Unlocking the Power of Mobile Data Collection in Healthcare

Key takeaways

 

1. Data is one of the most important pillars in healthcare, driving informed decision-making, improving patient outcomes, and shaping overall health policies.
2. With accurate data, medical professionals can respond to disease outbreaks, monitor key disease trends, and efficiently allocate resources to improve public health.
3. Healthcare organizations, however, face serious challenges in data collection and management partly because of over-reliance on manual methods such as paper-based forms.
4. Mobile data collection tools like ODK and KoBoToolBox, alongside other modes like SMS surveys and drones, have revolutionized healthcare by eliminating human error, sealing off data losses, and widening the scope of data.
5.  In this article, we explore how different health organizations have successfully implemented mobile data collection in diverse areas such as disease surveillance, malaria control, medical supplies monitoring, and emergency health response.

 

What is Mobile Data Collection?

Mobile data collection is a technology for capturing, storing, and managing data in real-time using mobile devices (mobile phones and tablets).

It is widely used in healthcare, agriculture, humanitarian aid, research, logistics, and market intelligence.

Healthcare organizations leverage mobile data collection tools and cloud storage technology to enhance efficiency, accuracy, and accessibility while eliminating paper-based processes.

 

Also read: What is Mobile Data Collection? Enhancing NGO Impact with ODK

How Does Mobile Data Collection Work?

The following is a step-by-step breakdown of how mobile data collection works. We have also included some of the tools used at each stage of the process:

 

1. Form Design: Creating Flexible and Dynamic Digital Forms

Survey authoring tools allow organizations to create customized digital forms capable of handling various data types, including text, GPS coordinates, barcodes, images, and voice recordings. These tools assist in designing, testing, and deploying digital forms efficiently.

 

Some tools used in form design include:

 

1. XLSForms – Excel-based form design standard used by ODK, KoboToolbox, and CommCare.
2. ODK Build – Drag-and-drop form designer for ODK users.
3. Kobo Form Builder – Simplified visual form creator for KoboToolbox.
4. SurveyCTO Designer – Enterprise-grade form-building with conditional logic.
5. Google Forms – A Basic web-based form creation tool.
6. Magpi Forms – Mobile-friendly form designer for surveys and data collection.

 

 

Healthcare organizations use mobile data collection tools and cloud storage technology to enhance the efficiency and accuracy of life-saving interventions. Picture/Courtesy

 

 

2. Data Collection: Capturing Data on Mobile Devices

Field agents and data collectors use mobile devices to collect data in the field.

Many tools support barcode scanning, GPS tracking, image capture, voice-to-text input, digital signatures, and many other functionalities.

Mobile data collection tools can also capture data offline, store it locally, and synchronize it with a server once an internet connection is available.

Some of the tools used to collect data using mobile devices include:

 

1. ODK Collect – An open-source mobile app for mobile data collection using ODK. ODK Collect can collect data offline.
2. KoboCollect – A Mobile app for data collection using KoboToolbox.
3. SurveyCTO Collect – Secure, offline-first data collection platform.
4. Survey123 by Esri – GIS-enabled app for geospatial data collection.
5. CommCare – Mobile case management tool used in health and humanitarian projects.
6. TaroWorks – Salesforce-integrated data collection tool.
7. Magpi+ – Supports multimedia data input.
8. Dimagi CommCare – Supports longitudinal tracking and case management.

 

 

3. Offline Data Collection: Capturing Data Without Internet Access

A key benefit of modern data collection tools is their ability to store data offline and sync it automatically when an internet connection becomes available.

Some of the tools for offline data collection include:

 

1. ODK Collect – Stores responses offline and syncs later to a cloud server.
2. KoboCollect – Stores responses offline and syncs later to a cloud server.
3. Magpi+ – Designed for low-bandwidth regions.
4. TaroWorks – Works offline and syncs with Salesforce CRM.
5. CommCare – Enables offline case tracking for healthcare and NGOs.
6. Surveys on Tab – Offline-first solution for market and corporate surveys.

 

 

Mobile data collection in surveys enables real-time data capture through smartphones or tablets and instant submission of responses. Picture/Courtesy

 

 

4. Data Synchronization: Uploading & Syncing Data to the Cloud

Once an internet connection is available, mobile data collection tools automatically sync collected data to a centralized cloud or on-premise servers for processing.

Some of the tools for data synchronization include:

 

1. ODK Central – Stores and manages synchronized data.
2. ODK Aggregate – Stores and manages synchronized data.
3. KoboToolbox Servers – Stores and manages synchronized data.
4. Google Sheets API – Auto-syncs data to spreadsheets for easy access.
5. RedCap – Secure data management for research and healthcare projects.
6. ODK Cloud, Microsoft Azure, AWS S3, Digital Ocean, Google Cloud – Secure cloud-based data storage solutions.

 

5. Data Management: Cleaning, Processing, and Storing Data

After collection, the data must be cleaned, processed, and organized for analysis and decision-making.

Some of the tools for data management include:

 

Microsoft Excel & Google Sheets – Used for basic data cleaning and filtering.

Power BI – Dashboard creation and business intelligence reporting.

Python & R – Advanced data processing and analytics.

Tableau – Data visualization and storytelling.

QGIS – GIS software for geospatial data mapping.

Google BigQuery – Cloud-based big data warehousing.

 

 

 

Mobile tools support offline data collection, allowing field workers to collect data in remote areas with limited internet connectivity. Picture/Courtesy

 

 

6. Reporting & Action: Analyzing Data for Decision-Making

After data is collected and processed, organizations generate reports, visualize insights, and automate decision-making processes.

Some of the tools for reporting & action include:

 

1. Microsoft Power BI – Interactive data visualization and reporting.
2. Google Data Studio – a Cloud-based business intelligence platform.
3. Tableau – Advanced analytics and visualization.
4. SPSS & Stata – Statistical tools for complex data analysis.
5. QGIS – GIS mapping and spatial analytics.
6. Looker (Google Cloud) – Data-driven business intelligence platform.

Although mobile data collection can take time to learn and implement, expert training significantly accelerates the learning process and helps you get up to speed quickly.

In-person training, consultancy, or self-paced mobile data collection courses significantly enhance the capacity of health professionals to collect data through digital tools and ensure real-time access to actionable insights.

How Mobile Data Collection is Revolutionizing Healthcare

Many health facilities globally continue to struggle with limited access to digital infrastructure or reliable internet connections, complicating the process of collecting and transmitting data.

Furthermore, the sheer volume of health data can overwhelm organizations, making it difficult to maintain data integrity and conduct meaningful analyses.

The adoption of mobile data collection and management is increasingly seen as a comprehensive solution to these challenges, thanks to its successful implementation by healthcare organizations worldwide.

 

The following is a list of case studies where healthcare organizations successfully adopted mobile data collection in different projects.

These real-world examples provide insights into the challenges and results after the adoption of mobile data collection, as well as additional details about the projects’ scope and the impact on beneficiaries.

 

 

 

 

An infectious disease expert works in a state-of-the-art health data center. Picture/Courtesy

 

1. ODK for Health Surveillance in Remote Areas by Médecins Sans Frontières (MSF)

Médecins Sans Frontières (MSF), also Doctors Without Borders, is an international humanitarian medical organization that provides emergency medical care to people affected by conflicts, epidemics, and natural disasters.

MSF is extensively involved in Africa, providing medical assistance in conflict-prone areas, including:

 

1. Remote regions of South Sudan
2. Central African Republic
3. Democratic Republic of Congo (DRC).

 

From its International Activity Report 2014, MSF listed the above 3 countries alongside Sierra Leone and Haiti as among the biggest country program beneficiaries based on project expenditure.

Project Details:

 

1. Since 2011, MSF has allocated an estimated annual budget of $10 million for disease surveillance in conflict-stricken South Sudan.
2. As a result of intense fighting and political instability, these regions face enormous infrastructural challenges, with poor road networks, scarce health facilities, and poor communication networks.
3. Doctors Without Borders implemented ODK between 2014 and 2015 as its primary healthcare data collection strategy to work around remote areas with limited resources.

 

 

Challenges Faced by Doctors Without Borders in Africa Before ODK

 

1. Health data collection was done manually on paper forms, making it slow, prone to errors, and cumbersome to analyze.
2. Communication infrastructure was poor, making it extremely difficult to transmit data from remote clinics to central offices in real-time.

 

Doctors Without Borders Headquarters in Geneva, Switzerland. Picture/Courtesy

 

 

Benefits After ODK Adoption

 

1. ODK facilitated the collection of data offline in areas without reliable internet access. The mobile devices used in data collection can also sync automatically when internet access is restored.
2. Improved data accuracy and faster reporting, enabling quicker responses to health crises.
3. Real-time data reporting helped health teams monitor infectious disease trends, identify outbreaks early, and allocate resources more efficiently.

 

Results of ODK Adoption on the Project Beneficiaries

People in conflict areas and remote locations who are vulnerable to disease benefitted in the following ways:

 

1. More efficient disease outbreak response (e.g., cholera, malaria).
2. Improved vaccination coverage tracking and response times.
3. Enhanced decision-making in resource-limited

 

Source

MSF International Activity Report 2014 

 

 

2. KoBoToolBox in Malaria Baseline Survey in Vietnam – Vietnam Public Health Association (VPHA)

Vietnam has made significant progress in combating malaria over the past few decades, but the disease remains a persistent challenge, particularly in rural and remote areas.

Vietnam’s diverse terrain, including dense forests, mountainous regions, and tropical climates, provides ideal conditions for the Anopheles mosquitoes that transmit malaria.

Baseline surveys are initial data collection processes that pave the way for major studies and malaria control projects.

 

Project Details

 

1. KoBoToolBox was adopted in 2021 during a baseline study by the Vietnam Public Health Association (VPHA) on Malaria.
2. This was part of an initiative to map and evaluate malaria transmission rates, health infrastructure, and community knowledge regarding malaria prevention.
3. The study was also conducted at a time when Vietnam was experiencing a fourth wave of the infamous COVID-19 pandemic.
4. Health authorities instituted social distancing measures and limited the movement of people.
5. KoBoToolBox offers a Vietnamese interface and is user-friendly. Its standout feature is the ability to capture photos, record locations, and input data, even in areas without internet connectivity.

 

 

Challenges Before the Adoption of KoBoToolBox 

 

1. Before using KoboToolbox, data collection for malaria surveys involved paper-based forms, which were time-consuming and prone to human error.
2. There were frequent issues with inconsistent or incomplete data, especially in remote areas where access to trained enumerators was limited.
3. In rural or hard-to-reach areas, the communication process between survey teams and the central data center was slow.
4. Managing paper-based data was cumbersome and required significant resources to store, digitize, and validate, further stretching project budgets.

 

 

Malaria remains one of the deadliest infectious diseases, particularly in sub-Saharan Africa. Picture/Courtesy

 

 

Key Benefits After the Adoption of Mobile Data Collection in Vietnam Health Surveys

 

1. Mobile data collection allowed enumerators to collect data directly on tablets or smartphones.
2. With features such as built-in validation rules, the tool minimized data entry errors and ensured data consistency across various sites.
3. The digital nature of the data collection enabled real-time data syncing to a central server. This allowed immediate access to survey results for analysis, enabling quicker interventions if necessary.
4. By reducing the need for paper, printing, and manual data entry, KoboToolbox significantly reduced operational costs.
5. Since KoboToolbox worked offline, it was ideal for the remote, often disconnected areas of Vietnam where internet access was unreliable.

Source

Conducting a Community Malaria Baseline Survey With an Innovative Approach in Vietnam – UNOPS

 

 

3. Drones for Sample Tracking in Mozambique – Drones For Health Initiative

Alongside other African countries like Rwanda, Kenya, and Senegal, Mozambique has extensively adopted the use of drones for health studies.

While drones are mostly used in transporting urgent medical supplies, they have proved to be a vital addition to collecting data for health research and disease control.

 

Project Details

 

 

1. Drones were adopted in 2022 during the second phase of a health study on Tuberculosis and COVID-19 prevalence in Mozambique.
2. The drones were deployed to assist in the specimen referral system where more than 15,000 samples collected from remote areas were transported.
3. VillageReach, a nonprofit organization, collaborated with the Mozambican National Institute of Health on this project, which also assessed the benefits and costs of using drones for transporting laboratory samples.
4. The drones were fitted with the Swoop Aero Data Tracker, a tool used to monitor and manage the performance and operations of drone delivery systems.
5. It collects real-time data on drone flights, helping to track samples in transit, and deliveries, optimize routes, and ensure safety and efficiency.
6. The tracking mechanism was invaluable in the mostly remote and rural Inahambane province of Mozambique.

 

Challenges Before the Adoption of Drones in Mozambique Health Data Collection

 

1. Remote health centers faced challenges with communication and real-time data sharing, which affected the overall coordination of health services.
2. Many areas, especially rural regions, lack reliable road networks, making it difficult to transport health samples on time.
3. The health system grappled with irregular sample collection and delayed delivery, leading to slower turnaround times for critical diagnostic results.

 

 

While drones are mostly used in transporting urgent medical supplies, they have proved to be a vital addition to collecting data for health research and disease control. Picture/Courtesy

 

 

Key Benefits After Adoption of Drones

 

1. Drones helped to extend the reach of health data collection to remote or hard-to-reach areas, increasing healthcare equity.
2. Drones significantly reduced the time required to collect and transport health samples, improving the turnaround time for diagnostic results.
3. Drones were able to maintain temperature-sensitive samples within the required conditions during transport, ensuring sample integrity and more reliable results.
4. The integration of Swoop Aero’s Data Tracker provided real-time visibility into the movement of samples, enhancing tracking, accountability, and transparency in healthcare.

 

Sources

Optimizing the Specimen Referral System in Mozambique with Drones – VillageReach

 

 

4. mTrac SMS Tool for Health Data Tracking in Uganda

mTrac is a mobile-based health management system used in Uganda and other countries to enhance real-time data collection and health reporting.

The system was adopted by UNICEF (the United Nations Children’s Fund), a global organization dedicated to promoting and protecting the rights of children, particularly in areas where they are most vulnerable.

 

Project Details

 

1. The mTrac system was introduced in 2011 and leverages SMS technology to enhance healthcare data collection, surveillance, and response in remote areas.
2. It allows healthcare workers to send vital health information via SMS (text messages) to a central system, which can then be analyzed and acted upon quickly.
3. Through mobile phones, mTrac enables health workers, even in areas with limited internet access, to report disease outbreaks, track stock levels of essential medicines, and receive alerts about health issues.

 

 

Challenges Before the Adoption of the mTrac SMS-based Health Data Collection Platform

 

1. Health facilities relied on paper-based reports, which were bulky, prone to errors, and delayed. This manual process was slow and made real-time monitoring impossible.
2. There were low rates of timely data submission from health facilities, which affected proper surveillance and response to health issues.
3. In some districts, issues like absenteeism, theft of medicines, and poor service delivery went unchecked due to weak monitoring systems.

 

Uganda’s health challenges, from infectious diseases to maternal health, create a high demand for data systems to guide interventions. Picture/Courtesy

 

 

Key Benefits After Adoption of mTrac SMS Tool in Uganda’s Healthcare Sector

 

1. mTrac enabled health workers to submit weekly health surveillance data via SMS. This provided authorities with up-to-date information, enhancing their capacity to respond to public health emergencies.
2. The system tracked diseases and sent automatic alerts when thresholds were reached, prompting quick interventions.
3. mTrac allowed for anonymous SMS reports, which were reviewed by the Ministry of Health, contributing to better health service delivery.
4. mTrac enabled low-cost, rapid polls and surveys to assess health facilities’ performance, enhancing data-driven decision-making.

 

Source

mTrac: Using innovations to improve healthcare – UNICEF Uganda

 

5. SurveyCTO in Population Services International (PSI) Family Planning Program – Kenya

 

Population Services International (PSI) is a global nonprofit organization that focuses on improving the health and well-being of individuals, particularly in low- and middle-income countries.

The PSI primarily operates in third-world countries, including Kenya, with a specific focus on the following areas:

 

1. Family planning and reproductive health
2. Maternal Health
3. HIV/AIDS prevention
4. Water Sanitation and Hygiene (WASH)
5. Malaria prevention

 

Project details

 

1. PSI is actively engaged in family planning initiatives in Kenya as a key component of its broader reproductive health efforts.
2. With an estimated budget of over $50 million a year, the organization has made massive strides in its population control efforts in the country.
3. Between 2018 and 2021, the Bill and Melinda Gates Foundation conducted a study on the impact of availability and market dynamics on the uptake and usage of family planning products in Kenya.
4. The study heavily relied on mobile data collection using modern tools like SurveyCTO.
5. The study was a progressive step in the family planning campaign spearheaded by PSI.

 

Challenges Before Adopting Mobile Data Collection

Traditional paper-based data collection led to delays in reporting and difficulties in tracking family planning metrics.

 

 

Family planning is a key strategy for promoting reproductive health, empowering individuals, and addressing population growth challenges in Kenya through increased access to contraceptive methods. Picture/Courtesy

 

 

Benefits After the Adoption of Mobile Data Collection

The mobile data collection approach positively impacted local women of reproductive age and assisted healthcare service providers in the following ways:

 

1. Real-time data collection using mobile devices allowed faster program adjustments and better resource allocation.
2. Improved healthcare data quality led to better decision-making and planning.
3. The integration of data with national databases brought better coordination in the rollout of family planning services across the country.

Source

Assessing the Complete Market For Family Planning From the Consumer’s Perspective

 

 

Also read: Transforming Agriculture with Accurate Data: ODK in Action

 

 

Key Benefits of Mobile Data in Healthcare Data Collection

 

Mobile Data Collection in Disease Surveillance

 

1. Mobile Data collection allows for the rapid collection of data, ensuring that health professionals can access up-to-date information quickly, crucial for timely decision-making in disease surveillance.
2. Mobile tools accelerate the data collection process by eliminating manual paper forms, reducing delays, and enabling quicker responses to outbreaks.
3. Mobile-based tools support offline data collection, allowing field workers to collect data in remote areas with limited or no internet connectivity.
4. Mobile data collection reduces the costs of paper-based data collection, including printing, transporting, and storing physical forms.

 

Mobile Data Collection in Vaccination Campaigns

 

1. Mobile devices facilitate the immediate collection and transmission of vaccination data, allowing authorities to monitor vaccination progress in real-time.
2. By replacing paper forms with mobile data collection, you streamline the process, reducing delays in reporting and enhancing the overall efficiency of vaccination campaigns.
3. Mobile tools work offline, allowing field workers to collect vaccination data in hardship areas with no internet connectivity.
4. Validation features and automatic error checks help ensure the data collected is accurate and consistent, which is critical for tracking vaccination coverage.

 

 

Mobile data collection enhances vaccine efficiency by enabling real-time tracking of distribution, monitoring coverage, and identifying areas with low vaccination rates. Picture/Courtesy

 

Conclusion

Conclusively, the use of mobile data collection tools, drones, and SMS technologies in the healthcare sector has significantly improved the efficiency, accessibility, and effectiveness of health services.

 

Mobile data collection enhances real-time reporting and decision-making, while drones facilitate the timely delivery of medical test samples crucial in capturing public health data and overcoming logistical challenges.

 

SMS tools provide a simple and reliable means of communication for health workers, ensuring quick data transmission and feedback. Together, these technologies are transforming healthcare delivery, particularly in underserved and rural regions.

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