Martin J. Ma
- Courses4
- Reviews32
- School: Brigham Young University
- Campus: Idaho
- Department: Economics
- Email address: Join to see
- Phone: Join to see
-
Location:
525 S Center St
Rexburg, ID - 83460 - Dates at Brigham Young University: March 2016 - July 2020
- Office Hours: Join to see
N/A
Would take again: No
For Credit: Yes
0
0
Mandatory
Awful
I took the class of Professor Ma for Intermediate Macroeconomics. After reading reviews, it seems like some very generous 150 and 151 students must have really been confused and extra kind. I read all the reviews and unfortunately can only corroborate bad ones. Overall, he's an awful guy.
N/A
Would take again: No
For Credit: Yes
1
0
Mandatory
Awful
Don't take Professor Ma's class. He gave us a quiz the first week, which I wasn't prepared for. He knew we weren't ready and still made us take it. He also gave us an exam with a graph that had numbers on it which weren't legible. Honestly, I didn't do it. I asked for another chance and he said tough luck to me. Like excuse me, he's the one that screwed it up.
Biography
Brigham Young University Idaho - Economics
Experience
Washington State University
Clinical Assistant Professor
Martin worked at Washington State University as a Clinical Assistant Professor
Washington State University
Ph.D. Student
Martin worked at Washington State University as a Ph.D. Student
BYU-Idaho
Professor of Economics
Martin worked at BYU-Idaho as a Professor of Economics
Education
Brigham Young University
BA
Economics
Washington State University
Doctor of Philosophy (Ph.D.)
Economics
Washington State University
Clinical Assistant Professor
Washington State University
Ph.D. Student
Publications
Efficiency of U.S. Dialysis Centers: An Updated Examination of Facility Characteristics That Influence Production of Dialysis Treatments
Health Services Research
Efficiency of U.S. Dialysis Centers: An Updated Examination of Facility Characteristics That Influence Production of Dialysis Treatments
Health Services Research
Efficiency of US Dialysis Centers: An Updated Examination of Facility Characteristics That Influence Production of Dialysis Treatments
ISPOR 18th Annual International Meeting New Orleans LA (Poster)
Medicare has announced plans to include efficiency measures in the End-Stage Renal Disease Quality Incentive Program. Few studies have analyzed US dialysis center efficiency, despite ongoing payment incentives to deliver dialysis care more cost-effectively. The objective of this study was to assess overall dialysis center efficiency as well as the impact of anemia drug choice on efficiency. Methods: Using 2010 data from Medicare Renal Cost Reports, a data envelopment analysis (DEA) was performed to model the technical efficiency of 4,343 free-standing dialysis centers. DEA uses a linear programming technique that converts multiple inputs (costs, staffing levels) and an output measure (number of dialysis sessions) to a relative efficiency score between 0 and 1, where scores are proportional to the efficiency frontier (score of 1.0.) A second DEA was conducted to assess changes in score distribution if labor and supply cost inputs were reduced due to switching to less frequent dosing of anemia drugs. Regression analysis was performed to account for variations in organizational and environmental conditions. Results: About 78% of facilities were owned by the two largest chains. Nearly 93% of facilities were for-profit; 75% were in urban areas. 33% of facilities were functioning efficiently (efficiency scores ≥.90); 30% had scores between .70 and .90, and 37% scored <.70. Neither the intensity of market competition nor the profit status of the facility had a significant effect on efficiency. Facilities that were members of large chains were less likely to be efficient. Cost and labor savings due to changes in drug protocols had little effect on overall dialysis center efficiency. Conclusion: Opportunities exist for continued improvements in the efficiency of US dialysis facilities. DEA may be a useful tool for evaluating dialysis center efficiency. Future studies should incorporate quality of care dimensions and case-mix adjustment in the measurement of efficiency.
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