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TJRCopyright 2015 FORCE-‐TJR. All rights reserved. Do not copy or distribute without permission.

FORCE-‐TJR Func


Today’s Goals

1.  FORCE-‐TJR: Overview of Design, Data and Impact to date(2010-‐2015).

2. FORCE and the FDA CRN (U01) IdenPfy poorly performing implants before revision using paPent-‐reports? –  Implant surveillance and PROs –  Industry pre-‐ and post-‐market surveillance


FORCE-‐TJR: comprehensive outcomes

$12 million AHRQ P50 award Department of Orthopedics and Physical RehabilitaPon University of MassachuseZs Medical School (2010-‐15)

1.  Develop a naPonal, representaPve TJR cohort with sustainable data infrastructure for comprehensive TJR outcome monitoring and feedback to providers. – UMass is the TJR data coordinaPng center for the next 20+ years

2.  UMass TJR research team conducPng comparaPve effecPveness research in TJR quality and outcomes.


Primary Outcomes: PaPent-‐reported pain and funcPon

“When he [the surgeon] saw the PRO survey, he saw how my func;on was, how bad it was….” Pa;ent, age 72, TKR, PA

VIEWPOINT

Beyond Joint Implant RegistriesA Patient-Centered Research Consortiumfor Comparative Effectiveness in Total Joint ReplacementPatricia D. Franklin, MD, MPH, MBAJeroan J. Allison, MD, MSDavid C. Ayers, MD

DESPITE THE PROVEN EFFECTIVENESS OF TOTALjoint replacement (TJR) surgery in relievingadvanced knee and hip arthritis pain, TJR out-comes have come under intense public scrutinyin recent years. The 2010 recall of ASR metal-on-metal hipimplants1 heightened awareness of the importance forimplant safety surveillance for this high-cost and high-useprocedure and exposed the need for a national systematicpatient-centered outcomes monitoring system. Thesesafety concerns and the exponential growth in TJR use—given the demographics of the baby boomer generation—emphasize the need for systematic comparative effective-ness research (CER) to inform patients, physicians,and policy makers about the optimal practices in TJRsurgery.

Recent estimates suggest that up to 500 000 US patientsreceived a metal-on-metal hip implant between 2003 and2010.2 Prior to the recall, case reports from across theglobe documented unusually high rates of early postopera-tive revision surgery among patients with these implants.National registries of England and Wales, Australia, andNew Zealand reported greater revision surgery rates withmetal-on-metal implants3 compared with conventionalmetal-on-polyethylene implants. In hindsight, the first signof implant failure was atypical patient-reported pain, fol-lowed by pathologic soft tissue changes. However, at thetime, registries were not systematically documenting longi-tudinal patient-reported symptoms (eg, pain and physicalfunction) after knee and hip surgery. The existence of suchsystematic patient-reported data may have brought atten-tion to these implants earlier. There is a current need, inthe United States in particular, for an efficient monitoringinfrastructure of population-based, longitudinal, patient-reported outcomes to provide evidence to inform patientand clinician decisions about optimal TJR timing, implantselection, surgical technique, and likely functionaloutcomes.

To address this need, the Agency for Healthcare Re-search and Quality funded a 4-year $12 million research pro-gram, Function and Outcomes Research for ComparativeEffectiveness in TJR (FORCE-TJR).4 Led by a team of re-searchers at the University of Massachusetts Medical Schoolin cooperation with a national network of surgeons,FORCE-TJR assembled a consortium of orthopedic prac-tices to serve as a research laboratory to generate CER toguide surgeon and patient decisions. The FORCE-TJR hasa national scope, is representative of US practices, includeslongitudinal patient-reported outcomes, and has the abil-ity to measure implant failure as well as important clinicaloutcomes and complications.

The FORCE-TJR ApproachThe FORCE-TJR model goes beyond the traditional im-plant failure or revision registry and integrates the prin-ciples of population-based prospective research based on pa-tient-centric outcomes. The FORCE-TJR is planning to enrollmore than 30 000 diverse patients receiving care from morethan 100 orthopedic surgeons representing all regions of thecountry and varied hospital and practice settings to ensurethat data reflect typical US practice. Specifically, the studywill include the following:

Diverse Orthopedic Practice Settings. Typically, TJR out-comes research is conducted in high-volume practices, of-ten in academic medical centers. However, the majority ofTJR surgeries in the United States are performed by generalorthopedic surgeons in community practices. By design, 67%of the 101 surgeons who have joined the FORCE-TJR con-sortium to date practice in community settings in 27 states.In aggregate, consortium surgeons perform more than 14 000TJR procedures each year using devices made by each of the5 leading device manufacturers.5 With more surgeons join-ing the study each month, FORCE-TJR is expected to ex-ceed target patient enrollment. Varied practice size, financ-ing (eg, private, health maintenance organization, Medicare),and geographic settings will ensure that this consortium in-cludes diverse patient populations, practice settings, andhealth care delivery and financing models.

See also pp 1227 and 1266.

Author Affiliations: Department of Orthopedics and Physical Rehabilitation (DrsFranklin and Ayers), Department of Quantitative Health Sciences (Dr Allison), Uni-versity of Massachusetts Medical School, Worcester.Corresponding Author: Patricia Franklin, MD, MPH, MBA, Department of Ortho-pedics and Physical Rehabilitation, University of Massachusetts Medical School,55 Lake Ave N, Worcester, MA 01655 ([email protected]).

©2012 American Medical Association. All rights reserved. JAMA, September 26, 2012—Vol 308, No. 12 1217

Joint Registry UpdateJoint Replacement Registries in the United States:

A New ParadigmDavid C. Ayers, MD, and Patricia D. Franklin, MD, MBA, MPH

This commentary serves as an introduction to an upcomingseries of articles about orthopaedic registries, in general, withan emphasis on lessons learned from the evolving U.S. andinternational total joint replacement registries. This paper pro-vides an overview of total joint replacement registries and thecurrent expansion of data collection beyond implant attributesand survival to include postoperative complications andpatient-reported outcomes.

Osteoarthritis is the most common cause of physical dis-ability in the U.S.1. The combination of osteoarthritis prevalenceand the success of total joint replacement in relieving pain andimproving function in patients with advanced osteoarthritis hasresulted in total joint replacement becoming the most commonand costly inpatient procedure among Medicare beneficiaries.Moreover, the fastest growing subgroup of patients undergoingtotal joint replacement consists of those less than sixty-five yearsof age2. More than one million total joint replacements are per-formed annually in the U.S., making measurement of total jointreplacement outcomes a public health priority. To measure andmonitor the outcomes of total joint replacement, state and na-tional total joint replacement registries are emerging that incor-porate lessons learned from long-standing international implantregistries as well as integrate new methods to quantify perioper-ative quality and patient-reported outcomes.

International total joint replacement registries have tra-ditionally focused on implant revision rates and tracked thelength of time between the initial total joint replacement andimplant removal. In this model, national registries incorporatelarge numbers of arthroplasties to identify relatively low annualfailure rates and the focus is on device longevity. However,today’s total joint replacement registries are broadening their fo-cus to include perioperative complications and patient-reported

outcomes following surgery. While the implant revision rate re-mains an important outcome, implant materials and technologyhave matured and patients and insurers want to understand thequality of care of the vast majority of patients who do not have arevision each year. Our health-care system is transforming from avolume-based system to a value-based system. Value is defined asoutcome divided by cost. Measurement of patient outcomes aftertotal joint replacement is increasingly emphasized.

The 2010 recall of metal-on-metal hip implants broughttotal joint replacement into the public eye and reinforced theimportance of recording symptoms such as pain and physicallimitations over time to assess the success of the surgery3. Earlysubstantial pain in the operatively treated joint was the first signof metal-on-metal problems. For decades, joint registries onlyreported implant data and revision rates, so any implant thatremained in the patient was considered a “success.” However,as was clear with themetal-on-metal situation, patients who havenot undergone revision may experience symptoms or complica-tions that must be quantified. In 2013, the Centers for Medicare& Medicaid Services (CMS) began publicly reporting thirty-dayhospital readmission rates following total joint replacements. Inearly 2014, the CMS added ninety-day all-cause complications tothe hospital reports on total joint replacements. Finally, the CMSconvened a technical expert panel to evaluate the role of patient-reported outcomes inmonitoring outcomes of total joint replace-ment in the U.S. Medicare population4.

To meet emerging clinical and policy needs, U.S. total jointreplacement registries must expand beyond implant tracking toinclude postoperative complications and patient-reported painand function. This same evolution can be observed internation-ally as the capture and reporting of patient-reported outcomesfollowing total joint replacement has expanded greatly over the

Disclosure:One ormore of the authors received payments or services, either directly or indirectly (i.e., via his or her institution), froma third party in support of anaspect of this work. None of the authors, or their institution(s), have had any financial relationship, in the thirty-six months prior to submission of this work, withany entity in the biomedical arena that could be perceived to influence or have the potential to influencewhat is written in this work. In addition, no author has hadany other relationships, or has engaged in any other activities, that could be perceived to influence or have the potential to influence what is written in this work.The complete Disclosures of Potential Conflicts of Interest submitted by authors are always provided with the online version of the article.

1567

COPYRIGHT ! 2014 BY THE JOURNAL OF BONE AND JOINT SURGERY, INCORPORATED

J Bone Joint Surg Am. 2014;96:1567-9 d http://dx.doi.org/10.2106/JBJS.N.00641


FORCE-‐TJR Research Cohort •  US representaPve cohort of >25,000 TJR paPents with

naPonal outcome norms for paPents of ALL ages. –  Readmissions (peri-‐op complicaPons) –  PROs –  Implant survivorship

•  New risk-‐adjustment methods for comparison of PROs and readmissions across surgeons and hospitals.

•  ComparaPve effecPveness research –  Over 30 publicaPons; dozens more in queue –  >100 presentaPons at naPonal and internaPonal meePngs –  New funding; long-‐term follow-‐up ongoing.


FORCE-‐TJR Cohort: 25,000 paPents; >200 Surgeons in 28 States

•  75% of surgeons are community -‐based

•  Fellowship-‐trained, general orthopedic surgeons

•  High and low volume surgeons/hospitals; urban and rural hospitals

•  Teaching hospitals, non-‐teaching hospitals

•  PaPents with private, public and HMO insurance

•  All major implant manufacturers

Core Clinical CentersUMass Medical School, Worcester, MA

Connecticut Joint Replacement Institute, Hartford, CT

The University of Rochester Medical Center, Rochester, NY

Medical University of South Carolina, Charleston SC

Baylor College of Medicine, Houston, TX

Community Sites currently enrolled

Map of Participating Core Centers and Community Sites

ID

MT NDMN MI

MISD

NE

KS

TX LAAL GA

SCNC

VA

PA

NY

VT NH ME

MARICT

NJDE

MDDC

WV

FL

MS

OK

IA

MO

ILIN

OH

KY

TN

WI

AR

NV UT

AZ NM

CO

WY

CA

OR

WA

Community Sites


FORCE-‐TJR FoundaPon 1. Web-‐based IT to interface with paPents and clinicians; diverse sekngs with varied EMRs..

2. OperaPonal procedures to track paPent over Pme •  Surgeon office – Hospital -‐-‐ Home over Pme •  Direct to paPent at home; >80% PRO capture

3. Generated risk-‐adjusted, naPonal TJR outcome benchmarks for both CMS paPents and


Before Surgery Surgery 30 -‐90 days

9 -‐12 months Annual?

PATIENT Hospital PATIENT (validate EHR)

•  PRO VR12/PROMIS10 HOOS/KOOS

•  CLINICAL Medical & MSK risks Demographic

•  OR Implant Lot/Catalog OperaPve Note

•  PRO Pain

•  CLINICAL ComplicaPon?

•  PRO VR12/PROMIS10 HOOS/KOOS

•  CLINICAL ComplicaPon? Revision?

•  PRO VR12 HOOS/KOOS

•  CLINICAL ComplicaPon? Revision?

FORCE-‐TJR: Longitudinal Data CollecPon Parallels CMS bundled payment pilot (CJR)

Matched CMS Data (2010-‐2014 and future)


Collect complete post-‐op events; not limited to the surgical hospital

Post-TJR Events

Surgeons All Payer;

CMS claims Participants*

•  25% of all 30-‐day readmissions go to non-‐surgical hospital.

(Range: 9%-‐40%)

•  FORCE-‐TJR combines claims, clinical data, and paPent-‐report.

•  PaPents over 65 years – matched to CMS data

(2010-‐2014; future)


ReporPng: Individual PaPents

1.  Real-‐Pme pre-‐op paPent risk profiles to tailor care and improve outcomes. 1.  Inform shared decisions

for surgery 2.  Tailor peri-‐operaPve

and post-‐discharge care 3.  Monitor in-‐home and

rehabilitaPon care.

FORCE-TJR OA REPORTID: 42012Patient Name: John DoePatient DOB: 1962-09-26Survey Date: 2015-09-08

TREND REPORT

Trended PCS Scores Trended MCS Scores Trended ADL Scores

Trended RH Pain Scores Trended RK Pain Scores Trended LK Pain Scores Trended LH Pain Scores

LATEST MEASURES

BMI: 21.30Smoking: CurrentLBP: MildDiabetes: YesCharlson Comorbidity Index: =2-5 [=0, =1, =2-5, > =6]

POST-OP EVENTS

Survey Date:

ER:OR:Hospital:

Powered by DatStat

2014/7 2014/10 2015/5 2015/90

15

30

45

60

40.534.3

48.8 51.3

2014/7 2014/10 2015/5 2015/90

15

30

45

60

44.640.5 54.6 53.4

2014/7 2014/10 2015/5 2015/90

25

50

75

100

69.257.9

88.2 92.5

2014/7 2014/10 2015/5 2015/90

25

50

75

100

75 100 100 100

2014/7 2014/10 2015/5 2015/90

25

50

75

100

3725

75 100

2014/7 2014/10 2015/5 2015/90

25

50

75

100

75 75 100 100

2014/7 2014/10 2015/5 2015/90

25

50

75

100

100 100 100 100


30 -‐90 day ER, readmit report (PaPents from this site were seen in 6 hospitals)

Your Site's TKR Patients 2013 N=142

FORCE-‐TJR (Primary TKR) Pa


Refined risk adjustment models for readmission and PROs ater TJR

•  Medical comorbidiPes •  BMI, smoking •  Pre-‐op FuncPon •  MSK comorbidi


For Surgeons: comparaPve data FORCE-‐TJR secure MD Website: quarterly outcome reports (1) My paPent risk profiles

compared to others? (2) My paPent pain and

funcPonal limitaPons pre-‐op?

(3)  Outcomes (pain relief and improved funcPon) comparable to the naPonal norm?


Ease of PRO administraPon; APP (AHRQ; with WPI)


Implant Failure and Revision

1.  Metal on metal demonstrated early pain/disability can be risk factor for implant failure.

2.  New Zealand registry reported 7 Pmes greater risk of revision within 5 years when significant pain at 6 and 12 months ater TJR.

FORCE-‐TJR reporPng both early pain and poor funcPon (implant performance) and revision.

–  ICOR library: Implant manufacturer, design, material, and component details are analyzed for both revision and poor performance in early years.

©FORCE-‐TJR


FDA U01 Award; network of TJR registries

•  Understand PRO/ pain as an indicator for poorly performing implants at risk for revision.

•  SupporPng post-‐market surveillance


FORCE/FDA Aim 1

•  Verify concordance between pa;ent-‐reported post-‐TJR adverse events, including implant revision and complica;ons, collected via web surveys, smartphone App, or CMS/ insurer claims data. –  Year 1: Web reported vs CMS comparisons in progress. –  2010-‐2013 CMS data; 2014 data pending – App final user interface tes;ng –  Year 2-‐4: App, Web, and CMS event rates


FORCE/FDA Aim 2 •  Detect prevalence of sub-‐op;mal implant performance as measured by persistent pain at six and 12 months post TJR by implant material (e.g., ceramic vs. metal hip) or design (e.g., mobile vs. sta;c knee).

•  Primary endpoints: Prevalence of moderate or severe surgical knee/hip pain by implant material or design.

•  AnalyPc Plan. Ater adjusPng for the paPent factors (e.g., age, sex, smoking), medical comorbidiPes (e.g., Charlson Comorbidity index, BMI), and musculoskeletal severity (e.g., pre-‐op joint pain, low back pain), known to be associated with post-‐operaPve pain and funcPon, mulPvariable models, clustered by surgeon, will test the associaPon of implant material/ design with six or 12-‐month pain and funcPon.


FORCE/Aim 3 •  Evaluate if severity of post-‐TJR pain at six months post-‐TJR

will predict risk of revision at 2 years aaer adjus;ng for BMI and medical and musculoskeletal comorbidi;es.

•  Using current FORCE cohort, >10,000 primary TKR and 8000 THR

procedures will be included. •  Primary endpoint: PredicPon model assessing the associaPon

between pain level ater TJR and revision (yes/no) by 2 years. •  AnalyPc Plan: Ater adjusPng for the paPent factors, medical and

musculoskeletal comorbidiPes, known to be associated with revision surgery, mulPvariable models, clustered by surgeon, will test the associaPon of 6-‐month pain score with revision (yes/no) at 2 years.


FORCE-‐TJR: Implant A vs All other

0

.01

.02

.03

.04

Den

sity

0 10 20 30 40 50 60 70 80pre_sf36_mcs

Oxinium FORCE

Oxinium vs. FORCEDistribution of Baseline SF36-MCS(TKR)

Pre-‐TKR Age Mean 64 vs 67 years P< 0.001

Pre-‐TKR MCS No difference mean

0

.02

.04

.06

Den

sity

30 40 50 60 70 80 90 100age

Oxinium FORCE

Oxinium vs. FORCEDistribution of Age(TKR)

Implant A (blue) vs All

Implant A (blue) vs All


Implant A vs FORCE; more obese

0

.02

.04

.06

.08

Den

sity

15 25 35 45 55bmi

Oxinium FORCE

Oxinium vs. FORCEDistribution of BMI(TKR)

0

.005

.01

.015

.02

.025

Den

sity

0 10 20 30 40 50 60 70 80 90 100pre_koos_pain_score

Oxinium FORCE

Oxinium vs. FORCEDistribution of Baseline KOOS Pain score(TKR)

Pre-‐TKR BMI Mean=31.5 vs 32.6 P


Post-‐TKR: KOOS pain, ADL

0

.01

.02

.03

.04

Den

sity

0 10 20 30 40 50 60 70 80 90 100post_koos_pain_score

Oxinium FORCE

Oxinium vs. FORCEDistribution of Post-op KOOS Pain score(TKR)

0

.01

.02

.03

.04

Den

sity

0 10 20 30 40 50 60 70 80 90 100post_koos_adl_score

Oxinium FORCE

Oxinium vs. FORCEDistribution of Post-op KOOS ADL score(TKR)

Post-‐TKR KOOS Pain Mean= 79 vs 82 P


Specific Implant Surveillance

•  Industry-‐ sponsored cohorts/samples •  Outcomes: post-‐op events (e.g., dislocaPon), PROs, revision of specific implants

•  1-‐5 year follow-‐up

•  Difference in paPent and/or clinical sub-‐groups? All users?


TJR

Contact us: Patricia Franklin [email protected] 508-‐856-‐5748 www.force-‐tjr.org 1-‐855-‐99FORCE (toll free) force-‐[email protected]

force9tjr - mdepinet site · 2020. 7. 27. · force-tjr assembled a consortium of orthopedic prac-...

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