Distribution of grants, consulting fees, and other payments to medical professionals by Speciality

The Center for Medical and Medicaid Services (CMS) new Open Payments database shows the consulting fees, research grants, travel and other reimbursements made to medical industry in 2013

There are 2,619,700 payments in the CMS data made to 356,190 physicians.   The average payment made to physicians was $255.22.   The median payment was $15.52.

Overall, Clinical Pharmacology and Orthopedic Surgery professions received the most grants and other payments.  The table below shows the percentage of average payment by specialty as a percentage of the average overall payment to all medical specialties.  The STATA code is listed below.

Medical Specialty % of average payment to all speciallites
Clinical Pharmacology 1516%
Orthopaedic Surgery 473%
Group: Multi-Specialty 436%
Nutritionist 328%
Medical Genetics 284%
Surgery 282%
Transplant Surgery 268%
Neurological Surgery 266%
Pathology 203%
Pediatrics 197%
Oral & Maxillofacial Surgery 160%
Laboratories 154%
Preventive Medicine 150%
Nuclear Medicine 135%
Neuromusculoskeletal Medicine 132%
Phlebology 130%
Radiology 123%
Thoracic Surgery 121%
Colon & Rectal Surgery 121%
Internal Medicine 116%
Anesthesiology 116%
Pharmacy Technician 115%
Dentist 108%
Group: Single Specialty 107%
Otolaryngology 97%
Other Service Providers 91%
Chiropractor 86%
Plastic Surgery 86%
Ophthalmology 84%
Allergy & Immunology 84%
Registered Nurse 83%
Agencies 81%
Technologists, Technicians & Other Technical Service Providers 79%
Physician Assistant 77%
Obstetrics & Gynecology 77%
Dermatology 74%
Podiatrist 73%
Psychiatry & Neurology 70%
Pain Medicine 64%
Urology 64%
Physical Medicine & Rehabilitation 57%
General Acute Care Hospital 57%
Counselor 56%
General Practice 52%
Dental Hygienist 43%
Student, Health Care 43%
Clinical Neuropsychologist 43%
Assistant, Podiatric 41%
Clinic/Center 40%
Optometrist 38%
Military Hospital 37%
Long Term Care Hospital 37%
Emergency Medicine 36%
Personal Emergency Response Attendant 36%
Respiratory, Developmental, Rehabilitative & Restorative Service Providers 35%
Dietary Manager 35%
Family Medicine 33%
Hospitalist 33%
Speech, Language & Hearing Service Providers 32%
Managed Care Organizations 31%
Electrodiagnostic Medicine 31%
Pharmacist 28%
Legal Medicine 27%
Nursing & Custodial Care Facilities 26%
Psychologist 24%
Hospital Units (Psychiatric and Rehabilitation) 22%
Licensed Practical or Vocational Nurse 20%
Suppliers 17%
Psychoanalyst 17%
Special Hospital 16%
Denturist 15%
Dental Laboratory Technician 14%
Social Worker 14%
Dietitian, Registered 13%
Residential Treatment Facilities: Mental Illness, Retardation, and/or Developmental Disabilities 11%
Psychiatric Hospital 10%
Eye & Vision Technician: Technologist 10%
Behavioral Analyst 9%
Emergency Medical Technician 9%
Dental Assistant 9%
Marriage & Family Therapist 9%
Chronic Disease Hospital 8%
Independent Medical Examiner 7%
Nursing Home Administrator 5%
Nurse’s Aide 5%

STATA Code

se “dataopenrecords-small.dta”, clear

rename recipient_state State
drop if State==”” | State==”AE” | State==”AA”| State==”AP” | State==”GU”| State==”ON” | State==”VI”| State==”PR”

keep physician_spec total number
rename p Specialty
sort S total number
drop if S==””
destring number, replace
collapse (mean) tot num , by(S)
rename tot Average_Payment_Amount
rename num Average_Number_of_Payments
outsheet S Average_P Average_N using “P:Business Dev ProjectsEmployStats9074 – OpenRecordsTablesspecialty_payments.csv”, comma nolabel replace

 

4 largest California MSAs see decrease in job openings for September

All 4 of the largest MSAs (metropolitan statistical areas) in California experienced a decrease in job openings for the month of August.

Los Angeles-Long Beach-Santa Ana

The Los Angeles-Long Beach-Santa Ana MSA experienced a decrease of 24,282 job openings in September 2014, a -17.73% change from August 2014.

Month Total Openings Percent Monthly Change Percent Yearly Change
Oct-13 116,232 7.74 -3.08
Nov-13 99,534 -14.37 -3.08
Dec-13 94,076 -5.48 -3.08
Jan-14 113,912 21.09 -3.08
Feb-14 108,563 -4.7 -3.08
Mar-14 110,825 2.08 -3.08
Apr-14 137,352 23.94 -3.08
May-14 129,540 -5.69 -3.08
Jun-14 129,782 0.19 -3.08
Jul-14 137,333 5.82 -3.08
Aug-14 136,939 -0.29 -3.08
Sep-14 112,657 -17.73 -3.08

San Francisco-Oakland-Fremont

The San Francisco-Oakland-Fremont MSA experienced a decrease of 10,642 job openings in September 2014, a -15.38% change from August 2014.

Month Total Openings Percent Monthly Change Percent Yearly Change
Oct-13 58,926 8.92 -0.61
Nov-13 50,552 -14.21 -0.61
Dec-13 47,699 -5.64 -0.61
Jan-14 57,523 20.59 -0.61
Feb-14 55,345 -3.79 -0.61
Mar-14 56,460 2.01 -0.61
Apr-14 69,647 23.36 -0.61
May-14 65,783 -5.55 -0.61
Jun-14 66,213 0.65 -0.61
Jul-14 69,790 5.4 -0.61
Aug-14 69,209 -0.83 -0.61
Sep-14 58,567 -15.38 -0.61

Riverside-San Bernardino-Ontario

The Riverside-San Bernardino-Ontario MSA experienced a decrease of 11,906 job openings in September 2014, a -22.93% change from August 2014.

Month Total Openings Percent Monthly Change Percent Yearly Change
Oct-13 43,869 6.87 -8.78
Nov-13 37,771 -13.9 -8.78
Dec-13 35,578 -5.81 -8.78
Jan-14 42,940 20.69 -8.78
Feb-14 40,977 -4.57 -8.78
Mar-14 41,811 2.03 -8.78
Apr-14 51,583 23.37 -8.78
May-14 48,935 -5.13 -8.78
Jun-14 49,141 0.42 -8.78
Jul-14 52,360 6.55 -8.78
Aug-14 51,924 -0.83 -8.78
Sep-14 40,018 -22.93 -8.78

 San Diego-Carlsbad-San Marcos

The San Diego-Carlsbad-San Marcos MSA experienced a decrease of 7,664 job openings in September 2014, a -15.64% change from August 2014.

Month Total Openings Percent Monthly Change Percent Yearly Change
Oct-13 41,147 8.09 0.48
Nov-13 35,358 -14.07 0.48
Dec-13 33,336 -5.72 0.48
Jan-14 40,242 20.72 0.48
Feb-14 38,895 -3.35 0.48
Mar-14 39,795 2.31 0.48
Apr-14 48,989 23.1 0.48
May-14 46,354 -5.38 0.48
Jun-14 46,681 0.71 0.48
Jul-14 49,258 5.52 0.48
Aug-14 49,007 -0.51 0.48
Sep-14 41,343 -15.64 0.48

Source: BLS

Retail Salespersons experienced the largest increase of job openings nationwide for September

Retail Salespersons experienced the largest increase of new openings of all occupations in the US for the month of September with 1,153 new job openings.

retail salesman

Month Occupation Total_Openings New_Openings
Sep-14 Retail Salespersons 52,394 1,153

Source: BLS

Image Source: http://www.businessweek.com/articles/2013-02-04/blackberry-and-best-buy-two-super-bowl-ad-flops

All major MSAs experienced decrease of job openings from August to September

Each major MSA (metropolitan statistical area) in the United States experienced a decrease in the number of total job openings from August 2014 to September 2014. Of all the major MSAs during this span, the New York-Northern New Jersey-Long Island MSA had the largest number of total openings for September, while the Ocean City MSA had the smallest decrease in job openings.

Month MSA Total Openings New Openings
Sep-14 New York-Northern New Jersey-Long Island, NY-NJ-PA 164,748 -32,386
Sep-14 Ocean City, NJ 1,978 -425

Source: BLS

STATA or R for data analysis in wage and hour cases?

In the stats world there is somewhat of a debate going on regarding which statistical analyses programs are “better”.  Of course, the answer always depends on what you use it for.  Some like the open-source, developing nature of R.  While others like the established and tried STATA.

In the world of labor and employment economics and in ligation matters that require data analysis of large sets of data, STATA wins hands down.  However, the open source nature of R is appealing in some settings; but the many decades of pre-written (and de bugged) programs make STATA the best choice in most employment and wage and hour cases that require analysis of large data sets.  Performing basic tabulations and data manipulations in R requires many lines of code while STATA often has the command built in.

Here are some interesting snippets from the web on the R v STATA debate:

http://www.researchgate.net/post/What_is_the_difference_between_SPSS_R_and_STATA_software

The main drawback of R is the learning curve: you need a few weeks just to be able to import data and create a simple plot, and you will not cease learning basic operations (e.g. for plotting) for many years. You will stumble upon weirdest problems all the time because you have missed the comma or because your data frame collapses to a vector if only one row is selected.

However, once you mastered this, you will have the full arsenal of modern cutting-edge statistical techniques at your disposal, along with in-depth manuals, references, specialized packages, graphical interface, a helpful community — and all at no cost. Also, you will be able to do stunning graphics.

 

http://forum.thegradcafe.com/topic/44595-stata-or-r-for-statistics-software/

http://www.econjobrumors.com/topic/r-vs-stata-is-like-a-mercedes-vs-a-bus