This presentation, shares methods for using data and risk thresholds for “early” warning and early detection – the keys to effective population management and proactive care coordination.
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Applying data - for population health
1. Pathways to Partnerships | Bridging Connections For Value edifecs confidential 1
Population Health
Ask the Experts Town Hall Series
2. Pathways to Partnerships | Bridging Connections For Value edifecs confidential 2
Applying Data
Trigger Early Warnings for Population Health
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Evolution of
Population Health
“The health
outcomes of a group
of individuals,
including the
distribution of such
outcomes within the
group.”
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Data Tsunami
Healthcare data is
increasing in volume
by 48% per year1
1. IDC Research
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Demonstration
Scenarios
Continuously collate and track digital data in a Member Journal
Assemble member “digital
footprint”
Rachel’s life events
Rachel visits ER – elevated
COPD condition
Rachel enrolls in P health plan
through FFM
RachelWest Exchange
Post-discharge
follow up
Rachel follows up
with PCP PulmonologistPCP
Referral
Jan 2014
Feb 2014
Mar 2014
CAU ERRachelWest
Longitudinal Member Journal
A03
837p
A01/A03
837i
A03
837
837p CCD
834 A03
837
CCD
ORU
ER ER+ IP
Enrollment
(Exchange) ER
PCP +
Referral
278 Req/Rep
NCPDP B1
Parent
Anthony’s Hypertension
management
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Early Warning System
Design
If Patient AGE > 40 and Patient has SMOKING HISTORY
or indicative symptom of DYSPNEA then Patient at-risk
for COPD, alert Care-coordinator
PID|0|PFX123456789|MRN12345||TEST^WEST^E||19811012||F|100 MAIN ST^APT
10B^ANYTOWN^AL^35244|| (205)555-1212| (205)681-2000
X999||M||a12345|999999999
PD1|||HEALTHCENTRE^^|123456789^DARTH^VADER^A^^^MD^^^^^^^
PV1|1|R|||||ANAKIN^SKYWALKER|LEA^SKYWALKER||||||||||||||||||||||||||||||||||||20110221
OBX|1|ST|^^^1010.1^Smoking Cessation^ASTM||Yes|||||||||20110221
DG1|1||401.9^HYPERTENSION, NOS
DG1|2|I9|786.59|CHEST PAIN|20110106095819-0800|F
DG1|3|I9|794.31|ABNORMAL EKG|20110106095819-0800|F
Age
Smoking History
Indicative symptom of dyspnea
Outpatient
Initiate guideline-based interventions for members at
risk of COPD within 7 days of detection
INGEST INBOUND DATA
DEFINE CLINICAL INTERVENTION RULE
PARTNERSHIP CARE MANAGEMENT GOAL
LINK BITS OF DATA TO CONCEPTS
Intervention
Gateway
Establish KPIs /
Incentives
Assemble
Integrated Patient
Records (IPRs)
Set Up Early
Warning System
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Next Steps
Watch
Recorded webinar
Population Health
Questions?
alison.south@edifecs.com
Editor's Notes
Let’s set the stage by defining what we mean by Population Health
Population health was defined by Kindig and Stoddart (2003) as “the health outcomes of a group of individuals, including the distribution of such outcomes within the group.”
Berwick and colleagues (2008) identify “improving the health of populations” as one element in the Institute for Healthcare Improvement’s (IHI) Triple Aim for improving the U.S. health care system (the other two elements call for improving the individual experience of care and reducing the per capita costs of care for populations).
OR
The Triple Aim defines 3 inter-dependent aspects of population health
- Improving the health of a population
- Improving the patients experience of care
- Reducing the per capita costs of care for populations
Health outcomes are measured for a defined group that is at-risk (based on agreement to metrics and measures of health)
How does that translate into practicing, actually implementing Population Health Management Programs at Oschner?
What you see her on this slide are the essential components of our Population Health program. If you take the 3 components at the lower left part of the circle, EMR, HIE and Analytics, these are the fundamentals of data access, integration, analysis and reporting that are essential for identifying your chronic conditions and patients at risk, stratifying them into groupings or cohorts that are then tied to interventions and programs, including targeted disease management, education and self-management training. On the upper part of the circle, Expanded PC access and developing a PCMH infrastructure is critical for holistic and team-based patient management, navigation and engagement. Post acute alignment is essential for addressing what happens to patients when they transition from the hospital to other settings. Aligning the post acute stakeholders is one way to prevent unnecessary readmissions. Finally, patient activation and engagement is important. Having implemented and scaled a diabetes population health management program, we know that diabetes self-management is critical for success.
Big Data is expanding on three fronts:
Volume – 48% per year as projected/estimated by IDC
Velocity – rate of change is increasing exponentially driven by MU, ACA, consumer-created data, HIEs, etc.
Variety – introduction of new data (consumer devices, mhealth apps, telehealth, genomics)
41% of health executives say the volume of data their organization manages has grown more than 50% in the last year alone.
Demo of Rachael West’s integrated patient record with all encounter and clinical data history.
Family view reveals that Rachael is related to Anthony, a hypertension patient.
Assembles Integrated Patient Record (IPR) by combining:
Discrete clinical elements from the Longitudinal Patient Journal, and enhance to normalize vocabulary to reduce duplication across data sources,
Risk Scores, Gaps in Care and Care Plan details from health plan systems, and
Value-Based Network awareness, healthcare team and contract KPIs
Enables transparency within the ACO – single patient view across the care continuum
Healthcare Data As a Service (hDaaS): Services-based access to IPR
Learn more: www.edifecs.com