5/2/2014

1

April 29, 2014

Western Clinicians Network

Optimizing Data and Analytics in an

Accountable Care Environment

Robert Moore, MD MPH

CMO, Partnership HealthPlan

Why is data important to Your

Organization?

Tells you where you stand relative to the industry

Helps you prioritize how to spend resources

Enables a common, unbiased language for discussing

performance

Can provide immediate feedback on process effectiveness

Can connect you to the entire health system

Gives you the power of negotiation – a seat at the table

5/2/2014

2

Accountable Care Environment

How is it related to Data and Analytics?

Accountable Care -1

What is an ACO?

https://www.youtube.com/watch?v=ULy5vjcGuDc

5/2/2014

3

Accountable Care Definitions:

A concept for organizing and delivering health care

that strives for:

Better care and incentive alignment to outcomes

Increased proactive, preventative health care

Access to the right care and a better, more effective patient

experience

Lower cost

Value-based, data-driven, patient-centered care that

rewards quality over quantity

Accountable Care -2

When is data needed? Improving patient outcomes

Operational efficiency

Population health interventions

Risk stratification

Strategic decisions

Testing different models of care

5/2/2014

4

Accountable Care requires:

Data-Driven Decision Management at all levels of your

Health Centers

Accountable Care -3

Objectives for Today

1. Explain the link between Accountable Care and Data and

Analytics

2. Learn how to use Data-Driven Decision Management in

the Health Center setting

Explain two key tactics to make data more accurate

Describe four tactics for using data to improve performance

5/2/2014

5

Disclosures Partnership HealthPlan of California:

Not for Profit Medicaid Health Plan

Organizations are Defined by Decisions

Examples:

Day to day operations: How many same day

appointment slots are saved for a Monday versus a

Wednesday?

Population management: How does Health

Center increase the cervical cancer screening rate?

Achieving outcomes: How are interventions for

each patient customized to improve disease

management?

Strategic decisions: Decision about whether or

not to build a new building.

Decision Management -1

5/2/2014

6

How Does your Organization Make

Business Decisions?

Decision Management -2

Decision Making:

Without Data

Data-driven Decision

Management

Based on emotions

Based on prior experience

Based on following others’

examples

Based on following others’

advice

Based on rough estimates

of financial impact

Based on regulations

Business decisions are

based on effective analysis

of verified data.

Decision Management -3

5/2/2014

7

Data-Driven Decision Management Abbreviated DDDM

MIT Center for Digital Business 4% higher productivity,

6% higher margins

Three components:

data accuracy,

data analysis,

interpretation of data and analysis

Decision Management -4

Health Center: BP Control Clinic Traditional decision-making method to change BP

medications

Pharmacist Run BP Control Clinics

Standardized method of checking BP

Standardized follow-up timing

Age-Based targets for control

Standardized algorithm for medication changes

Standardized nutritional curriculum

Coupled with education of PCPs on how to respond to abnormal BP readings

Will this lead to improved outcomes?

Decision Management -5

5/2/2014

8

Data Driven Disaster Serious problem caused by one or more ineffective data

analytic processes.

Decision Management -6

Data Accuracy

Axiom A: Never draw conclusions from the first report of data; there are always fundamental issues with the data to be fixed.

“If you torture data enough, it will confess”

Data Accuracy-1

5/2/2014

9

Data Credibility Example: UDS report

Race/ethnicity information

UDS report requirements

Definition of Native American

How patients think about ethnicity

How staff thinks about ethnicity

Each year: Report Generated

Free text

Blank

Acceptable format, but not what patient believes

Large gaps: do you fix this year’s data or just report it?

What do you do for next year? Data Accuracy-2

How should we approach a massive

data accuracy problem?

Another Example: Kaiser encounter data to health plan has

always been incomplete

Clean up of data is daunting, too massive.

Ask nicely to give us better data in the future

No change, but only noticed once per year.

Data Accuracy-3

5/2/2014

10

Achieving Data Accuracy

Principle 2: Fix accuracy of data going IN,

first, then decide if worth fixing old data.

Data Accuracy-4

Whose responsibility is it to have

reliable data?

Users of the DATA?

IT?

Management?

Creators of the Data?

QI (to help look for root causes of poor data)?

Or EVERYONE!

Data Accuracy-5

5/2/2014

11

Solutions for Improving Data Accuracy

1. Principle 3: While many departments work to

improve data accuracy, key to success is engaging

Data Creators

2. Get clean data entered in the first place:

Connect data creators with data customers

Start with Reports

Data Accuracy-6

Achieving Data Accuracy Create a good scorecard,

showing close to real-time

accuracy of the data going in.

Use of scorecard

Competition

Training Gaps

Process Improvement

Give units flexibility on how to

improve accuracy. Options:

Daily review

Lean six sigma

Internal competitionData Accuracy-7

5/2/2014

12

Creating a Good Scorecard Frequent feedback

Small number of measures, where actual action on these

measures is expected.

Psychological effect of how data is presented.

Measure the Error Rate, not the Success Rate.

Data Accuracy-8

Measuring the Error Rate: Example:

Compliance with Treatment authorization timeliness:

2 out of 200 TARS not processed in timely way: 99% processed

timely: range 0 to 30 at the end of each day.

In the last 10 days, the number of days that all TARS processed

timely was 1/10 or 10%.

Data Accuracy-9

5/2/2014

13

Some Barriers to Data Accuracy Lack of commitment to Data-Driven Decision

Management

Managers don’t know how to fix the problems

Managers refuse to admit that their data is substandard.

The organization doesn’t have the staff time to fix data problems

Solutions:

Fixing data accuracy company wide requires leadership of Senior Leaders.

Fixing this at department level will create pockets of good data.

Data Accuracy-10

Data Driven Decision Making

Axiom B: There is no such thing as a “simple” data request

Data Driven Decision Management-1

5/2/2014

14

Data driven decision-making Do you wait until have a data warehouse with reporting

tools, analytic software, excellent analysts, accurate data?

Or, do you start with the data that you have?

Data Driven Decision Management-2

Data Driven Decision Making Sometimes also called Evidence Based Decision Making

If not using the data that you already have to drive decisions, you

are not likely to do this with the addition of EDW, analysts,

reporting software.

Principle 4: Use the data you have to make Data-Driven

Decisions

Data Driven Decision Management -3

5/2/2014

15

Four tactics to use data to improve

performance

1. Give decision-makers near real-time performance data

at their fingertips.

2. Establish one, undisputed source of performance

data

3. Consciously articulate business rules and update them.

4. High quality coaching to decision-makers on a regular

basis (change the culture).

Data Driven Decision Management -4

1. Performance data at fingertips Examples:

daily call center volume by team from yesterday

Pharmacy TARS: daily amount of “new work” to be addressed

in coming day.

Use scorecards of measures that the managers can control.

Data Driven Decision Management - 5

5/2/2014

16

2. Establish one undisputed source of

performance data

Select data to be used, present to one team:

Clean up data coming in to make it more accurate.

Spread this to other teams

Look for new opportunities to clean up data

Data Driven Decision Management - 6

3. Continuously Articulate Business

Rules and Update them

Business rules definition:

Mechanism for specifying what

actions should be taken in a given

circumstance:

Broad business rules

Granular business rules

Align actions of the operational

decision makers with the strategic

objectives of the company

Components: Description of rules,

flowchart, training materials

Data Driven Decision Management -7

MA Evaluates BP (sitting)

BP elevated for age?

BP entered in Medical Record

Proceed with other vital signs

No

MA checks BP after patient

standing for 1 minute

Yes

BP still elevated for

age?No

Pharmacist evaluation of Medication Compliance

5/2/2014

17

4. Provider high quality coaching to

decision-makers on a regular basis

Coaching may focus on all

managers or individual

managers.

Training of coaches to be more

effective.

Lean-Six Sigma process analysis

Small tests of change: FOCUS-

PDSA cycles

Presentation of data

Other communication strategies

Data Driven Decision Management -8

Review Accountable Care requires Data Driven Decision Making at all

levels of the organization

Data-driven decision making in the Health Center setting requires Data accuracy Analysis Interpretation

Fix accuracy of new data before tackling old data cleanup

Engage the data creators to improve data quality

Four key steps for using data to drive improved performance Performance Data at fingertips of decision-makers

One undisputed source of performance data

Articulate business rules Decision-making coaching to change culture

5/2/2014

18

Questions and Comments?

References Ross, Beath, and Quaadgras, Dec. 2013. “You May Not Need

Big Data After All,” Harvard Business Review.

Redman, TC. Dec. 2013. “Data’s Credibility Problem.”

Harvard Business Review.