AI enabling better patient care leveraging data insights is making its way into every aspect of healthcare systems. Pluto7’s Healthcare services and ML solution is empowering the healthcare industry to be more predictive and proactive towards improving the overall patient experience. Leveraging key machine learning capabilities, this solution can impersonate the human cognition integration process and help analyze complex data sets. It provides prompt benefits to the processes that are standardized on a large scale. These solutions and services rely on a lot of data which exists across systems designed by various vendors needing data exchange. Interoperability hence continues to become critical in delivering impactful healthcare solutions. Following sections describe the various use cases which either currently or in future will rely on stronger interoperability as the need to exchange data across systems and platforms increases. 

Healthcare embracing machine learning capabilities

There are several developments that are majorly noticed in the healthcare industry over the past few months, solving the interoperability being the topmost among those. As per  Healthcare Information and Management Systems Society, Inc. (HIMSS), the definition of interoperability is stated as the ability of different information technology systems and software applications to communicate and exchange data. The patients’ data exchange in particular is focused on the increase in Health IT systems. The concept came about for the reason that the patients could have better visibility to their problems to which the healthcare system could respond on time with these specialized frameworks that used machine learning capabilities, defined by the implementation of Healthcare API by Google Cloud. 

Health Level Seven (HL7) is the Global Standards Developing Organization which is responsible for providing standards for healthcare interoperability. The Google Cloud Healthcare API is a route to intelligent analytics with machine learning competencies in Google Cloud. This is achieved with pre-built connectors for streaming data processing in Dataflow, scalable analytics with BigQuery, and ML with AI platforms. The Cloud Healthcare API is supported by Google Cloud’s security and privacy features which are HIPAA compliant. It is integrated with existing healthcare applications to ingest the HL7v2 messaging by interacting via fully managed REST APIs and web-friendly JSON format.

The attributes of the Cloud Healthcare API not just include being compliant with HIPAA but is also certified with HITRUST CSF. It provides a web-native, serverless scaling enhanced by Google’s infrastructure. 

Additionally, the Cloud Healthcare API is integrated with Apigee. The features of Apigee makes it ecosystem-ready and easy to use:

  • Pre-built healthcare assets
  • Compete developer experience 
  • Pre-deployed FHIR APIs
  • OAuth Integration 
  • Seamless communication with App Management

Google Cloud has long supported data interoperability and an API-based ecosystem to reduce friction surrounding healthcare data. Read complete story here.

Interoperability in Healthcare: The need of the hour

Looking back to a few years ago, all the records were maintained on papers requiring manual efforts and extended timings, and to access those, took another effort. Consider looking for an old record of a patient in between a whole bunch of files. To digitize the record management process was an initial positive step towards reducing the workload of human resources. Interoperability was a smart move taken to give better and overall visibility to the patients, healthcare systems, and healthcare providers. 

The patients would understand, get the desired help as and when needed and the healthcare systems would get the data silos in place, management becomes way easier. Not forgetting the holistic view of data management and ensuring the healthcare systems are able to get feedback regarding their services.

Now, let us talk about Healthcare ML. Pluto7 is a Google Cloud Premium Partner giving solutions on the same. As Smart Analytics, Machine Learning and Data Analytics experts, we develop powerful solutions to enable healthcare interoperability, breaking siloed systems. Our healthcare services and solutions provide our customers more control of their data, enabling new and different options to deliver top healthcare services. 

We leverage Google Cloud Healthcare API to improve clinical workflows for recruitment, matching and process optimization, optimize billing and payment determinations for clinical trials and other healthcare-related processes. 


DxTerity: Using data-driven precision medicine to combat autoimmune disease

Dxterity, a patient-centric genomics company, has a background of working with several top-10 global pharmaceutical companies on a range of autoimmune conditions. To make the relevant and enriched data available to the research community, main hurdle was to harmonize the data coming from various streams like Clinical Trials (CDISC in ODM-XML format), Patient data in the form of EHR (HumanAPI in near FHIR compliant format) and Genomic Data (from NGS). 

Pluto7 team, by using a combination of pre-processing the data for format conversion, leveraging the Google Cloud Healthcare API capabilities and extension to the predefined schemas handled the challenge.  Pluto7 deployed HTC (High Throughput Computing) framework to handle the genomic analytic workload arriving from NGS (Next Generation Sequencing) resulting in processing acceleration by 100 fold. 

After the improvisation of the sequencing analysis pipeline, DxTerity could scale faster and work towards population-scale remote clinical trial work, which was nearly impossible without the implementation of Cloud Healthcare API. The journey with DxTerity was positive as Pluto7 fortuitously developed a platform enabling machine learning model with the power of Cloud Healthcare API, letting DxTerity achieve the state-of-art precision medicine tools. 

Get a detailed  insight here.


The Keck School of Medicine of USC: Accelerating clinical trials using ML

Pluto7 helped the University of Southern California along with the Southern California Clinical and Translational Science Institute kick off their digitization journey to manage Clinical Trials and modernize its Medical Coverage Analysis (MCA). They needed to be efficient with an advanced approach to analytics. Pluto7 team worked with USC in this transformation. The team surveyed USC researchers to identify the challenges they were facing and assisted them in streamlining the process. 

For this project, Pluto7 built multiple machine learning models to read and understand the care guidelines, match the procedures, and assign it to the appropriate billing segments. Pluto7 leveraged the GCP Services  to successfully build a foundation to accelerate Clinical Trials and help support better patient outcomes. You can read the full story here.



The API-based ecosystem of Google Cloud is equipped with data interoperability to minimize the frictions in healthcare. Through the healthcare interoperability program, Google is set to understand the current state of a patient’s data and map the path of standardization and integration. Pluto7’s Healthcare ML combined with our services is well structured to enhance the clinical workflows for optimizing healthcare procedures in addition to revamping the billing and payment determinations. 

Click here to know more about Pluto7’s Healthcare ML or to get in touch to explore our healthcare solutions.


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