350 likes | 682 Views
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
E N D
VIReC Cyber Seminar Series 2006VA 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
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
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
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
Pharmacy Data Sources • Local Databases • VistA • VISN Warehouses • National Data Sources • PBM • DSS NDE Pharmacy SASⓇ Datasets • FCDM
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
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
VistA Pharmacy Data • Accessing • FileMan – hierarchical database management system • MUMPS • SQL • VISN Warehouses • Some contain prescription data • Relational databases
PBM Database • Pharmacy Benefits Management Database • FY1999 forward (October 1, 1998) • Maintained by PBM/SHG at Hines VA Hospital • Researchers must request extract
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
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
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
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
DSS NDE Pharmacy SASⓇDatasets • Information in the Datasets • Outpatient Prescriptions Dispensed • Inpatient Prescriptions Dispensed • IV • Unit Dose
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
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
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
Measurement Issues: Pharmacy Data Comparison • Preliminary Results
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
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
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
Measurement Issues: Exposure to specific medications ID 1 2 3
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
Measurement Issues: Exposure to specific medications • Calculation of cumulative ICS exposure • Determine strength for each prescription • Fluticasone 220g • Convert strength to beclomethasone equivalents • BDP_Equiv => 220*0.5 = 110g 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
Measurement Issues: Medication Adherence • Examine factors associated with non-adherence in patients with COPD • Measured adherence to respiratory medications using Medication Possession Ratio (MPR) • MPRi = • 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
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.
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
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
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/Medical-SAS-Datasets/SASdocumentation.htm • Includes lists of variables and their dataset locations • Descriptions of each of the variables • Values for selected variables
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
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
VIReC CyberSeminar Series 2006VA Databases and MethodsSponsored 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/