Presented by Professor Graham Wright Chair of Health Sciences Research, Walter Sisulu University

1. Using tablet computers to collect data in a rural clinic
by
Professor Graham Wright
Chair of Health Sciences Research

2. Me
• Research Champion
– Full professor – full time research
– Increase Research Capacity
• Chair of Health Sciences Research
• New requirement for specialist to do Mmed
– I supervise new supervisors and 130+ trainee in 29
specialties.

6. North Island
New Zealand
Eastern Cape
South Africa
113,729 km2
168,966 km2
3,366,200
6,562,053

7. HIV Rates
NZ
ZA
2001
1,600
4,400,000
2006
2,100
5,200,000
2011
2,600
5,600,000
HIV+ now running at 29% of population in Eastern Cape

8. Eastern Cape
Population groups
• Black African 86.3%
• Coloured 8.3%
• White 4.7%
• Indian or Asian 0.4%
Languages (11 Official SA Languages)
• Xhosa 78.8%
• Afrikaans 10.6%
• English5.6%
• Sotho 2.5%

9. Each territory's size on the map is drawn according to its
land area.
Peter's map

10. Territory size shows the proportion of people worldwide who receive good
basic health care that live there.

11. Each territory's size on the map is drawn according to its
land area.
Peter's map

12. Territory size shows the proportion of all people aged 15-49 with HIV (Human
Immunodeficiency Virus) worldwide, living there.

13. Each territory's size on the map is drawn according to its
land area.
Peter's map

14. The longest life expectancy at birth is in Japan, at 81 years 6 months. The
shortest life expectancy is in Zambia, at 32 years 8 months. The world average
life expectancy is 67 years.
Mthatha, South Africa is 47.
I am 67 next birthday!!!!!!

15. Each territory's size on the map is drawn according to its
land area.
Peter's map

16. Territory size shows the proportion of all people with some electrical power
in their homes living there.

17. 52 million population
“More than half of South African households benefit
from social assistance, and for 22% grants are the
main source of income. By the end of next
month, 16.1-million are expected to be grant
beneficiaries.”
Grants = approx 120 - 140 NZD per month
Only 5 million are registered to pay tax and
2 million pay the majority

18. Percentage of population with HIV+

19. in Eastern Cape
714 are clinics and
42 Community Health Centers.
Nurses do the job that in Europe and America would
be undertaken by a GP
Family Doctors in the Eastern Cape work in level 1
hospitals and occasionally go to clinics

23. HIV and TB are dangerous bed fellows: the co-infection
rates exceed 70%, with TB being the most common
opportunistic infection in HIV-positive patients.
Read more:
http://www.southafrica.info/about/health/health.htm#.Umkq2BarCYo#ixzz2ieI63pml

24. “Phone an ambulance? My dear, phoning an ambulance
doesn’t even cross my mind. In my seven years at Pilani Clinic,
I have never seen an ambulance at this clinic,” says Sister
Sylvia Horner.
Recently, there was no antiretroviral medicine for three
months

26. Nurses undertake most of the
primary care in the Eastern Cape
They use a lot of paper for
recording all sorts of information

28. Declaration of Alma-Ata
International Conference on Primary Health Care,
Alma-Ata, USSR, 6-12 September 1978
Target 9: Implement global and national health information and surveillance
systems
The development of key health status indicators for South Africa within a broad
“Health for All” framework was discussed a decade ago and the issues of poor
data quality recognised (HST 1998).
The data collected in clinics is used for National Indicators as well as data for
funding bodies and specific programs.

30. Assessing the implementation of a
Clinic System
Researcher Robert K. Yin defines the case study
research method as an empirical inquiry that
investigates a contemporary phenomenon within its
real-life context; when the boundaries between
phenomenon and context are not clearly evident; and
in which multiple sources of evidence are used
(Yin, 1984, p. 23).

31. Case Study
Critics of case study say that that have no grounds for
establishing reliability or generality of findings
And are only good for exploring a subject
This study is an illuminative study to explore the
implementation feasibility of an information system
so it can be considered as a “proof of concept” for
the rural area in which it is situated

32. Research Question
Can you implement a cloud
computer system accessing a
web2 database for patient
records successfully in a rural
area at Gqaqhala Clinic

33. Case Study Method
 Determine and define the research questions
 Select the cases and determine data gathering and analysis
techniques
 Prepare to collect the data
 Collect data in the field
 Evaluate and analyze the data
 Prepare the report
(Soy 1997)

34. The Equipment
The Clinic was supplied with state of the art Satellite 3G
connection with support from the top supplier in SA
together with a Desktop Computer and Printer
The software was supplied by a UK software house and
included two UK staff visiting to install the systems and
train.

35. The methods
 Data collection
 Record of time taken to input data
 Observations
 Record of issues seen by research team
 Interviews
 Record of issues discussed
 Examination of historical records
 Identification of issues

36. Issues with environment
• Cloud Computing is becoming Mainstream.
• Broadband exists on 3G but is extremely costly R15000 a Month to do what I used to do in UK for
R300
• Cloud relies “on always on systems” and thin
client
– Gmail is cloud computing
• Outages are a common occurrence – i.e. no
electricity sometimes for a week
• This clinic has no water – for washing or drinking

37. Computer literacy
Not enough initial training.
Non of the staff had seen or used a computer
before
• This was at a very basic level – no idea how to
switch on the computer and nobody knew their
password or user-name.
• The training was given by the system
programmers who only focused on the input of
data
• Note: all staff used mobile phones – the area has
3G connection

38. The are also major conceptual issues that need to
be addressed.
In primary care nurses take on a role which is
more aligned to that of a doctor. Their cognitive
processes are based in the same problem
oriented approach having been taught at
Universities which use Problem Orientated
Learning.
They are not familiar with the Care Plan approach
which is used by Hospital Nurses

39. Staff have a positive attitude!
• All of the nurses are positive about having a system
and have gained some confidence in using the
equipment following the employment of a computer
graduate for one month on site to teach and support
them.
• It would be expected that a positive response is
exhibited by staff when all of their senior line mangers
are positive about the system as they see the
opportunity to get computers for the clinical;
• and having all these important people from the DoH
visiting with the local politicians will have an influence.

40. Nurses data entry
• Analysis of a small sample shows an average of
– 19.58 minutes for inputting just the demographic data
– 14.15 minutes additionally for inputting the clinical
data.
– total of 34. 13 minutes which compares to 5 minutes
to complete the paper record.
• Work undertaken by A Odama for a Masters
thesis indicates that clinic nurses tend to leave
the completion of register sometimes to the end
of the week and then they rely on memory.

41. 4 Projects and team from 3 Faculties
data collection at rural clinics
Prof. Graham Wright
Dr. Don O’Mahony
Chrispin Kabuya
Tony Odama
Prof. Parimalarani Yogeswaran
Frederick Govere
Malcolm Ellis

42. Health Data Ownership and Data Quality: Clinics in
the Nyandeni district, Eastern Cape, South African
Wright and Odama
• clinical registers were designed to meet the needs of the
information officers at government institutions and not
necessarily the clinicians. This would probably explain the
exclusion of clinicians from the design process.
• This implies that the development of clinical registers is linked
to government initiatives for monitored health programmes
• The study identified 17 patient collection tools. Thirteen (13)
of these source tools originate from the Department of
Health, while others were ordinary notebooks used by all
health facilities surveyed to supplement the ones from the
Department.

43. Health Data Ownership and Data Quality: Clinics in
the Nyandeni district, Eastern Cape, South African
• In summary collated data lacked validity, reliability, precision
and there was no evidence clinics were using their data for
strategic decision-making. In essence, data quality was very
poor.
• Nurses who had a register in their room would not leave the
room to hunt for another register – they would leave the data
entry until the end of day or at clinic the nurses meet on a
Friday afternoon to fill in the registers
• National figures produced from such show each nurse seeing
an average 29 patients – I have never seen that few waiting to
see the nurses. Under-reporting possibly by 50%

44. Knowledge helps decisions

45. Nurses at Community health centres (CHCs) and their satellite
clinics provide primary health care services to most of SA
population ( Reagon, Irlam & Levin 2004) .

48. Why a Tablet as recording device?
• Electronic devices better than pen & paper?
• Handheld more portable & robust than
laptops and desktops?
• PDA’s?
• Android phones?
• Tablets: clinician-client interaction, ‘mobility
like paper’, ?

56. Paper Records: Nurses’ Experience
• ‘You will have to finish tomorrow and that is
not nice because it is today’s work, like today I
started with yesterday’s work.’
• ‘It’s like we‘re nursing the books than the
patients.’
• ‘The bad side it takes time and sometimes you
are exhausted and you omit some
information.’
O’Mahony D, Wright, G, Yogeswaran P, Govere F. 2013 Knowledge and attitudes of nurses in community health centres in the
King Sabata Dalindyebo Local Municipality, Eastern Cape Province, about electronic medical records. Curationis (in press)

57. Qualitative assessment
• Tablets were easy to use and saved time.
• Happy to use Tablets in preference to pen and
paper.
• Expressed a desire to extend the use of
Tablets to other areas of their work

58. DHIS: Data collection
• Retrospective
• Inaccurate
• No evidence that data analysis informs any
policy or programme management in
individual clinics
• Efforts under away to improve – using data
capturers e.g. tier.net, eKapa
Garrib, Stoops et al. 2008; Odama 2010; Heunis, Wouters et al. 2011

59. Principles of data capture:
Error Reduction
• Any piece of data is recorded only once, and it
is available for all users both in primary and in
secondary care
• ‘Enter once: use many times’
• Data quality improves the closer it is to the
point of capture and if the staff who enter
data benefit from the coding
Coiera 1997; Stonham, Heyes et al 2012; Douglas, Gabadu et al 2010

61. Tablet computers for recording TB data at a
community health centre, King Sabata Dalindyebo
Sub-District, Eastern Cape: a proof of concept report
The aims of this study were:
• Phase 1 - to describe the process of identifying
and developing a Tablet computer programme
to capture data
• Phase 2 - a qualitative evaluation of the use of
Tablet computers to record data at a rural CHC

63. Mthakulo Community Health Centre

64. The use of Tablet computers to record patient health
data at a CHC, Mhlontlo District, Eastern Cape
Aim: To compare the work burden of data
collection using Tablet computers compared with
handwritten entries in registers.
Objectives:
• To measure before and after Tablet
implementation
• The time taken for recording patient data
required for the DHIS
• The time taken for other tasks in the consultation

67. Chrispin setting up the new equipment

68. Training the research assistants on the T&M system

69. Tablet Data Collection at CHC
Hypothesis
Tablets will reduce nurses recording workload at
CHC
Method
• Quantitative: Time & motion study
• Qualitative: nurses experience of using Tablets
patients experience of Tablets in CHC
Recording data over 2 months

71. TB Room Registers (Manual)
1. Tick register - every patient visit recorded
2. Tuberculosis Register (GW 20/11)- every patient
visit recorded
3. Transfer out Form (GW20/14)
4. HCT register
5. Suspect Register
6. Case Identification & Follow-up Register
7. Notification of Medical Conditions Form
8. IPT Register
9. Blood Collection Book (a local Facility record)

72. TB room – note the number of papers to write on

73. HIV COUNSELLING AND TESTING REGISTER
HIV Test Results
SEX
Service Attended
Accept Test
Screening Test
Confirmatory Test
ELISA
TB Screen
Results
IPT
PCR
1
2
3
4
5
6
7
8
9
10
TOTAL
Age
M
F
Med
Self
ANC TB
STI
Pos
Neg
Pos
Neg
Neg
CD4 Cell
Count
Staging
Prophy Mento
laxis
ux
Other
method
Pos
Neg Yes
No
Name( Last,First)
Pos
Code
Family
Planning
No
Date
Referral
Year:
Yes
Month:
Comments
Sinature

74. They have introduced new forms to make it easier for the Data Capturers

76. Time & Motion Study
• Compare time for writing in registers before &
after implementation
• Java application running on apple server into
MySQL database
• Non of available suitable either environment
or too nursing – not primary care focused

77. The lady with the Tablet is undertaking a T&M study – what nurses do….

80. Layout & Deployment of Technologies

81. iXhosa Women may have three + legal Surnames at any one time.
National ID numbers based on age – sex so many with the same number

87. OR Tambo - What’s next?
As we are an NHI pilot site, we have been given the licence to
try out new things. One of those things is the development of
a software system that has the following modules:
1. Client record management system
2. Electronic data collection system for Community Health
Workers
3. District Computerised Client record management module
4. Electronic patient Registry module
I have been asked to rapidly resolve this one, by the end of
this financial year

88. The objectives of the planned National Health Insurance (NHI)
1. Provide improved access to quality health services
for all South Africans irrespective of whether they
are employed or not;
2. Pool risks and funds so that equity and social
solidarity will be achieved through the creation of a
single fund;
3. Procure services on behalf of the entire population
and efficiently mobilise and control key financial
resources; and
4. Strengthen the under-resourced and strained public
sector so as to improve health systems performance.

89. To successfully implement these reforms, the NDOH is
focussing on four key interventions:
1. A complete transformation of healthcare service
provision and delivery;
2. The total overhaul of the entire healthcare system;
3. The radical change of administration and
management of healthcare; and
4. The provision of a comprehensive package of care
under-pinned by a re-engineered Primary Health
Care service.

92. The Alliance for Affordable Internet founded by BernersLee's World Wide Web has as its goal the bringing
affordable internet to 90 percent of the global population
that don't have access yet.

93. The group's mission is to bring entry-level broadband service
to Asia and Africa, and to ensure it is priced at less than 5
percent of the country's average monthly income.
At present, a basic fixed line broadband connection costs
around a third of monthly income to those in developing
countries, compared to an average of two percent in the UK
and US.
Berners-Lee said lowering the cost is crucial to getting users
in developing countries online, citing the fact that in
Mozambique, 1GB of data can cost "well over" two months
wages for the average citizen.

94. Today, the internet isn’t accessible for two
thirds of the world.
Imagine a world where it connects us all.
Mark Zuckerberg

95. Biomedical Informatics: We Are What We Publish
Summary
This article is part of a For-Discussion-Section of Methods of
Information in Medicine on “Biomedical Informatics: We Are What
We Publish” written by Peter L. Elkin, Steven H. Brown, and Graham
Wright. It is introduced by this editorial and followed by a
commentary paper with invited comments. 29 pages in all.
In their paper, P. Elkin et al. attempt to define the fields of Medical
Informatics and Bioinformatics through a bottom-up approach by
searching the medical literature. This innovative approach provides
interesting results that are discussed in the commentary paper. In
subsequent issues the discussion may continue through letters to
the editor.

96. Discussion of “Biomedical Informatics: We Are
What We Publish”
A. Geissbuhler1; W. E. Hammond2; A. Hasman3; R. Hussein4; R. Koppel5;
C. A. Kulikowski6; V. Maojo7; F. Martin-Sanchez8; P. W. Moorman9;
L. A. Moura10; F. G. B. de Quirós11; M. J. Schuemie12; B. Smith13; J. Talmon14
1 Department of Radiology and Medical Informatics, Geneva University, Geneva, Switzerland;
2 Duke Center for Health Informatics, Durham, North Carolina, USA;
3 Department of Medical Informatics, AMC-University of Amsterdam , Amsterdam, The Netherlands;
4 The Biomedical Informatics Center of Excellence, Information Technology Institute, Ministry of
Communications and Information Technology, Egypt;
5 Sociology Department and the School of Medicine, University of Pennsylvania , Philadelphia, USA;
6 Department of Computer Science, Rutgers – The State University of New Jersey, New Jersey, USA:
7 Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de
Madrid, Madrid, Spain;
8 Health and Biomedical Informatics Centre, The University of
Melbourne, Melbourne, Victoria, Australia;
9 Medical Informatics Department, Erasmus University Medical Center, Rotterdam, The Netherlands;
10 Assis Moura eHealth, Porto Alegre, Rio Grande do Sul, Brazil;
11 Department of Health Informatics, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina;
12 Janssen Research & Development, Titusville, New Jersey, USA;
13 Department of Philosophy, University at Buffalo, Buffalo, New York, USA;
14 Centre for Research Innovation, Support and Policy, Maastricht University, Maastricht, The
Netherlands

97. Mark Shuttleworth was born in Welkom, Free
State, South Africa - a son of a surgeon.
Shuttleworth on board the
International Space Station –
the first African in space.