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Use and Integration of Freely Available U.S. Public, Use Files to Answer Pharmacoeconomic Questions:
Deciphering the Alphabet Soup

 

Slide 1: Use and Integration of Freely Available U.S. Public

Use Files to Answer Pharmacoeconomic Questions:

Deciphering the Alphabet Soup

Prepared by Ovation Research Group for the National Library of Medicine

October 20, 2006

Slide 2: Public Use Files: The Opportunities

  • Free or low-cost
  • Can answer many Pharmacoeconomic questions
  • Prevalence
  • Incidence
  • Utilization
  • Unit costs
  • Trends over time
  • Helpful for benchmarking other sources, or for sensitivity analyses

Slide 3: Public Use Files: Your Questions and the Alphabet Soup

  • HCUP
  • BRFSS
  • Prevalence?
    • MEPS
  • Incidence?
  • Time Trends?
    • NHANES
  • Utilization?
    • NHDS
    • NAMCS
  • Unit Costs?
    • NHIS

Slide 4: Where to Begin?

  •  Identify questions that are appropriate for PUF data
  •  Classify data by source and content
  •  Step through examples matching PUF data to research questions
  •  Review general guidelines and pitfalls to avoid
  •  Provide resources for future use

Slide 5: Questions that PUF Data can Answer

  • Prevalence of chronic disease
    • How many adults have arthritis in the US?
  • Incidence of acute diseases or events
    • What is the incidence of acute respiratory failure?

Slide 6: More Questions that PUFs can Answer

  • Medical resource use associated with a condition or procedure
    • Hospitalizations
    • Emergency Department, Outpatient, or ambulatory visits
  • Disease Direct Costs
  • Total amounts paid for health care for individuals with a disease
  • Indirect costs
    • Usually lost earnings attributable to a disease

Slide 07: Where to Begin?

  • Identify questions that are appropriate for PUF data
  • Classify data by source and content 
  • Step through examples matching PUF data to research questions
  •  Review general guidelines and pitfalls to avoid
  •  Provide resources for future use

Slide 08: Classification of PUF Data: Definitions

  • Population-based surveys
    • Generalizable to the non-institutionalized population
    • Include socio-demographic information
    • Information usually based solely on respondent self-report
  • Facility-based visit samples
    • Disease and utilization information from medical records
    • Prevalence inferences must be made cautiously

Slide 09: PUF Data: More Definitions

  • Administrative
    • Based on records of utilization kept by public agencies (e.g., Medicaid, Medicare)
    • Due to privacy concerns (HIPAA) Medicare and Medicaid claims data are now more difficult to obtain
  • Other
    • Utilities and files available for download

Slide 10: PUF Population-Based Surveys

  • National Health Interview Survey (NHIS)
    • Conducted annually by NCHS
    • Certain “priority”conditions asked of all adult and child respondents
    • Supplements available in various years
  • Medical Expenditure Panel Survey (MEPS)
    • Conducted annually by AHRQ since 1996
    • Household survey includes information on health-care resource use, costs, and insurance coverage

Slide 11: PUF Population-Based Surveys (cont)

  • National Health and Nutrition Examination Survey (NHANES)
    • Six waves of data available
    • Health information from physical and lab examinations
    • Wide range of disease information (e.g., infectious diseases, risk factors for cardiovascular disease)

Slide 12: PUF Population-Based Surveys (cont)

  • Behavioral Risk Factor Surveillance System (BRFSS)
    • Conducted annually by state agencies and NCHS
    • Gathers information on health behaviors linked to leading causes of death (e.g., heart disease, cancer, stroke)
    • Telephone survey

Slide 13: PUF Population-Based Surveys (cont)

  • Behavioral Risk Factor Surveillance System (BRFSS)
    • Conducted annually by state agencies and NCHS
    • Gathers information on health behaviors linked to leading causes of death (e.g., heart disease, cancer, stroke)
    • Telephone survey

Slide 14: PUF Population-Based Surveys (cont)

  • Longitudinal Studies of Aging (LSOAs)
    • Collaborative project of National Center for Health Statistics (NCHS) and the National Institute on Aging (NIA)
    • Study of individuals 70 years of age and over that records health, functional status, living arrangements, and health services utilization over time
    • Data obtained from a variety of sources (e.g., surveys, Medicare claims)
    • Chronic and acute conditions, as well as cause of death recorded

Slide 15: PUF Population-Based Surveys (cont)

  • National Immunization Survey (NIS)
    • Conducted annually by NCHS
    • Provides state and local area estimates of vaccination coverage in children between 19-35 months of age
    • Specific vaccinations administered to each child as reported by family and (optionally) by provider are recorded

Slide 16: PUF Facility-Based Samples

  • National Hospital Discharge Survey (NHDS)
    • Conducted annually by NCHS
    • Discharges from non-institutional, non-Federal hospitals
    • Primary and secondary diagnosis and procedure codes
    • Length of stay, discharge status, demographics

Slide 17: PUF Facility-Based Samples (cont)

  • National Ambulatory Medical Care Survey (NAMCS) and National Hospital Ambulatory Medical Care Survey (NHAMCS)
    • Conducted annually by NCHS
    • Sample of patient visits to office-based physicians (NAMCS) or Emergency or Outpatient Hospital Departments (NHAMCS)
    • Primary and secondary diagnosis and procedure codes
    • Drug provided/prescribed
    • Demographics

Slide 18: PUF Facility-Based Samples (cont)

  • Health Care Utilization Project National Inpatient Sample (HCUP-NIS)
    • Released annually by AHRQ
    • Currently includes 1,004 hospitals in 37 states
    • Similar information as NHDS, plus total charges and median income of patient’s residence
    • Small charge (e.g., $200 for 2004)
    • Some statistics can be run online at no charge

Slide 19: PUF Facility-Based Samples (cont)

  • Health Care Utilization Project Kids’Inpatient Database (HCUP-KID)
    • Available for 1997, 2000, and 2003 from AHRQ
    • 2003 release includes hospitals in 36 states
    • Same information as HCUP-NIS, but large enough to study rare conditions in children
    • Small charge (e.g., $200 for 2003)

Slide 20: PUF Facility-Based Samples (cont)

  • National Nursing Home Survey (NNHS)
    • Available for 1995, 1997, 1999, 2004
    • National sample of nursing home residents and staff
    • Diagnoses at admission
    • Use of various medical devices at admission
    • Demographics
    • Length of stay, total and daily charges

Slide 21: PUF Facility-Based Samples (cont)

  • National Home and Hospice Care Survey (NHHCS)
    • Available for 1992, 1994, 1996, 1998, 2000
    • Information is collected from home and hospice agencies and their patients
    • Diagnoses and procedures
    • Demographics

Slide 22: PUF Facility-Based Samples (cont)

  • Medicare Current Beneficiary Survey
    • Longitudinal sample of Medicare Beneficiaries by NCHS
    • Up to 4 years of data for each respondent
    • Health status, functioning, demographics
    • Utilization /cost information merged from administrative data
    • Must sign a data use agreement and purchase the files for $480 per year.
    • Certain high-level results for each year available online.

Slide 23: PUF Facility-Based Samples (cont)

  • Medicare Health Outcomes Survey (HOS)
    • Conducted periodically by CMS (Centers for Medicare and Medicaid Services)
    • Samples Medicare, managed care enrollees
    • Physical functioning and well-being at baseline & follow-up
    • No sampling weights yet for inference to entire Medicare managed care population

Slide 24: PUF Facility-Based Samples (cont)

  • National Compensation Survey (NCS)
    • Conducted periodically by BLS; most recently in 2005
    • Sample of workplaces by size
    • Wage information by occupation, industry, gender
    • Helpful for assigning unit costs for lost work time
    • Learning curve to find the data you need

Slide 25: PUF Facility-Based Samples (cont)

  • National Survey of Ambulatory Surgery
    • Study of ambulatory surgical care in hospital-based and freestanding ambulatory surgery centers (ASCs).
    • Originally conducted from 1994 to 1996, but it was discontinued due to lack of resources.
    • The NSAS is being conducted again in 2006.
    • Data for the NSAS will be collected for approximately 60,000 ambulatory surgery cases in 2006 from a nationally representative sample of hospital-based and freestanding ambulatory surgery

Slide 26: PUF Administrative Data

  • Medicaid State Drug Utilization Data
    • Available for 1996 to present in annual files
    • State and national level
    • NDC, FDA product name
    • Total reimbursed amount and total units reimbursed

Slide 27: PUF Administrative Data (cont)

  • Medicare Limited Dataset Standard Analytic Files
    • Available for 1991 –2004 in a series of files:
      • Part A claims (inpatient, outpatient, SNF, hospice, or HHA)
      • Part B claims (physician/supplier services, durable medical equipment)
      • Denominator
    • All entities must apply in order to purchase data
    • LDS mask date of service to the quarter of service, and age to 5-year categories
    • Total amounts charged and paid provided
    • Steep learning curve

Slide 28: PUF Administrative Data (cont)

  • Medicare Payment Rates and RVU
    • CMS provides annual RVU files on its web site
    • Not as user friendly as what you can buy (e.g., Physician Fees on disk)
    • Physician, clinical laboratory, ambulatory surgical procedures, and durable medical equipment available through an interactive web site

Slide 29: PUF Utilities

  • ICD-9-CM Diagnosis Codes
    • Codes with short definitions updated yearly by CMS
  • ICD-9-CM Conversion File
    • Records changes in diagnosis and procedure codes through time
  • Statistical Abstract of the United States
    • Published annually by US Census Bureau
    • Population information can be used for prevalence/incidence denominators
    • CPI information to standardize costs

Slide 30: Where to Begin?

  • Identify questions that are appropriate for PUF data
  • Classify data by source and content
  • Step through examples matching PUF data to research questions
  • Review general guidelines and pitfalls to avoid
  • Provide resources for future use

Slide 31: Answering Your Questions: Prevalence of a Chronic Condition

  • Is it Included in NHIS checklist?
    • Yes? Use NHIS Pool years if necessary
    • No? Is it Included in BRFSSor NHANES?
      • Yes? Use Use either or both Pool years if necessary
      • No? Is it Identifiable by 3-digit ICD-9-CM?
        • Yes? Use MEPS Backup with other sources
        • No? Try NHANES for lab or examination values

Slide 32: Prevalence of A Chronic Condition: Example Using NHIS

  • Prevalence of adults with asthma in the non-Institutionalized Population in 2001.
  • Use NHIS
    • “Have you ever been told by a doctor or other health professional that you have asthma?”included in adults condition sample
  • The Answer
    • Weighted estimate: 22.2 million out of 203.8 million adults (10.9%) in 2001 had been diagnosed with asthma.
    • May include individuals who no longer experience symptoms

Slide 33: Answering Your Questions: Incidence of Acute Disease or Injury

  • Injury?
    • Yes, NHIS Injury/Poisoning filePool years if necessary
    • No, Treated in particular setting(hospital, ED, doctor’s office)
      • Yes, Use appropriate facility survey(s)(HCUP-NIS, NHDS, NAMCS, NHAMCS)Discount multiple visits per event

Slide 34: Incidence of an Acute Condition: Example Using NHIS & Facility Surveys

  • Report to National Academies of Sciences Institute of Medicine on the Epidemiology of Poisoning (Cisternas and Blanc)
  • PUF Sources
    • NHIS injury/poisoning supplement
    • NAMCS, NHAMCS, and NHDS
  • Details
    • Poisoning identifiable through 3-digit ICD-9-CM and E-Codes
    • Known underreporting in NHIS
    • Supplemented by NAMCS, NHAMCS and NHDS
      • Discounted for multiple visits per individuals
      • Discounts based on episode-of-care information and expert opinion

Slide 35: Answering Your Questions: Unit Costs for Direct Medical Utilization

  • Is it Identifiable by 3-digit ICD-9-CM?
    • Yes, Subset from MEPS filesTry several ways of subsetting/summarizingIdentifiable
    • No, Identifiable by CPT-4 or DRG?
      • Yes, Medicare payment schedules
      • No, Identifiable by NDC?
        • Yes, Medicaid drug payment data AWP from Red Book

Slide 36: Unit Costs for Direct Medical Utilization: Example Using MEPS & AWP

  • Cisternas et al. “A Comprehensive Study of the Direct and Indirect Costs of Adult Asthma.”J Allergy ClinImmunol. 111 (6):1212-1218.
  • Public Cost Sources
    • MEPS for office and emergency visits and hospitalizations
    • Red Book(AWP) for drug prices
  • Details
    • Used positive paid amounts (not charges) from MEPS
    • Pooled several years of MEPS and standardized cost to a base year using medical component of the CPI
    • Calculated weighted average of AWP for all NDCsin drug classes based on market share

Slide 37: Where to Begin?

  • Identify questions that are appropriate for PUF data
  • Classify data by source and content
  • Step through examples matching PUF data to research questions
  • Review general guidelines and pitfalls to avoid
  • Provide resources for future use

Slide 38: Suggestion #1: Answer the Following Questions First

  • What segments of the population are affected by this condition/procedure?
    • Adults? children? elderly? nursing home residents?
  • In which patient settings does a treatment of interest occur?
    • Inpatient? ED? Doctors office?
    • Usually resolved in one patient encounter?
  • Which ICD-9-CM, CPT, or NDCsare used to identify your disease or treatment?
    • Is identification straightforward, or is there inherent uncertainty?

Slide 39: Suggestion #2: Know When to Pool

  • As a general rule, estimates from NCHS surveys require N>50
  • Can usually pool data from several waves/years
  • Check record layout and coding for each variable of interest in every year
    • Variables such as race, insurance status have changed through time

Slide 40: Suggestions #3: Apply Common Sense

  • Conduct a thorough literature review and compare your results to past studies
  • If time/budget permit, use several data sources and compare results
  • If complicated file merging is necessary, ensure you have technical expertise (SAS, SPSS) on hand
  • Conduct sensitivity analyses
    • Even using the same source, several definitions of your population can be applied

Slide 41: PUF Pitfall #1: Coding Inaccuracies

  • The Problem
    • Medical coding is an art, not a science
    • Variation across coders
    • Upcodingto maximize reimbursement
  • Mitigation
    • For diagnoses, compare results from primary field selection to any field inclusion
    • Compare distributions between payors/type of insurance for consistency

Slide 42: PUF Pitfall #2: Self-Report &Recall Bias

  • Problem for population-based surveys (MEPS, NHIS, BRFSS)
    • Respondents may not know their diagnosis
    • Respondents may forget diagnosis history
  • Mitigation
    • Augment with estimates from administrative sources
    • Augment with estimates from facility-based surveys

Slide 43: PUF Pitfall #3: Different Cost Perspectives

  • Perspectives can include charges, paid amounts, or allowed amounts
  • Pick a perspective and try to estimate an adjustment factor to apply to other perspectives
  • Example
    • Your study has chosen paid amount perspective
    • HCUP-NIS only provides charges
    • Develop a charge-to-paid ratio using similar hospitalizations from MEPS

Slide 44: PUF Pitfall #4: Combining Sources from Different Years

  • Check for changes in ICD-9-CM or CPT coding if applicable, e.g., hepatitis or AIDS
  • Pick a base year
  • If combining costs, adjust to base year using medical component of the CPI (from Statistical Abstract of the United States)
  • Don’t forget to divide the annual weight by the number of pooled years and adjust denominator appropriately.

Slide 44: Conclusions

  • PUF data are a cost effective resource for Pharmacoeconomic questions
  • Many are freely downloadable via the web
  • However, these sources should be used carefully and be supported by other estimates when possible.