Mark your calendars: the next Clean Sweep Live Auction will be on Thursday, June 21st Click to view the full catalogue

DOTmed Home MRI Oncology Ultrasound Molecular Imaging X-Ray Cardiology Health IT Business Affairs
News Home Parts & Service Operating Room CT Women's Health Proton Therapy Endoscopy HTMs Mobile Imaging
Ubicación actual:
> This Story

Conexión o Registro to rate this News Story
Forward Printable StoryPrint Comment



Cardiology Homepage

William Kozy LivaNova welcomes new board of directors member

Philips to acquire EPD Solutions for approx. $295 million Company has its eye on the EUR 2+ billion cardiac arrhythmia ablation market

FDA greenlights Neural Analytics' NeuralBot System Assesses risk of stroke and other neurological conditions

New algorithm predicts impact of heart transplants on survival in heart failure patients Acquires information based on 53 data points to predict rate and length of survival

Timothy J. Arens Surmodics announces leadership change and appointment of interim CFO

Early discharge associated with better outcomes after TAVR Researchers find that discharging patients within 72 hours yields clinical benefits

New tool predicts readmission among TAVR patients Recorded a score of 212 associated with a readmission rate of more than 30 percent

Penn Medicine performs first cardiac ablation procedure with the AcQMap system in US Patient is recovering nicely

How 3D printing could reduce complications after TAVR Using the pre-procedure CT data to create a model that can be implanted with a valve

Opportunities and challenges with 3D printing in cardiology A world of potential but costs remain a barrier

Hitachi and Partners Connected Heart
are utilizing AI to predict with higher
accuracy hospital readmission risks
among heart failure patients

Hitachi and Partners Connected Health assess readmission for heart failure with AI

por John R. Fischer , Staff Reporter
Hitachi Ltd. has teamed up with Partners Connected Health in a collaboration overseeing the use of artificial intelligence in predicting the risk of hospital readmission among heart failure patients, with explanations for its reasoning.

The Japanese-based company is utilizing its AI technology to predict with high accuracy which patients are most likely to be readmitted within 30 days of their initial release with those selected then enrolled into Partners Connected Cardiac Care Program, a remote monitoring and education program for patients with heart failure.

Story Continues Below Advertisement

Servicing GE Nuclear Medicine equipment with OEM trained engineers

We offer full service contracts, PM contracts, rapid response, time and material,camera relocation. Nuclear medicine equipment service provider since 1975. Click or call now for more information 800 96 NUMED

“The reason to limit the research target to a certain illness is to avoid complicating the problem. The reason to choose cardiac patients is that its number of patients is large, and it is a representative illness for higher medical cost from readmission,” Toru Hisamitsu, project manager of the collaboration for Hitachi, told HCB News. “It's not a challenge that is just limited to heart failure. We think that providing high quality and suitable medical care for every patient is required and the importance of value-based health care is receiving attention worldwide.”

The thirty-day readmission rate is an important aspect of hospital management and one that can incur penalties for hospitals from the U.S. Centers for Medicare and Medicaid (CMS) in accordance with the Affordable Care Act (ACA).

The Partners Connected Health innovation team simulated the readmission prediction program among heart failure patients participating in CCCP, while Hitachi used its AI technology to construct the prediction model.

The results of the project were compared to information on approximately 12,000 heart failure patients hospitalized and discharged by Partners HealthCare hospital network in 2014 and 2015. The prediction algorithm displayed a high accuracy rate of 0.71 in area under the curve (AUC) and proved it could significantly reduce the number of patient readmissions with an expectation of approximately $7,000 saved per patient per year among the cohort of CCCP patients.

The technology also extracts factors of information from each patient that contributed to the predictions, allowing it to explain its reasoning to enable physicians to make better medical decisions for clinical practice.

Both companies plan to conduct a joint study to evaluate the prediction program by clinicians and examine how to integrate it within clinical workflows.

“PCH will investigate the optimization of its care program based on the risk factors extracted by Hitachi's AI for the cardiac patients who have higher risk to readmit,” Himatsu said. “Also, Hitachi will investigate the brush-up of the AI algorithm for it. At the end, we will contribute to the improvement of medical treatment and the realization of cost reduction by providing [care] that [is] suitable to each patient.”

Back to HCB News
  Pages: 1

Cardiology Homepage

You Must Be Logged In To Post A Comment

Aumente su conciencia de marca
Subastas + ventas Privadas
Consigue el mejor precio
Comprar Equipo/Piezas
Encuentra El Precio Más Bajo
Noticias diarias
Lee las últimas noticias
Examina todos los usuarios DOTmed
Ética en DOTmed
Ver nuestro programa de ética
El oro parte programa del vendedor
Recibir las solicitudes de PH
Programa de distribuidor con servicio gold
Recibe solicitudes
Proveedores de atención de salud
Ver todos los HCP (abreviatura de asistencia médica) Herramientas
Encontrar/rellenar un trabajo
Parts Hunter +EasyPay
Obtener presupuestos para piezas
Certificado recientemente
Ver usuarios certificados recientemente
Recientemente clasificado
Ver usuarios certificados recientemente
Central de alquiler
Alquila equipos por menos
Vende equipos/piezas
Obtén más dinero
Mantenga el foro de los técnicos
Buscar ayuda y asesoramiento
Petición sencilla de propuestas
Obtén presupuestos para equipos
Feria comercial virtual
Encuentra servicio para el equipo
El acceso y el uso de este sitio está conforme a los términos y a las condiciones de nuestro AVISO LEGAL & AVISO DE LA AISLAMIENTO
Característica de y propietario DOTmeda .com, inc. Copyright ©2001-2018 DOTmed.com, Inc.