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Seven Opportunities for

Information Governance

Rita Bowen, MS, RHIA, CHPS, SSGB

Overview

• Benefits

• Information Governance Today

• Recommendations on Beginning an IG Program

• Seven Opportunities for Information Governance

• Three Key Points to Achieve Information Governance

• Connect the Dots Within the EHR

• Ultimate Goal for EHR data

Benefits

• Benefits of a strong information governance program:

– Greater staff efficiency

– Better quality and patient safety

– Return on investment for EHRs

– Identification of additional data opportunities

– Others

• Why HIM?

– HIM Professionals manage information

– Global perspective

– Forward looking

– Relationship builder for the data

– High integrity/data integrity

– Collaborative

– Open minded

Information Governance Today

• Benchmarking Survey Highlights

– Information governance programs are less prevalent and less

mature in healthcare organizations than is warranted

– Most organizations have not yet established a comprehensive

strategy for information governance

– The information governance framework and its foundational

components call for strengthening and expansion

– Information lifecycle management practices related to core

functions require improvement

Benchmarking Survey Results

50 %

Privacy Policy &

Practices

44%

Security Policy &

Practices

26%

Destruction

30%

Information Deletion

37%

Ability to preserve only relevant information in response to a

legal hold regardless of information type

50%

Records Stored

Onsite

42%

Records Stored Off-

site

Recommendations on Beginning an IG

Program

– Create a vision to drive change

– Obtain buy in from organizational management and compliance

– Convene a multidisciplinary steering committee

– Consider all functions of the information life cycle

– Conduct an assessment

– Use the Transformational HIM Model

– Identify the data flow

– Use what you learn from the current state assessments to

bolster conversations about the need for change

– Role –based access

– Leverage improvements aligned with changes already underway

– Develop measures and metrics

– Develop a time frame

– Take an incremental approach

1 – Information Integrity

• Clean Master Patient Index (MPI)

– Monitor, report, and correct errors

– BEST PRACTICE GOAL: <1%

• Policy and Procedures that promote data integrity

– Copy Functionality

– Corrections and Amendments

– Standalone Devices

• Hybrid Health Record… Issues

• Technology Vendor... Issues

• Data Dictionary

– Creating a data dictionary

– Elements

• Data Mapping

Integrity and Quality

• Design and Capture

• Content and Records Management

• Access and Use

1 – Information Integrity

• Potentially Problematic in EHRs per AHIMA Practice

Brief in August 2013:

– Template Documentation

– Cloning, Copy / Paste

– Voice Recognition without Validation

– Patient Identification

– Authorship of Entries

– Integrity of Amendments

Ross’s Cost of Quality Rule of 1-10-100

1 cost to

prevent

100

10 cost to

correct

Failure Cost

*Linda Kloss, Implementing IG, lessons from the field

2 – Information Use

• Benchmarks

– Quality

– Patient Outcomes

– Modeling /clinical

• Analyzing

– Marketing

– Predictive analytics

• HIEs & VDTs

– A single error in an electronic environment presents a risk that

can be magnified as the data transmits further downstream to

data sets, interfaced systems, and data warehouses.

• Reporting Purposes

• Healthcare Reform

2 – Information Use

• Lost revenue for inappropriately managing information use

– 14% of a company’s revenue can be lost when the enterprise does not manage and analysis data

– 40% of executives in the healthcare industry gave themselves a “D” or “F” rating regarding their level of preparedness for a data deluge (97% of the C-level that responded to the survey… stated “that they still had to make changes to improve information optimization”

• It is HIM’s responsibility to investigate and quantify the potential costs associated with inaccurate, incomplete or compromised data.

3 – Increase Data Confidence

• “Quality and safety, cost control, payment reform, care

delivery redesign and complying with regulatory changes

are top goals for healthcare organizations and all are

highly dependent on trustworthy information.”

• Established consistent data models will assure the

integrity and quality of the data maintained in the E-HR

• Standardization of:

– Data definitions

– Structure of clinical content (including smart text)

– Quality check points

– Auditing procedures

4 – Streamline Release of Information

• Bring ROI under one umbrella

– Fewer privacy concerns

– Enterprise strategy

• Definition of

– the “legal health record”

– Designated Record Set (DRS)

– Electronic-DRS

• Points to Ponder:

– Can your EHR be trusted for quality – or do you require a vendor to validate before

using data?

– Do you have absolute assurance that the correct information is being provided for

audit requests, etc.?

• Omnibus – focus to Minimum Necessary

– You should question Business Office Processes and sharing of health information.

– Can you account for all release of information activities?

5 – Information Lifecycle

Create

• Entered

• Purchased

• Derived

Process

• Moved

• Calculated

• Edited

• Transformed

Store

• Structured

• Unstructured

• Semi-structured

Transport

• Exchanged

• Transmitted

• Copied

Present

• Reported

• Analyzed

Archive

• Backed-up

• Vaulted

Purge

Risk

Information Lifecycle Recommended Actions

• Strengthen the IG practices of managing information throughout its lifecycle,

from creation or receipt through final disposition

• Establish interdepartmental teams to develop and apply reasonable,

workable IG practices to newer technologies and information types

• Formalize IG practices to enhance the integrity, quality and trustworthiness

of information

• Leverage the mature aspects of privacy and information security to enhance

other components of information governance

• Employ automated tools to identify and delete information that is eligible for

destruction

• Define effective practices to identify and preserve information needed for a

legal hold, reinstating business-as-usual practices upon conclusion of the

legal matter

• Establish routine and comprehensive assessments to identify areas of

vulnerability and opportunities to refine IG program components

6 – Computer Assisted Coding

• Dr. Sam Ho, Chief Clinical Officer at United Healthcare, noted during his

keynote address at AHIMA’s 2013 Coding Summit, ICD-10, Documentation,

and Computer Assisted Coding (CAD) to achieve the

– Better care of individual

– Better health for populations

– Reducing per-capita costs

• Vendor data integrity checklist

– Discussion of AHIMA Foundation Research in collaboration with the

Cleveland Clinic

• The Foundation/Cleveland Clinic research sought to answer the following

questions:

– Is there a measureable difference between traditional coding and the

uses of CAC in terms of coding timeliness and accuracy?

– Will the use of credentialed codes in conjunction with CAC result in

improved timeliness and accuracy?

7 – E-Discovery Preparation and HIM’s Role

• E-discovery is defined as the pretrial legal process used

to describe the method by which parties will obtain and

review electronically stored information. The 2006

Federal Rules of Civil Procedure (FRCP) served to place

electronically stored information (ESI) on equal footing

with paper documents in the eyes of the court.

– ESI of any kind can serve as evidence. This may cover any type

of ESI data or devices including, but not limited to, text, images,

voice, databases, spreadsheets, legacy systems, tape, Smart

phones, tablets, instant messages, e-mail, calendar files, and

Websites.

7 – E-Discovery Preparation and HIM’s Role

• Refer to AHIMA’s Practice Brief:

– AHIMA. (2013). E- Discovery Litigation and Regulatory

Investigation Response Planning: Crucial Components of Your

Organization’s Information and Data Governance Processes.

Journal of AHIMA 84(11), expanded web version.

Opportunity to advance HIM, as threaded

throughout the healthcare eco-system

• Privacy and access

• Data integrity and management

• Records lifecycle management

• Compliance and legal

• Coding and revenue cycle

• IT applications and security

• +++++++++

Three Key Points

• To achieve the full benefits of information governance, AHIMA believes the

following must be addressed:

– An accountability framework and decision rights to ensure the effective

use of information, enterprise-wide

– The defined processes, skills, and tools to manage information,

throughout its entire lifecycle, as a critical business asset

– The essential standards, rules, and guidelines for functioning in an

increasingly electronic environment

• In an EHR, it is imperative these content standards are built in the fiber of

decision making screens, templates, drop-down lists and other tools for

documentation. The IG standardization required include:

• Data definitions

– Structure for clinical content (including smart text)

– Quality check points

– Auditing processes

– Consistent data models

Ultimate IG Goal for EHR Data

• Accurate

• Complete

• Concise

• Consistent

• Universally understood by data users (design)

• Supports the legal business record & care process

• It is critical that both structured and unstructured data meet a

standard of quality if they are to be meaningful for internal and

external use, such as continuum of care and secondary purposes.

• Factors such as ease of use and design can facilitate adherence to

documentation guidelines and standards.

References

– AHIMA. (2013). E- Discovery Litigation and Regulatory Investigation Response

Planning: Crucial Components of Your Organization’s Information and Data

Governance Processes. Journal of AHIMA 84(11), expanded web version.

– AHIMA & Cohasset Associates. (2014). A Call to Adopt Information Governance

Practices. Benchmarking White Paper.

– Bowen, R. & Smith, A.R. (2014). Developing an Enterprise Data Strategy. HFMA.

Retrieved from https://www.hfma.org/Content.aspx?id=22046

– Demster, B. (2012). Data Ownership Evolves with Technology. Journal of

AHIMA, 83(9), pp. 52.

– Kloss, (2014) Implementing Health Information Governance, lessons from the

field. AHIMA product #AB100213.

– Landsbach, G. & Just, B. H. (2013) Five Risky HIE Practices that Threaten Data

Integrity. Journal of AHIMA 84(11), pp. 40-42.

– Practice Brief. (2013). Integrity of the Healthcare Record: Best Practices for EHR

Documentation. Journal of AHIMA, 84(8), pp. 58-61.

Questions

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