Five Tips To Improve Healthcare Data Integration | Healthcare Business Solution
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Five Tips To Improve Healthcare Data Integration

Five Tips To Improve Healthcare Data Integration
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As per a recent Google Cloud Survey, 96% of physicians have agreed that easier access to critical data could save lives. That is the growing importance of data-led decision-making in the healthcare field. Integrating data from different fields and formats is the first step in this process. We will look at five tips to do that effectively.

Why is Data Integration Important


It helps to reduce the costs and problems of building interfaces between different systems.  


Speed enhances interoperability. Data integration allows patient data and information to be shared with medical professionals in emergencies. With this, you can accurately identify risk factors and speed up diagnosis.


Data Integration improves decision-making as one gets a unified picture of the patient’s medical history. This could lead to better health outcomes.  


Faster, accurate medical data in public hospitals can lead to more equitable health services for all patients – irrespective of age, income level, gender, ethnicity, etc.  

Tips For Integrating Healthcare Data Systems

Gathering Right Data

The right questions need to be asked to understand the real-time data needs of healthcare professionals. Re-design and integrate systems as per those needs. Examples of some right questions are: what is the priority of the priority of your specific health system – Is it improving patient care quality or reducing the death rate? 

Prioritize APIs

As there is a large diversity in the medical field data, prioritize API-enabled infrastructure. API improves interoperability. It connects better the standardization of data, services and platforms. 

Going Cloud-native

Integration is hard in the medical field as medical data is often fragmented, coming in many formats from different sources. A cloud-native hybrid solution is the best to deal with this issue. 

Data Lakes For Large-Scale Storage

Data lakes can hold huge amounts of raw data in their native format. You can run analytics on it without moving data to a separate analytics system.

One Size Does Not Fit All

Most times, decision-makers in healthcare have no or little access to the data they like. You can design data access systems keeping all decision makers in mind.

As data has become the most needed resource in the medical field as well, integrating all kinds of data and making it easily available becomes crucial for the well-being of patients and society as a whole.

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