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Public Health Action
VOL 12 no 1 PUBLISHED MARCH 2022
PHA 2022; 12(1): 24–27
e-ISSN 2220-8372
AFFILIATIONS
1 Shadyside Family Medicine
Residency Program,
University of Pittsburgh
Medical Center,
Pittsburgh, PA,
2 Department of Biomedical
Informatics, University of
Pittsburgh, Pittsburgh, PA,
USA;
3 Global Health Informatics
Institute, Lilongwe,
Malawi;
4 University of Pittsburgh
Medical Center School of
Medicine, Pittsburgh, PA,
USA;
5 Hombro e Hombro, San
Jose, Honduras
CORRESPONDENCE
Correspondence to: Kevin
Kindler, Family Medicine,
UPMC Shadyside, 5215
Centre Ave Pittsburgh, PA
15232-1381, USA. email:
kindler.kevin@gmail.com
ACKNOWLEDGEMENTS
Funding for this work was
supported by Shoulder to
Shoulder Pittsburgh/San
Jose.
Conflicts of interest: none
declared.
KEY WORDS
pediatrics; Honduras; clinical
decision support; growth
tracking; stunting
Developing a portable field unit to improve well-child care
K. E. Kindler,1 G. P. Douglas,2,3 T. M. Mtonga,3 E. Katsalira,3 M. Lungu,3 J. B. Newton,4 M. Meyer,1
T. C. Castillo5
Malnutrition is a measurable decline in health
due to an excess, imbalance, or deficiency of
nutrients in the body.1,2 It is estimated that nearly 2
billion people in the world suffer from some form of
malnutrition, which could have long-term health and
economic consequences, such as physical and cogni-
tive stunting, severe illness, chronic disease, and de-
creased worker productivity.3–5 The Food and Agricul-
ture Organization of the United Nations estimates
that roughly 3.5 trillion US dollars (USD) are lost per
year in the global economy as a result of under and
overnutrition.3 Early identification of signs of malnu-
trition, followed by intervention, is essential to avoid
both short- and long-term impacts of malnutrition.
This is especially true for children, as malnutrition
and infection in early life increase the risk of chronic
non-communicable diseases in later life.6
Pediatric growth monitoring can be used to iden-
tify children at risk of deviating from their trend lines
before long-term consequences occur. The WHO and
the Centers for Disease Control and Prevention (CDC)
have both identified pediatric growth tracking as a top
priority and developed standard growth charts.7 The
2006 WHO growth chart is an international growth
standard for describing child growth in optimal condi-
tions and can be used to identify children whose mea-
surements indicate malnutrition.
Honduras, a low-income Central American coun-
try, has made significant progress toward reducing the
burden of moderate-to-severe nutritional deficiencies
(as measured by weight-for-age) from 24.3% in 1996
to 11.4% in 2005–2006.8 The difficulty with further
improving this statistic is due to poverty and a lack of
basic services in large parts of the country. A calcula-
tion of unmet basic needs in 2013 found that 15.9%
of Hondurans were either living in extreme poverty or
were unable to provide for their own or for their de-
pendents’ food, clothing, housing, and healthcare due
to lack of income or resources.9 On a national level,
Honduras has no formal electronic health record
(EHR) system to use as a repository for patient demo-
graphics and vitals. The creation of an EHR is under-
standably not a primary focus, as 87% of hospitals do
not have the daily supplies needed, 53% have defi-
cient facilities, and 50% do not have the minimum
medical equipment required for operation.8
The University of Pittsburgh Medical Center
(UPMC) Shadyside Family Medicine Residency Pro-
gram has partnered with Shoulder to Shoulder Pitts-
burgh/San Jose, a non-governmental organization in
San Jose, Honduras, and its US counterpart in Pitts-
burgh, PA, USA, to provide care to rural communities.
Using anecdotal evidence, local health workers in the
community identified malnutrition and stunting as
ongoing in the catchment population. Numerous in-
terventions targeting malnutrition were implemented
using a community-based primary care model. The
first intervention was a collaboration with a Hondu-
ran NGO, Projecto Mama, that provided locally pro-
duced soy-based nutritional biscuit supplement. This
was followed by the distribution of chispuditos, a soy
micronutrient supplement.10,11 Further community in-
put led to the implementation of a nutrition program
to provide eggs to both mother and child for the first
1,000 days of life. However, in the absence of a formal
structure for tracking stunting over time, it was impos-
sible to gauge the effectiveness of these longitudinally.
Studies conducted worldwide have shown the po-
tential impact of growth tracking in rural communi-
ties, although each study has implemented this work
differently. Work done in rural South Africa used a
community-based approach relying on individual
households to collect handwritten records; Kenya,
Received 12 July 2021
Accepted 18 November 2021
http://dx.doi.org/10.5588/pha.21.0062
BACKGROUND: Pediatric growth tracking has been
identified as a top priority by international health agen-
cies to assess the severity of malnutrition and stunting.
However, remote low-resource settings often lack the
necessary infrastructure for longitudinal analysis of
growth for the purposes of early identification and imme-
diate intervention of stunting.
METHODS: To address this gap, we developed a porta-
ble field unit (PFU) capable of identifying a child over the
course of multiple visits, each time adding new anthropo-
morphic measurements. We conducted a preliminary
field evaluation of the PFU by using the unit on two dis-
tinct visits to three schools in the area surrounding a
medical clinic in rural San Jose, Honduras. The unit was
used to assess children at each school as part of the com-
munity outreach.
RESULTS: Community outreaches to three schools were
conducted by two distinct teams, where they used the
device to assess 210 children. Of the 180 children regis-
tered during the first visit, 112 were re-identified and as-
sessed on the subsequent visit. Twenty-four instances of
moderate-to-severe malnutrition were identified and re-
ferred for further evaluation to the central clinic.
CONCLUSION: This initial assessment suggests that the
PFU could be an effective means of identifying at-risk
children.
Portable field unit for pediatric care 25
Public Health Action
Tanzania, and Uganda have all employed coalitions of commu-
nity health workers to track growth and provide nutritional coun-
seling in a similar fashion.12 While many existing interventions
focused on the process of collecting information, interpreting a
growth chart, and providing medical advice to evaluate a child’s
response, none of the reviewed studies propose a feasible elec-
tronic system capable of storing this information. Pediatric-fo-
cused EHRs like iPediatric EHR exist, although these are rarely ca-
pable of running portably; and, those that do work portably, lack
the ability to run offline and would not be able to withstand
harsh environments.13
The aim of this project was to develop a device capable of
monitoring children in rural Honduras over time for stunting,
wasting, and obesity, by adding new anthropomorphic measure-
ments during each visit, and providing a longitudinal analysis of
growth for the purposes of early detection and intervention plan-
ning. With no existing infrastructure to support this, a novel ap-
proach was adopted to develop both the hardware and software.
MATERIALS AND METHODS
Setting
The device described in this article was used to conduct commu-
nity outreach visits in the catchment area of a rural clinic in San
José del Negrito, outside the city of San Pedro Sula in Honduras.
Outreach visits consist of health screenings and a physical exam-
ination conducted at eight schools surrounding the clinic. These
outreach visits occur over a 10-day period and are conducted ev-
ery 6 months when a brigade of volunteer medical professionals
and students visit the clinic from the United States. The develop-
ment of the device was undertaken as a service-learning project
by a team from the Global Health Informatics Institute located in
Lilongwe, Malawi.
Device requirements and capabilities
The process of developing our system began with the identifica-
tion of user and device requirements. Due to the location and en-
vironment in which outreach visits are conducted, the unit’s
hardware had to be capable of operating without access to reliable
AC power. The hardware had to be portable to allow easy trans-
portation between schools. Furthermore, the hardware needed to
withstand temperature extremes and protect against water dam-
age during transportation.
To track pediatric growth, the device had to identify children
during repeated visits and record their weight and height. The
2006 WHO formulas for calculating Z-scores based on age,
weight, and height were used to assess the nutrition status of each
child. Age was calculated based on the child’s date of birth, which
was recorded when creating the initial patient record. Z-scores for
each child were compared to standard growth charts. Data were
exported from the unit using a USB drive and aggregated to deter-
mine the prevalence of malnutrition and calculate average
Z-scores.
Field testing plan
Field testing was conducted during two brigade visits, when the
unit was used to conduct outreach health screening at local
schools. The initial test was to determine whether the unit was
functional and to compile a list of bugs and feature requests.
Once the bugs had been resolved, a second test was conducted
during the subsequent brigade visit. One person per brigade was
trained on how to use the device to ensure that data input was
consistent. Three schools were chosen as pilot sites, following
which the unit’s use was expanded to cover all schools within the
clinic’s catchment area. Routine outreach data, which were previ-
ously recorded on paper, were collected electronically by the unit,
which required ongoing consent from guardians regarding care
provision. The PFU was handled only by the person inputting
data to avoid security concerns.
RESULTS
Device requirements and capabilities
The primary requirement for this intervention was a robust, por-
table device that could be transported to schools over rough ter-
rain and difficult weather conditions. To meet this requirement,
we developed a portable field unit (PFU) with a 10-inch touch-
screen display and a Raspberry Pi computer (Raspberry Pi Founda-
tion, Cambridge, UK). A rechargeable 12-volt sealed lead-acid bat-
tery was incorporated in the design to allow continued use of the
unit in remote off-grid settings. A barcode scanner and a thermal
label printer completed the set of peripheral devices. All the
equipment was housed in a commercially available waterproof
carrying case commonly used for carrying cameras/fragile equip-
ment. The PFU is shown in Figure 1.
The unit assigned each student a unique number. Students
were given a copy of their demographic record together with their
unique student number, which was printed on an adhesive label
using the thermal printer. To expedite the process of reviewing
and recording data, the printed copy of the student demographic
record also had the unique student number printed as a barcode.
By scanning this barcode in the application, the student’s record
could be retrieved and opened. In the absence of the identifica-
tion card, a student record could be retrieved using a search func-
tion based on different criteria such as name, sex, date of birth
and name of school.
Figure 2 shows the proposed workflow for a field nutrition sta-
tus assessment using the unit. The process begins with registering
the student, if they have not already done so. This procedure in-
volves the collection of information about the student’s name,
gender, date of birth, and school. Once data are recorded, a label
with demographic identifiers is printed and affixed to a plastic
card to create an identification card for the student. The student’s
FIGURE 1 Portable field unit with thermal printer and touchscreen
installed in case.
Portable field unit for pediatric care 26
Public Health Action
record then opens and height (in cm) and weight (in kg) are re-
corded. From this data, Z-scores for weight-for-age, height-for-
age, and body mass index (BMI) for age are calculated and dis-
played in a table with any previously collected data.
Field testing and preliminary data
The unit was first field tested in Honduras in September 2019,
and then in February 2020. During these brigades, outreach visits
to the three pilot schools were conducted using the unit. Demo-
graphic information for 234 students (ages 4–16 years) was
pre-populated into the PFU to shorten data entry time in the
field. All children present during brigades were included. During
the first brigade, 180 of the 234 registered students had measure-
ments for age, height and weight recorded. Z-scores for these stu-
dents were calculated and stored in the unit. During the second
brigade, a total of 142 of the 234 registered students were assessed
and their measurements recorded in the unit. Of these, 112
(62.2% of the original 180-student cohort) were assessed and had
measurements recorded in the previous outreach visit. A total of
210 children were assessed and 322 measurements were recorded
(Table). The data collected in these two brigades provided clinical
decision support in real time by presenting physicians with a ta-
ble of Z-scores over time. The analysis of these data revealed 24
cases of moderate-to-severe malnutrition (BMI-Z –2.0), with a
combined average BMI-Z of –0.32 necessitating referrals. Referrals
for counseling and intervention from the brigade were communi-
cated to families by the teacher if no parent was present during
the examination.
The PFU was transported to schools without compromising
the integrity of the device, and was used during the rainy season
with no loss of function or water damage. The battery charge
lasted long enough for the unit not to be shut down while in use.
The label printer and barcode scanner both functioned as in-
tended and were able to reliably print and scan when prompted
by the user. The touchscreen functioned consistently with no ap-
preciable calibration issues or input lag.
From a software usability perspective, the PFU operator was
able to navigate the unit efficiently to identify a child during a
second visit, either via the search function or by barcode scan-
ning. Data entry into the unit worked reliably and calculated val-
ues were displayed clearly in a table for comparison. The insight
garnered was then used to help physicians in determining when
it was appropriate to intervene.
The total cost of all components to build the PFU was USD350.
A second-hand thermal label printer costing USD75 was used to
keep the total cost of the unit low.
DISCUSSION
We successfully achieved the primary outcome of this project,
which was to develop a device capable of monitoring growth
among students to facilitate early identification of malnutrition
and stunting cases, and to assess the reliability of data entry and
Z-score output. The PFU is in line with the research previously
conducted in this field; it is unique in that it demonstrates a
method to track pediatric growth electronically, portably, and of-
fline. While tablets and smartphones can be used similarly, the
PFU is also able to create an adhesive label to facilitate longitudi-
nal tracking.
From September to February, there were slight variations in the
averages of Z-scores for BMI, height, and weight-for-age. This
variation could be due to a difference in the cohort of students
that presented that day. Due to the lack of a centralised method
of notifying students of our visit, we were forced to rely on word
of mouth from local health committee members to inform stu-
dents of our impending arrival. This likely contributed to the
large differences in the number of students at a given school in
one brigade vs. the subsequent one.
Data collected from the PFU were used to guide clinical deci-
sion-making by enabling real-time calculation of Z-scores. Of the
112 students with multiple data points entered into the unit, 24
children identified as either at-risk (down-trending Z-scores) or
moderate to severely malnourished (Z-score values <–2), and
were appropriately referred for further evaluation at the central
clinic in San Jose. An improving Z-score value for a malnourished
child could serve to demonstrate how an intervention between
the first and second brigade positively impacted growth.
Given that our unit’s initial primary data output was the calcula-
tion of Z-scores, we chose not to integrate with other projects at
this point. In the future, adding a notification for participation in
nutrition programs, including chispuditos and the first 1,000 days of
life program will be considered. Once further data points have been
collected, average Z-scores at different schools can be compared to
determine which communities require the most attention.
Other possible future goals of the project include adding a
field to specify whether the child has been referred for further
evaluation - either for medical reasons, impaired vision, or dental
abnormality. Although the integration of past medical history,
medications, allergies, and other conditions could all be useful
additions, the cost and time needed to incorporate these into the
unit were not feasible at this point. In the future, locally collected
data could be compared against the national data collected by the
UNICEF for the Global Nutrition Report.14 Possible consequences
of this work include diverting funds and time away from other
less useful projects; if the unit’s information does not result in an
improvement in stunting, the community may be disenfran-
chised from future interventions.15
CONCLUSION
Having identified moderate to severe malnutrition as a national
concern in Honduras, our focus was to create a device to quantify
the extent of malnutrition in the pediatric population in the
community. We developed and successfully piloted a PFU and
software unit capable of operating in the absence of reliable elec-
FIGURE 2 Data entry workflow. PFU = portable field unit.
TABLE A summary of the data collected from the two brigades
September 2019
Brigade
(n = 180)
mean ± SD
February 2020
Brigade
(n = 142)
mean ± SD
BMI for age Z-score, –0.46 ± 1.11 –0.15 ± 1.14
Height for age Z-score –1.16 ± 1.11 –1.13 ± 0.99
Weight for age Z-score –0.76 ± 1.21 –0.77 ± 1.16
SD = standard deviation; BMI = body mass index.
Portable field unit for pediatric care 27
Public Health Action
tricity, accurately identifying children, and calculating Z-scores
for clinical decision support. This initial assessment suggests that
the PFU could be an effective means of identifying at-risk chil-
dren; the data and insights gained from it would be essential in
long-term planning and analysis of nutritional interventions in
this setting.
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CONTEXTE : Les organismes internationaux de santé ont
identifié le suivi de la croissance des enfants comme une priorité
absolue pour évaluer la gravité de la malnutrition et les retards de
croissance. Cependant, les zones reculées à faibles ressources
n’ont souvent pas les infrastructures nécessaires à l’analyse
longitudinale de la croissance à des fins d’identification précoce
et d’intervention immédiate de lutte contre les retards de
croissance.
MÉTHODES : Pour combler ces lacunes, nous avons développé un
appareil portatif de terrain (PFU) capable d’identifier un même enfant
lors de plusieurs visites et d’ajouter les nouvelles mesures
anthropomorphiques de chaque visite. Nous avons réalisé une
évaluation de terrain préliminaire du PFU en utilisant l’appareil lors de
deux visites différentes dans trois écoles de la zone rurale aux
alentours d’une clinique médicale de San Jose, Honduras. L’appareil a
été utilisé pour évaluer les enfants de chaque école dans le cadre d’un
programme de sensibilisation communautaire.
RÉSULTATS : Des programmes de sensibilisation communautaire
ont été menés dans trois écoles par deux équipes différentes, qui ont
utilisé l’appareil pour évaluer 210 enfants. Sur les 180 enfants
enregistrés lors de la première visite, 112 ont été de nouveau
identifiés et évalués lors de la visite suivante. Vingt-quatre cas de
malnutrition modérée à sévère ont été identifiés et adressés pour
examen complémentaire à la clinique centrale.
CONCLUSION : Cette évaluation initiale suggère que le PFU
pourrait être un moyen efficace d’identification des enfants à risque.
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