Paddling Upstream from Data Collection to Improvement

Paddling Upstream:

Data Capture to Improvement

Cynthia Davis, Principal

October 1, 2013 CIC ADVISORY 2

Who We Are


Mission

CIC Advisory is a nationally recognized leader in

helping healthcare organizations use technology to

provide high quality and safer care for patients,

families and communities.


How We Are Different

Improving care and efficiency results requires

better processes rather than new or better tools.

Better processes are a people solution: using data

effectively calls for strategic and thoughtful

governance.

Effective leadership is also necessary to ensure

underlying data integrity.


Healthcare Analytic Adoption Model


Where is the Stream Going?


The Healthcare Challenge

Results (quality, ROI)

Operational (efficiency, productivity)

Clinical (analytics, workflow)

Financial (risk, referrals, revenue)

Network (owned, affiliated, contract)

Regulatory (payment reform, meaningful use)

Technology (infrastructure, data)Legal and Governance (antitrust, liability)

How to best manage the

dynamics of the shift


Moving Upstream

Care team

engagement

Workflow

HIT

Analytics

Define: Triple Aim

Measure

AnalyzeImprove

Control


Direction Moving Upstream in Alignment

Care Team Engagement

HIT

Analytics

Workflow

• Configure and Adopt New HIT Tools

• Triage and Select Interventions

• Coordinate Care

• Assess Patient Compliance

• Evaluate Outcomes

• Determine Intervention Efficacy

• Automate Care Guidelines

• Enable Care Team

• Support Patient Engagement

• Capture Compliance Measures

• Align Performance with At-Risk Contract

• Transform and Stratify Data

• Identify and Prevent Risk

• Alert Physicians, Patients

• Measure Quality, Cost Performance

• Determine Intervention Efficacy

• Measure At-Risk Performance

• Connect Patient Data

• Improve Speed and Accessibility

• Enable Workflow

• Improve Adoption, Usability

Define: Triple Aim

Measure

AnalyzeImprove

Control


Navigating the Stream with Paddle Alignment

Intervention Efficacy

Track Process,

Outcome:

Care Management

Triage,

Intervention Selection:

Care Management

Predict and Alert,

Population Analytics

Transform and Stratify:

Population Analytics

Integrate The Data:

Single Patient Record

Define: Triple Aim

Measure

AnalyzeImprove

Control


Enablers of Smooth Paddling:

The Quality and Quantity of Your Data

• Goals and

Preferences

• Visits

• Location

• Providers

Place Time

• Outcomes

• Interventions

• Drugs

• Therapy

• Education

• Symptom

• Management

• Behavior

• Activity

• Nutrition

Connections


How to Paddle


Transformation Approach

Prepare

1. Create urgency

2. Pull together a guiding council

3. Develop transformation vision and strategy

Adapted From: Kotter J. Our Iceberg Is Melting. 8-step process for successful change. Pages 130-131

“Set the Stage and

Decide What to Do”

“Take action”

“Maintain and improve”

Sustain

7. Don’t let up

8. Create a new culture

Conversion

Engage

4. Secure buy-in

5. Empower team members to act

6. Create short-term wins

Start hardwiring: transformation action plan


The Overall Process:

Methodology + Technology

1. Break Ground: Start building Level 0 and Level 1

infrastructure

2. Analyze Opportunities: Run the Key Process Pareto

Analysis to identify clinical and cost variability

3. Prioritize: Select the care processes or disease states for

targeted improvement

4. Organize: Establish the clinical process improvement teams

5. Set the Goals: Choose the AIM (Analytically Informed

Medicine) statement

6. Measure Precisely: Build the underlying Subject Area Mart

for precise analytics


The Four Key Questions

Who are we monitoring?

What are we measuring?

What are our goals?

How will we achieve them?

Identify patients with condition or

attribute of interest

Patterns of best practice, clinical

outcomes, costs

Targets for adherence,

outcomes and costs

Cultural behaviors Protocols, orders,

workflows…modifi

cations to the EMR


Data Governance (why)

We did a great Data

Cleanup effort last year but

the data is corrupt again.

Shouldn’t that effort made

sure that errors don’t creep

in again?

I am trying to determine why

we have different formulas

for inventory in different

systems.

Doesn’t anyone own or have

responsibility for this data

through the company?

I just reviewed a Data Model

of our business to prepare

for an acquisition. It looked

very nice but it used

indecipherable terminology,

a very old business model

and not current

I get two different results

from two different systems

and, guess what, they are

both wrong

I need to do a study/research

that looks at our revenue for

the last 5 years. I was told

that the data is all archived but

no one knows where it is or

how to retrieve it.

I clean up the data

that is usually

unclear and

inconsistent when

I receive it


Data Governance Benefits

• Data Governance (DG) are rules, policies, procedures, roles,

and responsibilities that guide overall management of data

• Governance provides the guidance to ensure that data is

accurate and consistent, complete, available, and secure

• Governance body based on people, process, & technology

• Data centric organization

• Master Data Management

• Prepare us towards effective and efficient changes

• Comprehensive and accurate data gives us the competitive

advantage in the market area

Data Governance helps us to manage our date


Use Case Discharge Location

Need:

• At D/C patients need to have correct discharge location

entered in XYZ

• Data will be used for Readmission Analytics and for

follow up survey call

Issue:

• Require entry in 2 systems to D/C a patient

• Current process follows two slightly different workflows in

XYZ for FirstNet and IP

• Data is a radial button selection for disposition but free

text detail for location


Team Process

• Team selection:– Target– Delivery (cohort)

– Members: Knowledge Manager, Subject Matter Experts

(both Physician & Nurse), Data Analyst, and Data Architects

– Kick-off meeting

• Weekly work meetings

• Identified Aim Statement & long term goal

• Selected, built, and refined metrics

• Created dashboard visualizations to display metrics

• Published dashboards for targeted audience

• Identified next Aim Statement -> repeat process


Data Quality Issues

• Gestational age charted in four different locations in

EHR[clinical peer groups changed operational use of EHR]

• Chart times for Stage 1 labor duration present only 68%

[clinical peer groups changed operational use of EHR]

• Errors in documentation (nurse name as provider for

C-Section) [correction process with Health Information Mgt]

• Delivery records missing the ‘Marked as Delivered’ indicator

[tracking process on units & correction process with HIM]


Indication For C-Section – The Problem

Not documented 15% of the time.

When documented,

it was not informative.


Next Steps: Requirements

Systematic Approach across all setting with effective Clinical and Data Governance

Communication and Collaboration tools that assist providers and coordinators

Resources to perform coordination tasks

• Proximity and close working relationship between coordinators and clinicians

• Patient contact with a coordinator, 24x7 access

Initial Focus on transitions of care, medication management, notification of and access to info on

hospitalizations, ED visits

Patient Engagement (Activation)

Health Information Exchange

Teleservices, Mobile Health

Analytical Tools to Manage Populations – assess medical/socioeconomic risk, define populations at risk,

measure outcomes

• Integrations of Financial and Clinical data to support analytics

• Ability to operate in Multiplayer Environment, different risk models


Thank You

Business

Paddling Upstream from Data Collection to Improvement