Maryland Jurisdiction Epidemiological Profiles Chartbook
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1 Jurisdiction Epidemiological Profiles Chartbook February 13, 2014 The Statewide Epidemiological Outcomes Workgroup Department of Pharmaceutical Health Services Research University of Baltimore School of Pharmacy Saratoga Building, 12 th Floor 220 Arch Street Baltimore,
2 CONTRIBUTORS This report was compiled by the following faculty, staff, and students of the Department of Pharmaceutical Health Services Research in the University of School of Pharmacy: Linda Simoni-Wastila, BSPharm, PhD Professor and Director, SEOW Corinne Woods, BSPharm, MPH Research Pharmacist, Pharmaceutical Research Computing SEOW Project Coordinator Wendy Klein-Schwartz, PharmD Associate Professor, Poison Center Patience Moyo, BA, PhD Student Graduate Research Assistant Yu-Jung Jenny Wei, PhD Post-Doctoral Fellow Ting-Ying Jane Huang, BSPharm, PhD Candidate Graduate Research Assistant Jeanne Yang, MCP Information Systems Engineer, Pharmaceutical Research Computing Katherine Fornili, MPH, RN, CARN Assistant Professor, UMB School of Nursing ACKNOWLEDGMENTS We thank Kathleen Rebbert-Franklin, Sue Jenkins, Larry Dawson, and Virgil Boysaw and the other staff at the Alcohol and Drug Abuse Administration (ADAA) in the Department of Health and Mental Hygiene for their support and guidance on this report.
3 Table of Contents Data Sources & Considerations for Use... 1 JURISDICTION RANKINGS Alcohol-Related Inpatient Hospitalizations... 5 Alcohol-Related Emergency Department Visits... 6 Opioid-Related Inpatient Hospitalizations... 7 Opioid-Related Emergency Department Visits... 8 Treatment Admissions... 9 Alcohol... 9 Marijuana Prescription Opioids Benzodiazepines Heroin Crack/Cocaine Co-Occurring Mental Illness Co-Occurring Mental Illness by County of Patient Residence Co-Occurring Mental Illness by County Where the Treatment Facility is Located Alcohol-Impaired Crashes All Ages Aged Years Marijuana Use Past-Month Use Perceptions of Risk of Smoking Marijuana Cocaine, Past-Year Use Pain Reliever, Past-Year Non-Medical Use Illicit Drug Use Past-Month Use of Illicit Drugs Other than Marijuana Past-Year Needing but Not Receiving Treatment Alcohol Use... 26
4 Past-Month Use Past-Month Binge Drinking Past-Year Needing but Not Receiving Treatment vs Abuse or Dependence JURISDICTION FINDINGS (Jurisdiction listed in alphabetical order; Baltimore City the last.) Alcohol-Related Inpatient Hospitalizations and Emergency Department Visits Opioid-Related Inpatient Hospitalizations and Emergency Department Visits Substance Use Treatment Admissions Motor Vehicle Crashes among Residents Aged Years
5 Data Sources & Considerations for Use Data Organization: Rankings of jurisdictions on their standing on select indicators are presented first followed by jurisdictions sorted alphabetically (Baltimore City at the end) under specific data sources. Health Services Cost Review Commission (HSCRC): In, the HSCRC an independent agency is charged with regulating hospital rates for all payers and is responsible for maintaining both the inpatient and outpatient facility data sets. The inpatient dataset contains discharge medical record abstracts and billing data on each of the state's approximately 800,000 yearly inpatient admissions. Hospitals submit data to the HSCRC on a quarterly basis and the agency generates research-ready datasets for public use. Access to the research level version of the inpatient or outpatient data requires the submission of an application to the HSCRC. Data is available through Important considerations regarding HSCRC data: 1. The county indicated in the charts refers to the location of the patient s place of residence and may not be the jurisdiction in which the hospital providing service is situated. 2. The data are available at the event level rather than individual level. This means that one individual can contribute multiple observations in the data. Automated Accident Reporting System (MAARS): The MAARS data is comprised of information extracted from motor vehicle accident reports submitted by over 200 law enforcement agencies. The purpose is to provide safety professionals, public officials, the private sector, and the general public information about traffic crashes throughout. It presents data extracted from motor vehicle crash reports submitted by more than 200 law enforcement agencies to the Enhanced Automated Accident Reporting System (MAARS). All crashes resulting in a vehicle being towed away, personal injury, or fatality are reported. Crash data are recorded by the state, county, or local law enforcement officer at the scene of the reportable crash. The Central Records Division of the State Police manages MAARS and provides copies of the reports to the public for a fee. The SHA maintains the electronic crash database, and is the primary contact for distribution of raw crash data. MHSO provides summary statistics based on reports generated from SHA s database. MAARS data through 2011 was used for this report. Important considerations regarding MAARS data: 1
6 1. Impaired crashes are those with at least one driver reported to be under the influence of either 'alcohol' or both 'alcohol and drugs'. 2. Crashes with unknown/unspecified age or gender were excluded, as well as those involving drugs only. National Survey on Drug Use and Health (NSDUH): The NSDUH provides national- and statelevel data on mental health as well as the use of tobacco, alcohol and illicit drugs (including non-medical use of prescription drugs) in the United States. NSDUH is sponsored by the Substance Abuse and Mental Health Services Administration (SAMHSA), an agency of the U.S. Public Health Service within the U.S. Department of Health and Human Services. A random sample of households is selected across the United States, and a professional field interviewer makes a personal visit to each selected household. After answering a few general questions during the in-person visit by the interviewer, residents of the household may be asked to participate. Participants answer most of the interview questions in private by entering their responses directly into a computer. The survey is conducted annually, with state-level data available from , substate-level data available every 2 years from and national data available Important considerations regarding NSDUH data: With the exception of six jurisdictions (Anne Arundel County, Baltimore City, Baltimore County, Charles County, Montgomery County and Queen Anne s County), NSUDH results are reported as aggregate data with several jurisdiction grouped into substate regions. The substate regions are as follows: North Central is comprised of Carroll County and Howard County; North East is comprised Caroline County, Cecil County, Harford County, Kent County, Queen Anne s County and Talbot County; South is comprised of Calvert County, Charles County, Dorchester County, St. Mary s County, Somerset County, Wicomico County and Worcester County; West is comprised of Allegany County, Frederick County, Garrett County and Washington County. State of Automated Record Tracking (SMART): SMART data include treatment admissions from all substance use disorder treatment facilities that receive state alcohol and/or drug agency funds (including Federal Block Grant funds) for the provision of treatment for substance use disorders. SMART does not include data from private or for-profit treatment facilities, hospitals, the state correctional system (unless licensed through the state substance use disorders agency) or federal agencies (the Bureau of Prisons, the Department of Defense, and the Veterans Administration). Data elements in SMART include: reason for admission, 2
7 primary and secondary substances of use, sociodemographic information, the presence or absence of mental illness and treatment modality. Data are current through Important considerations regarding SMART data: 1. The data are based on fiscal year and not calendar year. 2. The county indicated in the charts refers to the location of the patient s place of residence and may not be the jurisdiction in which the treatment facility is situated. 3. The data are available at the event level rather than individual level. This means that one individual can contribute multiple observations in the data. 4. The charts show the estimated rate of admissions for a specific primary substance problem per 1000 residents in each jurisdiction. 3
8 JURISDICTION RANKINGS 4
9 Alcohol-Related Inpatient Hospitalizations Data Source: Health Services Cost Review Commission (HSCRC) Rate of Alcohol-Related Hospitalizations in 2012 per 1000 Events Baltimore City Allegany Cecil Frederick Kent Dorchester Worcester Baltimore County Calvert Harford Queen Anne's Talbot Anne Arundel Prince George's Washington Carroll Wicomico Charles Caroline Montgomery St Mary's Somerset Garrett Howard
10 Alcohol-Related Emergency Department Visits Data Source: Health Services Cost Review Commission (HSCRC) Rate of Alcohol-Related Emergency Department Visits in 2012 per 1000 Events Baltimore City St Mary's Charles Kent Queen Anne's Calvert Allegany Talbot Anne Arundel Frederick Baltimore County Worcester Dorchester Washington Howard Caroline Montgomery Prince George's Wicomico Carroll Somerset Harford Cecil Garrett
11 Opioid-Related Inpatient Hospitalizations Data Source: Health Services Cost Review Commission (HSCRC) Rate of Opioid-Related Hospitalizations in 2012 per 1000 Events Baltimore City Cecil Frederick Baltimore County Carroll Allegany Anne Arundel Harford Queen Anne's Washington Caroline Kent Dorchester Wicomico Talbot Somerset Calvert Howard St Mary's Garrett Worcester Charles Montgomery Prince George's
12 Opioid-Related Emergency Department Visits Data Source: Health Services Cost Review Commission (HSCRC) Rate of Opioid-Related Emergency Department Visits in 2012 per 1000 Events Washington Baltimore City Frederick Caroline Baltimore County Calvert Cecil Carroll Worcester Harford Dorchester St Mary's Howard Somerset Talbot Wicomico Anne Arundel Queen Anne's Charles Montgomery Prince George's Allegany Kent Garrett
13 Treatment Admissions Data Source: State of Automated Records Tracking (SMART) Alcohol Alcohol (Primary Substance) Treatment Admissions in FY2012 per 1000 Population Dorchester Worcester Calvert Garrett Queen Anne's Kent Caroline Talbot St Mary's Cecil Wicomico Somerset Baltimore City Allegany Washington Charles Anne Arundel Overall Carroll Frederick Harford Howard Baltimore County Montgomery Prince George's
14 Marijuana Marijuana (Primary Substance) Treatment Admissions in FY2012 per 1000 Population Dorchester Wicomico Somerset Baltimore City Kent Calvert Worcester Caroline Talbot Queen Anne's Allegany St Mary's Washington Charles Cecil Garrett Overall Anne Arundel Baltimore County Harford Frederick Prince George's Howard Carroll Montgomery
15 Prescription Opioids Opioids (Primary Substance) Treatment Admissions in FY2012 per 1000 Population Calvert Cecil Caroline Kent Somerset Queen Anne's Garrett Wicomico Worcester St Mary's Dorchester Allegany Charles Harford Anne Arundel Baltimore City Washington Talbot Overall Frederick Carroll Baltimore County Howard Montgomery Prince George's
16 Benzodiazepines Benzodiazepines (Primary Substance) Treatment Admissions in FY2012 per 1000 Population Baltimore City Dorchester Queen Anne's Calvert Cecil Garrett Talbot Wicomico Allegany Anne Arundel Carroll Overall Washington St Mary's Somerset Harford Charles Caroline Baltimore County Worcester Montgomery Frederick Howard Prince George's Kent
17 Heroin Heroin (Primary Substance) Treatment Admissions in FY2012 per 1000 Population Baltimore City Queen Anne's Dorchester Caroline Cecil Wicomico Worcester Overall Talbot Anne Arundel Carroll Calvert Somerset Allegany Garrett Baltimore County Frederick Harford Washington Kent St Mary's Howard Charles Montgomery Prince George's
18 Crack/Cocaine Crack/Cocaine (Primary Substance) Treatment Admissions in FY2012 per 1000 Population Dorchester Baltimore City Kent Somerset Wicomico Worcester Calvert Queen Anne's Talbot St Mary's Cecil Overall Washington Allegany Frederick Caroline Carroll Anne Arundel Charles Harford Baltimore County Prince George's Montgomery Garrett Howard
19 Co-Occurring Mental Illness Substance Use Treatment Admissions & Co-Occurring Mental Illness FY2012 % of Cases with Co-Occurring Mental Illness Allegany Frederick Montgomery Carroll Washington Cecil Howard Calvert Queen Anne's Harford MARYLAND Wicomico Somerset Patient Residence Provider Jurisdiction Baltimore City Talbot Anne Arundel Dorchester Prince George's Worcester Garrett Kent Baltimore County Caroline St. Mary's Charles 15
20 Co-Occurring Mental Illness by County of Patient Residence Percent of Co-Occurring Mental Illness Among Cases of Patients Residing in Each Jurisdiction FY2012 Allegany Frederick Montgomery Carroll Washington Cecil Howard Calvert Queen Anne's Harford Wicomico Somerset Baltimore City Talbot Anne Arundel Dorchester Prince George's Worcester Garrett Kent Baltimore County Caroline St. Mary's Charles
21 Co-Occurring Mental Illness by County Where the Treatment Facility is Located Percent of Co-Occurring Mental Illness Among Cases of Patients Treated in Each Jurisdiction FY2012 Dorchester Carroll Allegany Kent Montgomery Worcester Washington Frederick Howard Queen Anne's Cecil Calvert Harford Baltimore City St. Mary's Prince George's Anne Arundel Wicomico Talbot Garrett Somerset Charles Baltimore County Caroline
22 Alcohol-Impaired Crashes Data Source: Automated Accident Reporting System (MAARS) Impaired crashes are those with at least one driver reported to be under the influence of either 'alcohol' or both 'alcohol and drugs'. All Ages Alcohol or Alcohol and Drug Impaired Crashes as a Percentage of All Motor Vehicle Crashes - All Ages (MAARS 2011) Somerset Kent Caroline Worcester Dorchester Garrett Queen Anne's Carroll Cecil Allegany St. Mary's Frederick Charles Calvert Harford Anne Arundel Washington Talbot Prince George's Howard Baltimore Wicomico Montgomery Baltimore City
23 Aged Years Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds (MAARS 2011) Kent Carroll Caroline Worcester Garrett Queen Anne's Allegany Dorchester Cecil Frederick Somerset Saint Mary's Howard Anne Arundel Harford Talbot Charles Montgomery Calvert Prince George's Washington Wicomico Baltimore Baltimore City
24 Marijuana Use Data source: National Survey on Drug Use and Health (NSDUH) Past-Month Use NSDUH: Marijuana Use in Past Month, by Age Group Anne Arundel Baltimore City Baltimore County Montgomery North Central North East Prince George's South West % Reporting Use 20
25 Perceptions of Risk of Smoking Marijuana Perceptions of Great Risk of Smoking Marijuana Once a Month vs Marijuna Use, Aged 12+ Years Anne Arundel Baltimore City Baltimore County Montgomery North Central Perceptions of Great Risk of Smoking Marijuana Once a Month 12+ Marijuana Use in Past Month 12+ North East Marijuana Use in Past Year 12+ Prince George's South West % Reporting 21
26 Cocaine, Past-Year Use Data source: National Survey on Drug Use and Health (NSDUH) NSDUH: Cocaine Use in Past Year, by Age Group Anne Arundel Baltimore City Baltimore County Montgomery to 25 North Central 1.5 North East Prince George's South 4.7 West % Reporting Use 22
27 Pain Reliever, Past-Year Non-Medical Use Data source: National Survey on Drug Use and Health (NSDUH) NSDUH: Nonmedical Use of Pain Relievers in Past Year, by Age Group Anne Arundel Baltimore City Baltimore County Montgomery to to 25 North Central North East Prince George's South West % Reporting Use 23
28 Illicit Drug Use Data source: National Survey on Drug Use and Health (NSDUH) Past-Month Use of Illicit Drugs Other than Marijuana NSDUH: Illicit Drug Use Other Than Marijuana in Past Month, by Age Group Anne Arundel Baltimore City Baltimore County to to 25 Montgomery North Central North East Prince George's South West % Reporting Use 24
29 Past-Year Needing but Not Receiving Treatment Needing But Not Receiving Treatment for Illicit Drug Use in Past Year vs Illicit Drug Dependence or Abuse, Aged 12+ Years Anne Arundel Baltimore City Baltimore County Montgomery North Central North East Needing But Not Receiving Treatment for Illicit Drug Use in Past Year Illicit Drug Dependence or Abuse in Past Year Prince George's 2.6 South West % Reporting 25
30 Alcohol Use Data source: National Survey on Drug Use and Health (NSDUH) Past-Month Use NSDUH: Past-Month Alcohol Use, by Age Group Anne Arundel Baltimore City Baltimore County Montgomery to 20 North Central North East Prince George's South West % Reporting Use 26
31 Past-Month Binge Drinking NSDUH: Past-Month Binge Drinking, by Age Group Anne Arundel Baltimore City Baltimore County Montgomery to 20 North Central North East Prince George's South West % Reporting Use 27
32 Past-Year Needing but Not Receiving Treatment vs Abuse or Dependence Needing But Not Receiving Treatment for Alcohol Use in Past Year vs Past-Year Alcohol Dependence or Abuse, Aged 12+ Years Anne Arundel Baltimore City Baltimore County Montgomery Need for alcohol treatment (but not receiving) North Central Past-year alcohol abuse/dependence North East Prince George's South West % Reporting 28
33 JURISDICTION TRENDS 29
34 Alcohol-Related Inpatient Hospitalizations and Emergency Department Visits Data Source: Health Services Cost Review Commission (HSCRC) Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Allegany Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
35 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Anne Arundel Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
36 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Baltimore County Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
37 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Calvert Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
38 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Caroline Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
39 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Carroll Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
40 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Cecil Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
41 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Charles Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
42 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Dorchester Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
43 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Frederick Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
44 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Garrett Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
45 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Harford Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
46 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Howard Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
47 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Kent Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
48 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Montgomery Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
49 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Prince George's Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
50 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Queen Anne's Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
51 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events St Mary's Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
52 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Somerset Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
53 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Talbot Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
54 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Washington Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
55 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Wicomico Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
56 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Worcester Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
57 Rate of Alcohol-related Inpatient Hospitalizations and ED Visits per 100 Events Baltimore City Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
58 Opioid-Related Inpatient Hospitalizations and Emergency Department Visits Data Source: Health Services Cost Review Commission (HSCRC) Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Allegany Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
59 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Anne Arundel Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
60 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Baltimore County Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
61 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Calvert Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
62 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Caroline Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
63 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Carroll Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
64 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Cecil Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
65 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Charles Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
66 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Dorchester Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
67 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Frederick Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
68 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Garrett Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED Opioid-related emergency department data for Garrett County residents in 2012 were not reported due to small sample size resulting in an unstable estimate. 64
69 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Harford Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
70 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Howard Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
71 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Kent Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
72 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Montgomery Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
73 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Prince George's Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
74 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Queen Anne's Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
75 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events St Mary's Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
76 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Somerset Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
77 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Talbot Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
78 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Washington Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
79 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Wicomico Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
80 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Worcester Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
81 Rate of Opioid-related Inpatient Hospitalizations and ED Visits per 100 Events Baltimore City Inpatient ED Inpatient ED Inpatient ED Inpatient ED Inpatient ED
82 Substance Use Treatment Admissions Data Source: State of Automated Records Tracking (SMART) 0 Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack 0 0 FY2008 FY2009 FY2010 FY2011 FY
83 6.00 Allegany County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack 0 0 FY2008 FY2009 FY2010 FY2011 FY
84 0 Anne Arundel County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack 0 0 FY2008 FY2009 FY2010 FY2011 FY
85 0 Baltimore County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
86 8.00 Calvert County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
87 8.00 Caroline County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
88 0 Carroll County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack 0 0 FY2008 FY2009 FY2010 FY2011 FY
89 0 Cecil County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
90 0 Charles County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
91 9.00 Dorchester County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
92 2.50 Frederick County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack 0 0 FY2008 FY2009 FY2010 FY2011 FY
93 9.00 Garrett County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
94 1.80 Harford County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
95 1.60 Howard County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
96 10 Kent County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
97 1.40 Montgomery County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
98 1.20 Prince George's County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
99 8.00 Queen Anne's County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
100 6.00 St Mary's County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack 0 0 FY2008 FY2009 FY2010 FY2011 FY
101 7.00 Somerset County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
102 8.00 Talbot County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
103 0 Washington County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
104 6.00 Wicomico County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack 0 0 FY2008 FY2009 FY2010 FY2011 FY
105 10 Worcester County Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack FY2008 FY2009 FY2010 FY2011 FY
106 10 Baltimore City Primary Substance Treatment Admissions Trends per 1000 Population Alcohol Rx Opioids Heroin Benzodiazepines Marijuana Cocaine/crack 0 0 FY2008 FY2009 FY2010 FY2011 FY
107 Motor Vehicle Crashes among Residents Aged Years Data source: Automated Accident Reporting System (MAARS) Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Allegany
108 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Anne Arundel
109 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Baltimore County
110 Alcohol or Drug & Alcohol-Impaired Crashes as a Percentage of Total Crashes among year olds Calvert
111 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Caroline
112 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Carroll
113 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Cecil
114 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Charles
115 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Dorchester
116 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Frederick
117 1 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Garrett
118 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Harford
119 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Howard
120 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Kent
121 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Montgomery
122 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Prince George's
123 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Queen Anne's
124 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds St Mary's
125 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Somerset
126 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Talbot
127 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Washington
128 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Wicomico
129 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Worcester
130 Alcohol or Alcohol and Drug Impaired Crashes as Percentage of Total Crashes among year olds Baltimore City
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