clinical intelligence: best practices in scip compliance
DESCRIPTION
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 monitoringTRANSCRIPT
Clinical Intelligence Solutions
Achieving High Quality Surgical Outcomes
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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
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Current Challenges
NEED TO COLLECT DISCRETE DATA:• in a manner sufficient to affect core measure outcomes while still in-process
and
• with enough granularity to identify opportunities for improvement, leveraging data for automated reporting
CHALLENGES• Culture of entering data via free form text (after the point of administration
) leads to inconsistent data collection and data
• Data is scattered throughout multiple, disparate sources resulting in labor-intensive processes ( including chart abstraction for Core Measures) to satisfy reporting needs
• The excessive timeframe to integrate, analyze, and report data prohibits “In-process” measures from benefiting current patient outcomes
• 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
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Performance Goal – “Consistently High Compliance”
January February March April May June July0
0.10.20.30.40.50.60.70.80.9
1
SCIP-1
SCIP-2
January February March April May June July0
0.2
0.4
0.6
0.8
1
SCIP-1
SCIP-2
From: INCONSISTENT
To: CONSISTENT
“Manual ProcessFatigue”
“AutomatedProcess
Improvement”
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Best Practice Alerts – Visibility into Execution
Alert – Document Care
Alerts: Relevant, Timely, Escalating
Patient Registers
Pre-Op/HoldingPreparation
PACU & Discharge
Patient Surgery (OR)
StandardProcess
StandardProcess
Clinician WorkStation
2. Notify Clinician
1. Process includes: Antibiotics w/in 1 hr 1 hr Clock Starts
4. Notify Supervisor
3. List of Patients Approaching EscalationCompliance Threshold
Supervisor Dashboard CNO, SVP, CMIO
5. Performance Review6. Process Review
7. Review & Revise Process as Needed
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Clinical Scenario: Antibiotic Administration
Patient
Is it a surgical
operation?Has an incision
been made? Anesthesiologist
Pre-OpNurse
PICISOR Manager
PICISAnes. Manager
Clinical Alert Processing
HL7 Messages
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Antibiotic Alert Processing: SCIP 1a, 2a (Alert 5)
Alert is sent to Anesthesiologist in PICIS Anesthesia Manager while still in the OR
If HL7 message is “Surgery Finish” and NO message with Antibiotic (Abx) given (from PICIS)
Check Safety Considerations and Allergies Administer appropriate Antibiotic (Abx)
Document Antibiotic given If patient didn’t receive Antibiotic (Abx), document
REASON
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2
1
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Current State – Post-Discharge CPT-4 Coding
ArrivalSurgery
DischargeDate
Opportunityto changecore measureresults
Admission
OR Surgery(Picis)
PACU / Admission Orders with diagnosis
(PICIS/Horizon)
Registration(Medipac)
Arrival
Pre-Op(Picis)
Surgery Prep Procedure Recovery
Medipac – Patient RegistrationPatient Records in Picis (free text and discrete data)Physician Orders are Verbal, or entered later
Horizon Clinical SystemsPatient Records are Scanned ElectronicPhysician Orders are 30-40% CPOE
Medical Coding (CPT-4 / ICD-9)Quality Measures AnalyticsDecision Support Systems
Medical Records Coding (HDM)
Post-Discharge
2-3
days
post
-dis
charg
e
CU
RR
EN
TLY
Concurrent Coding/Code at Booking
RECOMMENDATION
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‣ 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 the free-format text collected here!
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Alerts Application High-Level Architecture
Alerts Rules Engine
Desktop Alerts Client (Yahoo
Widgets)
Mobile Alerts Client(Pager)
Mobile Alerts Client (Smart Phone)
ReportingData Mart
Alerts Database(Normalized / Integrated Patient Data)
Data Abstraction Layer
Alerts Server
HL7 Message Bus
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What does the alert notification look like?
• The Alerts Client is responsible for the presentation of the alerts to the targeted user. The Alerts Client uses a combination of sound and window pops to announce an alert to the user.
Widget – Used to Notify Responders
Different colorsto indicate:• Normal• Escalated
• A rolling list of acknowledged and unacknowledged alerts for past 24-48 hours can also be viewed through the Alerts Client.
Near-Real-time
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Rules Engine: Main Alert Processing Logic
Visual Developmen
t Environment Main
processing loop
Componentized & easily extensible
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Alert Details by Department
Colors indicate configurable threshold levels for alert counts
Surgery
ICU
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Isolate Source of Alerts, Localize Response
Enterprise Compassionate Health Services
Facility Baywood Hospital, Metro North Clinic, …
Department Surgery, ED, Same Day, …
Unit North 1, West 2, …
Room 501, 503, 505, 502, 504, …
Case J.Smith, P.Jones, …
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Functionally: Reduce manual effort and time to report quality core measures Improve accuracy of reporting and SCIP compliance Develop evidence-based medicine and education guidelines and
resources Improve productivity of staff
Better Return on People (Lean Six Sigma)
Help identify best practices from retrospective reporting over time Create accountability through the use of best practice alerts
Technically: A scalable, extensible framework for reducing the effort to
implement additional subject areas after SCIP (CHF, AMI, Pneumonia, etc.)
Feasibility of open source technologies to meet the needs of the near-term business requirements, while still being in alignment with the long-term vision
The Solution – Core Functions & Benefits
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‣ 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
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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
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Summary – Progressing From Paper to Automation
Manual data collection
Collect discrete, accurate data elements
Scanning information into electronic system
Clinical Alerts affecting outcomes
Surgical Analytics using discrete data elements
SCIP Core Measures:OR SchedulingMaterials & Supply MgrMeds Admin
Pneumonia Core Measures:Paper Data CollectionManually scanned document
ALL Core Measures:Automated reporting;All data sources required
