Design-Reality Gap Analysis of a Failed Health Information System in a South African Public Hospital

Core Concepts

The failure of a Health Information System (HIS) in a South African public hospital highlights the critical need to address design-reality gaps, particularly in system capacity, IT risk management, and technical expertise, to ensure successful HIS implementation and improve healthcare delivery in resource-constrained settings.

Abstract

This research paper investigates the factors contributing to the failure of a Health Information System (HIS) in a public hospital in South Africa.

Bibliographic Information: Makumbani, H., & Tsibolane, P. (2024). Design-Reality Gap Analysis of Health Information Systems Failure. Procedia Computer Science, 00, 000–000. www.elsevier.com/locate/procedia

Research Objective: To identify the factors contributing to the failure of Health Information Systems (HIS) in South African public hospitals.

Methodology: The study employed a qualitative case study approach using semi-structured interviews with eight key stakeholders involved in the failed HIS implementation at the selected public hospital. The researchers used a hybrid data analysis approach combining deductive analysis based on the Design-Reality Gap Model and inductive thematic analysis.

Key Findings: The study identified several critical design-reality gaps contributing to the HIS failure:

• Information Dimension: Suboptimal data utilization and concerns about data quality, particularly due to manual data entry errors.
• Technology Dimension: Lack of clarity on the system's intended use, limited user involvement in the design phase, and inconsistencies in vulnerability scanning practices.
• Processes Dimension: System failure due to outdated infrastructure, reliance on manual workarounds, and lack of clarity on backup processes.
• Staffing and Skills Dimension: Significant shortage of advanced technical expertise, particularly in managing Linux-based systems.
• Management and Structure Dimension: Lack of accountability for system availability, absence of key risk indicators for IT risk management, and over-reliance on a centralized IT team.
• Other Resources Dimension: Insufficient budget allocation for system development and maintenance.

Main Conclusions: The study concludes that addressing design-reality gaps is crucial for improving HIS outcomes in public healthcare settings. The authors emphasize the need for:

• Investing in adequate IT infrastructure and technical expertise.
• Ensuring user involvement in all stages of HIS implementation.
• Implementing robust IT risk management practices.
• Allocating sufficient resources for system development and maintenance.

Significance: This research contributes to the understanding of HIS implementation challenges in developing countries and provides practical recommendations for policymakers and healthcare administrators to improve HIS success rates.

Limitations and Future Research: The study is limited to a single case study and may not be generalizable to other contexts. Future research could explore the role of government policies, vendor support, and user training in HIS success.

Stats

The data retrieved was only from 01st April 2017 until 11th November 2022.
Patient data dating back to system implementation in 1999 has been lost.
A total of 177,000 patients had to be manually captured in the new system.
80% of the patients have now been captured.

Quotes

"The HIS data was supposed to be used for decision-making by management. Unfortunately, the data is not being used as an asset."
"Clerks are not working 24/7, and the hospital is open 24/7, with patients coming in anytime...This compromises the data quality."
"The backup of the HIS was centralized to the provincial office in Johannesburg...The system was Linux based; the hospital has no skills to manage backups on the Linux environment."
"There are no key indicators to manage IT risks in the hospital.”
“Maintenance of system purely sat with the 3rd party as well as the central function managing HIS in the provincial government in Johannesburg.”

Key Insights Distilled From

Design-Reality Gap Analysis of Health Information Systems Failure

by Hanyani Maku... at arxiv.org 11-06-2024

https://arxiv.org/pdf/2411.03187.pdf

Deeper Inquiries

How can healthcare organizations leverage emerging technologies like artificial intelligence and blockchain to improve the resilience and effectiveness of HIS implementations?

Emerging technologies like artificial intelligence (AI) and blockchain hold immense potential to revolutionize Health Information Systems (HIS) and address the challenges highlighted in the case study. Here's how:
Artificial Intelligence (AI):

Predictive Maintenance: AI algorithms can analyze system logs and performance data to predict potential system failures. This allows for proactive maintenance, minimizing downtime and preventing disruptions like the one experienced by the South African hospital.
Data Quality Improvement: AI can be used to identify and rectify errors in patient data, such as inconsistencies in handwritten information. Machine learning models can learn from historical data to improve data accuracy and completeness.
Enhanced Decision Support: AI-powered clinical decision support systems can analyze patient data, identify potential risks, and suggest treatment options, aiding healthcare professionals in making more informed decisions.
Blockchain:

Enhanced Data Security and Privacy: Blockchain's decentralized and immutable nature makes it ideal for storing sensitive patient data. It can prevent unauthorized access and data breaches, addressing concerns raised by participants regarding data security and POPIA compliance.
Improved Interoperability: Blockchain can facilitate seamless data exchange between different healthcare providers and systems. This can address the challenge of fragmented data silos and improve care coordination.
Streamlined Supply Chain Management: Blockchain can track medical supplies and equipment throughout the supply chain, ensuring transparency and accountability. This can help prevent stockouts and ensure the authenticity of medical products.
Implementation Considerations:

Skills Gap: Healthcare organizations need to invest in training and upskilling their workforce to manage and maintain AI and blockchain-based systems.
Data Governance: Robust data governance frameworks are crucial to ensure responsible and ethical use of AI and blockchain in healthcare.
Integration Challenges: Integrating these technologies with existing HIS requires careful planning and execution to avoid interoperability issues.
By strategically leveraging AI and blockchain, healthcare organizations can enhance the resilience, security, and effectiveness of their HIS implementations, ultimately leading to improved patient care and operational efficiency.

Could the HIS failure be attributed to a lack of political will or insufficient funding prioritization for healthcare IT in South Africa, rather than solely focusing on design-reality gaps?

While the design-reality gap analysis provides valuable insights into the HIS failure, attributing it solely to those gaps risks overlooking the broader systemic issues within the South African healthcare system. A lack of political will and insufficient funding prioritization for healthcare IT likely played a significant role, exacerbating the challenges identified in the study.
Evidence from the Case Study:

Centralized IT Management: The reliance on a central team for HIS maintenance and backups, coupled with the lack of in-house expertise, suggests inadequate investment in building local capacity.
Outdated Infrastructure: The system's end-of-life status and reliance on unsupported technology point to a chronic underfunding of IT infrastructure upgrades.
Absence of Key Risk Indicators: The lack of IT risk management practices further highlights the low priority given to IT within the hospital's overall risk management strategy.
Broader Context:

Resource Constraints: South Africa's public healthcare system faces significant resource constraints, with competing demands for limited funding.
Historical Inequities: The legacy of apartheid continues to impact healthcare access and quality, with under-resourced public hospitals serving predominantly disadvantaged communities.
Political Priorities: Healthcare IT may not be a high political priority, leading to insufficient budget allocations and a lack of urgency in addressing systemic issues.
Conclusion:
The HIS failure is likely a symptom of broader systemic issues within the South African healthcare system. While addressing design-reality gaps is crucial, it's equally important to address the underlying political and funding challenges. Increased political will and prioritization of healthcare IT investments are essential to create a sustainable and resilient healthcare system.

What are the ethical implications of HIS failures, particularly concerning patient data loss and potential disruption of care, and how can these be mitigated in future implementations?

HIS failures, as illustrated in the case study, carry significant ethical implications, particularly regarding patient data loss and potential disruptions to care. These failures erode trust in the healthcare system and can have detrimental consequences for patients.
Ethical Implications:

Patient Data Loss: The loss of patient data, including medical history, treatment plans, and personal information, constitutes a severe breach of privacy and confidentiality. This can have long-term consequences for patients, potentially impacting future care decisions and insurance eligibility.
Disruption of Care: System downtime and the reliance on manual workarounds can lead to delays in treatment, medication errors, and misdiagnosis, jeopardizing patient safety and well-being.
Erosion of Trust: HIS failures erode public trust in the healthcare system's ability to safeguard sensitive information and provide reliable care. This can discourage individuals from seeking timely medical attention.
Mitigation Strategies:

Robust Data Backup and Recovery: Implementing redundant and secure data backup and recovery systems is paramount. This includes regular on-site and off-site backups, ensuring data can be restored swiftly and completely in case of system failures.
Enhanced Cybersecurity Measures: Investing in robust cybersecurity infrastructure and protocols is crucial to prevent data breaches and system outages. This includes firewalls, intrusion detection systems, and regular security audits.
Data Minimization and Access Control: Adhering to the principle of data minimization, collecting and storing only essential patient data, and implementing strict access controls can limit the impact of potential breaches.
Contingency Planning and Downtime Procedures: Developing comprehensive contingency plans and clear downtime procedures ensures continuity of care during system outages. This includes training staff on manual processes and communication protocols.
Transparency and Accountability: Fostering a culture of transparency and accountability is essential. This involves promptly informing patients about data breaches or system failures and outlining steps taken to mitigate harm.
Ethical Considerations in Future Implementations:

Prioritizing Patient Safety and Privacy: Ethical considerations should be at the forefront of all HIS implementations, prioritizing patient safety, privacy, and data security above all else.
Community Engagement and Trust-Building: Engaging with communities and addressing concerns about data privacy and system reliability can help build trust and encourage adoption.
Accountability and Oversight: Establishing clear lines of accountability and independent oversight mechanisms can ensure responsible and ethical HIS development and implementation.
By proactively addressing these ethical implications and implementing robust mitigation strategies, healthcare organizations can build more resilient, trustworthy, and patient-centered HIS, ultimately improving healthcare outcomes and strengthening the patient-provider relationship.