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Safety II
- 1. Safety II maximising success in healthcare
- 2. Me
- 4. #peskyhumans
- 6. Hollnagel
- 7. World Change
- 10. Healthcare change Organisation for Economic Co-operation and Development (2010), “OECD Health Data”, OECD Health Statistics (database). doi: 10.1787/data-00350-en (Accessed on 14 February 2011).
- 11. Technology
- 12. Changes in emphasis slide
- 16. Safety I : impact on focus
- 17. Safety : Find and fix
- 19. Linear relationships Malfunction Failure Function Success X
- 20. Safety I: outcome grid Good outcome Bad outcome Proper function ? Malfunction ?
- 21. Underfunding Lack of cot rails Poor leadership Poor morale High sickness rate Understaffed ward Hospital at capacity No observable beds Patient in side room Patient unobserved Budget overspend Urinary tract infection Delirium Dehydration Equipment Patient Staff Environment Fall Safety I aetiology
- 22. 0 2 7 days since a CRBSI on this ward
- 25. Changing Demand
- 27. Why do things work?
- 28. WAI vs WAD
- 30. Effect of variability Malfunction Failure Function Success Performance adaptation
- 34. That Graph Ability / Competence / Capacity / Function Interactions
- 35. That Graph Ability / Competence / Capacity / Function ✝ ✝✝ ✝ ✝ ✝ ✝ ✝ ✝ ︎︎ ︎ ✝
- 36. That Graph Ability / Competence / Capacity / Function ✝✝ ✝ ✝ ✝ ✝ ✝ ✝ ⭐︎ ⭐︎ ⭐︎ ⭐︎ ⭐︎ ⭐︎ ⭐︎ ⭐︎ ⭐︎ ⭐︎ ⭐︎ ⭐︎ ✝ ✝
- 37. ✝
- 38. Look at what goes right
- 41. Focus on frequent events
- 42. Remain vigilant
- 43. Invest in Safety
Editor's Notes
- Supporter of “safety” as a concept. Sidelined by the Patient Safety ‘movement’ in Scotland – parachuting / evangelistic / rigid / emphasising system Skeptical of SAER / CI “analysis” as a tool for change Believer in the brilliance of humans Optimistic about the potential to make improvements to behaviour
- Dismayed by the relentless focus on humans as the cause of disasters.
- If we could design out the humans (particularly in IT”solutions”) it would all be OK
- Started to have thoughts about turning this around. My “deal with this” file… Badness being easy to see, expectation of good outcomes, emphasis on “badness” in our safety provision, no emphasis on “heroic saves”, or thinking outside the box, and constraints placed on healthcare professionals by the ever increasing algorithmification of medicine. Lack of a cohesive “whole”
- Heard Erik Hollnagel speak last year. He is a Danish professor of Psychology, and published widely on safety and resilience engineering… Road to Damascus moment He put language and structure around my thoughts … this presentation is almost entirley based on my reading and understanding of his work
- Changed world – my lifetime Perhaps most in the way in which we exchange information Faster, wider, more interactive, smaller “signal to noise” Individual “broadcasting” in social media Less A-B and more one to many Connectedness Interdependence
- My twittter reach…
- Healthcare has changed too Less transmissible disease, (this is polio) and more non transmissible (IHD, obesity, diabetes, cancer) More multi-morbidity Increasing demand from healthcare users
- Relentless, unsustainable increase in healthcare spending
- Largely due to routine application of complex technologies and treatments – which were experimental 20 years ago. And application in more circumstances, in sicker patient groups, with acceptance of smaller benefits per intervention Technologies changing daily – more knowledge every year than we knew in total 20 years ago Response to fallible tech, or performance demands
- Attempts to algorithmify medicine are staggeringly complex
- Changes also in how we look at performance of healthcare Adverse event seem as inevitable cost of “progress” to being avoidable, and subsequently unacceptable – the so-called “never-event” Rise ot the Heathcare safety “industry” Reduce errors by 50% in 5 years
- Adaptation of models of incident causation developed for mechano-technical industries and based in the Scientific Management Theory Linear cause and effect models (domino effect, swiss cheese model) Relentless seeking of Root Causes in incidents and erecting barriers and defences against adverse events Misapplication to complex socia-technical systems such as healthcare, where the linear relationship between causation and outcome is usually much less clear. Key in these approaches is that the healthcare professional is a fallible element
- We need to look at how safety is defined in this initial (called “Safety I”) approach. Absence of bad things. WHO “prevention of errors and adverse events” Exemplified by “Make sure that this never happens again”
- Starting point in Safety I is identifying things that go badly. These are, largely, outweighed by the things that go well, even in healthcare Relentless focus on failure and the causes of failure Taxonomy of causes of failure invented to describe them “ workload, staffing, dependency, omission/commission/ unsafe culture Generation of huge databases of failures
- Resulted in the “seek and destroy”, or “find and fix” approach to healthcare safety, which has had limited effect on outcome over the last 20 years Implicit assumption of the linearity of cause and effect, limited applicability of solutions No explanation of the persistence of deficiencies within healthcare systems Explosion of regulators requiring reports on the causes of incidents, and setting targets for the reduction of incidents, and a “Duty of Candour” to “own up” when the outcome is poor (note – not when the process was flawed) Ongoing media interest in disasters fans the fire.
- This is difficult Not condoning poor care. At all. But… No-one set out to make these things happen. Basildon hospital did hundreds of hip replacements that year, thousands of patients had uncomplicated surgery in Wales, many pensioners didn’t fall over in Tyneside, and thousands of children (thankfully) were born without complication in the Royal Sussex.
- The problem is the assumption bad outcomes and good outcomes happen in different ways. Noticing that something has gone wrong leads us to label a cause, and act to eliminate that cause The alternative is to act to constrain practice in the expectation that it will not malfunction
- Problem of defining the “goodness” process by its outcome. Managers / regulators / guideline writers / governments are remote from “work as done” – the way that things actually happen most of the time Unintended consequences of changes to systems
- So to summarise some of the challenges posed by a Safety 1 approach: Firstly, safety is manifest by the absence of bad things – or rather, a system in unsafe if bad things happen, or the risk of bad things happening is perceived to be high. It can therefore only me measured in retospect. There is a vast taxonomy to describe things going wrong – decribing errors and failures, and a “science” around failure Perversely, if there are few adverse outcomes, it makes it very difficult to argue for continued focus– and safety declines. “That never happens…”, or “I can’t remember when I last heard...”
- Secondly, the aetiology of Safety 1 has flaws – chiefly that there is a direct link between cause and outcome – and that the cause can be deduced by retrospective analysis “causality credo” – the belief that badness happens because something went wrong. May be true of mechano-technical systems, but there is little support for this in complex, adaptive, socio-technical systems such as healthcare James Reason “the Swiss cheese model may have passed it’s sell by date”
- Thirdly, there is the assumption that healthcare systems can be deconstructed and understood, and that the function of individual components is bimodal – it works or it doesn’t This may be true for devices, and equipment where components are engineered for a purpose and whose function is fully understood. Timeline – seductive – linearity and inferred causality Not true for socio-technical systems which are near impossible to deconstruct, and whose components operate with varying degrees of function, and even change function, according to the prevailing circumstances.
- Safety 1 based on simple straightforward activity (1960-1990) Technologically simple, low integration, loose coupling (independent) and therefore understandable Assumed that systems are well deigned and maintained, Procedures are correct comprehensive and understood People do as expected and trained Designers have taken account of a wide range of contingencies 2010 Healthcare is rapidly evolving Evolved systems, human technology interface complex
- 2010 Healthcare is rapidly evolving Evolved systems, human technology interface complex Humans replaced by tech Ambitious safety targets Tackling solvable problems – often with technological solution s (tidier) Tightly coupled systems, interdependencies Humans BUFFER the system
- Impossible to describe what clinicians should do in all but the most trivial of situations Adaptation and flexibility are assets Constraining practice is counterproductive
- WAI vs WAD Scientific management theory – processes can be deconstructed and understood – and the best way can be defined. Time and Motion studies of the ‘60’s WAD (what actually happens) can be made to approximate WAI (the way it is supposed to be done) with useful effect In intractable (poorly understood) CAS WAI doesn’t approximate WAD CAS work because adaptability and variation compensate for the varying conditions of the system – and so need to understand WAD
- Work is adjusted to match conditions Minimally in tractable systems – don’t take off! Iceland volcano? Stop the line Major in intractable CAS Conditions often unfavourable “Stop” option not possible in emergency healthcare. – amazing that it works at all – not explained by analysing failure
- Can’t prescribe the correct action All outcomes are the result of everyday performance Understand why it goes right instead of looking at the failures Poor outcomes usually a combination of known variabilities, not a single point of failure
- Outcomes are emergent not resultant – in other words there is no direct connection between cause and effect, but some conditions are more permitting of different outcomes Conditions may be permanent or (more commonly) transient, and may be unpredictable Relationships between components are unstable Circumstances have to be inferred rather than observed
- Look at all outcomes Safety defined by what happens when it is present, not absent – the things that make it work This is in the high frequency, good outcomes More “goodness” = better safety (good argumnet for continued efforts) Performance adjustments that create or maintain acceptable working conditions despite variation in resource, time, or information
- Variation must be present
- Ends are easy to see, difficult to change, difficult to manage and have complex aetiology Middle often not seen (ignored), but easy to change, easy to manage and has relatively straightforward aetiology
- Ends are easy to see, difficult to change, difficult to manage and have complex aetiology Middle often not seen (ignored), but easy to change, easy to manage and has relatively straightforward aetiology
- Ends are easy to see, difficult to change, difficult to manage and have complex aetiology Middle often not seen (ignored), but easy to change, easy to manage and has relatively straightforward aetiology
- So, to sum up a saftey II approach: Look at what goes right Understand adjustment to everyday variation in conditions WAD is usually not the same as WAI
- There is very rarely “Bimodal Functioning in Healthcare – processes don’t “work or not work” – which is difficult in the context of bimodal (dead or alive, DVT, no DVT) outcomes
- Variability In performance – contingent upon the state of the system in which the process is taking place. Some variation is necessary. Some is not.
- Focus on frequent events Understand how work actually happens Frequent, small adjustments are easy to manage and change, whereas big changes on the basis of a bad outcome may not have the desired effect and may have unwanted consequences
- Remain vigilant Bad outcomes are possible, emergent, not as a result of malfunction Ongoing application of the things that work
- Invest in Safety Invest in maximising what goes right - measure it – see it increase – INVESTMENT
- Prioritise thoroughness over efficiency Allocate resource to understanding (and changing) work as done – long term investment because efficiency follows