
to individual respondents has remained a hypothetical issue.
Our initial goal in this study was to assess the data capture,
analysis and storage capabilities of a novel mobile InterVA
system (known as MIVA) in terms of the characteristics that
WHO has identified as necessary if VA is to become a part
of routine health surveillance; namely, simplicity, system
feasibility, adaptability to local context, cost-effectiveness
and program relevance. However, by combining real-time
electronic data capture with InterVA in a mobile device we
created a system that can compute the probable cause of
death of the deceased at the end of the VA interview. One
contribution of this paper is to highlight the new opportunities that arise from recording and analysing health data on
mobile phones. Another is to discuss how the field testing
of MIVA made the ethical implications of providing cause
of death and health information to respondents a very real
and pressing concern. We present the views of various
stakeholders on the risks and benefits of providing direct
feedback of cause of death to respondents, and whether,
given the technical ability, this should be done. We identify
the ethical issues, made apparent by the field study, that the
VA community should debate in order to clarify the role
that MIVA-like systems will play in health surveillance and
intervention. More generally, our study identifies ethical
issues that are relevant to the design of mobile devices that
both collect and analyse health data. A final contribution is
our discussion of some of the challenges of recording ‘open
histories’ on mobile devices. Our findings are relevant to
the design of mobile forms, in particular highlighting the
challenge of collecting unstructured data.
Session: Clinical Settings
CHI 2013: Changing Perspectives, Paris, France
RELATED WORK
Since the emergence of Human-Computer Interaction for
Development (HCI4D) in the late 1990s, improving
healthcare has been the focus of many projects [2, 6, 10].
PDAs have often been used to improve the efficiency and
effectiveness of medical data collection [7, 11]. The only
previous study we are aware of that uses a PDA to collect
and analyse VA data was carried out in 2008 in Burkina
Faso and Indonesia [4]. The system was used as part of a
one-off research project that evaluated a safe-motherhood
programme and therefore only focused on the deaths of
women of reproductive age. The implementation was successful, with hundreds of VA interviews being successfully
completed over 6 months and assigned a cause of death.
However, issues resulting from directly feeding back cause
of death information to respondents were only superficially
explored, establishing that respondents are extremely likely
to agree with the InterVA diagnosis of cause of death for
the simple reason that it is derived from a computer.
More recently, mobile phones have been increasingly used
for health data collection in the developing world, typically
lower-end devices because of their low cost, long battery
life and robustness. For example, CommCare [14] runs on a
Nokia C2-01 (~USD75), and in a longitudinal study in rural
India was found to be more effective than a paper-based
system and preferred by health workers because of the status derived from using the device and being able to use the
phone outside of a work context. However, smartphones are
reducing in price and becoming more robust and offer features such as processing power, larger screens and touch
interfaces. We chose a low specification smartphone in our
field study because of its ability to both collect and analyse
data as well as its longer battery life compared to more expensive devices.
Choosing an appropriate technology is one of the key characteristics of HCI4D projects that have successfully designed technologies to fit local contexts [9]. Two other key
factors are: first, building strong relationships with local
partners, carefully identifying all of the stakeholders involved (some of whom may have conflicting requirements);
and second, allowing users to participate, to varying extents, in the design process. These findings about relationships, participation and appropriate technology choice have
informed our approach, as we detail in the following sections, influencing our choice of site for the field study, our
design approach and choice of mobile device. In the next
section we describe the design of MIVA and how it was
shaped by the needs of multiple users and the WHO practical constraints.
SYSTEM DESIGN
Our goal in developing MIVA was to build a mobile
application for the direct data capture, rapid interpretation,
presentation and storage of cause of death information for
use in low-income settings. The software was designed to
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integrate the latest WHO VA standard questions with
InterVA-4 analysis software.
Users
The system has a number of different users, each with different needs, all of whom place practical constraints on the
design. First, are the field workers who will take the device
out into the field to interview relatives of the deceased. Second, are the local data managers whose job is to ensure
that the VA data collected by the fieldworkers is securely
stored in a form that makes it easy to analyse and present.
Third, are the respondents who are interviewed about the
death of a close relative. Fourth, are local, national and
global public health managers who need to plan and evaluate public health interventions and allocate resources. Fifth,
are population scientists who require mortality data for their
research.
We used a ‘weak’ participatory design approach, purposely
leaving parts of the design incomplete so they could be finished with the help of fieldworkers and data managers in
the field study. Our goal was to facilitate fieldworkers’
sense of ownership of the system and thereby encourage
them to provide useful feedback on the design, which can
be difficult to elicit in developing world contexts [1]. Two
researchers conducted the field study, one an experienced
VA researcher (EF), the other an HCI researcher and programmer (JB) who had developed the software and could
make rapid changes in response to feedback.
WHO VA standard questions
VA cannot ascertain all causes of death and does not perform equally well for all causes. Given these limitations,
WHO has developed standard questionnaires that ascertain
63 causes of death with reasonable accuracy from a VA
interview. An expert review group has created three standard questionnaires: death of a child aged under 4 weeks;
death of a child aged 4 weeks to 14 years; death of a person
aged 15 years and above. Each of these begin with a ‘general information’ module that records socio-demographic
information and information for data management, such as
time, date and location of the interview and a unique ID.
The subsequent modules include questions to ascertain the
signs and symptoms that help determine the probable cause
of death. Some questions relating to accidents and systemic
signs and symptoms (for example, for fever and intestinal
symptoms) are always asked; other questions are asked depending on the age and sex of the deceased. Our focus was
on designing a system that displayed only the relevant signs
and symptoms questions, given the age and sex of the deceased and answers to previous questions.
InterVA-4
The existing InterVA-4 software runs on Windows in batch
mode. The answers to the 246 WHO VA signs and symptoms questions are stored in a text file and, based on the
‘yes’ answers, the most probable cause or causes of death
are calculated using a Bayesian approach informed by a
table of probabilities associating symptoms to causes. The
Session: Clinical Settings
CHI 2013: Changing Perspectives, Paris, France
MIVA software was designed to use as much of the existing
InterVA-4 software as possible, in particular three spreadsheet files which specify: a) the order of questions; b) the
probabilities associating symptoms to causes (derived by
consulting experts); and c) the question skip patterns. These
files are used to configure the software each time it loads,
whereas the well-established Bayesian algorithm is hard
coded into the application.
Platform
Mobile devices, particularly phones, are the most widely
used technology in HCI4D [9], due to their widespread use
in the developing world, their cheapness, portability and
low energy consumption compared to laptops. Our goal was
to develop software that could be used on a wide range of
mobile phones. We therefore decided to develop software
that runs in HTML 5 browsers, a technology that is found
on many mobile devices and is cost-effective as all major
browsers are free to download. The software consists of an
HTML page that is stored locally on the mobile device.
JavaScript is used to implement the data capture and storage
functions. Some browsers, for example Firefox, have addons that enable the browser to run in full screen mode without navigation bars, which is useful as users cannot inadvertently navigate away from the browser while using the
system. For the field study reported in this paper we installed the software on four Sony Xperia U smartphones.
These were chosen for their small size, good battery life
(more than one day in offline mode) and low price
(GBP160). They can run all HTML 5 browsers, including
Firefox, Chrome and Opera and are therefore a good platform for testing the software on multiple browsers. During
the field study, the phones were used in silent mode and
auto-rotate was switched off as users found it both confusing and annoying when the screen switched from portrait to
landscape when they were conducting a VA interview.
Adaptability and maintenance
The software was designed so that it could be easily maintained and adapted to local contexts by non-programmers;
the key parameters of the system can be changed and updated using only a spreadsheet application. When the software is loaded in a browser it reads the three locally stored
configuration files described in the previous section. All of
these can be generated from spreadsheets using a script file
that comes with MIVA. For example, localization involves
translating the spreadsheet containing the English version of
the WHO VA questions into the local language, running the
script that converts the spreadsheet into a text file and then
uploading it to the mobile phone via a USB connection.
Updating the system with changes to the VA questions,
InterVA probabilities or question skip patterns is similarly
straightforward.
Interface
We purposefully designed the interface to be very simple
and have as few navigation controls on the screen as possible. Each question is presented, in turn, on a single screen
without any scrolling necessary. The system runs best in
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full screen mode without any browser controls or phone
utility bars visible (which can be achieved using freely
available browser add-ons). The interface consists of radio
buttons and two rectangular navigation buttons (a previous
and next button, the functions of which are communicated
symbolically rather than by text) (Figure 1). There are two
types of question: multiple choice, where there might be up
to 7 exclusive and exhaustive options, each of which can be
selected by a radio button; and simple questions with three
exclusive answer options: ‘yes’, ‘no’ and ‘don’t know’. All
of the questions are closed and involve selecting one option.
When a question screen is first presented to a user, none of
the radio buttons are checked. If a user tries to navigate to
the next or previous question before they have selected an
answer then the navigation button turns red and the user is
not able to move to another question. Once they have selected an answer the navigation buttons turn grey once more
and users are allowed to move to the next question or previous questions. If all of the relevant VA questions have been
asked then a small green circle appears at the bottom of the
screen between the navigation buttons. When this button is
pressed, MIVA stores the question responses in the browser’s local storage and takes the field worker to a finish
screen.
MIVA could at this point display the results of the InterVA4 analysis and show the calculated probable cause of death.
However, in the study reported in this paper, we decided to
withhold the cause of death information until the research
and community engagement managers better understood
any potential associated risks, and because the VA fieldworkers who were using our MIVA system recognized that
they did not have the necessary training to answer all the
questions that a respondent might ask about the cause of
death and its possible implications. In order to assess the
ethical implications of providing respondents with a probable cause of death at the end of the interview, as part of our
field study we not only evaluated MIVA but also interviewed the different stakeholders involved in the VA process (including respondents, fieldworkers, physicians,
population scientists, data managers and community engagement managers) to find out their views.
FIELD STUDY
A preliminary evaluation was designed to document and
assess the process of localizing the MIVA software, the
ability to train local fieldworkers in its use, the feasibility
and utility of MIVA for routine VAs, and opportunities and
risks in data storage, transmission and presentation. The
preliminary evaluation of MIVA took place in the Agincourt Health and Socio-demographic Surveillance System
(AHDSS), South Africa. Part of the INDEPTH international
network of HDSSs (www.indepth-network.org), the Agincourt study site constitutes a sub-district of Bushbuckridge
district, Mpumalanga Province, in the rural northeast of
South Africa. Since 1992, annual household surveys have
provided basic information on vital events, namely, births,
deaths and migrations. All identified deaths are followed-up
Session: Clinical Settings
CHI 2013: Changing Perspectives, Paris, France
Figure 2. Two fieldworkers conducting a verbal autopsy interview using mobile phones running MIVA
Figure 1. MIVA screen shots: Left – recording the age group of
the deceased. The previous question navigation button is greyed
out as this is the first question. Right – the final screen showing
a typical ‘Yes/No/Don’t know’ question and the green finish
button. The images show the questions in English but for the
field study they were translated into Shangaan, the local language in the Agincourt field study site in rural South Africa.
with a VA interview administered by a trained fieldworker
using a paper questionnaire. AHDSS currently covers approximately 16,000 households in 27 villages representing a
population of approximately 90,000 individuals [8].
The Agincourt site was selected as an ideal location to conduct the field study given the population’s and staff’s extensive experience in VA processes since 1993, making them
well-placed to compare MIVA to existing systems and provide feedback on MIVA and the WHO questions that it
incorporates. A further benefit of conducting the study in
the AHDSS is the ability to capture the views of a range of
end-users who routinely work with or are exposed to VA.
Field observations and qualitative data capture through unstructured interviews with all stakeholder groups complemented basic quantitative data on the duration of interviews
and interview completion rates.
Over a period of seven days spread over two weeks we
worked directly with four AHDSS VA fieldworkers, who
all have at least one year’s experience of carrying out VAs,
previous experience of fieldwork on other surveys, and one
of whom was a VA supervisor. The fieldworkers (3 female,
1 male) live in the community where they carry out VA
interviews, have completed a secondary school education
and are aged in their 30s and 40s. An initial focus group
discussion on the challenges and experiences of VA fieldwork provided an opportunity to build rapport with the
fieldworkers, which was considered crucial if they were to
provide honest and critical feedback. One driver (who takes
fieldworkers to respondents’ homes), one data typist (who
had also been a VA respondent the previous year) and the
data manager also participated. MIVA was then introduced
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as prototype software whose design the fieldworkers could
potentially influence. An initial translation of the WHO VA
questions and causes of death into Shangaan, the local language, was completed by a data typist. This formed the basis for training the fieldworkers on the questions they were
expected to ask and assessing their comprehension of all
questions and the causes of death that may be diagnosed by
InterVA/MIVA. During training, fieldworkers were encouraged to verify translations and to correct any mistranslations or ambiguities. These translations were subsequently
incorporated into MIVA, demonstrating to the fieldworkers
their ability to influence its design and heightening the
sense of participation.
Following this initial three-day training, the translations
were loaded onto four mobile phones and the fieldworkers
were trained in the use of MIVA on the phones – this was
the first time that the fieldworkers saw the mobile devices.
Initially, the fieldworkers were shown a version of the
software on a laptop and presented with a demonstration of
how the interface worked. Fieldworkers then carried out
role-play interviews, initially with the MIVA developers
and subsequently among themselves where they practiced
asking questions one at a time and entering the results.
During this process, fieldworkers also learned how to correct data entered into MIVA and how corrections might
result in different skip patterns of subsequent questions.
The process of role-play identified further translation issues
which were rapidly updated in the software.
From days 4 to 7, fieldworkers conducted a total of 10 real
VA interviews with respondents who had suffered
bereavement and consented to a VA interview during the
routine AHDSS processes in the preceding year (Figure 2).
Cases for interview were selected from a list of all
completed VAs in Agincourt village (closest to the field
office), with both male and female respondents of varying
ages (late teens to over 70 years) and deceased individuals
ranging from babies to the elderly. All respondents were
provided with details of the current study and signed a
consent form to be re-interviewed and included in the
current evaluation of MIVA. For the first six interviews,
two fieldworkers attended each interview – one asking the
questions but both entering the answers into MIVA, with
Session: Clinical Settings
CHI 2013: Changing Perspectives, Paris, France
each fieldworker having at least one opportunity to ask the
questions. The final four interviews were carried out by
individual fieldworkers on their own.
database and that they are indeed gathering data for the
correct individual.
RESULTS
Ten VA interviews were successfully completed over a
period of four days and the mean interview time using
MIVA was 22 minutes (s.d. 5 minutes), with interview
times getting shorter the more experience the fieldworkers
acquired. The mobile phone batteries lasted all day and
were charged each evening when the fieldworkers returned
to AHDSS office after conducting their VA interviews. The
display consumes the majority of the electricity and this can
be diminished by reducing its brightness to 50%, a level at
which the high contrast interface can still be clearly read. In
this mode, MIVA could be used for several days in the field
before the phone requires recharging. Each completed VA
interview generates less than 2KB of data to be stored on
the device or transmitted to a database. Several hundred VA
interviews can easily be stored on the mobile phone. None
of the fieldworkers felt that carrying the mobile phones and
using them in the field posed a security risk to themselves
or the devices, but recognized that this would not necessarily be the case in other settings such as urban centers.
Findings from the field study are presented under headings
that represent the key desirable features of a mobile VA
device as described by WHO.
Simplicity
Although the text size on the mobile phone screen was quite
small, none of the fieldworkers reported difficulty reading
it. Two out of the four fieldworkers had had previous experience with a touch screen device and all owned and were
familiar with mobile phones. After a short training session
with the mobile phone, all of the field workers were able to
use the touch interface to select a question response and
navigate through the questionnaire.
Feedback on the MIVA interface was received from fieldworkers as well as the AHDSS data team, who suggested
‘yes’, ‘no’ and ‘don’t know’ options for questions, despite
the fact that only affirmative answers are used to derive
cause of death by the InterVA-4 analysis algorithm. It was
felt that having the three exhaustive options, one of which
would have to be selected before progressing with the VA
interview, would reassure fieldworkers who could feel uncomfortable leaving any particular question without a definitive response. The requirement to enter an answer before
progressing with the interview further ensures that all necessary questions are asked. The three options and response
requirements were added to MIVA before field testing.
However, during the field testing of MIVA, the fieldworkers suggested a further option of “refused to answer” as
they felt that the current three options would not satisfactorily capture a respondent’s unwillingness to disclose information. Fieldworkers also expressed a desire for a facility
that would enable interviews to be suspended, saving all
entered data in a retrievable format should the respondent
wish to postpone completion of the interview to a later date.
The option of pre-populating the MIVA system with basic
background information of the deceased was suggested by
the data management team. Such an option may be suitable
for pre-enumerated populations, such as those in health and
demographic surveillance systems, where information on
the basic background and demographic characteristics of
the deceased will already be stored in a central database.
Pre-populated software could be used to allocate interviews
to fieldworkers and may simplify data management, quality
assurance and field activity coordination. However,
fieldworkers felt that this would reduce the flexibility and
autonomy they have over how they manage their workload.
A more suitable solution might be to store the basic
background information on the mobile device and populate
the relevant MIVA fields with relevant information, for
example, age and sex, when the fieldworker enters a unique
identifier for that particular case. This would provide an
opportunity for the fieldworker to verify data in the
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System Feasibility and Acceptability
Overall, all fieldworkers gave extremely positive feedback
on the MIVA system, describing it as better than the paperbased questionnaires they typically use to carry out VAs.
One of the features that all of the fieldworkers liked about
the system was its ability to automatically skip irrelevant
questions and the fact that it was impossible to miss relevant ones. They felt that this helped the interview to flow
more naturally and efficiently. The portability of the mobile
phone and digital storage of data was also considered to be
a considerable advantage, overcoming the need to transport
and securely store numerous paper questionnaires. The mobile phones were considered to be discreet (Figure 2) and
during field observations it was apparent that the presence
of the mobile phone did not seem to intrude into the dialogue between fieldworker and respondent and was perhaps
less intrusive than multi-paged A4 paper questionnaires.
During focus-group discussions and informal qualitative
interviews with the VA fieldworkers we conducted before
introducing the MIVA system, fieldworkers had described
their work as “very challenging”, mainly because
respondents can become very emotional during the VA
interview, particularly if the deceased died suddenly or
unexpectedly. According to the fieldworkers, the paperbased interviews that they carry out in AHDSS can take
between one to two hours to complete and fieldworkers can
conduct up to four interviews per day. This AHDSS VA
tool begins with an “open history” section in which the
respondent describes in their own words the circumstances
and sequence of events leading to death. VA fieldworkers
are trained to prompt respondents to provide as much detail
as possible and to report events in the sequence they
occurred. The open history is translated into English and
transcribed in longhand by the field worker during the
Session: Clinical Settings
CHI 2013: Changing Perspectives, Paris, France
interview. Fieldworkers report it is the most time
consuming step of the interview and also described it as the
part of the interview in which respondents can become very
emotional and consequently where they can feel most
“uncomfortable”.
Within this context, therefore, the fieldworkers recognized
the speed of interview using MIVA as a major strength and
reported that it would enable them to complete more interviews per day. Part of the reason for the quick interview
time compared to the paper-based VA questionnaire currently used by AHDSS was the absence of a free-text, openhistory section in MIVA. In addition to reducing the time,
fieldworkers also felt that the exclusive use of closed questions kept the interview fact-based and less emotional for
the respondents.
None of the ten interview respondents were displeased or
distracted by the use of mobile phones for data collection,
perhaps reflecting the ubiquitous nature of mobile telephony in rural South Africa. Indeed, two of the respondents
were holding their own mobile phones during the interviews and one accepted a phone call. There were no issues
in asking any of the questions that were presented in the ten
interviews conducted. One respondent was observed to become uncomfortable and slightly upset when asked about
the total costs of care incurred during the deceased’s terminal illness, evidently having suffered a heavy financial burden. Another respondent, a grown son to a deceased mother, found questions relating to his mother’s menopause
strange and felt it was unrealistic to expect him to know
such personal details about this aspect of his mother. Nevertheless, neither of these respondents took offence to the
questions, reflecting the skill and experience of the fieldworkers.
Despite the closed question design of all MIVA questions,
respondents did not always respond with simple yes, no or
don’t know responses, often giving longer explanations and
describing situations that ultimately lead to a clear definitive answer. After the field study, an international health
organization expressed a desire to build into MIVA a facility to capture longer narratives or make open-ended notes.
Though not necessary for deriving a cause of death from
MIVA and potentially being challenging on small devices
with touch-screen keyboards, this facility was recognized as
being particularly important to clinicians and those involved
in PCVA.
Adaptability to Local Context
Translation and localization of the WHO questions and
MIVA took approximately one and a half days; training
fieldworkers to use MIVA on the mobile phones took approximately one day. It is important to note that the VA
fieldworkers were highly trained and experienced. It was
beneficial to have an imperfect, first pass translation of the
questions from English to Shangaan prior to fieldworker
training. This forced the fieldworkers to carefully think
about the meaning of each question, increased familiarity
1495
with the questions and, through correcting the translations
which were directly entered into a spreadsheet and subsequently updated in MIVA, enhanced feelings of ownership
over the design process and the MIVA tool.
None of the fieldworkers felt that any of the WHO VA
questions were too sensitive to ask, although they recognized a need to be sensitive in asking some questions,
demonstrating the importance of having highly skilled
fieldworkers and reflecting the collective experience of the
fieldworkers in this study, each of whom has completed
several hundred VA interviews. Fieldworkers identified
some questions that were inappropriate or not applicable to
their setting. For example, they felt that descriptions of
vomited coagulated blood as “coffee grounds” or describing
a cyanosed baby as “blue” would not be recognized by respondents in their population. Nevertheless, the meanings
of such indicators were easily explained to the fieldworkers
who felt that, with appropriate training, they would be able
to convey the meaning of all the WHO VA questions to
respondents. Fieldworker interpretation and understanding
of the MIVA cause of death list was limited for the majority
of causes. Where fieldworkers felt that they did understand
what a specific cause was, their understanding was often
shown to be limited or incorrect when probed for further
details. This has important implications in terms of providing direct feedback of cause of death to respondents and the
fieldworkers themselves recognized that they would need
further training before they would be able to do this. The
fieldworkers were able to understand the idea of multiple
causes contributing to death. Furthermore, they felt that the
community in which they lived and worked would be able
to understand this idea if explained carefully, although further investigation is needed to verify this.
Cost Effectiveness
Whilst a rigorous evaluation of cost-effectiveness was beyond the scope of this study, the reduced interview time
observed and potential for a greater interview rate per day,
combined with the increasing affordability of suitable mobile phone technology and the reduced need for a data entry
stage, are indicative of overall cost-effectiveness and with a
potential cost advantage over traditional paper-based methods, especially over the long term as digital data storage
would be a lesser cost than that for paper-based questionnaires.
Program Relevance
In this context, program relevance relates to the suitability
of tools to meet the needs of those who want to know cause
of death data. However, there is a wide range of end-users
and, within the field of VA research, it is increasingly becoming apparent that it is unlikely that any single tool can
satisfy the needs of all. While program relevance may typically be applied to the end-users of the data, there are several other key stakeholders for whom MIVA has programmatic relevance, not least those directly involved in gathering, processing and storing the data. The perceptions of
Session: Clinical Settings
CHI 2013: Changing Perspectives, Paris, France
fieldworkers have already been described, whose overwhelming view is that the MIVA system could greatly facilitate their work, although possible improvements have been
noted and described above. Data managers, who are tasked
with processing VA data and packaging it in a format useful
to researchers and health program implementers, also
praised MIVA for the opportunities it offers to simplify the
data process and enhance data quality. Data security was
identified as a priority issue by this group of stakeholders. It
was felt that MIVA data, which are currently only stored in
the local memory of the browser, should also be backed-up
onto encrypted SD cards on the mobile and, given suitable
connectivity, uploaded as frequently as possible to a central
database.
Within the AHDSS, which is essentially an academic research site for population health and socio-demographic
surveillance, the MIVA system offers timely, standardized
data capture and analysis as well as opportunities for more
cost-effective field procedures. The standardized nature of
MIVA-derived cause of death results is likely to appeal to
researchers wishing to explore mortality trends over time
and space. Such features are also likely to address the needs
of local health managers, such as those tasked with prioritizing services for their community; MIVA could enable
rapid and low-cost estimation of the major mortality cause
burdens. Such data could subsequently be transferred upwards to inform national and global health authorities, such
as the WHO.
Those involved with health promotion or public health interventions may be more attracted to the potential for direct
feedback of cause of death to VA respondents. Similarly,
those involved in community engagement felt that the timeliness of results from MIVA was a significant advantage
over paper-based methods and felt that direct feedback of
cause to respondents was a positive development. In this
way, the MIVA approach has blurred the boundaries between health measurement and health promotion, raising a
number of operational and ethical issues that are explored
further in the Discussion section and relate directly to the
final stakeholder group – the VA respondents - who are the
group potentially impacted the most by the opportunities
offered by MIVA.
DISCUSSION
We begin by discussing two operational issues relating to
MIVA and then move on to considering the ethical issue.
First, by keeping all of the questions closed and not having
an open history section, fieldworkers were able to complete
VA interviews using the mobile system far more quickly
than with the paper-based questionnaires used in the
AHDSS (around 20 minutes for a MIVA interview compared to 1 or 2 hours using the paper questionnaire). As
reported above, fieldworkers liked the fact that respondents
did not become emotional when answering the closed
MIVA questions. This raises the issue of how useful is an
open history, and more generally open questions, for VAs.
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Do open responses provide a reliable source of data? We
interviewed one of the designers of the AHDSS questionnaire about their motivation for including an open history
section and she argued that not only did it provide data that
could help the process of PCVA, it was also emotionally
valuable for respondents as it gave them an opportunity to
talk about the death of their relative.
Although an open history is redundant for InterVA analysis,
WHO is keen for some optional open text fields to be added
to MIVA that could be used to record other observations at
the end of a VA interview. Although it is feasible to add
these to the interface, it will be tricky for a fieldworker to
add large amounts of text data quickly using a small touch
screen keyboard. For example, it would probably not be
possible to listen to an open history in Shangaan, translate it
into English and record it in real time, as is currently done
on paper-based VA questionnaires in the AHDSS. One possible compromise is to write down open histories, responses
to other open questions and extra observations in longhand
on paper and to link these records to the digital data generated by MIVA with a unique interview ID. Another possible approach is to use audio recordings but this would require respondents to be fitted with lapel microphones if the
quality is to be sufficiently high. Furthermore, automatically labelling and storing audio recordings could not be done
from within an HTML5 browser and would require dedicated application software.
MIVA can potentially reduce the cost of carrying out VAs
by decreasing the time it takes to carry out three stages in
the process: conducting the interview; analysing the responses to generate the probable cause of death; and inputting the interview data into a database. A second operational issue, raised by some AHDSS programme managers, was
that another saving that could derive from MIVA is not
having to use more highly skilled and paid VA fieldworkers
to carry out interviews. This is because it is only necessary
to ask closed questions and the system automatically calculates which ones need to be asked. However, we do not
think that MIVA replaces trained VA fieldworkers; rather,
we argue that the mobile system is only effective because of
the trained interviewer using it. For example, interviewers
have to interpret respondents’ answers if they do not follow
the ‘yes’, ‘no’ or ‘don’t know’ format and it is crucial that
they are sensitive to the emotional needs of respondents.
A final and important issue raised by the MIVA field study
is that it provides the opportunity of directly feeding-back
information to interview respondents unlike the traditional
one-way VA interview. This blurs the boundary between
health surveillance and opportunities for health promotion
activities and presents pressing ethical challenges that have
to be debated by the VA community. We explored the ethics of providing respondents with a probable cause of death
by interviewing different stakeholders in the VA process to
find out their opinion on this issue, an issue that has not
been considered in previous VA ethical discussions [5].
Session: Clinical Settings
CHI 2013: Changing Perspectives, Paris, France
All of the relatives of the deceased who we asked (9/10
interviewed) told us that they would like to know the probable cause of death of their relative after the VA interview.
VA fieldworkers reported that they are often asked by respondents during interviews if they can tell them the cause
of death of their relative. All four fieldworkers said they
would be prepared to give a diagnosis if the respondents
wanted to know. They thought that people would believe
the diagnosis of the mobile phone as they consider them to
be a type of computer (and therefore trust them).
Field workers acknowledge that it could be difficult to inform respondents of the probable cause of death, particularly if it involved a stigmatized disease, such as HIV. They
recognize that they would need extra training so that they
could answer respondents’ questions about causes of death
and related health issues. For example, when doing the
translation of the WHO VA questions from English into
Shangaan, we found that dementia and chronic obstructive
pulmonary disease (COPD) were new medical concepts for
them. Some of the fieldworkers also showed a limited understanding of causes of death - for example, one thought
that congenital malformation of a baby was the consequence of a sexually transmitted infection (STI). Although
this could be the case, it is not necessarily so, and this example illustrates how limited medical knowledge could
result in misleading and unnecessarily traumatic feedback
being given to respondents. Fieldworkers also thought that
people in their community could deal with multi-causality,
that is, understand that MIVA might generate more than
one probable cause of death and that high, medium and low
are better ways of giving probability information rather than
numbers.
In contrast to VA respondents and fieldworkers, the majority of population research scientists that we interviewed at
AHDSS were of the opinion that respondents should not be
told the probable cause of death. They recognize the importance of the issue and it is one that concerns them for
two main reasons. First, they worry that InterVA tells us
about the pattern of the probable causes of death in a population but cannot reliably provide this information for an
individual case. We call this the ‘scale’ issue – can InterVA
provide a reliable probable cause of death for an individual?
Second, there are population scientists concerned that
providing respondents with feedback on the probable cause
of death moves their work “out of the comfort zone of surveillance systems” and into the complex realm of public
health interventions. We refer to this as the ‘intervention’
issue. For example, one population scientist questioned the
extent to which researchers are responsible for the health of
the families they survey. He gave the example of the probable cause of death being an infectious disease such as TB
and asked whether researchers would then be responsible
for finding and informing the deceased’s recent close contacts. A further concern he had was who would finance this
activity.
1497
Another stakeholder we interviewed about giving respondents information about the probable cause of death was a
medical practitioner who carried out PCVA. She was concerned that the confidentiality rights of the deceased could
potentially be compromised and explained that doctors had
responsibilities to patients, even after they had died, and
that they would withhold some medical information from a
deceased’s family if it was not relevant to the cause of
death. One example they gave was not informing a husband
of the fact that his deceased wife had undergone an abortion
if this had not led to her death. We can label this the ‘confidentiality’ issue.
A final stakeholder we interviewed was a WHO VA expert
who acknowledged that there is no simple answer to the
question of whether respondents should be informed about
the deceased’s probable cause of death and that it is an important issue that needs to be carefully considered. In his
opinion the information should only be for the immediate
family and it should be conveyed by a medically trained
person, for example a health visitor or nurse, rather than by
a fieldworker at the end of a VA interview. However, this
again raises the question of how this would be funded.
In order to make progress on the ethics of providing respondents with a probable cause of death, a useful first step
would be for the VA community to debate the ‘scale’ issue.
Our stakeholder interviews found three differing opinions
on this issue. The first is that InterVA is a population tool
and is not reliable for individual cases. If correct, then this
resolves the ethical debate because MIVA could not provide a reliable probable cause of death. The second viewpoint is that a validation process needs to be carried out, for
example, by comparing the results of PCVA and InterVA,
case by case, and seeing the extent to which they agree. If
there is sufficient agreement, it is argued, then InterVA is
validated and the ethical challenge remains. The third opinion was that InterVA could be used for individual cases but
when doing VA, regardless of whether it is PCVA or InterVA, “there is an inherent uncertainty that you can’t get
away from”. This population scientist referred us to published studies comparing hospital doctors’ diagnoses of the
cause of death and what pathologists determined as the
cause of death and in 30% of cases there was disagreement
[11]. He argued that comparing InterVA to PCVA is therefore not a good way of validating the analysis software.
Given these diverging opinions, a key practical challenge
for the VA community is determining the validity and scope
of InterVA. If InterVA can provide reliable probable causes
of death for individual cases then two key ethical challenges
are to resolve the ‘intervention’ and ‘confidentiality’ issues.
As stated earlier, some VA stakeholders, for example, many
population scientists, see their role as gathering demographic data rather than engaging in public health interventions
and therefore they do not think that they are responsible for
giving respondents probable cause of death information
after a VA interview. However, the distinction between
Session: Clinical Settings
CHI 2013: Changing Perspectives, Paris, France
observation and intervention is not always clear-cut. For
example, one of the VA fieldworkers we worked with explained that he had been trained to explain to respondents
that participating in VAs is valuable for their community
because their purpose is “To help the health system and
those who are still living”. In this case, it might be argued
that regardless of the cost, and irrespective of whether scientists want the responsibility or not, they do have an ethical obligation to provide the community they are observing
with information that improves health systems. Whether
this responsibility is fulfilled by providing feedback in the
form of aggregated cause of death statistics at annual community meetings (as is currently done in AHDSS [8]) or
providing information to relatives about an individual’s
probable cause of death is a key ethical issue to be debated
by the VA community. The existing medical ethics literature can potentially provide insights into how the ‘confidentiality’ issue can be resolved.
tiple levels in a centralized setting. Proc. PD (2004), 5364.
CONCLUSION
The field study of MIVA in rural South Africa has demonstrated that this system meets practical WHO requirements
for a mobile verbal autopsy tool that can be used in lowincome settings. It also raised two operational issues: the
value of open questions for VAs; and the importance of
trained fieldworkers to use MIVA effectively. By incorporating VA data capture and InterVA functionality on a mobile phone, MIVA can provide a probable cause of death at
the end of an interview. This raises pressing ethical issues
in the VA community, with different stakeholders holding
different views on whether respondents should be informed,
and if so, by whom. Some population scientists question the
validity of InterVA to analyse individuals’ probable cause
of death (the ‘scale’ issue); furthermore, this stakeholder
group sees its role as doing research rather than running
public health projects (the ‘intervention’ issue). Doctors are
concerned that the rights of the deceased are not compromised (the ‘confidentiality’ issue). Respondents and fieldworkers were in favour of reporting the probable cause of
death to relatives of the deceased as they believe this information will benefit individuals and their wider community.
They view this issue as being as much a matter of saving
lives as one of recording deaths.
ACKNOWLEDGEMENTS
This work was supported by UCL Institute for Global
Health, UCL computer science strategic research fund and a
Wellcome Trust Strategic Award, (085417ma /Z/08/Z).
The Wellcome Trust, UK has funded the Agincourt verbal
autopsies (058893/Z/99/A; 069683/Z/02/Z; 085477/Z/08/Z)
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