Regional and Racial Variation in Primary Care and the Quality of Care Among Medicare Beneficiaries

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1 MethodsfortheDartmouthAtlasofHealthCareReport: RegionalandRacialVariationinPrimaryCareandthe QualityofCareAmongMedicareBeneficiaries September2010 DavidGoodman,MDMS ShannonBrownlee,MS Chiang HuaChang,PhD ElliottFisher,MDMPH KristenBronner,MA,Editor withtheassistanceofthedartmouthatlasofhealthcareworkinggroup Formoreinformation,visithttp://

2 Documentdescription: Thistechnicaldocumentprovidesadescriptionofthemethodsusedforthe DartmouthAtlasreport,RegionalandRacialVariationinPrimaryCareandthe QualityofCareAmongMedicareBeneficiaries,andtheaccompanyingmeasures. Thedocumentisdividedintothreesections.Inthefirstsection,anoverviewofthe methodsisgiven.thesecondsectionprovidesdescriptionsofeachmeasure, includingthenumeratorsanddenominators.thethirdsectionprovidesaformal descriptionofthemethodsusedtocalculateconfidenceintervals. Otherresourcescanbefoundathttp:// FrequentlyAskedQuestionsandtablescontainingthemeasures,withtheir correspondingconfidenceintervals. SectionOne:MethodsOverview I.Overallapproach Themethodsusedinthisreportweredevelopedoveranumberofyearsandhave beendescribedindetailinpeer reviewedpublications( publications/articles.aspx)andinpreviouseditionsofthedartmouthatlas ( enrollmentandclaimsdataofthemedicareprogramandarerestrictedtothefeefor servicepopulationoverage65;hmopatientsarenotincludedinouranalyses. II.Geographicareas Inthisreportwepresentdatafortwodifferentgeographicunits:(1)Dartmouth Atlashospitalserviceareas(HSAs)(N=3,436),whicharenaturalmarketsforhealth caredefinedonthebasisoftravelforcommoncausesofhospitalization;and(2) DartmouthAtlashospitalreferralregions(HRRs)(N=306),whicharelarger naturalmarketsreflectingtravelfortertiarycarethatincludeoneormorehsasand atleastonemajorreferralhospital.dataarealsoavailableonourwebsiteforstates andcounties.insomeareas,dataaresuppressedaccordingtocmsregulationsto preventpatientidentification. III.TheMedicarepopulation Theanalysespresentedinthisreportfocusoneithertheentirefee for service Medicarepopulationbetweentheagesof65and99whoareeligibleforPartA and/orpartb,orasubsetofthatpopulationatriskforaspecificprocedureor service.forexample,theanalysisofamputationratesexaminestheentiremedicare population,whiletheanalysesoftestingamongdiabeticsarerestrictedtomedicare beneficiariesbetweentheagesof65and75withadiagnosisofdiabetes.

3 Althoughtheanalysisoftreatmentandoutcomesacrossallracialandethnicgroups isanimportantgoal,thedesignationofrace/ethnicityinthemedicaredatais currentlylimited.wecompareblacksandnon blacksforseveralpracticalreasons. SeparateanalysesoftheHispanicpopulationarechallengingbecausefewerthan halfofself designatedhispanicsarecodedassuchinthemedicaredata,hispanics constitutelessthan6%oftheelderlypopulation(ascountedbytheu.s.census), andtheyarehighlyclusteredinafewcommunities,makingitdifficulttocompare communitiesandregions.althoughracialdesignationforasiansandamerican Indiansismoreaccurate,theirsmallnumbers(lessthan3%)alsolimittheprecision ofrace specificanalyses.atthesametime,excludinganyofthesepopulationsfrom theregionalcomparisonsinthisreportwasjudgedtobeundesirable.wetherefore restrictedtheanalysesinthecurrentreporttoblacksandnon blacks,and,forease ofexposition,werefertothenon blackpopulationaswhite.thesechallenges,and thefuturegrowthofthehispanicpopulation,underscoretheimportanceof improvingthecodingofraceandethnicity. IV.Primarycaremeasures Tomeasuretheprimarycarephysicianworkforce,wederivedcountsofphysicians fromthe2006americanmedicalassociation(ama)masterfile.the2006ama Masterfileincludesarecordfornearlyeveryallopathicandosteopathicphysicianin theu.s.withinformationaboutphysicianlocationandself reportedspecialty.we groupedthehundredsofmasterfilespecialtiesinto39categories.primarycare includedfamilyandgeneralpractitioners,generalpediatricians,andgeneral internists.welimitedphysicianstothosewhohavecompletedpost graduate medicaleducation(residency)andworkformorethan20hoursaweekinanoffice orhospital basedpractice.theageofphysicianswaslimitedto26to65. Theabovetabulationofphysiciansprovidedthenumeratorsforcalculatingsupply ratesforprimarycarephysicians.thedenominatorsareregionalpopulation estimatesdevelopedusingdatafromtheu.s.census.allrateswereadjustedfor regionalbordercrossingofpatientsandfordifferencesinpopulationageandsex usingtheindirectmethod. Ourmeasureofprimarycarephysicianclinicalactivityisreportedasclinicalfulltimeequivalentsper100,000beneficiaries.Thenumeratorofthisratewasderived intwosteps.wefirstidentifiedalloftheclaimsbyprimarycarephysicians(family practicephysiciansandgeneralinternists)forservicesprovidedinanoffice based ambulatorysetting,byhsaandhrr.wethenconvertedthesetofull time equivalentsbylinkingtheclaimbillingcodes(healthcarecommonprocedure CodingSystem(HCPCS)database)toworkeffort(workrelativevalueunits(RVUs)), andthendividingbytheaveragenumberofworkrvusperprimarycarephysician. NationalsurveysprovidedthedataontheaveragenumberofworkRVUsper primarycarephysicianbyspecialty. 1

4 Tocalculateannualvisitstoprimarycareclinicians,weidentifiedofficevisitsto generalinternistsandfamilypracticephysiciansfora20%sampleofthemedicare population.wealsoincludedofficevisitstonursepractitioners,althoughthismay slightlyover countprimarycare.tocalculatetherate(aproportion),theevent(the numerator)wasabeneficiarywithatleastoneprimarycareclinicianvisit,andthe population(thedenominator)wasthenumberofbeneficiarieslivingintheregion. Theserateswerecalculatedforeachyearandthenaveragedovertheperiod V.Qualityandoutcomemeasures Thesemeasuresrelyuponclaimssubmittedbyproviders(hospitals,physiciansand outpatientfacilitiesinthiscase)forspecificservicesdeliveredtothepopulation eligibleforthespecificmeasure.forexample,theanalysisofamputationsentailed identifyingallhospitaldischargesoffee for servicemedicarebeneficiarieswherean amputationofthelegwasrecorded.adetaileddefinitionofeachmeasureis documentedinthetablesinsectiontwoofthisdocument. Eachofthemeasuresiseitheraproportion(e.g.theproportionofdiabetics receivinghemoglobina1ctesting)orarate(e.g.thenumberofamputations experiencedbymedicarebeneficiariesdividedbythetotalnumberofmedicare beneficiariesinthegeographicareabeingstudied).arateisusuallyexpressedas thenumberofeventsper1,000medicarebeneficiaries.inthelattercase, beneficiariescanhavemorethanoneevent.whenappropriate,statistical adjustmentsarecarriedouttoaccountfordifferencesinage,raceandsex. VI.PrecisionofAtlasmeasures TheAtlasteamhastakencaretopreparemeasuresofreasonableprecisionandto providethenecessarysupportinginformationthatallowsuserstojudgethelikely importanceofdifferencesinratesandproportions. Thedenominatorsdifferwidely,dependingonthemeasureandtheregion.For somemeasures(e.g.dischargesforambulatorycare sensitiveconditions),theentire fee for servicemedicarepopulationisthedenominator.forotherindicators,such asthosefordiabeticsage65 75,thedenominatorsareobviouslymuchsmaller. Stratificationbyraceleadstoespeciallysmalldenominatorsinsomeregions.To preventmisinterpretationofthesignificanceofdifferencesinratesandproportions, wehavesuppressedaccess,qualityandoutcomemeasureswithadenominatorof lessthan200.forfull timeequivalentprimarycarelaborinputs,wehave suppressedareaswithadenominatoroflessthan100. Evenwiththissuppression,aratethatdiffersacrossregionsorracecannotbe assumedtobestatisticallysignificantorclinicallyimportant.confidenceintervals (95%)areprovidedatwww.dartmouthatlas.org/publications/reports.aspxtoguide users interpretation.althoughthesearenotformalinferentialtests,non

5 overlappingconfidenceintervalsgenerallymeanthatitisunlikelythatthe differencesoccurredbychance.thereadermustbecautiousinmakingmultiple comparisonswheredifferencesmaybefoundevenifoccurringbychance. Itisequallyimportanttointerprettheclinicalorpolicysignificanceofdifferences.If anobserveddifferenceinratesisnotimportant(particularlywhenincludingthe rangeoftheconfidenceintervals),thenastatisticaltestofthedifferenceismoot. Endnote 1. Goodman DC, Stukel TA, Chang CH, Wennberg JE. End-of-life care at academic medical centers: implications for future workforce requirements. Health Affairs (Project Hope) 2006;25:

6 SectionTwo:DefinitionsofMeasures Measure: Primary care physician supply Last revised: 3/1/09 Description: Primary care physicians per 100,000 residents during the measurement year. Time period: 2006 Population: Numerator: Rates: Adjustment: Geographies: Resident population according to U.S. Census estimate. Office- and hospital-based physicians present in American Medical Association Physician Masterfile with the following self-designated specialties: family practice (AMA codes AMF, FM, FP, FSM, GP), internal medicine (HPI, IFP, IM) or pediatrics (PD) who have completed residency training. Overall Age and sex indirect adjustment. Measure is also adjusted for patient border crossing. HRRs, HSAs

7 Measure: Primary care physician labor inputs Last revised: 7/1/10 Description: Full-time equivalent primary care physician labor inputs per 100,000 Medicare beneficiaries during the measurement year. Time period: 2007 Population: Numerator: Rates: Adjustment: Geographies: Medicare, non-hmo, age (mid-year); 20% sample, Part B eligible. Claims by primary care physicians (family practice physicians and general internists) for services provided in an office-based ambulatory setting, converted to full-time equivalents by linking the claim billing codes (HCPCS) to work effort (work relative value units) and dividing by the average number of work RVUs per primary care physician by specialty. Overall, blacks, and non-blacks Age, sex, race indirect adjustment States, HRRs, HSAs, counties

8 Measure: Ambulatory access to primary care clinicians Last revised: 11/16/09 Description: Defined as average percent of Medicare beneficiaries who had at least one ambulatory visit to a primary care clinician in the measurement year. Time period: Population: Medicare, non-hmo, age (mid-year); 20% sample, Part B eligible. Event: Part B ambulatory visit: CPT codes: , , , , , ; and place of service = office (place of service code 11), outpatient hospital (22), rural health clinic (72) or federally qualified health center (50); and physician specialty = general practice (specialty code 1), family practice (8), internal medicine (11), pediatrician (37), nurse practitioner (50), physician assistant (97) or clinic (70). Outpatient file: Rates: Adjustment: Geographies: Any visit to a rural health center (RHC) or federally qualified health center (FQHC) recorded in the outpatient file. Overall, blacks, and non-blacks Age, sex, race indirect adjustment States, HRRs, HSAs, counties

9 Measure: Diabetics receiving hemoglobin A1C test Last revised: 11/5/09 Description: Defined as the occurrence of at least one hemoglobin A1c event during the measurement year to a person with a diabetes diagnosis. Diabetes diagnosis: two face-to-face encounters with different dates of service in an ambulatory setting or nonacute inpatient setting or one face-to-face encounter in an acute inpatient or emergency room setting during measurement year or prior year. Time period: Population: Diabetes definition: Medicare, non-hmo, age (December 31); 20% sample, Parts A & B eligible. ICD-9 diagnosis codes: 250xx, 357.2x, 362.0x, , 648.0x: DRG codes: 294, 295; for Q4, MS-DRG codes 637, 638, 639. Outpatient/non-acute inpatient CPT codes: , , , , , , , , , , , 99420, 99429, 99455, 99456, 99499, , 99315, 99316, 99318, , Acute inpatient/emergency department CPT codes: , , 99238, 99239, , , 99291, Outpatient/non-acute inpatient revenue center codes: 051x, 052x, 057x-059x, 077x, 082x-085x, 088x, 0982, 0983, 0118, 0128, 0138, 0148, 0158, 019x, 055x, 066x. Acute inpatient/emergency department revenue center codes: 010x, , 0119, , 0129, , 0139, , 0149, , 0159, 016x, 020x-022x, 072x, 080x, 0987, 045x, Event: Rates: Adjustment: Geographies: CPT codes: 83036, 86037; CPT II codes: 3046F, 3047F Overall, blacks, and non-blacks None States, HRRs, HSAs, counties

10 Measure: Diabetics receiving eye examination Last revised: 11/5/09 Description: Defined as the occurrence of an eye exam during the measurement year. This includes diabetics who had one of the following: a retinal or dilated eye exam by an eye care professional (optometrist or ophthalmologist) in the measurement year a negative retinal exam (no evidence of retinopathy: ICD-9 codes , ) by an eye care professional in the year prior to the measurement year (specialty codes: 18=ophthalmology, 41=optometry). Diabetes diagnosis: two face-to-face encounters with different dates of service in an ambulatory setting or nonacute inpatient setting or one face-to-face encounter in an acute inpatient or emergency room setting during measurement year or prior year. Time period: Population: Diabetes definition: Medicare, non-hmo, age (December 31); 20% sample, Parts A & B eligible. ICD-9 diagnosis codes: 250xx, 357.2x, 362.0x, , 648.0x: DRG codes: 294, 295; for Q4, MS-DRG codes 637, 638, 639. Outpatient/non-acute inpatient CPT codes: , , , , , , , , , , , 99420, 99429, 99455, 99456, 99499, , 99315, 99316, 99318, , Acute inpatient/emergency department CPT codes: , , 99238, 99239, , , 99291, Outpatient/non-acute inpatient revenue center codes: 051x, 052x, 057x-059x, 077x, 082x-085x, 088x, 0982, 0983, 0118, 0128, 0138, 0148, 0158, 019x, 055x, 066x. Acute inpatient/emergency department revenue center codes: 010x, , 0119, , 0129, , 0139, , 0149, , 0159, 016x, 020x-022x, 072x, 080x, 0987, 045x, Event: ICD-9 procedure codes: , 14.9, , 95.11, 95.12, CPT codes: 67028, , 67101, 67105, 67107, 67108, 67110, 67112, 67141, 67145, 67208, 67210, 67218, 67227, 67228, 92002, 92004, 92012, 92014, 92018, 92019, 92225, 92226, 92230, 92235, 92240, 92250, 92260, , , ; CPT II codes: 2022F, 2024F, 2026F, 3072F, ; HCPCS codes: S0625, S3000. Rates: Adjustment: Geographies: Overall, blacks, and non-blacks None States, HRRs, HSAs, counties

11 Measure: Diabetics receiving blood lipids test Last revised: 11/5/09 Description: Defined as the occurrence of at least one blood lipids (LDL_C) test during the year to a person with a diabetes diagnosis. Diabetes diagnosis: two face-to-face encounters with different dates of service in an ambulatory setting or nonacute inpatient setting or one face-to-face encounter in an acute inpatient or emergency room setting during measurement year or prior year. Time period: Population: Diabetes definition: Medicare, non-hmo, age (December 31); 20% sample, Parts A & B eligible. ICD-9 diagnosis codes: 250xx, 357.2x, 362.0x, , 648.0x: DRG codes: 294, 295; for Q4, MS-DRG codes 637, 638, 639. Outpatient/non-acute inpatient CPT codes: , , , , , , , , , , , 99420, 99429, 99455, 99456, 99499, , 99315, 99316, 99318, , Acute inpatient/emergency department CPT codes: , , 99238, 99239, , , 99291, Outpatient/non-acute inpatient revenue center codes: 051x, 052x, 057x-059x, 077x, 082x-085x, 088x, 0982, 0983, 0118, 0128, 0138, 0148, 0158, 019x, 055x, 066x. Acute inpatient/emergency department revenue center codes: 010x, , 0119, , 0129, , 0139, , 0149, , 0159, 016x, 020x-022x, 072x, 080x, 0987, 045x, Event: CPT codes: 80061, 83700, 83701, 83704, 83715, 83716, 83721; CPT II codes: 3048F, 3049F, 3050F Rates: Adjustment: Geographies: Overall, blacks, and non-blacks None States, HRRs, HSAs, counties

12 Measure: Mammography Last revised: 11/5/09 Description: Defined as the occurrence of any mammogram during a 24 month period for women age Age restricted to 67 to allow two years of follow-back. Time period: Population: Event: Rates: Adjustment: Geographies: Medicare women, non-hmo, age (December 31 of last year of measurement period); 20% sample, Part B eligible. Any, but only one occurrence per patient during measurement year or prior year of: CPT codes: , 76083, G0202. ICD-9 codes: 87.36, 87.37; V codes: 76.11, UB-92 revenue center code: Overall, blacks, and non-blacks None States, HRRs, HSAs, counties

13 Measure: Leg amputation Last revised: 11/5/09 Description: Defined as average rate of leg amputation per 1,000 Medicare enrollees in the measurement year. Time period: Population: Medicare, non-hmo, age (mid-year), 100% MedPAR, Part A eligible at mid-year. Event: ICD-9 procedure codes to Rates: Adjustment: Geographies: Overall, blacks, and non-blacks Age, sex, race indirect adjustment States, HRRs, HSAs, counties

14 Measure: Discharges for ambulatory care-sensitive conditions Last revised: 11/5/09 Description: Ambulatory care sensitive condition discharge rate per 1,000 Medicare enrollees. Note this uses the Dartmouth Atlas definition and may differ from other commonly used definitions. Time period: Population: Medicare, non-hmo, age (mid-year), 100% MedPAR, Part A eligible at mid-year. Event: Any of the following: Primary diagnosis codes: A01 Convulsions 780.3x A02 COPD 491xx, 492xx, 494xx, 496xx, 466.0x 466.0x only w/secondary dx 491xx, 492xx, 494xx, 496xx A03 Pneumonia 481xx, 482.2x, 482.3x, 482.9x, 483xx, 485xx, 486xx Excl. secondary dx 282.6x A04 Asthma 493xx A05 CHF 428xx, , , , 518.4x Excl. sx 36.01, 36.02, 36.05, 36.1x,37.5x, or 37.7x A06 Hypertension 401.0x, 401.9x, , , Excl. sx 36.01, 36.02, 36.05, 36.1x,37.5x, or 37.7x A07 Angina 411.1x, 411.8x, 413xx Excl. sx A08 Cellulitis 681xx, 682xx, 683xx, 686xx Excl. sx ,except if 86.0x is the first and only sx code A09 Diabetes 250.0x, 250.1x, 250.2x, 250.3x, 250.8x, 250.9x A10 Gastroent x A11 Kidney/Urinary 590xx, 599.0x, 599.9x A12 Dehydration 276.5x Rates: Adjustment: Geographies: Overall, blacks, and non-blacks Age, sex, race indirect adjustment States, HRRs, HSAs, counties

15 Section Three: Calculation of Confidence Intervals

16 Calculating Confidence Intervals for Atlas Measures Center for Health Policy Research, The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Hanover, NH, USA May 6, 2008 Summary. This document provides a review of the methods used to calculate variances (and standard errors) of indirectly standardized rates for count variables and continuous variables. The methods may not be suitable for all situations for which confidence intervals are sought, for example, proportions. However, counts and continuous variables are the most common variables currently included in the Dartmouth Atlas for Health Care. Calculating Confidence Intervals for Count Variables The indirect standardized rate (ISR) for region i is calculated as: ISR i = m O i E i, where m is the crude national rate (total number of events divided by the total population), O i is the observed count in region i and E i is the expected count in region i. The expected count in region i is calculated as E i = j n ij crude rate j, where j is the stratum (say, age, sex or race). The variance of the ISR i is then written var(isr i ) = m2 var(o Ei 2 i ). 1

17 Table 1 Example of 3 Region, 2 Age group indirect standardization; included are the population counts (n), observed events (O) and expected events (E). Region Age Population Observed Expected Sum i j n ij Events O ij Events E ij Events E i In this calculation, we assume that var(o i ) = O i (Poisson assumption) and E i is constant. The standard error is then se(isr i ) = m E i Oi The normal distribution-based 95% confidence interval is then ( ISR i 1.96m O i Example E i, ISR i m O i E i An example with 3 regions (i = 1, 2, 3) and 2 age groups (j = 1, 2) is used to illustrate the principle. The counts are shown in Table 1. The population crude rate is m = = = The crude rate for crude rate 1200 j=1 = = 0.1 and the crude rate for crude rate 400 j=2 = = 90 = Using these calculations as a basis, ISR i=1 = = 0.067, ISR 32.5 i=2 = = and ISR i=3 = = ) = The standard errors are then se(isr 1 ) = = 0.015, se(isr 2) = = and se(isr 3 ) = = The 95% confidence intervals are then calculated as the ISR i plus and minus 1.96 times the standard error. 2

18 Calculating Confidence Intervals for Continuous Variables Continuous variables include Atlas variables such as patient days or expenditures. Using the same notation as above, the variance for continuous variables is written var(isr i ) = m2 var(o Ei 2 i ). However, we write the pooled variance (across all regions) var(o i ) as regions var(o i ) = n i i (n i 1)s 2 i i (n i 1) ( (n1 1)s 2 1 = n i i (n i 1) + (n 2 1)s2 2 i (n i 1) + (n 2 1)s2 3 i (n i 1) +... = n i s 2 P where n i is the number of people in the region i, s 2 i is the within region variance and where the second term is often written as s 2 P, simplifying the the representation of the pooled (weighted average) variance across regions. Then, the standard error is written se(isr i ) = ms P E i ni, and the normal distribution-based 95% confidence interval is then ( ISR i 1.96ms P ni, ISR i ms ) P ni. Example E i Expenditures for Region 1 have variance 6,000 and sample size 1,000. E i ) Meanwhile, expenditures for Region 2 have variance 3,000 and sample size 2,000. The pooled estimate of the variance is then written s 2 P = 1,000 6,000 3, ,000 3,000 3,000 = 4, 000. Now, if we assume the population crude mean expenditures (m) are 10,000, while the observed expenditures in Region 1 (O 1 ) are 8,000 and the expected expenditures for Region 1 (E 1 ) are 10,000, the adjusted expenditures for Region 1 are 10,000 8,000 10,000 = 8, 000. The variance of expenditures for Region 1 is then calculated as 4,000m2 1,000 E 2 = 126, 491. Alternatively, the standard error is 356 and the 95% confidence interval is then (7302, 8698). 3