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Healthcare systems are evidence based, and new evidence is always emerging, so agility should be part of a health system's operational mode. Yet if handling of the COVID-19 pandemic teaches us anything about health systems, it is that they are slow to adapters. This problem is general because emerging threats are not limited to viral pandemics, but can also include natural and unnatural disasters, new evidence about the safety and/or efficacy of drugs and devices, changes to medical supplies and more. All of these require healthcare providers to adapt their practice.

Adapting to change without breaking a complex system like a hospital requires, firstly, detecting the change, and secondly measuring the impact of change on performance. In other words, did the changed practice make patients better or worse?

The Piano research automation system can perform both tasks. It has

  • a growing repository with dozens of research projects for detecting and measuring changes in recent times, supporting clinicians looking for predictors for new conditions, and measuring patient outcomes;
  • flexible interfaces that let clinicians explore and modify research parameters without requiring advanced data skills to adapt research projects to new threats; and
  • automated evidence updates that quickly and accurately reproduce research and quickly provide feedback about the risks and effects of changes in practice.

Further Reading: Algorithm-based clinical quality improvement. Clinical guidelines and continuous quality improvement.

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