Post on 25-Jan-2017
Use of GIS technology to inform planning efforts through visualization of community level data in Hawaii
Presented byDonald Hayes, MD MPHCDC Assigned EpidemiologistHawaii Department of HealthFamily Health Services DivisionOct 16, 2015
Acknowledgments Pat Heu and Linda Chock, FHSD Chief -- acting Annette Mente, FHSD Planner Catherine Sorensen, FHSD Office of Primary Care
and Rural Health Division of Reproductive Health, CDC Maternal and Child Health Bureau, HRSA
Use of Data Increase awareness about particular
issue Grant applications Identify new research questions Identify Gaps in the data Prepare for legislation and policy work Program Evaluation Where should limited funds get
distributed
Some datasets in Hawaii
Birth Certificate
Death Certificate
Behavioral Risk Factor Surveillance System
Pregnancy Risk Assessment Monitoring SurveyYouth Risk Behavior Surveillance
Youth Tobacco SurveyBirth Defects
Women, Infant, and Children
Newborn Metabolic Screening
Newborn Hearing Screening
Early Intervention Services
Hawaii Household Survey
JABSOM National children studySchool Data
Emergency room data
EMS Transport Data
Injury Data
Cancer Registry
Fetal Deaths
Family Planning
Medicaid
Children with Special Health Needs
Breastfeeding survey
Perinatal Support Services
Child Death Review
ImmunizationEmergency Preparedness
Primary Care Contracts
Health Insurance Claims Data
Medical Outpatient Records
Electronic Health Records
Some FHSD Data Products Primary Care Data Book PRAMS Trend and County Reports FHSD Profiles Health Status of Children in Hawaii Perinatal and Title V Fact Sheets Birth Defects Surveillance Reports Journal Articles– Child Obesity, Adverse Birth Outcomes, Postpartum
Depression, Intimate Partner Violence, Breastfeeding, Physician Screening, Chronic Disease and Birth Outcomes, Adverse Childhood Events, Oral Health Services Utilization…..
Most reports are online at hawaii.gov websiteAll DOH and older FHSD: http://health.hawaii.gov/about/publications/Starting 2015, but still on all DOH: http://health.hawaii.gov/FHSD/publications/
Evaluation and Feedbackhttp://health.hawaii.gov/fhsd/evaluation-forms-2
Primary Care Needs Assessment (PCNA) Data Book Health and socio-economic indicators by
Community in Hawaii Multiple Data Sources
Census, ACS Vital Statistics BRFSS Hospital Discharge
Tables/Maps highlight differences Need Community Involvement
Background 1990-1994 Primary Care Access Plan Present Population Based Surveillance Data by
Community Improve awareness and discussion Facilitate data to action Initial MCH focus, starting in 2005 expansion to reflect
primary care
Diverse Audience including Health Policy Makers Legislators Planners Public
Distribution Hard Copy Online PDF
Summary Overview Summary Tables
(all indicators)
Chapter 1 Introduction
Chapter 2 Primary Care
Office Designations
Chapters 3-8 Indicators
Primary Care Areas Defined
• More detail on 3 largest areas (Ewa, E. Honolulu, W. Honolulu)- 11 new areas
• 2010 Census Tract Changes
Hospital Locations
Community Health Centers
Health Professional Shortage Areas
Methodology Census tract data aggregated into 35
communities in the State of Hawaii, County and State level.
For BRFSS data, Zip Codes converted to areas based on Missouri Data Center Zip code to census tract estimates
Hospital discharge data, priority was census tract information, but conversion used based on zip code for those without
SAS, SUDAAN software was used to create an Excel document for use in ArcGIS
2009 Version
2012 Version
2009 vs. 2012
Proportion of Population 65 years and over State: 14.0%
[13.3% in 2000]
7.7% in Mililani 8.1% in Kapolei-Makakilo
19.7% in Waikïkï-Pälolo 20.1% in Hawai‘i Kai-
Kaimuki
Socio-economic Indicators (Chapter 3)
Ratio = 2.6
Proportion of Population Native Hawaiian State: 21.3%
[19.8% in 2000]
11.3% in Waikïkï-Pälolo 11.3% in Airport-Moanalua
57.4% Häna 58.5% in Wai‘anae 61.8% in Moloka‘i
Ratio = 5.5
Proportion of Adult Population Uninsured State: 7.1%
3.5% in Hawai‘i Kai-Kaimuki 3.8% in McCully-Makiki
14.8% in Ka‘ū 15.7% in South Kona 19.4% in Häna
Ratio = 5.5
Proportion of Children in Households Receiving Assistance State: 17.2%
4.2% in Hawai‘i Kai-Kaimuki
4.7% in Lähainä
43.0% in Puna 49.2% in Wai‘anae
Ratio = 11.7
Infant Mortality Rate (per 1,000 live births)
State: 6.0
3.9 in Makawao 4.2 in Wailuku 4.2 in Köloa
10.1 in Wai‘anae 12.4 in North Kohala
Maternal and Infant Health (Chapter 4)
Ratio = 3.2
Proportion of Adults Who Are Obese State: 21.9%
13.2% in Hawai‘i Kai-Kaimuki
13.8% in Waialua
37.6% in Moloka‘i 43.5% in Wai‘anae
Morbidity-Risk Factors (Chapter 5)
Ratio = 3.3
Disease of the Heart Mortality Rate (per 100,000)
State: 135.2
72.3 in Mililani 97.4 in Hawai‘i Kai-
Kaimuki 109.1 in Hänalei
231.3 in Häna 260.4 in Wai‘anae
Mortality (Chapter 6)
Ratio = 3.6
Proportion of Adults with No Teeth Cleaning Within Past Year
State: 28.7%
18.4% in Hawai‘i Kai-Kaimuki
22.4% in Wahiawä 22.5% in McCully-Makiki
43.8% in Puna 47.6% in Wai‘anae 49.3% in Ka‘ū
Adult Oral Health (Chapter 7)
Ratio = 2.7
Proportion of Admissions with a Substance Related Disorder State: 8.9%
4.3% in Waipahu 4.5% in Mililani 5.0% in Hickam-Pearl City
13.7% in South Kona 13.8% in North Kona 14.2% in Häna 17.0% in Lähainä
Mental Health and Substance Related Admissions (Chapter 8)
Ratio = 4.0
Example 1: Grant Application ACA Grant For Home Visiting Announced
Portion related to Needs Assessment (NA) NA a requirement for Title V agencies
Portion of NA completed by use of data from PCNA Data Book for identification of high risk communities (poverty, low birth weight, infant mortality, no high school diploma, unemployment, etc….)
Data contributed to multi-million dollar grant award
Example 2: Data and Budget CutsReduction in Primary Care Contracts in
response to executive memo FHSD Recommendation made to not eliminate or
drastically reduce the funding and develop contingency plans before any drastic change in funding.
Data used to justify higher risk in the areas served by the contracts (poverty, per-capita income, unemployed, no high school diploma,...)
No reduction
Example 3: Community Health Needs Assessment
Individual Hospital CHNA Data used throughout several of the hospitals CHNA to
comply with federal requirements for nonprofit hospital organizations related to ACA (to satisfy a requirement of a community health needs assessment) . Various indicators used (in addition to other data sources and outreach) including substance use and mental health hospitalizations, behavioral risk factors, socio-economic, and mortality data.
Example 4: Overlays
Department of Native Hawaiian Health, JABSOM. Assessment and Priorities for Health & Well-Being in Native Hawaiians & Other Pacific Peoples. Accessed online at http://www2.jabsom.hawaii.edu/native/comm_ulu-reports.htm
Example 5: Other known uses Journal Article referencesBook Article referencesMedical Practice Business PlanRural Health Nursing Resources
EvaluationFeedback
Paper Online
Evaluation Results Information from:
Community non-profits Government agencies Education Institutions
Use it for: Needs Assessment Planning Grant Resource/Facilities Planning
How use? Community Health Centers (CHC) need to update their needs
assessments (part of their federal grant application process) every 3 years. The PCNA data book provides valuable health information stratified by geographic regions that match up with CHC service areas. As such, the PCNA data book makes finding relevant health data so much easier and convenient.
Used specific topic information and shared as fact sheets related to division and maternal and child health priorities. This assisted in discussion with other partners and supported further partnerships and use of this book by others in the State.
Indicators selected demonstrate significant community level differences and highlight the importance of data visualization by geography. Consolidates multiple data sources into one document
How use? Use it to share information with stakeholders about community level
differences. Raises awareness and discussion of complex issues A lot of information that highlights the geographic disparities are
very useful. This resources provides comparative data across a range of topics from birth to death. It includes risk factor and socio-economic characteristics which are very useful in characterizing communities for potential grant opportunities.
Have used this in the request for information and request for proposal process in serving specific geographical areas and as reference materials for providers to use. Have incorporated in presentations for grantors on areas being served through women's, infant and maternal and child health contracts. Have referenced in discussions with public health stakeholders and collaborative planning activities. Have recommended to community stakeholders for use in their planning and other activities to serve those in need.
Ability to demonstrate service providers are located in appropriate high risk communities
Other information? Early Childhood indicators. The ability to look at an online version that allows you to
get estimates from multiple indicators for a community. What about being able to look at overlays and see if there are statistical differences/relationships between communities.
Hospitalization data, trends...Wouldn't it be great to see this on an interactive map or if it could be dumped or used with UDS mapper?
Homelessness Would like to see associations between the various indicators. For example, how
much of the heart disease deaths are due to poverty characteristics. Can these maps be interactive so I can just select a community and get a download of all the data for that particular community. I know the length of the book is a concern, but think you should consider showing these same indicators by other groups when possible (Race, education, language, insurance, employment, etc...). Thanks for the great resource and look forward to its continued evolution and usefulness. When is the next version coming out?
Although aggregating the data based on population of each district, sometimes for some of the work that we do and information that we need, stratifying it further by ethnic background in each district will be very useful for us. Also, having a group on Micronesian (or maybe just Pacific Islander without Native Hawaiian) will also be useful as these groups are one of the special populations that FQHCs serve and data on this group would be useful (although I am not sure if their sample size would be sufficient to add them as another category). It would also be useful to add new indicators that the federal government is looking more into such as prediabetes.
Closing Comments Reports have helped raise awareness of data and issues Building capacity in health department Gradually increasing comfort and skills in GIS Opportunity to look at community level indicators based
on several data sources Geographic Disparities shown
- Some may be explained by race distribution- Others may be explained by age distribution- Others may be explained by poverty- What about other factors?
Additional analyses needed Superimposing two-three maps? Controlling for age, race/ethnicity and other factors
Partners want more so it is not just a static PDF/document Next revision to PCNA currently in process
Data Management
Data Analysisand
Interpretation
Data Collection
Data Presentationand
Translation
Socio-economic Indicators (Chapter 3)• Race (2010 Census)
- Alone- Alone or in
combination
In addition to Native Hawaiian and Filipino in 2009 data book, added White, Japanese, and Chinese in 2012 data book.
Primarily Multiple Race population in Hawaii• Chinese (73% are in combination)• Native Hawaiian (72%)• Filipino (42%)• Japanese (41%)• White (40%)
Proportion of Population Filipino State: 25.1%
[22.8% in 2000]
7.0% in Hawai‘i Kai-Kaimuki
45.6% Lïhu‘e 54.4% Waipahu 63.9% Läna‘i
Socio-economic Indicators (Chapter 3)
Ratio = 9.1
Primary Care Service Areas
Proportion of Adults with High Blood Pressure State: 28.4%
11.7% in Häna 22.3% in South Kohala 22.5% in Köloa 22.6% in Lähainä
32.5% in Hilo 32.6% in Wai‘anae 35.4% in Waialua 36.7% in Lïhu‘e
Morbidity-Risk Factors (Chapter 5)
Ratio = 3.1
Stroke Mortality Rate (per 100,000) State: 38.2
22.1 in ‘Ewa-Kalaeloa 22.8 in Mililani
49.5 in Hilo 56.4 in Waimea 67.8 in Läna‘i
Mortality (Chapter 6)
Ratio = 3.1
Unintentional Injury Mortality Rate (per 100,000)
State: 28.7
10.0 in Mililani 18.4 in Hickam-Pearl City 19.3 in ‘Ewa-Kalaeloa
48.7 in South Kona 52.1 in Waialua 58.6 in Wai‘anae
Mortality (Chapter 6)
Ratio = 5.9
Proportion Admissions w/ Delirium/Dementia Disorder State: 8.4%
4.3% in Moloka‘i 4.5% in Ka‘ū
11.8% in Waikïkï-Pälolo 11.9% in McCully-Makiki 14.8% in Hawai‘i Kai-Kaimuki
Mental Health and Substance Related Admissions (Chapter 8)
Ratio = 3.4
Proportion of Households with Linguistic Isolation State: 6.2%
0.3% in Häna 0.9% in Makawao
14.4% in Ala Moana- Nu‘uanu
21.1% in Downtown-Kalihi
Ratio = 70.3
Proportion of Adults Who Smoke State: 16.1%
9.9% in Hawai‘i Kai-Kaimuki
11.0% in Hänalei
25.3% in N Kohala 25.9% in Ka‘ū 26.0% in Wai‘anae
Ratio = 2.6
Cancer Mortality Rate (per 100,000)
State: 134.7
90.2 in Häna 91.9 in Mililani 95.2 in ‘Ewa-Kalaeloa
173.1 in Waimea 177.0 in Moloka‘i 197.0 in Wai‘anae
Ratio = 2.2
Proportion of Admissions with a Mood Disorder
State: 6.1%
3.1% in Moloka‘i 3.2% in Läna‘i 3.4% in Häna
8.0% in Hänalei 9.1% in Hilo 10.9% in Puna
Ratio = 3.5
Proportion of Civilian Labor Force Unemployed State: 4.6%
2.3% in Hawai‘i Kai-Kaimuki 2.3% in ‘Ewa-Kalaeloa
9.7% in Ka‘ū 13.5% in Moloka‘i
Ratio = 5.9
Example 2: Data and Budget Cuts June 28-30, 2011: Reduction in Primary Care
Contracts in response to executive memo FHSD Recommendation made to not eliminate or drastically
reduce the funding and develop contingency plans before any drastic change in funding. Data used to justify higher risk in the areas served by the contracts. (Gordon Takaki and Pat Heu, 2011 FHSD Meeting)
July 7, 2011: No reduction
Example 2: PCNA June 2010: ACA Grant For Home Visiting
Announced Portion related to Needs Assessment (NA) NA a requirement for Title V agencies
Sept 2010: Deadline for Needs Assessment Portion of NA completed by use of data from
PCNA Data Book for identification of high risk communities(Cindy Hirai led effort).
Data contributed to multi-million dollar grant