Occupation Overview. EMSI Q2 2015 Data Set. Medical Assistant October 2015. Western Technical College

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Occupation Overview EMSI Q2 2015 Data Set Medical Assistant October 2015 Western Technical College 400 Seventh Street La Crosse, Wisconsin 54601 608.785.9200 EMSI Q2 2015 Data Set www.economicmodeling.com 1

Parameters Occupations Code Description 31-9092 Medical Assistants Regions Code Description 55011 Buffalo County, WI 55023 Crawford County, WI 55053 Jackson County, WI 55057 Juneau County, WI 55063 La Crosse County, WI 55081 Monroe County, WI 55121 Trempealeau County, WI 55123 Vernon County, WI Timeframe 2016-2020 Datarun 2015.2 Employees Medical Assistants in 8 Counties Medical Assistants (SOC 31-9092):Perform administrative and certain clinical duties under the direction of a physician. Administrative duties may include scheduling appointments, maintaining medical records, billing, and coding information for insurance purposes. Clinical duties may include taking and recording vital signs and medical histories, preparing patients for examination, drawing blood, and administering medications as directed by physician. Excludes "Physician Assistants" (29-1071). Sample of Reported Job Titles: Chiropractor AssistantCertified Medical Assistant (CMA)Medical Assistant (MA)Registered Medical Assistant (RMA)Optometric TechnicianOptometric AssistantOphthalmic TechnicianMedical Office AssistantDoctor's AssistantClinical Assistant Related O*NET Occupation: Medical Assistants (31-9092.00) EMSI Q2 2015 Data Set www.economicmodeling.com 2

SOC Description 2016 Jobs 2020 Jobs 2016-2020 Change 2016-2020 % Change Openings Annual Openings Median Hourly Earnings 31-9092 Medical Assistants 383 404 21 5% 57 14 $14.46 Occupation Summary for Medical Assistants 381 5.5% $14.46/hr Jobs (2015) % Change (2016-2020) Median Hourly Earnings 38% below National average Nation: 8.5% Nation: $14.41/hr Growth for Medical Assistants (31-9092) 383 404 21 5.5% 2016 Jobs 2020 Jobs Change (2016-2020) % Change (2016-2020) EMSI Q2 2015 Data Set www.economicmodeling.com 3

Percentile Earnings for Medical Assistants (31-9092) $12.31/hr $14.46/hr $16.67/hr 25th Percentile Earnings Median Earnings 75th Percentile Earnings Regional Trends Region 2016 Jobs 2020 Jobs Change % Change Region 383 404 21 5.5% State 11,570 12,468 898 7.8% Nation 631,390 685,029 53,639 8.5% Western Technical College District 383 404 21 5.5% Regional Breakdown EMSI Q2 2015 Data Set www.economicmodeling.com 4

County 2020 Jobs La Crosse County, WI 195 Monroe County, WI 59 Vernon County, WI 42 Trempealeau County, WI 31 Jackson County, WI 29 Occupation Gender Breakdown Gender 2015 Jobs 2015 Percent Males 28 7.4% Females 353 92.6% Occupation Age Breakdown EMSI Q2 2015 Data Set www.economicmodeling.com 5

Age 2015 Jobs 2015 Percent 14-18 2 0.5% 19-24 44 11.5% 25-34 120 31.4% 35-44 89 23.3% 45-54 73 19.1% 55-64 47 12.5% 65+ 7 1.8% Occupation Race/Ethnicity Breakdown Race/Ethnicity 2015 Jobs 2015 Percent White 360 94.6% Hispanic or Latino 9 2.3% Asian 5 1.4% Black or African American 4 1.1% Two or More Races 1 0.4% American Indian or Alaska Native 1 0.1% Native Hawaiian or Other Pacific Islander 0 0.0% National Educational Attainment EMSI Q2 2015 Data Set www.economicmodeling.com 6

Education Level 2015 Percent Less than high school diploma 2.4% High school diploma or equivalent 23.3% Some college, no degree 42.9% Associate's degree 22.0% Bachelor's degree 7.2% Master's degree 1.4% Doctoral or professional degree 0.8% Occupational Programs 5 75 25 Programs (2014) Completions (2014) Openings (2014) CIP Code Program Completions (2014) 51.0801 Medical/Clinical Assistant 52 51.0705 Medical Office Management/Administration 15 51.0716 Medical Administrative/Executive Assistant and Medical Secretary 7 51.0713 Medical Insurance Coding Specialist/Coder 1 51.0899 Allied Health and Medical Assisting Services, Other 0 Industries Employing Medical Assistants EMSI Q2 2015 Data Set www.economicmodeling.com 7

Industry Occupation Jobs in Industry (2015) % of Occupation in Industry (2015) % of Total Jobs in Industry (2015) Offices of Physicians (except Mental Health Specialists) 208 54.6% 9.5% General Medical and Surgical Hospitals 67 17.6% 0.7% Offices of Chiropractors 38 10.0% 13.2% Offices of Physicians, Mental Health Specialists 20 5.1% 7.5% Offices of Optometrists <10 2.4% 7.7% EMSI Q2 2015 Data Set www.economicmodeling.com 8

Appendix A - Data Sources and Calculations Occupation Data EMSI occupation employment data are based on final EMSI industry data and final EMSI staffing patterns. Wage estimates are based on Occupational Employment Statistics (QCEW and Non-QCEW Employees classes of worker) and the American Community Survey (Self-Employed and Extended Proprietors). Occupational wage estimates also affected by county-level EMSI earnings by industry. Location Quotient Location quotient (LQ) is a way of quantifying how concentrated a particular industry, cluster, occupation, or demographic group is in a region as compared to the nation. It can reveal what makes a particular region unique in comparison to the national average. Institution Data The institution data in this report is taken directly from the national IPEDS database published by the U.S. Department of Education's National Center for Education Statistics. Completers Data The completers data in this report is taken directly from the national IPEDS database published by the U.S. Department of Education's National Center for Education Statistics. Staffing Patterns Data The staffing pattern data in this report are compiled from several sources using a specialized process. For QCEW and Non-QCEW Employees classes of worker, sources include Occupational Employment Statistics, the National Industry-Occupation Employment Matrix, and the American Community Survey. For the Self-Employed and Extended Proprietors classes of worker, the primary source is the American Community Survey, with a small amount of information from Occupational Employment Statistics. Industry Data EMSI industry data have various sources depending on the class of worker. (1) For QCEW Employees, EMSI primarily uses the QCEW (Quarterly Census of Employment and Wages), with supplemental estimates from County Business Patterns and Current Employment Statistics. (2) Non-QCEW employees data are based on a number of sources including QCEW, Current Employment Statistics, County Business Patterns, BEA State and Local Personal Income reports, the National Industry-Occupation Employment Matrix (NIOEM), the American Community Survey, and Railroad Retirement Board statistics. (3) Self-Employed and Extended Proprietor classes of worker data are primarily based on the American Community Survey, Nonemployer Statistics, and BEA State and Local Personal Income Reports. Projections for QCEW and Non-QCEW Employees are informed by NIOEM and long-term industry projections published by individual states. State Data Sources This report uses state data from the following agencies: Illinois Department of Employment Security, Employment Projections; Iowa Workforce Development; Michigan Department of Labor and Economic Growth, Bureau of Labor Market Information and Strategic Initiatives; Minnesota Department of Employment and Economic Development; Wisconsin Department of Workforce Development, Bureau of Workforce Information EMSI Q2 2015 Data Set www.economicmodeling.com 9