shapchartbook me may2011

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MaineSHAP Grantee Chartbook

Health Insurance Coverage Estimatesfrom the 2009 American Community Survey (ACS)

Prepared for:

State Health Access Program (SHAP)

Last Updated: May 13, 2011



May 13, 2011 www.shadac.org i

Maine SHAP Grantee Chartbook

This chartbook was prepared for the U.S. Department of Health and Human Services Health

Resources and Services Administration’s State Health Access Program (SHAP) by the State

Health Access Data Assistance Center (SHADAC).

5600 Fishers Lane

Rockville, MD 20857

HRSA Contact Person

Michelle Herzog

Ph. 301-443-0650

Email. [email protected]

2221 University Ave SE, Suite 345

Minneapolis, MN 55414

Ph. 612-624-4802

Fax. 612-624-1493


www.shadac.org/shap

Maine SHAP Grantee Organization: State of Maine, Governor’s Office of Health Policy

Project Director

Karynlee Harrington

Ph. 207-287-9900


mailto:[email protected]










May 13, 2011 www.shadac.org ii


Table of Contents Page

Introduction .................................................................................................................................................. 1

Summary Statistics ........................................................................................................................................ 1

Exhibit 1: Any Source of Health Insurance Coverage by Poverty Level, Age 0-64, ACS

2009 .......................................................................................................................................................... 1

Maps and Data Tables ................................................................................................................................... 2

Exhibit 2.1: Sub-State Uninsurance Estimates, Age 0-64, ACS 2009 ....................................................... 3

Exhibit 2.2: Demographic Profile by Source of Health Insurance Coverage, Age 0-64,

ACS 2009 ................................................................................................................................................... 4

Exhibit 2.3: Sub-State Uninsurance Estimates, Age 0-64, <200% FPL, ACS 2009 .................................... 5


<200% FPL, ACS 2009 ............................................................................................................................... 6

Exhibit 2.5: Sub-State Uninsurance Estimates, Age 0-64 by Federal Poverty Level(FPL), ACS 2009 ......................................................................................................................................... 7

Exhibit 3.1: Sub-State Uninsurance Estimates, Age 0-18, ACS 2009 ....................................................... 8


ACS 2009 ................................................................................................................................................... 9

Exhibit 3.3: Sub-State Uninsurance Estimates, Age 0-18, <200% FPL, ACS 2009 .................................. 10


<200% FPL, ACS ...................................................................................................................................... 11

Exhibit 3.5: Sub-State Uninsurance Estimates, Age 0-18 by Federal Poverty Level

(FPL), ACS 2009 ....................................................................................................................................... 12Exhibit 4.1: Sub-State Uninsurance Estimates, Age 19-64, ACS 2009 ................................................... 13


ACS 2009 ................................................................................................................................................. 14

Exhibit 4.3: Sub-State Uninsurance Estimates, Age 19-64, <200% FPL, ACS 2009 ................................ 15


<200% FPL, ACS ...................................................................................................................................... 16

Exhibit 4.5: Sub-State Uninsurance Estimates, Age 19-64 by Federal Poverty Level

(FPL), ACS 2009 ....................................................................................................................................... 17

Appendix A. Technical Assistance Available from SHADAC ....................................................................... 18

Appendix B. Data Source ............................................................................................................................ 19

Appendix C. Metro Area Sub-state (PUMA) Maps ..................................................................................... 20

Appendix D. Maine Map of Major Cities .................................................................................................... 22

Appendix E. Maine Map of County Boundaries ......................................................................................... 23



May 13, 2011 www.shadac.org 1


Introduction

This chartbook of health insurance coverage estimates is designed to be an easily accessed resource for

State Health Access Program (SHAP) grantees. Estimates for key population groups within your state

are provided in summary map format, with detailed tables for reference. Data provided in thischartbook are from the 2009 American Community Survey (ACS).

Your chartbook includes the following information for your state:

Maps of uninsurance estimates for children and adults, as well as children and adults under

200% FPL

Tables of health insurance coverage estimates for the above mentioned population groups, with

variance information

County-level estimates of uninsurance

Demographic profiles of state populations

Summary Statistics

Any source of health insurance coverage for Maine is shown in Exhibit 1. In 2009, 87.9% of the total

population age 0-64 had health insurance coverage. Two thirds (66.5%) had private coverage, while

26.1% reported having government coverage. Among individuals under 200% of the Federal Poverty

Level (FPL), 83.7% had insurance, with 31.0% having private coverage, and 60.1% having government

coverage.

Exhibit 1: Any Source of Health Insurance Coverage by Poverty Level, Age 0-64, ACS 2009

Source: U.S. Census Bureau, 2009 American Community Survey.

Note: Those who report multiple types of insurance coverage (i.e., private or public) are included

in each category; therefore, totals may add to more than 100 percent.

12.1%

87.9%

66.5%

26.1%

16.3%

83.7%

31.0%

60.1%

0%

20%

40%

60%

80%

100%

Uninsured Insured Private Coverage Government

Coverage

Total <200% FPL





Maps and Data Tables

Detailed uninsurance estimates begin with Exhibit 2.1. Each subpopulation is shown as a map, followed

by a detailed table. The estimates in the tables provide percent and standard error (for calculation of

confidence intervals). Additional subgroup estimates are available upon request.





Exhibit 2.1: Sub-State Uninsurance Estimates, Age 0-64, ACS 2009


* Statistically different from the state uninsurance estimate for people age 0-64 (12.1%).

Note: Sub-state areas are typically collections of counties and reflect the lowest level of geography available for a single year of

ACS data. In most metro areas sub-county estimates are available.





Exhibit 2.2: Demographic Profile by Source of Health Insurance Coverage, Age 0-64, ACS 2009

Definitions: % = Percent; SE = Standard Error

Note: Counts are presented in thousands.


Population Uninsured Insured PrivateCoverage

GovernmentCoverage

(000) % SE % SE % SE % SE

Race and Ethnic i ty

Hispanic 15 9.6 3.52 90.4 3.52 52.3 7.13 40.8 7.10

White Alone 1,030 12.1 0.57 87.9 0.57 68.0 0.96 24.7 0.93

Black Alone 16 6.3 3.25 93.7 3.25 29.6 9.70 67.6 10.11

Asian Alone 11 10.9 5.25 89.1 5.25 81.6 5.26 13.2 4.47

Mult ip le/other

non-Hispanic32 17.7 4.49 82.3 4.49 38.1 4.84 50.2 5.65

Tota l 1,104 12.1 0.57 87.9 0.57 66.5 0.98 26.1 0.96

Ag e0-18 292 5.8 0.77 94.2 0.77 60.0 1.80 39.1 1.83

19-24 113 23.2 2.03 76.8 2.03 56.3 2.41 22.5 2.04

25-44 302 14.9 1.03 85.1 1.03 65.3 1.44 24.1 1.31

45-64 397 11.4 0.71 88.6 0.71 75.1 1.00 19.1 0.88

Tota l 1,104 12.1 0.57 87.9 0.57 66.5 0.98 26.1 0.96

Poverty Level

0 -99% FPL 219 16.6 1.39 83.4 1.39 21.9 1.79 66.6 2.09

100-199% FPL 129 15.8 1.78 84.2 1.78 46.6 3.14 49.0 3.19

200-399% FPL 371 15.2 1.18 84.8 1.18 74.9 1.45 14.5 1.26

400%+ FPL 359 5.4 0.57 94.6 0.57 92.0 0.75 5.1 0.61

Tota l 1,078 12.3 0.58 87.7 0.58 66.4 0.97 26.1 0.96

Se x

Male 544 13.9 0.75 86.1 0.75 65.5 1.10 26.1 1.05

Female 560 10.3 0.65 89.7 0.65 67.4 1.12 26.1 1.14

Tota l 1,104 12.1 0.57 87.9 0.57 66.5 0.98 26.1 0.96

Work Status

Not work ing 152 11.1 1.11 88.9 1.11 42.2 1.86 57.0 1.86

Part -t ime 179 17.3 1.22 82.7 1.22 64.5 1.61 21.9 1.46

Ful l - t ime 500 14.1 0.82 85.9 0.82 78.9 0.95 10.4 0.70

Tota l 830 14.2 0.63 85.8 0.63 69.0 0.87 21.4 0.78





Exhibit 2.3: Sub-State Uninsurance Estimates, Age 0-64, <200% FPL, ACS 2009


* Statistically different from the state uninsurance estimate for people age 0-64 under 200% FPL (16.3%).







Exhibit 2.4: Demographic Profile by Source of Health Insurance Coverage,

Age 0-64, <200% FPL, ACS 2009

Definitions: % = Percent; SE = Standard ErrorNote: Counts are presented in thousands.

* Sample size for this subpopulation is not sufficient to provide an estimate.


Population Uninsured Insured

Private

Coverage

Government

Coverage(000) % SE % SE % SE % SE


Hispanic* 7 8.2 3.70 91.8 3.70 19.2 7.55 76.9 7.71

White Alone 313 16.6 1.09 83.4 1.09 32.5 1.84 58.7 1.85

Black Alone* 11 5.7 3.82 94.3 3.82 13.7 7.96 83.1 8.84

Asian Alone* 3 -- -- -- -- -- -- -- --

Mult ip le/other

non-Hispanic15 21.5 7.99 78.5 7.99 13.5 4.06 69.5 7.97

Tota l 348 16.3 1.12 83.7 1.12 31.0 1.76 60.1 1.81

Ag e

0-18 118 6.5 1.32 93.5 1.32 27.4 2.72 73.9 2.61

19-24 42 22.6 3.11 77.4 3.11 33.9 4.16 47.1 4.25

25-44 98 19.6 2.07 80.4 2.07 31.0 2.82 57.2 2.81

45-64 91 22.6 1.86 77.4 1.86 34.5 2.21 51.3 2.33

Tota l 348 16.3 1.12 83.7 1.12 31.0 1.76 60.1 1.81

Poverty Level

0 -99% FPL 219 16.6 1.39 83.4 1.39 21.9 1.79 66.6 2.09

100-199% FPL 129 15.8 1.78 84.2 1.78 46.6 3.14 49.0 3.19

200-399% FPL -- -- -- -- -- -- -- -- --

400%+ FPL -- -- -- -- -- -- -- -- --

Tota l 348 16.3 1.12 83.7 1.12 31.0 1.76 60.1 1.81Se x

Male 161 18.9 1.57 81.1 1.57 30.6 2.13 58.6 2.17

Female 187 14.1 1.26 85.9 1.26 31.4 1.98 61.3 2.11

Tota l 348 16.3 1.12 83.7 1.12 31.0 1.76 60.1 1.81

Work Status

Not work ing 86 11.9 1.50 88.1 1.50 23.3 2.25 73.9 2.28

Part -t ime 63 23.2 2.37 76.8 2.37 33.9 3.04 47.1 3.14

Ful l - t ime 86 28.9 2.40 71.1 2.40 42.4 2.76 36.0 2.66

Tota l 235 21.1 1.29 78.9 1.29 33.1 1.72 52.9 1.77





Exhibit 2.5: Sub-State Uninsurance Estimates, Age 0-64 by Federal Poverty Level (FPL), ACS 2009

Al l PovertyLevels

<200% FPL

% S E % S E

CountySub-state

area

Cumber land (part ) , York (part ) 00100 9 .7 1 .40 14 .5 3 .37

Cumber land (part ) 00200 12 .2 1 .96 16 .1 3 .61


Cumber land (part ) , L inco ln , Sagadahoc 00400 10 .5 1 .98 14 .3 3 .95

Hancock, Knox, Waldo (part ) 00500 16 .0 2 .04 20 .5 3 .54

Kennebec 00600 11 .0 2 .07 14 .7 3 .29

Androscoggin 00700 14 .1 2 .50 19 .6 6 .36

Frankl in , Oxford , Somerset 00800 16 .0 2 .08 18 .2 3 .35

Penobscot , P iscataquis , Waldo (part ) 00900 10 .4 1 .20 15 .8 2 .33

Aroostook, Washington 01000 14 .4 1 .68 15 .3 2 .53


Sub-state areas (also called PUMAs, or Public Use Microdata Areas) are typically collections of counties and reflect the lowestlevel of geography available for a single year of ACS data. In most metro areas sub-county estimates are available. See

Appendix C for maps of metro areas that have more than one sub-state area.

* Statistically different from the state uninsurance estimate for population group (Age 0-64, 12.1%; Age 0-64 <200% FPL,

16.3%).








No sub-state areas are statistically different from the state uninsurance estimate for people age 0-18 (5.8%).










* Sample size for this subpopulation is not sufficient to provide an estimate.


Population Uninsured Insured PrivateCoverage

GovernmentCoverage

(000) % SE % SE % SE % SE


Hispanic* 7 -- -- -- -- -- -- -- --

White Alone 259 5.9 0.80 94.1 0.80 62.9 1.74 36.2 1.78

Black Alone* 9 -- -- -- -- -- -- -- --

Asian Alone* 3 -- -- -- -- -- -- -- --

Mult ip le/other

non-Hispanic15 8.5 5.17 91.5 5.17 31.4 6.45 64.5 7.31

Tota l 292 5.8 0.77 94.2 0.77 60.0 1.80 39.1 1.83

Ag e0-18 292 5.8 0.77 94.2 0.77 60.0 1.80 39.1 1.83

19-24 -- -- -- -- -- -- -- -- --

25-44 -- -- -- -- -- -- -- -- --

45-64 -- -- -- -- -- -- -- -- --

Tota l 292 5.8 0.77 94.2 0.77 60.0 1.80 39.1 1.83

Poverty Level

0 -99% FPL 75 6.4 1.69 93.6 1.69 18.4 2.83 79.4 2.89

100-199% FPL 43 6.6 2.12 93.4 2.12 43.1 5.02 64.3 4.90

200-399% FPL 95 7.6 1.55 92.4 1.55 79.4 2.33 17.5 2.35

400%+ FPL 65 2.2 0.66 97.8 0.66 92.6 1.78 6.1 1.72

Tota l 278 5.9 0.79 94.1 0.79 60.4 1.79 38.8 1.85

Se x

Male 147 6.7 1.07 93.3 1.07 59.8 2.10 38.7 2.18

Female 146 5.0 0.91 95.0 0.91 60.1 2.25 39.6 2.28

Tota l 292 5.8 0.77 94.2 0.77 60.0 1.80 39.1 1.83

Work Status

Not work ing* 4 -- -- -- -- -- -- -- --

Part -t ime 11 5.3 2.29 94.7 2.29 84.6 4.04 14.0 3.91

Ful l - t ime* 3 -- -- -- -- -- -- -- --

Tota l 19 7.5 2.25 92.5 2.25 78.5 4.08 19.1 3.85







^ Data are missing for sub-state areas with fewer than 50 observations.

No sub-state areas are statistically different from the state uninsurance estimate for people age 0-18 under 200% FPL (6.5%).








Age 0-18, <200% FPL, ACS 2009



*Sample size for this subpopulation is not sufficient to provide an estimate.


Population Uninsured InsuredPrivate

Coverage

Government

Coverage

(000) % SE % SE % SE % SE


Hispanic* 4 -- -- -- -- -- -- -- --

White Alone 99 6.2 1.30 93.8 1.30 29.6 2.96 72.9 2.77

Black Alone* 6 -- -- -- -- -- -- -- --

Asian Alone* 1 -- -- -- -- -- -- -- --

Mult ip le/other

non-Hispanic8 13.9 9.18 86.1 9.18 14.9 5.79 76.0 9.64

Tota l 118 6.5 1.33 93.5 1.33 27.4 2.72 73.9 2.61Ag e

0-18 118 6.5 1.33 93.5 1.33 27.4 2.72 73.9 2.61

19-24 -- -- -- -- -- -- -- -- --

25-44 -- -- -- -- -- -- -- -- --

45-64 -- -- -- -- -- -- -- -- --

Tota l 118 6.5 1.33 93.5 1.33 27.4 2.72 73.9 2.61

Poverty Level

0 -99% FPL 75 6.4 1.69 93.6 1.69 18.4 2.83 79.4 2.89

100-199% FPL 43 6.6 2.12 93.4 2.12 43.1 5.02 64.3 4.90

200-399% FPL -- -- -- -- -- -- -- -- --

400%+ FPL -- -- -- -- -- -- -- -- --

Tota l 118 6.5 1.33 93.5 1.33 27.4 2.72 73.9 2.61

Se x

Male 56 7.2 1.91 92.8 1.91 27.9 3.36 72.2 3.39

Female 62 5.8 1.63 94.2 1.63 26.9 3.37 75.4 3.20

Tota l 118 6.5 1.33 93.5 1.33 27.4 2.72 73.9 2.61

Work Status

Not work ing* 2 -- -- -- -- -- -- -- --

Part -t ime* 2 -- -- -- -- -- -- -- --

Ful l - t ime* 1 -- -- -- -- -- -- -- --

Tota l 4 -- -- -- -- -- -- -- --






Al l PovertyLevels

<200% FPL

% S E % S E

CountySub-state

area


Cumber land (part ) 00200 3 .3 2 .42 - - - -

Cumber land (part ) , York (part ) 00300 3 .6 1 .47 - - - -

Cumber land (part ) , L inco ln , Sagadahoc 00400 2 .6 1 .63 - - - -


Kennebec 00600 5 .3 2 .20 - - - -

Androscoggin 00700 10 .3 3 .65 11 .3 7 .03





No sub-state areas are statistically different from the state uninsurance estimate for the population group (Age 0-18, 5.8%; Age0-18 <200% FPL, 6.5%).

Sub-state areas (also called PUMAs, or Public Use Microdata Areas) are typically collections of counties and reflect the lowest

level of geography available for a single year of ACS data. In most metro areas sub-county estimates are available. See


-- Data are suppressed for sub-state areas with fewer than 50 observations.








* Statistically different from the state uninsurance estimate for people age 19-64 (14.4%).












Population Uninsured InsuredPrivate

Coverage

Government

Coverage(000) % SE % SE % SE % SE


Hispanic 9 17.2 5.84 82.8 5.84 56.5 7.66 29.6 6.76

White Alone 771 14.1 0.65 85.9 0.65 69.7 0.89 20.8 0.80

Black Alone* 7 -- -- -- -- -- -- -- --

Asian Alone* 8 -- -- -- -- -- -- -- --

Mult ip le/other

non-Hispanic17 25.8 5.07 74.2 5.07 44.0 5.65 37.4 6.20

Tota l 812 14.4 0.64 85.6 0.64 68.8 0.88 21.5 0.79

Ag e

0-18 -- -- -- -- -- -- -- -- --

19-24 113 23.2 2.03 76.8 2.03 56.3 2.41 22.5 2.04

25-44 302 14.9 1.03 85.1 1.03 65.3 1.44 24.1 1.31

45-64 397 11.4 0.71 88.6 0.71 75.1 1.00 19.1 0.88

Tota l 812 14.4 0.64 85.6 0.64 68.8 0.88 21.5 0.79

Poverty Level

0 -99% FPL 144 21.9 1.66 78.1 1.66 23.7 1.92 60.0 2.16

100-199% FPL 86 20.3 2.02 79.7 2.02 48.3 2.85 41.4 2.86

200-399% FPL 275 17.8 1.32 82.2 1.32 73.4 1.50 13.4 1.20

400%+ FPL 294 6.1 0.65 93.9 0.65 91.9 0.75 4.8 0.55

Tota l 800 14.5 0.65 85.5 0.65 68.5 0.89 21.7 0.80Se x

Male 397 16.6 0.88 83.4 0.88 67.7 1.09 21.5 0.99

Female 415 12.2 0.73 87.8 0.73 70.0 1.02 21.4 0.96

Tota l 812 14.4 0.64 85.6 0.64 68.8 0.88 21.5 0.79

Work Status

Not work ing 148 11.2 1.13 88.8 1.13 41.2 1.84 58.1 1.84

Part -t ime 168 18.1 1.28 81.9 1.28 63.1 1.67 22.4 1.53

Ful l - t ime 496 14.1 0.82 85.9 0.82 79.0 0.95 10.2 0.70

Tota l 812 14.4 0.64 85.6 0.64 68.8 0.88 21.5 0.79







* Statistically different from the state uninsurance estimate for people age 19-64 under 200% FPL (21.3%).








Age 19-64, <200% FPL, ACS 2009

Definitions: % = Percent; SE = Standard ErrorNote: Counts are presented in thousands.



Population Uninsured Insured

Private

Coverage

Government

Coverage

(000) % SE % SE % SE % SE


Hispanic* 3 -- -- -- -- -- -- -- --

White Alone 213 21.4 1.32 78.6 1.32 33.8 1.78 52.1 1.83

Black Alone* 5 -- -- -- -- -- -- -- --

Asian Alone* 2 -- -- -- -- -- -- -- --

Mult ip le/other

non-Hispanic7 29.6 8.58 70.4 8.58 11.9 5.22 62.6 8.94

Tota l 230 21.3 1.31 78.7 1.31 32.9 1.72 53.0 1.78

Ag e

0-18 0 -- -- -- -- -- -- -- --

19-24 42 22.6 3.11 77.4 3.11 33.9 4.16 47.1 4.25

25-44 98 19.6 2.07 80.4 2.07 31.0 2.82 57.2 2.81

45-64 91 22.6 1.86 77.4 1.86 34.5 2.21 51.3 2.33

Tota l 230 21.3 1.31 78.7 1.31 32.9 1.72 53.0 1.78

Poverty Level

0 -99% FPL 144 21.9 1.66 78.1 1.66 23.7 1.92 60.0 2.16

100-199% FPL 86 20.3 2.02 79.7 2.02 48.3 2.85 41.4 2.86

200-399% FPL -- -- -- -- -- -- -- -- --

400%+ FPL -- -- -- -- -- -- -- -- --

Tota l 230 21.3 1.31 78.7 1.31 32.9 1.72 53.0 1.78

Se x

Male 105 25.0 2.03 75.0 2.03 32.0 2.27 51.4 2.39

Female 125 18.2 1.47 81.8 1.47 33.7 2.00 54.4 2.12

Tota l 230 21.3 1.31 78.7 1.31 32.9 1.72 53.0 1.78

Work Status

Not work ing 84 12.0 1.52 88.0 1.52 22.6 2.14 74.6 2.19

Part -t ime 61 23.5 2.43 76.5 2.43 33.8 3.11 47.2 3.21

Ful l - t ime 85 29.1 2.41 70.9 2.41 42.5 2.77 35.8 2.67

Tota l 230 21.3 1.31 78.7 1.31 32.9 1.72 53.0 1.78






Al l PovertyLevels

<200% FPL

% S E % S E

CountySub-state

area


Cumber land (part ) 00200 14 .9 2 .16 21 .4 4 .48


Cumber land (part ) , L inco ln , Sagadahoc 00400 13 .1 2 .43 18 .2 4 .46


Kennebec 00600 13 .0 2 .61 19 .4 4 .39

Androscoggin 00700 15 .7 2 .49 25 .9 6 .54




Definitions: % = Percent; SE = Standard ErrorSub-state areas (also called PUMAs, or Public Use Microdata Areas) are typically collections of counties and reflect the lowest

level of geography available for a single year of ACS data. In most metro areas sub-county estimates are available. See


No sub-state areas are statistically different from the state uninsurance estimate for population group (Age 19-64, 14.4%; Age

19-64 <200% FPL, 21.3%).






Appendix A. Technical Assistance Available from SHADAC

SHADAC has a contract with Health Resources and Services Administration (HRSA) at Health and Human

Services (HHS) to provide technical assistance to states that have received State Health Access Program

(SHAP) grants. This includes support for data collection, analysis and evaluation related to their SHAP

project work. A summary of assistance is provided below. Questions and requests can be directed to

Elizabeth Lukanen at 612-626-1537 or [email protected].

Data Assistance

Several SHADAC resources are available to help SHAP grantees access and utilize data relating to health

insurance coverage estimates, access to care, and understanding available data-specific technical

assistance resources. Resources include: SHADAC’s Data Center, an online table and chart generator;

issue briefs and technical briefs; and information on how to access microdata.

Web page: http://www.shadac.org/shap/technical-assistance/data

HRSA Benchmarks

SHADAC will also assist states in reporting HSRA benchmark data.

Web page: http://www.shadac.org/shap/technical-assistance/HRSA-Benchmarks

Evaluation

SHADAC staff are available to help SHAP grantees refine and implement evaluation plans, to ensure the

fidelity and success of SHAP-funded programs.

Web page: http://www.shadac.org/shap/technical-assistance/evaluations

Surveys

SHADAC has a variety of resources to help SHAP grantees conduct survey research and apply the results

to relevant audiences. SHADAC’s technical assistance can facilitate the sharing of information and

expertise among grantees, help policy makers understand the unique characteristics of state sub-

populations, and provide assistance in developing survey tools and methods.

Web page: http://www.shadac.org/shap/technical-assistance/surveys

State Reform Research and Strategies

SHADAC has provided evaluative information on health reform initiatives in states participating in the

State Health Access Reform Evaluation (SHARE) program. Many of these evaluations provide descriptive

information that may be useful for SHAP grantees.

Web page: http://www.shadac.org/shap/technical-assistance/ state-reform-research-and-strategies




http://www.shadac.org/shap/technical-assistance/data


http://www.shadac.org/shap/technical-assistance/HRSA-Benchmarks


http://www.shadac.org/shap/technical-assistance/evaluations


http://www.shadac.org/shap/technical-assistance/surveys


http://www.shadac.org/shap/technical-assistance/%20state-reform-research-and-strategies












Appendix B. Data Source

Source: U.S. Census Bureau, 2009 American Community Survey (ACS). Calculations by SHADAC.

Estimates for the ACS exclude military but include non-institutionalized group quarters such as

college/university housing, group homes intended for adults, residential treatment facilities for adults,workers’ group living quarters and Job Corps centers, and religious group quarters.

Population counts are presented in thousands.

Definitions: '%' = Percent; 'SE' = Standard error as a percent. Confidence intervals can be calculated

from the standard errors; for example, the 95% confidence interval is ±(1.96 * SE).

Insurance coverage note: Listed Medicaid rates include SCHIP and state-specific public programs. Those

who report multiple types of insurance coverage (i.e., private or public) are included in each category;

therefore, row totals may add to more than 100 percent. Active duty military coverage (e.g., TRICARE) is

considered employer-sponsored insurance, while VA coverage is considered government coverage.

ACS methodology note: The ACS asks respondents about their health insurance coverage at the time of

the interview.

For technical documentation on the ACS please visit http://www.shadac.org/content/acs-info-and-

resources.

http://www.shadac.org/content/acs-info-and-resources










Appendix C. Metro Area Sub-state (PUMA) Maps

(Source: http://www2.census.gov/geo/maps/puma/puma2k/me_puma5.pdf)





(Source: http://www2.census.gov/geo/maps/puma/puma2k/me_puma5.pdf)





Appendix D. Maine Map of Major Cities

Source: U.S. Census Bureau.



May 13 2011 www shadac org 23


Appendix E. Maine Map of County Boundaries

Source: U.S. Census Bureau.

shapchartbook me may2011

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