A Population Health Observatory
Short Course
Community Health Assessment
Data and Statistical Resources
Population Health Observatory
1
Acknowledgements
•
•
This course was funded by the New York State Department of Health,
through grants to the School of Public Health and Health Professions,
University at Buffalo (Maurizio Trevisan, P.I.)
The course was developed by the Population Health Observatory
(Randy Carter, Director) and presented to the public health
professionals in Western New York on behalf of the New York State
Department of Health and the Western New York Public Health
Alliance.
Primary Author:
Austin Miller, MS
Department of Biostatistics
Co-Author:
Don Rowe, PhD
School of Public Health and Health Professions
Contributors:
Department of Biostatistics
Randy Carter, PhD
Jim Java, MA
Wei Tan, BA
2
Background
•
•
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Mission of public health
– 1988 Report from the Institute of Medicine
– Assuring conditions in which people can be healthy
Three core functions of public health
– Assessment, Policy Development and Assurance
1987: NYCRR Part 40 Article 6 makes Community Health Assessments
(CHA) mandatory
– Assessment is critical in the ongoing public health planning process
1997: The Public Health Agenda Committee (PHAC) proposed a more
standardized format and content of the CHA
2004: The State Health Department contracted with the UB Population
Health Observatory to
– Strengthen the skills of the public health work force in WNY
– Establish a regional approach to community health assessment
activities (starting with Maternal and Child Health)
Source: 2005-2010 Community Health Assessment Summary Form
3
Community Health Assessment
Example and Data Sources
4
Community Health Assessment Guidance
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•
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The Community Health Assessment (CHA) is the ongoing process of
regular and systematic collection, assembly, analysis and distribution
of information on the health needs of the community
Includes statistics on health status, community health needs, gaps,
problems and assets
Sharing findings with key stakeholders enables and mobilizes
community members to work collaboratively towards building a
healthier community
The CHA forms the justification for the activities conducted in the
MPHSP (Municipal Public Health Services Plan) and any activities
undertaken by the Local Health Department
Source: 2005-2010 CHA Workgroup Checklist
5
Collaboration yields a more meaningful
assessment process
•
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•
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Schools
After school programs
Dept of Education
•
•
•
Health Departments
Hospitals, clinics
Private providers
Not for profits
Faith-based
organizations
•
•
•
•
Private Industry
Other Gov agencies
Police
Fire
Parks
6
Community Health Assessment Sections
•
•
•
•
•
•
•
Focus
Section One: Populations at risk
– Demographic descriptives, sickness and death rates, etc.
Section Two: Local Health Unit Capacity Profile
– Specific information about the local health department
Section Three: Problems and Issues in the Community
– Community resources, collaborations, discussions of unmet needs
Section Four: Local Health Priorities
– What they are, how they were identified, steps that have been taken,
progress that has been made…
Section Five: Opportunities for Action
– Including roles of other community resources (schools, businesses, etc)
Section Six: Report on Statewide Performance Measures
– “Format to be provided later”
Section Seven: Community Report Card
Source: 2005-2010 CHA Workgroup Checklist
7
Community Health Report Cards
•
•
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Intent of the report cards
– Report cards are a convenient way to distribute important health information in
an easy to understand summary form meant for public consumption. They are
usually done on a county by county basis. Examples below are illustrational only.
Monroe County
Cortland County
Regional Report Card
– Disease, morbidity and mortality do not respect county boundaries
– Analyses that transcend county boundaries give a more refined picture of
disease patterns and distribution
– A regional report card sets the stage for a regional approach to assessing AND
solving health problems in an evidenced based, cost effective manner
– What should a Regional Report Card look like?
•
There is no prescribed format but we can look at Monroe and Cortland county as examples.
– What value does it have?
•
Easy to understand, informs the “community”, develops advocacy, focuses on common problems and
differences, leads to problem resolution
8
Monroe County Report Card
Source: http://www.healthaction.org/ReportCards.html
9
Monroe County Report Card
Progress Toward Goals
Goal
Responsibility
Actions
Source: http://www.healthaction.org/ReportCards.html
10
Monroe County Report Card
Status Measures
Summary measures
and commentary
A link to the full report
Source: http://www.healthaction.org/ReportCards.html
11
Monroe County Report Card
Health Action Partnership
Source: http://www.healthaction.org/ReportCards.html
•
HEALTH ACTION is a partnership of
15 local organizations working
cooperatively to improve the health
of Monroe County residents
•
A series of report cards covering
people of all ages and the quality of
the environment in Monroe County
have been developed and are
updated periodically
•
After the release of each report
card, the Monroe County Board of
Health, with extensive community
input, selects two priorities for
community-wide action for the next
four to five years
12
Cortland County’s Web-Based Report Card
Introduction
Scoring Each Metric
"Cortland Counts"
Cortland Counts 2004: An Assessment of Health and Well Being in Cortland
County NY (Report Card only)
Favorable status compared to upstate, state &/or
national data
Cortland Counts 2003: An Assessment of Health and Well Being in Cortland
County NY (Report Card only)
Cortland Counts 2002: An Assessment of Health and Well Being in Cortland
County NY (full updated report)
Cortland Counts 2001: An Assessment of Health and Well Being in Cortland
County NY (full original report)
In an effort to meet the needs of the
entire community, SVHC has been
working with COPC of
SUNY Cortland, the County Health
Department, Cortland Memorial
Hospital, and the United Way of
Cortland County to develop a
comprehensive community assets
and needs assessment. The
assessment will extend beyond
health issues to a "quality of life"
assessment.
By obtaining a broader view of the
condition of the local community, individual agencies will be better able to plan
for and obtain adequate resources to meet unidentified, under-served and/or
emerging needs. The first two assessments are complete and are posted
online. The original full report and the July 2002 Community Report Card
(summary report) are also available at the Seven Valleys Health Coalition
office at 10 Kennedy Parkway, at several local businesses, and at all local
libraries.
Source: http://www.sevenvalleyshealth.org/report04/1_3.htm
A closer look is required. Change in percent or rate
may be desired
*
0% = best in U.S
50% = national average
100% = worst in U.S.
\/
Goal is to decrease the number
/\
Goal is to increase the number
--
neither favorable nor unfavorable
TBD
To be determined
AA
Age adjusted to 2000 census
BMI
Body Mass Index
*
0% = best in U.S
50% = national average
100% = worst in U.S.
**
Country Music Park went from 100,000
participants in 2002 to 1,400 in 2003.
13
Cortland County’s Web-Based Report Card
Snapshot of the Data
Indicators of Health and Safety
Healthy
People
2010
Goal
Upstate
NYS
Data
Current
NYS
Data
Nationa
l Data
Births to women
receiving 1st
trimester
prenatal care
(1,2,3)
83.2%
(2001)
77.7%
(2001)
73.0%
(2001)
83.7%
(2002)
Hospitalization
for asthma (0-4
yr. old children)
53.5/
10,000
(19992001)
36.8 /
10.000
(19992001)
71.0/
10.000
(19992001))
55.4/
10,000
(1999)
25.0/
10,000
\/
Low birth weight
babies <2500g
7.1%
(2001)
7.0%
(2001)
7.7%
(2001)
7.8%
(2002)
5%
\/
Indicators
(2,3)
(22,16)
90%
Cort.Co.
Status
Cort.
Co.
Goal
Cortland
Co. Data
/\
The report card is not focused solely on Maternal Child Health issues. Shown is a portion of the Maternal Child
Health section. The report card includes much more information on several other topics.
Source: http://www.sevenvalleyshealth.org/report04/1_3.htm
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Categories within CHA Section One
Populations at Risk
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(A) Demographic and health status information
– Descriptives: age, race, gender, prevalence of poverty, employment,
education, households
– Natality, morbidity, mortality
– Data for smaller areas (minor civil division, zip codes, or census tracts)
– Particular emphasis on interpreting demographic trends for the
relationship to poor health and needs for public health services
– 121 metrics
(B) Access to Care
– Availability of hospitals, clinic, private providers, etc.
– Discussion of primary care and preventive health services utilization
– Commonly-identified barriers and affected sub-groups
(C) Behavioral Risk Factors
– Estimates for the prevalence of health risk behaviors
(D) Local Health Care Environment
Source: 2005-2010 CHA Workgroup Checklist
15
The Value of a Regional Approach
The problem with large-area aggregates
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In a sense, County-level Community
Health Assessments are akin to
County-level median income
– Difficult to compare. Information
is spread across different
documents and different formats
– Some evidence of differences
between Counties
– Nothing stands out as a glaring
problem
Not actionable
– Could start with Allegany, where
the median income is lowest
– Cannot identify at-risk populations
from this level of aggregation
– Other Counties have low-income
areas, but these are hidden…
County
Median
Income
Population
Allegany
32,106
49,927
Cattaraugus
33,404
83,955
Chautauqua
33,458
139,750
Erie
38,567
950,265
Genesee
40,532
60,370
Niagara
38,136
219,846
Orleans
37,972
44,171
Wyoming
39,895
43,424
Overall
37,678
1,591,708
16
The Value of “Smaller Areas”
Thematic Mapping to Identify Hotspots
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•
The benefit
– Identify “high risk” areas
(irrespective of County
boundaries)
– Find issues hidden in countylevel aggregates
– Easy visualization
The challenge
– Smaller geographic areas =
smaller populations
•
Lake Ontario
Compromise the privacy of
individuals
– Volatility in the metrics
•
False Alarms
– Software and data availability
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The CHA is a Big Project
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A big project for a Big Objective
Project teams
Data collection and analysis
Report Writing
– Format
– Contents
– Regional vs. County priorities
Identifying priorities
Developing meaningful action plans
Implementing changes
Working with constituents
Etc.
18
Where do they expect me to find data for
121 State-recommended metrics?
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A few websites that might be useful
– http://www.healthypeople.gov/
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National and selected State data
Updated Quarterly
Measures progress towards the Healthy People 2010 objectives
– http://www.chc.gov/nchs/healthywomen/htm
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State-level data on the health and wellbeing of women
Must install the “Beyond 20/20” software (free)
– http://www.cdc.gov/nchs/nhis.htm
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National Health Interview Survey
Numerous national health statistics, with information on health insurance and access to care
– http://www.cdc.gov/nchs/nvss.htm
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National Vital Statistics System
Births, deaths, marriages, etc.
– http://www.cdc.gov/nchs/sets.htm
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The Statistical Export and Tabulation System (SETS) gives data users the tools to access and
manipulate large data files
NHCS provides many data sets for use in SETS 2.0. Some of them include data on aging, births,
deaths, and health care and service utilization
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Where do they expect me to find data for
121 State-recommended metrics
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The majority of required data is available on the Community Health
Data Set Website
– http://www.health.state.ny.us/nysdoh/chac/chds.htm
18 sections, each with multiple data sets
1. Demographic & Socioeconomic
Characteristics
2. Physical Activity and Fitness
3. Nutrition
4. Tobacco Use
5. Substance Abuse: Alcohol &
Other Drugs
6. Family Planning
7. Violent and Abusive Behavior
8. Unintentional Injuries
9. Oral Health
10. Maternal & Infant Health
11. Child/ Adolescent/ Young Adult
Health
12. Heart Disease and Stroke
13. Cancer
14. Chronic Conditions
15. HIV Infection
16. Sexually Transmitted Diseases
17. Immunization
18. Infectious Diseases
… and growing
Source: http://www.health.state.ny.us/nysdoh/chac/chds.htm
20
A Screen Shot of the State’s data web site
What are these?
Section Heading (18 total)
Datasets available
Source: http://www.health.state.ny.us/nysdoh/chac/chds.htm
21
Types of data available on the website
Decoding the symbols on the datasets
Symbol
What you get
(G)
Trend graph
(M)
Bar chart or map
(pdf format)
(T)
3 year table
(T+TR)
3 year table +
10 year trend plots
Click on County
For Detail
What’s this?
Year
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Single
Year
773.3
745.7
839.5
744
663.2
624.2
642.4
631.6
620.3
630.4
Upstate
3-Year
New
Average York
786.2
776.4
748.9
677.3
643.3
632.7
631.5
627.5
720.2
721.5
699
651.4
643.8
627.4
608.6
619.7
620.9
637
Source: http://www.health.state.ny.us/nysdoh/chac/chds.htm
LUNG & BRONCHUS CANCER - DEATHS AND DEATH RATES PER 100,000 RESIDENTS
SOURCE: 1998-2002 VITAL STATISTICS DATA AS OF AUGUST, 2004
ADJUSTED RATES ARE AGE ADJUSTED TO THE 2000 UNITED STATES POPULATION
REGION
DEATHS
POPULATION
COUNTY
1998
1999
2000
2001
2002
TOTAL
2000
REG-1 WESTERN NEW YORK
ALLEGANY
36
29
41
39
40
185
49,908
CATTARAUGUS
45
68
59
54
45
271
83,916
CHAUTAUQUA
71
85
99
93
102
450
139,584
ERIE
704
701
713
690
691
3,499
949,403
GENESEE
38
42
30
44
53
207
60,325
CRUDE
RATE
ADJUSTED
RATE
74.1
64.6
64.5
73.7
68.6
67.7
56.9
53.7
61.4
61.2
22
Age Adjustment
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What does “Adjusted” mean?
The tempting conclusion may not be right
•
•
On the State website, mortality-based indicators are presented as both crude
and age-adjusted rates
Usefulness of crude rates depends on your purpose
– Unadjusted rates can be used to describe the health of the population
– Adjusted rates can be used to compare health care systems
– Age adjustment removes risk differences caused by differences in age
distribution
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The problem: Age disparity can lead to misleading conclusions about health care availability or quality
Older people die at a faster rate. Counties with a relatively higher percentage of older people will have
higher mortality rates
The standard population used for adjustment is the 2000 United States population (as decreed by the
Center for Disease Control)
Can adjust for anything if factor-specific rates are available
– Race, education, income, employment…
Adjusted rates should be viewed as relative indexes rather than actual
measures of risk
– Adjusted rates don’t mean anything by themselves. They only have meaning in
comparing risks of similarly adjusted populations.
– “Adjusted rates” are also referred to as “standardized rates”
24
How to do an “age adjustment”
Ischemic Heart Disease Rates for Black and White Mean (per 100,000 population)
Ages 35-74 years. United States, 1986
Direct Age Adjustment
Age Group Standard Pop
35 to 45
14,000
46 to 54
14,000
55 to 64
11,000
65 to 74
7,000
Total
46,000
(1)
% of total
30.4%
30.4%
23.9%
15.2%
100.0%
x
Black Men
Crude
Adjusted
56.1
17.1
183.5
55.8
457.0
109.3
919.4
139.9
404.0
322.1
(2)
=
(3)
White Men
Crude
Adjusted
35.8
10.9
154.3
47.0
450.1
107.6
1062.8
161.7
425.8
327.2
(4)
1. Find a Standard Population. Calculate the percentage of the standard
population that falls in each age strata
2. Find the strata-specific crude rates for the target populations to be
compared
3. Within each age strata, multiply the target population crude rate by the
percent of the Standard population
- This is an interim step. By themselves, the resulting numbers don’t mean much
4. Add up the results of step 3 to get the age adjusted rates
25
An age-adjustment example
Lung cancer death rates
LUNG & BRONCHUS CANCER - DEATHS AND DEATH RATES PER 100,000 RESIDENTS
SOURCE: 1998-2002 VITAL STATISTICS DATA AS OF AUGUST, 2004
ADJUSTED RATES ARE AGE ADJUSTED TO THE 2000 UNITED STATES POPULATION
REGION
DEATHS
POPULATION
COUNTY
1998
1999
2000
2001
2002
TOTAL
2000
REG-1 WESTERN NEW YORK
ALLEGANY
36
29
41
39
40
185
49,908
CATTARAUGUS
45
68
59
54
45
271
83,916
CHAUTAUQUA
71
85
99
93
102
450
139,584
ERIE
704
701
713
690
691
3,499
949,403
GENESEE
38
42
30
44
53
207
60,325
CRUDE
RATE
ADJUSTED
RATE
74.1
64.6
64.5
73.7
68.6
67.7
56.9
53.7
61.4
61.2
EASY interpretation: Compared to Genesee, Erie county has
a much higher lung cancer death rate
• CRUDE death rates: Erie is 7% higher than Genesee
BETTER interpretation: Erie County has a higher percentage
of older people. Older people have higher lung cancer death
rates. If this age difference did not exist, the lung cancer
death rates would be the same
• Relative indexes, for comparison only
26
Small differences in age structure potentially result in
Big Changes in Interpretation
Percent of Total Population in Each Age Group
Age Group
Erie
Genesee
1-4
5-9
10-14
15-17
18-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85+
Total
% less than 65
% 65 or more
Crude Rate
Adj Rate
5.84%
6.40%
7.07%
4.17%
2.68%
6.64%
5.56%
6.45%
7.21%
8.04%
7.67%
6.75%
5.43%
4.23%
3.79%
3.84%
3.49%
2.56%
2.17%
5.62%
6.57%
7.64%
4.73%
2.62%
6.01%
5.08%
6.42%
7.72%
8.78%
7.84%
6.54%
5.53%
4.31%
3.63%
3.41%
3.16%
2.33%
2.08%
100.0%
100.0%
84.2%
15.8%
85.4%
14.6%
73.7
61.4
68.6
61.2
27
Random Numbers, Error and
Confidence Intervals
28
How do we interpret these numbers? First, some
esotericism about randomness
•
Random Number: A number is random in the sense of how it was
generated
– The observed rate that you see is one element of a set of possible
outcomes generated by an underlying (unknown) process
Process
(unknown
rate)
Random
Error
Possible
Outcomes
Observed Rate
(Random Number)
0 100
70.9
72.78
70.0
82.5
62.5
69.7
85.0
62.5
7.13
7.21
True RateErie=
X per 100,000
100
0.0
True RateGenesee=
Y per 100,000
3.59
87.86
61.7
44.8
85.7
26.6
45.3
30.5
Erie Lung Cancer Death Rate
• 2000:= 75.10
• 2001:= 72.68
• 2002:= 72.78
Genesee Lung Cancer Death Rate
• 2000:= 49.73
• 2001:= 72.94
• 2002:= 87.86
29
The Goal: Reverse the chain
Make judgments about the Process that account for random error
Process
(unknown
rate)
Random
Error
Possible
Outcomes
0 100
70.9
72.78
70.0
82.5
62.5
69.7
85.0
62.5
7.13
7.21
True RateErie=
X per 100,000
100
0.0
True RateGenesee=
Y per 100,000
The unknown process
3.59
87.86
61.7
44.8
85.7
26.6
45.3
30.5
show us about…
Observed Rate
(Random Number)
Erie Lung Cancer Death Rate
• 2000:= 75.10
• 2001:= 72.68
• 2002:= 72.78
Genesee Lung Cancer Death Rate
• 2000:= 49.73
• 2001:= 72.94
• 2002:= 87.86
What do the
Observed Results…
• What is the Genesee Rate? Is it different than the Erie Rate?
• Is there truly a difference, or do differences in observed rates result from
randomness in the process?
30
Types of Error
•
Random Error
– Variation due to chance
•
•
When the number of events is LARGE, random variation is usually small
When the number of events is SMALL (fewer than 100), and the probability of an event is small,
random variation can be very large
– Random variation affects interpretation of data
•
•
– The number of events that actually occurred may be considered as one of a
large series of possible results that could have occurred under the same
circumstances.
Sampling Error (Estimates from Surveys)
– Different surveys yield different results
– Surveys are used to “sample” a portion of the population
•
•
High variation in observed rates makes estimates of the true rate less certain
Getting information from EVERYONE is often impractical (or impossible)
– Sampling Error: variation in an estimate that occurs by chance because a sample
of the population is surveyed, rather than the entire population
Bias
– The sample does not fairly, accurately represent the population
– The sample rate is systematically different from the true rate
31
Example of Bias
•
Consider a telephone survey in Dunkirk NY
– Large migrant worker population doesn’t have phones
– Presence of migrant workers depends on the timing (season) of the
survey
– Many phone numbers are not listed, or not available
• Nationally, about 10% of households with cellphones and no land-lines
32
The Histogram
Percentage of the Total Population
A “picture” of the data. Shows which outcomes are more likely.
48% of the outcomes were
between 6 and 8
There is a 13% probability that a
randomly selected observation
will be between 10 and 12.
• No strict definition for the ranges
• Define so they are informative
• Equal ranges might be easier to
explain or interpret.
Group the observations into ranges
33
Comments on Histogram
•
•
Histograms help to identify which measure of central tendency is more
descriptive
Which measure is the best?
– The “average” may not be the best measure
• The average is always mathematically correct
• The average will vary considerably if
– the sample size is small
– there are outliers
• Best for symmetric data
– The “median” might be better
• The median is the observed value that splits the sample in half
– 50% had less than X, 50% had more
• Better if the histogram is “skewed” (not symmetric)
• Not as sensitive to outliers
• Less common, and may be confused with the average
34
Using a Histogram to Select the Best
Measure of Central Tendency
Symmetric Histrogram
Asymmetric Histrogram
(normal distribution)
(binomial distribution)
30%
25%
25%
20%
20%
Percent
Percent
15%
15%
10%
10%
5%
5%
0%
0%
0
1
2
3
4
5
6
7
8
9
10
0
1
2
3
Z1
Median: 3.00
Average: 3.04
4
5
6
7
8
9
10
Z2
Median: 2.0
Average: 2.8
A 40% difference
35
Confidence Intervals for Rates
An estimated range for the underlying True Rate
•
•
For confidentiality reasons, make sure you have 5 or more cases
(deaths, births…)
Some Definitions
– c:= number of observed cases
– N:= total population (e.g. in the county)
– π:= the true (unknown) rate
– p:= the observed rate (per person)
• =c/N
•
– Z:= 1.96 (for a 95% confidence interval)
The formula
p  z / 2
•
p 1  p 
N
   p  z / 2
The True Rate
p 1  p 
N
Interpretation: “95% of the time, the true rate lies within this range”
36
Comparing One County to Another
Lung Cancer Example
Rates Per Person
REGION/COUNTY
ALLEGANY
CATTARAUGUS
CHAUTAUQUA
ERIE
GENESEE
# of Lung Cancer
Cases (2002)
40
45
102
691
53
2000
Pop'n
49,908
83,916
139,584
949,403
60,325
Conf Int
Conf Int
2002 Rate Lower Limit Upper Limit
0.0008015 0.0005532 0.0010498
0.0005363 0.0003796 0.0006929
0.0007307 0.0005890 0.0008725
0.0007278 0.0006736 0.0007821
0.0008786 0.0006421 0.0011150
p  z / 2
p 1  p 
N
p  z / 2
Rate Per 100,000 People
Conf Int Conf Int
2002
Lower
Upper
Rate
Limit
Limit
80.15
55.32
104.98
53.63
37.96
69.29
73.07
58.90
87.25
72.78
67.36
78.21
87.86
64.21
111.50
p 1  p 
N
Allegany
If the intervals DO
NOT overlap, we can
say that the county
rates are different.
Cattaraugus
Chautauqua
Erie
If the intervals do
overlap, more formal
tests are required.
Genesee
25
50
75
100
125
Lung cancer mortality rate per 100,000 people
37
Testing Differences Using
Overlapping Confidence Intervals
•
Rates with confidence intervals that DO NOT overlap ARE significantly
different
– If two confidence intervals do not overlap, the True Rates are
significantly different
•
Look at each pair separately
•
This is a conservative test for significance. Using more formal tests,
the difference between two rates may be statistically significant even
though the confidence intervals overlap
38
Some Notes on
Confidence Intervals
•
•
Formal interpretation:
– “If repeated samples of the same population are taken, 95% of the
associated confidence intervals will contain the true rate.”
– Intuitively, a confidence interval is an interval of plausible values of the
true rate, constructed using the sample and its corresponding standard
error, given the data that was observed.
Any confidence interval may or may not contain the true population
rate
– There is always a chance that the numbers you are using are not
reliable
– By purely random chance, a 95% confidence interval will NOT cover the
True Rate 5% percent of the time
39
Strategies for Reducing the Effects of Random Error
Strategy
Combine Time
Periods (eg 19982000)
Combine
Geographies
Pros
Cons
Stabilizes
Ignores
the estimate differences
between times
Stabilizes
Ignores
the estimate differences
between places
40
Comparing Counties to the Regional Average
Infant Mortality Example
Infant
Deaths Total Births
County
(2000-2002) (2000-2002)
Allegany
12
1,610
Cattaraugus
26
3,001
Chautauqua
29
4,623
Erie
261
32,716
Genesee
9
2,031
Niagara
57
7,402
Orleans
9
1,481
Wyoming
9
1,308
Total
412
54,172
Rates Per Person
Conf Int
Conf Int
2002
Lower
Upper
Rate
Limit
Limit
0.00745
0.00325
0.01165
0.00866
0.00535
0.01198
0.00627
0.00400
0.00855
0.00798
0.00701
0.00894
0.00443
0.00154
0.00732
0.00770
0.00571
0.00969
0.00608
0.00212
0.01004
0.00688
0.00240
0.01136
0.00761
0.00687
0.00834
Allegany
Cattaraugus
Chautauqua
Erie
Genesee
Niagara
Orleans
Wyoming
WNY OVERALL
Rate Per 1,000 Births
Conf Int Conf Int
Lower
Upper
2002 Rate
Limit
Limit
7.4534
3.2520 11.6548
8.6638
5.3480 11.9796
6.2730
3.9970
8.5489
7.9777
7.0137
8.9417
4.4313
1.5426
7.3200
7.7006
5.7092
9.6921
6.0770
2.1188 10.0352
6.8807
2.4008 11.3607
7.6054
6.8738
8.3370
• Genesee is
significantly lower
than the WNY Average
• More formal tests
needed to determine
differences between
counties
1
2
3
4
5
6
7
8
9 10 11 12
WNY Region Avg = 7.6
Infant mortality rate per 1000 live births
41
Comparing Counties to the
Healthy People 2010 Goal
•
Infant Mortality in some counties (and in the WNY Region) was
significantly higher than the Healthy People 2010 goal of 4.5 deaths
per 1,000 live births
Healthy People 2010 Goal
=4.5 deaths per 1,000 births
Counties with
larger
minority
populations.
Adjust for
race to
compare
healthcare
systems.
Allegany
Cattaraugus
Chautauqua
Erie
Genesee
Niagara
Orleans
Wyoming
WNY OVERALL
1
2
3
4
5
6
7
8
9
10 11 12
Infant mortality rate per 1000 live births
42
Questions about Confidence Intervals?
43
Using National Survey Data To Derive Rate Estimates
For Small Counties
44
Estimating Rates in Small Counties
•
•
•
Goal: To estimate how many people in your county have a given
condition or behavior
Challenge: Reliable and representative data for counties with small
populations are hard to get
– State and National surveys probably don’t have enough sampling
coverage to support a reliable estimate
– This gets even more difficult if sub-populations (e.g. race or age
segments) are to be analyzed
Strategies
– Aggregate time periods
– Aggregate geographic areas
– Modify the sampling scheme of an existing strategy (expensive)
– Conduct your own survey (time consuming/expensive)
– Use results from National Surveys
45
How Many People in Wyoming County Smoke?
•
•
•
•
Assumptions
– Don’t know the answer already
– There’s no survey in Wyoming County that contains the answer
– We can’t ask everyone (not enough time or money)
One possible data source = National Health Care Survey (NHCS)
Uses a combination of health care provider surveys
The NHCS obtains information about
• the facilities that supply health care
• the services rendered, and
• the characteristics of the patients served
– Each survey is based on a multistage sampling design that includes
health care facilities or providers and patient records.
– Data are collected directly from the establishments and/or their records
rather than from the patients
– Data for this national probability sample survey are obtained from 500
hospitals and 270,000 patient records annually
46
Using Results from a National Survey
•
The big assumption: That individuals with similar characteristics behave
similarly in both populations
– NHCS is a survey of hospital record data
– What percentage of people in your county visited a hospital in the past year?
– Do these people behave differently than the rest of the population?
•
•
Yes. For example, smokers are more likely to go to the doctor
Standardization Process
– Apply strata-specific rates from the survey to your population
– Possible stratifications
•
•
•
•
Age
Race
Education
Many others
– Assumes that the strata in your population has the EXACT SAME rates is strata
in the study population
•
•
You cannot test this assumption without relatively complete health data for the County
If you COULD test this assumption, you would not need this methodology!!
– Collaborate with a statistician. This could be much more involved.
47
National Smoking Rates from the
National Health Care Survey (NHCS)
Source: http://www.cdc.gov/nchs/data/series/sr_10/sr10_225.pdf
48
Wyoming County Population
Age Stratification of the NYS Health Dept Website
Age Group
<1
1
2
3
Wyoming
Population
437
407
402
442
4
5-9
10-14
454
2,533
3,017
15-17
18-19
20-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
65-69
70-74
75-79
80-84
85+
TOTAL
1,970
1,157
2,949
2,691
3,261
3,795
3,863
3,460
2,963
2,321
1,766
1,382
1,273
1,059
847
716
43,165
There are some smokers in these age strata. So
this process tends to underestimate the number
of smokers in the county (an example of “bias”.)
Age Group
Wyoming
Population
18-44
45-64
65-74
75+
17,716
10,510
2,655
2,622
Total
Check
33,503
33,503
Combine the age strata counts into
ranges comparable to NHCS data
Source: http://www.health.state.ny.us/nysdoh/chac/cha/pop/p2002_56.htm
49
Finishing the Estimate
a
Age Group
•
•
•
Wyoming
Population
18-44
45-64
65-74
75+
17,716
10,510
2,655
2,622
Total
Check
33,503
33,503
x
b
=
Nat'l
Smoking
Rate
25.2
22.0
12.1
5.7
Overall Rate
c
Smokers in
Wyoming
4,464.4
2,312.2
321.3
149.5
7,247.3
21.6%
Multiply the County age-strata counts (a) by the age-specific rates
from the survey (b)
– This yields an estimate of the number of people in each age-strata that
smoke
Add up the age strata counts to get an estimate of the total number of
Smokers in Wyoming County (c)
Calculate the overall smoking rate

7, 247.3 smokers
 21.6%
33,503 population 18+ years old
50
Questions about Using National Survey Data to
Estimate Rates in Small Counties
51
Trend Analysis
•
•
•
•
You are regularly asked to interpret trends, and determine if a rate is
improving or not
Statistical methods for analyzing trends are beyond the scope of this
course
– Least squares regression
– Logistic regression if all the rates are between 30% and 70%
– Others
The truth may not be apparent from a simple trend graph
Help is available. Collaborate with a statistician.
52
Template for a Regional
Maternal Child Health Assessment
53
Background
•
•
•
•
The Problem:
– Community Health assessment activities are laborious
– Reporting format is highly variable, making comparison across counties
difficult
– Inter-county comparison would be simplified in a Regional Report
Proposed Solution: Develop a Regional Report
2004 contract between the NY State Department of Health and the UB
School of Public Health and Health Professions
Goals of the Contract:
– To strengthen the skills and competencies of the public health work
force in Western New York
– To establish a regional approach to community health assessment
activities in Western New York
• Starting with Maternal Child Health
•
The UB Population Health Observatory began working on the contract
in November 2004
54
Contract Deliverables Summarized
•
•
•
•
•
Assess the MCH data used by members of the WNY Public Health Alliance
– Developed a survey
– Assess 14 possible MCH datasets on a several possible uses
– Results to be discussed later
Develop and gain consensus on a method of reporting MCH data in a
consistent manner
– Created a reporting template, including 70+ MCH metrics by county, by year
– Approved at the Dec 22, 2004 WNY Public Health Alliance meeting
Set up methodology for data transfer
– Data will be gathered from the NYS Health Information Network (HIN)
– A package requesting data access is being compiled for submission to the State
Create map-templates for each County
– Sample size/prevalence rate issues to be discussed
Conduct a training session with representatives of the eight County Health
Departments
55
Anticipate including about 70 maternal child health
metrics for the eight Western New York Counties
56
Demographic Comparisons
57
An Executive Summary for High-Level Comparisons
58
A Page for Each Metric
(the Numbers)
Confidentiality requirements
Watch out for small counts
Five year trends by
• Each county
• WNY Total
• Upstate Total
Show
• Actual number
• Rate
59
A Page for Each Metric
(Graphics and Explanations)
60
Maternal Child Health Data Available on the
NY State Health Department Website
61
CHA Data Requirements Available at
http://www.health.state.ny.us/nysdoh/chac/chds.htm
Community Health Assessment
Section One (Populations at Risk)
General Population Description
Population breakdown by age, race and ethnicity
Proportion of special populations
Median familiy income
% unemployed
High school dropout or attendence rate
% of population at or below poverty level
% of children in poverty
Access to Quality Services
% Medicaid or selfpay at delivery
% of adults who could not see doctor due to cost
% of children uninsured (less than 18 years)
Chronic Diseases
Cancer
% of women with PAP in last 2-3 years
% of women with mammogram in past 2 years
% screened for colorectal cancer
Cancer Incidence
Lung
Breast
Cervical
Colorectal
Oral (age 45-74)
Source: http://www.health.state.ny.us/nysdoh/chac/chds.htm
Website Data Section
Healthy People 2010 Goal
Demographics
Demographics
Demographics
Demographics
Demographics
Demographics
Demographics
Demographics
Cancer
Cancer
Cancer
97% of women
70% of women over 40
50% of adults
Cancer
Cancer
Cancer
Cancer
Cancer
62
CHA Data Requirements Available at
http://www.health.state.ny.us/nysdoh/chac/chds.htm
Community Health Assessment
Section One (Populations at Risk)
Cancer Mortality
Lung
Breast
Cervical
Colorectal
Oral (age 45-74)
Diabetes
Rates of diabetes hospitalizations/1000 diabetics
Diabetes mortality
Uncontrolled diabetes hospitalizations (18-64 years)
Diabetes prevalence in adults
Website Data Section
Healthy People 2010 Goal
Cancer
Cancer
Cancer
Cancer
Cancer
44.9 death per 100,000 population
22.3 deaths per 100,000 females
2.0 deaths per 100,000 females
13.9 deaths per 100,000 population
2.7 deaths per 100,000 population
Chronic Conditions
45 deaths per 100,000 population
Chronic Conditions
Environmental Health
Healthy Homes
% Children screened for lead by age 2
Children ages 1-6 with blood lead levels >= 10 g/dl
Water Quality
% of public water supplies in compliance
% of population served by acceptable water systems
Family Planning
% of births to teen (<18) mothers
Pregnancy rate (total)
Adolescent pregnancy rate, 10-14 yrs
Adolescent pregnancy rate, 15-17 yrs
Adolescent pregnancy rate, 15-19 yrs
Induced abortion to pregnancy ratio
Source: http://www.health.state.ny.us/nysdoh/chac/chds.htm
95% of population
Family Planning
Family Planning
Family Planning
Family Planning
Family Planning
Family Planning
43 per 1,000 females aged 15 to 17
63
CHA Data Requirements Available at
http://www.health.state.ny.us/nysdoh/chac/chds.htm
Community Health Assessment
Section One (Populations at Risk)
Food Safety
E.coli
Salmonella
Shigella
# and rate of foodborne outbreaks in regulated facilities
Heart Disease and Stroke
Cardiovascular disease mortality (IDC 10 100-199)
Diseases of the heart mortality (ICD 10 100-109,113,120-151)
Coronary heart disease mortality
Cerebrovascular disease mortality (ICD 10 160-169)
BP check in the last two years
Cholesterol check in the last two years
% adults with high blood pressure
% adults with high cholesterol
Website Data Section
Healthy People 2010 Goal
1 case per 100,000
6.8 per 100,000
Heart Disease
Heart Disease
Heart Disease
Heart Disease
Heart Disease
166 deaths per 100,000 population
48 stroke deaths per 100,000 population
95 percent
16%
17%
HIV
AIDS case rate
AIDS mortality rate
% of HIV positive newborns
Immunizations and Infectious Diseases
% 65+ with flu vaccine in last year
% 65+ ever had pneumonia vaccine
Pneumonia/flu hospitalizations (65+ years)
Measles incidence
Rubella incidence
Pertussis incidence
HIB incidence
Hep A incidence
Hep B incidence
Number of TB cases per 100,000 population
HIV Infection
HIV Infection
HIV Infection
19.5 case per 100,000
Immunization
Immunization
Immunization
Immunization
Immunization
Immunization
Infectious Diseases
Infectious Diseases
Infectious Diseases
364 nationally
9 nationally
20.3 per 100,000
20.1 cases among persons aged 2 to 18 years
64
Source: http://www.health.state.ny.us/nysdoh/chac/chds.htm
CHA Data Requirements Available at
http://www.health.state.ny.us/nysdoh/chac/chds.htm
Community Health Assessment
Section One (Populations at Risk)
Injury Prevention and Control
Suicide Mortality
Homicide Mortality
Self-inflicted injury hospitalizations
Assault hospitalizations
Unintentional Injury Mortality
Unintentional Injury Hospitalizations <10 years
Unintentional Injury Hospitalizations 10-14 years
Unintentional Injury Hospitalizations 15-24 years
Unintentional Injury Hospitalizations 25-64 years
Unintentional Injury Hospitalizations 65+ years
Traumatic brain injury hospitalizations
Indicated abuse and neglect cases (<18 years)
Work related injury mortality/10,000 workers
Alcohol related motor vehicle injuries and dealths
Drug related hospitalizations
Maternal Child Health
% early prenatal care
% late or no prenatal care
Infant mortality rates (before 1 year)
Neonatal mortality (within the first 28 days)
Postneonatal mortality (between 28 days and 1 year)
Spontaneous fetal deaths (20+ weeks gestation)
% infants with gestational age <37 weeks (preterm)
Maternal mortality
SIDS mortality
Spina bifida or other NTD's
% Very low birth weight (<1.5k)
% Low birth weight (<2.5k)
% pregnant woment with anemia (low SES)
Source: http://www.health.state.ny.us/nysdoh/chac/chds.htm
Website Data Section
Violent/Abusive Behavior
Violent/Abusive Behavior
Violent/Abusive Behavior
Violent/Abusive Behavior
Unintentional Injury
Unintentional Injury
Unintentional Injury
Unintentional Injury
Unintentional Injury
Unintentional Injury
Unintentional Injury
Unintentional Injury
Substance Abuse
Substance Abuse
Maternal & Infant Health
Maternal & Infant Health
Maternal & Infant Health
Maternal & Infant Health
Maternal & Infant Health
Maternal & Infant Health
Maternal & Infant Health
Maternal & Infant Health
Maternal & Infant Health
Maternal & Infant Health
Maternal & Infant Health
Nutrition
Healthy People 2010 Goal
3 per 100,000
17.5 per 100,000
45 per 100,000
10.3 per 1,000 children under age 18 years
3.2 deaths per 100,000 Workers age 16+
4.1 per 100,000
90% of live births
4.5 per 1000 live births
2.9 per 1000 live births
1.2 per 1000 live births
4.1 per 1000 live births
7.6% of live births
3.3 per 100,000 live births
0.25 per 1000 live births
3 per 10,000 live births
0.9% of live births
5.0% of live births
20% of low income pregnant women
65
CHA Data Requirements Available at
http://www.health.state.ny.us/nysdoh/chac/chds.htm
Community Health Assessment
Section One (Populations at Risk)
Nutrition and Overweight
% of adults eating 5+ servings of fruit/vegetables per day
% of adults overweight or obese
% children underweight (0-4 years, low SES)
% children overweight (2-4 years, low SES)
Website Data Section
Healthy People 2010 Goal
Nutrition
Physical Activity/Fitness
Nutrition
Nutrition
50%
15%
Oral Health
Oral health status in 3rd graders, caries experience
Oral health status in 3rd graders, untreated caries
Oral health status in 3rd graders, dental sealants
Oral health status in 3rd graders, last dental visit
Oral health status in 3rd graders, insurance coverage
Oral health status in 3rd graders, regular source of dental care
Physical Activity and Fitness
% of adults with regular and sustained physical activity
% of adults with no leisure time physical activity
Respiratory Diseases
Pediatric (0-4 years) asthma hospitalizations
Asthma hospitalizations (0-17 years)
Asthma hospitalizations (5-64 years)
Asthma hospitalizations (65+ years)
Asthma hospitalizations (Total)
% of adults ever have asthma
% of adults now have asthma
Asthma mortality
COPD mortality
COPD hospitalizations
Source: http://www.health.state.ny.us/nysdoh/chac/chds.htm
5% of low income children
42% children aged 6 to 8 years
21% children aged 6 to 8 years
50% children aged 6 to 8 years
56% visited in the previous year
Physical Activity/Fitness
Childhood/Adolescence
Childhood/Adolescence
Chronic Conditions
Chronic Conditions
Chronic Conditions
30% of adults aged 18 years and older
20% adults aged 18 years and older
25 per 10,000
7.7 per 10,000
11 per 10,000
Chronic Conditions
60 per 100,000
66
CHA Data Requirements Available at
http://www.health.state.ny.us/nysdoh/chac/chds.htm
Community Health Assessment
Section One (Populations at Risk)
STD
Rates of early syphilis (15-19 years)
Gonorrhea (15-19 years)
Chlamydia (15-24 years, male and female)
Website Data Section
Healthy People 2010 Goal
Sex. Trans. Diseases
Sex. Trans. Diseases
19.3 per 100,000
19.1 per 100,000
19.1 per 100,000
Substance Abuse
Cirrhosis mortality
Adult binge drinking
Teen binge drinking
Chronic Conditions
Substance Abuse
Substance Abuse
4.2 per 100,000
Tobacco
% of adults smoking cigarettes
Youth smoking
Tobacco Use
Tobacco Use
12% of adults
16% of adolescents
Vision and Hearing
Pediatric (0-4 years) otitis media hospitalizations
Childhood/Adolescence
Source: http://www.health.state.ny.us/nysdoh/chac/chds.htm
67
Glossary
•
•
•
•
•
•
•
•
•
•
•
•
Adjusted: Altered to accommodate certain requirements or bring into a proper relation
Confidence Interval: An interval of plausible values of the true rate, constructed using the
sample and its corresponding standard error, given the data that was observed
Incidence: The number of new cases of disease occurring in a population during a defined
time interval
Metric: A measurement
Morbidity: The relative incidence of a particular disease
Mortality: The ratio of deaths in an area to the population of that area; usually expressed
as “per 1,000 per year” or “per 100,000 per year”
Natality: The ratio of births to the general population; aka the birth rate
Prevalence: The ratio of the number of cases of a disease present in a population at a
specified time, and the number of individuals in the population at that specified time
Random error: Changes in the environment that cause observed rates to deviate from the
true rate. The source of deviation from the truth.
Standard Deviation: A statistic used as a measure of the dispersion or variation in a
distribution
Standardization: Methods for comparing rates in different populations while effectively
holding constant such characteristics as age, race, etc.
Standard Error: A function of the standard deviation, used for estimating confidence
interval
68
Course Evaluation
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•
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•
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Technology aided in the learning process
Opportunities for Improvement
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