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Presenter Disclosure:Robert E. Suter, DO, MHA, FAHA

• Financial Disclosures

– Employed by American Heart Association

• Unlabeled / Unapproved Use Disclosures

– None

Presentation Objectives:

1. Describe the current status of Stroke systems

2. Describe the ICD‐10 changes related to Stroke and CMS plans

3 Discuss the impact these and cofounding developments may3. Discuss the impact these and cofounding developments may have on stroke system of care and implementation of guidelines

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In the Beginning…..

• Greeks called it “A l ” “ t k“Apoplexy”- “struck down by violence,”

• Jacob Wepfer University of Padua in the mid-1600s discovered it was due to disruption of the blood supply to the brain

• No effective treatments

Along came Imaging

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Then a Treatment

Then a Treatment Controversy

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Meanwhile Stroke Programs Developed

• Public/Provider Education:

• Hospital Designation:

• Acute Stroke Ready Hospitals

• Primary Stroke Hospitals

• Comprehensive Stroke Hospitals

• Hospital Performance Improvement

• Target Stroke (JAMA 2014:311(16):1632‐40

Local Stroke Systems Assembled

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Then along came another treatment‐endovascular clot retrieval 

• SWIFT PRIME (Solitaire With Intention For Thrombectomy Primary Endovascular Treatment) Jeffrey L. Saver et al in NEJM. 196 patients in 39 y pcenters in seven countries

• Significantly decreased disability and increased independent 90 days after a stroke compared to IV-tPA alone (60.2% vs 35.5%; P = .0002).

• REVASCAT (Revascularization w/ Solitaire Anterior 

Circulation Stroke Within 8 Hours) Tudor G. Jovin et 

al  NEJM. 206 patients 4 stroke centers in Spain 

• Up to 8 hours significant improvement in return   to functional independence (43.7% vs 28 2%)28.2%)

• MR CLEAN study was published by Olvert A. Berkhemer, MD, et al NEJM (2015;372:11–20).,

• Intra‐arterial within 6 hours is effective/safe• ESCAPE Mayank Goyal et al in NEJM (2015; 

372:1019–1030). • EXTEND‐IA Bruce C.V. Campbell et al NEJM (2015;372:1009–

1018).

Current Stroke Systems?

• Differentiate Patients byDifferentiate Patients by Severity

• Provide for Bypass of Primary Centers

• Provide for Rapid Transfer between Facilities whenbetween Facilities when patient needs are identified

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CMS Stroke Mortality Report Card

Centers for Medicare & Medicaid Services 30‐day stroke mortality and 30‐day stroke readmissionmeasures

CMS Stroke Mortality Reporting• “AHA/ASA Fully supports the development of properly 

risk‐adjusted outcome measures for stroke. • During the development of the Centers for Medicare & 

Medicaid Services 30‐day stroke mortality and 30‐day stroke readmission measures, expressed that these measures were not adequately designed because they do not include a valid initial stroke severity measure, such as the National Institutes of Health Stroke Scalesuch as the National Institutes of Health Stroke Scale. 

• These outcome measures may be prone to mischaracterizing the quality of stroke care being delivered by hospitals and may ultimately harm acute ischemic stroke patients.” 

(Stroke. 2014;45:1589‐1601.)

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CMS and AHA/ASA?

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CMS and AHA/ASA

ICD‐10 Modifications New subcategory R29.7 Initial National Institutes of Health Stroke Scale (NIHSS) 

Code first Cerebral infarction (I63.‐) • New sub‐sub category R29.70 NIHSS score 0‐9 • New code R29.700  Initial NIHSS score 0 • New code R29.701  Initial NIHSS score 1 • New code R29.702  Initial NIHSS score 2 • New code R29.703  Initial NIHSS score 3 • New code R29.704  Initial NIHSS score 4 • New code R29.705  Initial NIHSS score 5 • New code R29.706  Initial NIHSS score 6 • New code R29.707  Initial NIHSS score 7 • New code R29.708 Initial NIHSS score 8New code R29.708  Initial NIHSS score 8 • New code R29.709  Initial NIHSS score 9 •• New sub‐sub category R29.71 Initial NIHSS score 10‐19 • New code R29.710  Initial NIHSS score 10 • New code R29.711  Initial NIHSS score 11 • New code R29.712  Initial NIHSS score 12 • New code R29.713  Initial NIHSS score 13 • New code R29 714 Initial NIHSS score 14

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The Centers for Medicare & Medicaid Services (CMS) publicly reports a 30‐day hospital‐level stroke mortality measure on Hospital Compare as part of the Inpatient Quality Reporting (IQR) program. 

Claims‐Based and Hybrid Measures of 30‐Day Mortality Following Acute Ischemic Stroke Hospitalization Incorporating Risk Adjustment for Stroke Severity Technical Report (2015)

CMS contracted with Yale New Haven Services Corporation, Center for Outcomes Research and Evaluation (CORE) to develop new stroke mortality measures that include an assessment of stroke severity in the risk adjustment models. This work was initiated in response to stakeholder feedback about the current measure and grows out of CMS’ commitment to continually improve on quality measures and to seek opportunities to develop measures with clinical data. This new measure work became possible in part due to changes in clinical guidelines and hospital practices that allow for more standard collection of stroke severity.Based on a review of the literature, community comments, and current clinical yguidelines for stroke care, we selected the National Institutes of Health Stroke Scale (NIHSS) as the stroke severity assessment to be incorporated into the measures. 

We KNOW how to reduce morbidity and mortality in stroke!

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2015 AHA/ASA Focused Update of the 2013 Guidelines for the Early Management of Patients With Acute Ischemic Stroke Regarding Endovascular g g gTreatment A Guideline for Healthcare Professionals From the American Heart Association/American Stroke AssociationWilliam J. Powers, Colin P. Derdeyn, José Bil, Christopher S. Coffey, Brian L. Hoh, Edward C. Jauch, Karen C. Johnston, S. Claiborne Johnston, Alexander A. Khalessi, Chelsea S. Kidwell, James F. Meschia, Bruce Ovbiagele, Dileep R. Yavagal on behalf of the American Heart Association Stroke Council

Stroke. 2015;STR.published online before print June 29 2015

The American Academy of Neurology affirms the value of this guideline as an educational tool for neurologists.Endorsed by the American Association of Neurological Surgeons (AANS); Congress of Neurological Surgeons (CNS); AANS/CNS Cerebrovascular Section; American Society of Neuroradiology; and Society of Vascular and Interventional Neurology

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STEMI Systems

Will ICD‐10 allow Stroke Destination Triage to Work?

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Model EMS agencies and hospitals can successfully 

put all of these components p pinto place 

Our Challenge

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f l kMission: Lifeline ‐ Stroke

Q ti ?Questions?

Thank you!Thank you!

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AHA/ASA Acute Stroke Systems of Care Vision

• “Connect the various dots” and various parts of the nations current Stroke system

• Connect regions and states into a unified interstate and national system that puts the needs of Stroke 

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patients first

• Coordinate and improve acute stroke care at all levels

We can do this, and we believe that M:L is the obvious template!

Together to End Stroke™, a national initiative to educate Americans that stroke is

largely preventable, treatable and beatable.

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Quality Programs Review

Science Advisory Coordinating CommitteeVersion: 9 30 14Version: 9.30.14

Quality is Why!

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Basic, Translational, and Clinical Research

AHA/ASA/ACC Guidelines and Statements

Traditional Role of

AHA/ASA

Scientific Sessions and Meetings 

AHA/ASA/ACC Guidelines and Statements

ACC/AHA Performance Measures

AHA/ASA

Implementation into Clinical Practice

Improved Clinical Outcomes

Marked Gaps, Variations, Disparities in Care Quality

Bridging the Gap Between Knowledgeand Clinical Practice

• Implement evidence-based care

Systems Clinical PracticeAHA/ACC

Guidelines

III I IaIIaIIa IIbIIbIIb IIII III IIIII I IaIIaIIa IIbIIbIIb IIII III IIIII I IaIIaIIa IIbIIbIIb IIII III III IaIIaIIa IIbIIbIIb IIII III II

Adapted from the American Heart Association. Get With The Guidelines; 2001.

• Improve communications• Ensure compliance • Improve quality of care

• Improve outcomes

• Clinical trial evidence

• National guidelines

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• AHA Quality Programs think of the patient, the hospital, and the healthcare provider from a system-perspective including resources for:

Heart and Stroke Systems of Care

for:

– Pre-hospital – emergency cardiovascular events

– Inpatient diagnosis and treatment

– Outpatient disease management, prevention, and follow up carefollow-up care

– System-wide providing operational excellence in Heart Failure, Stroke, and STEMI care accreditation

– System-wide data to support care of the patient from A-Z

AHA QI Programs: Comprehensive Performance Improvement System Support and Resources

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Comprehensive tools, resources, education, feedback, networking, highly

trained staff, and recognition opportunities

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AHA Get With The Guidelines®Web Based Patient Management Tool

Web‐based data entry with real ti d t lit h k

Track performance over time and against benchmarks from similar 

time data quality checks

hospitals or all hospitals

Personalized patient education materials 

Building the Quality Improvement System & Hospital Teams

• Physician Champion(s)

• Nurses

• Pharmacists

• Hospital Administrators

• Directors of Cardiac Services, Quality Improvement and Case Management

• Cardiac Rehab TeamCardiac Rehab Team

• EMS

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Reach of Get With The Guidelines®

78% of US populationwithin reach of a GWTG Hospital

42% of all US hospital use one or more of ouruse one or more of our quality programs.

Get With The Guidelines-Heart Failure Participation, Quality of Care and Clinical Outcomes

Measure GWTG‐HF Hospitals(n=355)

Non‐GWTG Hospitals(n=3909)

P‐Value

(n=355) (n=3909)

LVEF documented 92.8% 83.0% <0.0001

ACEI/ARB in LVSD 85.6% 81.4% 0.001

Discharge Instructions

67.7% 55.3% <0.001

Smoking Cessation Counseling

85.7% 81.3% 0.04

Hospital Compared data 2005-2006Heidenreich PA et al Am Heart J 2009;158:546-53

Counseling

Risk-adjusted 30-day mortality for HF was lower in Get With The Guidelines PAA hospitals compared

to non-Get With The Guidelines hospitals

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Reduction or Elimination in Race/Ethnicity Related Disparities in Care

Acute Myocardial Infarction Care Heart Failure Care

Cohen et al. Circulation . ePub May 17, 2010 Thomas K, et al.  Am Heart J 2011;161:746‐54.

Registry Data Linked to Medicare Data for Clinical and Comparative Effectiveness

Clinical Registry Data Medicare Claims Data

Wealth of data on clinical characteristics,  Minimal clinical data symptoms, comorbid conditions, vital signs, laboratories, treatments, short term outcomes 

Limited or absent longitudinal outcome data

Often no unique identifiers

Detailed data on hospitalizations, procedures outpatient visits, health care utilization, costs, and deaths (and some data on medications from Part D) 

Identified

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American Heart Association’s

The Next Logical Step:Provide a Resource to Investigators

Scientific Program to Innovate the Research Experience Alliance™

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MaRISS – Mild and Rapidly Improving Strokes Study

The ASPIRE Alliance Prototype Study

Study Overview

•Design: Prospective observational study

•Sample Size: 2650 acute ischemic stroke patients

•Patient Eligibility- Ischemic stroke < 4.5 hours

- Mild stroke NIHSS ≤ 5Mild stroke NIHSS ≤ 5

- Rapidly improving stroke

•Targeted Number of Participating Sites: 100

•Duration of Follow-up: 90 days

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AHA Technical Infrastructure for TGA (Current) and Expanded HIT Research “Connector”

Applicatio

n La

TGA

Measure Set

Measure set

Reporting(Meta Data)

ayer

Data &

 Analytic

Mission: Lifeline

Hospital

Pre‐Hospital Research

(Registry Data)

Raw Practice Data

Measure analytics

Aggregated Practice Data(Data Marts)

Aggregated Program Data

s Layer

Hospital Accreditation/Certification Current Portfolio

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Find Certified and Award-Winning Hospitals Near You!Heart.org/QualityMap

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Table 1. Peformance of 30-Day Mortality Risk Models for Acute Ischemic Stroke Without and With the NIHSSc-Statistic Generalized R 2

Predicted Event Rate by Decileof Predicted Risk, %Lowest Highest NRI, % (95% CI) IDI, % (95% CI)Risk model without NIHSS 0.772(0.769–0.776)0.174 5.94 47.13 — 12.8*Risk model with NIHSS 0.864(0.861–0.867)0.335 4.81 65.49 — 27.7*Difference 0.091(0.088–0.094)0.161(0.155–0.167)— — 93.1(91.6–94.6)15.0(14.6–15.3)P value <0.0001 <0.0001 — — <0.0001 <0.0001The NRI index compares the shifts in reclassified categories by observed outcome, resulting from the addition of NIHSS score to the model. A higher NRI indexindicates a greater improvement in risk discrimination and improved reclassification. The IDI measures how the model that included NIHSS score reclassifiedpatients compared with the model without NIHSS score. A higher IDI index indicates a greater improvement in risk discrimination and improved reclassification.p p g g p pAge, sex, past medical history of prior stroke/transient ischemic attack, and 84 condition codes are adjusted for in the modeling.CI indicates confidence interval; IDI, integrated discrimination improvement; NIHSS, National Institutes of Health Stroke Scale; and NRI, net reclassificationimprovement.*Discrimination slope defined as the difference of estimated mean probability for events and estimated mean probability for nonevents.Reprinted from Fonarow et al16 with permission of the publisher. Copyright © 2012, American Medical Association. All rights reserved

Table 2. Hospital Ranking Agreement Based on 30‐Day Mortality Risk Models Without and WithAdjustment for NIHSSRank Based on Model With NIHSSTop 20% Middle 60% Bottom 20% TotalRank based onmodel withoutNIHSSTop 20% 110 55 1 156Middle 60% 55 367 47 469Bottom 20% 1 47 109 157Total 156 469 157 782Rank Based on Model With NIHSSTop 5% Middle 90% Bottom 5% TotalRank based onmodel withoutNIHSSTop 5% 23 16 0 39Middle 90% 16 668 19 703Bottom 5% 0 19 21 40Total 39 703 40 782Rank Based on Model With NIHSSBetter Than Expected* As Expected* Worse Than Expected* TotalRank based onmodel withoutNIHSSBetter than expected* 13 9 0 22As expected* 15 713 6 734Worse than expected* 0 15 11 26Total 28 737 17 782NIHSS indicates National Institutes of Health Stroke Scale.*Hospitals with the 95% confidence intervals of the estimated random intercepts not covering the null point are considered tohave performance that is significantly better or worse than the average hospital. These categories are analogous to the portionsof hospitals identified in Hospital Compare as having better than expected, as expected, or worse than expected 30‐day riskstandardizedmortality rates.Reprinted from Fonarow et al16 with permission of the publisher. Copyright © 2012, American Medical Association. All rights reserved.

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Hospital Compare was created through the efforts of Medicare and the Hospital Quality Alliance. The Hospital Quality Alliance (HQA): Improving p Q y p Q y ( Q ) p gCare Through Information was created in December 2002.HQA was a public‐private collaboration established in December 2002 to promote reporting on hospital quality of care. HQA consisted of organizations that represented consumers, hospitals, doctors, employers, accrediting organizations, and federal agencies. The HQA effort was intended to make it easier for consumers to make informed health care decisions and to support efforts to improve quality in U.S. hospitals. Since it's inception, many new measures and topics have been displayed in the site. I 200 h fi f 10 " " f di l dIn 2005, the first set of 10 "core" process of care measures were displayed on such topics as heart attack, heart failure, pneumonia.and surgical care. 

In March 2008, data from the  Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey, also known as the CAHPS Hospital Survey, was added to Hospital Compare. HCAHPS provides a standardized instrument and data collection methodology for measuring patient's perspectives on hospitalstandardized instrument and data collection methodology for measuring patient s perspectives on hospital care.  Also in 2008, data on hospital 30‐day mortality for heart attack and heart failure was displayed.  Later in 2008, mortality rates for pneumonia was added. In 2009, CMS added data on hospital outpatient facilities, which included outpatient imaging efficiency data as well as emergency department and surgical process of care measures. 2010 saw the addition of 30‐day readmission measures for heart attack, heart failure,and pneumonia patients.This year, in 2012, we added data on the CMS readmission reduction program and measures that were voluntarily submitted by hospitals participating the American College of Surgeons  National Surgical Quality Improvement Program.  The three measures are:Lower Extremity Bypass surgical outcomesOutcomes in Surgeries for Patients 65 Years of Age or OlderColon Surgery OutcomesColon Surgery OutcomesHospital Compare continues to evolve, and in 2013 will include data on the new Hospital Value Based Purchasing program. 

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applaud CMS for its responsiveness to stakeholder concerns regarding the inadequacy of the administrative claims‐based risk‐regarding the inadequacy of the administrative claims based riskadjustment model that is now in use in the 30‐Day Mortality Following Acute Ischemic Stroke Hospitalizationmeasure. CMS listened to the serious concerns expressed by AHA/ASA and numerous other organizations regarding the potential unintended consequences related to misclassification of hospital performance using this model, which does not adjust for stroke severity. A measure of stroke severity is essential for optimal discrimination of h i l l l li i k i h i bili i khospital‐level mortality risk, given the great variability in stroke severity and outcomes for patients hospitalized with ischemic stroke

all three of the new models, each of which incorporates the National Institutes of Health Stroke Score (NIHSS) as aNational Institutes of Health Stroke Score (NIHSS) as a measure of initial stroke severity, represents a significant improvement over the claims‐based risk model that is currently in use. Although there are many different methods of measuring the severity of stroke, the NIHSS is well‐validated, highly reliable, and an extremely strong predictor of both mortality and short‐ and long‐term functional outcomes. It is recommended in national guidelines and widely used inIt is recommended in national guidelines and widely used in clinical practice. The approval last year of a new ICD‐10 code for initial NIHSS should also improve the feasibility of using it the proposed risk models

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We are very supportive of the efforts of CMS to refine the risk model by exploring the use of new data sources to create a hybrid model that incorporates the anticipated new ICD‐10 code combined with clinical data from EHRs. We also appreciate that this work is taking place well in advance of the expected implementation of the new ICD‐10 code for initial NIHSS in October 2016, rapid uptake of which we intend to facilitate by working closely with hospitals

JCAHO and CMS programs have clearly influenced how hospitals prioritize QI goals. They have improved organizational culture and staff attitudes toward QI and have resulted in hospitals’ devoting additional resources toward QI and honing feedback and accountability mechanisms. This is not surprising, given their near-mandatory nature. Evidence that changes in leadership’s focus has rapid, trickle-downchanges in leadership s focus has rapid, trickle down effects on front-line staff suggests that national programs have “raised the floor,” stimulating hospitals to actively engage in QI that had not been doing so before.

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Hospital CompareHospital Compare is a consumer‐oriented website that provides information on Hospital Compare is a consumer oriented website that provides information on how well hospitals provide recommended care to their patients. This information can help consumers make informed decisions about health care. Hospital Compare allows consumers to select multiple hospitals and directly compare performance measure information related to heart attack, heart failure, pneumonia, surgery and other conditions. These results are organized by:• Patient Survey Results• Timely and Effective Care• Readmissions, Complications, and Deaths• Use of Medical ImagingLi ki Q li P• Linking Quality to Payment

• Medicare VolumeAccess the Hospital Compare Web site at www.hospitalcompare.hhs.gov.

All three of the models offered as options should greatly enhance CMS’ ability to accurately classify hospital performance and to limit the risk of y y y p punintended adverse effects on patient care. We leave it to CMS’ discretion to select the best alternative for its programs based on a careful evaluation of each model and look forward to revalidating the models once the ICD‐10‐derived NIHSS data are available. 

The AHA/ASA is very pleased that the data collected by our GWTG‐Stroke registry was useful in developing the updated risk models and appreciates the opportunity to collaborate with CMS on this important effort.  We look pp y pforward to other opportunities to collaborate in the future.

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Process and structure measures are widely used to assess the quality of cardiovascular care, but these typically cover only a narrow aspect of care for any given patient. 

Patient outcomes can be aggregate markers of quality, integrating structural and process variables that can’t otherwise be measured, but outcomes are difficult to measure in ways that allow fair comparisons among providers. 

Risk‐adjustment can provide a means to determine whether differences in outcomes across providers can be attributed to the actions of the providers and not just to characteristics of the patient populations they care for, or chance alone

I i i l d l i k d l h ill i i f i h i i ifi lIt is essential to develop a risk model that will capture patient information that is significantly related to the outcome of interest that should be accounted for to make valid comparisons. 

Poorly performing models may cause misclassification of healthcare providers’ outcomes, and could lead to serious adverse consequences on patient care due to risk avoidance, potentially worsening disparities and unfairly penalizing providers. 

The importance of these issues has been intensified by CMS’s decision to publicly report 30‐day stroke mortality using administrative data only for risk adjustment.

A measure of stroke severity is essential for optimal discrimination of hospital‐level mortality risk, given the great variability in stroke severity and outcomes for patients with ischemic stroke. However, it is not included in CMS’ current risk adjustment model.

The NIHSS is a validated tool for assessing initial stroke severity that is widely used in practice. It has been shown to predict mortality in acute ischemic stroke in several prior studies and its use is supported by evidence‐based guidelines.

An objective, standardized assessment of stroke severity, such as the NIHSS, is essential for determining eligibility for thrombolytic therapy and facilitates communication of stroke severity among health care providers, helping to guide appropriate care and potentially improving patient outcomes.providers, helping to guide appropriate care and potentially improving patient outcomes. 

Recent study of hospitals participating in GWTG‐Stroke evaluated the impact of using NIHSS, as a measure of stroke severity, on hospital performance rankings. In this analysis, hospital transfers after admission were excluded, whereas the CMS analysis included hospital transfers but adjusted for them. In that analysis, there was a significant reclassification of hospitals when stroke severity, as measured by the NIHSS was used in the model.*

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AHA/ASA and other organizations expressed our concerns regarding the inadequacy of the administrative claims‐based risk adjustment model to CMS on numerous occasions, without success. 

To facilitate the incorporation of stroke severity in the CMS model, the AHA/ASA, with the support of a number of other societies, proposed adding a new ICD‐10 code to capture initial NIHSS.**

Dr. Aisha Liferidge defended the NIHSS proposal before the ICD‐10 Coordination and Maintenance Committee at their meeting in Sept. 2014.

The ICD‐10 Committee approved the new code and it will become effective on October 1, 2016 

CMS heard stakeholders concerns and their contractor, Yale/CORE, is now working on developing a revised risk‐adjustment model that will incorporate the NIHSS.  

Likely will be rapid uptake once an ICD‐10 code is available and the NIHSS is explicitly incorporated in the CMS risk‐standardized stroke outcome measures, allowing for more robust risk adjustment for stroke outcome measures and enhancing the accuracy of quality of care reporting. 

Fonarow GC, Pan W, Saver JL, Smith EE, Reeves MJ, Broderick JP, Kleindorfer DO, Sacco RL, Olson DM, Hernandez AF, Peterson ED, Schwamm LH. Comparison of 30‐day mortality models for profiling hospital performance in acute ischemic stroke with vs without adjustment for stroke severity. JAMA. 2012;308:257–264.

** Other groups that supported the proposal: American Academy of Neurology American Association of Neurological Surgeons and Congress of Neurological American Other groups that supported the proposal: American Academy of Neurology, American Association of Neurological Surgeons and Congress of Neurological, American College of Emergency Physicians, American Society of Neuroradiology, National Association of EMS Physicians, Centers for Disease Control and Prevention (Paul Coverdell National Acute Stroke Program, Division for Heart Disease and Stroke Prevention), National Stroke Association,  Neurocritical Care Society, The Office of the National Director of Neurology of the Department of Veterans Affairs, Society of NeuroInterventional Surgery and the Stroke Belt Consortium supported the proposal

Other Sources:Katzan IL, Spertus J, Bettger JP, Bravata DM, Reeves MJ, Smith EE, Bushnell C, Higashida RT, Hinchey JA, Holloway RG, Howard G, King RB, Krumholz HM, Lutz BJ, YehRW; on behalf of the American Heart Association Stroke Council, Council on Quality of Care and Outcomes Research, Council on Cardiovascular and Stroke Nursing, Council on Cardiovascular Radiology and Intervention, Council on Cardiovascular Surgery and Anesthesia, and Council on Clinical Cardiology. Risk adjustment of ischemic stroke outcomes for comparing hospital performance: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2014;45:918–944.

Krumholz HM, Brindis RG, Brush JE, Cohen DJ, Epstein AJ, Furie K, Howard G, Peterson ED, Rathore SS, Smith SC Jr, Spertus JA, Wang Y, Normand SL. Standards for statistical models used for public reporting of health outcomes: an American Heart Association scientific statement from the Quality of Care and Outcomes Research Interdisciplinary Writing Group. Circulation. 2006;113:456–462.

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American Heart Association ASPIRE(AHA Scientific Program for Integrating the Research Experience)

• Collaborative research network built upon American Heart Association’s suite of quality improvement registries.

• Point of contact for collaborating researchers• Point of contact for collaborating researchers.

• Contact: ASPIRE@heart.org.

Eric E. Smith 63

We KNOW how to reduce morbidity and mortality in 

cardiovasacular disease and strokecardiovasacular disease and stroke

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CORE collaborated with the American Heart Association/American Stroke Association (AHA/ASA) to complete this work. Early in the project we determined that a measure could be

Claims‐Based and Hybrid Measures of 30‐Day Mortality Following Acute Ischemic Stroke Hospitalization Incorporating Risk Adjustment for Stroke Severity Technical Report (2015)

Early in the project, we determined that a measure could be developed using NIHSS scores obtained from either Medicare administrative claims or from the electronic health record (EHR). An International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD‐10)‐based stroke severity score could be added to the claims‐based model, whereas an EHR‐based stroke severity score could be used to develop a measure that uses both claims and EHR data (hybrid measure). ( y )Because the most preferable form of the measures was unclear at the outset of development, this report describes the development of two types of 30‐day hospital‐level stroke mortality measures that contain the NIHSS: a claims‐only measure and hybrid measures, which utilize both claims and clinical EHR data. 

The cohorts and outcomes of the measures are aligned with CMS’s original, publicly reported stroke mortality measure. Both new measures were developed using a 

Claims‐Based and Hybrid Measures of 30‐Day Mortality Following Acute Ischemic Stroke Hospitalization Incorporating Risk Adjustment for Stroke Severity Technical Report (2015)

linked dataset consisting of Medicare fee‐for‐service (FFS) claims and AHA/ASA Get With The Guidelines® (GWTG)‐Stroke registry data. GWTG‐Stroke registry data were used because at the time of measure development (2015), it was the largest database that included both the NIHSS and clinical EHR variables. To build the risk adjustment model for the claims‐only measure, the 41 claims‐derived variables in the current publicly reported measure were considered as candidate variables in addition to the NIHSS. Variables that were predictive of mortality in the multivariate model were included in the final claims‐only risk model. To build the risk‐adjustment models for the hybrid measures, 14 clinical EHR 

i bl id d i ddi i h 41 l i d i d i bl d NIHSSvariables were considered in addition to the 41 claims‐derived variables and NIHSS. Similarly, variables that were predictive of mortality in the multivariate model were included in the final hybrid risk models. In an effort to streamline measure calculation and reduce dependence on claims data, the third measure is a hybrid measure that only utilizes data elements that could be extracted from an EHR for risk adjustment. 

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This report presents three risk‐adjustment models for stroke mortality: The updated claims‐only model includes 19 claims‐derived variables and the

Claims‐Based and Hybrid Measures of 30‐Day Mortality Following Acute Ischemic Stroke Hospitalization Incorporating Risk Adjustment for Stroke Severity Technical Report (2015)

The updated claims only model includes 19 claims derived variables and the NIHSS; one hybrid model includes 17 claims‐derived variables, 3 clinical EHR variables, and the NIHSS; and the other hybrid model includes 8 clinical EHR variables and the NIHSS. All of the measures have modestly higher c‐statistics and more parsimonious risk models than the current publicly reported stroke mortality measure.

d l i i diff d C S h iBy developing measures using two different data sources, CMS has options with regards to their approach to the implementation of a stroke mortality measure that includes stroke severity.