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PROACT: Iterative Design of a Patient-Centered Visualization for - - PowerPoint PPT Presentation

Jun 02, 2023 658 likes •897 views

PROACT: Iterative Design of a Patient-Centered Visualization for Effective Prostate Cancer Health Risk Communication. Hakone A, Harrison L, O8ley A, Winters N, Gutheil C, Han PK, Chang R. Presented by James Hicklin Context: prostate cancer

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SLIDE 1

PROACT: Iterative Design of a Patient-Centered Visualization for Effective Prostate Cancer Health Risk Communication.

Presented by James Hicklin

Hakone A, Harrison L, O8ley A, Winters N, Gutheil C, Han PK, Chang R.

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SLIDE 2

Context: prostate cancer

  • 80% of cases clinically localized
  • Two treatment categories
  • AcJve treatment (surgery, radiaJon)
  • ConservaJve treatment (watch & wait)
  • Only 10% of paJents choose conservaJve

treatment

  • Fear of cancer (“death sentence”)
  • Lack of informaJon
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Patient lack of information

  • ExisJng tools physician-oriented
  • PaJent numeracy can be problemaJc
  • CogniJve biases exist

h8ps://urology.ucsf.edu/research/cancer/prostate-cancer-risk-assessment-and-the-ucsf-capra-score

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SLIDE 4

System goals

  • Improve prostate cancer paJent

understanding of their individual health risk informaJon

  • Provide a framework for physicians to guide

them in communicaJng risk informaJon

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SLIDE 5

Design process

  • IteraJve design based off paJent & doctor

evaluaJon of prototype

  • First iteraJon
  • NarraJve established from consulJng experts
  • VisualizaJons inspired from review of health risk

communicaJon literature

  • Data sourced from validated clinical predicJon

models

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SLIDE 6

Clinical prediction models

  • Individualized prognosis esJmates based on

real evidence

  • Not widely used
  • IncompaJble with clinical pracJce
  • Not paJent-oriented
  • Two CPMs inform data in PROACT
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SLIDE 7

Iteration #1

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SLIDE 8

Risk of death

Hakone et al., IEEE Transac2ons on Visualiza2on and Computer Graphics, 2017

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SLIDE 9

Probability of survival

Hakone et al., IEEE Transac2ons on Visualiza2on and Computer Graphics, 2017

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SLIDE 10

Combined probabilities

Hakone et al., IEEE Transac2ons on Visualiza2on and Computer Graphics, 2017

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Evaluation (iteration #1)

  • 2 urologists and 6 prostate cancer survivors
  • HypotheJcal scenarios completed (paJents:

4, urologists: 1)

  • Decision confidence assessed at 4 points

(paJents only)

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SLIDE 12

Findings (iteration #1)

  • Sequence of narraJve important – “How

much 2me do I have leD?”

  • Difficult to reason without this
  • Context is criJcal – heightened emoJonal

state causes difficulty in processing informaJon

  • Suggests that first step of tool should calm the

paJent down

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SLIDE 13

Findings (iteration #1)

  • Sliders controlling temporal element were

completely ignored

  • Temporal area chart not understood by 6 out
  • f 8 parJcipants
  • Perhaps parJcipant demographics not

properly considered

  • “I like numbers, but I’m old so I oDen need 2me

to study graphs”

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SLIDE 14

Findings (iteration #1)

  • ParJcipants confused as colors across

visualizaJons were inconsistent, despite data being condiJonally linked

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SLIDE 15

Iteration #2

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PROACT demo

hKp://tuDsvalt.github.io/proact/demo/pilot2/

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SLIDE 17

Discussion

  • All paJents recalled lack of informaJon

provided by physician, and resorted to searching the internet for informaJon

  • Study contribuJons:
  • Allows paJent access and understanding of

clinical predicJon models

  • CommunicaJon guide for consultaJons
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SLIDE 18

Discussion: design guidelines

  • Account for user’s emoJonal state
  • NarraJve flow of visualizaJon is criJcal
  • DisJll complex models into simple

visualizaJons

  • Minimize interacJon
  • Sacrifices exploraJon
  • But for general public, this may improve

understanding of data

  • Grounded iteraJve design
  • EffecJve when used in target user groups
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Critique

  • Pros
  • Sample representaJve of target user
  • Converts physician-oriented clinical predicJon

models to paJent-oriented risk visualizaJons

  • Simple visualizaJons so that wide range of

target users can understand informaJon

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Critique

  • Cons
  • IteraJve process feels a li8le contrived – cannot

imagine any 80 year old being able to understand the temporal area chart.

  • Sample size small
  • No effort made to represent and convey uncertainty
  • Only accounts for two treatments – other

treatments available but not discussed

  • Only takes survival into account – other a8ributes

(side effects, cost, etc.) not considered

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SLIDE 21

References

  • Hakone, Anzu, Lane Harrison, Alvi8a O8ley, Nathan

Winters, Caitlin Gutheil, Paul K. J. Han, and Remco Chang. "PROACT: IteraJve Design of a PaJent-Centered VisualizaJon for EffecJve Prostate Cancer Health Risk CommunicaJon." IEEE TransacJons on VisualizaJon and Computer Graphics 23.1 (2017): 601-10.

  • Stephenson, Andrew J., Michael W. Ka8an, James A.

Eastham, Eric A. Klein, Fernando J. Bianco, Andrew J. Vickers, Ofer Yossepowitch, and Peter T. Scardino. "Prostate Cancer-Specific Mortality Aler Radical Prostatectomy For PaJents Treated In The Prostate- Specific AnJgen Era." The Journal of Urology 179.4 (2008): 649.

  • Lu-Yao, Grace L. "Outcomes of Localized Prostate Cancer

Following ConservaJve Management." Jama 302.11 (2009): 1202.

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SLIDE 22

Thank you! Questions?