SCIP Compliance has been a major struggle for many Healthcare Providers. Specific quality programs are often inflexible in the data collection and reporting demands they place on care providers, which leads to poor documentation on care delivery and compliance. Learn how to leverage near-real-time alerts to ensure compliance with best practices, driving the highest quality surgical care. In this 1 hour webinar you will gain valuable insight into how you can: Facilitate more informed decisions by providing visibility into hospital-wide and cross-facility metrics and trends Prioritize the need for corrective actions by benchmarking against industry standards, best practices and internal goals Improve hospital performance by identifying and replicating demonstrable best practices across the organization Increase staff productivity and data accuracy through automatic and embedded performance monitoring

1. Clinical Intelligence Solutions Achieving High Quality Surgical Outcomes

2. The Well Known Challenges Continue … Variations in the quality of care and resulting patient outcomes Technology adoption to support clinical insights lags behind other areas After the fact performance improvement programs often allocate scarce resources to “paper chasing” activities that have little value and almost no hope of impacting current cases Regulatory bodies impose ever increasing reporting requirements that today’s solutions just can’t handle Hospitals are paying too many punitive penalties and often fail to attain all available pay for performance quality incentives / performance-based rewards based on slow or poor reporting

5. Data is scattered throughout multiple, disparate sources resulting in labor-intensive processes ( including chart abstraction for Core Measures) to satisfy reporting needs

6. The excessive timeframe to integrate, analyze, and report data prohibits “In-process” measures from benefiting current patient outcomes

7. Lack of clinical data strategy for integrating multiple diverse sources to support analytics and clinical decision support Each subject area investigated offers similar challenges with actionable alerting due to data quality and availability issues

8. Performance Goal – “Consistently High Compliance” From: INCONSISTENT “Manual Process Fatigue” To: CONSISTENT “Automated Process Improvement”

9. Best Practice Alerts – Visibility into Execution CNO, SVP, CMIO 5. Performance Review 6. Process Review 7. Review & Revise Process as Needed Supervisor Dashboard Clinician WorkStation  Alerts: Relevant, Timely, Escalating 2. Notify Clinician 4. Notify Supervisor Alert – Document Care 3. List of Patients Approaching Escalation Compliance Threshold 1. Process includes:  Antibiotics w/in 1 hr  1 hr Clock Starts Standard Process Patient Registers Pre-Op/Holding Preparation PACU & Discharge Patient Surgery (OR)

10. Clinical Scenario: Antibiotic Administration Clinical Alert Processing HL7 Messages PICIS OR Manager Pre-Op Nurse Is it a surgical operation? Has an incision been made? Patient PICIS Anes. Manager Anesthesiologist

12. If patient didn’t receive Antibiotic (Abx), document REASONAlert is sent to Anesthesiologist in PICIS Anesthesia Manager while still in the OR 2 If HL7 message is “Surgery Finish” and NO message with Antibiotic (Abx) given (from PICIS) 1

13. Current State – Post-Discharge CPT-4 Coding RECOMMENDATION Concurrent Coding/Code at Booking Medical Coding (CPT-4 / ICD-9) Quality Measures Analytics Decision Support Systems Discharge Date Opportunity to change core measure results Admission Horizon Clinical Systems Patient Records are Scanned Electronic Physician Orders are 30-40% CPOE 2-3 days post-discharge Medipac – Patient Registration Patient Records in Picis (free text and discrete data) Physician Orders are Verbal, or entered later CURRENTLY Arrival Surgery Medical Records Coding (HDM) Registration (Medipac) Pre-Op (Picis) OR Surgery (Picis) PACU / Admission Orders with diagnosis (PICIS/Horizon) Arrival Surgery Prep Procedure Recovery Post-Discharge

14. Too frequent use of the Picis memo field Eliminates the ability to efficiently and automatically analyze the data No standardized processes for collecting and documenting data There are no consistent data collection points and locations for the data across clinical workflows; and no data owners responsible for its quality No designated, authoritative sources for each piece of data collected SCIP Chart abstractors have to look in up to 9 places for SCIP data Like the Accountability Matrix, all data needs a trusted source and owner Current State: Obstacles to Discrete Data Collection Can’t analyze thefree-format text collected here!

15. Alerts Application High-Level Architecture Desktop AlertsClient (Yahoo Widgets) Mobile Alerts Client (Pager) Mobile Alerts Client (Smart Phone) Alerts Server Alerts Rules Engine Alerts Database (Normalized / Integrated Patient Data) Reporting Data Mart Data Abstraction Layer HL7 Message Bus

19. Alert Details by Department ICU Surgery Colors indicate configurable threshold levels for alert counts

20. Alert Details broken out by SCIP Core Measure ICU Surgery

21. Alert Details with Rolling 12 Month view ICU Surgery

22. Isolate Source of Alerts, Localize Response Enterprise Compassionate Health Services FacilityBaywood Hospital, Metro North Clinic, … DepartmentSurgery, ED, Same Day, … Unit North 1, West 2, … Room 501, 503, 505, 502, 504, … Case J.Smith,P.Jones, …

24. Reduce manual effort and time to report quality core measures

25. Improve accuracy of reporting and SCIP compliance

26. Develop evidence-based medicine and education guidelines and resources

27. Improve productivity of staff

28. Better Return on People (Lean Six Sigma)

29. Help identify best practices from retrospective reporting over time

30. Create accountability through the use of best practice alerts

31. Technically:

32. A scalable, extensible framework for reducing the effort to implement additional subject areas after SCIP (CHF, AMI, Pneumonia, etc.)

33. Feasibility of open sourcetechnologies to meet the needs of the near-term business requirements, while still being in alignment with the long-term visionThe Solution – Core Functions & Benefits

34. Retrospective Reporting – This component includes the following functionality: The creation of the underlying dimensional data mart The creation of the Business Objects Universe to access the underlying dimensional data mart The Xcelsius dashboard, WEBI reports and/or Crystal reports for retrospective reporting This functionality is included due to: Ability to demonstrate the value of the overall solution – Dimensional data marts, Business Objects Universes and Xclesius dashboards Dashboards

35. Main Points Consistently high Core measure compliance benefits: Quality of Care Patient Satisfaction Hospital Reputation Financial Returns Discrete data is essential for automating the reporting, analysis, and presentation of core measure compliance An alert mechanism is scalable for future measures by simply expanding business logic/rules Alerts can be delivered via text, email, page, widget prompt An alert is as real-time as the systems holding the data Alerts are clinician “Reminders” not “Dictators” Superior Outcomes Dollars Spent = Value to the Patient

36. Summary – Progressing From Paper to Automation SCIP Core Measures: OR Scheduling Materials & Supply Mgr Meds Admin ALL Core Measures:Automated reporting; All data sources required Pneumonia Core Measures: Paper Data Collection Manually scanned document

37. Questions? Thank You!