Innovar para construir el hospital del futuro

Dr. Lluís Blanch Torra

Senior Critical Care

Director Institut d’Investigació I Innovació Parc Taulí I3PT

WFSICCM Council Member

Madrid - May 29, 2019

L.Blanch is inventor of one Corporació Sanitaria Parc

Taulí owned US patent: “Method and system for

managed related patient parameters provided by a

monitoring device,” US Patent No. 12/538,940.

L.Blanch is founder of BetterCare S.L. which is a

research and development company, start up of

Corporació Sanitària Parc Taulí.

Financial Disclosures

Lluis Blanch MD, PhD

Intensive Care Med 2016 DOI 10.1007/s00134-016-4525-y

Computer Driven Intensive Care

Genetic Analysis

“Triage”

Structural & Physiological

Organ Analysis

Organ Reconstruction

and the brain?

Hospital/

Critical Care

of the

Future

3D-printed

organs

Virtual &

BiosensorsNew

Materials

New Disciplines

L. Blanch

Hospital / Critical Care

of the Future

Heterogeneity & Personalization

Data

Information Technologies & Prediction

Humans

Hospital / Critical Care

of the Future

Heterogeneity & Personalization

Data

Information Technologies & Prediction

Humans

THE PRECISION MEDICINE INITIATIVE

Mission statement:

To enable a new era of medicine through research, technology, and policies that empower

patients, researchers, and providers to work together toward development of individualized

care.

- President Obama, January 30, 2015

https://www.whitehouse.gov/precision-medicine

Syndromic Medicine: Guidelines

Precision

Medicine

Personalized Medicine

Protocols for Specific Subgroups

October & December 2018

January to May 2019

Recognized versus Unrecognized ARDS

JAMA. 2016;315(8):788-800

Difficulties of Developing &

Testing Therapies in ALI & ARDS

• ALI/ARDS definitions have deficiencies in

discrimination

• Multiple etiologies: pulmonary versus

extrapulmonary

• Heterogeneous cohorts with different age &

comorbidities: alcohol abuse, diabetes,…

• Multifaceted pathophysiology of pulmonary

injury

8.309.344 Cases of Invasive MV for Nonsurgical

Indications from 1993 to 2009

Journal of Critical Care 2015

139.500

adults/year

in Spain

Mortality ≈ 30%

Hospital / Critical Care

of the Future

Heterogeneity & Personalization

Data

Information Technologies & Prediction

Humans

Sources of Big Data“of course in the ICU”

Iwashyna TJ & Liu V

AnnalsATS 2014;11:1130-5

Iwashyna TJ & Liu V

AnnalsATS 2014;11:1130-5

Continuous

Respiratory Data

Waveforms

Sources of Big Data“of course in the ICU”

Turner MC et al AJRCCM Articles in Press. Published on 17-December-2015

Ware LB et al AJRCCM Articles in Press. Published on 17-December-2015

Long-Term Ozone Exposure & Respiratory Diseases

Critical Care (2017) 21:257

Managing the Scale of Clinical and Biologic Data

Single cell

sequencing

Sampling

multiple organs

Sequencing in

millions of patients

Multiple points per

patient per day

Trillion Data Points

Sep 2018

Supervised learning algorithms to uncover the relationship

between patient clinical features (such as laboratory tests and vital

signs) and mortality in order to predict the outcome in future cases.

Crit Care Med 2017

Area under the receiver operating characteristic

(AUROC) curves for predicting sepsis 4 hr in advance.

Extraction and Machine Learning:

A total of 65 features from the EMR and bedside

monitoring data

Machine learning–based tools embedded

within EMR improve early detection and

prompt treatment in those with early

sepsis and can predict septic shock

Sep 2018

Unsupervised learning algorithms used to uncover naturally

occurring groupings or clusters of patients based on their clinical

characteristics, without targeting a specific outcome

Patient Heterogeneity

Differences in categorical variables

based on phenotype assignment

Differences in the standardized values of each variable by

phenotype on the y-axis, with the individual continuous

variables along the x-axis

ALVEOLI

ARMA

* *

**

JAMA May 19, 2019

Derivation cohort: 20.189 patients with sepsis

Validation cohort: 43.086 patients with sepsis

IL-6

Inflammatory Cytokines Across

Phenotypes

Short-term Mortality by Phenotype

Big Data is Real World Data

Differences with RCTs

Type

Results

Population

Monitoring

Randomization

Cost

Observational

Effectivity

No restrictions

Not Necessary

No

Cheap

Hospital / Critical Care

of the Future

Heterogeneity & Personalization

Data

Information Technologies & Prediction

Humans

Information Technologies & Devices

Information overload

ICU ITs

Lack of Information !

The Connectivity Envelope of the Future ICU

Halpern NA. Chest 2014;145:903

No patient data continuity

Different manufacturers

Different communication protocols

Lack of interoperability

Specific hospital department solutions

ICU & Information: Today

Medical Devices

Capture, integration and

processing system

20

15

Real time webview

HIS

Asynchronies

database

ICU clinical

practice

IEE

DC

Data analytic tools

+offline review

Patient bedside

ICU clinical data

HL7

storage

Waveforms

repository

Research

Monitoring in the Era of

Precision Critical Care

Respir Care 2018;63:464-478

International Journal of Medical Informatics 112 (2018) 166–172

Flow of the data. Relationship between the Clinical

Information System and ICU-DaMa.

Minimum Datasets

& Quality Metrics

The Future

Blanch L et al. Intensive Care Med 2015;41:633-641

Asynchrony index (AI) % per hour in 4 patients

Asynchronies are difficult to predict !!

1.010 p. with ARDS

In 67 ICU MV patients we

analyzed 9,251 h of MV

(9,694,573 breaths)

Double cycling

occurred in 0.6%.

Crit Care Med 2018; 46: 1385–92

Effect of Double Cycling on Tidal Volume

67 patients, 9,251 hours, 9,694,573 breaths

↑↑Strain

↑↑Stress

de Haro C et al Crit Care Med 2018;46:1385–92

Precise Information on DC is Lacking

In 7 hours

10620 10640 10660 10680 10700 10720 10740

0

1

2

3

4

nu

mb

er

of D

C

Power = 61 Duration (min) = 26

AUC = 30.5

2 min

Clusters of Double Cycling & Breath Stacking

* *** ** ** *

de Haro C et al. CCM 2018;46:1385-92

Male 39y. Moderate ARDS. 24 h MV. SAS 2-3. Day 1 (12.09pm)

Data Analytics in ICU

Sci Rep. 2018 Dec 4;8(1):17614

Sci Rep. 2018 Dec 4;8(1):17614

State transition for the Poisson hidden Markov models from the

time series indexed each 15 min.

Transition probability matrixState transition diagram

Male 39y. Moderate ARDS. 24 h MV. SAS 2-3. Day 1 (12.12pm)

Hospital / Critical Care

of the Future

Heterogeneity & Personalization

Data

Information Technologies & Prediction

Humans

Cross Disciplines = Cross Fertilization

Early Neurocognitive Rehabilitation in Intensive Care

Project funded by La Marató TV3 2010

Multidisciplinary Team

ENRIC at ClinicalTrials.Gov

JAMA October 24, 2018

Reduce job strain prevalence by improving the ability of ICU

nurses to cope with stressful situations:

Progress in the management of potentially iatrogenic situations

Analyze stress & emotions felt by nurses dealing with a difficult situation

Manage the quality of team relationships

Simulated scenarios

Debriefing sessions that discussed soft skills and practices

Conclusions: Among ICU nurses, an intervention that included education,

role-play, and debriefing resulted in a lower prevalence of job strain at 6

months compared with nurses who did not undergo this program

Humans & Artificial Intelligence

Artificial

Intelligence

(AI)

AI is the ability of computers to replicate

tasks that only humans could do in the past

Toll E. JAMA, June 20, 2012

physicianartist

family

Muchas Gracias !!