Disclosure belangen spreker (potentiële ......Tumor Board-report Free text. Many variations. •...

(potentiële) belangenverstrengeling Zie hieronder

Voor bijeenkomst mogelijk relevante relaties met bedrijven

Bedrijfsnamen

ZINL, Health Holland, NWO-DATA2PERSON funding for projects related to shared decision making

Member scientific advisory board Evidencio (unpaid)

Member scientific advisory board Pathology Image Exchange (PIE, unpaid)

Member expert council CZ (unpaid)

Evidencio CZ

Disclosure belangen spreker

Decision support in Oncology - Oncoguide

Xander Verbeek, IKNL

• 1990-1996 Applied Physics

• 1996-2004 PhD/Post Doc CARIM

• 2004-2014 Philips Health Informatics

• 2004-2006 Health Information Management

• 2014-today IKNL Chief Innovation Officer, Head of Health Informatics

& Data Science

Xander Verbeek

IKNL

Netherlands

Cancer

Registry

Registration

Analysis

3. Application

Patient

data

Population Based

Registy

Knowledge

Actionable

Insight

1

2

3

4. Standardization

4

OncolinQ innovation program – technology innovations

Rapid

Learning

Healthcare

System

Registration

Analysis

3. Application

Patient

data

Population Based

Registy

Knowledge

Actionable

Insight

1

2

3 Decision support,

data & knowledge services

Privacy preserving

distributed machine learning

Secure electronic data

exchange & access

Standardization,

FAIR principles

Field research

Scope: Clinical information management and decision making

http://www.uke.uni-hamburg.de/index.php?id=-1_-1_-1&as_link=http://www.uke.uni-hamburg.de/index.php

http://www.hopkinshospital.org/index.html

http://www.cancer.dartmouth.edu/index.shtml

http://www.vumc.nl/

http://www.mca.nl/

http://www.mdanderson.org/

http://www.google.nl/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&ved=0CAcQjRxqFQoTCOK_2ff39ccCFUo4FAody9YOtw&url=http://www.amphia.nl/&psig=AFQjCNFIpZxkb1IG_9UdSN0A1AieSbgrLw&ust=1442299890683440

Near exponential growth scientific publications

Breast Cancer Prostate Cancer

Lung Cancer Colorectal Cancer

Netherlands Cancer Registry

2018: 2,3 miljoen 2018: 2,3 miljoen

Number of patients in NCR

+250 publications/year

Towards a rapid learning healthcare system

010100101001010

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100101011010011

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Guideline driven Data driven

From guidelines to algorithms and data driven decision support


CT scan

MRI Decision

Echo +

biopsy

Care

pathway

Initial diagnostics Initial treatment

Decision

Chemotherapy

+ CT scan

Surgery +

pathology

Decision

Chemotherapy

Radiotherapy

Re-operation

Post-operative treatment

Preg-

nant

Age

CT scan

MRI

>=50j

<50j

nee

ja

… Echo +

biopsy

cT

<cT1

>=cT2 G

Chemotherapy

+ CT scan

Surgery +

pathology >G1

pT

pT1 Chemotherapy

Radiotherapy

G

pT2

>=pT3 >=G2

G1

R

Re-operation

Free

Not free

Data driven

decision

algorithms

<= G1

Tumor

Board

Tumor

Board

Method based on insights from decades of research on computer interpretable guidelines

Recommendations

Clinical Decision Trees

M. Hendriks, X. Verbeek, T. Vegchel, M. vd Sangen, L. Strobbe, J. Merkus, H. Zonderland, C. Smorenburg, A. Jager, S. Siesling (In Press JCO-CCI)

“It captures the

essence of the

guideline” Physicians @ NCCN

conference 2018

Example: postoperative radiotherapy breast cancer

Clinical Decision Trees


Nodes

Patient/disease

characteristics

(e.g. Surgical Margin)

Nodes

Patient/disease

characteristics

(e.g. Surgical Margin) Branches

Cut-off values

(e.g. Free)

Branches

Cut-off values

(e.g. Free)

Leaves

Recommendation

(e.g. Radiotherapy)

Leaves

Recommendation

(e.g. Radiotherapy)

Data item:

Surgical margin (SNOMED CT 82868003)

Value set:

-Free (SNOMED CT 55182004)

-Focal not free (SNOMED CT 370109009)

-More than focal not free (code requested)

Source:

PALGA PROTOCOL excision specimen


Standardization as prerequisite for connecting to EHR

Rigorous application of

appriopriate international

classification and coding

systems

Rigorous application of

appriopriate international

classification and coding

systems

PICO


Standardization as prerequisite for connecting to EHR

Standardized

Standardization – linguistic unity

Pathology report • Free

• Focal not free

• More than focal not free

Registries • Radical or absent and DCIS radical or absent

• Radical or absent and DCIS focal not radical

• Radical or absent and DCIS not radical

• Focal not radical and DCIS radical or absent

• Focal not radical and DCIS focal not radical

• Focal not radical and DCIS not radical

• Not radical and insignificant

• Margin invasive and/or DCIS component not clearly

stated

Guideline • Tumor free margin

• Focal extension

• More then focal extension

• Radical/not radical

• Margin involvement

• Tumor free resection

• Irradicality

• Free resection margins

• Focal tumor positive

margin

• Extensive tumor positive

margins

Tumor Board-report Free text. Many

variations.

Information standard: • Free

• Focal nor free

• More than focal not free

Surgical tumor margin


Results Breast Cancer

376 subpopulations

199 pages free text 60 decision trees 114 data-items • 49% pathology

• 27% radiology

• 24% clinical

• 66 ~ TNM

• 8 ~ BIRADS

• 90 ~ SNOMED

Oncoline Art-DECOR Oncoguide

+ +


guideline algorithms information standard


RESTful API

EHR connector

Implementation pilots

Submitted to JCO

Impact on quality of documentation and workload of the introduction of a

national information standard for breast cancer tumor board reporting

Kees C.W.J. Ebben1, Melle Sieswerda1, Ernest Luiten2, Joan Heijns3, Carmen van der Pol4, Maud Bessems5,6, Aafke

Honkoop7,6, Mathijs Hendriks8, Xander A.A.M. Verbeek1

Clinical evaluation study Amphia Hospital

Oncoguide Advisor

OG Guideline Surgery, mastectomy

OG Trial NEXUS-II

OG Predict 5-y survival Neoadjuvant chemotherapy 12-34%

5-y survival Surgery 14-41%

Patient: Isabella Strong, (01-12-1973) Tumor Board (pre-op)

Diagnosis Breast cancer

TNM cT3a cN1 cM0

Morphology/Grade Tubuloductal G3

Receptor ER+ PR- HER2+

RECOMMENDATION Neoadjuvant chemotherapy

OncolinQ innovation program

PALGA standardized pathology report

Patient: I. Strong, (01-12-1973)


Morphology Tubuloductal G3


IIA

Electronic Health Record (EHR) standardized reporting Oncoguide

Knowledge sources

Patient: #3%3416AA, (01-12-1973)


TNM cT3a cN1 cM0

Morphology Tubuloductal G3


Registries

NKR ↓

Integrating Real World Data

NKR ↓

2013

2014

2015

2016


NKR ↓

17449

18330

14507

124

3813

97% 86%

2391

7774

48%

1834 185

372

284

212

64% 67% 60% 75%

881


Integrating Prediction Models

•New prediction models

•Validation international models

IBM Watson versus Oncoguide

Other developments

Beyond Breast Cancer Beyond Oncology Beyond the Netherlands

“If medicine wishes to stay in control of its own future, physicians will not

only have to embrace algorithms, they will also have to excel at developing

them, bringing machine learning methods into the medical domain”

www.iknl.nl

www.linkedin.com/company/iknl

twitter.com/iknl

1 2

Registration Analysis

3

Application


CT scan

MRI Decision

Echo +

biopsy

Care

pathway

Initial diagnostics Initial treatment

Decision

Chemotherapy

+ CT scan

Surgery +

pathology

Decision

Chemotherapy

Radiotherapy

Re-operation

Post-operative treatment

Preg-

nant

Age

CT scan

MRI

>=50j

<50j

nee

ja

… Echo +

biopsy

cT

<cT1

>=cT2 G

Chemotherapy

+ CT scan

Surgery +

pathology >G1

pT

pT1 Chemotherapy

Radiotherapy

G

pT2

>=pT3 >=G2

G1

R

Re-operation

Free

Not free

Data driven

decision

algorithm

<= G1

Tumor

Board

Tumor

Board


Based on insights from decades of research in health informatics

Data

Integrating Prediction Models

NABON workgroup EHR standardization

Disclosure belangen spreker (potentiële ......Tumor Board-report Free text. Many variations. •...

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