The Use of Surveillance Resources to Support Prevention of CVD

1
The Use of Surveillance Resources to Support
Prevention of CVD

• David Goff, MD, PhD
• Professor
• Wake Forest University School of Medicine

2
Learner Objectives

• To become familiar with
• the rationale for surveillance of CVD
• current approaches to surveillance of CVD
• available data sources
• Mortality
• Morbidity/Outcomes
• Quality of Care
• Access to Care
• Risk factors

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What is Surveillance?

• Surveillance is the ongoing, systematic
  collection, analysis, and interpretation of
  outcome-specific data for use in the planning,
  implementation and evaluation of public health
  planning.

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Why do we need CVD Surveillance?

• Estimate CVD burden and trends
• Mortality, Morbidity and Risk Factors
• Understand natural history of a disease
• regional, gender or ethnic differences
• test hypotheses about etiology
• changes in health practices
• changes in health care delivery

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Why do we need CVD Surveillance?

• Provide the data required for effective public
  policy
• allocation of preventive resources
• allocation of medical services
• allocation of research resources
• evaluation of control/prevention strategies

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CVD Surveillance Loop
Data Interpretation
Program Evaluation
Data Analysis
Information Dissemination
Program Implementation
Data Collection
Program Planning
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CVD in the US

• 58,800,000 Americans have CVD
• High blood pressure 50,000,000
• Coronary heart disease 12,000,000
• Myocardial infarction 7,000,000
• Angina pectoris 6,200,000
• Congestive heart failure 4,600,000
• Stroke 4,400,000
• Rheumatic fever/rheumatic heart disease
  1,800,000
• Congenital cardiovascular defects 1,000,000

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Mortality

• CDC WONDER
• http//wonder.cdc.gov/
• http//wonder.cdc.gov/mortsql.shtml
• National Center for Health Statistics
• http//www.cdc.gov/nchs/
• State Centers for Health Statistics
• CDC(P) Atlases

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Geographic Information Systems (GIS) Analysis of
Stroke Mortality
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CDC WONDER Query
Query Description Compressed
Mortality Data for Years
1979-1998 Location
FORSYTH(FIPS37067) , North Carolina
(FIPS37) Ages
All Ages Race All
Races Gender Both
Genders Grouped by Race
Standard Population Year
2000 Race
All Races Gender
Both Genders Location
The United States
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CDC WONDER Query Forsyth County, NC
Using the following ICD Codes 410-414.9
429.0-429.9 Race Death Count Population
Age Adjusted Rate Crude Rate B
2,388 1,312,010 261.3
182.01 O 11
43,605 83.8(UNR)
25.23(UNR) W 9,109
3,935,123 236.4
231.48
Blacks F 1,226
713,441 138.8
171.84 M 1,162 598,569
224.3
194.13 Whites F 4,235
2,060,114 178.2
205.57 M 4,874 1,875,009
366.0 259.95
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CDC WONDER QueryAll Counties, NC
County Name Death Count Population Age
Adjusted Rate ALAMANCE 5,602
2,152,594 264.5 ALEXANDER
1,190 550,339
268.4 ALLEGHANY 555
193,068 217.4 ANSON
1,628 489,459
315.2 ASHE 1,315
454,490 237.6 AVERY
919 298,838
309.8 BEAUFORT 2,633
849,969 298.6 BERTIE
1,204 414,853
288.9 . FORSYTH 11,508
5,290,738 241.0 . NASH
3,827 1,532,456
287.7 .
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http//www.cdc.gov/nchs/data/nvsr/nvsr48/nvs48_11.
pdf
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Morbidity/Outcomes/Quality of Care

• National Health Care Survey
• http//www.cdc.gov/nchs/nhcs.htm
• Medicare/PROs
• Medicaid
• Managed Care Organizations
• HEDIS
• AHA Get With The Guidelines
• BRFSS
• NHANES
• Registries

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National Health Care Survey (NHCS)

• Four record-based surveys merged and expanded
  into one integrated survey of health care
  providers
• New data on alternative health care settings
• Ambulatory surgical centers
• Hospital outpatient departments
• Emergency rooms
• Hospices
• Home health agencies

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National Health Care Survey (NHCS)

• The survey is a source of a wide range of data on
  the health care field and a significant resource
  for monitoring health care use, the impact of
  medical technology, and the quality of care
  provided to a changing American population.

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NHCS

• Existing surveys
• National Hospital Discharge Survey (NHDS)
• National Ambulatory Medical Care Survey (NAMCS)
• National Nursing Home Survey
• National Health Provider Inventory
• New survey components
• National Survey of Ambulatory Surgery
• National Hospital Ambulatory Medical Care Survey
• National Home and Hospice Care Survey
• National Employer Health Insurance Survey

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Number and rate of discharges NHDS
http//www.cdc.gov/nchs/about/major/hdasd/nhds.htm
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Hospital Stroke Rate and In-Hospital Stroke
Death NHDS
Howard. Neuroepidemiology 199110251-259
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NAMCS

• http//www.cdc.gov/nchs/about/major/ahcd/officevis
  itcharts.htm

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NAMCS, 1998 Symptoms/Reasons for Office Visits
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NAMCS, 1998 General Diagnosis for Office Visits
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NAMCS, 1998 Specific Diagnosis for Office Visits
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NAMCS, 1998 Clinical Tests during Office Visits
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Number and percent distribution of drug mentions
by therapeutic classification, NAMCS 1998
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NAMCS, 1998 Medications Prescribed at Office
Visits
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Age Adjusted Average Annual Discharge Rates by
County for NC, SC, and GA, 1996-1998 Medicare
Beneficiaries (All strokes ICD-9 430-438)
Average annual discharge rates per 1000 enrollees
4.2 - 21.6
21.7 - 25.0
25.1 - 28.8
28.9 - 52.9
Slide Courtesy of Louise Henderson, Medical
Review of North Carolina
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Medicare Data CCP

• Design
• Center for Medicare and Medicaid Services (CMS)
  QI project with baseline measurement, feedback,
  remeasurement and comparison samples
• Participants
• All Medicare patients in Alabama, Connecticut,
  Iowa, and Wisconsin with principal dx of AMI
  June - Dec 1992 and Aug-Nov 1995
• External Comparison Random sample of rest of
  nation Aug-Nov 1995

Marciniak TA, et al. JAMA 19982791351-1357.
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Medicare Data CCP

• Intervention
• Data feedback by peer review organizations
• Hospital-specific plans
• Outcome measures
• Processes of care
• Length of stay
• Mortality

Marciniak TA, et al. JAMA 19982791351-1357.
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Medicare Data CCP
Marciniak TA, et al. JAMA 19982791351-1357.
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Selected State Performance on 2 Medicare
Performance MeasuresFrom Jencks JAMA, Volume
284(13).October 4, 2000.1670-1676
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Average State Rank on 22 Medicare Performance
MeasuresFrom Jencks JAMA, Volume
284(13).October 4, 2000.1670-1676
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MCO DataAchieving Cardiac Excellence (ACE)
Project

• CDC-funded project designed to reduce
  hospitalizations among patients with CHF by
  increasing the utilization of therapies proven to
  reduce morbidity and mortality.
• Design
• MCO population and databases
• Baseline measurements of quality
• Feedback and chart reminders
• Remeasurements
• No comparison group

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MCO DataUse of CHF related medications, 1998
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MCO DataUse of CHF related medications, 1998

• Substantial practice variability in ACEI use
• Highest use practice 86
• Lowest use practice 14
• High quality care would be reflected in low
  variability across practices.

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MCO DataACE Results 1998 - 2000
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(No Transcript)
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NCQAs State of Managed Care Quality Report 2000
http//www.ncqa.org/index.htm
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NCQAs State of Managed Care Quality Report 2000
http//www.ncqa.org/index.htm
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NCQAs State of Managed Care Quality Report 2000
http//www.ncqa.org/index.htm
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NCQAs State of Managed Care Quality Report 2000
http//www.ncqa.org/index.htm
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AHA Get With The Guidelines

• Secondary Prevention of CHD
• Guidelines
• Quality improvement tool
• Database
• http//www.americanheart.org/getwiththeguidelines/
  
• Patient tracking form

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Major Stroke Risk Factors For WhitesBehavioral
Risk Factor Surveillance SystemTop Row Men
Bottom Row Women
Hypertension Diabetes
Cigarette Smoking
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TC Screening (Ever) BRFSS, 1997
BRFSS, 1997.
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TC Screening in Past 5 Years (Among Screenees)
BRFSS, 1997
BRFSS, 1997.
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BP Screening (Past 2 Years) BRFSS, 1997
BRFSS, 1997.
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Awareness, Treatment, and Control of High Blood
Pressure in Adults NHANES
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Observed and Estimated 50th Percentile of SBP by
Birth Cohort and Age
Estimated using the following independent
variables age, age2, birthyear, agebirthyear,
and age2birthyear.
Goff DC Jr, et al. Ann Epidemiol. 200111271-9
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Data Based Promotion of CVH

• Many useful databases available on line and by
  request (CDC, NCHS, CMS, State Centers for Health
  Statistics, Peer Review Organizations, etc.)
• Data available regarding mortality, morbidity,
  other outcomes, access to and quality of care,
  and risk factors.
• Develop relationships with state epidemiologists,
  PROs, MCOs
• Use data to identify opportunities for
  improvement and to evaluate programs