The DOI matches its Crossref record; 20 of the 22 references it cites were found in a registry or an index.
The Effect of Education on Medical Technology Adoption: Are the More Educated More Likely to Use New Drugs
Open accessAbstract
There is a large body of work that documents a strong, positive correlation between education and measures of health, but little is known about the mechanisms by which education might affect health.One possibility is that more educated individuals are more likely to adopt new medical technologies.We investigate this theory by asking whether more educated people are more likely to use newer drugs, while controlling for other individual characteristics, such as income and insurance status.Using the 1997 MEPS, we find that more highly educated people are more likely to use drugs more recently approved by the FDA.We find that education only matters for individuals who repeatedly purchase drugs for a given condition, suggesting that the more educated are better able to learn from experience.
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“The study revealed that highly educated employees tend to adopt new technologies more quickly than those who are less educated [75]”
From A Study of the Adoption and Implementation of Enterprise Resource Planning (ERP): Identification of Moderators and Mediator (2020) · cites this paper as [75]
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Cites
Economic Status and Health in Childhood: The Origins of the Gradient
Case, A. C., Lubotsky, D. H., & Paxson, C. H. (2002) · American Economic Review · doi:10.1257/000282802762024520 · Cited by 1,753
The Relationship Between Education and Adult Mortality in the United States
Lleras-Muney, A. (2005) · Review of Economic Studies · doi:10.1111/0034-6527.00329 · Cited by 1,282
Self-citationThe Comparative Advantage of Educated Workers in Implementing New Technology
Bartel, A. P., & Lichtenberg, F. R. (1987) · The Review of Economics and Statistics · doi:10.2307/1937894 · Cited by 978
Self-citationThe Relationship Between Education and Adult Mortality in the United States
Lleras-Muney, A. (2002) · doi:10.3386/w8986 · Cited by 929
Self-citationExploring the health–wealth nexus
Meer, J., Miller, D. L., & Rosen, H. S. (2003) · Journal of Health Economics · doi:10.1016/s0167-6296(03)00059-6 · Cited by 355
Why Are There Returns to Schooling
Rosenzweig, M. R. (1995) · American Economic Review · Cited by 241
Decision Making and Prescribing Patterns—a Literature Review
Bradley, C. (1991) · Family Practice · doi:10.1093/fampra/8.3.276 · Cited by 136
Educational Inequality in Adult Mortality: An Assessment with Death Certificate Data from Michigan
Christenson, B. A., & Johnson, N. E. (1995) · Demography · doi:10.2307/2061741 · Cited by 122
Do (more and better) drugs keep people out of hospitals?
Lichtenberg, F. R. (1996) · PubMed · Cited by 120
Self-citationCoulson, N. E., Terza, J. V., Neslusan, C. A., & Stuart, B. (1995) · PubMed · Cited by 81
Research works printed but not linked: 14
- Berger, Mark C. and J. Paul Leigh, 1989, ``Schooling, Self Selection and Health,'' Journal of Human Resources, Vol. 24, pp.433-455
- Elo, Irma T. and Samuel H. Preston, 1996, ``Educational Differentials in Mortality: United States, 1979-85,'' Social Science and Medicine 42(1), pp. 44-57
- Feldman J. D. Makuc, J. Kleinman and J. Cornoni-Huntley, 1989, ``National Trends in Educational Differences in Mortality,'' American Journal of Epidemiology, pp. 919-933
- Grossman, Michael, 1972, ``On the Concept of Health Capital the Demand for Health,'' Journal of Political Economy 80, (Illinois, United States) 223-255
- Grossman, Michael and R. Kaestner, 1997, "Effects of Education on Health," in J.R. Berhman and N. Stacey Eds., The Social Benefits of Education, University of Michigan Press, pp. 223-255
- Hurd, Michael, Daniel McFadden, Angela Merill and Tiago Ribeiro, forthcoming, "Healthy, Wealthy, and Wise? New Evidence from AHEAD Wave 3," Journal of Econometrics Kaiser Foundation, November 2001, "Understanding the Effects of Direct- to-Consumer Prescription Drug Advertising," report, www. kff.org
- Kenkel, Donald, April 1991, ``Health Behavior, Health knowledge and Schooling,'' Journal of Political Economy, Volume 99, Issue 2, pp. 287- 305
- Leigh, J. Paul and Rachna Dhir, 1997, ``Schooling and Frailty Among Seniors,'' Economics of Education Review, Volume 16, No. 1, pp. 45-57
- Lichtenberg, Frank R. September/October 2001 "Are the Benefits and Costs of Newer Drugs Worth Their Cost? Evidence from the 1996 MEPS," Health Affairs 20(5), pp. 241-51.
- Nelson, Richard R. and Edmund S. Phelps, 1966, "Investment in Humans, Technological Diffusion and Economics Growth," American Economic Review, pp. 69-75
- Pappas, Gregory, Susan Queen, Wolber Hadden and Grail Fisher, 1993, ``The Increasing Disparity in Mortality Between Socioeconomic Groups in the United States, 1960 and 1986,'' The New England Journal of Medicine, pp. 103-109
- Rosenzweig, Mark R. and T. Paul Schultz, May 1989, ``Schooling, Information and Nonmarket Productivity: Contraceptive Use and its effectiveness,'' International Economic Review, 30920. pp. 457-77
- Sander, William, 1995, ``Schooling and Quitting Smoking,'' Review of Economics and Statistics, 77, pp. 191-199
- Schwartz, RK, Avorn J. Soumerai and Jerry Avorn, 1989, "Physician Motivation for non-scientific drug prescribing," Social Science and Medicine, vol. 28, pp. 577-582
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Educational gaps in medical care and health behavior: Evidence from US Natality data
Price, J., Price, J., & Simon, K. I. (2011) · Economics of Education Review · doi:10.1016/j.econedurev.2011.03.012 · Cited by 3
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Engelhardt-Woelfler, H., & Leopold, L. (2017) · Springer Reference Sozialwissenschaften · doi:10.1007/978-3-658-06477-8_20-1 · Cited by 3
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de Sousa, E. A., dos Santos, A. M. A., & Jacinto, P. D. A. (2016) · Revista Econômica do Nordeste · doi:10.61673/ren.2013.396 · Cited by 3
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Kusuma, I. D. M. A. W., Pramono, B. A., Wulandari, F. Y., Fajar, M. K., Widohardhono, R., Hafidz, A., & Ardha, M. A. A. (2024) · Retos · doi:10.47197/retos.v56.104894 · Cited by 2
“Education serves as a vital conduit for adapting to and mastering new technologies (Lleras-Muney & Lichtenberg, 2002), and educated individuals are often seen as more productive at work than their less-educated counterparts (Kampelmann et al., 2018).”
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Alhabsi, A. (2019) · Arrow - TU Dublin (Technological University Dublin) · doi:10.21427/n85q-4j66 · Cited by 2
Cong, Z. (2009) · RAND Corporation eBooks · doi:10.7249/rgsd242 · Cited by 1
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Ostrach, B. M. M. (2013) · Anthropology · doi:10.4172/2332-0915.1000101 · Cited by 1
Health insurance and the uptake of new drugs in the United States
Gemmill, M., Serra‐Sastre, V., & Costa‐Font, J. (2009) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199550685.003.0007 · Cited by 1
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Myers, K., Frenette, M., Sweetman, A., Dostie, B., & Langlois, C. (2014) · Cited by 1
Masiero, G., Filippini, M., Ferech, M., & Goossens, H. (2007) · RePEc: Research Papers in Economics · Cited by 1
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Leigh, A. (2009) · SSRN Electronic Journal · doi:10.2139/ssrn.1521228 · Cited by 1
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Chinzara, Z. (2014) · RePEc: Research Papers in Economics · Cited by 1
Efeitos do Programa Saúde na Escola em indicadores municipais de saúde
Ferolla, L. M. (2019) · doi:10.11606/t.96.2019.tde-09102019-120243 · Cited by 1
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Granados, R. M., Martín‐Martín, J. J., & Aguilera, J. D. D. J. (2008) · RePEc: Research Papers in Economics
Johnson, D. K. N., & Lybecker, K. M. L. A. N. (2011) · Growth and Change · doi:10.1111/j.1468-2257.2011.00569.x
Educational Trajectories and Health over the Life Course: A Role for the DSBN Academy?
Etherington, C. (2013) · Canadian Graduate Journal of Sociology and Criminology · doi:10.15353/cgjsc-rcessc.v2i1.15
Usatin, R. (2014) · Seton Hall University eRepository (Seton Hall University)
Nguyen, H. Q. (2015) · UA Campus Repository (The University of Arizona)
Does HAVA Help the Have-Nots? U.S. Adoption of New Election Equipment, 1980-2008Preprint
Johnson, D. K. N., & Lybecker, K. M. L. A. N. (2008) · SSRN Electronic Journal · doi:10.2139/ssrn.1290871
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Hall, A. (2015) · RePEc: Research Papers in Economics
Lynch, J. L., & von Hippel, P. T. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2583971
Matsmak, J., & Chanvarasuth, P. (2013)
Human Capital, Technology and Inequality
Asif, Z. (2018) · Queensland University of Technology · doi:10.5204/thesis.eprints.122964
Sayegh, M. M., & Sidani, D. (2023) · Lecture notes in information systems and organisation · doi:10.1007/978-3-031-24775-0_2
Trevena, L., Paay, J., McDonald, R. L., Williams, J. L., & Meyer, D. (2025) · Disability and Rehabilitation Assistive Technology · doi:10.1080/17483107.2025.2551712
“…these variables are significant predictors of user intention. education as an antecedent variable was also included in the current study. this was because some studies have identified a positive relationship between the level of education in end-users and the adoption of new technology [16–18].”
Cardiovascular Risk Factor Prevalence and Control by Education Strata in Older Adults in 3 Countries
Lawton, R. I., & Cutler, D. (2026) · JAMA Network Open · doi:10.1001/jamanetworkopen.2026.25410
Metadata
- Authors
- Lleras-Muney, A., & Lichtenberg, F.
- Affiliations
- National Bureau of Economic Research (US)
- ORCID
- Lichtenberg, Frank
- Venue
- National Bureau of Economic Research
- Publisher
- National Bureau of Economic Research
- Published
- 2002-09
- OpenAlex
- W1941471126
- Cited by
- 141
- References
- 22
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 3 · 2023: 4 · 2022: 3 · 2021: 2 · 2020: 6 · 2019: 6 · 2018: 7 · 2017: 4 · 2016: 11 · 2015: 12 · 2014: 7 · 2013: 6 · 2012: 3
- Type
- report
- Language
- en
- Open access
- green
- doi.org
- Locations
- National Bureau of Economic Research (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- National Bureau of Economic Research (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Pharmaceutical Economics and Policy
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Healthcare Policy and Management
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Keywords
- education, medical technology adoption, prescription drug use, income, experiential learning, Medicare Part D
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