back pain outcomes using longitudinal data (bold ... slides...mr stadnik/ 1998 17-60 61-71 52% 80%...
TRANSCRIPT
Back pain Outcomes using Longitudinal Data (BOLD):
Lessons for LIRE (and Other Pragmatic Trials)
Jeffrey (Jerry) Jarvik, M.D., M.P.H.Professor of Radiology and Neurological Surgery
Adjunct Professor Health Services and Pharmacy
Director, Comparative Effectiveness, Cost and
Outcomes Research Center (CECORC)
University of Washington
Disclosures• Physiosonix (ultrasound company)
– Founder/stockholder• Healthhelp (utilization review)
– Consultant• Evidence-based Neuroradiology (Springer)
– Co-Editor
• AHRQ: R01 HS019222-01
•NIH 1UH2AT007766-01
Acknowledgements-BOLD
Key PeopleUW
• Jerry Jarvik, MD,MPH- PI• Katie James, PA-C, MPH-Proj
Dir• Bryan Comstock, MS- Biostats• Nick Anderson, PhD-
Biomedical Informatics• Brian Bresnahan, PhD- Health
Economist• Patrick Heagerty, PhD- Biostat• Judy Turner, PhD-
Psychologist/Pain expert
Non-UW• Rick Deyo, MD, MPH-OHSU• Dan Cherkin, PhD-GHRI• Heidi Berthoud MPH- GHRI• Safwan Halabi, MD-HFHS• Dave Nerenz, PhD- HFHS• Dave Kallmes, MD- Mayo• Jyoti Pathak, PhD- Mayo• Patrick Luetmer, MD- Mayo• Andy Avins, MD MPH-KPNC
Inappropriate Imaging• 30-40% of imaging studies in the
U.S. may be inappropriatePicano E. Sustainability of medial imaging. BMJ. 2004;328:578-580
Background and Rationale• Lumbar spine imaging frequently
reveals incidental findings• These findings may have an
adverse effect on:–Subsequent healthcare utilization–Patient health related quality of life
Prevalence of Disc Degeneration in Normals
Modality Author/ Year
Age Range
Prev
MR Boden/ 1990
20-60 60-80
44% 93%
MR Stadnik/ 1998
17-60 61-71
52% 80%
MR Weishaupt/ 1998
20-50 72-100%
MR Jarvik/ 2001
35-70 91%
Disc Degeneration
Back pain Outcomes using Longitudinal Data (BOLD)
• CER for seniors with back pain• AHRQ funded- part of $1.1 billion
American Recovery and Reinvestment Act (ARRA)
BOLD CHOICE (Clinical and Health Outcomes Initiative in CE)
• Overall goal: establish registry to evaluate effectiveness, safety, and cost-effectiveness of interventions for pts > 65 with back pain
• Setting: HMO Research Network• Sites
– Kaiser Northern CA: Andy Avins– Henry Ford Health System Detroit: Dave Nerenz– Harvard Pilgrim/Vanguard Boston: Srdj Nedeljkovic
BOLD CHOICE: 3 Aims1. Establish BOLD registry2. Conduct observational cohort
study of early imaging3. Conduct RCT of epidural steroid
injections plus local anesthetic (LA) vs. LA alone
BOLD Aim 1: Registry Measures• 1) Roland-Morris Questionnaire• 2) 0-10 pain NRS-avg pain past 7d• 3) pain interference with activity (BPI)• 4) patient expectation re recovery• 5) PHQ-4 Depression/Anxiety• 6) EQ-5D• 7) Brief fall screen
BOLD Aim 2: Early Imaging Cohort• Observational cohort • Compare early to no early imaging in
elderly with new visit for LBP • Outcomes: Disability (RMDQ), pain,
subsequent resource utilization• Propensity score matching to control for
variables that affect receiving imaging
BOLD Aim 2: Early Imaging Cohort• Observational cohort • Compare early to no early imaging in
elderly with new visit for LBP • Outcomes: Disability (RMDQ), pain,
subsequent resource utilization• Propensity score matching to control for
variables that affect receiving imaging
Lumbar Imaging with Reporting of Epidemiology (LIRE) Proposed Study Flow
Primary Care Clinics With LBP Patients
Randomize Clinics
Macro with prevalence info
Outcomes Assessment-
Resource Utilization
No macro with prevalence info
Outcomes Assessment-
Resource Utilization
LIRE Primary Aim• To determine whether inserting age-
specific prevalence of imaging findings among asymptomatic subjects into lumbar spine imaging reports decreases back-related interventions (imaging, injections, surgeries, etc.) over the subsequent year
GHC Test Template
Intervention Text
Stepped Wedge Design
Stepped Wedge Design
• A one-way cluster, randomized crossover design
• Temporally spaces the intervention • Assures that each participating clinic
eventually receives the intervention• Within site comparison controls for
between site differences (eg- CPT coding)
LIRE Sites• Kaiser Permanente
Northern California
– Andy Avins, MD MPH
• Henry Ford Health System– Safwan Halabi, MD
• Group Health Research Institute/GHC– Dan Cherkin, PhD
• Mayo Clinic Health System– Dave Kallmes, MD
Site CharacteristicsSite #
Primary Care
Clinics
# PCPs # Patients # Back Pain Visits (2011)
# L-spine
Imaging exams
Kaiser PNCA 17 1096 2,430,000 149,300 44790Henry Ford 26 230 187,000 23,900 7170Group Health 24 303 347,000 37,700
11310Mayo Clinic 61 269 1,500,000 106,700 32010Total 128 1,898 4,464,000 317,600 95,280
LIRE Aims/Working Groups and Leaders1. Refinement of benchmark text
Jerry Jarvik, MD MPH2. Implementation of cluster randomization
Bryan Comstock, MS3. Spine intervention intensity measure
Brian Bresnahan, PhD4. Electronic data capture
Nick Anderson, PhD5. IRB, Protocols, Subcontracts
Katie James, PA, MPH
LIRE Aims/Working Groups and Leaders1. Refinement of benchmark text
Jerry Jarvik, MD MPH2. Implementation of cluster randomization
Bryan Comstock, MS3. Spine intervention intensity measure
Brian Bresnahan, PhD4. Electronic data capture
Nick Anderson, PhD5. IRB, Protocols, Subcontracts
Katie James, PA, MPH
LIRE Aim 3• Develop/validate a composite
measure of spine intervention intensity-a single metric of overall intensity of resource utilization for spine care
Aim 3 Progress• Working with site programmers to
pull CPT data• Already established data pulls for 2
sites• Constructed density plots of CPT
–For QC checks–Compare site use of codes
BOLD: CPT Code Frequencies By SiteSite 1Site 2Site 3
BOLD: Density Plot of Radiology CPT Code Frequencies By Site for QC
Site 1Site 2Site 3
BOLD: Density Plot of Surgery CPT Code Frequencies By Site
Site 1Site 2Site 3
Aim 3 (cont.)• Converted CPT codes to RVUs as
our primary metric of back-related utilization–Used total RVU (tech + pro)–Did not use geographic adjuster–Use 2012 values using CMS look-up
files
Converting CPTs to RVUs
• Validate CPT conversion by directly pulling RVUs from one site
Example RVU ValuesHCPCS DESCRIPTION TOTAL 2012
RVUs72100 X-ray exam of
lower spine1.07
99214 Office/outpatient visit level 4
2.26
72131 CT lumbar spine w/o dye
6.27
72148 MRI lumbar spine w/o dye
11.31
63047 Laminectomy 32.89
CPT Proportion of RVUs
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
99214 99233 99223 99213 99285 72148 99215 G0202
Site 1Office level IV
Subsequent hospital care
Initial hospital care Office
level III
ED visit MR Lspine
Office level V
Screening mammo
dig
Challenges• CPT counts seem to differ by site
– Step wedge design helps to address this since before-after comparison is within site
– Using only back-related RVUs improves accuracy/reliability using algorithm developed by Martin et al at Dartmouth
• Different pharmacy data systems (e.g. not all sites have Rx filled data)– Within-system comparisons will be valid
Challenges• System differences will always be present
in large pragmatic trials• When do pragmatic trials become meta-
analysis of parallel trials?
Key People to ThankUW
• Katie James, PA-C, MPH-Proj Dir
• Bryan Comstock, MS- Biostats• Nick Anderson, PhD-
Biomedical Informatics• Brian Bresnahan, PhD- Health
Economist• Patrick Heagerty, PhD- Biostat• Judy Turner, PhD-
Psychologist/Pain expert
Non-UW• Rick Deyo, MD, MPH-OHSU• Dan Cherkin, PhD-GHRI• Heidi Berthoud. MPH- GHRI• Safwan Halabi, MD-HFHS• Dave Nerenz, PhD- HFHS• Dave Kallmes, MD- Mayo• Jyoti Pathak, PhD- Mayo• Patrick Luetmer, MD- Mayo• Andy Avins, MD MPH-KPNC