1. 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

2. Outline Introduction Waste Method Results Discussion Conclusion

3. 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.

4. 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.

5. 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

6. 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

7. 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

8. 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

9. Results No. of categories ManufacturingHealthcareInformation 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) 1Transportation Inefficient processes Motion/ Conveyance HandoffsMass Electronic communication HandoffsTransportation 2Over-processingProcessingDuplicate of services Over-processingRelearningFailure demandOver-processing 3Over-production Over-treatmentExtra featuresFlow excessOver-production 4InventoryStock on handInefficient processes InventoryPartially done workLegacy databases and file archives Inventory 5WaitingTime on handInefficient processes WaitingDelaysFlow demandWaiting 6MotionMovementInefficient processes Motion/ Conveyance Task switchingGatekeepers/ Single seat licenses Unnecessary motion Motion 7ErrorsMaking defective products Errors DefectsFlawed flowDefectsErrors 8Expensive inputsResource inefficiency 9ConfusionFailures in execution of care delivery Processing inefficiency 10Failures of care coordination Lack of system discipline 11Administrative complexity 12Pricing failures 13Fraud and abuse 14Reinvention 15External quality enforcement 16Recurring incident 17Ineffective communication 18Over engineering 19Environmental waste 20Underutilized human potential

10. 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.

11. 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.

12. 12 Thank You! Maryati M. Yusof mmy@ftsm.ukm.my