Analytics for Compliance:A Case Study of Deployment

Barbara J. PiascikSr. Vice President/Chief Compliance Officer

St. Vincent Catholic Medical Centers

1

Topics of Discussion

� Introduction to St. Vincent Catholic Medical Centers

� Preparing the data

� Workflow and process improvement

� Sample results

� Risk assessment

� Measuring success

2

St. Vincent Catholic Medical Centers

� Services as a major healthcare resource for the New York Metropolitan area

� Anchored by St. Vincent’s Hospital Manhattan in Greenwich Village 440-bed acute care hospital

� Facilities also include:

– Behavioral health hospital

– Skilled Nursing/Hospice Facilities

– Home Health Care agency

– physician practices with multiple outpatient services

– An ambulance company

3

New York Experience

� NYS Office of Medicaid Inspector General – has developed tools and extensive staff to use

data for review, potential audits and program improvements

� 1300 published audits over the last 18 months

4

St. Vincent Position and Strategy

� Need for improved visibility into our data

� Manual processes were inefficient

� Reacting to the data rather than being ahead of the data

� Decision made to implement data analytics

5

Healthcare Analytics

� Definition: A rapidly evolving field of healthcare business solutions that make extensive use of data, statistical

and qualitative analysis, explanatory and predictive modeling.

� If you don’t review your own data somebody else will be looking.

6

Who is looking at your data?

� OIG

� MIC

� OMIG

� RAC

� Quality organizations

� Your patients

� Commercial payers

7

Data Mining – What is it and what do we do with it??

� Definition: The process of extracting patterns from data.

� Track & Trend

� Equal Results

•Slice & Dice

8

Data Friend or Foe???Warning

� Too much vs too little

� Dangers:

– Privacy

– Encryption

– Accuracy

– No plan

9

Convert to Usable Format

� Home grown report writer or database

� Known tools like Access or Crystal

� Bolt on system

� Enterprise analytics

10

Data, Data Everywhere

� How to begin

– Inventory of current systems

– Inventory of current reports

– Implementation team of stakeholders

– Ultimate purpose of data

� Determine what to measure

� “Single Source of Truth” across organization

11

Gathering the Data

� How to get information into system for analysis

� Convert information into useable format

� Verify that data is accurate and complete

� Automate as much as possible

12

AccuracyMission Critical

� Data must be trusted to be:

– Correct

– Complete

– Current

– Old stuff

� How much is too much??

� How old is usable?

13

Warning – WarningBe Careful What You Ask For

� Too much information can destroy a project

� What are my key metrics to measure?

� Targets for my key metrics?

� How often – daily, weekly, monthly?

� Is there time to review data timely?

� Can it promote an action?

14

Workflows

� Who needs the information?

� Is the process manual – as user wants to see

it or automatic?

� If it is automatic, is there accountability for review?

� If data shows problem – what happens??

15

Success!!!

� SVCMC’s Patient Access Department

� Analyze and right “rules” for our organization

� Data sent daily for previous day

� Each day report of errors sent to various supervisors

� Sorted by registrar

� Current policy all must be corrected within 24 hours

� Clean bill rate from 78% to 99% in just 6 months

16

Sample Graphs

17

Looking Good!!!

� Sophistication of presentation

� Board of Directors

� Senior Management

� Who needs details

� Quick highlights of negative trends

18

Challenges

� Lots and lots of internal systems

� Internal resources

� Lots of trial and error

19

Did what you fix work??

� Monitoring

– Dashboards and key performance metrics

– Efficiency tools, i.e. targets and automatic alerts

– Allows for accurate monitoring of corrective action

– Timely fixes

� Process improvement

� Managing performance

� Measuring success

20

Risk Assessment

� How do you find where your risks are hiding?

� Rules engine (100s of RAC rules alone)

� Benchmarking to standards (PEPPER, MEDPAR)

� Trend analysis

21

New Ideas

� Review of potential audits out there

� New service – is it successful?

� Old service – still needed?

� Government workplans

22

Operational Uses

� Some uses of analytics– Top 10 tests done

– Top 10 most expensive tests

– Wait times

– Geographical analysis

– Identify risk target areas prior to an audit (RAC/MIC) and

proactively change HIM/coding/billing practices

– Understand the financial impact of dollars at risk across a portfolio

of accounts

– Identify root causes (coding and documentation) of compliance

risk

23

Risk vs Reward

� Problems revealed

� Action needed

� Potential self-disclosure

� Able to find a problem quickly

� Allows for quick review of multiple risks

� Consistent data

24

ImplementationWorth its Weight in Gold

� Do your research – not all analytics systems are the

same

� Partnering with the system vendor

� Usable information

� Good results require:

– Time

– Energy

– Resources

– Good IT tools

– Purpose in mind

25

Changes, Changes, Changes

� Learn it – it changes

� How quickly do you know

� How timely do you find out

26

In Summary

� Good channels of internal communication

� Measuring the right data

� Workflow aligned for action

� Proactive analyses

� Ongoing monitoring of data

� Assessing success

27

Thank You

� Contact information

– Barbara J. Piascik

– 212-356-4538

– bpiascik@svcmcny.org

28

Questions

Enjoy the rest of the conference!!!

29