1

Quality Data Automation - A Journey with BISession 148, February 13, 2019

Evan Bernard, MS, Senior Clinical Data Analyst, Memorial Hermann

Mary Gatmaitan, MS, LSSGB, RN, Project Manager, Memorial Hermann

2

Evan Bernard, MS

Mary Gatmaitan, MSN, LSSGB, RN

Has no real or apparent conflicts of interest to report.

Conflict of Interest

4

• 1:30 – 1:35 Introduction of Session & Presenters

• 1:35 – 2:20 A Journey with Business Intelligence (BI)

» The State of Health Analytics

» Quality Reporting in Health Care

» Case Study: Integrating BI to report Quality Metrics at Memorial Hermann

• 2:20 – 2:30 Q&A and Session Evaluations

Agenda

5

Learning Objectives

Discuss the healthcare

organization's

conversion from paper

to an Automated BI

system for Quality data

Describe the steps

used by the Quality

Analytics team to

implement change

Define the barriers

that need to be

addressed to

ensure a

successful

implementation

6

A Snapshot of Memorial Hermann

7

Velocity

Variety

Volume

Three V’s of Big Data

Source: https://whatis.techtarget.com/definition/3Vs

8

Difficult Data

Source: https://www.healthcatalyst.com/insights/5-reasons-healthcare-data-is-difficult-to-measure

9

• As defined by the New England Journal of Medicine:

“…healthcare delivery model in which providers, including

hospitals and physicians, are paid based on patient health

outcomes.”

Value-Based Care

Source: https://catalyst.nejm.org/what-is-value-based-healthcare/

10

• Patient-centered medical homes (PCMH)

• Accountable Care Organizations (ACO)

• Value-Based Purchasing (VBP)

• Pay-for-Performance (P4P)

Value-Based Care Models

Source: https://hbr.org/2013/10/doubts-about-pay-for-performance-in-health-care

11

• Health systems are becoming repositories of data for many

departments.

• The desire for data are expanding across healthcare.

• Organizations are searching for ways to transform different types

of data into knowledge to improve overall business operations.

– Clinical

– Administrative

– Financial

– Operational

The Desire for Business Intelligence

12

• Governed quality data for each facility

– Multiple CMS reimbursement programs

– Five (5) patient registries

– CDC’s National Healthcare Safety Network

– In-house data repositories

SO MUCH DATA!

Memorial Hermann’sQuality, Patient Safety,& Infection Control

13

How can we provide the RIGHT data to the

RIGHT people at the RIGHT time?

Quality Analytics' Concern

14

Transform reports to one focused delivery platform.

Approach

Deployment strategy with department

leadershipInformation Technology (IT) department

engagement

Assessment of team’s current process Training on business intelligence software

15

Initial Team Assessment

Recorded each team members’ monthly processing times.

Ninety-six work hours were spent on the main operating report

Concerns around frequent changes to regulatory needs

Data literacy levels varied across facilities, departments, and

disciplines

Adhoc data requests extended data processing times and needed

a more intact managing system

1

3

4

2

16

17

• Team members were trained on how to use BI tool

• Introduced concepts of data visualization to team

• Incorporated previous skills and learned new skills

• Practiced redesigning current data into insightful visuals

BI Tool Education for Team

18

• Discussions with IT department

– Cybersecurity

– User Access

– Data Governance

IT Engagement

20

• Discussions with department leadership

– Competing project priorities

– Resource allocation

Departmental Strategy

• Overall / System View

• Facility View

Phase 1

Unit Specific Views

Phase 2

Patient Level

Detailed View

Phase 3

21

• Discussions with user group

– Cultural changes

– Education materials required

Departmental Strategy

22

• Thirty-two (32) dashboards for users

• Fifty-four percent (54%) reduction in repetitive tasks.

• Total number of reprocessing days went from forty (40) days to

eight (8) days

Outcomes

23

24

• Streamlined data scrubbing and created ETLs for minimal

processing

• Updated ticketing system for adhoc requests and dashboard

access

Outcomes

25

Saving the Environment

May: 1147 pagesAugust: 874

pages

November:

377 pages

26

Lessons Learned

Cultural changes are challenging but can often be the

most rewarding.

Business intelligence software transform data as

well as your workload.

Buy-in and support from leadership is essential for

new technology usage.

Implementation of a business intelligence software is only

the beginning. Your data possibilities are now endless.

27

Evan Bernard, MS

• LinkedIn: https://www.linkedin.com/in/evan-bernard-ms-

282b6447

Mary Gatmaitan, MSN, LSSGB, RN

• LinkedIn: https://www.linkedin.com/in/mary-gatmaitan-msn-

rn-99079532

Don’t forget to complete the online session evaluation

Questions?

https://www.linkedin.com/in/evan-bernard-ms-282b6447https://www.linkedin.com/in/mary-gatmaitan-msn-rn-99079532