Columna Patient Flow is a solution that supports the day-to-day work and decision-making of clinics on the care pathways of bedbound patients.


Columna Patient Flow



Columna Patient Flow allows the coordinating nurses to gain an overview of admitted patients and their allocation at the hospital.

The machine learning solution Systematic Forecasting makes it possible to provide forecasts for the occupancy of ward beds and the duration of admissions. This is done by feeding a computer large volume of historical data for several years’ admissions by ward. Based on historical and current data, the computer identifies the methodology and deviations that form the basis of forecasts for the future duration and care pathways of admissions which contribute to improving individual care pathways and patient flow on a larger scale.

By integrating Columna Patient Flow with data from Johns Hopkins University the solution can also provide an overview over pandemics.

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  • Supports day-to-day work across hospital wards regarding care pathways
  • Provides an overview of the hospital’s bed occupancy now and later
  • Provides an overview of plans for transfers and discharges at ward level
  • Supports clinics in decisions that enhance each care pathway
  • Uses big data and machine learning technology to optimise forecasts on a day-to-day basis for clinics
  • Provides decision-making support in staff planning as regards to patient occupancy in the form of forecasts that contribute to enhanced resource planning and safer care pathways.


Supports bed occupancy overview and critical decision-making


Bed occupancy overview

Columna Patient Flow provides bed occupancy overview and decision-making support in the form of forecasts of patient occupancy. The aim is to support the ‘secure patient flow’ process and enrich it with decision-making support for the coordination of care pathways and resource planning with the goal of having the right number of staff at high occupancy. And correspondingly reducing staff numbers when forecasts estimate lower occupancy.

The best possible care pathways

Interdisciplinary collaboration between hospital wards is supported by focusing on the promotion of optimal (safe and effective) care pathways and utilisation of capacity to ensure that the right patient is in the right bed, gets the right treatment at the right time from the right treatment team. This is done through machine learning-based forecasts which are able simultaneously to highlight patients who are likely to be readmitted or experience complications during their admission. In this way, Columna Patient Flow supports the critical decisions that doctors and nurses have to make when a high-risk patient’s course of treatment needs to be planned, as well as supports the clinical practice in becoming more proactive rather than reactive.

Columna Patient Flow is a tool for clinics both in short-term here-and-now planning of capacity utilisation and in long-term staff planning.


It is an easily accessible system that continuously can be adjusted, and the entries are in real time. We also see that enhanced cooperation and greater understanding across hospital wards is now in place











Bed Occupancy Forecast Illustration 

The diagram above illustrates the way in which Columna Patient Flow uses historical data to produce a bed occupancy forecast for the rest of the day in a given ward. The diagram can be used to support clinician’s workflow when they must decide whether to do something about the current bed occupancy to prevent overcrowding later.


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