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UID:3792-2675@rg-trier-luxemburg.gi.de
CLASS: PUBLIC
SUMMARY:AI4Health Lecture Series: Markus Lingman and Mattias Ohlsson
DESCRIPTION:The next talk of the AI4Health lecture series will continue on 
 November 11 with a talk on "Information driven healthcare in Halland" by Ma
 rkus Lingman and Mattias Ohlsson (Region Halland/Halmstad University, Swede
 n).\n\nInformation driven healthcare in Halland\n\nRegion Halland in Sweden
  is the main healthcare provider for the county of Halland (about 330 000 i
 nhabitants). Region Halland realized early on the potential impact of infor
 mation driven healthcare; using data and data analytics to improve the heal
 thcare system. Region Halland have during the last ten years developed and 
 maintained a comprehensive healthcare data infrastructure covering clinical
  and administrative information pertaining to every consumer in Halland of 
 healthcare with public funding. This means approximately 500 000 patients t
 reated in Halland now and in the past and includes all the Region’s care de
 livery units and also the pharmacies. Work is ongoing to include the munici
 palities, who have responsibility for e.g. elderly care. Halmstad (Regional
  Capital of Halland) University, and in particular CAISR (Centre for Applie
 d Intelligent Systems Research), have had a longstanding and seamless colla
 boration with Region Halland with the focus on applying AI and machine lear
 ning towards information driven healthcare solutions. This work also includ
 es collaborations with international partners (e.g. Harvard Medical School 
 and Brigham Women’s Hospital in Boston). Over the last years, Region Hallan
 d has been able to cut costs in the healthcare service at the same time as 
 the population has grown and there has been a substantial increase in patie
 nt arrivals to the emergency departments. Also medical quality of care has 
 improved. The efficiency improvement has been achieved e.g. by reducing hos
 pital bed days without affecting occupancy levels, by decreasing the admiss
 ion rates to the hospital, and increasing the fraction patients that can be
  discharged early. Many of these achievements were enabled by using informa
 tion driven healthcare, by introducing data analytics and better prognostic
 s for the management of the healthcare system. For 2019, Region Halland is 
 one of only two regions in Sweden that do not show a large economical defic
 it in the healthcare service. Several regions are flagging for large staff 
 layoffs in their healthcare systems for 2020. Detailed and comprehensive ca
 re data, together with modern AI and analysis tools, play an important role
  in delivering effective care by facilitating healthcare providers to to cr
 eate actionable insights and take better informed decisions. What is also r
 equired is a methodology and organization on how to systematically work wit
 h information driven improvement work around quality and productivity where
  the goal is to understand how the patient is affected in the healthcare sy
 stem. Region Halland have developed a model for organization, working metho
 ds and a nine-step process on how to go from idea, to follow-up of an imple
 mentation of a change in the health care system. The model gives the decisi
 on maker a powerful tool to choose the initiatives that give the best resul
 ts at the system level. This includes creating agile multidisciplinary team
 s around system issues and use the nine-step process for a data-driven impr
 ovement work that considers all the necessary aspects including production,
  quality and economy with the highest possible degree of detail. We will pr
 esent how Region Halland works with information driven healthcare, both how
  to find insights and to get them implemented, and show research projects a
 nd results that have emerged through the collaboration between Region Halla
 nd and CAISR at Halmstad University. We also present ongoing work in develo
 ping methods and infrastructure for distributed machine learning, such that
  medical databases located at different healthcare provides can be utilized
  when creating AI and machine learning solutions related to information dri
 ven healthcare.\n\n- See more at: https://acc.uni.lu/ai4health/\n\n\n\nWe i
 nvite you to join this Webinars.\n\nMeeting link: https://unilu.webex.com/u
 nilu/j.php?MTID=m060774148c89025957b2831d3031c1fc\n\nMeeting number (access
  code): 163 267 6786 Meeting password: UL-AIForHCWebs\n\nHost key: 478625 \
 n\nSee more at: acc.uni.lu/ai4health
LOCATION:Online
DTSTAMP:20200928T094948Z
DTSTART:20201111T150000Z
DTEND:20201111T170000Z
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