understanding waste for lean health information systems: a preliminary review
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Understanding Waste for Lean Health Information Systems: A Preliminary Review. Nadia Awang Kalong & Maryati Mohd . Yusof Strategic Information Systems Group Centre for Software Technology & Management Faculty of Information Science & Technology Universiti Kebangsaan Malaysia. - PowerPoint PPT PresentationTRANSCRIPT
Understanding Waste for Lean Health Information Systems:
A Preliminary Review
Nadia Awang Kalong & Maryati Mohd. YusofNadia Awang Kalong & Maryati Mohd. Yusof
Strategic Information Systems GroupStrategic Information Systems GroupCentre for Software Technology & ManagementCentre for Software Technology & Management
Faculty of Information Science & Technology Faculty of Information Science & Technology Universiti Kebangsaan MalaysiaUniversiti Kebangsaan Malaysia
Outline
• Introduction• Waste • Method • Results• Discussion• Conclusion
Introduction
• Rising healthcare cost is due to service inefficiency that leads to huge medical errors
• HIS: enabler and barrier to service improvement• Need for holistic and systems thinking approach to
improve HIS effectiveness and efficiency Lean • identifying and eliminating waste
• Lack of waste understanding – barrier to applying Lean in supporting HIS improvement.
Introduction
• Limited Lean study in Health Information Systems (HIS) primarily in waste identification.
• Review the literature to provide an insight into the nature of waste in HIS from the perspective of Lean management.
Waste
• Refers to non-value added activity that exists in a process flow.
• Also defined as any item for which a customer refuses to pay.
• 7 categories of waste (manufacturing sector by Ohno): over-production, inventory, waiting, transportation, over-processing, motion and errors.
• No waste categories identified in studies in the HIS domain
Methods
• Electronic search: PubMed, Ebcohost, Science Direct, Scopus, ISI Web of Knowledge
• Search terms: Lean, waste, healthcare, informatics and information technology
• Key expert research, established textbooks, web search engines, and citation searching and chaining
Results
• Models that can be used directly to evaluate waste and enhance Lean transformation in HIS are limited.
• 8 research discussed waste models for the healthcare and IT domains– 4 in healthcare domain– 4 in IT domain
Results
• Waste in healthcare– Direct application– Define a new sub category – expensive input– Minor modification to Ohno’s; new category -
confusion• Waste in IT– Major modification; mapped new category with
Ohno’s– Identify irrelevancy and inconsistency to IT service
Results No. of
categoriesManufacturing Healthcare Information Technology
Ohno (1988) Bush (2007) Bentley et al. (2008)
Jimmerson (2009)
Berwick & Hackbarth (2012)
Poppendieck & Poppendieck
(2003)
Hicks (2007) Bell & Orzen (2010)
Kundu &Manohar (2011)
1 Transportation Transportation Inefficient processes
Motion/Conveyance
Handoffs Mass Electronic communication
Handoffs Transportation
2 Over-processing Processing Duplicate of services
Over-processing Relearning Failure demand Over-processing Over-processing
3 Over-production Over-production Over-production Over-treatment Extra features Flow excess Over-production
4 Inventory Stock on hand Inefficient processes
Inventory Partially done work Legacy databases and file archives
Inventory Inventory
5 Waiting Time on hand Inefficient processes
Waiting Delays Flow demand Waiting Waiting
6 Motion Movement Inefficient processes
Motion/
Conveyance
Task switching Gatekeepers/Single seat licenses
Unnecessary motion
Motion
7 Errors Making defective products
Errors Errors Defects Flawed flow Defects Errors
8 Expensive inputs Resource inefficiency
9 Confusion Failures in execution of care delivery
Processing inefficiency
10 Failures of care coordination
Lack of system discipline
11 Administrative complexity
12 Pricing failures
13 Fraud and abuse
14 Reinvention
15 External quality enforcement
16 Recurring incident
17 Ineffective communication
18 Over engineering
19 Environmental waste
20 Underutilized human potential
Discussion
• We reviewed 8 waste models in the context of the healthcare and IT domains.
• A total of 20 waste categories were summarized• 7 waste categories from the manufacturing sector exist
in both the healthcare and IT domains.• Most of the proposed additional categories were
actually covered in the existing Ohno’s model, except– Environmental waste
• Thus, the original waste model can be adapted to identify waste in both the healthcare and IT sectors.
Conclusion
• Waste understanding in the IS context could contribute to a successful Lean transformation and improve HIS, but
• Studies related to Lean waste identification in HIS are still limited, maybe due to
• The nature of waste in the IS context is not clear and visible, unlike in the manufacturing domain.
• Ohno’s waste model is suitable to be used as a guideline in understanding and identifying waste in both the healthcare and IT domains and subsequently for improving HIS.