PowerPoint Presentation · C2C – the eHealth Company From the radiological archive to the...
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Transcript of PowerPoint Presentation · C2C – the eHealth Company From the radiological archive to the...
Fraud by patient identity theft leads to
economic losses
Un SECOND VICTIMS Clinicians suffer with errors that harm the patient’s health
Una incorrecta identificación supone 50% less errors with id wristbands, but still…
236 reports in 2 years of patient harm related to loss of id
wristbands or wrong data on them.
24,000 reports in 1 year of wrong identified
patients.
5.59% of the NHS healthcare spending in patient identity
theft
Patients identified by
iris, fingerprint, and /or face
UMANICK Identity 4 Health
A suite of integrated products
It can work stand alone, or
Integrated with other hospital software and systems with:
- HL7
-UMANICK Identity SDK
-UMANICK Identity API, through web services
UMANICK Identity 4 Health
Easy to deploy and integrate
•Logical access to medical
records
•Physical access
UMANICK Identity 4 Health
to identify hospital staff:
UMANICK Identity WorkBench
Desktop version – Fingerprint recognition
UMANICK Identity WorkBench
Desktop version – Face recognition
UMANICK Identity WorkBench
Desktop version – Iris recognition
UMANICK Identity Portal
Web version – Fingerprint recognition
UMANICK Identity Mobile
APP tablets & smartphones: Face identification
UMANICK Identity Mobile
APP tablets & smartphones: Iris identification
Customers already trust UMANICK:
NEUTRAL-IZE YOUR PACS
Óscar López
C2C – the eHealth Company
From the radiological archive to the universal medical imaging repository
PACS
Universal imaging repository
Hospital
PACS
Dermathology ECGs
Ultrasound
Radiology
Endoscopy
Ophthalmology
Hospital
Electronic Patient Record
Hospital
Enterprise Imaging Environment
Hospital Hospital
Hospital
Hospital
Hospital
Hospital
Collaboration Environment
PACS limitations
• DICOM only
• Radiological viewer
• Sharing content out
• Web access
• Multi PACS interoperation
• Storage from mobile devices
• EMR integration
• …
How to solve
this limitations ?
Image credit: Michael Gray
VNA images and objects services bus
Anatomical Pathology
NIKON Coolpix 995
OLYMPUS DP12
OLYMPUS DP71
Cardiology
CARDIOPLUS Cardiotest Plus
GE VIVID 3 / VIVID 4 / VIVID 5
GE VIVID e / VIVID i
GEM-MED Gem Heart One
GEM-MED Gem Heart One+
HP SONOS 5500
MORTARA ELI 150 / ELI 210
MORTARA ELI 250 / ELI 350
NIHON KOHDEN CardiofaxS ECG-
1250K
PHILIPS PAGEWRITER TRIM II
PHILIPS PAGEWRITER TRIM III
PHILIPS SONOS
QRS Universal EGC
Digestive System
FUJI-FUJINON System 4400
Processor
OLYMPUS Exera CV-145
OLYMPUS Exera CV/CLV-160
Gynaecology
GE Voluson 730 Expert
OLYMPUS OTV-S6 CLV-S30
TOSHIBA Aplio 25
TOSHIBA Aplio 50
TOSHIBA Nemio 10
TOSHIBA Nemio 20
TOSHIBA PowerVision 6000
TOSHIBA SSH-140A
Hematology
NIKON DS-Fi1
Laboratory
RADIOMETER NPT7
Neurology
TOSHIBA Nemio
Ophthalmology
TOPCON CL-100
TOPCON CT-60
TOPCON KR-8800
TOPCON TRC-50IX
TOPCON TRC-NW5S
ZEISS HFA 740i
ZEISS HFA 745
ZEISS HFA II 750i
Anatomical Pathology / Cardiology / Dermatology / Digestive System/ Gynaecology / Hematology/ Laboratory / Neurology / Ophthalmology / Ear, Nose and Throat / Surgery / Radiology / Traumatology / Urology
MIO LT™ - Integrated devices
Surgery
KARL STORZ PC-Aida 20093301
PHILIPS BV Libra
PHILIPS BV-300
STRYKER Striker Digital Capture
Radiology
FUJI FCR Capsula XL
SIEMENS ECAT
SIEMENS Multistar Top
SIEMENS Magnetom Impact
SIEMENS Polycat
Traumatology
GE LUNAR
Urology
OLYMPUS OTV-S6/CLV-S30
OLYMPUS VISERA OTV-S7/CLV-
S40
PHILIPS ATL Ultrasound
PHILIPS HDI 4000
TOSHIBA USBUA240A
Dermatology
CANON PowerShot A620
FOTOFINDER Dermoscope HD
NIKON Coolpix 4500
NIKON Coolpix 5400
NIKON Coolpix 8400
OLYMPUS E330
Ear, Nose and Throat
APPLITEC MSV-2000
FUJINON System 2200
KARL STORZ Celicam Dxpal
202320/20
OLYMPUS Exera CV/CLV-160
OLYMPUS Exera EV/CLE 145
OLYMPUS OTV-SC CLH-250
Ophthalmology
ALCON OCUSCAN RxP
ALCON ULTRASCAN
BAUSCH & LOMB TECHNOLAS 217
BAUSCH & LOMB ORBSCAN
BAUSCH & LOMB ZYWAVE
CANON CR6-45NM
CANON GF-60V
HAAG-STREIT BQ 900
INDO NIDEK AOS-1100
INDO NIDEK ARK-700
INDO NIDEK ARK-2000E
INDO NIDEK LM-820
INDO NIDEK LM-990
INDO NIDEK RT-2100
RIS/PACS
Hospital
< My patients
My images > DICOM Worklist>
< DICOM Worklist
App
TOMA™ - Transfer Objects to Medical Archives
MIO TOMA™
< WEB SERVICES / DICOM >
EPR +
MIO WADO
· Query & Retrieve of DICOM Studies
· MultiPACS integration
· Management tools
· High availability
· Prefetching and preparation of the studies
· Optimized for MedViewer (Universal clinical viewer)
MIO WADO™
C2C - The eHealth company – HiMMS CIO Summit - 15/10/2015
Anatomical Pathology (Server rendering)
Cardiology (DICOM Waveform)
C2C - The eHealth company – HiMMS CIO Summit - 15/10/2015
C2C - The eHealth company – Presentación Corporativa - 15/10/2015
Other “–ologies” (Opthalmology, Dermatology, Digestive…)
C2C - The eHealth company – Presentación Corporativa - 15/10/2015
MEDTING Clinical Collaboration
“CUIDISS“ HACIA LA MEDICINA PERSONALIZADA “CUIDISS“ TOWARD PERSONALIZED MEDICINE
Marcelino Alonso
Intellihealth Technologies Manager
Introducción
Modelo Asistencial
Claves
Objetivo
Proyecto Cuidiss
Sumario / Summary
Introducción
Sumario Sumario / Summary
Desafíos Desafíos / Challenges
Desafíos Desafíos / Challenges
Participativa / Participative
Personalizada / Personalized
Predictiva / Predictive
Preventiva / Preventive
Introducción
Propuesta de valor
Sumario / Summary
Offer of value
Propuesta de valor …..
Offer of value …..
Quality
Costs Accessibility
Conclusión: “nueva Propuesta de Valor”
Conclusion: " new Offer of Value "
Possible
• Identificar necesidades y riesgos
– Estratificar
– Predecir
• Apoyar la toma de decisiones
– Clínicas
– Proceso vs gestión población
• Mejorar la investigación / innovación
– Mas enfocada
– Menos cara
– Comprobación efectividad: impacto clínico y social
Medicina Personalizada / Personalized Medicine
Introducción
Modelo Asistencial
Sumario / Summary
Health Care Model
Cambio de modelo / Paradigm shift
Claves del cambio “red proactiva”
Keys of the change " proactive network "
GESTIÓN POBLACIONAL
Population Management
Asistencia en Red
Sistemas Información
Análisis datos
Gestión proactiva
Evidencia científica
Mejores prácticas
Claves del cambio “Buenas prácticas y TiCs”
Keys of the change " Best practices and Tics "
Network Assistance
IT Systems
Analysis of Data
Proactive management
Scientific evidence
Best practices
Introducción
Claves del cambio
Sumario / Summary
Keys of the change
Cultural
Tecnológico
Análisis
Información
Cambio de modelo Paradigm shift
Analysis of Data
Technological
Cultural
Tecnológico
Análisis
Información
Cambio de modelo Paradigm shift
Cambio de modelo vs. “un trabajo Departamental”
Paradigm shift vs. " a departmental work "
Cultural
Tecnológico
Análisis
Información
Cambio de modelo Paradigm shift
Technological
Telemedicina 5/8
Cultural
Tecnológico
Análisis
Información
Cambio de modelo Paradigm shift
Analysis of Data
Cambio de modelo vs. “Información masiva”
Paradigm shift vs. " Mass information "
Cambio de modelo vs. “Nuevas Herramientas”
Paradigm shift vs. " New tools "
Proyecto
Cuidiss
Sumario / Summary
CUIDISS Project
Cambio de modelo vs. “Nuevas Herramientas”
Paradigm shift vs. " New tools "
Población
SIP
Demografía
Morbilidad (HIS)
Atención ambulatoria
Alternativas hospitalización
Hospitalización
Bloque quirúrgico
Gastos variables
Biopatologia
Farmacia hospitalaria
Farmacia de receta
Atención Primaria
E-health
Cambio de modelo un “Real Data World”
Paradigm shift --- " Real Data World "
