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2011 AHRQ Annual Conference

Maryland’s Approach to Racial and Ethnic Minority Health Data

Analysis and Reporting

Dr. David A. Mann

September 21, 2011

Office of Minority Health and Health DisparitiesMaryland Department of Health and Mental Hygiene

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Uses of Data for Disparities Elimination

• Identify, Locate and Quantify Disparities

• Understand Causes of Disparities and Plan Interventions

• Track Progress Towards Elimination

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Causal Chain for Health Outcomes

Social Determinants of Health

Level 1

Risk Factor PrevalenceLevel 2

Disease Frequency

Morbidity and Mortality

Level 3

Level 4

Health Care Access and Quality

Case-SpecificEvent Rates

Genetics:At each step, individual or group genetic patterns can influence the susceptibility to moving from one level to the next.

Example: Food desert + no safe place for exercise (level 1) >>Obesity (level 2) >> Diabetes (level 3) >>Diabetes-related: blindness, ESRD, amputations, death (level 4)

Public Health

(4 levels of illness)

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Data Sources for Health Outcomes

Social Determinants of Health

Level 1

Risk Factor PrevalenceLevel 2

Disease Frequency

Morbidity and Mortality

Level 3

Level 4

(4 levels of illness)

Non health data sources:Poverty rate, unemployment rateHS graduation rate, crime rate, etc.

BRFSS data, other local surveys, registries, “claims-coded prevalence”*

BRFSS data, other local surveys, registries, “claims-coded prevalence”*

Vital Statistics data, CDC Wonder, BRFSS, registries, “claims-coded prevalence”*

*“Claims-coded prevalence”: prevalence estimate using the count with relevant codes from administrative data as numerator; and one of three denominators: Utilizers, enrollees, or an entire population.

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Health Outcomes >> Utilization

Social Determinants of Health

Level 1

Risk Factor PrevalenceLevel 2

Disease Frequency

Morbidity and Mortality

Level 3

Level 4

(4 levels of illness)

Health Care Utilization Data*:Disparities in Utilization Rates More may be better: Joint replacement, cardiac revascularization, etc. More is worse: diabetic amputationsDisparities in Costs: Frequency Disparity in Cost Severity Disparity in Cost

Case-SpecificEvent Rates

*Utilization data may be provider-based (hospital discharge or ER data), or may be payer-based (insurance data). In the future it may be medical record based (EMR + HIE). Data accuracy and unique ID may vary by source.

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What Maryland Has Done

• (L4) Mortality: Vital Statistics Reports and CDC Wonder• (L3) Disease Frequency

– Incidence: Cancer Registry, HIV/AIDS registry, US Renal Data System (ESRD incidence)

– Prevalence: BRFSS (prevalence of doctor diagnosis only)

• (L2) Risk Factor Prevalence– Behavioral factors from BRFSS: smoking, obesity, physical

activity. Smoking also from state tobacco survey.– Screening factors from BRFSS: mammography, colonoscopy

• (L1) Social Determinants of Health– County level social risk profiles.

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What Maryland Has Done (2)

• Cost of disparities analysis in discharge data– Hospital discharge data analysis of Black-White hospitalization

disparities

• Cost of disparities analysis in Medicare data– Analysis of ACSC admissions in Medicare recipients age 65+– Removes problem of out of state admissions

• Examples of this work, which illustrate various themes and lessons, follow.

– Issues of age-adjustment are central to most analyses– Pros and cons of rate ratios vs. rate differences are important

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Mortality Data byRace and County (L4)

0

200

400

600

800

1000

1200

1400

Black or African American White

Age-Adjusted All-Cause Mortality (rate per 100,000) by Black or White Race and by Jurisdiction, Maryland 2004-2006 Pooled

Age-adjusted death rates for Blacks could not be calculated for Garrett CountySource: CDC Wonder Mortality Data 2004-2006

Somerset has a smaller disparity than Montgomery …

But Somerset has much worse Black mortality than Montgomery, and the 2nd worst White mortality

Lesson: The disparity metric displayed alonecan be misleading !!!

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Cause-Specific MortalityData by Race and County (L4)

Lesson: For small counties (Iike Somerset) or small racial or ethnic groups, pooling multiple years of data can allow metric estimation even for less common outcomes (like diabetes compared to heart and cancer)

Age-Adjusted Mortality Rates (per 100,000), Selected Causes of Death forBlacks or African Americans and Whites, Somerset County, Maryland 2002-2006

65.9

966.4

342.4230.8

25.1

258.0342.5

965.2

0

200

400

600

800

1000

1200

All Cause Heart Cancer Diabetes

Black or African American White

Source: CDC Wonder online Database, Compressed Mortality Files 2002-2006

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Rate Ratio vs. Rate DifferenceBlack vs. White Mortality Disparity, 14 Leading Causes of Death, Maryland 2008

Rate Rate StatewideRatio Difference Cause of Age-adjusted

Disparity Disparity Death DifferenceRank Rank Rank* Disease Black White Ratio per 100,000

All Causes 919.5 736.4 1.25 183.1

6 1 1 Heart Disease 240.1 188 1.28 52.1

7 2 2 Cancer 212.8 175 1.22 37.8

8 8 3 Stroke 45.1 38.3 1.18 6.8

4 Chronic lung Disease 21.4 40 0.54 -18.6

5 Accidents 24.8 26.4 0.94 -1.6

3 4 6 Diabetes 37.2 17.6 2.11 19.6

9 9 7 Alzheimer's Disease 19.2 18.6 1.03 0.6

8 Flu&Pneumonia 16.8 18.3 0.92 -1.5

5 6 9 Septicemia 27.7 14.8 1.87 12.9

4 7 10 Kidney diseases 21.8 11.1 1.96 10.7

2 5 11 Homicide 21.7 3.7 5.86 18.0

12 Suicide 4.4 10.5 0.42 -6.1

1 3 13 HIV/AIDS 21.7 1.4 15.50 20.3

14 Chronic Liver Disease 6.3 7.2 0.88 -0.9

Mortality per 100,000Age-adjusted

(Yellow highlight indicates Black or African American death rate higher than the White death rate)Source: Maryland Vital Statistics Annual Report 2008

LargestDisparityBy RateDifference:Heart,Cancer

LargestDisparityBy RateRatio:HIV/AIDS,Homicide

Lesson:“Worst”DisparityDepends on Which Metric is Used

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Ratio vs. Difference: Implicationsfor Trends and Evaluation

(Age-adjusted Rate per 100,000)

All Cause Mortality 2020 All Cause Mortality 2030 Change % Change

Black 200 90 -110 -55%

White 100 30 -70 -70%

Difference 100 60 -40 -40%

Ratio 2.0 3.0 1.0 50%

Hypothetical Results of a Minority Health Program: Success or Not?

Lesson: Rate ratio disparity metrics, considered in isolation, can underestimate the success of minority health programs.This is crucial to understand if trends in such metrics are used forfunding decisions.

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US Renal Data System Datafor ESRD Incidence (L3)

Lesson: Fine age stratification for age-adjustment, plus long multi-year pool can make the data robust for estimation in smaller groups.

Incidence of All-Cause ESRD by Age and Race, Maryland 1991- 2001 Pooled

(DHMH Analysis of US Renal Data System data)

0

100

200

300

400

500

0-24 25-34 35-44 45-54 55-64 65-74 75+

Age group

ne

w c

as

es

pe

r 1

00

,00

0

White

Black

Asian

American Indian

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BRFSS Data forRisk Factor Prevalence (L2)

Lesson: Coarse age stratification for age-adjustment, plus multi-year pooling can make the data robust for estimation in smaller groups.

Source: Maryland BRFSS Data 2004 to 2008

Percent of Persons (45 - 64 yrs) Classified as Obese (BMI > 29.99)Maryland BRFSS 2004 - 2008

27.6%30.0%

17.8%

37.3%*

0%

10%

20%

30%

40%

50%

Non Hisp, White Non Hisp, Black Non Hisp, Other Hispanic

* = significantly different from NH White rate

*

Percent of Adults Age 45-64 Classified as Obese, Maryland 2004-2008

18-44 and65+ show a similar pattern to 45-64

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Utilization Analysis for Cost of Disparities

Formula for attributable fraction in the exposed: (RR-1)/RR(2.4-1)/2.4 = 1.4/2.4 = 58.3% of Black Asthma hospitalizations are excess.

Black vs. White Disparity Ratios for Adults with Asthma, Maryland 2006

Source: This figure is Figure 8-5 from the DHMH report Asthma in Maryland 2007

330% more ED visitsand 140% morehospital admissionswith only 30% more asthma indicates adisparity in diseasemanagementsuccess.

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Discharge Data Analysis of Cost of Disparities

Cost of Excess Black or African American Admissions

Medicaid All Payer Primary Diagnosis Excess Cost Excess Cost

All Diagnoses $59 Million $481 Million

Heart Disease $5 Million $38 Million

Cancer $1 Million $7 Million

Diabetes $3 Million $26 Million

Asthma $2 Million $18 Million

Neonatal Intensive $3 Million $20 MillionCare Admissions

Does not include Outpatient Care costs

MHHD Analysis of HSCRC Hospital Discharge Data

Cost of Disparities, Maryland 2004

Hospital Component of Hospital Admissions

Does not include Physician component of Hospital AdmissionDoes not include Emergency Room costs

How might out of stateadmissions be affectingthese estimates?

1. Check consistency with Estimates in Baltimore City,an “internal” jurisdictionwhere admissions out ofstate are less likely.

2. Check consistency with estimates from Medicaredata, where the out of stateissue does not exist.

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Medicare Data Analysis of Cost of Disparities for Maryland

Primary Diagnosis

Congestive Heart Failure

Urinary Tract Infection

Dehydration

Diabetes

Asthma

Hypertension

Does not include Outpatient Care costs

MHCC analysis of Maryland Medicare data

Cost of Excess Black or African American AdmissionsCost of Disparities, Maryland 2006

Hospital Component of Hospital Admissions

Does not include Physician component of Hospital AdmissionDoes not include Emergency Room costs

MedicareExcess Cost

$13 Million

$1 Million

$2 Million

$2 Million

$5 Million

$1 Million

Source: Differences in Hospitalizations for Ambulatory Care Sensitive Conditions Among Maryland Medicare Beneficiaries—2006. Maryland Health Care Commission.

Analysis of Medicaredata in persons age65+ is consistent withthe statewidedischarge dataanalysis.

Analysis of payer-basedclaims data (vs. provider-based data) whereavailable avoids themissing out-of-stateutilization issues.

Frequency disparity vs. Severity disparity.

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Discharge Data Analysis of Cost of Disparities

Why was analysis restricted to Black vs. White in 2004?

Count of admissions missing race data: 30,087Count of admissions missing Hispanic ethnicity data: 51,483

Count of admissions recorded as American Indian or Alaska Native: 1,537 Missing race as percent of known AIAN = 1957%

Count of admissions recorded as Asian or Pacific Islander: 12,011Missing race as percent of known API = 250%

Count of admissions recorded as Hispanic: 19,449Missing Hispanic ethnicity as percent of known Hispanic = 265%

Count of admissions recorded as Black or African American: 207,495Missing race as percent of known Black or African American = 15%

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Contact Information

Office of Minority Health and Health DisparitiesMaryland Department of Health and Mental Hygiene

201 West Preston Street, Room 500 Baltimore, Maryland 21201

Website: http://www.dhmh.maryland.gov/hd

Chartbook: http://www.dhmh.state.md.us/hd/pdf/2010/Chartbook_2nd_Ed_Final_2010_04_28.pdf

Phone: 410-767-7117Fax: 410-333-5100

Email: healthdisparities@dhmh.state.md.us