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Improving the recording and reporting of facility-based mortality using open source mobile technology: lessons from Cross River HDSS, Nigeria.

1. Introduction

Mortality, migration and fertility are three essential indicators that give insight into the population status, distribution and structure of any nation. Mortality (death event) is inevitable and a one-time occurrence that often creates deep vacuum, difficult to fill in a family, community, organization and the society in general. The impact of this unfortunate event can be too severe and irreparable. Any nation desiring to sustain or improve the growth of her economy therefore, makes effort at ensuring minimal occurrence of this event, especially preventable deaths. One of the common ways of reducing death rates is by tracking all deaths and identifying the root causes in order to help plan interventions and prevent future occurrence from the same causes.

However, the difficulty of tracking all deaths arises from the fact that death happens anywhere. Usually, deaths that occurred in the community are termed community-based deaths while all deaths in formal health facilities are known as facility-based deaths. Over the years, governments have developed measures for tracking death events, wherever and whenever they occur. For instance, the National vital registration system was solely designed among other objectives, to register all deaths, be it in the facility or community. Health and demographic surveillance systems are also platforms setup especially in low and medium-income countries (LMICs) to track deaths in communities.

Countries are often at crossroad in setting up these data collection platforms due to cost. Fully functional vital registration systems are systems that would have guaranteed efficient and complete collection of death records. However, high implementation costs often prevent countries from adopting its use. Salawu (2009) asserts that standard vital registration systems are only functional in few countries (wealthy countries) where there are resources and better infrastructure. For poorer countries, implementation takes close to a decade or more; a process which has forced hospital managements to continue the use of paper-based approaches in spite of the numerous limitations in paper-based data collection systems. Another approach for recording death events is through the implementation of some form of facility-based surveillance systems and programmes in health facilities. A typical example is the tracking of deaths in South Africa health institutions to assess the impacts of disease burden using programmes such as Confidential Enquiry into Maternal Deaths (CEMD), Peri-natal Problem identification Programme (PPIP), Child Healthcare Problem Identification Programme (Child PIP) and National Injury Mortality Surveillance System [NIMSS] (Joubert, et al., 2012). Some routine health management information systems have features for capturing facility-based deaths also. The DHIS2 tracker is one of such tools used for sharing basic clinical data across health facilities. It permits the collection, management and analysis of disaggregated data such as immunization, neonatal and maternal deaths audits (DHIS2, 2016).

The importance of reliable data on facility-based deaths need not be over-emphasized. Accurate recording and timely reporting of facility deaths are at first instance, legal proof of the death event. It provides formal backing and reference on the issues (place, time, cause of death, ailment leading to death, etc.) surrounding the death. More so, the information needed in understanding the etiology (study of the causes and origins of diseases) and its economic burden on the nation as provided through timely and accurate collection of this one-time event is used by governments and researchers in measuring mortality rates and trends within a fixed-time periods. Policies that can strengthen socioeconomic development and reduce the mortality rate of nations can be formulated based on the outcome of mortality data that have been reviewed and analyzed.

Fatality rates of life-threatening health issues and emergencies can be reduced or even prevented, if there is timely availability of data on such a condition. Examples can be drawn from the experiences in tackling the Ebola and Lassa fever epidemics which Nigeria, Liberia, Guinea, and few other countries suffered great loss. The timely detection and recording of the Ebola hemorrhage fever led to Nigeria's success story in curtailing the disease from spreading.

Mortality information is crucial and needed by nations for effective national planning (population forecasting, social description), health sector planning (planning and development, evaluation of health services and programmes) and epidemiological and medical research interventions [epidemiological studies, and evaluation of medical procedures] (Hill, 1984). Accuracy in recording and reporting can strengthen the integrity of facility-based mortality data by eliminating errors arising from mortality bias and under-reporting. Besides, the accuracy of this data can assist health policy planners to implement policies and programmes that will reduce premature death and improve the quality of life. An implication of not having accurate recording of mortalities which is often as a result of omission of death events and errors in the coding of key variables like age and dates is seen in the inability of health policy planners to measure death rates, cause of deaths, sex- and age-specific mortality patterns and differentials in countries (Mathers & Boerma, 2010). Reliable data sources are therefore required for comparing death rates and trends among countries. Without accurate or timely collection of these data, results from such comparisons will be skewed or inconclusive.

1.1 Problem with paper-based approaches

Notwithstanding the numerous benefits of collecting and reporting facility-based deaths, the collection method matters, as this affects the quality, access, and completeness of such data. There are many problems inherent in paper-based approaches to collecting and reporting of facility-based mortality data. Some of these problems are difficulty in tracing and correcting probable mistakes once written and archived, inconsistent and/or misleading terminologies in the classification and reporting of symptoms and diagnosed cause of death among health facilities or individual physicians. For instance, a physician may classify cardiopulmonary arrest and chronic heart failure as symptom and cause of death, while another records renal disease and cardiovascular disease. This disparity in documenting the cause of death can mislead data analysts, thereby yielding erroneous statistics and decision-making on deaths (Mirabootalebi, Mahboobi, & Khorgoei, 2011).

A well-designed electronic mortality data collection tool can prevent these problems, by coding likely symptoms and causes as dropdown options, radio buttons and check boxes from which users can choose. Another solution would be enforcing data integrity through complex skip pattern and restriction of some sets of possible responses in the electronic form design (Tomlinson, et al., 2009). The inclusion of these form design features into clinical data collection tools has the potential to: reduce entry errors, reduce data collection time and improve the quality of mortality data collected. This is justified in the study by Paudel, Ahmed, and Pradhan, (2013) which assessed the benefits and challenges of using tablet personal computers (PCs) and wireless technologies in administering demographic and health survey in Nepal, South Asia.

Other problems associated with paper-based methods include: huge budgets on paper, storage space and filing infrastructures. There is also possibility of losing collected death records to natural disasters and accidents such as flood and fire outbreaks. Quick access to and retrieval of these records are also not possible. Researchers have also established that paper-based systems have no mechanism for ascertaining completeness, data integrity, accuracy and timeliness of data collection and entry (Douglas, et al., 2005; Njuguna, et al., 2014). This is a critical concern in the use of paper-based systems for facility-based mortality data collection. The use of information technology approaches is an optimal solution to these problems of paper-based data recording and reporting (Satterlee, McCullough, Dawson, & Cheung, 2015). The goal of this study is to contribute knowledge on techniques for improving the recording and reporting of deaths that happen in health facilities, using open source mobile information technology.

2. Literature Review

2.1 Paper-based approaches to recording and reporting of deaths

Reporting and management of facility-based mortality data can be done using different approaches. The predominant method used in many resource-constrained health institutions is the paper-based method. This method relies on paper forms, registers and books for recording hospital death information. With the establishment of the National Health Management Information System (NHMIS) by the Nigeria Federal Ministry of Health (FMOH) in 1991, health facilities have since employed the use of standardized paper-based Health Management Information System (HMIS) forms for facility data collection and reporting. HMIS is a mechanism for collecting and generating information required for operating health services and also for research and planning (Asangansi, et al., 2013). In terms of deaths, HMIS forms are used in health facilities to collect monthly summaries of facility-based data. Completed forms at health facility level are sent to the local government level for onward transfer to the state and then national. In Nigeria, the high cost of data aggregation and transmission using the HMIS forms led to the use of the DHIS2 software (HISP, 2016).

The software supports the electronic collection of HMIS data. Unfortunately, many health facilities are not able to migrate to the DHIS2 platform. Findings from the Nigeria Health ICT Phase 2 Field Assessment exercise conducted by the UN Foundation in collaboration with the Ministry of Health in 2014 showed that DHIS2 is operational in just a quarter of health facilities across selected representative clusters assessed (UN Foundation, 2015). This daunting result justifies the need for alternative cost-effective platforms for collecting data on vital events like mortality.

2.2 Electronic approaches to recording and reporting of deaths

Having identified the problems of paper-based systems, health and information technology practitioners have, over the years, sought the use of electronic approaches as alternate solutions. In the early 1960s, hospitals in the United States used computer-assisted microfilm systems to index and store deaths and other vital events records for easy retrieval. Prior to the advent of this technology, vital information were stored in files in the form of ledgers (Logrillo, 1997). Electronic death registration system is another system developed for registering deaths. It is a secure system used in Washington to register and edit death certificates online. The web-based application allows reporting of deaths from health facility to local and national offices of government for management (Mirabootalebi, Mahboobi, & Khorgoei, 2011). Though it streamlines the recording process and reduces the time of data collection and filing, it does not support mobile devices and also requires users to have high-speed internet connection (New York State Department of Health, 2016).

In order to have detailed, complete and timely information on all violence-related mortalities among residents and non-residents, the United States Center for Disease Control and Prevention designed a surveillance system--National Violent Death Reporting System (NVDRS), which extracts information from crime laboratories, death certificates, medical examiner and law enforcement files and records (Paulozzi, Mercy, Frazier, & Annest, 2004). Notwithstanding the relevance of NVDRS in reporting and preventing violence related deaths such as suicides, homicides, deaths of undetermined intent, there exists crucial factors limiting its global adoption: (1) only a few low-, middle- and high-income countries have the required resources to implement the system, (2) collation of violence-related mortality data from different locations can only be done by a single agency with requisite technical competencies such as public health with vast knowledge in epidemiological surveillance (Butchart, 2006).

Africa is also not left out in the struggle to correctly use mortality information in assessing impact of health policies and planning. Electronic systems designed to capture comprehensive and timely data on mortality have been deployed in healthcare settings to boost the civil registration systems of some countries. In most cases, these systems are intervention-specific, hence cannot be used for the assessment of all death events in a health facility. For instance, the Malawian government in 2014 made concerted efforts at reducing maternal mortality through the implementation of a national Maternal Death Surveillance and Response (MDSR) system. The objectives of the project include: improving timely and quality reporting of all maternal deaths, systematize verbal autopsies and maternal death audits (Konopka, 2016). Obviously, it is pertinent to have a cost-effective, scalable and sustainable electronic system (preferably open source-based system) that is able to routinely report diagnoses and deaths information for administration and quality assurances purposes. This is because health facilities are the major source of mortality data needed for national and subnational policy and planning.

2.3 The use of mobile technology in recording and reporting of deaths

With the gradual transition from paper-based systems to a more flexible, efficient and cost-effective means of recording facility-based mortalities, the use of mobile technology has been developed and used in many settings (developed and developing countries) to enhance data collection and entry. Feedback from projects that were implemented using mobile-driven technology shows the overwhelming advantages of mobile technology. A review by Hall et al. (2014) on the impacts of using mobile technologies in Low-and-middle-income countries to measure common and crucial health outcomes highlighted these benefits. The use of mobile technology minimizes data entry errors and reduces the rate of data loss. It also strengthens data collection, tracking and reporting of vital events.

2.4 Available open source tools for recording and reporting of deaths

The adoption of open source tools in the development of data collection and management systems by health institutions, especially in developing countries, is a low-cost technological innovation that has improved the standard of hospital data collection and reporting systems. This is practically due to the flexibility of adapting and extending existing open source software to suit hospital-specific requirements, without unnecessary duplication of effort, as such preventing the lock-in complexities that are concomitant with proprietary systems (Reynolds & Wyatt, 2011).

Though there are really no established literatures reporting the use of open source solutions specifically for recording and reporting of facility-based mortalities, different countries have built or adapted some medical and health records open source-based applications that incorporate mortality data capturing features. A typical example is the DHIS2 software which is used as the health management information system in many developing countries. DHIS2 Tracker is a module built into the DHIS2 software, which supports longitudinal tracking, aggregation and exporting of one-time events such as deaths and births into DHIS2 core application for validation checks, mapping and reporting (HISP India, 2016).

In a review conducted by Meystre and Muller (2005), the authors outlined several customizable open source software presently in use in most health institutions around the world. Examples include: Care2x, OpenVistA, FreeMed, OpenEMed, OSCAR McMaster and OpenEMR. Results from a similar study conducted in September, 2010 by the National Opinion Research Center (NORC), Chicago on the use of open source electronic health record systems in medical institutions also demonstrated the robustness and flexibility of using open source solutions in healthcare settings. It was reported that open source medical software such as VistA electronic health record, OpenMRS, MedLynks and ClearHealth were customized and implemented by different health institutions to address the specific requirements of these institutions. (Goldwater, et al., 2013). The concern would be on the cost of hardware, ancillary software, technical expertise and other resources needed for the successful implementation and continuous support of the chosen open source solution. We addressed this concern by implementing a facility-based mortality data collection system using mobile tools built on simple free and open source software technology.

3. Methodology

3.1 Study Setting

The Cross River health and demographic surveillance system (Cross River HDSS) is a research platform operating two cohorts located within the southern senatorial district of Cross River State in south-south Nigeria. The two cohorts have a combined population of 33,446 persons in 8,508 households (48% of which are rural dwellers) continuously under surveillance. The rural cohort is located in the Akpabuyo Local Government Area (LGA) of the state and the urban cohort located in Calabar-Municipality; both in the southern part of the state. Data on community-based deaths is collected 4-monthly in each of these cohorts using verbal autopsy procedures (INDEPTH Network, 2008). However, there is a secondary and tertiary health facility respectively in the rural and urban cohorts, where facility-based deaths are recorded. There is the St. Joseph's Hospital in Akpabuyo and the University of Calabar Teaching Hospital in Calabar-Municipality.

3.2 Conceptual Design

Figure 1, describes the conceptual design for collecting and reporting facility-based deaths. At one end, you have the end-users who are the health workers (HWs) using either mobile (Android) smartphones or web-forms (Internet-connected computers using HTT Protocol) to collect and send mortality data from a health facility. This data is originally recorded on hospital registers. At the other end, there is a web server implemented on ODK Aggregate (Open Data Kit, 2016), hosted with cloud technology (Google Cloud Platform, 2016). The web server hosts XML-formatted (blank) electronic mortality forms, as well as receives data from the users (health workers) over GSM or Internet (web form HTTP) upload. This data is first saved in the cloud-based web server. Later, and when appropriate, technical/admin users download the data into different formats, (particularly CSV) for analysis and reporting. XML (extensible markup language) is a kind of markup language used by application designers to define a set of rules for encoding documents in a format which is both human readable and machine-readable (Quin, 2015).

3.3 Use Case

In software systems design, a use case is a list of steps, typically defining interactions between a role (known in unified modeling language [UML] as an "actor") and a system that supports a particular business goal. The actor can be a human, an external system, or time that triggers the use case. Use cases are used to show a system's context and functionality (Booch, et al., 2007). The use case for this study is shown in Figure 2.

From the Use Case diagram of Figure 2, the following actions take place in the system:

* Create Form & Upload: The

technical/admin user creates the mortality surveillance data collection forms in XMLcompatible format and uploads to the ODK Aggregate Web Server.

* Download F orm: The health worker, using an Android mobile phone configured to point to the ODK Aggregate Web Server, downloads the blank mortality form into the phone.

* Fill & Upload Form: The health worker fills the form with individual mortality episodes. S/he can view and edit the entries for the form fields before uploading the form to the ODK Aggregate Web Server.

* View Submitted Data: The technical/admin staff logs onto the ODK Aggregate Web Server to view the submissions from health workers who submitted data from different remote locations.

* View Form & Form List: Both the health worker and technical/admin staff can view the list of available forms for data entry. While the health worker views the forms list with his/her mobile device, the technical/admin user can also view the forms from the Web Server, including forms that are not yet available for use by the health worker.

* Download Data for Analysis: The essence of every data collection exercise is to report findings from the data. After submissions, the technical/admin staff can download the data from the ODK Aggregate Server, mostly in CSV format, for analysis and reporting. Data can also be downloaded into KML format for geo-mapping of health facilities.

4. Implementation

4.1 Results

The implementation of this study was piloted at the University of Calabar Teaching Hospital (UCTH) Calabar, which is one of the health facilities collaborating with the Cross River HDSS. Android Tablet PCs and Android smartphones installed with ODK Collect v1.44 were used to capture and transmit retrospective mortality data from the Records Department of UCTH to ODK Aggregate server v1.4.4 deployed on Google App Engine Cloud. The data was exported into CSV (comma separated values) format. Data was analyzed using an open source software, the R Statistical Computing Software v3.3.1 (The R Foundation, 2016). Figures 3-5 show some of the results from the analysis.

The use of electronic formats to capture mortality records made data input simpler and faster, as about 95% of the input fields are mere dropdown lists from which choices could be made. This reduces, to the barest minimum, errors due to user text input, thus enforcing some level of system input controls. The ability of the ODK technology to export data in compatible formats, like CSV, facilitates the analysis and reporting of data using any analysis software (Creativyst Software, 2010). The availability of data in the cloud enhances access and facilitates the ability to generate reports even from remote locations. The reports shown in Figures 3 5 of this study are seldom promptly available in most health facilities in Nigeria, due to reasons ranging from inconsistent data formats based on paper storage, to lack of resources to implement information technology solutions. The use of free and open source tools takes away costs associated with software and enhances interoperability (Walli, Gynn, & Rotz, 2005; Shaikh & Cornford, 2011).

5. Conclusion

This study has demonstrated that, the lack of availability of mortality data from health facilities due to poor recording-keeping from paper-based approaches can be reduced to the barest minimum, when electronic data collection and reporting tools are introduced. It has also shown that, the use of free and open source technology will ensure affordability and enhance interoperability when these solutions interface with other systems in these facilities. The prompt availability of information on facility-based deaths (especially on cause of death) can go a long way in assisting health policy and interventions by hospital administrators and other stakeholders in the healthcare sector.

The merits notwithstanding, the introduction of electronic data collection and reporting method as presented in this study is limited by the difficulty with which text can be typed using smartphones, especially on mortality issues, where sometimes a narrative on symptoms during illness may be informative. However, these narratives can be captured as photo inputs to form part of the individual record during data collection. Besides, there are other facility-based electronic data reporting methods, like DHIS2 that reports aggregated data. Future research could explore the integration of the mortality surveillance system with the DHIS2.

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Iwara Arikpo (1,2),*, Idongesit Eteng (1), Anthony Okoro (2), Uchenna Nnabuko (1)

(1) Department of Computer Science

(2) Cross River HDSS, Directorate of Research & Quality Assurance University of Calabar, Nigeria

* Corresponding Author: iiarikpo@gmail.com, iwara.arikpo@unical.edu.ng

Figure 4: Proportion of deaths by ward

% of deaths by Ward (N = 151)

Ante-natal Ward            0.7
Cardio-Thoracic-Ward       1.3
Casualty Ward              0.7
ENT Ward                   0.7
Female Medical Ward        37.7
Female Orthopaedic Ward    0.7
Female Surgical Ward       3.3
Intensive-Care Unit        0.7
Male Medical Ward          40.4
Male Orthopedic Ward       1.3
Male Surgical Ward         2.0
Paediatric Medical Ward    6.0
Paediatric Surgical Ward   0.7
Post-natal Ward            0.7
Sick Baby Unit             2.0

Note: Table made from bar graph.

Figure 5: Proportion of deaths by diagnosed causes

First diagnosed cause of death (%)

Burns                    1.3
Cancer                   3.3
Diabetes                 4.6
Gastro enteritis         0.7
HIV/AIDS                 5.3
Hypertension             6.0
Injuries                 2.0
Malaria                  1.3
Stroke                   4.0
Tetanus                  0.7
Other (various causes)   60.9

Note: Table made from bar graph.
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Author:Arikpo, Iwara; Eteng, Idongesit; Okoro, Anthony; Nnabuko, Uchenna
Publication:Computing and Information Systems
Article Type:Report
Geographic Code:6NIGR
Date:May 1, 2016
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