Overall decision-making in the digital medical environment

Intelligent data integration can help improve the quality of data-based decision-making, especially when clinical decision-makers face multiple obstacles and challenges in the patient’s path. This is critical in today’s digital healthcare environment, where the quality of decision-making depends on the quality and availability of basic data.

In medicine, decision-making has a clear goal: to benefit patients. Healthcare decisions depend on professional standards, expertise, patient wishes, and treatment possibilities.

Achieving this goal increasingly relies on the intelligent use of medical data. The ever-increasing range of multi-dimensional health data from electronic medical records, image databases, and other multi-level, often fragmented IT systems is becoming more and more important for making up-to-date, patient-oriented decisions and designing care.

Of course, not all medical decisions are necessarily difficult. In some simple health care situations, professional medical knowledge is enough to find expedient solutions, so the decision is simple. As the number of diagnosis and treatment options increases, as well as the amount of relevant patient data and the risk of complications, decision-making becomes more complex.

The challenge in complex cases is to integrate extensive data from various sources, such as clinical, radiological or laboratory information; genetic and pathological results; and insights into behavioral and social conditions, so that decision-making meets the highest possible quality standards, and consider To the patient’s personal situation and preferences.

From the initial clinical contact to follow-up, medical decision-making runs through the entire nursing process. The problems that health care providers need to address are:

• What needs to be done in diagnosis and treatment?
• How to effectively use my resources in the process?
• With whom should I share information and coordinate to achieve the best results for the patient?

Digital technology can improve all these aspects of decision-making and provide valuable decision support for patient paths.

For various reasons, complex decisions may fail. Patient data may be inaccessible or too extensive and unstructured. Information may be ignored. The guidelines may not be fully implemented. These challenges can lead to inefficient and costly workflows and affect clinical outcomes.

However, they can be solved by a scalable and flexible digital platform that can collect patient data from various IT systems and institutional sources, and allows caregivers to easily access patient data at all touch points in the patient’s journey. This intelligent data integration can ultimately provide a more comprehensive patient situation and support overall decision-making in the medical field.

Today’s IT architecture must be able to evolve and grow as requirements change.

Siemens Healthineers designed its digital health platform as a flexible tool that can use increasingly important data for healthcare. Its integrated marketplace provides one-stop access to a growing number of proprietary applications and partner applications that have been planned and pre-reviewed to provide advanced and customized digitization for a wide range of healthcare providers and care situations.

Digitization is of course not only a technical issue, but also a conceptual issue. Healthcare is increasingly using large amounts of complex health data, and three changes will promote digital transformation:

1. Healthcare providers need a digital infrastructure that is as simple as possible, versatile and adaptable: ideally a system-wide platform for network data.
2. Suppliers need more and more intelligent applications to meaningfully apply networked data to specific operational and clinical problems.
3. As digitalization changes the nature of medical decisions, such decisions will continue to be the responsibility of doctors and patients. Nonetheless, healthcare providers will increasingly utilize advanced digital decision support, incorporate large amounts of data into their deliberations, and use it in profitable ways.

Learn more about how Siemens Healthineers supports intelligence Data integration and decision support Follow the patient path.

This content was produced by Siemens Healthineers. It was not written by the editors of MIT Technology Review.