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Lecture 13: Clinical decision support systems
Dr. Martin Chapman
Principles of Health Informatics (7MPE1000). https://martinchapman.co.uk/teaching
Recall: Where are we?
Lecture 2 – models, information and information
systems – informatics definitions.
Lectures 3 + 4 – informatics skills – how can principles
from informatics guide the way we work in healthcare?
Lectures 5 + 6 – everything you need to know about
information systems (designing them, evaluating them,
implementing them…)
Foundation
Built on
Built on
Where are we?
Lecture 5 – electronic health records
Lectures 7 + 8 – computable guidelines
Lectures 9 + 10 – communication systems
Lectures 11 + 12 – terminology systems
…
Examples, broadly, of
information systems, which
could be explored in any
order.
Let’s also not forget the
connection with
interventions.
(protocol systems)
Lecture structure
1. What is a clinical decision support system (CDSS)?
2. What can a CDSS do?
3. What are the benefits of CDSSs?
4. What might stop a CDSS from being successful?
This is very much the ‘what’ before the ‘how’. The ‘how’ will come
in Lecture 14.
Learning outcomes
1. Be able to define, at a high level, a clinical decision support
system (CDSS).
2. Understand the different features offered by a CDSS, and rank
them in terms of their complexity and level of automation.
3. Understand the benefits of a CDSS.
4. Be able to critique the notion of a CDSS, and understand why
the implementation of one may not be successful.
What is a clinical decision support system
(CDSS)?
Recall: Automation
Capturing knowledge in this way is useful, because we can then
provide it to a computer in order to automate its application.
If we cannot fully represent the model in a computer, then human
involvement may be required (semi-automated).
Similarly, computers may play more of a supportive role, organising
data or providing visualisation of that data.
Sinks
A computer, as an
information system, could
automatically determine
whether a plane will sink or
not.
Recall: It all comes back to public health interventions…
If we can automate the application of knowledge to health data,
then we can automate (the introduction of) interventions.
If we can’t fully use information systems to automate this
application, then they can assist clinicians in the delivery of
interventions.
Diabetes
A computer, as an
information system, could
automatically determine
whether a patient has
diabetes and act accordingly
This second example from Lecture 2 was really hinting towards the
concept of a CDSS, which, based on these examples, we can define as:
Assisting human decision-making and improving decision outcomes
in a clinical setting
We later saw an example of a CDSS fitting this description in Lecture
10…
What is a CDSS?
Recall: Mobile applications – CONSULT
Sensors (wearables) help to
monitor a patient’s state remotely. We store our data
centrally using a
standard, and
communicate in the
same standard.
We have a reasoning
engine, providing the
DSS component.
Patients (and clinicians) can view
the data collected by the system,
and the recommendations
(interventions) suggested.
The EHR can also
be referenced to
contextualise
sensor readings
and interventions
A real focus on taking
telemonitoring to the next
level in terms of
promoting self-
management.
Martin Chapman, Abigail G-Medhin, et al. Using microservices to design patient-facing
research software. In Proceedings of the IEEE 18th International Conference
on e-Science (e-Science), 2022.
This second example from Lecture 2 were really hinting towards the
concept of a CDSS, which, based on these examples, we can define as:
Assisting human decision-making and improving decision outcomes
in a clinical setting
We later saw an example of a CDSS fitting this description in Lecture
10…
To go beyond this simple definition and help us better understand
what a CDSS is, we can consider the types of tasks CDSSs assist with.
What is a CDSS?
What can a CDSS do?
Automated
Assistive
Complex
Simple
Ranked
diagnoses
MRI
interpretation
Vital
monitoring
What can a CDSS do?
Diagnosis
We’ll categorise examples of
CDSS features as follows:
Example: CDSS diagnosis
What can a CDSS do?
Therapy planning
Guiding the treatment of a
patient
Automated
Assistive
Activity
templates
Patient-
specific plans
Radiation
dosage
calculation
Complex
Simple
What can a CDSS do?
Prescribing
Automated
Assistive
Dosage
calculators
Gene-drug
advice Drug-drug
interaction
identification
Complex
Simple
What can a CDSS do?
Process support
The organisation of wider
clinical activities beyond
just diagnosis
Automated
Assistive
Patient flow in
secondary care
Screening
reminders
Guideline
adherence
monitoring
Complex
Simple
What can a CDSS do?
Automated
Assistive
Data-based
disease
likelihood
Clinical process
simulation
Risk
predictor
collection
Risk assessment
Complex
Simple
What can a CDSS do?
Image recognition
Automated
Assistive
Past case
matching
(case-based
reasoning)
Pattern to
disease
matching
Dynamic
organ
rendering
Complex
Simple
What can a CDSS do?
Evidence retrieval
Software shapes our
decisions by selecting the
information we use to
make them
Automated
Assistive
Query
formulation
Search
agents
EHR-
contextualised
search
Complex
Simple
What can a CDSS do?
Lab support
Computer support when
ordering or receiving the
results of lab tests
Automated
Assistive
Generating
reports
Addition of
diagnostic
hypothesis
Workflow
guidance
Complex
Simple
What are the benefits of CDSSs?
Now we understand what a CDSS
is, let’s discuss its benefits…
What are the benefits of CDSSs?
Patient safety
Reduction in
medication errors and
adverse drug events
Enhanced prescribing
behaviour
‘Incorrect dosage
decreased from 2% to
<0.3%’
‘A 55% reduction in
adverse drug events’
What are the benefits of CDSSs?
Improved patient
outcomes
Improved clinical
process measures
Time released for
patient care
Quality of care
‘Reduced time to achieve
control of a disease’
‘Issue resolution 29%
shorter when alerts received’
‘Orders completed 63
minutes faster’
What are the benefits of CDSSs?
A reduction in cost due to many
of the CDSS features, and their
associated benefits, seen, e.g.
fewer medication errors = fewer
liability costs.
Efficiency of
healthcare delivery
What might stop a CDSS being
successful?
What might stop a CDSS being successful?
Clinician resistance
Poor technology
infrastructure
Such as limited availability of
EHR data, upon which CDSSs
typically operate
Because a CDSS may not fit
into their workflows.
Complexity of
conditions
Some conditions may not be
amenable to automated
support
Summary
A clinical decision support system (CDSS) is defined as ‘assisting
human decision-making and improving decision outcomes in a clinical
setting’.
We have seen how a CDSS assists human decision-making by helping
with tasks such as medication dosage, and how, in practice, this
improves outcomes like patient safety.
While a CDSS has lots of benefits, in practice its impact may be
limited by factors such as the attitudes of clinicians.
References and Images
Enrico Coiera. Guide to Health Informatics (3rd ed.). CRC Press, 2015.
Brendan C. Delaney, Vasa Curcin, Anna Andreasson, Theodoros N. Arvanitis, Hilde Bastiaens, Derek Corrigan, Jean
Francois Ethier, Olga Kostopoulou, Wolfgang Kuchinke, Mark McGilchrist, Paul Van Royen, and Peter Wagner.
Translational Medicine and Patient Safety in Europe: TRANSFoRm–Architecture for the Learning Health System in
Europe. BioMed research international, 2015, 2015.
https://fontawesome.com/

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Principles of Health Informatics: Clinical decision support systems

  • 1. Lecture 13: Clinical decision support systems Dr. Martin Chapman Principles of Health Informatics (7MPE1000). https://martinchapman.co.uk/teaching
  • 2. Recall: Where are we? Lecture 2 – models, information and information systems – informatics definitions. Lectures 3 + 4 – informatics skills – how can principles from informatics guide the way we work in healthcare? Lectures 5 + 6 – everything you need to know about information systems (designing them, evaluating them, implementing them…) Foundation Built on Built on
  • 3. Where are we? Lecture 5 – electronic health records Lectures 7 + 8 – computable guidelines Lectures 9 + 10 – communication systems Lectures 11 + 12 – terminology systems … Examples, broadly, of information systems, which could be explored in any order. Let’s also not forget the connection with interventions. (protocol systems)
  • 4. Lecture structure 1. What is a clinical decision support system (CDSS)? 2. What can a CDSS do? 3. What are the benefits of CDSSs? 4. What might stop a CDSS from being successful? This is very much the ‘what’ before the ‘how’. The ‘how’ will come in Lecture 14.
  • 5. Learning outcomes 1. Be able to define, at a high level, a clinical decision support system (CDSS). 2. Understand the different features offered by a CDSS, and rank them in terms of their complexity and level of automation. 3. Understand the benefits of a CDSS. 4. Be able to critique the notion of a CDSS, and understand why the implementation of one may not be successful.
  • 6. What is a clinical decision support system (CDSS)?
  • 7. Recall: Automation Capturing knowledge in this way is useful, because we can then provide it to a computer in order to automate its application. If we cannot fully represent the model in a computer, then human involvement may be required (semi-automated). Similarly, computers may play more of a supportive role, organising data or providing visualisation of that data. Sinks A computer, as an information system, could automatically determine whether a plane will sink or not.
  • 8. Recall: It all comes back to public health interventions… If we can automate the application of knowledge to health data, then we can automate (the introduction of) interventions. If we can’t fully use information systems to automate this application, then they can assist clinicians in the delivery of interventions. Diabetes A computer, as an information system, could automatically determine whether a patient has diabetes and act accordingly
  • 9. This second example from Lecture 2 was really hinting towards the concept of a CDSS, which, based on these examples, we can define as: Assisting human decision-making and improving decision outcomes in a clinical setting We later saw an example of a CDSS fitting this description in Lecture 10… What is a CDSS?
  • 10. Recall: Mobile applications – CONSULT Sensors (wearables) help to monitor a patient’s state remotely. We store our data centrally using a standard, and communicate in the same standard. We have a reasoning engine, providing the DSS component. Patients (and clinicians) can view the data collected by the system, and the recommendations (interventions) suggested. The EHR can also be referenced to contextualise sensor readings and interventions A real focus on taking telemonitoring to the next level in terms of promoting self- management. Martin Chapman, Abigail G-Medhin, et al. Using microservices to design patient-facing research software. In Proceedings of the IEEE 18th International Conference on e-Science (e-Science), 2022.
  • 11. This second example from Lecture 2 were really hinting towards the concept of a CDSS, which, based on these examples, we can define as: Assisting human decision-making and improving decision outcomes in a clinical setting We later saw an example of a CDSS fitting this description in Lecture 10… To go beyond this simple definition and help us better understand what a CDSS is, we can consider the types of tasks CDSSs assist with. What is a CDSS?
  • 12. What can a CDSS do?
  • 13. Automated Assistive Complex Simple Ranked diagnoses MRI interpretation Vital monitoring What can a CDSS do? Diagnosis We’ll categorise examples of CDSS features as follows:
  • 15. What can a CDSS do? Therapy planning Guiding the treatment of a patient Automated Assistive Activity templates Patient- specific plans Radiation dosage calculation Complex Simple
  • 16. What can a CDSS do? Prescribing Automated Assistive Dosage calculators Gene-drug advice Drug-drug interaction identification Complex Simple
  • 17. What can a CDSS do? Process support The organisation of wider clinical activities beyond just diagnosis Automated Assistive Patient flow in secondary care Screening reminders Guideline adherence monitoring Complex Simple
  • 18. What can a CDSS do? Automated Assistive Data-based disease likelihood Clinical process simulation Risk predictor collection Risk assessment Complex Simple
  • 19. What can a CDSS do? Image recognition Automated Assistive Past case matching (case-based reasoning) Pattern to disease matching Dynamic organ rendering Complex Simple
  • 20. What can a CDSS do? Evidence retrieval Software shapes our decisions by selecting the information we use to make them Automated Assistive Query formulation Search agents EHR- contextualised search Complex Simple
  • 21. What can a CDSS do? Lab support Computer support when ordering or receiving the results of lab tests Automated Assistive Generating reports Addition of diagnostic hypothesis Workflow guidance Complex Simple
  • 22. What are the benefits of CDSSs? Now we understand what a CDSS is, let’s discuss its benefits…
  • 23. What are the benefits of CDSSs? Patient safety Reduction in medication errors and adverse drug events Enhanced prescribing behaviour ‘Incorrect dosage decreased from 2% to <0.3%’ ‘A 55% reduction in adverse drug events’
  • 24. What are the benefits of CDSSs? Improved patient outcomes Improved clinical process measures Time released for patient care Quality of care ‘Reduced time to achieve control of a disease’ ‘Issue resolution 29% shorter when alerts received’ ‘Orders completed 63 minutes faster’
  • 25. What are the benefits of CDSSs? A reduction in cost due to many of the CDSS features, and their associated benefits, seen, e.g. fewer medication errors = fewer liability costs. Efficiency of healthcare delivery
  • 26. What might stop a CDSS being successful?
  • 27. What might stop a CDSS being successful? Clinician resistance Poor technology infrastructure Such as limited availability of EHR data, upon which CDSSs typically operate Because a CDSS may not fit into their workflows. Complexity of conditions Some conditions may not be amenable to automated support
  • 28. Summary A clinical decision support system (CDSS) is defined as ‘assisting human decision-making and improving decision outcomes in a clinical setting’. We have seen how a CDSS assists human decision-making by helping with tasks such as medication dosage, and how, in practice, this improves outcomes like patient safety. While a CDSS has lots of benefits, in practice its impact may be limited by factors such as the attitudes of clinicians.
  • 29. References and Images Enrico Coiera. Guide to Health Informatics (3rd ed.). CRC Press, 2015. Brendan C. Delaney, Vasa Curcin, Anna Andreasson, Theodoros N. Arvanitis, Hilde Bastiaens, Derek Corrigan, Jean Francois Ethier, Olga Kostopoulou, Wolfgang Kuchinke, Mark McGilchrist, Paul Van Royen, and Peter Wagner. Translational Medicine and Patient Safety in Europe: TRANSFoRm–Architecture for the Learning Health System in Europe. BioMed research international, 2015, 2015. https://fontawesome.com/