Surgeon and hospital factors Surgeon and hospital factors associated with the use of associated with the use of differentially-reimbursed differentially-reimbursed hip fracture procedureship fracture procedures

Mary L. Forte DC, Beth A.Virnig PhD, MPH, Roger Feldman PhD, Sara Durham MS, Marc Swiontkowski MD,

Mohit Bhandari MD, MSc, Robert L. Kane MD

Research supported in part by a contract from CMS to the Research Data Assistance Center under contract #500-01-0043

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BackgroundBackground

266,000266,000++ hip fractures annually in U.S. hip fractures annually in U.S.

Vast majority are treated surgicallyVast majority are treated surgically

Intertrochanteric (IT) hip fractures: ~47% Intertrochanteric (IT) hip fractures: ~47% of elderly hip fracturesof elderly hip fractures

Two devices: Two devices: – Plate with screwsPlate with screws

– Intramedullary nail (IMN) Intramedullary nail (IMN) New in U.S. ~1988; specific CPT code 1992New in U.S. ~1988; specific CPT code 1992

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The devicesThe devices

Plate with screws Intramedullary nail

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How the implants compareHow the implants compare

Outcomes similar for most IT fractures:Outcomes similar for most IT fractures:– Functional outcomes: ~same Functional outcomes: ~same – Mortality: ~sameMortality: ~same– Complications: IMN higherComplications: IMN higher– Stay-related:Stay-related:

Length of stay: ~same Length of stay: ~same OR time: ~sameOR time: ~sameBlood use: IMN less (smaller incision)Blood use: IMN less (smaller incision)

IMN better for IMN better for unstableunstable fxs (3-29%) fxs (3-29%)No outcomes evidence to support the need for No outcomes evidence to support the need for IMN for IMN for stablestable IT fractures IT fractures

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BackgroundBackgroundSurgeons: paid by RVUsSurgeons: paid by RVUs– Two CPT codes differentiate the procedures Two CPT codes differentiate the procedures

(27244, 27245)(27244, 27245)– Surgeons paid $270 more by Medicare to use Surgeons paid $270 more by Medicare to use

IMN than plate/screws (range $233-328)IMN than plate/screws (range $233-328)

Hospitals: DRGsHospitals: DRGs– Both devices in the same two DRGs: 210, 211 Both devices in the same two DRGs: 210, 211 – Not reimbursed for device costs Not reimbursed for device costs

IMN costs hospital ~$1000 more per implant IMN costs hospital ~$1000 more per implant than plate/screwsthan plate/screws

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Study aimStudy aim

Identify the surgeon and hospital factors Identify the surgeon and hospital factors that were associated with IMN use that were associated with IMN use among Medicare intertrochanteric hip among Medicare intertrochanteric hip fracture patients treated with internal fracture patients treated with internal fixation 2000-02 fixation 2000-02

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IMN variation by State was not explained IMN variation by State was not explained by patient factors in 2002by patient factors in 2002

Forte et al JBJS 2008;90:691-9

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MethodsMethods

Patients: Patients: MedPAR, Carrier, Denominator files 2000-02MedPAR, Carrier, Denominator files 2000-02– Age 65+, Parts A & B enrolled, non-HMOAge 65+, Parts A & B enrolled, non-HMO– Inpatient surgery with internal fixation for IT hip Inpatient surgery with internal fixation for IT hip

fracture (MedPAR)fracture (MedPAR)– Exclude high-energy trauma, cancer-related, Exclude high-energy trauma, cancer-related,

revisions, infection, bilateral fxsrevisions, infection, bilateral fxs– Surgeon claim for specific device (Carrier)Surgeon claim for specific device (Carrier)

Kept first surgery per patient: 3/1/00-12/31/02Kept first surgery per patient: 3/1/00-12/31/02

Surgeons: Surgeons: MPIER fileMPIER file

Hospitals: Hospitals: Provider of Services (POS) fileProvider of Services (POS) file

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MethodsMethods

AnalysisAnalysis– Binary outcome: IMN or plate/screwsBinary outcome: IMN or plate/screws– Surgeon and hospital characteristics used Surgeon and hospital characteristics used

as predictors, adjusted for patient factorsas predictors, adjusted for patient factors– Nonlinear mixed models: Nonlinear mixed models: SAS SAS Proc NLMIXEDProc NLMIXED

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MethodsMethods

Predictors:Predictors:– Surgeons: Surgeons:

age, degree, Orthopaedic Board certification, Medicare age, degree, Orthopaedic Board certification, Medicare IT fx case volume (quartile), # of case hospitalsIT fx case volume (quartile), # of case hospitals

– Hospitals: Hospitals: Medicare IT fx case volume (quartile), ownership, Medicare IT fx case volume (quartile), ownership, teaching status teaching status (3 options)(3 options)

– Patient covariates: Patient covariates: age, sex, race, nursing home-Medicaid assistance age, sex, race, nursing home-Medicaid assistance statusstatus

• Excluded: Charlson (screened in nlmixed: not sig.)Excluded: Charlson (screened in nlmixed: not sig.)

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Patient samplePatient sample

192,365 cases 3/1/00 – 12/31/02192,365 cases 3/1/00 – 12/31/02Mean age 84 years Mean age 84 years

77% female77% female

94% white94% white

11% subtrochanteric (unstable) fractures11% subtrochanteric (unstable) fractures

20.1% admitted from a nursing home 20.1% admitted from a nursing home

IMN: 8% in 2000; 17.1% 2002IMN: 8% in 2000; 17.1% 2002

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SurgeonsSurgeons

15,091 surgeons 15,091 surgeons

Median age: 46 yrs Median age: 46 yrs

Median volume: 10 cases (7.8%=1 case) Median volume: 10 cases (7.8%=1 case)

95% MDs, 5% DOs 95% MDs, 5% DOs

65% Orthopaedic Board-certified65% Orthopaedic Board-certified

64% group practice64% group practice

56% operated at one hospital 56% operated at one hospital

14% operated at 3 or more hospitals14% operated at 3 or more hospitals

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HospitalsHospitals

3,480 U.S. hospitals 3,480 U.S. hospitals – Median IT fx volume: 41 cases Median IT fx volume: 41 cases (2.3%=1 case)(2.3%=1 case)

– Teaching status:Teaching status:

30.3% teaching hospitals30.3% teaching hospitals

4.3% teaching hospitals with resident case(s)4.3% teaching hospitals with resident case(s)

– Type of ownership:Type of ownership:

15.0% For-profit15.0% For-profit

18.5% Government18.5% Government

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Results: Model selectionResults: Model selection

3 models considered: 3 models considered: – No random effects, hospital random effects, surgeon random effectsNo random effects, hospital random effects, surgeon random effects

No random effects model:No random effects model: – Significantly worse fit by likelihood ratio test Significantly worse fit by likelihood ratio test (p<0.0001 for both)(p<0.0001 for both)

Surgeon random effects models fit better than Surgeon random effects models fit better than hospital random effects models by AIC, BIChospital random effects models by AIC, BIC

Patient and surgeon characteristics contributed Patient and surgeon characteristics contributed substantially to model fit; hospital characteristics substantially to model fit; hospital characteristics less soless so

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PredictorPredictor ( (ref. group*ref. group*))

Random surgeon Random surgeon intercepts modelintercepts model

Odds ratio (OR)Odds ratio (OR)Confidence intervalConfidence interval

for the ORfor the OR

Surgeon ageSurgeon age

<35 yrs<35 yrs 5.135.13 3.87 – 6.81 3.87 – 6.81

35-39 yrs35-39 yrs 2.582.58 2.05 – 3.24 2.05 – 3.24

40-44 yrs40-44 yrs 1.401.40 1.17 – 1.75 1.17 – 1.75

45-49 yrs*45-49 yrs* 1.001.00 --

50-54 yrs50-54 yrs 0.790.79 0.62 - 0.99 0.62 - 0.99

55-59 yrs55-59 yrs 0.610.61 0.47 – 0.79 0.47 – 0.79

60-64 yrs60-64 yrs 0.700.70 0.52 – 0.94 0.52 – 0.94

65+ yrs65+ yrs 0.640.64 0.42 – 0.96 0.42 – 0.96

p<0.0001; p<0.05

Results: Surgeon factorsResults: Surgeon factors

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Predictor (Predictor (ref. group*ref. group*))

Random surgeon Random surgeon intercepts modelintercepts model

Odds ratio (OR)Odds ratio (OR)Confidence intervalConfidence interval

for the ORfor the OR

Professional degreeProfessional degree

Dr. of Osteopathy (DO)Dr. of Osteopathy (DO) 2.062.06 1.51 – 2.811.51 – 2.81

Medical doctor (MD)*Medical doctor (MD)* 1.001.00 --

Ortho. Board CertificationOrtho. Board Certification

Not Ortho. Board certifiedNot Ortho. Board certified 1.131.13 0.97 – 1.310.97 – 1.31

Ortho. Board certifiedOrtho. Board certified** 1.001.00 --

Practice structurePractice structure

GroupGroup** 1.001.00 --

Other Other 0.990.99 0.87 – 1.140.87 – 1.14

p<0.0001; p<0.05

Results: Surgeon factorsResults: Surgeon factors

1717p<0.0001; p<0.05

PredictorPredictor ( (ref. group*ref. group* ) )

Random surgeon Random surgeon intercepts modelintercepts modelOdds ratio (OR)Odds ratio (OR)

Confidence intervalConfidence intervalfor the ORfor the OR

Number of IT fracturesNumber of IT fractures

1-41-4 1.231.23 0.99 – 1.520.99 – 1.52

5-105-10 0.880.88 0.74 – 1.060.74 – 1.06

11-1711-17 0.850.85 0.71 – 1.030.71 – 1.03

18 + 18 + ** 1.001.00 --

Case hospitalsCase hospitals

oneone** 1.001.00 --

twotwo 1.211.21 1.03 – 1.411.03 – 1.41

threethree 1.471.47 1.17 – 1.841.17 – 1.84

four or morefour or more 2.442.44 1.76 – 3.381.76 – 3.38

Results: Surgeon factorsResults: Surgeon factors

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PredictorPredictor ( (ref. groupref. group** ))

Random surgeon Random surgeon intercepts modelintercepts model

Odds ratio (OR)Odds ratio (OR)Confidence intervalConfidence interval

for the ORfor the OR

Number of IT fracturesNumber of IT fractures

1-171-17 0.830.83 0.70 – 0.980.70 – 0.98

18-4118-41 0.840.84 0.75 – 0.940.75 – 0.94

42-7842-78 0.940.94 1.02 – 1.031.02 – 1.03

79+79+** 1.001.00 --

Type of ownershipType of ownership

Non-profitNon-profit** 1.001.00 --

For profitFor profit 1.101.10 0.99 – 1.230.99 – 1.23

GovernmentGovernment 1.051.05 0.93 – 1.190.93 – 1.19

Results: Hospital factors

p<0.0001; p<0.05

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PredictorPredictor ( (ref. group*ref. group*))

Random surgeon Random surgeon intercepts modelintercepts model

Odds ratio (OR)Odds ratio (OR)Confidence intervalConfidence interval

for the ORfor the OR

Teaching statusTeaching status

Non-teachingNon-teaching** 1.001.00 --

TeachingTeaching 1.121.12 1.03 – 1.221.03 – 1.22

Teaching-resident on caseTeaching-resident on case 1.581.58 1.26 – 2.001.26 – 2.00

YearYear

20002000** 1.001.00 --

20012001 1.771.77 1.67 – 1.881.67 – 1.88

20022002 4.684.68 4.40 – 4.974.40 – 4.97

Results: Hospital factors, year

p<0.0001; p<0.05

2020

Overall findingsOverall findings

Best model fit: Best model fit: patient, surgeon and patient, surgeon and hospital predictors with surgeon random hospital predictors with surgeon random interceptsintercepts;; the addition of hospital the addition of hospital predictors only minimally improved model fit predictors only minimally improved model fit after inclusion of surgeon random effects after inclusion of surgeon random effects

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ConclusionsConclusions

1.1. Surgeon effects are stronger than hospital effects Surgeon effects are stronger than hospital effects in the use of IMN for Medicare IT hip fracture in the use of IMN for Medicare IT hip fracture patients patients

2.2. Surgeon factors, resident case involvement and Surgeon factors, resident case involvement and teaching hospital status were strong predictors of teaching hospital status were strong predictors of IMN useIMN use

3.3. Surgeons under age 45, those operating at more Surgeons under age 45, those operating at more than one hospital and DOs were significantly than one hospital and DOs were significantly more likely to use IMN more likely to use IMN

4.4. The effects of higher IMN use on patient The effects of higher IMN use on patient outcomes warrants further investigationoutcomes warrants further investigation

LimitationsLimitations

NLMIXED: one random effectNLMIXED: one random effect

Orthopaedic Board certification status, Orthopaedic Board certification status, group practice: under-identifiedgroup practice: under-identified

Hospital IT fx volume: IT fx-specific; may Hospital IT fx volume: IT fx-specific; may not parallel overall hospital case volumenot parallel overall hospital case volume

Claims dataClaims data

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Policy implicationsPolicy implications1.1. Higher Medicare reimbursement to surgeons for IMN Higher Medicare reimbursement to surgeons for IMN

may contribute to higher IMN use when a less-may contribute to higher IMN use when a less-expensive procedure would give similar outcomes in expensive procedure would give similar outcomes in the majority of casesthe majority of cases

2.2. IMN use can be expected to increase as long as the IMN use can be expected to increase as long as the RVU payment incentive remains and IMN RVU payment incentive remains and IMN procedures are not harder to performprocedures are not harder to perform

3.3. No objective evidence exists that IMN procedures No objective evidence exists that IMN procedures require more surgeon work require more surgeon work

4.4. The process of assigning RVUs to procedures using The process of assigning RVUs to procedures using physician/surgeon surveys may be contributing to physician/surgeon surveys may be contributing to the propagation of RVU-related financial incentivesthe propagation of RVU-related financial incentives

Acknowledgement:Acknowledgement:

Lynn Eberly, PhDLynn Eberly, PhDDept. of Biostatistics Dept. of Biostatistics

University of MinnesotaUniversity of Minnesota