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Data utilization helps to reduce costs and improve patient care: Case TAYS

The healthcare industry is experiencing fundamental transformation as it moves from a volume-based business to a value-based business. With increasing demands from consumers for enhanced quality of care and increased value, healthcare providers and payers are under pressure to deliver better outcomes.


The cost dynamics of healthcare are changing, driven by people living longer, the pervasiveness of chronic illnesses and infectious diseases, and defensive medicine practices. New market entrants as well as new approaches to healthcare delivery are increasing complexity and competition on the field. This requires finding new procedures and applying modern technologies, such as modern data analytics to help healthcare professionals to work in a more productive and efficient way.

- Analytics can provide the mechanism to sort through the torrent of health care related data, and help organizations deliver on growing demands. One should remember, though, that health care professionals are always needed to make decisions and act based on new information provided by analytics.

 

Data analytics helps to automatically identify patients with long term multiple illnesses

Tampere University hospital is one of the biggest hospitals in Finland, providing demanding and highly specialized health care services to over one million Finns. With the recognition of health care industry being deep in transformation, the hospital wanted to explore new possibilities of analytics and data utilization in order to improve their overall competitiveness.

Together with Quva Oy, a company specialized in providing analytics and software solutions, the hospital started a pilot project in order to find out how analytics could help them to operate in more productive ways. With Quva’s machine learning and data analytics, the hospital was able to recognize that resources were scattered and unequally divided; only 10 % of all the patients caused nearly 70 % of the total costs, significant number of patients having multiple, long term illnesses.

- In general there are effective care protocols for different individual illnesses, but in case of a patient with multiple, long term illnesses, there is severe need to come up with more centralized and focused patterns. In the future, it is crucial that we are able to better identify the multiple illness patients early on, in order to better allocate our resources and provide preventive care, clarifies Erkki Kujansuu, The Chief Administrative Physician in Tampere University Hospital.

 

Data has no limitations

Quva Oy`s CEO, Emil Ackerman, encourages the health care industry to carry out similar pilot projects. Being able to put together all the pieces of data, such thing that no human can do, helps, for example to see, totally new, even surprising correlations affecting the entire operations. Advanced analytics can support health care in various ways, such as:

  1. Automatically identify patients with long term, multiple illnesses from the certain occurring data patterns
  2. Point out the patients that are moving along care process in a non-efficient way
  3. Recognize the previous patient cases with similar illnesses automatically from the history data
  4. Understand which factors might have caused certain patient security related incidents and close calls
  5. Forecast patients’ risk to have or get multiple illnesses



What we accomplished with this particular pilot project was the great amount of detailed, readily interpreted data, that we were able to understand, allowing us to utilize it effectively in decision making in the future - to improve and optimize overall operations, reduce costs, improve patient care and customer experience.

Erkki Kujansuu, MD, PhD, Administrative Medical Director, Pirkanmaa Hospital District

The collaboration with Quva Oy was outmost excellent. They took initiative, listened us carefully and communicated with us by using such terminology that we could easily understand. They presented their methods and analytic tools in great detail, and what even more important, actually showed us not only their means but the concrete results achieved by applying them into action. In the very short timeline, Quva experts were able to create credible patterns from the data to identify patients with long term, multiple illnesses as well as to produce concrete information related to challenges experienced during the identification process.

Doris Holmberg- Marttila, Chief Physician, Tampere University Hospital


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Quva Oy

Business ID: 2348506-3

Address: Sumeliuksenkatu 18 B
33100 Tampere, Finland

Electronic invoice address: 003723485063

Vertrieb

Emil Ackerman 
+358 45 2086 816 
emil.ackerman(at)quva.fi

Juho Liljeroos
+358 40 7418 498
juho.liljeroos(at)quva.fi

Andere Kontakte: 
firstname.lastname(at)quva.fi

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