Using VA Pharmacy Data.ppt

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					              VIReC Cyber Seminar Series 2006




    VA Databases and Methods
          Using VA Pharmacy Data
                         Presented by
                 Todd A. Lee, PharmD, PhD
             Senior Investigator, MCHSPR COE
       VIReC, Senior Scientific Expert Pharmacy Data
Research Assistant Professor, Northwestern University Feinberg
                     School of Medicine



                                                                 1
        Session Objectives

Measurement Issues with Pharmacy Data

Key Data Source Review: PBM Data & DSS
Pharmacy Data

Measurement Issues and Use of Pharmacy Data

Where To Go For More Help




                                              2
  Pharmacy Data Measurement
           Issues
Comparability of data sources
 – Do PBM and DSS contain the same data?
Medication utilization
 – Recent year? Longer historical view? Does policy change impact
   medication use?
Exposure to specific medications or medication classes
 – Are specific drugs associated with better/worse outcomes?
Medication adherence
 – How much of a prescribed medication are patients using?
Combining outpatient and pharmacy data to identify events
 – Can we identify acute exacerbations of COPD with outpatient and
   prescription data?
Assessing comorbidity or case-mix with medication data
 – Diagnoses-based measures vs. pharmacy-based measures



                                                                     3
       Session Objectives

Measurement Issues with Pharmacy Data

Key Data Source Review: PBM Data & DSS
Pharmacy Data

Measurement Issues and Use of Pharmacy
Data

Where To Go For More Help
                                         4
Pharmacy Data Sources
Local Databases
– VistA
– VISN Warehouses


National Data Sources
– PBM
– DSS NDE Pharmacy SASⓇ Datasets
– FCDM



                                   5
      VistA Pharmacy Data

Veterans Health Information Systems and
Technologies Architecture
All Prescription Orders and Fills
– Inpatient and Outpatient
– CMOP (Consolidated Mail Outpatient Pharmacy)
   • in VistA system for site where fill was requested
Local Files
– At each VistA installation



                                                         6
      VistA Pharmacy Data

Prescription Orders Dispensed
– Prescription File (FILE 52) - Outpatient
– Pharmacy Patient File (FILE 55) - Inpatient
   • IV Orders (FILE 55.01)
   • Unit Dose Orders (FILE 55.06)
– Local Drug File (FILE 50)
Years covered
– 1997 forward
– Varies by site


                                                7
     VistA Pharmacy Data

Accessing
– FileMan – hierarchical database management
  system
– MUMPS
– SQL
VISN Warehouses
– Some contain prescription data
– Relational databases



                                               8
          PBM Database
Pharmacy Benefits Management Database

FY1999 forward (October 1, 1998)

Maintained by PBM/SHG at Hines VA
Hospital

Researchers must request extract


                                        9
National Extracts - PBM




                          10
             PBM Database
Information in the Database
–   Outpatient Prescriptions Dispensed
–   Inpatient Prescriptions Dispensed (IV & Unit Dose)
–   Selected Labs
–   Controlled Substance Use
–   Automatic Replenishment/Ward Stock
–   Procurement and Accounting
–   Provider Information
–   Patient Information


                                                    11
    PBM Database Variables
            Outpatient Prescription
Dispensing Details
–   Fill Date
–   Drug Name
–   Station Name
–   Quantity
–   NDC – National Drug Code
–   Dosing Instructions
–   VA Drug Class
–   Dispense Unit and Price per Dispense Unit



                                                12
   PBM Database Variables
          Outpatient Prescription
Provider Information
– Provider ID
– Provider Service
   • Cardiology, Dental, Nursing, Surgery, etc.
– Provider Specialty & Subspecialty
– Provider Type
   • Staff, Fee, or Non-VA (TPB)
Patient Information
– Patient Prescription Status

                                                  13
 DSS NDE Pharmacy SASⓇ
        Datasets
Decision Support System National Data
Extract Pharmacy SASⓇ Datasets.
FY2002 forward
Located on the host at the Austin Automation
Center
Directly accessible by Researchers




                                           14
National Extracts - DSS




                          15
      DSS NDE Pharmacy
        SASⓇDatasets
Information in the Datasets
– Outpatient Prescriptions Dispensed
– Inpatient Prescriptions Dispensed
   • IV
   • Unit Dose




                                       16
 DSS NDE Pharmacy SASⓇ
        Datasets
Files
– RMTPRD.MED.DSS.SAS.FYYY.VISNX.PHA
   • YY – year
   • VISN – V1TO5, V6TO10, V11TO16, V17TO22
   • X – I for inpatient, O for outpatient
        – Based on patient status for encounter not type of
          prescription
        – Safest to always use both files
– Inpatient
   • RMTPRD.MED.DSS.SAS.FY03.V1TO5I.PHA
– Outpatient
   • RMTPRD.MED.DSS.SAS.FY03.V1TO5O.PHA


                                                              17
                        PBM vs. DSS
                    PBM                            DSS

Cost                Drug supply cost               Actual cost (ACT_COST)
                                                   Dispensing cost (DISPCOST)
                                                   Supply cost (VS_COST)
Access              Researcher requested extract   Direct access



Data availability   FY1998 (Outpatient)            FY2002 (Outpatient & Inpatient)
                    FY2006 (Inpatient)

Directions for      SIG available
use



                                                                               18
       Session Objectives

Measurement Issues with Pharmacy Data

Key Data Source Review: PBM Data & DSS
Pharmacy Data

Measurement Issues and Use of Pharmacy
Data

Where To Go For More Help
                                         19
     Measurement Issues: Pharmacy
           Data Comparison
          CSP 456 Hernia Study
          Population
           – 1,591 Patients in the CSP 456 Study
          Prescriptions
           –   Outpatient
           –   FY2002
           –   Fills and refills
           –   42,469 prescriptions
Report Available at:
     http://www.virec.research.va.gov/References/TechnicalReports/VIReCTechnicalReport1.pdf

                                                                                    20
    Measurement Issues:
 Pharmacy Data Comparison
Preliminary Results
                 Prescriptions with "Discrepancies"                   Total
                           Unatched Days
Number of Prescriptions on the PBM file only                          136
Number of Prescriptions on the DSS file only                          42
Number of Prescriptions with Unequal Quantities                       200
                            Matched Days
Number of Prescription with a Drug Name only on PBM                    131
Number of Prescriptions with a Drug Name only on DSS                   14
Number of Prescriptions with no Drug Name on DSS or PBM                112
Number of Prescriptions with a Name for Different Drug on DSS & PBM    97
Total Number of Discrepancies                                          732
Percent of Total Number of Prescriptions                              1.7%




                                                                              21
   Measurement Issues:
Pharmacy Data Comparison
Limitations
– Outpatient only
– Cohort not representative of whole population
Conclusions
– DSS and PBM Pharmacy extracts capture same
  prescriptions
– DSS or PBM?
Future Comparisons
– Inpatient data?
– Representative Cohort
Anecdotal evidence of other examples where match
is not as good

                                                   22
Measurement Issues: Medication
         Utilization
Did change in prescription drug copayment impact
medication utilization? (HSR&D ECI 02-220, PI:
Kevin T. Stroupe, PhD)
Examined 30-day equivalents of use of chronic
medications in 3 groups of patients before and after
copayment change
Identified utilization in several categories: essential
vs. non-essential; OTC vs. prescription; high cost vs.
low cost; brand vs. generic
Number of medications obtained from the VA
decreased among those subject to copayments and
biggest effects were in low cost and OTC
medications

                                                      23
Measurement Issues: Exposure to
     specific medications
 Determine if the use of ICS is associated with an
 increased risk of non-vertebral fractures in patients
 with COPD in the VA
 Conducted a nested case-control study in a cohort of
 VA patients with COPD
 Found increased risk of fractures in COPD patients
 using high dose ICS
 Needed to quantify amount of use of inhaled
 medications
 Pharmacy data not always easy to work with –
 particularly true with regard to inhaled products
 – More straightforward to calculate cumulative exposure when
   dealing with tablets/capsules than with inhalers


                                                            24
     Measurement Issues: Exposure to
          specific medications


ID




1

2



3




                                   25
Measurement Issues: Exposure to
     specific medications
  VA_PRODUCT
  – Used to determine specific product
  – Used to determine dose strength
  – Used to determine number of actuations
  SIG
  – Used to determine dosing frequency
  – Used to determine number of doses per day




                                                26
Measurement Issues: Exposure to
     specific medications

 Calculation of cumulative ICS exposure
  – Determine strength for each prescription
     • Fluticasone 220g
  – Convert strength to beclomethasone equivalents
     • BDP_Equiv => 220*0.5 = 110g per dose
  – Determine number of doses per prescription
     • quantity dispensed * doses per product
     • 1 canister * 120 actuations/canister = 120 doses
  – Calculate beclomethasone equivalents for each prescription and
    sum for cumulative exposure


                                                               27
Measurement Issues: Medication
         Adherence
Examine factors associated with non-adherence in
patients with COPD
Measured adherence to respiratory medications
using Medication Possession Ratio (MPR)
              DaySupply
                    Aug1, 2003toJuly 31, 2004
MPRi = ((LastRxDate DaySupply)  Aug1,2003)
Found use of CMOP and hospitalizations in prior
period associated with higher adherence
Cautions: day supply variable accuracy (oral meds
vs. inhaled meds); accounting for medications and
days supply at beginning and end of period of interest

                                                    28
Measurement Issues: Combining
 Outpatient and Pharmacy Data
Identify acute exacerbations of COPD in the
outpatient setting
Use a combination of outpatient ICD-9 codes and Rx
data
Found many outpatient ICD-9 codes non-specific for
identifying COPD exacerbation
Most Rx for oral steroids or antibiotics dispensed
within ±5 days of ICD-9 code
Used algorithm to disqualify ICD-9 codes and
medication prescriptions
– SIGS with cellulitis, pharyngitis, sinusitis, etc.


                                                       29
 Measurement Issues: Identifying
Comorbidities with Pharmacy Data
 Development of a VA-based version of RxRisk
 (Chronic Disease Score)
 – Sloan KL, et al. Construction and characteristics of RxRisk-
   V: a VA-adapted pharmacy-based case-mix instrument. Med
   Care 2003; 41(6): 761-74
 Potential value in using pharmacy-based measures
 versus ICD-based measures
 RxRisk-V performed similarly to HCC and ADG case-
 mix adjusters when predicting costs prospectively
 – Sales AE, et al. Predicting costs of care using a pharmacy-
   based measure risk adjustment in a veteran population. Med
   Care 2003; 41(6): 753-60


                                                             30
       Session Objectives

Measurement Issues with Pharmacy Data

Key Data Source Review: PBM Data & DSS
Pharmacy Data

Measurement Issues and Use of Pharmacy
Data

Where To Go For More Help
                                         31
                VIReC Help
VIReC Webpage
http://www.virec.research.va.gov

– Information on VA data sources and how to
  access data
– Documentation on some VA datasets, i.e., Medical
  SAS datasets:
    • http://www.virec.research.va.gov/DataSourcesName/Med
      ical-SAS-Datasets/SASdocumentation.htm
    • Includes lists of variables and their dataset locations
    • Descriptions of each of the variables
    • Values for selected variables


                                                           32
       VIReC Help (cont’d)
HSRData Listserv
– Join at VIReC Web site
– Discussion among > 200 data stewards, managers,
  and users
– Past messages in archive (on intranet)

VIReC Help Desk
– VIReC staff will answer your question and/or direct
  you to available resources on topics
– VIReC@va.gov
– (708) 202-2413
                                                  33
                     References
Arnold N, Hynes DM, Stroupe KT. VIReC Technical Report 1:
Comparison of VA Outpatient Prescriptions in the DSS Datasets and
the PBM Database. Edward Hines, Jr. VA Hospital, Hines, IL: VA
Information Resource Center, January 15, 2006.
Lee TA, Weiss KB. Risk of non-vertebral fractures associated with
inhaled corticosteroid use in obstructive lung disease. Am J Respir Crit
Care Med. 2004; 169(7): 855-859.
Charbonneau A, Rosen AK, Ash AS, Owen RR, Kader B, Spiro A, III, et
al. Measuring the quality of depression care in a large integrated health
system. Med Care 2003; 41(5):669-680.
Sloan KL, et al. Construction and characteristics of RxRisk-V: a VA-
adapted pharmacy-based case-mix instrument. Med Care 2003; 41(6):
761-74
Sales AE, et al. Predicting costs of care using a pharmacy-based
measure risk adjustment in a veteran population. Med Care 2003;
41(6): 753-60



                                                                       34
                   VIReC CyberSeminar Series 2006

     VA Databases and Methods
         Sponsored by VA Information Resource Center (VIReC)
                   Every first Tuesday of the month
                           from 1 – 2 pm ET
                           Next Cyber Seminar:
                             November 7, 2006
                            “VA-Medicare Data”
      Presented by: Kathy Mallin, PhD and Kristin Koelling, MPH (VIReC)
This session focuses on assessing non-VA health care use using VA-Medicare data. The
following is the session agenda:
* Why use VA-Medicare Data?
* Learn about the VA-Medicare Data Merge Initiative and available data
* Understand how to request VA-Medicare data
* Learn where to go for help
 Schedule available at: http://www.hsrd.research.va.gov/for_researchers/cyber_seminars/




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