Fresenius Medical Care: Enabling Patient Care Solutions with Near Real-Time Data-Driven Insights

Fresenius Medical Care innovates with breakthrough technology using clinic medical information system data from a dialysis machine at the clinic site. The point of care device embeds the models into the edge with Kafka feeds so that the clinic can react to patients dialysis treatment. The Kafka events feed into Kinesis Data Streams, AWS Lambda, Kinesis Data Analytics, and SageMaker visualized with Elasticsearch Service in Kibana for the near real-time feed of the patient treatment. The machine data set is used to detect the patient's blood pressure to predicting their dialysis and provide proactive measures of treatment. The data is also streamed into Amazon Kinesis Data Firehose and aggregated with the data warehouse ingested by Glue and into S3 Data Lake for further data analysis and modeling by the data scientist to discover additional predictive models for patient care.
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[@velumani3760]

Very nice explanation

[@pankajkarmakar7782]

Nice model to inject data through kafka and then analysis also use firehose to store to s3. It would be Interesting to know what raw data format is used (like avro, parquet orc because avro is not good for analysis) and which DB user. 👏👏 Good explanation. Liked her punch line word - SURE!! 😅

[@kc310]

When will Amazon Care (Virtual Healthcare) become available for Amazon customers?

[@Gvozd111]

Thanks for sharing! What’s the benefit of having kafka in front of the kinesis?

[@mrsaloomtv707]

Kafka is managed streaming for Apache Kafka , it uses Apache Kafka and kinesis Is used in streaming data with real-time analytics so you can see analytics in real time