HRP 199: Undergraduate Research
Students undertake investigations sponsored by individual faculty members. Prerequisite: consent of instructor.
Terms: Aut, Win, Spr, Sum

Units: 118

Repeatable for credit

Grading: Letter or Credit/No Credit
Instructors:
Baker, L. (PI)
;
Bhattacharya, J. (PI)
;
Bundorf, M. (PI)
...
more instructors for HRP 199 »
Instructors:
Baker, L. (PI)
;
Bhattacharya, J. (PI)
;
Bundorf, M. (PI)
;
Coram, M. (PI)
;
Corso, I. (PI)
;
Efron, B. (PI)
;
Friedman, G. (PI)
;
Goldstein, M. (PI)
;
Hastie, T. (PI)
;
Heidenreich, P. (PI)
;
Henderson, V. (PI)
;
Hlatky, M. (PI)
;
Ioannidis, J. (PI)
;
Johnstone, I. (PI)
;
Kessler, D. (PI)
;
King, A. (PI)
;
Kurian, A. (PI)
;
Lavori, P. (PI)
;
Lu, Y. (PI)
;
Macario, A. (PI)
;
Maldonado, Y. (PI)
;
Miller, G. (PI)
;
Nelson, L. (PI)
;
Olshen, R. (PI)
;
Owens, D. (PI)
;
Parsonnet, J. (PI)
;
Popat, R. (PI)
;
Rogosa, D. (PI)
;
Sabatti, C. (PI)
;
Sainani, K. (PI)
;
Shih, M. (PI)
;
Sieh, W. (PI)
;
Simard, J. (PI)
;
Tian, L. (PI)
;
Tibshirani, R. (PI)
;
West, D. (PI)
;
Whittemore, A. (PI)
;
Wise, P. (PI)
;
Wong, W. (PI)
HRP 207: Introduction to Concepts and Methods in Health Services and Policy Research I
Primarily for medical students in the Health Services and Policy Research scholarly concentration. Topics include health economics, statistics, decision analysis, study design, quality measurement, cost benefit and effectiveness analysis, and evidence based guidelines.
Terms: Aut

Units: 2

Grading: Medical Satisfactory/No Credit
Instructors:
Haberland, C. (PI)
HRP 223: Introduction to Data Management and Analysis in SAS
Provides handson introduction to basic data management and analysis techniques using SAS. Data management topics include: Introduction to SAS and SAS syntax, importing data, creating and reading SAS datasets, data cleaning and validation, creating new variables, and combining data sets. Analysis techniques include: basic descriptive statistics (e.g., means, frequency) and bivariate procedures for continuous and categorical variables (e.g., ttests, chisquares).
Terms: Aut

Units: 2

Grading: Medical Satisfactory/No Credit
Instructors:
Park, L. (PI)
;
Popat, R. (PI)
HRP 225: Design and Conduct of Clinical and Epidemiologic Studies
Intermediatelevel. The skills to design, carry out, and interpret epidemiologic studies, particularly of chronic diseases. Topics: epidemiologic concepts, sources of data, cohort studies, casecontrol studies, crosssectional studies, sampling, measures of association, estimating sample size, and sources of bias. Prerequisite: A basic/introductory course in statistics or consent of instructor.
Terms: Aut

Units: 3

Grading: Medical Option (MedLtrCR/NC)
Instructors:
Popat, R. (PI)
HRP 229: Spectrum Scholars Seminar
Preference to trainees awarded Stanford internal KL2, TL1 grants. Focus is on students and junior faculty who have received a Spectrum KL2 or TL1 Award. Discussions include progress and challenges involved in starting and conducting clinical research, current courses, time management and resources; support from peers; education and professional development. All scholars are required to attend a weekly seminar series meeting throughout the year that will cover an array of crosscutting methodological topics with published examples of implementation. Prerequisite: Awarded a Spectrum KL2, TL1 Grant or Spectrum UL1
Terms: Aut, Win, Spr, Sum

Units: 1

Repeatable for credit

Grading: Medical Satisfactory/No Credit
HRP 234: Engineering Better Health Systems: modeling for public health (HUMBIO 154A, MED 254)
This course teaches engineering, operations research and modeling techniques to improve public health programs and systems. Students will engage in indepth study of disease detection and control strategies from a "systems science" perspective, which involves the use of common engineering, operations research, and mathematical modeling techniques such as optimization, queuing theory, Markov and KermackMcKendrick models, and microsimulation. Lectures and problem sets will focus on applying these techniques to classical public health dilemmas such as how to optimize screening programs, reduce waiting times for healthcare services, solve resource allocation problems, and compare macroscale disease control strategies that cannot be easily evaluated through randomized trials. Readings will complement the lectures and problem sets by offering critical perspectives from the public health history, sociology, and epidemiology. Indepth case studies from nongovernmental organizations, departm
more »
This course teaches engineering, operations research and modeling techniques to improve public health programs and systems. Students will engage in indepth study of disease detection and control strategies from a "systems science" perspective, which involves the use of common engineering, operations research, and mathematical modeling techniques such as optimization, queuing theory, Markov and KermackMcKendrick models, and microsimulation. Lectures and problem sets will focus on applying these techniques to classical public health dilemmas such as how to optimize screening programs, reduce waiting times for healthcare services, solve resource allocation problems, and compare macroscale disease control strategies that cannot be easily evaluated through randomized trials. Readings will complement the lectures and problem sets by offering critical perspectives from the public health history, sociology, and epidemiology. Indepth case studies from nongovernmental organizations, departments of public health, and international agencies will drive the course. Prerequisites: A course in introductory statistics, and a course in multivariable calculus including ordinarily differential equations. Open to upperdivision undergraduate students and graduate students. Human Biology majors enroll in
HUMBIO 154A. Prerequisite:
MATH 51 or
CME 100 and Human Biology Core or
Bio 141 or
BioHopk 174H
Terms: Aut

Units: 4

Grading: Letter or Credit/No Credit
Instructors:
Basu, S. (PI)
HRP 236: Epidemiology Research Seminar
Weekly forum for ongoing epidemiologic research by faculty, staff, guests, and students, emphasizing research issues relevant to disease causation, prevention, and treatment. May be repeated for credit.
Terms: Aut, Win, Spr

Units: 1

Repeatable for credit

Grading: Medical Satisfactory/No Credit
HRP 243: Health Policy Seminar: Health Care Delivery
This seminar course is intended to introduce students to the role of policy in the delivery of healthcare in the United States. Speakers will include a mix of Stanford faculty and experts in health care financing delivery from around the bay area. There will be no assignments and lunch will be provided.
Terms: Aut

Units: 1

Repeatable for credit

Grading: Medical Satisfactory/No Credit
Instructors:
Bundorf, M. (PI)
;
Song, N. (TA)
HRP 245: Intensive Course in Clinical Research
The Intensive Course in Clinical Research (ICCR) is a oneweek immersion course designed for new or aspiring clinical investigators, medical students, residents, graduate students, fellows and junior faculty interested in pursuing careers in clinical and transnational research. Students spend five days and four evenings immersed in all aspects of research study design and performance. The format combined didactic with intense group/team activities focused on practical issues in clinical research design  from selection of a researchable study question through actual writing of a research proposal. Lectures and panel discussions are presented by an accomplished faculty of Stanford clinical researchers and key leaders from the Stanford community. Every presentation includes a discussion of relevant issues. The course is supported by over 40 faculty and fellows from across the School of Medicine.
Terms: Aut

Units: 2

Grading: Medical Option (MedLtrCR/NC)
Instructors:
Asch, S. (PI)
;
Boothroyd, J. (PI)
;
Cullen, M. (PI)
...
more instructors for HRP 245 »
Instructors:
Asch, S. (PI)
;
Boothroyd, J. (PI)
;
Cullen, M. (PI)
;
Goodman, S. (PI)
;
HalpernFelsher, B. (PI)
;
Leonard, M. (PI)
;
Magnus, D. (PI)
;
Popat, R. (PI)
;
Sainani, K. (PI)
;
Shah, N. (PI)
;
Stave, C. (SI)
;
Tsao, P. (SI)