Seven Opportunities for Information GovernanceAlisha R. Smith, RHIA

Overview

• Benefits• Information Governance Today• HIM Core Model• 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

HIM Core Model

POLICY

EDUCATION

R ESEA R C H

S T A N D A R D S

Health InformationGovernance and Stewardship

Data Capture, Validation & Maintenance

Information Analysis,

Transformation & Decision

Support

Information Dissemination

& Liaison

Health Information ResourceManagement and Innovation

Quality and Patient Safety

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

Unifying Information Governance

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

Data Mapping Example

Data Mapping Example

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

1 – Information Integrity

• Medical Identity Theft• Create an enterprise steering committee• Collaboration is required

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

*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.

Information Use Integrity and Quality attributes

• Accurate• Complete• Valid• Timely

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.”

• Example of a provider that didn’t trust the data

3 – Increase Data Confidence

• Quality healthcare depends on the availability of quality data. – A meaningful electronic health record (EHR) improves the ability for healthcare

professionals to enact evidence-based knowledge management and aids decision making for care.

– EHRs can have a positive impact on quality of care, patient safety, and efficiencies… HOWEVER.. Without accurate and appropriate content in a usable and accessible form, these benefits will not be realized.

3 – Increase Data Confidence

• 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

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

4 – Streamline Release of Information

• Omnibus – focus to Minimum Necessary– Question the linkage of data within the EHR.– Question Business Office Processes and sharing of health information.– Can you account for all release activities?– Are you ready for increased patient inquiry on the use and sharing of their health

information?

5 – Information Lifecycle

Risk

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

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

6 – Computer Assisted Coding

• 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?

6 – Computer Assisted Coding

• Findings of AHIMA Foundation/Cleveland Clinic Study– CAC increased coder productivity by more than 20%– Quality only achieved by pairing a credentialed coder with CAC– About 6 months (at minimum) required to fine tune NLP engine to link data for

CAC• Must continue to focus on the “fuzzy” science

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

Connect the Dots in the Fiber of Your EHR

• 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

• Observe AHIMA’s Data Quality Management Model – this is available on AHIMA’s BOK at www.ahima.org

Ultimate 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, L. (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