Alzheimer’s & Dementia 9 (2013) 472–474

Medicare Public Use Files and Alzheimer’s disease factorsin 2008 and 2010

Sergio Iv�an Prada*PROESA and Universidad Icesi, Cali, Colombia

1. Lead

A new set of files are available to researchers as freedownloads and they contain nonidentifiable claim-specificinformation for Fee-for-Service (FFS) Medicare beneficia-ries. Data on use and payments per beneficiary for PartA, B, and D are available for Alzheimer’s disorders and10 other chronic conditions, allowing for novel comparisons.

2. Background

In 2011, the Centers for Medicare & Medicaid Services(CMS), which administers the Medicare program in theUnited States, launched a data initiative called Basic StandAlone (BSA) Medicare Claims Public Use Files (PUFs).The objective was to increase access to its Medicare claimsdata through the release of deidentified data files availablefor public use. These files are available to researchers asfree downloads and contain nonidentifiable, claim-specificinformation.

Several PUFs are now available for students, analysts,and researchers. A set of these is by type of claim: Inpatient,Durable Medical Equipment (DME), Prescription DrugEvents, Hospice, Carrier, Home Health Agency (HHA),and Skilled Nursing Facility (SNF). Another set summarizesclaims by patient characteristics (Chronic Conditions), byinstitutional provider, and by drug profiles. Some are avail-able for 2 years (2008 and 2010) and some for only 1 year(2008 or 2010).

Of particular interest for readers of this journal is theChronic Conditions PUF (CC-PUF), which includes dataforMedicare beneficiaries diagnosed with “Alzheimer’s Dis-ease and Related Disorders or Senile Dementia”. I describehere this new data source, discuss its advantages and limita-tions, and demonstrate the utility of the file.

*Corresponding author. Tel.: 157.2.321.20.92; Fax: +57.2.555.14.41.

E-mail address: siprada@proesa.org.co

1552-5260/$ - see front matter � 2013 The Alzheimer’s Association. All rights r

http://dx.doi.org/10.1016/j.jalz.2013.04.509

3. CMS’ CC PUF

The CMS Chronic Conditions PUF (CC PUF) is a file inwhich each record is a profile or cell defined by selectedcharacteristics of Medicare beneficiaries. These characteris-tics are age category (in 5-year intervals), gender, indicatorsfor 11 chronic conditions, and an indicator for whether thebeneficiary holds dual-eligibility status (eligible for Medic-aid). The number of records represents the number of uniquecombinations of these characteristics observed in the Medi-care population in the reference year. For each profile, claim-related payment and utilization variables are provided in theform of averages per beneficiary.

The PUF represents 100% of the Medicare beneficiariesprovided in the 100% Beneficiary Summary File for eachreference year. The 100% Beneficiary Summary File is cre-ated annually by CMS and contains demographic, entitle-ment, and enrollment data for beneficiaries who weredocumented as being alive for some part of the referenceyear of the Beneficiary Summary File, are entitled to Medi-care benefits during the reference year, and are enrolled inMedicare Part A and/or Part B for at least 1 month in the ref-erence year. The 100% Beneficiary Summary File containsapproximately 48 million beneficiaries, all of who are repre-sented in the PUF.

The CC PUF provides utilization measures for Medicarebeneficiaries who are enrolled in FFS plans. The averagesare calculated for different types of Medicare beneficiariesby months of enrollment. Beneficiaries with 12 months ofenrollment in FFS Part A or Part B are separated from ben-eficiaries with less than 12 months of enrollment. Table 1summarizes information available in the CC PUF.

4. Advantages and limitations

These PUFs have several advantages. First, they offera multidimensional view (by all combinations of age cate-gories, gender, Medicaid eligibility, and chronic conditions)

eserved.

Table 1

Analytical Variables in Centers for Medicare & Medicaid Services (CMS) Chronic Conditions Public Use Files (PUF)

Part A Part B Part C Part D

12 months Less 12 months 12 months Less 12 months 12 months Less 12 months 12 months Less 12 months

Beneficiaries Count Count Count Count Count Count Count Count

Enrollment Months of

enrollment

Months of

enrollment

Months of

enrollment

Months of

enrollment

Medicare

payment

Total, Inpatient, SNF, Other Part A services Total, Carrier, Outpatient, Other

Part B services

Drug cost

Medicare utilizatio Inpatient admissions, SNF covered days Carrier visits, Outpatient visits Number of prescriptions

S.I. Prada / Alzheimer’s & Dementia 9 (2013) 472–474 473

of payment and utilization variables for Medicare beneficia-ries by program that was previously unavailable to analysts.Second, they represent 100% of the Medicare beneficiaries,overcoming sampling shortcomings. Third, they provide an-alytical variables separated by program and enrollment type,which are figures that were not available to the public ina PUF before.

Fourth, chronic conditions included in these PUFs aretaken directly from the CMS Chronic Condition Data Ware-house Condition Categories, which in turn, are identified us-ing peer-reviewed clinical algorithms that look for validInternational Classification of Diseases Version 9 (ICD-9)/Current Procedural Terminology Version 4 (CPT)/Health-care Common Procedure Coding System (HCPCS) codesin claims files for chronic-disease-specific reference time pe-riods. The algorithm used [1] is available elsewhere.1 Fifth,CC PUFs include payments and utilization variables for eachprofile. Neither the National Health Interview Survey(NHIS) nor the Center for Disease Control’s BehavioralRisk Factor Surveillance System (BBRFSS) includes suchinformation. Although the Medical Expenditure Panel Sur-vey (MEPS) collects information on expenditures by sourceof payment (i.e., private,Medicaid, andMedicare) on a hand-ful of medical conditions, these conditions are self-reportedand rely on accurate recollection by respondents.2

Some limitations of these PUFs are (1) they do not allowfor analyzing some types ofMedicare enrollees, such as peo-ple with disabilities or end-stage renal disease3 (2) the dual-eligibility indicator groups all Medicare beneficiaries whoare eligible for any form of Medicaid benefit in any monthin the reference year and does not allow for investigationof different types of dual-eligibilities4 (3) the data only con-tain Medicare payments and do not allow for analysis ofother sources (e.g., other insurers, out-of-pocket expenses);

1Available at http://www.ccwdata.org/cs/groups/public/documents/

document/ccw_conditioncategories.pdf (Last accessed April 10, 2013).2MEPS HC-128 2009 Medical Conditions Documentation. Retrieved

from: http://meps.ahrq.gov/mepsweb/data_stats/download_data/pufs/h128/

h128doc.pdf (Last accessed April 10, 2013).3For details on Medicare eligibility, see http://www.socialsecurity.gov/

pubs/10043.html (Last accessed April 10, 2013).4For a review of different types of Medicaid coverage of Medicare ben-

eficiaries, see https://www.cms.gov/MLNProducts/downloads/Medicare_

Beneficiaries_Dual_Eligibles_At_a_Glance.pdf. (Last accessed April 10,

2013).

and (4) because of deidentification techniques applied tothe original data, some profiles have missing values.

5. Analytic utility

To demonstrate the analytic utility of these files, I estimatethe marginal effect of the chronic condition “Alzheimer’sDisease and Related Disorders or Senile Dementia” on thoseMedicare payments and utilizationvariables in the PUF.5 Themarginal effect is defined as the ratio between beneficiarieswith such a condition and those without any condition. I re-strict the analyses to beneficiaries enrolled in Part A and Bfor the entire year who were not eligible for Medicaid.6

The rationale is as follows: (1) by excluding those thatwere not enrolled for the full year, we control for changesdue to deaths and for those just aging into the program; and(2) by excluding those eligible for Medicaid, we focus on de-terminants of cost only for Medicare beneficiaries whosecharacteristics (e.g., health, socioeconomic status) might dif-fer from dual-eligible beneficiaries. Table 2 shows thesemar-ginal effects by gender and age categories for 2008 and 2010.Notice that each figure is the ratio of average values per ben-eficiary in the same profile, not per user.

Results show that having “Alzheimer’s/Senile Dementia”as the only chronic condition increases the averageMedicarepayment for Part A by a factor of 9.1 for male enrollees in2008 and by a factor of 10 in 2010. Likewise, this factorwas 10.1 in 2008 and 11.4 in 2010 for females. By age,the highest factor is seen for those 65–69 for both sexesand years. Among the different components of Part A pay-ments, SNF and other non-inpatient payments have factorsof 37 for males and 22 for females. Regarding utilization var-iables, having “Alzheimer’s/Senile Dementia” as the onlychronic condition increases inpatient admissions by 4.6and 4.7 for males in 2008 and 2010, respectively, and 3.6for females. SNF days increased by a factor of approxi-mately 40 for males and 25 for females.

Looking at Part B, average Medicare payment increasedby a factor of 2.0 for male enrollees in 2008 and by a factorof 2.1 in 2010. This factor was 1.5 in 2008 and remained the

5The PUFs are also useful to analyze the effect of multiple chronic

conditions that we do not consider in this study.6These are not two disjoint populations. Most traditional Medicare

(Part A) beneficiaries also have Part B coverage (w90%).

Table 2

Marginal effect of Alzheimer’s disease and other dementia on selected Medicare payment and utilization variables for full-year enrollees that were not dual-

eligible in 2008 and 2010

Part A payment per beneficiary Part A utilization per beneficiary

Total Inpatient SNF Other Inpatient admissions SNF days

2008 2010 2008 2010 2008 2010 2008 2010 2008 2010 2008 2010

All male 9.1 10.0 4.6 4.9 37.6 36.4 35.2 38.1 4.6 4.7 40.8 38.9

Male

Under 65 7.3 9.0 5.7 6.5 26.6 30.1 18.8 27.3 5.1 5.8 31.9 29.6

65–69 9.7 11.6 5.7 7.3 68.0 60.0 64.1 55.8 5.2 5.9 67.8 62.9

70–74 7.5 8.7 4.4 5.1 36.8 36.7 36.7 40.5 4.1 4.6 38.6 39.8

75–79 6.7 7.3 3.6 3.8 21.9 22.8 24.4 27.8 3.8 4.0 25.5 27.1

80–84 6.7 6.9 3.6 3.7 16.1 13.5 16.5 17.7 3.8 3.6 18.5 14.8

85 and older 7.3 8.0 4.4 4.5 12.3 12.4 11.0 11.7 4.5 4.6 13.1 13.0

All female 10.1 11.4 3.6 3.6 21.8 22.4 42.8 49.7 3.6 3.6 25.2 24.9

Female

Under 65 8.3 8.6 5.4 4.9 29.0 28.8 33.1 39.1 4.0 3.8 33.8 32.2

65–69 8.8 9.7 4.8 4.6 35.0 30.4 65.7 89.8 4.0 3.8 44.3 42.8

70–74 6.6 7.6 3.2 3.4 19.9 22.5 45.1 55.5 3.0 3.3 24.5 24.5

75–79 7.1 7.5 3.0 2.9 14.1 13.8 34.5 39.9 3.2 3.0 17.4 15.7

80–84 6.8 7.3 2.8 2.9 9.8 8.8 23.0 24.4 3.0 2.9 11.2 10.1

85 and older 7.7 8.5 3.5 3.6 7.2 7.5 13.3 14.5 3.6 3.7 8.0 8.1

Part B payment per beneficiary Part B utilization per beneficiary

Total Carrier Outpatient Other Carrier visits Outpatient visits

2008 2010 2008 2010 2008 2010 2008 2010 2008 2010 2008 2010

All Male 2.0 2.1 1.8 1.8 1.9 1.9 5.5 6.2 1.7 1.7 1.9 1.9

Male

Under 65 2.6 2.5 2.4 2.4 2.7 2.2 3.4 3.1 2.0 2.0 2.3 2.2

65–69 2.3 2.4 2.1 2.0 2.3 2.3 6.3 7.1 1.9 1.9 2.1 2.2

70–74 1.9 1.9 1.7 1.7 1.8 1.9 5.2 6.0 1.7 1.7 1.9 1.8

75–79 1.7 1.7 1.5 1.5 1.7 1.6 5.3 5.8 1.6 1.6 1.7 1.7

80–84 1.6 1.6 1.3 1.3 1.6 1.5 5.2 5.5 1.4 1.4 1.6 1.5

85 and older 1.7 1.7 1.3 1.3 1.6 1.6 4.8 5.2 1.2 1.2 1.6 1.5

All Female 1.5 1.5 1.2 1.2 1.3 1.3 6.6 7.0 1.1 1.1 1.3 1.3

Female

Under 65 2.3 2.3 2.0 2.0 2.1 2.0 4.2 4.8 1.6 1.5 1.7 1.6

65–69 1.7 1.8 1.6 1.6 1.7 1.7 6.4 7.2 1.5 1.5 1.5 1.6

70–74 1.5 1.5 1.3 1.3 1.5 1.4 5.8 6.0 1.3 1.3 1.4 1.3

75–79 1.4 1.3 1.1 1.1 1.3 1.3 5.8 5.8 1.2 1.1 1.3 1.2

80–84 1.3 1.3 1.0 1.0 1.2 1.2 5.3 5.8 1.0 1.0 1.2 1.2

85 and older 1.5 1.4 1.1 1.0 1.4 1.4 4.3 4.3 0.9 0.9 1.3 1.3

S.I. Prada / Alzheimer’s & Dementia 9 (2013) 472–474474

same in 2010 for females. Among the different componentsof Part B payments, Carrier and Outpatient factors did notchange between 2008 and 2010 and were 1.8 and 1.9 formales and 1.2 and 1.3 for females, respectively. Lastly “Alz-heimer’s/Senile Dementia” is associated with 1.7 more doc-tor visits for males in 2008 and 2010 and 1.1 for females.Likewise, outpatient visits increased by a factor of approxi-mately 1.9 for males and 1.3 for females.

6. Conclusions

In this short news report, I have explained and shownthe analytic utility of one of the newly released CMS

PUFs. In particular, using 24 cells out of at least 21,000cells available in the Chronic Conditions File for eachyear it was possible to compute factors by which paymentsand utilization increased associated with “Alzheimer’s Dis-ease and Related Disorders or Senile Dementia”. Analysts,researchers, students, and practitioners may benefit fromusing these files.

Reference

[1] Taylor DH, Fillenbaum GG, Ezell ME. The accuracy of Medicare

claims data in identifying Alzheimer’s disease. J Clin Epidemiol

2002;55:929–37.