In today’s digitalized healthcare system, the quality of decision making depends on the quality and availability of the underlying data. Intelligent data integration can help improve the quality of data-driven decision-making, especially in scenarios where clinical decision-makers face multiple obstacles and challenges along the patient journey.

In medicine, decision-making has a clear goal: for the benefit of the patient. To achieve this goal, the intelligent use of medical data is increasingly important.

Of course, not all medical decisions are necessarily difficult. In some uncomplicated care situations, professional medical knowledge is sufficient to find a meaningful solution so that decisions are easy. Decision-making becomes more complex, however, as the number of diagnoses and treatment options, the volume of relevant patient data, and the risk of complications increase.

The constantly growing, multidimensional range of health data from electronic medical records, image databases and other multi-layered and often fragmented IT systems is becoming more and more important in order to make contemporary, patient-oriented decisions and to design care processes accordingly.

The challenge in a complex case is to integrate a wide variety of data from different sources. Clinical, radiological and laboratory information; genetic and pathological findings; and insights into behavioral and social conditions should contribute to a decision that meets the highest possible standards and takes into account the personal situation and preferences of the patient.

Medical decisions are made along the continuum of care, from initial clinical contact to follow-up care. The questions healthcare providers need to ask themselves are:

  • What do I have to do diagnostically and therapeutically?
  • How can I use my resources efficiently in the process?
  • Who should I share and coordinate information with in order to achieve the best possible outcome for the patient?

Complex decisions can fail for various reasons. Patient data may not be accessible or it may be too large and unstructured. Information could be overlooked. Policies may not be adequately executed. These challenges can lead to inefficient and costly workflows and affect clinical outcomes.

However, such challenges can be solved with a scalable and flexible digital platform that collects patient data from sources in various IT systems and institutions and enables nurses easy access to patient data across all touchpoints of the patient journey. Intelligent data integration can ultimately provide a more comprehensive picture of the patient and support holistic decision-making in medicine.

Healthcare is increasingly using the full spectrum and mass of large and complex health data, and three changes will make this change even broader:

  • First, healthcare providers need a digital infrastructure that is as simple as possible, but also versatile and adaptable: ideally, a system-wide platform for networking data.
  • Second, providers need a growing number of intelligent applications that can meaningfully apply networked data to specific operational and clinical issues.
  • Third, as digitization changes the way medical decision-making is made, such decisions will continue to be the responsibility of doctors and patients. Nevertheless, healthcare providers will increasingly have to resort to advanced digital decision-making aids in order to incorporate the wealth of data into their considerations and use them profitably.

Siemens Healthineers designed its digital health platform as a flexible tool that uses the increasingly important data for health care. The integrated marketplace offers access to a growing number of proprietary applications as well as curated and pre-checked partner applications from a single source, thus enabling advanced and tailor-made digitization for a variety of healthcare providers and care situations.

Find out more about how Siemens Healthineers supports healthcare providers with solutions that support intelligent data integration and decision-making along the patient path.

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