Healthcare Delivery Reimagined: Patient Flow and Care Coordination Analytics
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Come to learn how Splunk’s data analytics platform could be utilized to solve many high impact business problems in healthcare delivery systems to reduce cost, improve patient outcome and safety, and enhance care coordination experience. Analyze observed behavior from healthcare event data and metadata to discover patterns, monitor compliance, and optimize the workflow. Furthermore 80% of healthcare data is unstructured (clinical free text and documentation), or semi-structured and many new data sources are such as tele health, mobile health, sensors, and devices are getting integrated in many healthcare systems specifically in the area of chronic disease management. So, one need analytics software that can harvest, interpret, enrich, normalize, and model diverse structured and unstructured data and analytics approaches that embrace the “data turmoil” by relying less on standardized data items and more on the capability to process data in any format.
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Healthcare Delivery Reimagined: Patient Flow and Care Coordination Analytics
- 1. Copyright © 2015 Splunk Inc. Data Informed Healthcare Delivery Process Improvement
- 2. 2 Agenda Problem Background and Motivation Process Analytics Solution Overview Solution Features and Benefits: Executive Solution Features and Benefits: Operations User Solution Features and Benefits: Informatics User Product Demonstration
- 3. 3
- 4. 4 Information Flow in Care Delivery: Spaghetti http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3002133/
- 5. Requires complex cross domain coordination
- 6. 6 And Flow is Care Condition Specific
- 7. 7 Current picture of My Visit Source: HIMSS Presentation, capturing patient flow value stream Algorithmsforinnovation.org 26 National Average Wait Time for Specialist Visit
- 8. 8 Underlying Problem Areas Examples Process variations that reduces efficiency without improving outcome Mismatch of supply and demand: Nurse Staffing, Patient Scheduling, Beds, Operating Room, Emergency Department Best Practices/Checklist hard to implement
- 9. 9 Event Type Event ID Attributes (Timestamp, Department, Resource) Registration 4798668 02/06/2015 14:00 A John Lab 4798669 02/06/2015 14:00 B Pete Consultation 4798670 04/06/2015 11:00 C Rose Medication Order 4798671 04/06/2015 12:00 C Pete Medication Dispense 4798672 04/06/2015 10:00 D John Transport 4798673 04/06/2015 15:00 E Pete Billing 5798670 03/06/2015 14:00 F Pete 9 Good News: Increasing Healthcare Digitization- Flows are Captured in Events
- 10. 10 Virtual Physical Cloud Healthcare Data is Time Oriented and Diverse 1 EHR Systems Web Services Developers App Support Telecoms Networking Desktops Servers Security Devices Storage Messaging Patient Surveys clickstream HIE Patient Networks Healthcare Apps IT Systems and Med Devices Patient Generated Data Medical Devices CDR Mobile PHI Access Audit Logs HL7 Messaging Sensors Departmental and Homegrown Applications
- 11. 11 Goal With Splunk: From Spaghetti To Lasagna Reduce Unwarranted Variations Source: processmining.org
- 12. 1 Real Time Diverse Data Integration End to End Process Discovery and KPI visibility Detect and Monitor Process Anomaly and Bottlenecks Predict, Recommend, and Forecast Using Process Analytics: Improvement Method + Real Time Data Analytics
- 13. 13 Patient Flow Data Sources Examples Health Event Data: Application Event Logs HL7 Messages and Logs Web Logs Device Data: RTLS Asset Tracking Patient Tracking (optional non-US) Medical Device Logs
- 14. 14 Future State My Visit Enabled by Process Analytics Source: HIMSS Presentation, capturing patient flow value stream
- 15. 15 Anticipated Improvements and Measurements Anticipated Improvement Opportunities Prediction of Resource Requirements next hour/day/week Identify Over provision of low or non value added activity Find low utilization of expensive clinicians, operating room, devices, supplies, and clinic space. Discover use of clinicians for less skilled activities Identify routine care delivered in expensive settings Detect long waiting time and delays because of lack of cross functional coordination KPI to Improve Time for patient waiting for an inpatient bed ER Wait Time Cycle time of discharge order received to room clean and ready. Waiting time for scheduled surgery Reduction in inventory and equipment capex/opex
- 16. 16 Traditional Process Analysis Vs. Splunk Approach Splunk Approach Discover actual behavior of people, organization, and machines and relate to modeled behavior. Correlate millions of ad-hoc events showing how reality is different from perceptions, opinions, and beliefs. Provide clue for standardization, reduce unwarranted variations, and better prepare to handle ad-hoc events. Traditional Approach Based on the opinion of the expert. Assemble an appropriate team and to organize process modeling sessions. The knowledge of the team members is used to build an adequate process model.
- 17. 17 Why Now? Shift in The Payment System and Care Delivery Models New Care Delivery Models: Accountable Care Organizations, Mergers, Acquisition, and Partnerships. Shift of Payment Systems: fee for service to fee for quality. Margins are thinner, infection penalty, readmission penalty. Aging Populations, new population with insurance: more demand on constrained resources
- 18. 18 Why Now? Increased Patient Participation More Choices- new entrants in the market- Wal-Mart, Walgreens, CVS Patient’s skin in the game: Highly deductible plans, sharing of costs Availability of Patient Portals, Online Communities, and Consumer tools- Mobile, Sensors, Home Health Increased Transparency on cost and quality data
- 19. 19 19 Business Value of Process Analytics Increase Staff Productivity, reduce error, optimize time 1 Reduce cost without outcome tradeoff 2 3 Improve patient outcome, experience, and engagement
- 20. 20 2 Executive Solution Features and Benefits
- 21. Process KPI Dashboards 2 • Waiting Times/Delays at Highly Utilized Flow Steps • Current Bed Capacity • Current Imaging Frequency • Current discharge to bed readiness time
- 22. 22 2 Visualize Patient Flow
- 24. 24 24 Business Benefits Process Flows and real time Capacity and Time Metrics 1 Comparison Data- by min, hour, days, months etc. 2 3 Make data informed time critical operational decisions
- 25. 25 2 Clinical Operations Solution Features and Benefits
- 26. 26 Finding and Troubleshooting Bottlenecks
- 27. Utilization Management KPI temporal view
- 28. Visualize flow and frequency
- 29. Visualize Entity Relations Ex: relations among conditions and procedures
- 30. 30 Automatic Notifications: Actionable Alerting
- 31. 31 31 Business Benefits Monitoring for Joint Commission and other best practices 1 Detect trends, anomalies, and inconsistencies and troubleshoot 2 3 Make data informed time critical operational decisions
- 32. 32 3 Informatics Solution Features and Benefits
- 33. 33 3 Real World Business Questions, Improvement Opportunities, feedbacks Data Collection Data Preparation Exploratory Visualization, Statistics and Machine Learning Communication, Visualization Reports, Findings Evaluation Knowledge Discovery, developing and evaluating Knowledge, Rules, and KPI Decision Support Product Think of the Process/Walk in the Patients’ shoes
- 34. Process Mining Platform Pre Mortem Data : Real Time Monitoring, Anomaly Detection , and Predictions Case Management Anomaly Detection, Linkage, Correlations/ Patterns Alerts Predictive Modeling/M odel Maintenance Data Warehouse New Events Standard Reports/Que ries Data Archival Rules System
- 35. Process Data Mining Core Engine 35 Analytics Platform Integrate Untapped Data: Any Source, Type, Volume, Velocity Healthcare Apps Data/HL7 Events Healthcare Apps Audit Logs Medical Device (PACS)/RFID Metadata (logs) Patient Generated Data Hadoop Clusters Relational Database No SQL Data StoreSplunk Clusters Explore Visualize Dashboard ShareAnalyze Monitor and alert External Applications Integration (SDK, REST API)
- 37. 37 37 Business Benefits Diverse Data Integration and Enrichments 1 Tools for process discovery and visualizations 2 3 Make real time knowledge available to operations and executives
- 38. 38 Splunk Resources • Search Tutorial: http://docs.splunk.com/Documentation/Splunk/latest/SearchTutorial/Welcom etotheSearchTutorial • Training Videos: http://www.splunk.com/view/educa3on-videos/SP-CAAAGB6 • Splunk Docs: http://docs.splunk.com/Documentation/ • Splunkbase Apps & Answers: http://apps.splunk.com/ http://answers.splunk.com/ • Splunk Wiki: http://wiki.splunk.com/ • Developers: http://dev.splunk.com/ • Exploring Splunk Book: http://www.splunk.com/goto/book
- 39. 39 Interactive, cut/paste examples from popular source repositories: D3, GitHub, jQuery Splunk 6.x Dashboard Examples App https://splunkbase.splunk.com/app/1603 Custom SimpleXML Extensions App https://splunkbase.splunk.com/app/1772 Splunk Web Framework Toolkit App https://splunkbase.splunk.com/app/1613 Machine Learning Toolkit: https://splunkbase.splunk.com/app/2890/ Example Advanced Visualizations and Machine Learning Toolkit 3
- 40. 40 http://dev.splunk.com/view/python-sdk/SP- CAAAEU2 http://dev.splunk.com/sdks http://dev.splunk.com/restapi REST API, SDKs, and Custom Search Command 4
- 41. Thank You Adrish Sannyasi Healthcare Solution Architect Splunk, asannyasi@splunk.com
Editor's Notes
- Do we know what a drug or diagnosis code means and does it mean the same in different EHRs? Similarly, do we know what an EHR event in an EHR event log means and does it mean the same in different systems. This last will be important for comparing process models, as EHRs are so user- customizable. “Check Meds” in one EHR might be called “Medications” in another. What exactly does “Check Meds” mean? Where, exactly, does it fit in a hierarchy of tasks, such as “checking” other things besides medications or involvement of medications in other activities besides “checking”? Is asking a patient about medications (or retrieving the medication list from online) an example of “Check Meds”? Is there a difference in the ordering and frequency of activities between patients that were treated by either a high- or low-volume surgeon? (control-flow perspective) Is there a difference in resource involvement between patients that were treated by either a high- or low-volume surgeon? (organisational perspective) Is there a difference in time-related performance between patients that were treated by either a high- or low-volume surgeon? (performance perspective) Is there a difference in the ordering and frequency of activities between patients that had a throughput time of 80 and 40 minutes or less in respectively the pre-operative and final postoperative examination and patients with a longer throughput time? Is there a difference in time-related performance between patients that had a throughput time of 80 and 40 minutes or less in respectively the pre-operative and final postoperative examination and patients with a longer throughput time? It is apparent that the business processes in the medical domain are dynamic, ad-hoc, unstructured and multi-disciplinary in nature. he goal of clustering is to obtain homogeneous group of patients.
- A defining characteristic of modern health care is the rapidly accelerating increase in information that is available to assist with the delivery of care and system management. Time oriented data, 2. High diversity, 3. Some data is functional others are event logs generated by machines. Data came from activities which are part of sequential process Data is timestamped Activities are interdependent discrete events Machine data is generated by many different sources within the healthcare IT infrastructure. These sources include healthcare specific data sources such as electronic health record (EHR) systems, HL7 messaging, and connected medical devices. The data sources include core IT systems that support different applications such as desktops, servers, storage and network devices. Finally, they include all the patient facing applications and systems – portals, billing systems, claim management systems. Machine data generated by this infrastructure shares the core characteristics of big data – lot of data (high volume), created rapidly (high velocity), from different sources (variety), and data that changes over time (variability). Getting timely and relevant insight into this data can be a source of huge value for the healthcare ecosystem.
- Data Science: validate your assumptions, formulate your hypotheses and test it, find simple principles that may have large impacts and generalized across the population.
- Cost of adding adding one additional bed: $1 M+
- Vmware – House of Demos app. VM forest, esx server. Status of VMs when you click on particular one. One of the most useful types of visualizations is a “Sankey diagram”, which is used to describe flows through systems. These can be customer flows through marketing or sales funnels, traffic flows through the actual network, energy flows through a physical system, capital flows through a financial system, etc. It’s a very streamlined form of visualization that cuts out everything unrelated to “flow”. Technically, this is a graph visualization: the nodes are smushed to these bars along the side, and edges are represented by these fat bars connecting nodes. The width of a node is proportional to the volume of flow in and out of the node, and the width of an edge is proportional to the flow from the start node to the end node.
- Customer journey: convert, repeat Mobile Patent Suits Dashed links are resolved suits; green links are licensing. “Thomson Reuters published a rather abysmal infographic showing the "bowl of spaghetti" that is current flurry of patent-related suits in the mobile communications industry. So, inspired by a comment by John Firebaugh, I remade the visualization to better convey the network. That company in the center? Yeah, it's the world's largest, so little wonder it has the most incoming suits.” mbostock’s block #1153292 August 18, 2011 http://bl.ocks.org/mbostock/1153292
- Alerts are triggered when certain conditions are met by the results of the search upon which it is based. Alerts can be based on both historical and real-time searches. When an alert is triggered, it performs an alert action. This action can be the sending of the alert information to a designated set of email addresses, or the posting of the alert information to an RSS feed. Alerts can also be set up to run a custom script when they are triggered. You can base these alerts on a wide range of threshold and trend-based scenarios, including empty shopping carts, brute force firewall attacks, and server system errors.
- Splunk products are being used for data volumes ranging from gigabytes to hundreds of terabytes per day. Splunk software and cloud services reliably collects and indexes machine data, from a single source to tens of thousands of sources. All in real time. Once data is in Splunk Enterprise, you can search, analyze, report on and share insights form your data. The Splunk Enterprise platform is optimized for real-time, low-latency and interactivity, making it easy to explore, analyze and visualize your data. This is described as Operational Intelligence. The insights gained from machine data support a number of use cases and can drive value across your organization. [In North America] Splunk Cloud is available in North America and offers Splunk Enterprise as a cloud-based service – essentially empowering you with Operational Intelligence without any operational effort.
- Is there a difference in the ordering and frequency of activities between patients that were treated by either a high- or low-volume surgeon? (control-flow perspective) Is there a difference in resource involvement between patients that were treated by either a high- or low-volume surgeon? (organisational perspective) Is there a difference in time-related performance between patients that were treated by either a high- or low-volume surgeon? (performance perspective) Is there a difference in the ordering and frequency of activities between patients that had a throughput time of 80 and 40 minutes or less in respectively the pre-operative and final postoperative examination and patients with a longer throughput time? Is there a difference in time-related performance between patients that had a throughput time of 80 and 40 minutes or less in respectively the pre-operative and final postoperative examination and patients with a longer throughput time? It is apparent that the business processes in the medical domain are dynamic, ad-hoc, unstructured and multi-disciplinary in nature. he goal of clustering is to obtain homogeneous group of patients.