a new tool for the assessment of resilience in healthcare: a social … · 2020-02-27 · a new...
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A new tool for the assessment of resilience in healthcare: a social network analysis perspective
Tarcisio A. Saurin, Vanessa B. Becker
8th RHCN meeting, Osaka, August 2019
Collaboration relies on social networks, and these influence the four resilience abilities
Anticipating, monitoring, responding, learning
These can be assessed in terms of social networks
Broader research question
How can SNA support the assessment of resilience in healthcare?
Background
Who are the key players in the four networks?
Are the key players available?
Are the key players the same in the four networks investigated?
Do the key players provide reliable information?
How can SNA contribute to the assessment of resilience in socio-
technical systems?
Anticipating Monitoring
Responding Learning
Which actors are the key sources of resilience?
Research question addressed in this presentation
(availability . reliability . betwenness* . in-degree*) * Normalized
• Maximum possible resilience score = 5 . 5 . 5 . 5 = 625
The score can be calculated for each agent within each network
TENTATIVE Resilience Score
(1) Characterization of the respondent and of three contextual factors
Frequency of interruptions
Participation in daily interdisciplinary rounds
Shift
(2) A roster of staff, from which the respondent should select those they rely upon for advice. Besides, questions on:
Availability (time)
Reliability (precision)
(3) Contribution of the interaction for each resilience ability
Frequency of the interaction
The SNA questionnaire
Monitoring consists of continually perceiving changes, disturbances, threats or opportunities during your daily activities, as close as possible to real-time
E.g. You may be interested in monitoring relevant changes in the patient´s clinical condition
For the people you selected, please indicate the frequency they are contacted for monitoring
Exemplar question: monitoring
Never Less than once a month
1-3 times a month
1-3 times a week
Daily
Nurse A X
Doctor B X
Adult ICU of a major public teaching hospital, 34 beds
Patients admitted from Emergency department, surgical unit, wards, other hospitals
About 200 employees from 15 professional groups, 6 shifts
Scenario of this study
Overall response rate = 67%
Sample profile
n % n %
Doctors 40 20% 16 12%
Nurses 32 16% 25 19%
Nurse technicians 115 57% 84 63%
Staff Total Respondents
n % n %
Doctors 40 20% 16 12%
Nurses 32 16% 25 19%
Nurse technicians 115 57% 84 63%
Allied health 14 7% 8 6%
TOTAL 201 100% 133 100%
Staff Total Respondents
Never Rarely Sometimes Frequently Always
Participation in rounds
35% 10% 24% 18% 14%
Frequency of interruptions
3% 14% 27% 45% 11%
Results
Metrics Monitoring Anticipating Responding Learning
Density 2.2% 2.0% 2.8% 2.3%
Connectedness 46% 54% 64% 55%
Highest-in-degree DR 169 N135 DR 169 DR 169
Highest-out-degree NT 10 NT 106 NT 32 N186
Betweeness N94 N94 N135 N94
The ranking of several agents was VERY DIFFERENT across the networks, based on the resilience score
NT 193 was the 31st for Monitoring, and the 6th for Anticipating
DR 48 was the 41st for Responding and the 4th for Learning
Other agents had more stable and higher positions
N94 was the 1st for Monitoring, Anticipating, and Responding, while the 2nd for Responding
A same interaction can effectively contribute to the four potentials
How can these professionals balance availability, reliability, betwenness, and in-degree? Which resilience strategies?
Results
Doctors were slightly less frequent in the top 10 resilience scores, in comparison with considering only the in-degrees
They appeared 16 times among the top ten based on the in-
degrees rankings
12 times based on the resilience scores
Doctors were less available than other professionals
How can availability increase?
Results
Low density may suggest reliance on other resources for resilience
It may also simply be that the four potentials are weak in the ICU
Application of RAG
Captured social interactions are those when the respondent requests advice
What about when the respondent offers advice?
E.g. A nurse may take the initiative to let a doctor know what is
going on in the ICU (monitoring)
Some implications and limitations
Complete data analysis
Interviews with the main sources of resilience
Further statistical analysis (clusters)
Combine the multiple network layers
Additional test: new ICU, and other ICUs (other countries?)
What a resilient network looks like?
What are normal thresholds for the network metrics?
Investigation of how visual management influences on the networks
Next steps
Thank you!
Doctors are usually the main source of advice for other professionals
Doctors usually request advice from other doctors (54% density for the learning network)
Density for the learning network
* In degree: How much they are contacted by other professionals; ** Out-degree: how much they contact others
Main results
Doctor* Nurse Nurse technician
Allied health Average out-degree (without
own group)
Doctor** 0.54 0.29 0.31 0.18 0.26
Nurse 0.58 0.47 0.30 0.33 0.40
Nurse technician 0.43 0.46 0.36 0.28 0.39
Allied health 0.66 0.41 0.35 0.64 0.47
Average in-degree (without own group)
0.56 0.39 0.32 0.26
23 questions on the resilience potentials
Scale from fully disagree (1) to fully agree (5)
Ex. 1. The interdisciplinary rounds contribute to the monitoring of what is going on in the ICU, including conditions and events that may imply in
undesired impacts to the ICU and clinical condition of patients
Ex. 2 Interruptions in my work (telephone, colleagues, family, etc.) are not frequent and not hinder the monitoring of what is going on in the ICU
Three closure questions
The ICU is resilient
Patients are safe
Professionals are safe
Complementary RAG survey