ICD-10 Readiness and Clinical Research Is your research … · May 22, 2008 Presentation titlePage...

May 22, 2008 Presentation titlePage 1

ICD-10 Readiness and Clinical ResearchIs your research compliance program ready for the transition?

HCCA Research Compliance Conference

3 June 2014

Co-presenter

Page 2 HCCA Research Compliance Conference

Your speakers

Erika Stevens

Senior Manager, Health Care Advisory

Ernst & Young LLP

Mary Rydman

Director, Human Research Protections Office (HRPO)

Dignity Health



Using a case study

Using Dignity Health as the case study, this session describes clinical research compliance issues impacted by ICD-10 conversion, and includes an in-depth analysis of processes for mitigating research compliance risks impacted by ICD-10.


Learning objectives

► Describe research compliance issues impacted by ICD-10 conversion

► Analyze key processes for mitigating research compliance risks resulting from ICD-10

► Evaluate a large health system’s approach to readiness for ICD-10 conversion, and its impact on the clinical research enterprise



Background and purpose of International Classification of Disease (ICD)

Clinical codes must be capable of accurately describing diagnoses, illnesses and medical procedures. They are critical to improving the quality of health care.

The Centers for Medicare and Medicaid Services (CMS) mandates conversion from ICD-9 to ICD-10 by 1 October 2015, as ICD-9 is outdated, and unable to effectively assign new codes, describe rapidly changing medical treatments and provide technological growth.

The move from ICD-9 to ICD-10 will be an overhaul!


Additional fields and new formats are among the complexities that will make implementing ICD-10 a significant undertaking.

ICD-10 introduction

The most significant difference with ICD-10 codes is that they are alphanumeric, and utilize more fields than current ICD-9 codes.

Key ICD-10-CM characteristics (diagnosis codes)

► Replacing ICD-9-CM Volume I and II; specifically designed as a “logical” predecessor

► Alphanumeric

► Restructured classification

► Certain diseases have been reclassified to reflect current medical knowledge

► Specificity and detail have been expanded

► Expanded code length

The additional fields and characters used by ICD-10 coding schemes allow for significantly more granularity, and a wider variety of codes.

Number of ICD-9 and ICD-10 codes for diagnoses and procedures

Source: ICD-10-CM and ICD-10-PCS Update, Thirteenth National HIPAA Summit, 26 September 2006; Rand Study, March 2004.



Key ICD-10 characteristics

1► Replacing ICD-9-CM Volume III; a “dramatic departure” from current practice

2► Alphanumeric and surgical codes lack decimals

3► Ability to aggregate codes across all essential components of a procedure

4

► Multi-axial structure — each code character has the same meaning within the specific procedure section, and across procedure sections

5► Ability to easily incorporate new procedures and technologies

6► All terminology precisely defined and used consistently across all codes


How does ICD-10 implementation impact clinical research?



What are the implications for healthcare research?

As part of recent reform efforts related to administrative simplification, clinical effectiveness and quality-based payments, ICD-10 becomes essential to accurate research information, billing and outcomes analysis.

► Population health research

► Quality of care research

► Care outcomes research

► Ability to effectively assign risks

► Data mining capabilities for increased analysis of diagnosis, treatment efficacy, prevention, etc.

► Ability to acquire rich clinical information, uncover phenomena, discover previously hidden relationships and create meaningful ways to advance health care

► Recruitment

ICD-10 affects:

The ultimate goal is to improve health, and to help the US health system share data more accurately in diagnosing and treating diseases.


ICD-10 impacts clinical research business and technology

ICD-10 implementation represents an enterprise-wide challenge that requires both a business and an IT solution, but can lead to beneficial returns if executed with prudence.

ICD-10 Potential impacts to clinical research

Technology

► Impact to enterprise-wide systems and processes

► Technical dependency on vendors and third-party solutions

► Complexity of required crosswalks

Impact

► ICD-10 impacts the business processes of clinical research on a daily basis

► Programs can be redesigned to take advantage of improved recruitment and population targeting

► Provider utilization of the breadth of ICD-10 can impact the effectiveness of the research enterprise

Business

► Complex research-related business processes re-engineering

► Multiple tiers of staff education and training

ICD-10 can improve clinical research capabilities, but will require organizations to understand and plan for implementation and update challenges.



ICD-10 impacts the clinical researchrevenue cycle

Scheduling/ registration

Pre-awardprocesses

Research records/case report forms (CRFs)

Charge master Post-awardprocesses

► Scheduling

► Registration

► Study budget development

► Study budget negotiation

► Contract negotiation

► Medicare coverage analysis

► Study billing grid

► Abstracting data

► Data entry

► Computer-assistedcoding

► Charge master (Embedded ICDcodes)

► Standard of care (SOC) charges

► Study-related charges

► Charge capture for study-related vs. SOC charges

► Invoicing sponsors

► Invoicing third-party payers

Clinical research revenue cycle


ICD-10 impacts participant care and finance

Ancillary departments Care management Financial management

► Tests/procedures ordering

► Pharmacy

► Laboratory

► Radiology

► Nutrition/diabetes education

► Electronic health records

► Clinical protocols

► Clinical reminder

► Performance measurement

► Disease management

► Decision support

► Cost accounting

► External data reporting

Participant care and finance



ICD-10 impacts clinical research billing

Modifier Q0 – investigational clinical service provided in a clinical research study that is in an approved clinical research study

Appropriate usage:

► When a service is performed as part of an approved clinical research study

► When the service is investigative in nature

Modifier Q1 – routine clinical service provided in a clinical research study that is in an approved clinical research study

Appropriate usage:

► When a service is performed as part of an approved clinical research study

Services conducted in clinical research are often part of routine clinical care, which is covered by Medicare, and commercial carriers. Historically, these costs were covered by sponsors. The CMS and commercial carriers provide guidance on billing for clinical research.


How does ICD-10 implementation benefit clinical research?



Benefits: detailed data

The ICD-10 coding system is more specific, and is able to capture public health data

more effectively and clearly, than ICD-9.

Benefits of detailed data:

► Alphanumeric format allows for future revisions without disrupting the current system

► More precise research due to finer code detail

► Ability for code analysis and recruitment when direct participant contact is limited or non-existent

► Enhanced ability to uncover trends, identify potential epidemics and more accurately report public health diseases, and top causes of mortality and morbidity

► The overall rankings for disease capture are found to be significantly higher with ICD-10 than with ICD-9


Benefits: data sharing

► Data may be shared among investigators in the US, but also abroad

► Data sharing is essential in determining the public’s overall health

► Each WHO-licensed country has developed its own procedure coding system. Data quality may be sacrificed, as discrepancies may exist in the data from one country to another

ICD-10 for clinical research gives researchers the ability to share data.

Without conversion to ICD-10, researchers in the US have limited ability to track and respond to global health threats.



What are the associated challenges?


Challenges

► Many opportunities for coding errors exist, ranging from inaccurate or missing information, to simply miscoded data

► Coding accuracy can be a complicated matter

► Critical in the first few months, coders may default to the best known code as opposed to the correct code, as they fully learn ICD-10 coding

► Coded data was not created specifically for research purposes

► Failure to abstract relevant data, or from incorrect coding of the abstracted data

Even when data quality is good, the diagnoses that are coded do not reflect the severity of disease, diagnostic findings are not coded and clinical sequence is not available

Research using the data must deal with data quality and validity limitations which arise because the data is not created for research purposes.

Quality of the data



Challenges (continued)

► The National Center for Health Statistics created General Equivalence Mappings (GEMs), otherwise known as “crosswalks,” to translate one code set to the other

► Some investigators will need to jump between ICD-9 and ICD-10, depending on the time frame involved in a study

Clinical research crosswalkICD-10 Z00.6 Examination of participant/control in a clinical research program

ICD-9 V70.7 Examination of participant in a clinical trial

“Crosswalking”


Challenges (continued)

Multiple implementation deferments

The health care industry is forced to respond to another delay in implementation. On 1 April 2014, President Obama authorized an ICD-10 implementation deferment after the Senate approved the measure as part of the Sustainable Growth Rate “doc fix” legislation.

The new implementation date is set for 1 October 2015.



GEMs

Why do we need them?

► GEMs are used for converting large databases of ICD-9 codes, linking data in long-term clinical studies that span the transition date or analyzing data collected before and after the transition

► Primarily, they are intended to be used for translations of code lists or code tables used by an application when codes in one code set are the only source of information

The CMS cautions that “GEMs are not crosswalks. They are reference mappings, to help the user navigate the complexity of translating meaning from one code set to the other.


GEMs limitations

► Some ICD-9 clusters map to one ICD-10 code, and some ICD-10 codes map to a cluster of ICD-9 codes. GEMs cannot provide a simple one-on-one translation.

► There are more than 8,000 ICD-10 codes that map backwards to more than one equally plausible ICD-9 code.

► Most codes have an approximate match, with one additional choice forthe most specific code mapping. GEMs have limited use for automated crosswalking.

► GEMs are useful in the same way that an English-to-French dictionary is useful. One can look up English words and their French translations, just like crosswalking from ICD-9 to ICD-10, but that does not mean that all French words in existence have a direct English equivalent, nor does every word mean exactly the same thing in every context.



Obstetrical diagnoses do not correlate due to different axes of organization

ICD-10 description ICD-9 description

026.851 – Spotting complicating pregnancy, first trimester

649.50 – Spotting complicating pregnancy, unspecified episodeof care

026.852 – Spotting complicating pregnancy, second trimester

649.51 – Spotting complicating pregnancy, delivered

026.853 – Spotting complicating pregnancy, third trimester

649.53 – Spotting complicating pregnancy, antepartum

Technical challenges: data comparability

In order to effectively interpret data across periods, mappings are required to associate ICD-10 codes with corresponding ICD-9 codes (and vice versa).

Example of ICD-9 to ICD-10 mappings


Successful ICD-10 implementation into the clinical research enterprise

In order to be successful, organizations will need to start early to successfully plan and execute a strategy for implementation of ICD-10 into clinical research processes.

► Senior sponsorship and leadership will be critical

► Transforming research processes related to ICD-10 will require enough lead time to allow the organization to develop sufficient proficiency by the required personnel

► Process transformation will need to be coordinated with software changes to successfully support early adoption, and/or dual processing of ICD-9 and ICD-10 codes

The “sleeping giant” is an organization’s inability to recognize the breadth and magnitude of the required transformation, and to not start planning early enough.



ICD-10 and clinical research case study: Dignity Health


Dignity Health profile

► Founded in 1986, and headquartered in San Francisco

► Dignity Health is the fifth largest hospital provider in the nation, and the largest hospital system in California

► 60,000 employees

► Presence in 17 states, including 41 hospitals in Arizona, California and Nevada

► $15 billion annual revenue



Research activity at Dignity Health

► 33 hospitals conduct clinical and/or data research

► 1,000 open clinical and data trials

► 2,000+ individuals are involved in the management and oversight of research

► Numerous medical foundations, clinics and physician groups

► Five regional Institutional Review Boards (IRB)

Each dot on the map is a research site


Scope of research at Dignity Health

General research activity:

► Drug

► Device

► Biological (stem cells)

► Genomics

► Procedure

► Data

► Nursing/social behavioral

► Animal

► Bench

► Tissue/bio-repository

► Decedent (organ donation)



ICD-10 and clinical research case study: assessment of ICD-10 impact to clinical research at Dignity Health


ICD-10 transition impacts at Dignity Health

All of Dignity Health is impacted

► ICD codes flow through operational processes, systems and analytical tools at Dignity Health and associated entities

► Payers and vendors represent complex connection points

► Current staffing may not meet the increased demands

► Increased specificity will require enhanced physician documentation, and may result in a drop in physician productivity

Challenges

► Complex planning for system-wide transition

► Business and technology strategy and remediation

► Process reengineering, training and change management

ICD-9-CM (Diagnosis)

3-5 digits primarily numeric (except V

and E codes)≈14,000 unique

codes

ICD-10-CM7 alphanumeric

characters> 68,000 unique

codes

ICD-9-CM (Procedure)

3-4 digits≈ 4,000 unique

codes

ICD-10-PCS (Inpatient)

7 alphanumeric characters

> 72,000 unique codes

Note: procedure codes only applicable to inpatient facilities



The ask

► Dignity Health is required to comply with ICD-10, a regulatory requirement that involves updating 30+ year-old diagnosis codes used within the industry to facilitate the transfer of information between payers and providers. Becoming ICD-10 compliant requires significant changes to Dignity Health’s processes and supporting technology.

► Dignity Health desired to understand the research community’s transition readiness for the new code set, and to determine current and future use of ICD codes for clinical research activities.

► An ICD-10 and clinical research survey was conducted to garner a better understanding of the impacts to Dignity Health’s clinical research enterprise.

► The migration from the current ICD-9 standard to the ICD-10 standard will be a complex organizational change for Dignity Health and its clinical research community.


Steps taken

ICD-10 and clinical research survey

► The clinical research and ICD-10 survey was sent out to approximately 90 selected contacts within Dignity Health’s clinical research community on 14 September 2012

► The purpose of the survey was to determine current and future use of ICD-9/10 codes for clinical research activities and transition readiness within the research community

► Initial summary analysis included a total of 79 received survey responses



Clinical Research Thought LeadershipGroup (TLG)

The purpose of the TLG is to address the areas of clinical research that could potentially be impacted by the change from ICD-9 to ICD-10. Impacted areas may include:

► Data integrity crosswalk

► Billing compliance training

► Data elements/feasibility

► Organizational readiness

► Clinical research IT remediation


Challenges and obstacles

► Numerous facility departments/personnel involved in billing process:► Research office/contracts, budgets, coverage analysis

► Principal investigators/research coordinators

► Patient registration

► Clinical departments

► Health information management

► Patient financial services

► Billing regulations require the use of multiple documents to determine what is billable to study sponsors and/or third-party payers. Study documents should be consistent, but often they are not.



Current use of V70.7 – how well is Dignity Health doing now?

High-level, system-wide report:

► All inpatient or outpatient claims with ICD-9 code V70.7 were reported in primary or secondary condition

► Timeframe: past five years to present

► All payers

► All Dignity Health facilities


V70.7 report questions

How accurate is the report?

► For the facilities represented, does this look like the report expected?

► Is every facility that engages in research appearing on the report?

► Is every facility listed under a Dignity Health IRB?

► Does the number of accounts for each facility reflect the number of subjects enrolled?

► How active is each site in making sure the codes are added tothe bill?



Managing payer denials based on V70.7 and patient enrollment

High-level, system-wide report:

► All inpatient or outpatient claims with ICD-9 code V70.7 were reported in primary or secondary condition

► Timeframe: past five years to present

► All payers

► All Dignity Health facilities


Limitations on denials report

Report includes any encounter with a diagnosis code of V70.7 and a denial from a payer at some point in time

► The denial may NOT have anything to do with the diagnosis code –hard to ascertain actual denial reason

► Does not indicate which particular study the patient was enrolled, or service received

► In most cases, researchers are not notified of denials by patient financial services

► In some cases, denied and aging claims were turned over to collections, and patients would arrive to the clinic with a research consent stating they would not be billed



Survey results

► 60% of respondents utilize ICD codes for patient identification and/or recruitment purposes

► 45% of respondents capture ICD codes as a data element

► 25% of respondents utilize ICD codes for ongoing monitoring of enrolled subjects

► 63% of respondents answered “no” when asked if they were aware of a strategic plan within their facility to address ICD-10 within the clinical research enterprise


What Dignity Health learned

► Dignity Health’s system needs a comprehensive and centralized research billing compliance plan and program

► Dignity Health needs to be in compliance with the National Coverage Determination Medicare Clinical Trial Policy

► Primary challenge for ICD-10 preparation is knowing when to add the research code initially

► Very little IT impact with regard to automated reporting, data collection, subject recruitment and on-site data repositories

► Very low awareness of ICD-10 implementation in general



Opportunities garnered from the survey

The research community faces significant challenges associated with ICD-10 implementation. However, conducting this survey affords Dignity Health leadership the ability to:

► Establish a plan for mitigating challenges associated with ICD-10 implementation in its clinical research business and technology operations

► Embrace and champion change efforts, and its visibility sets the direction for major initiatives related to clinical research and ICD-10 impacts

► Better understand the organization’s need for training and education to support ICD-10 implementation readiness

► Initiate dialogue with investigators and research staff regarding the process of mapping of ICD-9 codes to their ICD-10 equivalent for multiple areas within the clinical research enterprise

► Potentially align themselves with industry partnerships to grow Dignity Health’s research portfolio by sharing investigator’s data


ICD-10 and clinical research case study: back to the basics



The desired result

Correct billing/ reimbursement

Denial management if

necessary

Subject enrolled

Subject flagged by registration

HIM/coding notified patient is

a research subject

Correct coding/V70.7

Adding Q0 & Q1 modifiers

Adding NCI number to claim

Bill reviewed/ adjusted per billing plan


ICD-10 and clinical research case study:next steps



System review of current practice

Dignity Health and our revenue cycle vendor are conducting a system-wide review of research billing operations:

► Presentation of findings and recommendations

► Documenting future state process flows for both Dignity Health and our revenue cycle vendor

► High-level reporting of findings to Clinical Research Billing TLG

► High-level roadmap to remediation


How will Dignity Health achieve billing compliance?

► Develop means to coordinate and communicate study information; identify all key personnel and departments involved in billing process

► Develop and promote transparency in study documents

► Develop and document process; develop clear, written procedures for operationalizing Dignity Health’s policies and procedures related to research billing



Answering basic questions and clarifying common misunderstandings

► When must the V70.7 be used?

► Registered with Clinicaltrials.gov?

► Funded studies?

► Unfunded studies?

► Routine but research?

► Screen failures?

► Registry studies?

► When will a study have a National Clinical Trials identification number?

► Who is responsible for each step?

► Who is accountable for compliance?


Learning objectives review



Learning objectives

► Describe research compliance issues impacted by ICD-10 conversion

► Analyze key processes for mitigating research compliance risks resulting from ICD-10

► Evaluate a large health system’s approach to readiness for ICD-10 conversion, and its impact on the clinical research enterprise


Questions?



Appendix


Overview of longitudinal survey relatedto ICD-10

The purpose of the survey is to determine current and future use of ICD-9/10 codes for research activities.



Longitudinal survey results summary

Role of survey respondents within clinical research:

► Clinical coordinator (84%)

Primary areas of research identified in survey:

► Oncology (37.5%), Neurology/Stroke (33.3%), Cardiology/Interventional cardiology (14.6%), Surgery (14.6%)

Research funding sources:

► Commercial (65%) and federal (46%)

Tools used for research data collection:

► Sponsor tools (73%), paper (58%), Excel (37%)

Facilities currently using ICD-9 codes for research:

► 31.3%


Longitudinal survey results summary (continued)

How facilities currently use ICD-9 codes in research:

► Patient identification (48.4%), uncertain (29%), capture code as data element (16.1%)

How longitudinal outcomes are tracked:

► Both prospective and retrospective data collection (58%), prospective data collection (22.6%)

Awareness of strategic ICD-10 planning within clinical research:

► Uncertain (52%), none of the studies will require conversion (32%)



Longitudinal survey results next steps

► Review identified study protocol for enrollment methodology

► Identify current methods for enrollment and feasibility studies

► Review inclusion/exclusion criteria

► Assess need for crosswalk

► Identify requirements for data extraction

► Identify studies impacted by ICD-9 and ICD-10


Role of survey respondents withinclinical research

84%

2%4%

4%2%2%2%

Clinical Coordinator Regulatory Coordinator Research Assistant

Principal Investigator Clinical Research Coordinator Program manager

Oncology Reasearch Nurse

What is your role?



Primary areas of research identified in survey

Other responses varied from heart/lung transplant, neurosurgery, electrophysiology, congestive heart failure, radiation oncology, Parkinson’s disease, hematology, pathology and wound care.

14.6%

33.3%

8.3% 8.3%

37.5%

14.6%18.8%

0.0%5.0%

10.0%15.0%20.0%25.0%30.0%35.0%40.0%

Ane

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Ca

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Cri

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End

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Sur

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Unc

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er

(ple

ase

spec

ify)

What are the primary therapeutic areas of your research?(choose all that apply)


Research funding sources

45.8%

64.6%

25.0%

14.6%

6.3%10.4%

14.6%

6.3% 6.3%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

Fed

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l

Co

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ial

Inve

stig

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Initi

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d a

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stig

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Initi

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Sta

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Dig

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He

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osp

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Fo

und

atio

n

Un

fun

ded

Unc

erta

in

Oth

er

(ple

ase

spec

ify)

How is your research funded?(choose all that apply)

Other responses included pharmaceutical industry and School of Medicine with grants for commercial sources.



Tools used for research data collection

37.5%

12.5% 14.6%

58.3%

72.9%

2.1%8.3%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%E

xcel

Acc

ess

Hom

egro

wn

syst

em

Pap

er

Spo

nso

r to

ols

Unc

erta

in

Oth

er

How does your facility track data collected for your research?(choose all that apply)


Other methods of data collection

► Per monitoring visit, data collection and electronic data capture

► Electronic case report forms (eCRFs)

► Electronic data systems

► Invivo, Inform eCRFs and Oracle RDC

► Sponsor electronic data capture secure websites

► Various programs: DataTrack; RAVE; Inform

► Electronic and paper case report forms

► Homegrown systems and tools (residents use paper and own tools for data-only studies)

► Sponsor tools:

► Electronic data capture websites

► eCRFs with Clinical Research Organizations (CROs) (PPD, Intralinks, etc.)

► Electronic budget tools and invoicing provided by CROs

► Paper forms

► Specific electronic databases

► Proprietary software systems

► Internal Excel financial data tools



Facilities currently using ICD-9 codesfor research

31.3%

35.4%

8.3%

18.8%

6.3%

Yes

No

Does your facility utilize ICD-9 codes for research purposes?

31.3% of survey respondents answered “yes” when asked if their facility currently uses ICD-9 codesfor research purposes.


How facilities currently use ICD-9 codesin research

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

Pat

ien

tid

entif

icat

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/rec

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ent

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ang

es

Unc

erta

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Oth

er (

ple

ase

spec

ify)

How does your facility utilize ICD-9 codes?(choose all that apply)



How longitudinal outcomes are tracked

22.6%

6.5%

58.1%

12.9%

Pro

spe

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ata

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0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

For studies with long-term follow-up, how are outcomestracked over time?


Awareness of ICD-10 planning withclinical research

12.9%

0.0%3.2%

0.0%

32.3%

51.6%

Les

s th

an

25

%

25-

50%

50-

75%

Gre

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an

75

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No

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sion

Unc

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0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

For longitudinal studies requiring conversion between ICD-9 and ICD-10, on average, what percentage of data per study do you

estimate will require conversion?


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ICD-10 Readiness and Clinical Research Is your research … · May 22, 2008 Presentation titlePage...

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