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February 09, 2010, MGH, Swaziland
Practical Approaches to development of patient safety
information systems
Chien-Tsai Liu, Professor Graduate Institute of Biomedical Informatics,
Taipei Medical University
The Conference on Patient Safety & Integrated Health Records
Patient safety definitions
Narrowly: the issues specifically related to adverse events and their prevention
Broadly: any aspect of healthcare and health services that may lead to patient injury, and any interventions, including clinical, organisational and policy changes that aim to reduce injury
Patient safety is now one of the most important issues in healthcare internationally through the initiative “World Alliance for Patient Safety” led by the World Health Organisation (Oct. 2004 )
Medical Errors Adverse Events
No harm events
Near Misses
Preventableevents
Sentinel Events
Negligence
A Venn diagram of Patient safety definitions
財團法人醫院評鑑暨醫療品質策進會 http://www.tjcha.org.tw/
Deaths associated with medical errors
5 elements for improving Patient safety
• A ‘just’ or ‘fair’ culture that encourages a reporting and questioning culture that is complemented by systems for reporting and analysing incidents both locally and nationally.
• A good in depth analysis process to establish root causes for selected individual incidents and aggregate incident reviews which enables learning.
• A process to ensure that actions are implemented, and corresponding improvements in patient safety and quality of care can be demonstrated.
• Effective processes for sharing information at various levels - nationally, organisationally and clinically - for learning and improvement.
• A redefinition of both punitive and non-punitive compensation systems in the healthcare environment, and an assessment of their impact on the patient safety culture and its achievements.
Major causes of medical errors & adverse events
Major causes of medical errors & adverse events
• Incomplete or missing informationMany adverse drug events could be avoided if
healthcare providers had more complete information about which drugs their patients are taking and why
Lack access to patients’ complete medical history.
• Organizational factorsDeficiencies in system design, organization and
operation, including an organization’s strategy, its quality management tools, and its capacity to learn and adapt
Main strategies for preventing medical errors and adverse events using IT
Tools to improve communication Making knowledge more readily accessible Assisting with calculations Performing checks in real time Assisting with systemic checking & monitoring Providing decision support
Bates and Gawande, NEJM 2003
IT in healthcare applications: a review
Decision Support Systems Computerized Physician Order Entry Adverse event systems & alert systems Electronic Medical Record (EMR) Incident reporting systems
ICT systems can lead to considerable benefits in patient safety only if they are user-friendly and fully integrated with other relevant systems.
HAI surveillance systems: an example
Hospital acquired infection (HAI) surveillance is a systematic, ongoing data collection, analysis and reporting process that quantitatively monitors temporal trends in the occurrence and distribution of susceptibility and resistance to antimicrobial agents, and provides information useful as a guide to medical practice, including therapeutics and disease control activities. .
A HAI surveillance system features: • Multiple systems involved• Integrated work & information flows;• Decision support; Monitoring & Alerts; Reporting
UTI Risk factors extracted from EMRs
Risk factors Description Sources from
fever fever (body temperature >38℃) CPOE + IMS
Urine/blood culture order
Urine/blood culture orders CPOE + LIS
Urine/blood culture result
positive urine/blood bacterial results LIS
urine routine examination
pyuria (urine specimen ≥10 white blood cell [WBC]/mm³ or ≥3 WBC/high power field of unspun urine)
LIS
antibiotic oral and injection antibiotics CPOE+ MMS
invasive devicesindwelling urinary catheter, cystoscopy, PCN, double J, cystofix
IMS
LIS : Laboratory information system; IMS: Inpatient management information System PMS: Medication management information system; CPOE: computerized provider order entry
Other EMRs
Interconnected secure networks
Msg delivery
Data collection & integration engine
HAI surveillance
database
Analysis, visualization &
presentation
Alerts & reporting management
Early detection of infected cases & clusters (DSS)
RIS(Radiology
images reports)
LIS(Culture orders & results)
IMS(patient
admission data )
CPOE(diagnosis &
orders)
NRS(care plan
&drug administration)
The framework of HAI surveillance system
Integrated patient profiles based on the CDC guidelines
Dashboard for summary of patients’ infection information
Refresh patients information
Selection of risk predictors
Red: positive/yes; green: negative/no
Click a specific patient to view his detailed admission data
Decision support: Algorithms for detection of suspected HAI cases
Discrimination functions demonstrate high sensitivity ( 99.25%) & Specificity ( 94.92 %)
the confirmed cases can be exported to the excel files for further analysis
The confirmed cases can be linked to CDC’s reporting system.
Summary
• IT systems in healthcare applications have shown the effectiveness in reducing the number of advent events, and improving practitioner performance.
• The systems also could introduce or facilitate new types of errors (information errors and human-machine interface flaws)
• Evidence-based evaluation methods for evaluating such safe systems are critical.
Summary (2)
• Evidence-based evaluation methods for evaluating such safe systems are critical.
Phase 1: a systematic review of the health informatics
literature involving technology-facilitated or technology-
induced error.
Phase 2: reviewing the literature and generating a
comprehensive heuristics that could be used to evaluate
an HIS for technology-induced errors.
Phase 3: conducting evaluation of the system using evidence-
based heuristics
Healthcare quarterly Vol. 12 Special issue 49-54: Ensuring the safety of health information systems: using heuristics for patient safety
