8/23/2020 MD Insider Case Study | Google Cloud MD Insider: Matching patients with physicians for better outcomes Tell us your challenge. We're here to help. Contact us (/contact) To give customers grAebaoteurt MD Insider insights, MD Insider mMDo Invsiededr’s machine learning (ML) from another cloud pprlaotfvormid geenrerates performance insights on providers across the healthcare to Google Cloud Platform Aecobsyostuemt tMo hDelp Iimnpsroivde epartient and used Kubernetesex pEerniengceins aend quality of care. to automate containeMDr Insider’s machine learning (ML) platform Industries: Healthcare, Technology generates performance insights on providers management, improvacirnosgs the healthcare ecosystem to help improve performance 5x whilepLaotcieant ieoxnpe: rUiencitees dan Sdt qautaelisty of care. accelerating time to mIPnroddauuscrtkrsi:e Besig:t QHueeraylthcare, Technology by 30%. (https://cloud.google.com/bigquery/), Cloud Dataproc (https://cloud.google.com/dataproc/), Location: United States Cloud Functions (https://cloud.google.com/functions/), Cloud Google Key Management Service https://cloud.google.com/customers/md-insider/ 1/12 8/23/2020 MD Insider Case Study | Google Cloud (https://cloud.google.com/kms/), Cloud Cloud 5x perforBmigQuaerny (hctteps://cloud.google.com/bigquery/) Results Pub/Sub (https://cloud.google.com/pubsub/), improvemClColueodu ndD aStQaLp r(ohcttps://cloud.google.com/sql/), (hCtltopusd:/ /Sctloruadg.geoogle.com/dataproc/) Helps (https://cloud.google.com/storage/), Compute increase ClEonugdi nFeu n(hctttiopns:s//cloud.google.com/compute/), processing (hCtotpnsta://incelor uRde.giosotrgyle.com/functions/) power by 5x, (https://cloud.google.com/container-registry/), Cloud Key Management Service giving Cloud IAM (https://cloud.google.com/iam/), (https://cloud.google.com/kms/) Kubernetes Engine customers (https://cloud.google.com/kubernetes-engine/), greater Cloud Pub/Sub (https://cloud.google.com/pubsub/) Operations insights into Cl o(hutdt pSsQ:/L/c (lhotutdp.sg:/o/oclgolue.dc.ogmoo/gplreo.dcoumct/ss/qolp/e) rat ions physician ) Cloud Storage (https://cloud.google.com/storage/) performance , TensorFlow (https://www.tensorow.org/) Accelerates Compute Engine time to (https://cloud.google.com/compute/) market up to CoTnetlal iunser y Roeugris ctrhyallenge. We're here to help. 30% by (https://cloud.google.com/container-registry/) helping Contact us (/contact) developers Cloud IAM (https://cloud.google.com/iam/) be more Kubernetes Engine ecient (https://cloud.google.com/kubernetes-engine/) Enables Operations analyses of (https://cloud.google.com/products/operations) larger datasets as TensorFlow (https://www.tensorow.org/) the company grows Patients about to undergo a healthcare procedure understandably want the best medical professionals they can get. But how can they know which doctors https://cloud.google.com/customers/md-insider/ 2/12 8/23/2020 MD Insider Case Study | Google Cloud have had the most experience and the best outcomes with that particular procedure? How can they make an informed decision about which doctor to select when the information they have is limited to the doctor’s practice area and subjective reviews from other patients? MD Insider (https://mdinsider.com/) is working to solve that problem using machine learning (ML) to objectively analyze doctor performance. By analyzing data from thousands of institutions and millions of doctor-patient interactions and medical events, MD Insider identies physician performance insights based on their experience and outcomes. Insights are then integrated into a triage engine, that enables consumers to search for and schedule appointments with providers who meet their clinical criteria and convenience preferences, such as insurances accepted, oce hours, locations, and language. MD Insider also offers robust data APIs to help health systems, health plans, and employers reduce costs and improve quality of care. Payers use the APIs to curate high-quality provider networks and manage provider directories. Examples of MD Insider's data APIs include Provider Experience and Share of Practice metrics, Provider Quality and Outcomes, Network Modeling, Expert Clinical Search Taxonomy, Find a Provider, Acute-Care Hospital Quality, and Provider and Facility Metadata. https://cloud.google.com/customers/md-insider/ 3/12 8/23/2020 MD Insider Case Study | Google Cloud “We use Google Cloud Platform the way the cloud was supposed to be used. By comparison, other cloud providers feel like you’re renting somebody else’s data center.” —Ed Holsinger, Lead Data Engineer and Head of Data Science, MD Insider MD Insider is continuously ingesting the latest performance data about physicians and analyzing billions of rows of data. Requiring constant scalability, the company was born in the cloud; however, it had diculty conguring server instances for the optimal balance of memory and CPU, and its Hadoop cluster had to be kept running 24/7. Network performance was often slow for no apparent reason. As a result, https://cloud.google.com/customers/md-insider/ 4/12 8/23/2020 MD Insider Case Study | Google Cloud failure rates from node timeouts increased, and costs grew along with the data. MD Insider had to estimate its usage and pay up front, and received little nancial benet from sustained use commitments. Knowing that data would continue to grow, MD Insider decided to move its data services — the most demanding and complex portion of its infrastructure — to Google Cloud Platform (https://cloud.google.com/) (GCP), and took advantage of GCP managed services for container management and big data analytics. “One of the reasons we decided to move to Google Cloud Platform is because it feels like a unied, well- designed cloud architecture and pricing model,” says Ed Holsinger, Lead Data Engineer and Head of Data Science at MD Insider. “We use Google Cloud Platform the way the cloud was supposed to be used. By comparison, other cloud providers feel like you’re renting somebody else’s data center.” “Moving to Google Cloud Platform and using Kubernetes Engine gave us 5x the processing https://cloud.google.com/customers/md-insider/ 5/12 8/23/2020 MD Insider Case Study | Google Cloud power for analyzing physician performance at 75% less cost. Our data scientists have more power than ever before to generate insights for our customers.” —Ed Holsinger, Lead Data Engineer and Head of Data Science, MD Insider 5x the performance, 75% less cost MD Insider now uses Kubernetes Engine (https://cloud.google.com/kubernetes-engine/) to automate container management and deploy clusters in minutes with just a few clicks. When hundreds of machines are required to analyze a large dataset, automation in Kubernetes Engine deploys ML models as containers, each of which manages the full lifecycle of its task, including scaling up resources, deploying results, and https://cloud.google.com/customers/md-insider/ 6/12 8/23/2020 MD Insider Case Study | Google Cloud scaling back down when the task is nished. It’s easy for MD Insider to specify exactly how much CPU and memory each container needs, helping maximize performance while reducing costs. “Moving to Google Cloud Platform and Kubernetes Engine gave us 5x the processing power for analyzing physician performance at 75% less cost,” says Ed. “Our data scientists have more power than ever before to generate insights for our customers. Data scoring jobs that used to take three business days now take four hours.” Adds Galen Meurer, Senior Software Engineer at MD Insider: “Even if all Google Cloud Platform had to offer was Kubernetes Engine, I would still want to use it. Previously we spent up to 30% of our time managing our container infrastructure, which we can now use for product development.” A foundation for data science MD Insider was happy to nd that GCP offers a wide variety of managed services. For example, the company is supplementing its Kubernetes Engine clusters with BigQuery (https://cloud.google.com/bigquery/) for its big data masters and selection jobs, enabling scientists to analyze new and different types of data as well as analyze larger datasets in less time. MD Insider also uses Cloud Storage (https://cloud.google.com/storage/) for big data staging and Cloud Dataproc https://cloud.google.com/customers/md-insider/ 7/12 8/23/2020 MD Insider Case Study | Google Cloud (https://cloud.google.com/dataproc/) to run managed Apache Spark clusters for data processing. “Google Cloud Platform gives us an incredibly powerful cloud architecture for data engineering and data science,” says Eric Wilson, CEO of MD Insider. “That gives our scientists independence, they can do what they need to do without waiting and with no contention between them.” A developer-friendly platform Migrating its data services was such a success that MD Insider decided to move the rest of its infrastructure to GCP, including the front end for its web application. Since the migration, MD Insider has experienced no unplanned downtime on GCP, allowing it to easily meet the 99.5% uptime SLA it promises to customers. It’s also taking advantage of Build Triggers in Kubernetes Engine to automate container builds and reduce build times by more than 40%. Production code can be updated in seconds, with no impact to end users other than making new features available. “GCP has simplied our workow in so many ways, from intelligent load balancing to content delivery and automating builds,” says Matthew Frey, Software Engineer. “Everything on GCP is cohesive and developer friendly, with a superior