Federico Girosi | Geographic variation in medical expenditures for GP services in NSW older adults


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Associate Professor Federico Girosi gave an update on her research using the 45 and Up Study data at the Sax Institute's 45 and Up Study Collaborators' Meeting.

This meeting is an annual event that offers our research partners, supporters and other interested parties the opportunity to receive a comprehensive update on the 45 and Up Study’s progress and updates on research projects that are using the Study resource. The meeting is also an opportunity for researchers, health decision makers and evaluators to engage and discuss the potential for maximising the Study’s value.

For more information, visit www.saxinstitute.org.au.

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Federico Girosi | Geographic variation in medical expenditures for GP services in NSW older adults

  1. 1. Geographical Variation in Medical Expenditures: What Varies, How Much and Where University of Western Sydney • • • • Federico Girosi Xiaoqi Feng Louisa Jorm Thomas Astell-Burt Australian National University • • • • Ian McRae Soumya Mazumdar Danielle Butler Paul Konings
  2. 2. why study geographic cost variation? variation may have different sources • unobservable features • access to care • use of guidelines/technolo gies • … geographic variation may point to inefficient use of resources
  3. 3. first in a series of investigations in geographic variation of costs Today we focus on yearly total GP expenditures We document variation in total expenditures at individual and geographic level We relate variation in expenditures to variation in visits and price We look at the role of remoteness in explaining variation across Statistical Local Areas (SLAs)
  4. 4. data and methods 45 and Up data linked to MBS data • accessed through SURE GP services: MBS items representative of primary care • 85% of claims: consultation level B, C and A yearly expenditures and visits • 6 months around interview date • cost is expressed in constant 2012 $ All regression are OLS • Ellis et al. (2013) already showed it is preferable • our results are not dependent on specific method
  5. 5. definition of key variables • Charge: how much was charged by the physician Ci: charge for visit i n: number of visits in a year
  6. 6. Variation in charges across SLAs Average per capita yearly charges for GP services average NSW charge Adjusted for: • age • sex • SES • health status • risk factors
  7. 7. What does this figure suggest? After controlling for individual characteristics there is significant variation in annual GP charges across SLAs • Ratio of 95th to 5th percentile in charges is 1.6 Remoteness will play a role in explaining the observed pattern • Charges in cities are 31% larger than charges in outer regions
  8. 8. what varies? Visits or Prices? Log(Charge) = log(Price) + log(Visits) We run three regressions at individual level: Log(Charge) = βX R2=0.23 Log(Charge) = log(Price) + βX R2=0.30 Log(Charge) = βX + log(Visits) R2=0.92 It is visits that drives variation in charges this remains true even for specific MBS items
  9. 9. What explains the variation at individual level? Covariates: • age • sex • SES • health status • risk factors • SLA
  10. 10. What explains the variation across SLAs at aggregate level? Charge (R2 = 0.45) Visits (R2 = 0.39) Price (R2 = 0) Estimate t value Estimate t value Estimate t value (Intercept) 394.7 107.3 8.1 86.6 46.9 140.5 Inner regional -56.6 -9 -1.3 -8.2 0.2 0.3 -10.8 -2.1 -9.3 -0.2 -0.3 -1.7 -1.4 -1.9 0.9 0.3 Outer regional -94.9 Remote -46.5
  11. 11. Summary There is significant variation in GP expenditures across SLAs unexplained by individual characteristics The variation is due to variation in the number of GP visits, rather than in the average price per visit Observed individual characteristics explain 20% of the variance in GP expenditures Remoteness explains a large proportion of the variance in aggregate SLA GP expenditures
  12. 12. Additional Material
  13. 13. Variation of SLA means Charge Mean 366 Ratio of 99th to 1st percentile 2.15 Ratio of 75th to 25th percentile 1.21 Coefficient of variation 0.14 R squared 0.20 Visits 7.5 2.18 1.27 0.17 0.24 Price 47 1.39 1.10 0.08 0.09
  14. 14. Focus on a specific item: 23 (level B consultation) Log(Charge) = log(Price) + log(Visits) We run three regressions: Log(Charge) = βX R2=0.16 Log(Charge) = log(Price) + βX R2=0.18 Log(Charge) = βX + log(Visits) R2=0.95 It is visits that drives variation in charges
  15. 15. Remoteness Is Likely to Play an Important Role in the Analysis Adjusted for: • age • sex • SES • health status • risk factors