by the Committee on Geographic Variation in Health Care Spending ...

NOTE: These materials were prepared by subcontractors for consideration by the Committee on Geographic Variation in H ealth Care Spending and Promotion of High-value Care . These analyses were commissioned and overseen by the Committee. However, the findings and views expressed in the subcontractor reports do not necessarily reflect those of the NRC/IOM or the Committee. Neither the methodology nor the subcontractor reports have been subject to formal institutional review for the Interim Report. As the committee continues to review the findings from the analyses contained herein, we invite you to provide feedback on the content of these reports. Please note that any comments will be entered into the project’s public access file, and will be available for public review. Provide Feedback

Geographic Variation in Spending, Utilization and Quality: Medicare and Medicaid Beneficiaries May 2013 Thomas MaCurdy Jay Bhattacharya Daniella Perlroth Jason Shafrin Anita Au-Yeung Hani Bashour Camille Chicklis Kennan Cronen Brandy Lipton Shahin Saneinejad Elen Shrestha Sajid Zaidi

Acumen, LLC 500 Airport Blvd., Suite 365 Burlingame, CA 94010

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EXECUTIVE SUMMARY A large body of research indicates that there exists significant regional variation in health care spending, utilization, and quality. For instance, the Dartmouth Atlas found that per capita Medicare reimbursements in Miami were more than twice as high as in Minneapolis.1 Other studies have also found significant variation in expenditures for end-of-life care and in the likelihood that individuals are diagnosed with a specific disease.2 In the popular media, Atul Gawande’s article in the New Yorker magazine further advanced the notion that variation in physicians’ chosen practice patterns drives variation in Medicare costs observed even in cities close to one another.3 Gawande uses the Texan cities of McAllen and El Paso to highlight this point. By first identifying the source of this geographic variation, policymakers can potentially develop and implement initiatives to alter practice patterns in high-cost areas. This study contributes to this debate by examining geographic variation in the volume and intensity of per capita health care services and spending for both Medicare and Medicaid beneficiaries. This project was undertaken under the direction of the Institute of Medicine (IOM) and includes the analyses performed at their behest. This study does not necessarily reflect Acumen’s own analytic approach but rather was designed to follow specifications required by IOM to promote consistency across contractors. This report therefore presents a comprehensive set of results that examine myriad issues underlying regional differences in Medicare and Medicaid spending. Specifically, this report aims to answer the following research questions: 1. How much geographic variation exists in per capita volume of healthcare services? 2. Are regions with high utilization levels likely to have high utilization rates in the future? 3. Is the variation in the volume of medical services greater within or across regions? 4. Do regions that provide a high volume of medical services when treating beneficiaries for a given disease also provide a high volume of medical services when treating all other diseases? 5. What types of services are the primary drivers of regional variation in the utilization of medical services? 6. Are areas with high utilization levels more likely to have high quality care?

The Center for the Evaluative Clinical Services and Dartmouth Medical School, The Dartmouth Atlas of Health (Chicago: American Hospital Publishing, Inc., 1996). 2 Y Song et al., "Regional Variations in Diagnostic Practices," New England Journal of Medicine 2010, no. 363 (2010). 3 Atul Gawande, "The Cost Conundrum: What a Texas town can teach us about health care," New Yorker(June 2009), http://www.newyorker.com/reporting/2009/06/01/090601fa_fact_gawande. 1

Acumen, LLC

IOM Study of Geographic Variation | May 2013 i

7. Are regions with high utilization levels in Medicare likely to have high utilization levels in Medicaid? To answer these questions, this report relies on claims (outpatient rehabilitation); IP claims: last four digits of Provider Number:  2000-2299 (long term care)  4000-4499 OR third digit of "M" OR third digit of "S" (psychiatric)  3025-3099 OR third digit of “R” or “T” (rehab) PB claims: Place of Service IN (31 (skilled nursing), 32

"Berenson-Eggers Type of Service (BETOS)," Centers for Medicare & Medicaid Services, https://www.cms.gov/Medicare/Coding/HCPCSReleaseCodeSets/BETOS.html.

Medicaid Specification

 

   

All IP claims OT claims: BETOS IN ("D1G" (drugs administered through DME), "O1E" (other drugs), "O1D" (chemotherapy)) all RX claims OT claims: first digit of BETOS IN ("M" (evaluation and management), "I" (imaging), "T" (tests)) All LT claims OT claims:  Place of Service IN (31 (skilled nursing), 32 (nursing facility), 34 (hospice), 51 (inpatient psychiatric), 52 (psychiatric facility), 53 (community mental health center), 56 (psychiatric residential treatment center), 61 (inpatient rehab), 62 (outpatient rehab))

95

Acumen, LLC

Service Category

Medicare / Medicaid Claim Types

Medicare Specification

Medicaid Specification 

(nursing facility), 34 (hospice), 51 (inpatient psychiatric), 52 (psychiatric facility), 53 (community mental health center), 56 (psychiatric residential treatment center), 61 (inpatient rehab), 62 (outpatient rehab))

Procedures

OP, PB / OT

Type of Service in (7 (nursing facility), 13 (home health), 33 (rehab), 35 (hospice))



OP and PB claims: first digit of BETOS="P" (procedures)



OT claims: first digit of BETOS="P" (procedures)





OT claims: BETOS = “O1A” (ambulance) OR Revenue Center code 0450-0459, or 0981 (emergency room) OR Place-of-Service = 23 (ambulance) IP claims: Revenue Center code 0450-0459 or 0981 (emergency room)



Emergency Room / Ambulance

OP, PB / OT, IP



OP claims: BETOS = "O1A" (ambulance) OR Revenue Center code 0450-0459 or 0981 (emergency room) PB claims: BETOS = "O1A" (ambulance) OR Place of Service IN (23 (emergency room), 41 (land ambulance), 42 (air or water ambulance))

Other

All claim types



Any claim not previously categorized



Any claim not previously categorized

The Medicare analysis further divides post-acute care into categories to determine the main cause of variation. The table below presents the substratifications of the post-acute care categories. IOM Study of Geographic Variation | May 2013

Table B.2: Post-Acute Care Category Definitions Post-Acute Care Category Skilled Nursing Home Health Hospice

Other Post-Acute

Medicare Specification SNF claims PB claims: Place of Service in: 31 (skilled nursing), 32 (nursing facility), HH claims HS claims PB claims: Place of Service in: 34 (hospice), OP claims: Type of Service IN (4, 5, 6) AND Facility Type="7" (outpatient rehabilitation); IP claims with last four digits of Provider Number 4000-4499 OR third digit of "M" OR third digit of "S" (psychiatric) IP claims with last four digits of Provider Number 3025-3099 OR third digit of “R” or “T” (rehab)

96

Post-Acute Care Category

Medicare Specification IP claims with last four digits of Provider Number: 2000-2299 (long term care) PB claims: Place of Service in: 51 (inpatient psychiatric), 52 (psychiatric facility), 53 (community mental health center), 56 (psychiatric residential treatment center), 61 (inpatient rehab), 62 (outpatient rehab))

B.3

Utilization Counts Medicare Method

Utilization Count Measure

Code

Code type

Description

Acumen, LLC

Number of Inpatient Surgical Admissions

All valid DRGs

Number of Inpatient Medical Admissions

All valid DRGs

DRG

Count of observed inpatient medical admissions. No more than 1 per day.

Number of Inpatient Surgical Days

All valid DRGs

DRG

Count of inpatient surgical days

DRG

Count of inpatient medical days

CPT CPT

Office visit, E&M, new pt., minimal Office visit, E&M, new pt., minor

Number of Inpatient Medical Days Number of days with an outpatient office visit

All valid DRGs 99201 99202

DRG

Count of observed inpatient surgical admissions. No more than 1 per day.

Notes IP claims (noninterim) with admission date in episode window and an acute shortterm/CAH provider number and surgical MSDRG IP claims (noninterim) with admission date in episode window and an acute shortterm/CAH provider number and medical MSDRG Same specification as Number of Inpatient Surgical Admissions Same specification as Number of Inpatient Medical Admissions OP and PB claims. Can have only 1

Medicaid Method

Combine categories using IP claims; does not differentiate between medical and surgical admissions. Count of inpatient admissions. No more than 1 per day.

Combine categories using IP claims; does not differentiate between medical and surgical days. Count of inpatient days. OT claims. (Underreported in states with

97

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Medicare Method Utilization Count Measure

IOM Study of Geographic Variation | May 2013

Number of RX drug fills

Code

Code type

99203

CPT

99204

CPT

99205

CPT

99211

CPT

99212

CPT

99213

CPT

99214

CPT

99215

CPT

99241 99242 99243 99244 99245

CPT CPT CPT CPT CPT

Description

Notes

Office visit, E&M, new pt., low complexity Office visit, E&M, new pt., moderate complexity Office visit, E&M, new pt., high complexity Office visit, E&M, established pt., minimal Office visit, E&M, established pt., minor Office visit, E&M, established pt., low complexity Office visit, E&M, established pt., moderate complexity Office visit, E&M, established pt., high complexity E&M, Consultation, minimal E&M, Consultation, minor E&M, Consultation, low E&M, Consultation, moderate E&M, Consultation, high

outpatient office visit per day

All valid NDC claims

NDC

For each person/NDC/Day: =1 if days’ supply 30

99281 99282 99283 99284

CPT CPT CPT CPT

Emergency dept visit, minimal Emergency dept visit, minor Emergency dept visit, low Emergency dept visit, moderate

99285

CPT

Emergency dept visit, high

Number of Emergency Department Visit Days

OP, PB, or DM claims with HCPCs with BETOS in (D1G, O1E, or O1D), and all Part D claims OP claims with Revenue Center code 0450-0459 or 0981; and IP claims with Revenue Center code 0450-0459 or 0981 and restricting to Source of Admission =7. Max 1 per person per day.

Medicaid Method prevalent local code system usage)

RX claims. (Underreported in states with prevalent local code system usage)

OT claims with Revenue Center code 0450-0459 or 0981, or Place-of-Service = 23; and IP claims with Revenue Center code 0450-0459 or 0981. Max 1 per person per day.

98


Code

Code type

Description

Notes

Medicaid Method

CPT

Maximum of 1 procedure of each type on any given day. OP and PB claims.

OT claims (Underreported in states with prevalent local code system usage.)

Sentinel Services

Cardiac Stress Test

ICD-9 and CPT

Nuclear stress tests

No more than 1 test per enrollee day. IP, OP, and PB claims.

OT and IP claims (Underreported in states with prevalent local code system usage.)

Sentinel Services

Bilateral Cardiac Catheterization

ICD-9 and CPT

Bilateral cardiac catheterization

No more than 1 procedure per enrollee day. IP, OP, and PB claims.


Hip and knee replacement



IP claims for the cholecystectomy cohort; IP, PB, and OP claims for the aggregate cohort. For the cholecystectomy cohort, only check the claims on the index date.

ICD-9 and CPT. IP claims for the cholecystectomy cohort; IP and OT claims for the aggregate cohort. (Under-reported in states with prevalent local code system usage.)



Number of Imaging Encounters

Diagnostic Imaging Codes

Discretionary Services


Hip and Knee Replacement

Cholecystectomy

CPT

ICD-9 and CPT

Laparoscopic cholecystectomy as percent of all cholecystectomy, calculated for the cholecystectomy cohort and the aggregate cohort. For the cholecystectomy cohort, use only IP claims because the cohort is defined using only IP claims. For the aggregate cohort, use IP, OP, and PB claims to capture all cholecystectomies. This measure is not risk-adjusted because it is a process of care quality measure.

Acumen, LLC


Hysterectomy

CPT

Hysterectomy

99

Acumen, LLC



Specialist encounters


78

Code

Lower Back Surgery

See Outpatient Visits

Code type

Description

Notes

CPT

Lower back surgery


CPT

Same specifications as number of days with an outpatient office visit, but restrict to visits to a physician specialist78 except those to a primary care physician (01=General practice, 08=Family practice, 11=Internal medicine, 37=Pediatric medicine, and 38=Geriatric medicine) and to 65=Physical therapist.

Medicaid Method OT and IP claims (Underreported in states with prevalent local code system usage.)

Not included in analysis as Medicaid claims do not include specialty codes.

The analysis uses CMS’ definition of physician specialty code found in the Medicare claims processing manual: "Medicare Claims Processing Manual: Chapter 26 - Completing and Processing Form CMS-1500 Data Set. Section 10.8.2: Physician Specialty Codes," The Centers for Medicare & Medicaid Services, http://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c26.pdf.

100 B.4

Condition-Specific Quality Measures

Condition Acute/ Ischemic Stroke

Diabetes

Acumen, LLC

79

79

Quality Measure Discharged on Antiplatelet Therapy: Patients aged 18 and older with diagnosis of ischemic stroke or TIA who were prescribed antiplatelet therapy at discharge. Rate of Lowerextremity Amputation among Patients with Diabetes: Discharges of age 18 and older with ICD-9-CM procedure code for lower extremity amputation and diagnosis of diabetes in any field.

Type

Specification

External Source

Link to measure

Process

Programmed to align with AAN/ACR/PCPI/ NCQA Performance Measure #2 specifications

American Academy of Neurology, American College of Radiology, Physician Consortium for Performance Improvement®, National Committee for Quality Assurance. Stroke and stroke rehabilitation physician performance measurement set. Chicago (IL): American Medical Association (AMA), National Committee for Quality Assurance (NCQA); 2009 Feb. 20 p.

Measure 2 (Page 7): http://www.amaassn.org/ama1/pub/uploa d/mm/pcpi/strokeworksheets.pdf

Outcome

Programmed in accordance with AHRQ Prevention Quality Indicator (PQI) #16 specifications

AHRQ quality indicators. Guide to prevention quality indicators: hospital admission for ambulatory care sensitive conditions [version 3.1]. Rockville (MD): Agency for Healthcare Research and Quality (AHRQ); 2007 Mar 12. 59 p. (AHRQ Pub; no. 02-R0203).

http://www.qualityindica tors.ahrq.gov/Downloads /Software/SAS/V41A/Te chSpecs/PQI%2016%20 Rate%20of%20Lowerextremity%20Amputatio n.pdf

AHRQ quality indicators. Prevention quality indicators appendices [version 4.2]. Rockville (MD): Agency for Healthcare Research and Quality (AHRQ); 2010 Sep. 1 p. AHRQ quality indicators. Prevention quality indicators: technical specifications [version 4.2]. PQI #16 rate of lower-extremity amputation among patients with diabetes. Rockville (MD): Agency for Healthcare Research and Quality (AHRQ); 2010 Sep. 2 p.

At the recommendation of the team clinician, the chosen approach enforces all optional exclusions in the quality measures in order to give providers the benefit of the doubt in cases where certain services may not be appropriate for beneficiaries with certain characteristics.

101

Acumen, LLC

Condition


Pneumonia

79

Quality Measure Comprehensive diabetes care: percentage of members 18 through 75 years of age with diabetes mellitus (type 1 and type 2) who had an eye screening for diabetic retinal disease. Comprehensive diabetes care: percentage of members 18 through 75 years of age with diabetes mellitus (type 1 and type 2) who had a hemoglobin A1c (HbA1c) test during the measurement year. Bacterial Pneumonia Admission Rate: All discharges of age 18 years and older with ICD-9-CM principal diagnosis code for bacterial pneumonia.

Type

Specification

External Source

Link to measure

Process

Programmed to align with HEDIS specifications.

National Committee for Quality Assurance (NCQA). HEDIS® 2011: Healthcare Effectiveness Data and Information Set. Vol. 1, narrative. Washington (DC): National Committee for Quality Assurance (NCQA); 2010. various p.

See HEDIS measure: Comprehensive diabetes care: percentage of members 18 through 75 years of age with diabetes mellitus (type 1 and type 2) who had an eye screening for diabetic retinal disease.

Process

Programmed to align with HEDIS specifications.

National Committee for Quality Assurance (NCQA). HEDIS® 2011: Healthcare Effectiveness Data and Information Set. Vol. 1, narrative. Washington (DC): National Committee for Quality Assurance (NCQA); 2010. various pages.

See HEDIS measure: Comprehensive diabetes care: percentage of members 18 through 75 years of age with diabetes mellitus (type 1 and type 2) who had a hemoglobin A1c (HbA1c) test during the measurement year.

Outcome

Programmed to align with AHRQ PQI #11 specifications


http://www.qualityindica tors.ahrq.gov/Downloads /Software/SAS/V41A/Te chSpecs/PQI%2011%20 Bacterial%20Pneumonia %20Admission%20Rate. pdf

AHRQ quality indicators. Prevention quality indicators appendices [version 4.2]. Rockville (MD): Agency for Healthcare Research and Quality (AHRQ); 2010 Sep. 1 p. AHRQ quality indicators. Prevention quality indicators: technical specifications [version 4.2]. PQI #11 bacterial pneumonia admission rate. Rockville (MD): Agency for Healthcare Research and Quality (AHRQ); 2010 Sep. 3 p.

102

Condition Rheumatoi d Arthritis

Depression

79

Acumen, LLC

Quality Measure Rheumatoid arthritis: Percentage of members who were diagnosed with rheumatoid arthritis and who were dispensed at least one ambulatory prescription for a disease modifying anti-rheumatic drug (DMARD). Antidepressant medication management (effective acute phase treatment): Percentage of members 18 years of age and older who were diagnosed with a new episode of major depression, and treated with antidepressant medication, and who remained on an antidepressant medication for at least 84 days (12 weeks) Antidepressant medication management (effective continuation phase treatment): Percentage of

Type

Specification

Process

Programmed to align with HEDIS specifications

External Source

Link to measure


See HEDIS measure: Rheumatoid arthritis: percentage of members who were diagnosed with rheumatoid arthritis and who were dispensed at least one ambulatory prescription for a disease modifying anti-rheumatic drug (DMARD).

National Committee for Quality Assurance (NCQA). HEDIS® 2011: Healthcare Effectiveness Data and Information Set. Vol. 2, technical specifications. Washington (DC): National Committee for Quality Assurance (NCQA); 2010. various pages. Process


National Committee for Quality Assurance (NCQA). HEDIS® 2011: Healthcare Effectiveness Data and Information Set. Vol. 1, narrative. Washington (DC): National Committee for Quality Assurance (NCQA); 2010. various pages. National Committee for Quality Assurance (NCQA). HEDIS® 2011: Healthcare Effectiveness Data and Information Set. Vol. 2, technical specifications. Washington (DC): National Committee for Quality Assurance (NCQA); 2010. various pages.

Process


National Committee for Quality Assurance (NCQA). HEDIS® 2011: Healthcare Effectiveness Data and Information Set. Vol. 1, narrative. Washington (DC): National Committee for Quality Assurance (NCQA); 2010. various pages. National Committee for Quality Assurance (NCQA).

See HEDIS measure: Antidepressant medication management (effective acute phase treatment): percentage of members 18 years of age and older who were diagnosed with a new episode of major depression, and treated with antidepressant medication, and who remained on an antidepressant medication for at least 84 days (12 weeks)

See HEDIS measure: Antidepressant medication management (effective continuation phase treatment): percentage of members 18 years of age and older

103

Acumen, LLC

Condition

Congestive Heart Failure

Acute Myocardia l Infarction

79

Quality Measure members 18 years of age and older who were diagnosed with a new episode of major depression, and treated with antidepressant medication, and who remained on an antidepressant medication for at least 180 days (6 months) Congestive Heart Failure (CHF) Admission Rate


Acute myocardial infarction (AMI): Percentage of members 18 years of age and older during the measurement year who were hospitalized and discharged alive from July 1 of the year prior to the measurement year to June 30 of the measurement year with a diagnosis of AMI and who received persistent beta-blocker treatment for six

Type

Specification

External Source

Link to measure

HEDIS® 2011: Healthcare Effectiveness Data and Information Set. Vol. 2, technical specifications. Washington (DC): National Committee for Quality Assurance (NCQA); 2010. various pages.

who were diagnosed with a new episode of major depression, and treated with antidepressant medication, and who remained on an antidepressant medication for at least 180 days (6 months)

http://www.qualityindica tors.ahrq.gov/Downloads /Software/SAS/V41A/Te chSpecs/PQI%2008%20 CHF%20Admission%20 Rate.pdf See HEDIS measure: Acute myocardial infarction (AMI): percentage of members 18 years of age and older during the measurement year who were hospitalized and discharged alive from July 1 of the year prior to the measurement year to June 30 of the measurement year with a diagnosis of AMI and who received persistent beta-blocker treatment for six months after discharge

Outcome

Programmed in accordance with AHRQ PQI #8 specifications

AHRQ quality indicators. Prevention quality indicators: technical specifications [version 4.2]. PQI #8 congestive heart failure (CHF) admission rate. Rockville (MD): Agency for Healthcare Research and Quality (AHRQ); 2010 Sep. 3 p.

Process


National Committee for Quality Assurance (NCQA). HEDIS® 2011: Healthcare Effectiveness Data and Information Set. Vol. 1, narrative. Washington (DC): National Committee for Quality Assurance (NCQA); 2010. various pages. National Committee for Quality Assurance (NCQA). HEDIS® 2011: Healthcare Effectiveness Data and Information Set. Vol. 2, technical specifications. Washington (DC): National Committee for Quality Assurance (NCQA); 2010. various pages.

104

Condition

Quality Measure months after discharge

79

Type

Coronary Heart Disease

Antiplatelet Therapy: Percentage of patients aged 18 and older with a diagnosis of coronary artery disease seen within a 12 month period who were prescribed aspirin or clopidogrel Chronic Obstructive Pulmonary Disease (COPD) Admission Rate

COPD

Specification

External Source

Link to measure

Process

Programmed to align with ACC/AHA/ PCPI Chronic Stable Coronary Artery Disease Performance Measure #6 specifications

American College of Cardiology, American Heart Association, Physician Consortium for Performance Improvement®. Clinical performance measures: chronic stable coronary artery disease. Tools developed by physicians for physicians. Chicago (IL): American Medical Association (AMA); 2005. 8 p.

Measure 6 (Page 55): http://www.amaassn.org/ama1/pub/uploa d/mm/pcpi/cadminisetjun e06.pdf

Outcome

Programmed in accordance with AHRQ's PQI #5 specifications


http://www.qualityindica tors.ahrq.gov/Downloads /Software/SAS/V41A/Te chSpecs/PQI%2005%20 Chronic%20Obstructive %20Pulmonary%20Dise ase%20%28COPD%29 %20Admission%20Rate. pdf

AHRQ quality indicators. Prevention quality indicators appendices [version 4.2]. Rockville (MD): Agency for Healthcare Research and Quality (AHRQ); 2010 Sep. 1 p.

Acumen, LLC

AHRQ quality indicators. Prevention quality indicators: technical specifications [version 4.2]. PQI #5 chronic obstructive pulmonary disease (COPD) admission rate. Rockville (MD): Agency for Healthcare Research and Quality (AHRQ); 2010 Sep. 2 p.

105

Acumen, LLC

Condition


Cataract

79

Quality Measure Pharmacotherapy management of chronic obstructive pulmonary disease (COPD) exacerbation: Percentage of COPD exacerbations for members 40 years of age and older who had an acute inpatient discharge or ED encounter between January 1 to November 30 of the measurement year and who were dispensed a bronchodilator within 30 days of the event Cataracts: Complications within 30 Days Following Cataract Surgery Requiring Additional Surgical Procedures

Type

Specification

Process


External Source

Link to measure


See HEDIS measure: Pharmacotherapy management of chronic obstructive pulmonary disease (COPD) exacerbation: percentage of COPD exacerbations for members 40 years of age and older who had an acute inpatient discharge or ED encounter between January 1 to November 30 of the measurement year and who were dispensed a bronchodilator within 30 days of the event

National Committee for Quality Assurance (NCQA). HEDIS® 2011: Healthcare Effectiveness Data and Information Set. Vol. 2, technical specifications. Washington (DC): National Committee for Quality Assurance (NCQA); 2010. various pages.

Outcome

Programmed to align with AAO/PCPI/NCQ A Performance Measure #3 specifications

American Academy of Ophthalmology, Physician Consortium for Performance Improvement®, National Committee for Quality Assurance. Eye care physician performance measurement set. Chicago (IL): American Medical Association, National Committee for Quality Assurance; 2007 Oct. 36 p. [42 references]

Measure 3 (Page 17): http://www.amaassn.org/ama1/pub/uploa d/mm/pcpi/eye-care-twoworksheets.pdf

106

Condition Low Back Pain

Cholecyste ctomy

Breast Cancer

79

Quality Measure Use of imaging studies for low back pain: Percentage of members with a primary diagnosis of low back pain who did not have an imaging study (plain x-ray, MRI, CT scan) within 28 days of the diagnosis Laparoscopic Cholecystectomy Rate

Percentage of women 42 to 69 years of age who had one or more mammograms during the measurement year or the year prior to the measurement year.

Type

Specification

Process


Process

Process

Programmed to align with AHRQ Inpatient Quality Indicator (IQI) Measure #23 specifications

Programmed to align with HEDIS specifications, modifying age range as defined for measure.

External Source

Link to measure


See HEDIS measure: Use of imaging studies for low back pain: percentage of members with a primary diagnosis of low back pain who did not have an imaging study (plain x-ray, MRI, CT scan) within 28 days of the diagnosis

National Committee for Quality Assurance (NCQA). HEDIS® 2011: Healthcare Effectiveness Data and Information Set. Vol. 2, technical specifications. Washington (DC): National Committee for Quality Assurance (NCQA); 2010. various pages. AHRQ quality indicators. Guide to inpatient quality indicators: quality of care in hospitals - volume, mortality, and utilization [version 3.1]. Rockville (MD): Agency for Healthcare Research and Quality (AHRQ); 2007 Mar 12. 91 p. AHRQ quality indicators. Inpatient quality indicators: technical specifications [version 4.2]. IQI #23 laparoscopic cholecystectomy rate. Rockville (MD): Agency for Healthcare Research and Quality (AHRQ); 2010 Sep. 1 p. National Committee for Quality Assurance (NCQA). HEDIS® 2011: Healthcare Effectiveness Data and Information Set. Vol. 1, narrative. Washington (DC): National Committee for Quality Assurance (NCQA); 2010. various pages.

http://www.qualityindica tors.ahrq.gov/Downloads /Software/SAS/v41A/Te chSpecs/IQI%2023%20L aparoscopic%20Cholecy stectomy%20Rate.pdf

See HEDIS measure: Breast cancer screening: percentage of women 40 to 69 years of age who had one or more mammograms during the measurement year or the year prior to the measurement year.

Acumen, LLC

107

Acumen, LLC

Condition

79

Quality Measure Radiation therapy is administered within 1 year (365 days) of diagnosis for women 18 to 69 years of age receiving breast conserving surgery for breast cancer.

Type Process

Specification

External Source

Link to measure

Programmed to align with ASCO/NCCN measure specifications, modifying age rage as defined for measure.

American Society of Clinical Oncology (ASCO) National Comprehensive Cancer Network (NCCN)ASCO/NCCN quality measures, endorsed by NQF. ASCO/NCCN quality measures: breast and colorectal cancers. Alexandria (VA): American Society of Clinical Oncology, National Comprehensive Cancer Network, Inc.; 2007 Apr. 5 p.

Table 1 (Page 2): http://www.asco.org/AS CO/Downloads/cancer% 20Policy%20and%20Cli nical%20Affairs/NCCN/ ASCO%20NCCN%20Q uality%20Measures%20t able%20web%20posting %20with%20CoC%2005 07.pdf


108 B.5

Composite Quality Measures Quality Measure

Patient Safety Indicator Composite: Patient Safety for Selected Indicators (PSI #90)80

Inpatient Quality Indicator Composite: Mortality for Selected Conditions (IQI #91)81

Prevention Quality Indicator Composite (PQI #90)82

80

Components PSI #03 Pressure Ulcer Rate PSI #06 Iatrogenic Pneumothorax Rate PSI #07 Central Venous Catheter-Related Blood Stream Infection Rate PSI #08 Postoperative Hip Fracture Rate PSI #12 Postoperative Pulmonary Embolism or Deep Vein Thrombosis Rate PSI #13 Postoperative Sepsis Rate PSI #14 Postoperative Wound Dehiscence Rate PSI #15 Accidental Puncture or Laceration Rate IQI #15 Acute Myocardial Infarction (AMI) Mortality Rate IQI #16 Congestive Heart Failure (CHF) Mortality Rate IQI #17 Acute Stroke Mortality Rate IQI #18 Gastrointestinal Hemorrhage Mortality Rate IQI #19 Hip Fracture Mortality Rate IQI #20 Pneumonia Mortality Rate PQI #01 Diabetes Short-Term Complications Admission Rate PQI #03 Diabetes Long-Term Complications Admission Rate PQI #05 Chronic Obstructive Pulmonary Disease (COPD) or Asthma in Older Adults PQI #07 Hypertension Admission Rate PQI #08 Congestive Heart Failure (CHF) Admission Rate PQI #10 Dehydration Admission Rate PQI #11 Bacterial Pneumonia Admission Rate PQI #12 Urinary Tract Infection Admission Rate PQI #13 Angina without Procedure Admission Rate PQI #14 Uncontrolled Diabetes Admission Rate PQI #15 Asthma in Younger Adults Admission Rate PQI #16 Rate of Lower-Extremity Amputation Among Patients with Diabetes

Acumen, LLC

"Quality Indicator User Guide: Patient Safety Indicators (PSI) Composite Measures, Version 4.4," The Agency for Healthcare Research and Quality, http://qualityindicators.ahrq.gov/Downloads/Modules/PSI/V44/Composite_User_Technical_Specification_PSI%20V4.4.pdf. 81 "Quality Indicator User Guide: Inpatient Quality Indicators (IQI) Composite Measures, Version 4.4," The Agency for Healthcare Research and Quality, http://qualityindicators.ahrq.gov/Downloads/Modules/IQI/V44/Composite_User_Technical_Specification_IQI%20V4.4.pdf. 82 "Quality Indicator User Guide: Prevention Quality Indicators (PQI) Composite Measures, Version 4.4," The Agency for Healthcare Research and Quality, http://qualityindicators.ahrq.gov/Downloads/Modules/PQI/V44/Composite_User_Technical_Specification_PQI%20V4.4.pdf.

109 C.1

Composition of Risk Adjustment Clusters for Medicare Analysis Cluster Independent Variable 84


Market-Level Variables

Beneficiary-Level Variables

Acumen, LLC

Appendix C: RISK ADJUSTMENT SPECIFICATIONS

83

Year Partial Year Enrollment Age Sex Age-Sex Interaction Health Status Race Income Institutionalization Status New Enrollee Indicator Dual Enrollment Status Supplemental Medicare Insurance Hospital Competition Percent of Population Uninsured Supply of Medical Services Malpractice Environmental Risk Physician Composition Access To Care Payer Mix Medicaid Penetration Health Professional Mix Supplemental Medicare Insurance

Control

1

X X

X X X X X

2 (Baseline)

X X X X X X

3

4

5

X X X X X

X X X X X

X X X X X X X X

X X X

683

7

8

9

10

X X X X X

X X X X X X X

X X X X X X X X

X X X X X X X

85

X X X X X X X X X X X X

X X X X X X X X X X X X X X

X

X X X X X X X

Cluster 6 is not applicable to the Medicare or Medicaid analysis. The indicator variable for year of analysis is only used in the analysis of the full 2007 through 2009 data. 85 Cluster 8 does not include the income indicator because the income indicator is highly collinear with the dual enrollment status indicator. 84

X X X X

110

C.2

Composition of Risk Adjustment Clusters for Medicaid Analysis Cluster Independent Variable

Market-Level Variables

Beneficiary-Level Variables

88

Acumen, LLC

86

Year Partial Year Enrollment Age Sex Age-Sex Interaction Health Status Race Institutionalization Status New Enrollee Indicator State Indicator Hospital Competition Percent of Population Uninsured Supply of Medical Services Malpractice Environmental Risk Physician Composition Access To Care Payer Mix Medicaid Penetration Health Professional Mix

Control

1

X X

X X X X X

2 (Baseline)

X X X X X X

3 X X X X X X

X X

86

4

5 X X X X X X X X X

Cluster 4 is the same as cluster 1 for the Medicaid analysis. Cluster 6 is not applicable to the Medicare or Medicaid analysis. 88 The indicator variable for year of analysis is only used in the analysis on the full 2007 through 2009 data. 87

687

7

8

9

10

X X X X X

X X X X X X X X X

X X X X X X X X X

X X X X X X X X X X

X X X X X X X X X

X X X X X X X X X

X X X X X X X

111

Acumen, LLC

C.3

Beneficiary-Level Characteristics

Beneficiary-Level Variable

Medicare Measure

Age

EDB/EL

5-year age bands tied to 65 (e.g., 65-69), one age band for under 65, and one age band for over 90, indicating beneficiary age as of index date.

Sex Age*Sex Interaction

EDB/EL EDB/EL

Male/Female Age* Sex interaction (e.g., 65-69 and Female, 65-69 and Male, etc.)

Race and Ethnicity

EDB/EL

White, Black, Hispanic, Asian, Other (includes North American Native category), Unknown.

EDB

Low Income Subsidy (LIS). Flag as LIS if beneficiary submits any LIS copay or subsidy during the observation period. LIS information is available for Part D beneficiaries only, so any beneficiary who is counted as LIS is also enrolled in Part D.

Income


89

Data Source: Medicare/Medicaid

Health Status

CWF/(MSIS & MAX)

CMS 2008 HCC health status and enrollment indicators during look-back period of 365 days from the index date. HCCs include one originally disabled indicator and an ESRD indicator. HCC interactions do not include interactions with Medicaid status.89

New Enrollee Indicator

CWF/(MSIS & MAX)

Indicator for whether beneficiary has a full year of claims history (enrollment in A AND B) prior to the observation start date.

Medicaid Measure 5-year age bands tied to 20 (e.g., 20-24), one age band for 18-19, and one age band for over 90, indicating beneficiary age as of index date. Same as Medicare Same as Medicare White, Black, Hispanic, Asian, Other, Unknown (includes Missing category) Not included because this information is not available on Medicaid claims. CMS 2008 HCC health status indicators during look-back period of 365 days from the index date. HCC interactions do not include interactions with Medicaid status or disability status. Indicator for whether beneficiary has a full year of claims history (FFS enrolled with no benefits restriction) prior to the observation start date.

When risk-adjusting the composite quality measures for the aggregate analysis, the regression uses the HCCs from the prior calendar year instead of the HCCs from the year prior to the inpatient event to assure consistency across the components of the quality measures.

112

Beneficiary-Level Variable Institutionalization Status

Dual Eligibility Status

Partial Year Enrollment

Supplemental Medicare Insurance

Acumen, LLC

90

Data Source: Medicare/Medicaid

Medicare Measure

RAPS/LT

Indicator variable for being in long-term care for at least 90 consecutive days in the calendar year prior to the year of analysis.90

EDB

Indicator variable for enrollment in both Medicare and Medicaid at any time during the observation period.

EDB/EL

EDB

Cohort Analysis: Three sets of indicator variables for enrollment during the observation window,91 indicating if the beneficiary is enrolled in the first month, second month, third month, etc.: 1. Order of months alive and enrolled in Medicare Part A 2. Order of months alive and enrolled in Medicare Part B 3. Order of months alive and enrolled in Medicare (Part A OR B) AND Part D Aggregate Analysis: Two indicator variables for continuous enrollment from the first month of enrollment through the calendar year: 1. Continuously enrolled and alive in Medicare Part A or B 2. Continuously enrolled and alive in Medicare (Part A OR B) AND Part D Indicator for the presence of supplemental Medicare insurance. This indicator as defined in the EDB includes Medicaid enrollment. However, because this analysis includes a dual-enrollment indicator, beneficiaries enrolled in Medicaid are not counted as having supplemental insurance.

Medicaid Measure Indicator variable for being in long-term care for at least 90 cumulative days in the calendar year prior to the year of analysis. Not included because dualenrolled beneficiaries are dropped from the Medicaid analysis.

One set of indicator variables for order of months enrolled in Medicaid during the observation window. To be considered enrolled, beneficiary must be alive, FFS enrolled and have no benefits restriction.

Not included.

For beneficiaries in the cholecystectomy cohort whose observation period overlaps 2006, because 2006 is the earliest year of data available for this analysis, the institutionalization status indicator for both the Medicare and the Medicaid analysis examines the entire 2006 time period. 91 Because the observation window for the cataract cohort can vary between three and six months, the fourth through sixth indicators of the partial year enrollment variable for cataracts are zero if either the beneficiary is not enrolled in the relevant part of Medicare for that month or the observation window has ended.

C.4

Market-Level Characteristics

Market-Level Variable

Data Source

Variables

Hospital Competition

AHA

Herfindahl index (HHI) of competition based on the distribution of beds in each market Teaching hospital=1 if there is at least 1 teaching hospital in the HRR Specialty hospital=1 if there is at least 1 specialty hospital in the HRR Government-owned hospital=1 if there is at least 1 government owned hospital in the HRR

Percent of Population Uninsured

InterStudy

Supply of Medical Services

ARF

Malpractice Environment Risk

MPFS

Physician Composition

ARF

Access to Care

ARF

Payer Mix

InterStudy

Medicaid Penetration

InterStudy

Number of hospitals per 1,000

Health Professional Mix

ARF

Percent of Medicare Beneficiaries with Supplemental Insurance

EDB

Acumen, LLC

Population uninsured

Number of hospital beds per 1,000 Medicare malpractice GPCI Physicians per 1,000 Active primary care physicians per 1,000 Active specialists per 1,000 Indicator for Health Professional Shortage Areas (HPSAs), weighted by county population. Medicare analysis only: percent of Medicare population covered by managed care plans Medicaid analysis only: percent of Medicaid population covered by managed care plans = (# Medicaid beneficiaries / total population in HRR) Six variables for non-physicians per capita. These variables are not included in Harvard’s market-level file. This analysis has created these variables from ARF data. Physician’s Assistants Active Nurse Practitioners Nurse Anesthetists Active Certified Nurse Midwives Registered Nurses Licensed Practical Nurses and Licensed Vocational Nurses Medicare analysis only: Percent of beneficiaries with supplemental Medicare insurance: (Number of beneficiary-months enrolled in supplementary Medicare insurance) / (Number of beneficiary-months alive and enrolled in Medicare Part A or B but not C). Beneficiaries are counted for each month. This indicator as defined on claims includes Medicaid enrollment. However, because this analysis includes a dual-enrollment indicator, beneficiaries enrolled in Medicaid are not counted as having supplemental insurance.


113

Appendix D: SUPPLEMENTARY STATISTICS FOR AMI, CHD, DIABETES, AND STROKE COHORTS – MEDICARE The following sections provide supplementary statistics for Medicare beneficiaries in four selected cohorts. These cohorts include beneficiaries with the following conditions; acute myocardial infarction (AMI), chronic heart disease (CHD), diabetes, and stroke. To characterize the patterns of regional variation for beneficiaries in these specific cohorts, the appendix examines the following issues: (i) variation in spending across the nation; (ii) stability of medical service volume over time; (iii) variation in the volume of medical services within and across regions; (iv) key service categories driving the results, and (v) variation in the volume of medical services across cohorts. For statistics presented for each of the first five topics is limited to beneficiaries in the AMI, CHD, diabetes and stroke cohorts, but sixth topic examines the correlation in the volume of medical services by HRR across all fifteen cohorts. D.1

Variation in Medicare Spending Across the Nation Table D.1: Price-Standardized Risk-Adjusted Monthly Medicare Cost, AMI # Episodes

Avg.

Std. Dev.

1,024,431

$5,591

$4,710

Female Male

512,902 511,529

$5,591 $5,591

White

881,250

Black

Category

Min

Percentile

Max

90-10 Difference

10th

50th

90th

-$20,602

$2,138

$4,697

$9,866

$258,334

$7,728

$4,567 $4,844

-$20,602 -$16,706

$2,108 $2,168

$4,744 $4,651

$9,896 $9,835

$229,528 $258,334

$7,788 $7,667

$5,591

$4,542

-$16,706

$2,287

$4,734

$9,717

$251,103

$7,430

96,324

$5,591

$5,663

-$20,602

$1,245

$4,366

$11,152

$258,334

$9,908

Asian

12,223

$5,591

$5,850

-$12,490

$1,570

$4,274

$10,737

$132,732

$9,166

Hispanic

17,881

$5,591

$5,710

-$14,656

$1,411

$4,344

$10,900

$175,316

$9,489

Other

15,383

$5,591

$5,260

-$15,336

$1,915

$4,614

$10,019

$136,033

$8,103

1,370

$5,591

$5,202

-$12,934

$1,631

$4,689

$9,941

$81,611

$8,310

Dual

267,748

$5,591

$5,247

-$17,176

$1,456

$4,551

$10,795

$219,416

$9,339

Non-Dual

756,683

$5,591

$4,509

-$20,602

$2,465

$4,731

$9,558

$258,334

$7,093

651,584

$5,462

$3,354

-$12,772

$2,601

$4,703

$9,227

$229,395

$6,626

372,847

$6,322

$9,133

-$20,602

-$1,599

$4,609

$15,041

$258,334

$16,640

All

Unknown

Alive During Entire Episode Died During Episode

Table D.2: Price-Standardized Risk-Adjusted Average Monthly Medicare Cost, Stroke Category

114

#

Avg.

Std.

Min

Percentile

Max

90-10

Acumen, LLC

Episodes

Dev.

10th

50th

90th

Difference

All

618,106

$5,047

$3,928

-$16,287

$1,767

$4,140

$9,517

$161,689

$7,751

Female Male

359,863 258,243

$5,047 $5,047

$3,800 $4,093

-$13,370 -$16,287

$1,734 $1,810

$4,229 $4,026

$9,441 $9,628

$124,931 $161,689

$7,707 $7,818

White

506,223

$5,047

$3,716

-$12,902

$1,960

$4,177

$9,388

$161,689

$7,428

Black

83,586

$5,047

$4,817

-$16,287

$1,045

$3,923

$10,317

$124,931

$9,273

Asian

8,078

$5,047

$4,460

-$10,630

$1,521

$3,921

$9,843

$61,388

$8,322

11,023

$5,047

$4,729

-$9,605

$1,214

$4,002

$10,179

$100,794

$8,964

8,352

$5,047

$4,221

-$10,970

$1,683

$4,062

$9,556

$75,549

$7,873

844

$5,047

$4,053

-$5,024

$1,550

$4,237

$9,409

$64,278

$7,859

Dual

173,793

$5,047

$4,451

-$13,370

$1,090

$4,177

$10,067

$124,931

$8,977

Non-Dual

444,313

$5,047

$3,699

-$16,287

$2,177

$4,129

$9,295

$161,689

$7,118

422,274

$4,916

$3,263

-$12,902

$2,017

$4,087

$9,021

$146,811

$7,004

195,832

$5,908

$6,774

-$16,287

-$637

$4,796

$13,104

$161,689

$13,740

Hispanic Other Unknown

Alive During Entire Episode Died During Episode

Table D.3: Price-Standardized Risk-Adjusted Average Monthly Medicare Cost, CHD Avg.

All

18,856,261

$1,960

$2,538

-$19,048

Female Male

8,562,970 10,293,291

$1,960 $1,960

$2,536 $2,540

White

16,437,459

$1,960

Black

1,443,533

Asian

305,736

Hispanic Other Unknown Dual Non-Dual Alive During Entire Episode Died During Episode

Std. Dev.

Percentile

# Episodes

Category

Min

10th

Max

90-10 Difference

50th

90th

$240

$1,417

$4,364

$1,319,163

$4,124

-$18,784 -$19,048

$166 $311

$1,389 $1,436

$4,498 $4,253

$221,962 $1,319,163

$4,332 $3,941

$2,458

-$18,854

$295

$1,426

$4,312

$1,319,163

$4,017

$1,960

$3,237

-$19,048

-$281

$1,246

$5,040

$261,733

$5,321

$1,960

$2,493

-$16,738

$414

$1,504

$4,012

$136,316

$3,598

364,269

$1,960

$2,952

-$18,784

-$106

$1,297

$4,913

$180,687

$5,019

284,552

$1,960

$2,606

-$16,817

$263

$1,502

$4,178

$247,687

$3,914

20,712

$1,960

$2,743

-$10,503

$66

$1,353

$4,657

$82,031

$4,591

4,017,579

$1,960

$3,192

-$19,048

-$290

$1,173

$5,222

$1,319,163

$5,512

14,838,682

$1,960

$2,336

-$18,394

$441

$1,447

$4,149

$403,953

$3,708

17,146,365

$1,884

$2,129

-$16,096

$308

$1,408

$4,108

$403,953

$3,799

1,709,896

$3,428

$6,401

-$19,048

-$1,978

$2,257

$9,682

$1,319,163

$11,660

Table D.4: Price-Standardized Risk-Adjusted Average Monthly Medicare Cost, Diabetes Category

# Episodes

Acumen, LLC

Avg.

Std. Dev.

Min

Percentile 10th

50th

90th

Max


90-10 Difference

115

Avg.

All

18,533,150

$1,632

$2,260

-$16,295

Female Male

10,246,929 8,286,221

$1,632 $1,632

$2,114 $2,428

-$16,295 -$15,821

White

14,469,046

$1,632

$2,208

-$16,295

$157

Black

2,577,191

$1,632

$2,544

-$15,821

-$108

Asian

439,860

$1,632

$1,920

-$13,116

$415

Hispanic

579,711

$1,632

$2,535

-$14,727

Other

445,583

$1,632

$2,110

21,759

$1,632

5,498,487

Unknown Dual Non-Dual Alive During Entire Episode Died During Episode

116

Std. Dev.

Percentile

# Episodes

Category

Min

10th

Max

90-10 Difference

50th

90th

$121

$1,264

$3,508

$1,686,844

$3,388

$144 $89

$1,262 $1,268

$3,517 $3,497

$215,532 $1,686,844

$3,373 $3,408

$1,272

$3,481

$1,686,844

$3,324

$1,196

$3,768

$400,951

$3,876

$1,366

$2,935

$131,260

$2,520

-$71

$1,125

$3,993

$410,211

$4,064

-$13,521

$245

$1,379

$3,140

$156,666

$2,895

$2,346

-$15,655

$9

$1,175

$3,731

$73,947

$3,722

$1,632

$2,631

-$15,821

-$239

$1,022

$4,238

$171,498

$4,477

13,034,663

$1,632

$2,086

-$16,295

$320

$1,313

$3,226

$1,686,844

$2,906

17,440,041

$1,567

$2,011

-$13,590

$167

$1,259

$3,289

$1,686,844

$3,122

1,093,109

$3,419

$5,583

-$16,295

-$1,539

$2,205

$9,528

$400,951

$11,067

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D.2

Stability of Medicare Service Volume over Time

Table D.5: Pearson Correlation of HRR-Level Medicare Utilization 2007-2009 (AMI) 2007 2008 2009

2007 1.000 0.853 0.827

2008 0.853 1.000 0.868

2009 0.827 0.868 1.000

Table D.6: Spearman Correlation of HRR-Level Medicare Utilization 2007-2009 (AMI) 2007 2008 2009

2007 1.000 0.836 0.812

2008 0.836 1.000 0.863

2009 0.812 0.863 1.000

Table D.7: Pearson Correlation of HRR-Level Medicare Utilization 2007-2009 (Stroke) 2007 2008 2009

2007 1.000 0.810 0.792

2008 0.810 1.000 0.814

2009 0.792 0.814 1.000

Table D.8: Spearman Correlation of HRR-Level Medicare Utilization 2007-2009 (Stroke) 2007 2008 2009

2007 1.000 0.803 0.808

2008 0.803 1.000 0.813

2009 0.808 0.813 1.000

Table D.9: Pearson Correlation of HRR-Level Medicare Utilization 2007-2009 (CHD) 2007 2008 2009

2007 1.000 0.924 0.866

2008 0.924 1.000 0.926

2009 0.866 0.926 1.000

Table D.10: Spearman Correlation of HRR-Level Medicare Utilization 2007-2009 (CHD) 2007 2008 2009

2007 1.000 0.901 0.836

2008 0.901 1.000 0.908

2009 0.836 0.908 1.000

Table D.11: Pearson Correlation of HRR-Level Medicare Utilization 2007-2009 (Diabetes) 2007 2008 2009

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2007 1.000 0.971 0.952

2008 0.971 1.000 0.957

2009 0.952 0.957 1.000

IOM Study of Geographic Variation | May 2013 117

Table D.12: Spearman Correlation of HRR-Level Medicare Utilization 2007-2009 (Diabetes) 2007 2008 2009

D.3

2007 1.000 0.947 0.926

2008 0.947 1.000 0.929

2009 0.926 0.929 1.000

Variation in Volume of Medicare Services Within and Across Regions Table D.13: Medicare Service Utilization Within and Across Regions, AMI Unadjusted Average of HRR Standard Deviations Weighted Average of HRR Standard Deviations Standard Deviation of HRR Means Average of HRR 90-10 Differences Weighted Average of HRR 90-10 Differences 90-10 Difference of HRR Means

$5,583 $5,864 $870 $9,582 $10,201 $2,182

PriceStandardized $5,517 $5,741 $663 $9,532 $10,045 $1,618

PriceStandardized Risk-Adjusted $4,478 $4,644 $424 $7,413 $7,726 $1,050

Table D.14: Medicare Service Utilization Within and Across Regions, Stroke Unadjusted Average of HRR Standard Deviations Weighted Average of HRR Standard Deviations Standard Deviation of HRR Means Average of HRR 90-10 Differences Weighted Average of HRR 90-10 Differences 90-10 Difference of HRR Means

$4,513 $4,760 $681 $9,166 $9,620 $1,593

PriceStandardized $4,498 $4,692 $595 $9,190 $9,542 $1,498


Table D.15: Medicare Service Utilization Within and Across Regions, CHD Unadjusted Average of HRR Standard Deviations Weighted Average of HRR Standard Deviations Standard Deviation of HRR Means Average of HRR 90-10 Differences Weighted Average of HRR 90-10 Differences 90-10 Difference of HRR Means

118

$2,862 $3,008 $232 $4,597 $4,825 $552

PriceStandardized $2,847 $2,953 $213 $4,609 $4,775 $485

PriceStandardized Risk-Adjusted $2,441 $2,512 $137 $4,018 $4,127 $352

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Table D.16: Medicare Service Utilization Within and Across Regions, Diabetes PriceStandardized

Unadjusted Average of HRR Standard Deviations Weighted Average of HRR Standard Deviations Standard Deviation of HRR Means Average of HRR 90-10 Differences Weighted Average of HRR 90-10 Differences 90-10 Difference of HRR Means

D.4

$2,515 $2,686 $248 $3,902 $4,109 $552

$2,506 $2,647 $244 $3,921 $4,084 $531

PriceStandardized Risk-Adjusted $2,090 $2,201 $153 $3,278 $3,386 $348

Service Categories Driving Medicare Results

Post-Acute Care

Procedures

ER/Ambulance

Other

0.15 0.02 0.05 0.13 0.04 0.16 0.05

Diagnostic

.

Prescription Drugs

Remaining Costs Acute Care Prescription Drugs Diagnostic Post-Acute Care Procedures ER/Ambulance Other

Acute Care

Remaining Costs

Table D.17: AMI Medicare Service Category Utilization, Pearson Correlation (2007)

0.15 1.00 0.00 0.02 0.13 0.00 0.13 0.03

0.02 0.00 1.00 0.24 -0.04 0.29 0.08 0.08

0.05 0.02 0.24 1.00 -0.05 0.30 0.20 0.13

0.13 0.13 -0.04 -0.05 1.00 0.00 0.07 0.03

0.04 0.00 0.29 0.30 0.00 1.00 0.07 0.09

0.16 0.13 0.08 0.20 0.07 0.07 1.00 0.07

0.05 0.03 0.08 0.13 0.03 0.09 0.07 1.00

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Post-Acute Care

Procedures

ER/Ambulance

Other

0.19 0.01 0.05 0.17 0.07 0.22 0.11

Diagnostic

.

Prescription Drugs


Acute Care

Remaining Costs

Table D.18: Stroke Medicare Service Category Utilization, Pearson Correlation (2007)

0.19 1.00 0.00 0.03 0.17 0.00 0.18 0.05

0.01 0.00 1.00 0.21 -0.04 0.24 0.07 0.07

0.05 0.03 0.21 1.00 -0.04 0.30 0.16 0.10

0.17 0.17 -0.04 -0.04 1.00 0.05 0.12 0.10

0.07 0.00 0.24 0.30 0.05 1.00 0.08 0.09

0.22 0.18 0.07 0.16 0.12 0.08 1.00 0.07

0.11 0.05 0.07 0.10 0.10 0.09 0.07 1.00


Post-Acute Care

Procedures

ER/Ambulance

Other

0.24 0.05 0.12 0.22 0.06 0.26 0.08

Diagnostic

.

Prescription Drugs


Acute Care

Remaining Costs

Table D.19: CHD Service Category Medicare Utilization, Pearson Correlation (2007)

0.24 1.00 0.02 0.07 0.22 0.01 0.23 0.04

0.05 0.02 1.00 0.20 -0.02 0.17 0.03 0.06

0.12 0.07 0.20 1.00 -0.04 0.36 0.10 0.10

0.22 0.22 -0.02 -0.04 1.00 0.00 0.15 0.04

0.06 0.01 0.17 0.36 0.00 1.00 0.04 0.10

0.26 0.23 0.03 0.10 0.15 0.04 1.00 0.04

0.08 0.04 0.06 0.10 0.04 0.10 0.04 1.00

120

Post-Acute Care

Procedures

ER/Ambulance

Other

0.32 0.05 0.18 0.30 0.09 0.26 0.11

Diagnostic

.

Prescription Drugs


Acute Care

Remaining Costs

Table D.20: Diabetes Medicare Service Category Utilization, Pearson Correlation (2007)

0.32 1.00 0.02 0.11 0.32 0.02 0.23 0.06

0.05 0.02 1.00 0.17 -0.01 0.14 0.02 0.06

0.18 0.11 0.17 1.00 0.01 0.35 0.09 0.12

0.30 0.32 -0.01 0.01 1.00 0.01 0.18 0.06

0.09 0.02 0.14 0.35 0.01 1.00 0.05 0.09

0.26 0.23 0.02 0.09 0.18 0.05 1.00 0.04

0.11 0.06 0.06 0.12 0.06 0.09 0.04 1.00

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121 D.5

Variation in Volume of Medicare Services Across Cohorts

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Table D.21: Pearson Correlation of Medicare Beneficiary Utilization Across Cohorts Acute

Acute

Chronic


Cancer

Chronic

Cancer

Agg

AMI

Cat

Chol

Pneu

Stroke

Arthr

CHD

CHF

COPD

Depr

Diab

LBP

Breast

Lung

Prost

Aggregate

1.000

0.712

0.534

0.588

0.733

0.803

0.831

0.910

0.920

0.937

0.920

0.957

0.957

0.587

0.551

0.501

AMI

0.712

1.000

0.339

0.633

0.843

0.780

0.582

0.742

0.833

0.770

0.684

0.741

0.739

0.551

0.679

0.545

Cataract

0.534

0.339

1.000

0.353

0.331

0.345

0.461

0.536

0.483

0.525

0.430

0.556

0.477

0.311

0.339

0.230

CHOL

0.588

0.633

0.353

1.000

0.625

0.577

0.501

0.589

0.624

0.618

0.527

0.584

0.593

0.406

0.488

0.409

Pneumonia

0.733

0.843

0.331

0.625

1.000

0.833

0.600

0.722

0.847

0.803

0.756

0.760

0.741

0.530

0.674

0.548

Stroke

0.803

0.780

0.345

0.577

0.833

1.000

0.670

0.777

0.868

0.830

0.815

0.804

0.804

0.501

0.588

0.524

Arthritis

0.831

0.582

0.461

0.501

0.600

0.670

1.000

0.810

0.766

0.830

0.807

0.812

0.846

0.475

0.433

0.373

CHD

0.910

0.742

0.536

0.589

0.722

0.777

0.810

1.000

0.918

0.943

0.848

0.912

0.907

0.516

0.537

0.427

CHF

0.920

0.833

0.483

0.624

0.847

0.868

0.766

0.918

1.000

0.947

0.888

0.915

0.907

0.583

0.622

0.502

COPD

0.937

0.770

0.525

0.618

0.803

0.830

0.830

0.943

0.947

1.000

0.921

0.939

0.935

0.560

0.595

0.467

Depression

0.920

0.684

0.430

0.527

0.756

0.815

0.807

0.848

0.888

0.921

1.000

0.905

0.916

0.527

0.496

0.454

Diabetes

0.957

0.741

0.556

0.584

0.760

0.804

0.812

0.912

0.915

0.939

0.905

1.000

0.933

0.537

0.535

0.478

LBP

0.957

0.739

0.477

0.593

0.741

0.804

0.846

0.907

0.907

0.935

0.916

0.933

1.000

0.574

0.556

0.485

Breast

0.587

0.551

0.311

0.406

0.530

0.501

0.475

0.516

0.583

0.560

0.527

0.537

0.574

1.000

0.608

0.524

Lung

0.551

0.679

0.339

0.488

0.674

0.588

0.433

0.537

0.622

0.595

0.496

0.535

0.556

0.608

1.000

0.519

Prostate

0.501

0.545

0.230

0.409

0.548

0.524

0.373

0.427

0.502

0.467

0.454

0.478

0.485

0.524

0.519

1.000

122

D.6

Variation in Medicare Quality of Care across Cohorts

Regions that perform well on one quality metric for Medicare beneficiaries do not necessarily perform well on another quality metric. Table D.22 displays the correlation between the composite quality measures, and Table D.23 displays the correlation between quality of care as measured by each condition-specific quality metric.92 The correlations between the composite quality measures ranges from -0.02 (for the PQI and PSI measures) to 0.24 (for the PSI and IQI measures). Mechanically, the potentially avoidable complications and iatrogenic events measured by the composite PSI may result in an inpatient mortality that is captured by the IQI, which may cause the positive correlation between quality of care for the PSI and IQI measures. The correlations between the condition-specific measures, shown in Table D.23, range from -0.38 (for the diabetes retinal screening measure and the cholecystectomy measure) to 0.90 (for the depression acute phase treatment measure and the depression chronic phase treatment measure). If one treats each condition-specific measure-to-measure correlation as a single observation, the average correlation between an HRR’s quality score on one measure and its quality score on any other measure is 0.07. Intuitively, having high-quality providers for one condition in a region does not necessarily suggest that the quality of care for another condition is also above average. For example, while the Lake Charles, LA, HRR is the highest-performing HRR for the cataract measure, it is in the worst-performing 10th percentile for the cholecystectomy measure; cataract surgery and cholecystectomies are performed by very different types of physicians. Table D.22: Pearson Correlation between Composite Quality Measures for Medicare Beneficiaries PSI

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92

IQI

PSI

1.00

IQI

0.24

1.00

PQI

-0.02

0.18

PQI

1.00

For some quality measures, a lower score indicates better quality. The correlations in both tables have been renormalized for interpretability so that a positive correlation always means that higher costs are associated with a higher quality of care. In addition, both tables shows Pearson correlations, and the Spearman rank correlations show similar results.

123 Table D.23: Pearson Correlation between Condition-Specific Quality Measures for Medicare Beneficiaries

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AMI Arthritis BC Radiation BC Screening Cataract CHD CHF Chol. COPD Adm. COPD Bronch Depr. Acute Depr. Chronic Diab. Amput. Diab. Hemo. Diab. Retinal LBP Pneumonia Stroke

BC Rad

BC Screen

1.00 0.23 -0.02 0.27 0.25 -0.01 0.00 -0.18 -0.12 0.21 0.25 -0.24 0.10 0.23 0.01

1.00 0.08 0.03 0.10 -0.01 -0.13 -0.11 0.13 0.11 0.16 0.05 0.20 0.25 0.04

-0.31 0.11

-0.07 0.04

AMI

Arth.

1.00 0.63 0.14 -0.04 0.19 0.17 -0.14 -0.12 -0.25 -0.02 0.13 0.20 -0.17 0.11 0.25 0.03 -0.36 0.10

COPD Adm.

COPD Bronch.

Depr. Acute

Depr. Chron.

Diab. Amp.

Diab. Hemo.

Diab. Ret.

1.00 0.09 -0.24 -0.18 -0.23 -0.06 -0.18 -0.38 -0.08

1.00 0.25 0.00 0.02 0.36 -0.06 -0.09 0.31

1.00 0.04 0.08 0.35 0.18 0.32 0.36

1.00 0.90 0.19 0.29 0.39 0.19

1.00 0.21 0.28 0.41 0.21

1.00 0.16 0.13 0.28

1.00 0.40 -0.10

1.00 0.19

0.11 -0.04

0.60 0.02

0.37 0.09

-0.04 0.02

-0.04 0.01

0.42 -0.02

0.16 0.17

-0.09 0.12

Cat.

CHD

CHF

Chol.

1.00 0.08 0.11 -0.07 -0.08 -0.09 -0.08 0.03 0.00 0.05 0.18 0.06 -0.05

1.00 0.03 -0.18 -0.10 -0.28 -0.18 0.12 0.09 -0.30 -0.01 -0.02 -0.19

1.00 -0.11 -0.05 -0.13 -0.01 0.13 0.17 0.05 0.30 0.14 -0.14

1.00 0.10 0.67 0.21 0.20 0.19 0.29 0.00 0.01 0.39

-0.02 0.05

-0.27 0.04

-0.08 0.28

0.47 0.01

LBP

Pneu.

Str.

1.00 -0.18 -0.08

1.00 0.03

1.00


D.7

Relationship between Medicare Utilization and Quality of Care

Regions that utilize a high level of services do not necessarily provide a higher quality of care. Table D.24 shows the correlation between HRR-level quality indices and pricestandardized, risk adjusted costs for each quality measure. In Table D.24, positive correlations, which are highlighted in red, indicate that higher spending on patients in that cohort is associated with a higher quality of care for that measure.93 The average of the correlations is -0.16. The strongest positive correlation with utilization exists for the composite IQI measure (0.24), and the strongest negative correlation with utilization exists for the COPD bronchodilators quality measure (-0.48). These results must be interpreted with caution and not as evidence that increased spending causes higher or lower quality outcomes for two reasons. First, beneficiaries who are included in a disease cohort are sicker than the general population by default, and the risk adjustment methodology for the quality measures that are risk adjusted may not adequately capture these differences in health status. Second, mechanical relationships between the quality measures and utilization may cause the correlations to be artificially strong. For example, the outcome in the COPD admissions measure is an inpatient admission. As the rate of admissions increases in a region, indicating a lower quality of COPD care, spending in the region will also increase because admissions are high-cost. Thus, this relationship may induce a negative correlation between spending and the quality of care provided.

93

For some quality measures, a lower score indicates better quality. The correlations in Table D.24 have been renormalized for interpretability so that a positive correlation always means that higher costs are associated with a higher quality of care. In addition, while Table D.24 presents Pearson correlations, the Spearman rank correlations show similar results.

124

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Table D.24: Pearson Correlation of Medicare Quality and Utilization Quality Measure

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Correlation with Utilization

AMI - Beta Blockers

-0.186

Arthritis - DMARD

0.085

Breast Cancer - Radiation

0.005

Breast Cancer - Screening

0.036

Cataract - Complications

-0.061

CHD - Antiplatelets

-0.012

CHF - Admissions Cholecystectomy Laparoscopy Rate

-0.349

COPD - Admissions

-0.324

COPD - Bronchodilators

-0.483

Depression - 12 Weeks

-0.287

Depression - 6 Months

-0.340

Diabetes - Amputation

-0.081

Diabetes - Hemoglobin

-0.203

Diabetes - Retinal Screening

-0.363

LBP - Imaging

-0.401

Pneumonia - Admissions

-0.005

Stroke - Antiplatelets

-0.061

Aggregate - PSI

-0.094

Aggregate - IQI

0.240

Aggregate - PQI

-0.481

-0.078


Appendix E: SUPPLEMENTARY STATISTICS FOR AMI, CHD, DIABETES, AND STROKE COHORTS – MEDICAID The following sections provide supplementary statistics for Medicaid beneficiaries in four selected cohorts. These cohorts include beneficiaries with the following conditions; acute myocardial infarction (AMI), chronic heart disease (CHD), diabetes, and stroke. To characterize the patterns of regional variation for beneficiaries in these specific cohorts, the appendix examines the following issues: (i) variation in spending across the nation, (ii) stability of medical service volume over time, (iii) variation in the volume of medical services within and across regions, (iv) key service categories driving the results, and (v) variation in the volume of medical services across cohorts. The statistics presented for each of the first five topics is limited to beneficiaries in the AMI, CHD, diabetes and stroke cohorts, but the sixth topic examines the correlation in the volume of medical services by HRR across all fifteen cohorts. E.1

Variation in Medicaid Spending Across the Nation Table E.1: Price-Standardized Risk-Adjusted Average Medicaid Cost, AMI

Beneficiary Criteria

# Episodes 34,003 16,696 17,307 17,924 8,215 710 2,611 801 3,742

All Female Male White Black Asian Hispanic Other Unknown

Avg. $5,344 $5,346 $5,342 $5,344 $5,345 $5,343 $5,345 $5,296 $5,354

Percentile

Std. Dev.

Min

$19,537 $18,736 $20,281 $18,643 $20,850 $19,422 $19,496 $15,023 $21,558

-$19,930 -$19,391 -$19,930 -$19,930 -$16,856 -$14,298 -$12,797 -$12,736 -$17,809

10th

50th

90th

$1,107 $1,013 $1,199 $1,533 $532 $755 $865 $1,365 $740

$4,276 $4,278 $4,272 $4,449 $3,942 $4,106 $4,336 $4,349 $3,867

$10,121 $10,189 $10,052 $9,603 $11,068 $10,262 $9,947 $10,351 $11,038

Max $1,238,740 $521,726 $1,238,740 $1,238,740 $521,726 $133,087 $143,875 $82,871 $399,187

90-10 Difference $9,014 $9,177 $8,853 $8,070 $10,535 $9,507 $9,082 $8,986 $10,298

Table E.2: Price-Standardized Risk-Adjusted Monthly Medicaid Cost, Stroke Beneficiary Criteria All Female Male White Black Asian Hispanic Other Unknown

126

# Episodes 19,104 10,507 8,597 7,398 7,174 463 1,593 417 2,059

Avg. $4,737 $4,742 $4,732 $4,733 $4,740 $4,758 $4,734 $4,697 $4,750

Percentile

Std. Dev.

Min

$15,701 $15,377 $16,089 $14,116 $17,959 $14,327 $12,137 $14,379 $15,687

-$12,412 -$12,412 -$10,870 -$10,831 -$12,412 -$8,505 -$6,810 -$8,718 -$7,180

10th

50th

$1,042 $1,136 $939 $1,277 $701 $1,114 $1,462 $1,365 $1,259

$3,581 $3,622 $3,522 $3,693 $3,355 $3,787 $3,865 $3,570 $3,520

90th $9,431 $9,344 $9,549 $9,284 $9,772 $9,197 $9,146 $9,051 $9,497

Max $186,205 $129,356 $186,205 $186,205 $136,926 $80,140 $64,586 $47,605 $155,951

90-10 Difference $8,389 $8,208 $8,610 $8,007 $9,071 $8,083 $7,684 $7,686 $8,238

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Table E.3: Price-Standardized Risk-Adjusted Monthly Medicaid Cost, CHD Beneficiary Criteria

508,374 262,211 246,163 270,318 109,348 12,770 48,651 11,721 55,566

All Female Male White Black Asian Hispanic Other Unknown

Percentile

# Episodes

Avg.

Std. Dev.

$2,873 $2,873 $2,873 $2,873 $2,873 $2,873 $2,873 $2,873 $2,873

$12,236 $11,194 $13,256 $11,898 $13,701 $10,771 $10,481 $11,937 $12,604

Min -$18,541 -$18,541 -$16,788 -$16,215 -$18,541 -$15,438 -$13,927 -$13,361 -$17,564

10th

50th

$386 $484 $284 $498 -$55 $1,030 $683 $698 $372

$2,163 $2,217 $2,102 $2,219 $1,932 $2,309 $2,319 $2,148 $2,035

90th $5,796 $5,694 $5,920 $5,684 $6,465 $4,835 $5,291 $5,337 $5,960

Max

90-10 Difference

$1,245,901 $527,315 $1,245,901 $1,245,901 $527,315 $217,268 $177,360 $235,920 $404,610

$5,409 $5,210 $5,635 $5,186 $6,520 $3,805 $4,608 $4,639 $5,587

Table E.4: Price-Standardized Risk-Adjusted Average Monthly Medicaid Cost, Diabetes Beneficiary Criteria All Female Male White Black Asian Hispanic Other Unknown

E.2

# Episodes

Avg.

Std. Dev.

1,308,102 841,639 466,463 564,030 318,423 33,597 177,464 42,290 172,298

$2,008 $2,008 $2,008 $2,008 $2,008 $2,008 $2,008 $2,008 $2,008

$8,674 $7,901 $9,916 $8,613 $9,712 $7,001 $6,912 $8,215 $8,870

Percentile Min -$18,723 -$15,966 -$18,723 -$15,966 -$18,723 -$14,177 -$12,644 -$12,329 -$15,167

10th $398 $500 $207 $391 $179 $822 $710 $635 $427

50th $1,485 $1,520 $1,414 $1,462 $1,378 $1,638 $1,632 $1,550 $1,459

90th $4,011 $3,884 $4,277 $4,094 $4,338 $3,323 $3,491 $3,603 $3,962

Max $337,820 $153,783 $337,820 $153,783 $337,820 $118,246 $133,620 $239,230 $276,551

90-10 Difference $3,614 $3,385 $4,070 $3,703 $4,159 $2,501 $2,781 $2,968 $3,536

Stability of Medicaid Service Volume over Time

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Table E.5: Pearson Correlation of HRR-Level Medicaid Utilization 2007-2009 (AMI) 2007 2008 2009

2007 1.000 0.780 0.656

2008 0.780 1.000 0.639

2009 0.656 0.639 1.000

Table E.6: Spearman Correlation of HRR-Level Medicaid Utilization 2007-2009 (AMI) 2007 2008 2009

2007 1.000 0.739 0.656

2008 0.739 1.000 0.645

2009 0.656 0.645 1.000

Table E.7: Pearson Correlation of HRR-Level Medicaid Utilization 2007-2009 (Stroke) 2007 2008 2009

2007 1.000 0.537 0.532

2008 0.537 1.000 0.644

2009 0.532 0.644 1.000

Table E.8: Spearman Correlation of HRR-Level Medicaid Utilization 2007-2009 (Stroke) 2007 2008 2009

2007 1.000 0.489 0.398

2008 0.489 1.000 0.505

2009 0.398 0.505 1.000

Table E.9: Pearson Correlation of HRR-Level Medicaid Utilization 2007-2009 (CHD) 2007 2008 2009

2007 1.000 0.796 0.708

2008 0.796 1.000 0.767

2009 0.708 0.767 1.000

Table E.10: Spearman Correlation of HRR-Level Medicaid Utilization 2007-2009 (CHD) 2007 2008 2009

2007 1.000 0.842 0.710

2008 0.842 1.000 0.733

2009 0.710 0.733 1.000

Table E.11: Pearson Correlation of HRR-Level Medicaid Utilization 2007-2009 (Diabetes) 2007 2008 2009

128

2007 1.000 0.884 0.735

2008 0.884 1.000 0.752

2009 0.735 0.752 1.000

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Table E.12: Spearman Correlation of HRR-Level Medicaid Utilization 2007-2009 (Diabetes) 2007 2008 2009

E.3

2007 1.000 0.843 0.668

2008 0.843 1.000 0.743

2009 0.668 0.743 1.000

Variation in Volume of Medicaid Services Within and Across Regions

Table E.13: AMI Dispersion of Medicaid Service Utilization Within and Across Regions Unadjusted Average of HRR Standard Deviations Weighted Average of HRR Standard Deviations Standard Deviation of HRR Means Average of HRR 90-10 Differences Weighted Average of HRR 90-10 Differences 90-10 Difference of HRR Means

$16,609 $18,618 $2,207 $10,127 $10,123 $5,153

PriceStandardized $16,642 $18,547 $2,183 $10,161 $10,031 $5,150

PriceStandardized Risk-Adjusted $15,254 $16,973 $1,632 $9,324 $9,012 $4,137

Table E.14: Stroke Dispersion of Medicaid Service Utilization Within and Across Regions Unadjusted Average of HRR Standard Deviations Weighted Average of HRR Standard Deviations Standard Deviation of HRR Means Average of HRR 90-10 Differences Weighted Average of HRR 90-10 Differences 90-10 Difference of HRR Means

$14,194 $15,573 $1,804 $8,771 $9,030 $4,359


PriceStandardized Risk-Adjusted $13,097 $14,228 $1,377 $8,263 $8,277 $3,204

Table E.15: CHD Dispersion of Medicaid Service Utilization Within and Across Regions Unadjusted Average of HRR Standard Deviations Weighted Average of HRR Standard Deviations Standard Deviation of HRR Means Average of HRR 90-10 Differences Weighted Average of HRR 90-10 Differences 90-10 Difference of HRR Means

$12,078 $12,284 $1,211 $6,623 $6,270 $3,003



Table E.16: Diabetes Dispersion of Medicaid Service Utilization Within and Across Regions Unadjusted Average of HRR Standard Deviations

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$8,763

PriceStandardized $8,832

PriceStandardized Risk-Adjusted $7,783


PriceStandardized

Unadjusted Weighted Average of HRR Standard Deviations Standard Deviation of HRR Means Average of HRR 90-10 Differences Weighted Average of HRR 90-10 Differences 90-10 Difference of HRR Means

E.4

$9,378 $896 $4,787 $4,678 $2,069

$9,298 $894 $4,836 $4,645 $1,976

PriceStandardized Risk-Adjusted $8,089 $613 $3,879 $3,602 $1,319

Service Categories Driving Medicaid Results

Diagnostic

Post-Acute Care

Procedures

ER/Ambulance

Other

. -0.08 0.04 0.40 0.05 0.31 -0.12 0.01

Prescription Drugs


Acute Care

Remaining Costs

Table E.17: AMI Medicaid Service Category Utilization, Pearson Correlation (2007)

1.00 -0.01 0.27 0.03 0.25 -0.15 -0.01

1.00 0.08 0.08 0.12 0.04 0.12

1.00 0.03 0.38 0.27 0.03

1.00 0.03 0.01 -0.01

1.00 0.11 0.07

1.00 0.01

1.00

130

Diagnostic

Post-Acute Care

Procedures

ER/Ambulance

Other

. -0.04 0.06 0.42 0.08 0.20 -0.08 0.01

Prescription Drugs


Acute Care

Remaining Costs

Table E.18: Stroke Medicaid Service Category Utilization, Pearson Correlation (2007)

1.00 0.00 0.30 0.05 0.18 -0.13 0.00

1.00 0.09 0.11 0.10 0.03 0.14

1.00 0.06 0.32 0.25 0.03

1.00 0.00 0.06 -0.03

1.00 0.04 0.06

1.00 0.01

1.00

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Acute Care

Prescription Drugs

Diagnostic

Post-Acute Care

Procedures

ER/Ambulance

Other


Remaining Costs

Table E.19: CHD Medicaid Service Category Utilization, Pearson Correlation (2007)

0.02 0.05 0.36 0.04 0.28 -0.02 0.03

1.00 0.00 0.23 0.03 0.22 -0.06 0.01

1.00 0.11 0.05 0.12 0.02 0.13

1.00 0.01 0.36 0.28 0.06

1.00 0.01 0.03 0.00

1.00 0.12 0.07

1.00 0.01

1.00

.

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Acute Care

Prescription Drugs

Diagnostic

Post-Acute Care

Procedures

ER/Ambulance

Other


Remaining Costs

Table E.20: Diabetes Medicaid Service Category Utilization, Pearson Correlation (2007)

0.11 0.09 0.39 0.06 0.21 0.12 0.06

1.00 0.02 0.27 0.04 0.13 0.06 0.01

1.00 0.12 0.05 0.12 0.04 0.12

1.00 0.02 0.30 0.35 0.06

1.00 0.02 0.04 0.00

1.00 0.12 0.06

1.00 0.03

1.00

.


132

E.5

Variation in Volume of Medicaid Services Across Cohorts Table E.21: Pearson Correlation of Medicaid Beneficiary Utilization Across Cohorts Agg

AMI

Cat

Chol

Agg

1.00

AMI

0.502

1.00

Cat

0.586

0.567

1.00

Chol

0.459

0.508

0.548

1.00

Pneu

Stroke

Arthr

CHD

CHF

COPD

Depr

Diab

LBP

Breast

Lung

Pneu

0.640

0.672

0.660

0.648

1.00

Stroke

0.515

0.568

0.508

0.454

0.571

1.00

Arthr

0.639

0.533

0.628

0.579

0.566

0.582

1.00

CHD

0.651

0.693

0.733

0.689

0.726

0.607

0.818

1.00

CHF

0.706

0.668

0.694

0.631

0.718

0.649

0.795

0.922

1.00

COPD

0.689

0.639

0.717

0.679

0.732

0.571

0.736

0.854

0.857

1.00

Depr

0.774

0.583

0.734

0.607

0.711

0.552

0.799

0.869

0.837

0.816

1.00

Diab

0.794

0.576

0.741

0.624

0.692

0.611

0.829

0.831

0.837

0.842

0.925

1.00

LBP

0.770

0.598

0.744

0.649

0.725

0.561

0.779

0.848

0.821

0.834

0.937

0.931

1.00

Breast

0.235

0.279

0.389

0.361

0.173

0.295

0.448

0.406

0.331

0.333

0.411

0.439

0.464

1.00

Lung

0.351

0.472

0.346

0.213

0.395

0.427

0.339

0.430

0.454

0.430

0.318

0.339

0.364

0.294

1.00

Pros

0.473

0.380

0.567

0.443

0.495

0.461

0.568

0.584

0.542

0.604

0.601

0.561

0.658

0.212

0.259

E.6

Pros

1.00

Variation in Medicaid Quality of Care Across Cohorts

Regions that provide high-quality care for one treatment for Medicaid beneficiaries do not necessarily provide high-quality care for another treatment. Table E.22 presents the correlation between the composite quality measures.94 Correlations for the aggregate measures are also weak and range from -0.198 (for the PSI and PQI measures) to 0.041 (for the PSI and IQI measures ,

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94

For some quality measures, a lower score indicates better quality. The correlations in both tables have been renormalized for interpretability so that a positive correlation always means that higher costs are associated with a higher quality of care. In addition, both tables show Pearson correlations, and the Spearman rank correlations show similar results.

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suggesting there is little relationship between a region’s overall quality of care for one metric and the region’s quality of care for another metric for Medicaid beneficiaries. Table E.23 displays the correlation between each condition-specific quality metric. In Table E.23, results are not shown for the breast cancer radiation, breast cancer screening, or stroke quality measures because too few HRRs had a sufficient number of events in the denominator of the measure to be reported. The correlations between the condition-specific measures range from -0.334 (for the COPD admissions and diabetes retinal screening measures) to 0.744 (for the two depression measures). If each measure-to-measure correlation is treated as a single observation, the average correlation between an HRR’s quality score on one measure and its quality score on any other measure for Medicaid beneficiaries is 0.06. Intuitively, because different types of providers treat different conditions, having providers that perform high-quality care for one condition in a region does not necessarily imply that the region also has providers that perform above-average for another condition. Table E.22: Pearson Correlation between Composite Quality Measures for Medicaid Beneficiaries PSI

IQI

PSI

1.00

IQI

0.041

1.00

PQI

-0.198

-0.131

PQI

1.00


134

Table E.23: Pearson Correlation between Condition-Specific Quality Measures for Medicaid Beneficiaries AMI

Arth.

BC Rad

BC Screen

Cat.

CHD

CHF

Chol.

COPD Adm.

COPD Bronch.

Depr. Acute

Depr. Chron.

Diab. Amp.

Diab. Hemo.

Diab. Ret.

LBP

AMI Arth.

0.413

BC Rad BC Screen Cat.

0.077

0.154

CHD

-0.072

0.109

0.040

CHF

0.359

-0.095

0.015

-0.018

Chol. COPD Adm. COPD Bronch. Depr. Acute Depr. Chron. Diab. Amp. Diab. Hemo. Diab. Ret.

-0.253

0.001

-0.106

-0.109

0.108

0.319

0.039

0.024

-0.052

0.072

0.168

0.706

0.208

-0.011

0.099

0.230

0.042

0.264

0.277

0.293

0.188

0.065

-0.050

0.027

0.069

0.128

0.361

0.238

0.196

0.072

-0.067

-0.008

-0.070

0.076

0.744

0.495

0.151

-0.111

0.000

0.252

0.117

0.012

0.348

-0.171

-0.090

-0.103

-0.016

0.187

-0.102

0.108

-0.160

-0.170

-0.182

-0.032

0.049

-0.093

-0.268

-0.053

0.236

0.015

0.182

-0.114

-0.334

-0.145

-0.057

-0.013

-0.115

0.727

LBP

0.120

-0.020

-0.108

0.045

-0.032

0.048

-0.029

-0.025

-0.016

0.076

0.011

-0.156

-0.238

Pneu.

-0.047

-0.146

-0.095

-0.015

0.556

0.163

-0.016

0.064

-0.150

-0.133

0.240

0.199

0.228

Str.

0.116

Pneu.

Str

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E.7

Relationship between Medicaid Utilization and Quality of Care

Regions with high utilization do not necessarily provide a higher quality of care for Medicaid beneficiaries. Table E. 24 shows the correlation between HRR-level quality indices and price-standardized, risk adjusted costs for each quality measure. No results are shown for the breast cancer radiation, breast cancer screening, or stroke quality measures because too few HRRs had a sufficient number of events in the denominator of the measure to be reported. In Table E.24, positive correlations, which are highlighted in red, indicate that higher spending on patients in that cohort is associated with a higher quality of care for that measure.95 The average of the correlations is weakly negative, at -0.031. The strongest positive correlation with utilization exists for the composite PSI measure (0.24), and the strongest negative correlation with utilization exists for the diabetes retinal screening measure (-0.267) These results must be interpreted with caution and not as evidence that increased spending causes higher or lower quality outcomes for two reasons. First, beneficiaries who are included in a disease cohort are sicker than the general population by default, and the risk adjustment methodology for the quality measures that are risk adjusted may not adequately capture these differences in health status. Second, some mechanical relationships between the quality measures and utilization may cause the correlations to be artificially strong. For example, the outcome in the CHF admissions measure is an inpatient admission. As the rate of admissions increases in a region, indicating a lower quality of CHF care, spending in the region will also increase because admissions are high-cost. Thus, this relationship may induce a negative correlation between spending and the quality of care provided.

95

For some quality measures, a lower score indicates better quality. The correlations in Table E.24 have been renormalized for interpretability so that a positive correlation always means that higher costs are associated with a higher quality of care. In addition, while Table E.24 presents Pearson correlations, the Spearman rank correlations show similar results.

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Table E.24: Pearson Correlation Medicaid Quality and Utilization Quality Measure

Correlation with Utilization

AMI - Beta Blockers

0.014

Arthritis - DMARD

-0.147

Breast Cancer - Radiation Breast Cancer - Screening Cataract - Complications

-0.134

CHD - Antiplatelets

0.006

CHF - Admissions

-0.209

Cholecystectomy - Laparoscopy Rate

-0.161

COPD - Admissions

0.170

COPD - Bronchodilators

0.017

Depression - 12 Weeks

-0.062

Depression - 6 Months

0.213

Diabetes - Amputation

-0.024

Diabetes - Hemoglobin

-0.217

Diabetes - Retinal Screening

-0.267

LBP - Imaging

-0.011

Lung Cancer - NONE Pneumonia - Admissions

-0.060

Prostate Cancer - NONE Stroke - Antiplatelets

136

Aggregate - PSI

0.235

Aggregate - IQI

0.091

Aggregate - PQI

-0.019

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Appendix F: GEOGRAPHIC VARIATION IN SPENDING FOR MEDICARE ADVANTAGE BENEFICIARIES Whereas the body of this report examines only Medicare fee-for-services (FFS), this appendix extends the analysis to investigate regional variation in spending for MA beneficiaries.96 Specifically, this appendix addresses the following research questions: 1. How much variation is there in per capita spending in Medicare Advantage across the nation? 2. Are regions with high Medicare Advantage premiums likely to have high Medicare Advantage premiums in subsequent years? 3. Do beneficiaries in regions with more Medicare Advantage plan competition have lower Medicare Advantage premiums? 4. Are regions with high Medicare Advantage spending levels also likely to have high spending levels in Medicare fee-for-service? The remainder of this appendix proceeds as follows. First, Section F.1 briefly describes CMS payment policy for Medicare Advantage beneficiaries. Section F.2 describes the methodology used to answer the five research questions posed above, including the data sources, cohort definitions, outcome variables, and risk adjustment specifications. Finally, Section F.3 directly evaluates each research question. F.1

Medicare Advantage Payment Policy Overview

The Medicare Advantage program (also known as Part C), originally named the Medicare+Choice (M+C) program, allows private insurers to contract with Medicare to provide Medicare-covered Part A and B services to beneficiaries. CMS’s goal for the MA program is to allow market competition to incentivize insurers to provide high-quality care at a lower cost than traditional Medicare FFS for Medicare beneficiaries.97 MA plans often include prescription drug coverage, but beneficiaries that choose plans that do not cover prescription drugs can enroll separately in Medicare prescription drug plans (PDP). Beneficiaries typically choose their MA plan based on the services covered and the premiums (if any) they require beneficiaries to pay for those services. To finance these services, Medicare Advantage Organizations (MAOs) receive a fixed monthly payment per beneficiary, adjusted for beneficiary health status. 96

This analysis examines all Part C beneficiaries, which include those enrolled in certain private health plans, known as cost plans, which are not technically MA plans. For simplicity, from this point forward, this report includes cost plans when referring to Medicare Advantage unless otherwise noted. 97 Centers for Medicare & Medicaid Services, "Medicare Managed Care Manual, Chapter 1: Introduction," http://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/mc86c01.pdf.

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The following two sections provide a brief overview of the Medicare Advantage program. Section F.1.1 describes overall MA enrollment and five different MA plan types. Section F.1.2 discusses the steps CMS uses to determine Medicare and beneficiary payments. F.1.1 Medicare Advantage Enrollment and Spending The MA option has been growing in popularity in recent years. Whereas in 2001 only 15 percent of Medicare beneficiaries were enrolled in MA, in 2011 25 percent of beneficiaries chose an MA plan. CMS spending on MA plans is projected to be $115 billion in 2012 and account for 21 percent of total Medicare spending.98 Although Congress established MA with the aim of providing services to Medicare beneficiaries at a reduced cost than FFS, payments to MA plans in 2012 exceed what CMS would have paid for those beneficiaries in traditional Medicare by 14 percent.99 There are five main types of health plans available to Medicare beneficiaries, including local coordinated care, private fee-for-service, regional preferred provider organization, medical savings account, and cost plans. First, local coordinated care plans (CCPs) include local health maintenance organizations (HMOs) and preferred provider organizations (PPOs). Local CCPs contract with a network of providers and are required to offer at least one plan that includes Part D drug coverage in their service area. CCPs also generally require a primary care gatekeeper to refer beneficiaries for certain services. Second, private fee-for-service plans (PFFS) are not required to establish networks of providers or offer prescription drug coverage. Third, regional PPOs are similar to local PPOs but provide coverage for an entire geographic region that is defined by CMS.100 Fourth, medical savings account plans (MSAs) offer a high-deductible plan with an MSA that beneficiaries can use to cover cost-sharing or non-covered services. Fifth, cost plans are compensated based on calculated reasonable costs for the Medicare-covered services they provide for each beneficiary instead of a fixed rate per beneficiary. Cost plans are not technically MA plans as Congress authorized their creation under a different section of the Social Security Act. 101Unlike traditional FFS, beneficiaries in cost plans are overseen by a network of providers, though CMS does pay FFS rates when beneficiaries in cost plans receive services outside of their network. In 2007, at the start of this study’s analysis period, 70 percent of MA 98

"Medicare: Medicare Advantage Fact Sheet," The Henry J. Kaiser Family Foundation, http://www.kff.org/medicare/upload/2052-15.pdf. 99 "The Medicare Advantage Program: Status Report," MedPAC Report to the Congress: Medicare Payment Policy, http://www.medpac.gov/chapters/Mar12_Ch12.pdf. 100 CMS sets benchmarks for regional PPOs at the regional level differently than for county-based plans. Regional benchmarks are a blend of a plan-bid component, based on the weighted average of the bids for regional plans in that region, and a statutory component, consisting of the weighted average of the county capitation rates in that region. 101 "Medicare Managed Care Manual, Chapter 1: Section 1876 Cost Plans," Centers for Medicare & Medicaid Services, http://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/mc86c01.pdf.

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beneficiaries were enrolled in a local HMO, while 5.8 percent were enrolled in another type of local CCP. In addition, 19.4 percent were enrolled in a PFFS plan, and 4.8 percent were enrolled in any other type of plan, including MSAs, regional PPOs, and cost plans.102 Figure F.1 presents MA plan enrollment by type in 2007. Figure F.1: MA Plan Enrollment by Type, 2007

F.1.2 Payments to Medicare Advantage Plans The total payments an MA plan receives for each beneficiary is determined using the following five steps: 1. CMS sets a benchmark for each county; 2. The MAO places a bid for the plan’s expected monthly costs per beneficiary; 3. The plan’s bid is compared to the local county benchmark, and the lower amount is the set as the plan’s base rate; 4. CMS pays the plan the base rate for each enrollee, adjusted for the plan’s beneficiary case mix and including a rebate if the bid is below the benchmark; 5. Enrollees may also pay a monthly premium to the plan. MA payments are based first on the capitated rate, or benchmark, CMS sets each year for MA plans in a given county to cover a minimum set of services per beneficiary. The benchmark represents the maximum amount that CMS will pay any MA plan to provide this core set of services. Benchmarks are historically based on the estimated average Medicare FFS costs in that

102

Mark Merlis, "Medicare Advantage Payment Policy," National Health Policy Forum (2007).

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county.103 A county’s benchmark is updated each year by the greater of a two percent increase or the expected national growth in Medicare spending. CMS is required to rebase the benchmarks using current FFS costs at least every three years.104 For beneficiaries with end stage renal disease (ESRD), MA plans are paid separate state-level capitated rates set outside the bidding process that are much higher than non-ESRD capitated rates to account for the higher expected health expenditures of beneficiaries with ESRD. Second, for each plan it offers, the MAO places a bid that represents the expected costs for the plan to cover the core set of services for an average beneficiary, including administrative fees. The plan’s bid does not take into account the expected enrollee case mix. CMS may negotiate bid amounts with most plans. Third, the plan’s bid is compared to the local benchmark. The benchmark represents CMS’ maximum monthly payment per beneficiary. Thus, if the bid is less than the benchmark, the base rate is set at the bid; if the bid is greater than or equal to the benchmark, the base rate is set at the benchmark. Fourth, to calculate the payment to the plan, the base rate is adjusted for the plan’s expected beneficiary case mix using the CMS-HCC model.105 The CMS-HCC model is estimated using FFS claims for beneficiaries in Original Medicare to predict costs based on demographic and health factors. Because MA beneficiaries tend to be healthier than beneficiaries in Original Medicare, the aggregate payments to MA plans after accounting for beneficiary health status would be lower than if MA beneficiaries represented the average set of beneficiaries on which the CMS-HCC model was developed. Thus, CMS also multiplies all base rates by a single budget neutrality adjustment factor to prevent a decrease in payments to MA plans due to lower risk scores.106 If the plan’s bid is less than the benchmark, CMS pays the plans the bid and a rebate for part of the difference between the benchmark and bid after adjusting for health status. CMS retains 25 percent of the difference, and the plan uses the remaining 75 percent to cover additional benefits or reduce premiums or cost sharing paid by beneficiaries.

103

Some benchmarks in rural areas were initially set higher than FFS costs to increase plan availability. "The Medicare Advantage Program," MedPAC Report to the Congress: Medicare Payment Policy, http://www.medpac.gov/chapters/Mar09_Ch03.pdf. 104 The rebased rates are calculated using a rolling five-year average of FFS costs. "Medicare Managed Care Manual, Chapter 8: Determination of Annual Capitation Rates," Centers for Medicare & Medicaid Services, http://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/mc86c08.pdf. 105 "Medicare Advantage Rates & Statistics: Risk Adjustment," Centers for Medicare & Medicaid Services, https://www.cms.gov/Medicare/Health-Plans/MedicareAdvtgSpecRateStats/Risk_adjustment.html. 106 CMS began to phase out the budget neutrality adjustment in 2007, and it was completely phased out by 2011. "Medicare Managed Care Manual, Chapter 8: Budget Neutral (BN) Risk Adjustment," Centers for Medicare & Medicaid Services, http://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/mc86c08.pdf.

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Finally, enrollees may pay a premium to the plan. Enrollee basic premiums for plans that bid below the benchmark are always zero. These plans, however, may offer additional services, sometimes at an increased premium for the beneficiary. If the plan bid is greater than or equal to the benchmark, the plan will require beneficiaries to pay a premium to make up the difference between the plan’s expected costs per beneficiary and what CMS will pay the plan. F.2

Methodology for Measuring Regional Variation in MA Spending

The MA analysis measures geographic variation in spending using an approach similar to the FFS analysis, but the scope of the analysis is limited by the fact that claims-level utilization data is not available for MA beneficiaries. Whereas individual-level claims are available for all services received by FFS enrollees, only monthly plan payments are available for most MA enrollees. Because CMS only began collecting encounter data from MA plans in April 2012 and this study is limited to the 2007-2009 time period, this analysis can only observe regional variation in MA spending based on total premiums paid to MA plans.107 Beneficiary MA premiums can vary due to a number of factors such as input costs, beneficiary health status, plan competition, and other factors. This analysis controls for variation due to input costs by price standardizing spending and controls for beneficiary health status by risk adjusting spending. Thus, the remaining spending variation is primarily due to differences in health plan competition and other unmeasured factors. The remainder of this section details the methodology used by this analysis to measure regional variation in spending. Section F.2.1 describes the data sources used in this study, and Section F.2.2 defines which beneficiaries are included in the analysis and explains how this study creates condition-specific beneficiary cohorts. Section F.2.3 specifies how this study calculates health care expenditures for MA beneficiaries. Finally, Section F.2.4 defines the risk adjustment econometric specifications. Following the precedent set for the Medicare FFS and Medicaid analyses, this study defines a region as a Hospital Referral Region (HRR). F.2.1 Data Sources This analysis uses the universe of MA and FFS data from 2007 through 2009 to study geographic variation in health care expenditures. Table F.1 presents the data sources that create the relevant analytic files. The analysis utilizes enrollment data for Medicare Part C to determine demographic information, enrollment dates, and third party buy-in information. To determine monthly premiums for each MA beneficiary, this analysis uses the Part C monthly payment files which include payments by CMS for each beneficiary, including rebates, and the beneficiary’s premium paid to the plan, if any. In addition, beneficiaries in some cost plans can receive their 107

"CMS Manual System: Pub 100-20 One-Time Notification," Centers for Medicare & Medicaid Services, http://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/downloads/R978OTN.pdf.

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services through Original Medicare. Payment for these services is not included in the base rate paid to the cost plan but is separately reported in the Medicare FFS claims files. To measure these costs, this report uses all Medicare FFS claims for these beneficiaries. Finally, this report measures MA beneficiary prescription drug costs using data from the Medicare Prescription Drug Event (PDE) files. The PDE file includes beneficiaries enrolled in either a stand-alone Part D plan (PDP) or a Medicare Advantage Part D (MA-PD) plan integrated into their own MA Part C plan. Unlike the monthly MA premium data in the monthly membership files, the PDE data do measure beneficiary utilization of specific pharmaceuticals. Table F.1: MA Data Sources Data Source

Years

Medicare Parts A and B Claims

2007 2009

Medicare Part D Claims

2007 2009

Medicare Part A, B, and C Enrollment Data

2007 2009

Data Files Common Working Files (CWF) for: Home Health (HH), Physician (PB), Inpatient (IP), Skilled Nursing Facility (SNF), Outpatient (OP), Hospice (HS), and Durable Medical Equipment (DME) claims Prescription Drug Event (PDE) Enrollment Database (EDB) Common Medicare Environment (CME) Enterprise Cross-Reference (ECR) Files MARx files: Full Enrollment Files, Monthly Membership Files, Risk Scores

Medicare Part C and D Enrollment Data

2007 2009

Risk Adjustment Processing System (RAPS) HPMS Files: Beneficiary Cost, Formulary, and Pharmacy files for Part D

F.2.2 Beneficiary Cohort Definitions This report analyzes regional variation in costs for MA beneficiaries as a whole as well as for specific MA beneficiaries with four conditions. Because MA data includes only monthly capitation claims that represent the total costs paid for MA beneficiaries, this study does not define condition cohorts using ICD-9 diagnoses codes, as is done in the FFS analysis. Instead, the analysis defines the cohorts using CMS’ HCC health status indicators, which are available on a yearly basis for Part C enrollees. CMS calculates the HCCs, however, based on the diagnosis codes that MA plans submit to CMS each year. Table F.2 presents a mapping of ICD-9 diagnosis codes to the HCC categories for the four condition cohorts examined in this analysis.108

108

In the FFS analysis, beneficiaries with a chronic condition are automatically enrolled in that chronic cohort in the next year of the analysis period. Because health data for MA beneficiaries is only available yearly, however, MA beneficiaries are only included in a chronic cohort if they have the relevant HCC for that year. The chronic cohorts for the MA analysis include COPD, depression, and diabetes.

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Table F.2: MA Condition Cohort Definitions Condition

2008 HCC Number(s)

ICD-9 Diagnosis Codes

Chronic Obstructive Pulmonary Disease

108

491.0, 491.1, 491.20, 491.21, 491.22, 491.8, 491.9, 492.0, 492.8, 493.20, 493.21, 493.22, 496, 518.1, 518.2

55

296.00, 296.01, 296.02, 296.03, 296.04, 296.05, 296.06, 296.10, 296.11, 296.12, 296.13, 296.14, 296.15, 296.16, 296.20, 296.21, 296.22, 296.23, 296.24, 296.25, 296.26, 296.30, 296.31, 296.32, 296.33, 296.34, 296.35, 296.36, 296.40, 296.41, 296.42, 296.43, 296.44, 296.45,296.46, 296.50, 296.51, 296.52, 296.53, 296.54, 296.55, 296.56, 296.60, 296.61, 296.62, 296.63, 296.64, 296.65, 296.66, 296.7, 296.80, 296.81, 296.82, 296.89, 296.90, 296.99, 297.0, 297.1, 297.2, 297.3, 297.8, 297.9, E9500, E9501, E9502, E9503, E9504, E9505, E9506, E9507, E9508, E9509, E9510, E9511, E9518, E9520, E9521, E9528, E9529, E9530, E9531, E9538, E9539, E954, E9550, E9551, E9552, E9553, E9554, E9555, E9556, E9557, E9559, E956, E9570, E9571, E9572, E9579, E9580, E9581, E9582, E9583, E9584, E9585, E9586, E9587, E9588, E9589, E959

Diabetes

15, 16, 17, 18, 19

250.40, 250.41, 250.42, 250.43, 250.70, 250.71, 250.72, 250.73, 250.60, 250.61, 250.62, 250.63, 250.80, 250.81, 250.82, 250.83, 250.10, 250.11, 250.12, 250.13, 250.20, 250.21, 250.22, 250.23, 250.30, 250.31, 250.32, 250.33, 250.50, 250.51, 250.52, 250.53, 250.90, 250.91, 250.92, 250.93, 250.00, 250.01, 250.02, 250.03, V5867

Stroke

96

433.01, 433.11, 433.21, 433.31, 433.81, 433.91, 434.01, 434.11, 434.91, 436

Depression

For both the aggregate and four condition-specific cohorts, this analysis applies three exclusion restrictions to ensure that the estimated spending figures capture most (if not all) of a beneficiary’s healthcare spending. The MA approach broadly uses the same set of exclusion criteria as the FFS analysis, although some of the institutional features of the MA data sources require unique restrictions. Table F.3 presents the number of beneficiaries lost to each exclusion restriction for the full 2007 through 2009 analysis. Because these exclusions need not be applied in any order, some beneficiaries will be excluded based on more than one restriction. As a result, the total percent of beneficiaries excluded is not necessarily equal to the sum of the beneficiaries lost to each restriction.The analysis excludes beneficiaries whose enrollment data show that Medicare was the secondary payer for their claims because Medicare is not paying the full cost of these beneficiaries’ healthcare (column B in Table F.3). Beneficiaries who have Medicare as the secondary payer are typically the working aged or working disabled. The analysis also excludes beneficiaries with any negative net monthly CMS payment amount on their MA claims because negative net payment amounts typically appear due to data errors from date mismatches or double adjustments applied by CMS (column C). Finally, the analysis excludes beneficiaries if their enrollment information cannot be matched to an entry in the EDB. In the aggregate cohort, these restrictions remove 5.2 percent of Part C beneficiaries.

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Table F.3: MA Beneficiary Exclusions

A

B

C

D

E

Total Number of Beneficiaries

Medicare is not Primary Payer

Negative Monthly Payment

Not Found in EDB

Total Beneficiaries Lost

32,758,423

5.15%

0.10%