This document analyzes human factors that predict failure and success in implementing hospital information systems in sub-Saharan Africa. It studied 19 implementation projects and identified 14 potential failure factors and 15 success factors through staff interviews and project evaluations. High predictive failure factors included resignation to poor quality, psychological issues, siloed culture, unrealistic timelines, poor training and support. High success predictive factors included clear communication, realistic timing, process changes, stakeholder agreement, and quick wins. The document concludes many commonly assumed factors like skills, incentives and consideration of current practices did not show predictive value.

1. Human Factors Predicting Failure and
Success in Hospital Information System
Implementations in sub-Saharan Africa
Frank Verbeke
Department of Medical Informatics
Vrije Universiteit Brussel
School of Public Health
University of Rwanda

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Introduction
 Hospital Information Systems (HIS)
implementation has gained momentum in
sub-Saharan Africa
 Experiences with OpenClinic GA from 19
hospitals in Rwanda, Burundi, DR Congo,
Congo-Brazzaville, Gabon and Mali
 Many succeeded, some failed
 Failure & success factors?

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Materials & methods
 19 HIS implementation projects analyzed
 Pre-implementation assets identification
 Classification
 Problem documentation in implementation logbooks
 Classification
 Forwarded solutions and work-arounds & results obtained
 297 health facility staff interviewed
 Iterate through all projects
 Score global project success (0 – 5 based on 6 questions)
 Score impact on the project of each identified asset & problem
(0 – 5)

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10 functional categories of risk
factors and facilitators
1. Infrastructure
2. Patient administration
3. Financial information management
4. Reason for encounter and diagnostic coding
5. Medical record management
6. Lab information management
7. Medical imaging
8. Reporting and statistics
9. Systems integration
10. Project management issues and human factors

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Human, cultural and environmental
factors
 14 potential failure & 15 success
factors
 Irrational
 Hard to solve
 Evaluation of predictive value?

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Predictive value of human
factors
 For each project
 Average of 14 asset item scores = project opportunity level
 Average of 15 problem item scores = project risk level
 Correlations
 between asset item scores & global project success score (prediction
of implementation success)
 between problem item scores & global project success score
(prediction of implementation failure)
 With p-value for the F-test on the regression with a confidence level
of 95%
 r < 0.6: low predictive value
 0.6 <= r < 0.75: moderate predictive value
 r >= 0.75 high predictive value

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Results: implementation failure
factors
 High predictive value
 Resignation to poor health
service quality
 Psychological factors
 Organizational culture and silo
mentality
 Unrealistic implementation time
frames
 Poor technical assistance
 Insufficient training
 Discontinued follow-up
 Perceived complexity
 Low measured user
satisfaction
 Moderate predictive
value
 Unclear goals
 Absence of a project
champion
 Resistance to change
and power shifts

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Results: implementation success
factors
 High predictive value
 Clear communication
 Realistic timing
 Business process
reengineering ability
 Stakeholder consenus
 Holistic approach
 Quick wins implementation
 Adequate technical assistance
 High user satisfaction
 Moderate predictive
value
 Broad staff enrollment
 Progressive change
management
 Sufficient and continued
training
 Perceived user
friendliness

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Risk level & opportunity level –
project success regressions

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Conclusions
 High predictive value of most of the forwarded
failure & success factors
 Surprisingly: low or no statistical evidence for
predictive value of the following factors:
 Insufficiently ICT skilled staff before implementation
 Incentives
 Availability of clinician & ICT-staff intermediaries
 Consideration of prevailing practice