Category Archives: Research

New paper on mHealth: Improving the Routine HMIS in Nigeria through Mobile Technology for Community Data Collection

Untitled

The paper’s abstract

Decision makers in many developing countries lack the required data needed for evidence-based health management. One reason for this is that the routine national health management information systems (HMIS) do not extend to the ‘last mile’, the communities and the informal setting of villages, where a significant proportion of health events occur. Community-based HMIS data collection is often either poor, or non-existent, in low resource settings. Efforts at establishing community-based HMIS in the past have often failed, or at best, become dysfunctional, beset by challenges with supporting infrastructure such as erratic power supply, poor road transportation and poor telecommunication. However, the advent of mobile technology with its increasing penetration into the rural areas has permitted a re-envisioning and redesign of HMIS data collection. The study described in this paper presents lessons from the application of mobile technology to the collection of data from households and individuals, with the aim of improving the routine HMIS. It utilized a participatory action research approach; and was carried out in Cross River State in Southern Nigeria. The paper makes three major contributions. Firstly, it briefly describes the context and operations of a mobile-based community data collection system designed and implemented to provide high quality health and demographic data for the national HMIS. Secondly, it details organizational mechanisms by which the application of mobile technology reduces the difficulty of data collection from communities and districts, thus strengthening the district-based national health information system. Thirdly, the paper points to emerging challenges and areas for further research. Overall, evidence from the research suggests mechanisms by which mHealth data collection improves the HMIS organization, through savings in organizational resources, increases in information quality and in organizational efficiency (technology as an occasion to restructure) as well as in creating new possibilities for institutionalized HMIS data collection.

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Paper published: Understanding HMIS Implementation in a Developing Country Ministry of Health Context – an Institutional Logics Perspective

This Public Health Informatics research paper discusses the institutional aspects of HMIS implementation in the real world setting of a developing country Ministry of Health. It highlights the complexity of such an endeavor, in a context that, as HMIS implementers generally agree, can often be contested, dysfunctional and/or simply put, a hard nut to crack.

I generated the paper’s word cloud (see below) – a word cloud is a visual representation of the paper’s text data, highlighting the most used words or keywords.

HMIS institutional logics paper asangansi

The paper’s abstract

Globally, health management information systems (HMIS) have been hailed as important tools for health reform (1). However, their implementation has become a major challenge for researchers and practitioners because of the significant proportion of failure of implementation efforts (2; 3). Researchers have attributed this significant failure of HMIS implementation, in part, to the complexity of meeting with and satisfying multiple (poorly understood) logics in the implementation process.

This paper focuses on exploring the multiple logics, including how they may conflict and affect the HMIS implementation process. Particularly, I draw on an institutional logics perspective to analyze empirical findings from an action research project, which involved HMIS implementation in a state government Ministry of Health in (Northern) Nigeria. The analysis highlights the important HMIS institutional logics, where they conflict and how they are resolved.

I argue for an expanded understanding of HMIS implementation that recognizes various institutional logics that participants bring to the implementation process, and how these are inscribed in the decision making process in ways that may be conflicting, and increasing the risk of failure. Furthermore, I propose that the resolution of conflicting logics can be conceptualized as involving deinstitutionalization, changeover resolution or dialectical resolution mechanisms. I conclude by suggesting that HMIS implementation can be improved by implementation strategies that are made based on an understanding of these conflicting logics.

Keywords: Social issues in Public Health Informatics; developing countries; health management information systems; institutional logics; institutional aspects of information systems; action research; Nigeria; Ministry of Health; change management

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In Nigeria, Mobile overtakes Desktop – Generation mI

This has long been discussed; the large potential that exist for m4D, mobiles for development. But it is now cemented by data, which clearly illustrates how the internet is increasingly accessed in developing countries.

Mobile Overtakes Desktop

Mobile vs Desktop

Note: It doesn’t necessarily mean that access on the desktop is reducing. No, look again, the y-axis is percentage, so it means it more of a ratio or percentage. The actual number of hits from personal computers may still be rising (or may be stagnant…or worse dropping) but clearly this shows that most of the hits to the internet from Nigeria have been from mobiles…from few months ago.

Permit me to say that Nigeria’s mobile internet (mI) generation began a while back. I feel opportune to be able to place my thesis right in this center of activity and investigate how this can be used to leverage health care, which is in dire need of a fix.
I think this data clearly makes an argument for expanding our global health arsenal to mobile web tools. More so as the current mobile internet price wars in Nigeria will further increase access to more people.

Contrast this to the worldwide trend, which shows a change that is less than 10%;
Worldwide; Mobile vs Desktop war

Lets leave it at that for now…
PS: Data based on thousands of sites on the StatCounter network (as recognized by ip address). By May 2010 the StatCounter site had 19,336,215 hits from Nigeria (out of a worldwide total of 16 billion hits)

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Writing up thesis on mHealth…Scaling mHealth in Low-Resource settings

Scaling is a central concern in public health. More so, it is an underlying assumption because it is largely concerned with the health of the entire populace. The motivation to scale health services and its associated components including health information networks is underpinned by everything ‘public’ about public health. It is a basis for WHO’s mission and was well captured in its landmark ‘Health for All’ conference in Alma Ata 40 years ago (WHO, 1978). It is also the basis for spreading evidence-based and scientifically proven small-scale interventions to the populace (Black 1986, Taylor 2010). Scaling up global health initiatives and packages, rolling them to the lowest levels is thus a core strategy in reaching for the Millenium Development Goals targets by 2015 (United Nations, 2010).

Despite considerable increases in funds directed at scaling health services in low-resource settings and their associated information systems (Ravishankar et al 2009), reaching the lowest levels of care and the populace in targeting the MDGs have been largely unsuccessful (United Nations, 2010).

In this regard, mHealth, the application of mobiles for health is promising. Mobile technology is transforming healthcare by increasing access to healthcare and health-related information including hard-to-reach populations, improving the ability to track diseases, providing timlier and more actionable public health information and expanding access to health education as well as training (VitalWave, 2009). From a mass media perspective, it is also regarded as the fastest scaling media technology in history compared with how long it took print, recordings, cinema, radio, television and internet to scale (Ahonen, 2008).

In this research, the role of mHealth in scaling health information networks is investigated. Is mHealth the magic bullet it is envisioned to be? Are they any constraints – technical, strategic, organizational? What are the key lessons for architectural and implementation design?

Research aims and objectives coming…

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Statistics for Nigeria from Opera Mobile

Interesting statistics from Opera on Nigeria
http://www.opera.com/smw/2009/11/

Snapshot: Nigeria

* Page-view growth since November 2008: 311.2%
* Unique-user growth since November 2008: 211.4%
* Page views per user: 361
* Data (compressed) transferred per user (MB): 5
* Data (compressed) transferred per page view (KB): 14

Top 10 sites in Nigeria (unique users)

1. facebook.com
2. google.com
3. yahoo.com
4. bbc.co.uk
5. goal.com
6. wikipedia.org
7. cnn.com
8. sharemobile.ro
9. nairaland.com
10. myspace.com

Top handsets for November 2009

1. Nokia 3110c
2. Nokia 5130
3. Nokia 2600c
4. Nokia N70
5. Nokia N72
6. Nokia 6300
7. Sony Ericsson K750i
8. Nokia 2630
9. Sony Ericsson K800i
10. Nokia 3500c

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mHealth: Connectivity and Accessibility as Key

mHealth is widely regarded as the application of mobile technology to health. This is a useful simplification especially to the uninitiated and the unsuspecting…
It doesn’t do justice to what is ‘mobile’ and socially ‘mobilized’ in mhealth, thereby presupposing a simplistic technologically deterministic result.

I was just thinking that the key feature in the practice of mobile communication in health is connectivity rather than mobility, especially in the context of developing settings. Of course, connectivity becomes an issue when mobility arises.

But look back and think: haven’t individuals and communities been mobile from time immemorial? Haven’t technologies been mobile in themselves? walking around the surface of this crust we call the earth?
What mobiles and telecommunications introduce to use now is mainly connectivity, accessibility on the go. It is the increased individualized capacity to access global and local networks from any place and any time that is making much difference.

We need to begin to foster this phenomenon for health, allowing access to health-related information to everyone. That should move us closer to meeting the MDGs (if you don’t know what that means, chances are that you don’t need it…lol).

This is one of the major ways we should develop the mHealth space.

Ime Asangansi is an mHealth researcher based in Nigeria. He is a research fellow at the University of Oslo, Norway.

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