capacity strengthening and training needs assessment results survey results... · 2013. 3. 7. · 1...
TRANSCRIPT
1
Capacity Strengthening and Training
Needs Assessment Results
In order to identify key areas of needs a survey was designed for member centers. The purpose of this
survey was to elicit complementary information or specific details on capacity strengthening and
training priorities at member centers. The underlying goal is to enable the INDEPTH Network to
better target or to tailor capacity strengthening efforts to the pressing needs of members, and/or work
with them to further strengthen their capacities.
For the survey, a series of questions were asked ranging from identifying the specific areas that
centers currently need assistance to the main areas for capacity strengthening or training that they
think INDEPTH should support or should pursue in collaboration with member centers. In all, 32
centers (25 Africa, 7 Asia/Oceania) covering about 37 HDSSs attempted to complete the survey,
although a handful of the forms were not fully completed before submission. This notwithstanding,
the response level to this particular survey given the time was very impressive and clearly highlights
the importance of any form of capacity strengthening to member centers. Table 1 and Figure
1summarizes the broad areas where centers indicate they currently have pressing capacity
strengthening needs.
Table 1: Broad areas where centers require specific assistances and level of importance
Notes: The total number of member HDSSs that completed the survey is 33.
Priority areas for assistance Count Extremely
Important
Import
ant
Doesn't
Matter
Much
Deal
Breaker
Fieldwork/Data collection 8 4 8 4 1
Data management/quality 23 15 14 1 0
Scientific Research 25 17 8 1 1
Policy Dialogue* 14 8 10 1 1
Admin/Accounting* 4 0 4 4 1
Training 13 6 9 3 1
Others (specify): Funding 3 0 2 0 0
2
Clearly, there are two key broad areas where an overwhelming majority of centers are in pressing
need for assistance in terms of capacity strengthening: scientific research and data management
capabilities. These areas were also those that feature most among the priority areas rated by most
centers as extremely important. To some extend policy dialogue and training also seem to feature
among the needs of close to half of those who attempted the survey.
Figure 1: Broad areas of capacity strengthening needs
Specific details on the needs under each broad area
Further to identifying and ranking the broad areas where they need assistance, the center leaders
were requested to provide at list five specific details on their needs under each broad area. Some of
the answers were not so specific, though. As one would expect, the specifics under each broad area
varied considerably across the centers but somehow there are some specific areas of convergence or
areas that came up repeatedly. Under the respective broad areas, we try to underscore the specific
areas that were frequently mentioned across centers. The details by centre are presented in Tables 2-7.
0
4
8
12
16
20
24
28
3
Fieldwork/data collection
In relation to fieldwork and data collection need, the most commonly mentioned specific need is in
relation to electronic data capture (e.g. use of PDA, mobile of data collection, training in automotive
or data collection using electronic gadgets, etc.) The next area that came up several times was quality
assurance and QC or ensuring the quality of data collected and/or effective monitoring with limited
resources. Another closely related detail that was mentioned by several centers is capacity building
for interviewers and supervisors and the rational organization of data collection and/or migration
reconciliation. The more sporadic needs mentioned under this broad area include: linking HDSS with
HIS, Collecting of historical fertility and nuptiality data, understanding missing data from the field,
Verbal Autopsy-Open history (refresher) and collecting of individual, household and compounds
covariates time-dependent. The details by center are presented in Table 2.
Data management/quality
Data management as already noted is a major area of concern to most of the member HDSSs. Because
of the interconnection with the fieldwork and the data collection exercise, we notice that some of the
key specific needs mentioned under data collection also came up under data management. Indeed,
among these already mentioned specific needs that came up here is the electronic data capture systems
with more specifics like administering/managing complete electronic medical records systems and or
linking HDSS data with HIS. Another area that came up prominently in the answers is data quality
assurance and quality control checks or longitudinal data quality assessment. This came up in various forms
like need to reduce errors in data entry from data management, implementation of quality checks,
treatment of missing values, timely completeness, data verification methods and more importantly
evaluation of data in Demography.
One other specific need that came up could be summarize by data storage, handling, security, sharing
and ownership. One of the answers captures this as the need to apply the same data format across
centers (harmonization) where others simply mentioned the need to implement an effective method
of securing data, training in software for longitudinal data management, data management and
cleaning, funding for formalized data management training, standard procedure for data
management, expertise to manage large databases, extracting information from databases and
merging databases, etc.
As centers move from paper capture to electronic or paperless, the data management systems have to
be changed accordingly as older systems like FoxPro, HRS2 are becoming obsolete. So, consistent
with the growing specific need to implement the electronic data capture (PDA, mobile,…) is the
similarly large number of cases where answers like need for programming in SQL, migration from
FoxPro to SQL, training on the administration and database management using SQL server, data
mining and statistical analysis using SQL, data management built on MySQL and learning XML.
4
Table 2: Center Specific areas of assistance under Fieldwork/Data collection
Center Name
Specific areas related to fieldwork/data collection
1 2 3 4 5
ChiliLab
Quality assurance and QC
plan Training data collectors
Tools and technology
support
Dodowa Collecting data using PDA
FilaBavi questionnaire development
capacity building for
interviewers and
supervisors
keeping good
relationship with family
for long time
cross check between
interviewers and
supervisors information transferring
Gilgel Gibe
Kanchanaburi
different methods of data
collection
field work data quality
control
Kilite Awlaelo
use of PDA, mobile for data
collection
Nanoro Electronic data collection
Linking HDSS data with
HIS
Collecting of historical
fertility and nuptiality
data
Collecting of individual
covariates time-
dependent
Collecting of household
and compounds
covariates time-
dependent
Navrongo None
Nouna
Design electronic data
collection forms using PDA
Train fieldworkers in
electronic data collection
devices
Purworejo
Data collection using
electronic gadget
New method/ techniques
updated of DC system
Taabo
Have never done this activity
in the past so they need to
enhance their knowledge in
this area
Rational organization of
data collection
To better adapt our data
collection tools
To ensure the quality
of data collected
Learn from
experienced centers to
better meet future
challenges
Vadu
Effective Monitoring with
limited resources
Understanding missing data
from the field
West Kiang Automative Data Collection
Nahuche Migration Reconciliation VA - Open history
5
Table 3: Center Specific areas of assistance under Data management/quality
Center Name
Specific areas related to data management
1 2 3 4 5
Agincourt Data life cycle
Bandafassi, Mlomp & Niakhar quality indicators development improve databases
Bandim more funding for formalised data management training
ChiliLab Standard procedure for data management QA&QC plans
Supervision and training supervisors
Dabat Training on longitudinal data management
Training on Software for longitudinal data management
Training on Database management using SQL server
Training on Programming using ASP.NET and/or JAVA
Training on INTER-VA model software
Dikgale Manage the data base Identify mistakes in data collection
Extract information from data base
To merge a data base (Exel file) with Dikgale data base
Dodalab Data checking and cleaning How to apply the same format of data in all centres Causes of deaths (VA) Sharing data
Dodowa Programming in SQL Data management using SQL
Understanding and using Visual Basic
FilaBavi computer checking automaticly storage the data
quality insurance in each step
ownership of data set
Kanchanaburi longitudinal database management
database management programme
Kintampo Migration from foxpro to SQL
Mbita Data verification methods
Nanoro
Move from HRS2 to other system of data management build on MySQL
Integrate changing in individual covariate time-dependent in the data base
Integrate changing in individual covariate time-dependent in the data base
Linking HDSS data with HIS
Training of data management team
Navrongo
Expertise to manage and large database like the HDSS data
Ability to do basic statistical analysis
6
Center Name
Specific areas related to data management
1 2 3 4 5
Purworejo Handling data Supervision to quality control
Taabo
Capacity building in administration of SQL database server
We will use PD As very soon and we will need to know how to migrate SQL database in MySQL and also to learn XML language. This is a new experience for us
Reduce errors in data entry from data management
Ensure proper quality control of data
Implement an effective method of securing data
Vadu timely completeness
quality checks during cross checking on the field and at data entry
West Kiang Data Security
Administering/managing complete electronic medical records system
Nahuche Training in SQL Server Data mining & Stats analysis using SQL
Evaluation of data in Demography
Advance STATA programming
Long. Data quality assessment
Magu Additional manpower
Sarpone Electronic data capture systems CRF Designs
Quality checks implementation
PiH/Wosera Electronic data capture systems Data mgmt and cleaning
7
Table 3 shows the specific areas of assistance in data management for the respective centres. Aside
from the forgoing identified clusters of needs, the other needs that can be picked up from the answers
include: Causes of deaths (VA), and Training on INTER-VA model software, ability to do basic
statistical analysis, Advance STATA programming, integrating changing individual covariate time-
dependent into data base as well as Training on Programming using ASP.NET and/or JAVA.
Scientific Research (data analysis, scientific writing, publications)
As noted earlier, the scientific research needs seem to be the most pressing for almost all the centers
that responded to the survey. Though there were numerous answers, it is interesting that we can
easily reduce all the answers to a handful of specific needs namely: longitudinal data analysis (LDA)
or survival analysis which is core to the HDSS process, the art of scientific writing and routine report
writing, identifying appropriate publication channels or journals, skills in different research designs
and proposal writing, training in advanced statistical analysis and statistical software (such as
STATA, R, SAS, SPSS, EPI-INFO, NVIVO) with STATA and R coming up several times. Indeed, given
the workload of data collection, processing, quality control and management it does not come as a
surprise that many of the centers seem to be having hard times managing the art of scientific writing
and publication in high impact journals in combination with the production of technical progress
reports on the different projects (see Table 4 for specific details by centre).
Policy Dialogue/communication and/or dissemination
In the area of policy dialogue and communication, one of the main current needs relates to the
production of newsletters, prepare oral presentation and how to write policy briefs or what might be
termed strategic packaging of research findings. In short they are concern with acquisition of good
communication skills and how to decide what results are interesting to disseminate and by what
channel. The second specific need here relates to effective communication and policy dialogue which
come up in various forms including broad answers and specifics alike: policy
dialogue/communication strategy, engaging policy makers, working with press and media to convey
research results, communication with district health office, establish a communication policy for
lobbying the HDSS, develop a policy dialogue for a good advocacy with authorities, which tools must
be used (policy briefs, etc.), how to prepare the tools?, communicating scientific results to
international and local audience, etc. Lastly, there is reference to communicating results to the
community and creating local communication cells within the HDSS (see Table 5).
8
Table 4: Center Specific areas of assistance under Scientific Research
Center Name
Specific areas related to scientific research
1 2 3 4 5
Agincourt Advanced statistical analysis
Ballabgarh
Bandafassi, Mlomp & Niakhar routine data analysis routine report writing
ChiliLab Desiging good research/study
Skills in intervention study
design and data analysis
Publication support and
follow up improvement
Skills in data
management and
analysis
longitudinal
studies
Dabat Training on STATA, SAS
Training on Longitudinal
data analysis
Training on Manuscript
writing
Training on
Qualitative data
management,
analysis and
write up
Dodalab Longitudinal data analysis
How to write a successful
paper
Dodowa Longitudinal Data analysis
Writing scientific publication
using HDSS data
FilaBavi data analysis scientific writing
find relevant journal to
submit papers
Kanchanaburi longitudinal data analysis
scientific writing and
publications
Karonga Stata workshops Paper writing workshops
Kilite Awlaelo Longitudinal data analysis survival analysis cluster analysis
Analysis of GIS
data
Kintampo
Longitudinal analysis of DSS
data
Mbita Methods of data analysis
Scientific paper writing and
publication
Nanoro working group
9
Center Name
Specific areas related to scientific research
1 2 3 4 5
Navrongo
Ability to do basic data and
statistical analysis
Ability to draft and complete
a manuscript
Nouna
skills in data analysis software
such STATA , EPI INFO,
NVIVO, R
Conduct a successful
scientific writing skills in proposal writing
skills in
publication
targeting high
impact journals
Skills in mortality data
analysis
Ouagadougou scientific writing how to choose the journal?
Purworejo
Updated data management
system Scientific writing
How to publice the paper
for young researcher
Taabo
To be able to draft a research
protocol
Advanced data analysis
(multivariate analysis,
retrospective analysis,
multivariate analysis,
spatial analysis) to fully
exploit the longitudinal data
Know the steps of
scientific writing to
valorize Taabo HDSS
data
Become familiar
with the basic
concepts of a
publication
How to organize and to
manage research
activities within the
HDSS
Vadu Use of open source software
writing skills improvement
of junior staffs
West Kiang Stata
Nahuche LDA Research design Art of scientific writing
Technical paper
on data
cleaning/mgmt
Magu
Additional manpower
(statistician)
Sarpone
Data analysis-stats training on
stata/r/spss Scientific writing
scientific communication
skills
PiH/Wosera
Data analysis-stats training on
stata/r/spss Report writing
10
Table 5: Center Specific areas of assistance under Policy dialogue and communication
Center Name
Specific areas related to policy dialogue
1 2 3 4 5
Bandafassi, Mlomp & Niakhar production of newsletters participative management
Bandim
get people to listen to
something they do not want to
hear
get the system to accept a
critique
Dikgale
To assists with informing Dept
of Health of our results
important for policy
Ifakara Engaging policy makers
Translation of research
findings to policy/action
Strategic packaging of
research findings
Effective
communication Negotiating capital
Nouna
acquiring good
communication skills how to write a policy briefs
communicate scientific
results to international and
local audience
Tips in
disseminating
research findings
Ouagadougou
what result is interesting to
disseminate by which channel?
Which tools must be used?
(policy briefs, etc.)
How to prepare
the tools?
Taabo
Establish a communication
policy for lobbying the HDSS
How to publish the results
to community
Develop a policy dialogue
for a good advocacy with
authorities
Create a local
communication
cell within the
HDSS
Improve and ensure
the HDSS better
management
West Kiang
Dialogue with national health
service and bureau of
statistics to turn the
forthcoming national census
into a national HDSS
Magu Writing policy briefs
Sarpone Writing policy briefs
Comm skills for policy
dialogue
Translating research data
into valuable health info
11
Table 6: Center Specific areas of assistance under Administration/accounting
Center Name
Areas related to administration and accounting
1 2 3 4 5
Bandim more funding for administration
project specific planning and
accounting
Nouna skills in conducting projects audits
skills in using accounting software
such as TOMPRO, SAGE
skills in project financial
reporting
Purworejo How to manage funding effectively Documentation Lack of Funding
Vadu
Timely response to requests from
researchers timely response to funder queries
monitoring all spending and
ensuring to keep within
available limits of the budget
Table 7: Center Specific areas of assistance under Training & others
Center Name
Areas related to Training
1 2 3 4 5
Bandim
funding to promise training
grants time training in English
ChiliLab Training for data managers
Training for young
scientists Data analysis
Dissemination of
scientific
outcomes
Dodalab
Master program on
demography and
epidemiology
Short courses on
longitudinal data
management and analysis PhD training
Dodowa GIS,
FilaBavi
material development to use
data for training
supervisor for research
students
Kanchanaburi data analysis data management
Karonga
Opportunities for internships,
scholarships Analysis skills (see above)
Kintampo
Demography at MSc and PhD
levels
12
Center Name
Areas related to Training
1 2 3 4 5
Mbita Biostatistics and Epidemiology
Nanoro
data management oriented
analysis
for French people, linguistic
ilmmersion for their staff
Nouna Basic biostatistics training
training in good clinical
practice and good
laboratory practics
Training in ethic of
research
training of junior
research in
English skills
Training in InterVA
Betha final version
Purworejo
Data collection using
electronic gadget Data management Data analysis Lack of funding
Taabo
How to assess the health
needs of individual
communities
Plan appropriate
interventions
Evaluate policies and
programs or health
services that promote
and sustain a healthy
environment, healthy
living for individuals and
for populations
Analyze and
propose solutions
to public health
problems
Coordinate data
collection procedures,
lead studies and
critically interpret the
results of statistical
analysis while ensuring
the development of the
presentation of the
results these analyses
to the public and to
health professionals
Vadu
quality data collection on the
field
West Kiang Statistics Demography
Sarpone How to talk to funders
How to develop a business
plan
13
Administration/accounting
As noted previously, this area does not seem to be much of an issue to many but the few issues that
came up are related to funding and the effective management of funds to ensure that they within
budget limits, training in major accounting software as well as gaining insights/skills in project
financial reporting and project audits. This apparently will ensure timely response to requests from
researchers and to funders’ queries. Interestingly here there was sporadic allusion to the development
and maintaining of a web site as well as the role/relationships with affiliated institution (Table 6).
Training
Training is one of the areas that centers are continuously grappling with. In response to this question
of the leader clearly underscore this persistent need in the following terms. We always need additional
training for our junior level staff. As with many HDSSs we are quite remote from other institutions where
training can take place. The senior staff who provide this training and mentorship have many commitments. In
terms of the specifics, reference was commonly made to training on data analysis, data management
oriented analysis, electronic data collection and quality control. This may mainly refer to short
courses though only one case mentioned explicitly short courses on longitudinal data management
and analysis. There is also the express need for training in ethics of research, good clinical practice
(GCP) and good laboratory practices. Indeed, training of data managers and young scientists is
underscored. With respect to long term training and the priority fields of studies: Masters and PhD
training was cited and the main fields that came up include demography and epidemiology, basic
biostatistics or biostatistics and epidemiology, biostatistics and information sciences, statistics and GIS
(see details in Table 7).
Opportunities for internships and mentorship (supervisor for research students), funding to promise
or offer training grants were also mentioned. Meanwhile training in English is obviously a need
among the member HDSSs in non-English speaking countries.
Challenges to capacity strengthening and training and strategies adopted to overcome
Regarding the major challenges to capacity strengthening efforts of the various member HDSS,
funding was the most commonly mentioned by most of the centers. Staff retention, overload and lack
of qualified though commonly accepted was only mentioned by a third of those who mentioned
funding as an issue. A few other challenges that came up include: the absence of a demographer, lack
of clear career path for each worker, lack of qualified staff in use of SQL while the limited linkage
with institutions which provide capacity building, like for short term training, PhD training was also
alluded to.
14
Figure 2: Key challenges to capacity strengthening efforts
The strategies adopted to address these challenges depend on the nature of the challenge mention. To
the perennial challenge of funding centers indicate active search for funding to support the HDSS
either from the parent university (for those affiliated with universities), requesting government
assistance via the national network, seeking external funding as well as developing research
proposals and actively responding to calls for proposals and consultancy. In addition, some centers
do implement a strategy of setting aside 20% of each project to cover data collection costs or charging
other projects that are nested into the HDSS.
Regarding the staff related challenges, center indicated the use of varied incentives to attract and/or
retain qualified staff. Indeed, most of the strategies are more or less consistent with the effort to
enhance the capabilities of the staff. Sending staff for training, applying for scholarships, working
with other HDSS sites in the country, using local experts and training of staff by experts from other
centres (cross-sites within INDEPTH), attending INDEPTH workshops, liaising to create link with
universities abroad, internal workshops and providing various training opportunities, support to
attend conferences as well as paying competitive salaries are among the strategies implemented by
the centers to overcome the challenges identified.
0
5
10
15
20
25
Funding staff retention No qualified
persons
Staff overload Others
15
Main areas of capacity strengthening and training for INDEPTH support
Given the tall list of specific areas that were likely to crop …The survey requested the centers to
provide a list up to five of their key areas of capacity strengthening that INDEPTH should possibly
support. In all 22 of the 33 centres that attempted the survey provided at least an answer to this
question. Among the tall list that came up, the most prominent areas include longitudinal data
management and analysis methods, data verification methods and data quality control, SQL training,
scientific writing and publications, routine report production and proposal development. Training
workshops and training grants/support in various areas including data management, demography,
biostatistics and information sciences as well as a course in demographic surveillance are some of the
main areas for training that INDEPTH should possibly support as indicated by the centres. Of course,
funding, fund raising and financial management also featured among the proposed activities (see
details in Table 8).
Potential areas of collaboration that INDEPTH can pursue
A follow up question require the centres to suggest potential areas of collaboration that INDEPTH can
develop with them respectively. A total of 21 centres mentioned at least an area. Among the potential
areas mentioned are the following: organizing INDEPTH trainings and workshops, on the job
trainings and sandwich programmes, data management and analysis, cause of death analysis using
interVA, joint research and publications, funding and financial support. More importantly, a
considerably long list of areas for collaborative studies came up some of which already appear on
INDEPTH’s scientific agenda while others seems new. These areas to be considered include: studies
on chronic diseases, NCD, clustering of adult mortality, maternal and child health, GIS and health
indicators, parasitology, vaccine trials of INDEPTH interests, health impact assessment,
environmental health, epidemiological studies, social economic status, social gerontology, monitoring
and evaluation research, antibiotic use and resistance, universal health coverage as well as migration
and health. Table 9 shows the details on potential areas by centre.
On the strategy frequently adopted by INDEPTH for training held by the Secretariat in Accra of
counting on the best available international faculty to facilitate, most of those who responded to this
question agree that this is a good initiative, reliable and fantastic idea that allows for well organized-
and experienced trainers. However, it is also recommended to provide opportunities to sites in the
INDEPTH network to play roles in the training activity and to involve more scientists from HDSSs.
Other members caution that though it is a good strategy, this may make INDEPTH too dependent on
that faculty and that it will be better to have more than one faculty to facilitate specific issues. In short
HDSS members should be involved if the skills needed are there. Yet another thought that this
strategy is acceptable but would prefer to invite international faculty from ONLY the HDSS centers.
Note worthy was the suggestion for regional workshops on grounds that this would be very useful to
decrease travel time. Indeed, this is an idea that INDEPTH has debated on for a while the cost factor.
Furthermore, members would definitely prefer practical trainings, not theoretical ones.
16
There is more or less general consensus that center to center (mentorship) support is a fantastic idea,
Centres are strongly in support of this and are consequently willing to release their staff to assist
others. Indeed, some members stated that this is a priority and that this is one of the positive points of
the Network to get mutual assistance which is helpful in better use of available strengths within
network. In terms of reasonable duration for release of staff this ranged from about one week per staff
to a maximum of about two months per year.
17
Table 8: Tabular summary of main areas for INDEPTH Support
Center Name
Main areas for INDEPTH Support
1 2 3 4 5
Bandafassi, Mlomp & Niakhar data management
data analysis (fertility,
migration, nuptiality) routine report production
Bandim training grants English training data manger training
Dabat
training on longitudinal data
management and analysis
training on database
management using SQL server
training on manuscript
writing
Training on
ASP.NET and/or
JAVA
interview and field
supervision skill
Dikgale
To allocate a person to train
staff in data management and analysis
DodaLab
Longitudinal data
management and analysis Causes of deaths Data sharing
Dodowa SQL GIS
Kanchanaburi data analysis data management
Karonga
Training workshops (on site
would be very good)
Kilite Awlaelo Data Analysis data base-HRS2 or HRS3
Kintampo training in demography SQL training
data analysis
(longitudinal) publications
Mbita Data analysis methods Data verification methods
Nanoro Data analysis Electronic data capture system
Modeling of population,
environment parameters
and diseases
Navrongo data management scientific writing Financial management
Nouna
Support junior researcher for
Master degree training
Support training in data
analysis using basics statistical
software
Support training in
scientific writing and
proposal writing
support training
in data
dissemination
and publication
Ouagadougou data quality control scientific writing publications
Purworejo Funding Updated methodology Course in demographic Research
18
Center Name
Main areas for INDEPTH Support
1 2 3 4 5
surveillance proposal writing
Taabo
Scientific Research (data
analysis, scientific writing,
publications)
Public health: biostatistics and
information sciences
Data
management/quality
Fieldwork/Data
collection
Policy Dialogue,
communication
and/or dissemination
Vadu
paper writing and proposal
writing data collection using technology
Nahuche Longitudinal data analysis Scientific writing
Proposal development
and writing
Magu
data analysis techniques for
quantitative
data analysis techniques for
qualitative data data archiving
making photo
identity card for
HDSS members
Sarpone Data Management Policy Dialogue Fund raising
PiH/Wosera
ISHARE project will continue
to provide a training platform
to the participating sites,
please continue
Certificate or Degree training
(with Wit or I2IT) for the data
management staff
Human resource
management training
19
Table 9: Tabular summary of Potential areas for collaboration
Center Name
Potential areas for INDEPTH Collaboration
1 2 3 4 5
Bandafassi, Mlomp & Niakhar workshops
Bandim you tell me
Dabat Training, field epi Joint publication Financial support
Hosting our own
web-site joint research
Dikgale Studies on chronic diseases
DodaLab NCD Maternal and child health
Inequity in health care
seeking behaviour
Universal health
coverage
Antibiotics use and
resistance
Dodowa Clustering of adult mortality GIS and Health indicators
Health Impact
assessment
Kanchanaburi social gerontology migration and health
monitoring and
evaluation research
Kilite Awlaelo
Creating partnership
opportunities
Kintampo data analysis publications data management
Mbita Maternal and Child health Parasitology Environmental Health
Social economic
status
Nanoro
Training in good clinical
practices
Navrongo
On the job training and
sandwich programmes
Nouna
Pursue collaboration in cause
of death analysis using
InterVA
Pursue collaboration in use of
electronic devices for HDSS
data collection
Strengthen researchers
capacities in data
analysis
Use the HDSS
platform for
health
intervention
effectiveness
assessment
20
Center Name
Potential areas for INDEPTH Collaboration
1 2 3 4 5
Ouagadougou publications funding
Purworejo Research Training
Taabo Monitoring Evaluation Sharing of experiences
Vadu
organizing INDEPTH trainings
and workshops
Vaccine trials of INDEPTH
interests Epidemiological studies
Nahuche
Investing in training of our
staff to support the budding
HDSS sites in the northern
part
Research that seeks
interventions to reduce the
exceedingly high maternal
mortality
Magu
Starting disability interest
group
Sarpone Clinical trials at any Phase
Training (GCLP, Molecular
biology, Parasitology,
Immunology of malaria)
Neglected Tropical
Diseases
PiH/Wosera NCD survey iSHARE Nutrition study
21
Appendix A: Selections of Specific needs within the broad areas
Broad area Selected key specific needs
Fieldwork/Data collection • Use of PDA, mobile and/electronic gadget for data collection, designing the
necessary forms, etc
• Ensuring the quality of data collected: Quality assurance and QC plan: field
work data quality control
• Capacity building for interviewers and supervisors and rational organization of
data collection, migration reconciliation
• Linking HDSS data with HIS
• VA - Open history refresher
• Collecting of historical fertility and nuptiality data
• Collecting of individual covariates time-dependent
• Collecting of household and compounds covariates time-dependent
• Learn from experienced centers to better meet future challenges
Data management/quality
• Electronic data capture systems including managing complete electronic
medical records system and/or linking HDSS data with HIS
• Data life cycle: handling, storage of data, sharing data, ownership of data and
how to implement an effective method of securing data
• Longitudinal data quality assessment/ Evaluation of data in Demography
• Capacity building in administration of SQL database server
• Training on longitudinal data management
• longitudinal database management
• Expertise to manage and large database like the HDSS data
• how to migrate SQL database in MySQL and also to learn XML language
• database management programme
• Ability to do basic statistical analysis
• Causes of deaths (VA)
• Training on Programming using ASP.NET and/or JAVA
• Training on INTER-VA model software
• Quality checks during cross checking on the field and at data entry
• Understanding and using Visual Basic
Scientific Research (data
analysis, scientific writing,
publications)
• Longitudinal data analysis, Survival analysis
• Scientific paper writing and publication, Cluster analysis
• Find relevant journal to submit papers
• Analysis of GIS data
• Methods of data analysis
• Use of open source software
• Writing scientific publication using HDSS data
• Writing skills improvement of junior staffs
• routine data analysis
• Training on Manuscript writing
22
Policy
Dialogue/communication
and/or dissemination
• To assists with informing Dept of Health of our results important for policy
• Engaging policy makers
• Translation of research findings to policy/action
• Develop a policy dialogue for a good advocacy with authorities
• Prepare oral presentation
• Communication of study results to the community as part of dissemination
Administration/accounting • Timely response to requests from researchers
• skills in conducting projects audits
• Standard structure of the center
• How to manage funding effectively
• skills in using accounting software such as TOMPRO, SAGE
• The role and relationship with affiliated institution
• Develop and maintain web site
• Timely response to funder queries
• Computer accounting
• Monitoring all spending and ensuring to keep within available limits of the
budget
Training • Material development to use data for training
• Statistics
• Supervisor for research students
• quality data collection on the field
• Biostatistics and Epidemiology
• GIS and Demography
• Training for data managers
• Demography at MSc and PhD levels
• Basic biostatistics training
• training in good clinical practice and good laboratory practices
• for French people, linguistic immersion for their staff
• Dissemination of scientific outcomes
• Training in InterVA version
Others • Lack of funding
• How to assess the health needs of individual communities
• Plan appropriate interventions
• Evaluate policies and programs or health services that promote and sustain a
healthy environment, healthy living for individuals and for populations
• Analyze and propose solutions to public health problems
• Coordinate data collection procedures, lead studies and critically interpret the
results of statistical analysis while ensuring the development of the
presentation of the results to the public and to health professionals
• How to talk to funders
• How to develop a business plan
23
Appendix B: Review by Tim Evans (to be incorporated into the draft report)
1) In terms of the survey design it will be good if you can be clear as to the logic informing the design. Is there
an underlying framework that identifies what the "capacities" or "competencies" of INDEPTH sites should be?
Do the questions cover the full spectrum of these expected competencies?
The capacities or competencies of the INDEPTH members have been shifting with changes in the
landscape of world research and as they gain experience over time. There is a no clear underlying
framework that outlines exactly what the competencies of an INDEPTH member should be. But it is
normally expected that they should be able to collect good quality data on the major population
dynamics of the defined populations they cover, process and provide core data for INDEPTHStats as
well as analyze and publish scientific papers. Though not in exact details, our questions in the survey
effectively covered the broad spectrum of their expected/anticipated areas of competencies. In
addition, we left the questions sufficiently open in the hope of capturing all their needs and
constraints
2) I raise this issue, because the first set of results Table 1 identify data management and scientific research as
the key constraints in contrast to say data collection and training.
Regarding the results presented in Table 1, these are simple counts of the HDSSs (or leaders) who
mentioned that a particular area is where the HDSS has some critical needs for assistance. These
results where data management and scientific research received the highest hits (hence identifying
these areas as where most HDSSs have needs) is simply a reflection of the fact that most of these
HDSSs have been involved in data collection for such a long time that they no longer see data
collection and/or fieldwork as an issue. In fact, even considering the number of rounds they do per
year, it will be surprising if they will need assistance (aside from funding). Furthermore, the results
are consistent with what we observed from the INDEPTH member survey that was previously
completed by 41 HDSSs. Based on this member survey, the 41 HDSSs as at 2011 had a total of 64
statisticians and 78 demographers (masters and PhDs level). Some of them as noted in the current
needs assessment survey do not even have a demographer. When we looked at data managers, the 41
HDSSs in question had a total of 66, alongside 57 database administrators and 52 software developers
(for a total of 173). If we compare the latter figures to the data entry staff (270) and fieldworkers/field
supervisors (1271), it is just logical that the main constraints for most of these HDSSs would emerge at
the data management level. Of course, there are a few who may be having serious challenges with the
field operations. But as noted in the current survey, we believe that the eventual introduction of
electronic data capture will minimize the problems even at the data management level.
3) Regarding training -- this seems a bit fuzzy...as it is so intimately linked to capacity building. Is the
expectation that each DSS should have a training function i.e. a capacity for training? Is the intent of the
question then to assess whether the DSS sites feel they have this capacity for training? OR is the question
24
asking if the sites have unmet needs for training? I get the sense it is the latter and if so, it seems to be a bit
redundant with respect to the inventory of topical areas for training i.e. collection, management, etc..
The expectation is that most, if not all HDSSs should be able to initiate and support some form of
training. However, the question was intended to assess the types of training needs that they had and
whether these are really pressing needs relative to those in the other areas. As you rightly put it we
were asking them whether they had unmet needs for training.
4) I'm wondering if the survey has asked if there are things that have worked or not worked related to building
individual capacities of staff (mentoring, sandwich PhDs, internships, fellowships, career development awards,
etc) and/or institutional capacities (managing DSS data entry systems efficiently; grants management; HR
management to promote retention and careers of staff; sustainable financing)?
This is an important question that we missed in the survey! We need to go back to those who
responded with this question on the things that worked or did not work in their efforts to build
individual capacities of staff. We asked a related question though, on the major challenges to their
capacity strengthening and training efforts. The most commonly cited challenges relates to funding
and staff retention of those trained. These come up frequently even during discussions with various
members. We will definitely follow up with the question on things that have worked or not worked.
5) I think it would be interesting to get some insights on what has been attempted at the individual site level vs
across the INDEPTH network in terms of capacity strengthening -- has capacity strengthening been left largely
to individual sites? or has the Network fostered capacity strengthening efforts and if so how effective have they
been.
In general both INDEPTH and the individual sites are actively involved in capacity strengthening at
different levels. The beneficiaries of INDEPTH efforts differ across the Network, though.