clinical work to design better systems Prof Johanna Westbrook - - PowerPoint PPT Presentation

clinical work to design better systems
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clinical work to design better systems Prof Johanna Westbrook - - PowerPoint PPT Presentation

Cognitive Informatics understanding clinical work to design better systems Prof Johanna Westbrook Director, Centre for Health Systems & Safety Research Australian Institute of Health Innovation Health Informatics Conference August 2017


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Cognitive Informatics – understanding clinical work to design better systems

Health Informatics Conference August 2017

Prof Johanna Westbrook Director, Centre for Health Systems & Safety Research Australian Institute of Health Innovation

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Cognitive Informatics (CI)

Understanding work processes within the context of human cognition and designing solutions that can improve clinical work, patient engagement and public health, Patel et al 2015

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What do we know about clinical work?

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Health Care is a complex adaptive system

 Agents are autonomous often pursuing different agendas  Behaviour is emergent  Agents work in networks. They share some common rules for behaving and work together without a central source of direction.  Dynamic and use experimentation. Trial things and then adapt behaviours.

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A complex adaptive system in action

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To design technology that is effective in supporting and innovating work improving safety and outcomes it is fundamental to understanding clinical work + Human cognitive capacity

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Measuring work and communication patterns in the field – linking these to

  • utcomes

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Social Network Analysis Observational Studies

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Network Emergency Department Staff

  • Professional

clusters

  • Highly connected

53% of possible ties

  • Size indicates Prof

Experience

  • Senior Doctor

N= 103 staff – 94% How often do you seek advice to solve a work-related problem?

Social Network Analysis

Creswick et al

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Association between Communication Networks and Errors

Clinicians report that communication is central to reduce medication errors

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Prescribing error rate 19.4 / 100 patient days N=240 admissions Prescribing error rate 9.0/100 patient days N=428 admissions Who do you seek medication advice from at least weekly

Social Network Analysis on wards

84% of staff agreed that if doctors and nurses talked more frequently there would be fewer medication errors 54% agree that if doctors and nurses talked more frequently there would be fewer medication errors

Significantly lower % than Ward A, P=0.027

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Same hospital, same policies and procedures yet substantial differences in the way teams organise to delivery care HIT needs to support the work of these networks, reinforce behaviours likely to support better health

  • utcomes
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Direct Observational Studies of Clinicians

Goggle Box ~1 million Australian viewers each week

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14 OFFICE I FACULTY I DEPARTMENT

Work Observation Method By Activity Timing -

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Junior Doctors -

Benefits and Burden of Clinical Information Systems

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Junior Doctors’ Work

Direct observational studies to capture time spent in different work tasks Day time 08:30-19:00 12 junior doctors, 151 hours Night time 22:00-08:00 8 junior doctors, 96 hours Weekend 08:00-19:00 16 junior doctors, 160 hours

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17 OFFICE I FACULTY I DEPARTMENT

Task Weekend Dayshift Night shift Indirect care 32 24* 16* Direct care 23 13* 14* Social/breaks 9 16* 28* Supervision/ education 1 7* 2* Multi-tasking 21 19 6* Interruption rate (per hr) 6.6 2.2* 1.3*

Percentage of Time

* significant difference P<0.001

Weekend Work

  • Highest % of time in clinical care
  • Interrupted frequently
  • Inadequate rest breaks

High cognitive demand

L Richardson et al Internal Medicine Journal, 2016, 46, 819-825

Work is dynamic

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Implications – CIS which support the dynamic nature of clinical work Keeping track of multiple tasks Provide guidance Supporting fatigued users

Systems which can adapt to users’ needs at different times and in different situations

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Emergency Department – window into complex adaptive system

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US Emergency Department in 1960s

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Observational Study in Sydney Emergency Department

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Aim: Understand the dynamic nature of work

 Dayshifts 08:00-18:00  36 Doctors – shadowed for 120 hours, 58 sessions  Collect detailed information on all tasks and interactions

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Task Type Communication Direct Care Indirect Care Documentation In Transit Prescribing Other Prompts

P a t i e n t s

0 20 40 60 80 100 120 Time (Mins)

Dynamic nature of work – Senior Resident Medical Officer

1 2 3 4 5

Dr Scott Walter

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Task Type Communication Direct Care Indirect Care Documentation In Transit Prescribing Other Prompts

0 20 40 60 80 100 120 140 160 180 200 Time (Mins)

P a t i e n t

1 2 3 4 5

Registrar

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Task Type Communication Direct Care Indirect Care Documentation In Transit Prescribing Other Prompts

0 20 40 60 80 100 120 140 160 180 200 Time (Mins)

1 2 3 4 5 6 7 8 9 10 P a t i e n t

Consultant

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Internationally, well recognised that ED physicians experience a high rate of interruptions Multi-tasking is promoted as a effective work strategy Experimental evidence from psychology demonstrates interruptions and trying to multi-task add significant cognitive load task errors. Implications of these work patterns for cognitive load and performance?

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Driving and mobile phone use

Drivers who use a mobile phone are 31% more likely to experience an accident involving injury or death

Simulations show that just listening to a passenger reduces driver performance – e.g. lane deviations

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Studies in health on the effects

  • f interruptions on work

Nurses interrupted during chemotherapy administration - more errors than those not interrupted

(Prakesh et al 2014)

Operating room simulation - anaesthetists who immediately responded to an interruption all failed to check a blood product before

  • transfusion. (Liu et al 2009)
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Aim: To understand the extent to which interruptions and multi-tasking may be associated with task errors

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Methods

 Large Sydney ED, 36 Drs  Tested Working Memory Capacity of Drs  Sleep in the 24 hours prior to observation  Demographics of drs and patient age; ED workload  Recorded all tasks, interruptions and multi-tasking  Identified all prescribing tasks during observations and later assessed these for errors.

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Sleep

Following observation sessions Drs reported whether they had received average, > or < than average sleep in the previous 24 hours Average sleep reported for 64.3% sessions < average 19.6% > average 16.1% Average = 6.7 hours; < average = 5.6; > average 7.8

Recommended sleep for adults 7-9 hours

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Interruptions and Multi-tasking

7.9 interruptions/hour; 9.4/hour when prescribing Spent 4.6% of overall time multi-tasking 20.1% of prescribing time multi-tasking

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Prescribing Errors

 27 clinical errors , 181 legal/procedural errors  Clinical error rate 11/100 orders; 0.4/patient  Legal/procedural 76/100 orders; 2.6/patient

deClifford et al 2007 Impact of an ED pharmacist on prescribing errors in an Australian

  • Hospital. Pharm Pract Res. 37(4) 284-86

Reported medication error rate 20/100 orders; 1.6/patient. Definitions of prescribing errors were not reported but appeared to focus more on clinical errors but included adverse drug reactions

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Legal /Procedural Errors

Incomplete

  • rder

Medication Order Oxycodone 5-10mg orally when required, up to a maximum dose of 20mg Description of error Frequency omitted from order

Incomplete

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Morphine 2.5mg subcutaneously every four hours when required Maximum daily dose omitted from order

Clinical Errors

Wrong strength

Thyroxine 50mg orally

  • nce daily

Dose should have been 50mcg.

Wrong drug (drug- disease interaction)

Aspirin 100mg orally

  • nce daily

Prescribed for patient with corrosive gastritis/duodenitis and for whom there was no active disease for which aspirin is required.

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Clinical prescribing errors

Errors were significantly associated with:  Interruptions during prescribing

  • RR 2.82 (1.23-6.49), p<0.01

 Consultants made fewer clinical errors than junior dr

  • p<0.002

 Drs with higher WMC scores had significantly fewer errors  For every 10 point improvement in their WMC test score there was a 19% decrease in error rate  Doctors with below average sleep had a clinical error rate >15 times that of doctors who had average sleep

  • RR 16.44, p<0.001
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What are the implications of these results for design of IT?

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 Resilience engineering – focus on factors that help a complex system be safe. Resilience “The intrinsic ability of a system to adjust its functioning prior to, during, or following changes and disturbances, so that it can sustain required operations under both expected and unexpected conditions." Hollnagel, 2010  CIS designs which recognise complexity & cognitive load - e.g.

  • support situational awareness
  • recovery from interruption
  • adaptive decision support (e.g. features appearing at different

times, to different people)

Future Directions

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“…solutions too often are created for an imaginary world based on how things ought to work, without considering the realities created by context and constraints of the actual work environment.”

(Wears et al, 2015 Ann Emerg Med)

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Constraints of human capacity within different contexts

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How far have we come?

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Johanna.westbrook@mq.edu.au

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Thank You