IDEAS home Printed from https://ideas.repec.org/p/yor/hectdg/23-15.html
   My bibliography  Save this paper

Effectiveness of Population-Based Hypertension Screening: A Multidimensional Regression Discontinuity Design

Author

Listed:
  • Kämpfen, F.;
  • Gómez-Olivé, X.;
  • O’Donnell, O.;
  • Riumallo Herl, C.;

Abstract

By detecting asymptomatic risk factors, such as hypertension, population-based screening can prevent disease but also induce use of low-value healthcare by false positives. Using data on individuals aged 40+ in rural South Africa and a multidimensional regression discontinuity design, we estimate effects of clinical referral of those with measured blood pressure (BP) above diagnostic thresholds for hypertension. Referral increases hypertension treatment but has no effect on BP after four years, on average. However, for screens that are less likely to be false positives—based on time of day and air temperature at BP measurement—we estimate that referral reduces mean systolic BP by 5 mm Hg (3.6%) and raises the probability of achieving BP control by 22 percentage points (44%). These results demonstrate the potential for false positives to lower the average effect of screening.

Suggested Citation

  • Kämpfen, F.; & Gómez-Olivé, X.; & O’Donnell, O.; & Riumallo Herl, C.;, 2023. "Effectiveness of Population-Based Hypertension Screening: A Multidimensional Regression Discontinuity Design," Health, Econometrics and Data Group (HEDG) Working Papers 23/15, HEDG, c/o Department of Economics, University of York.
  • Handle: RePEc:yor:hectdg:23/15
    as

    Download full text from publisher

    File URL: https://www.york.ac.uk/media/economics/documents/hedg/workingpapers/2023/2315.pdf
    File Function: Main text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ryan D. Edwards, 2018. "If My Blood Pressure Is High, Do I Take It to Heart? Behavioral Effects of Biomarker Collection in the Health and Retirement Study," Demography, Springer;Population Association of America (PAA), vol. 55(2), pages 403-434, April.
    2. Sebastian Calonico & Matias D. Cattaneo & Rocio Titiunik, 2014. "Robust data-driven inference in the regression-discontinuity design," Stata Journal, StataCorp LP, vol. 14(4), pages 909-946, December.
    3. Sebastian Calonico & Matias D. Cattaneo & Rocio Titiunik, 2014. "Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs," Econometrica, Econometric Society, vol. 82, pages 2295-2326, November.
    4. Matias D. Cattaneo & Michael Jansson & Xinwei Ma, 2020. "Simple Local Polynomial Density Estimators," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1449-1455, July.
    5. Emily Oster, 2018. "Diabetes and Diet: Purchasing Behavior Change in Response to Health Information," American Economic Journal: Applied Economics, American Economic Association, vol. 10(4), pages 308-348, October.
    6. Capuno, Joseph & Kraft, Aleli & O'Donnell, Owen, 2021. "Effectiveness of clinic-based cardiovascular disease prevention: A randomized encouragement design experiment in the Philippines," Social Science & Medicine, Elsevier, vol. 283(C).
    7. Hut, Stefan & Oster, Emily, 2022. "Changes in household diet: Determinants and predictability," Journal of Public Economics, Elsevier, vol. 208(C).
    8. Prina, Silvia & Royer, Heather, 2014. "The importance of parental knowledge: Evidence from weight report cards in Mexico," Journal of Health Economics, Elsevier, vol. 37(C), pages 232-247.
    9. Ciancio, Alberto & Kämpfen, Fabrice & Kohler, Hans-Peter & Kohler, Iliana V., 2021. "Health screening for emerging non-communicable disease burdens among the global poor: Evidence from sub-Saharan Africa," Journal of Health Economics, Elsevier, vol. 75(C).
    10. Kim, Hyuncheol Bryant & Lee, Suejin A. & Lim, Wilfredo, 2019. "Knowing is not half the battle: Impacts of information from the National Health Screening Program in Korea," Journal of Health Economics, Elsevier, vol. 65(C), pages 1-14.
    11. Papay, John P. & Willett, John B. & Murnane, Richard J., 2011. "Extending the regression-discontinuity approach to multiple assignment variables," Journal of Econometrics, Elsevier, vol. 161(2), pages 203-207, April.
    12. Charles E. Phelps & Alvin I. Mushlin, 1988. "Focusing Technology Assessment Using Medical Decision Theory," Medical Decision Making, , vol. 8(4), pages 279-289, December.
    13. Christopher Jepsen & Peter Mueser & Kenneth Troske, 2017. "Second Chance for High School Dropouts? A Regression Discontinuity Analysis of Postsecondary Educational Returns to the GED," Journal of Labor Economics, University of Chicago Press, vol. 35(S1), pages 273-304.
    14. Michal Kolesár & Christoph Rothe, 2018. "Inference in Regression Discontinuity Designs with a Discrete Running Variable," American Economic Review, American Economic Association, vol. 108(8), pages 2277-2304, August.
    15. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    16. Rebecca L. Thornton, 2008. "The Demand for, and Impact of, Learning HIV Status," American Economic Review, American Economic Association, vol. 98(5), pages 1829-1863, December.
    17. Matias D. Cattaneo & Michael Jansson & Xinwei Ma, 2018. "Manipulation testing based on density discontinuity," Stata Journal, StataCorp LP, vol. 18(1), pages 234-261, March.
    18. Zhao, Meng & Konishi, Yoshifumi & Glewwe, Paul, 2013. "Does information on health status lead to a healthier lifestyle? Evidence from China on the effect of hypertension diagnosis on food consumption," Journal of Health Economics, Elsevier, vol. 32(2), pages 367-385.
    19. Slade, Alexander N., 2012. "Health investment decisions in response to diabetes information in older Americans," Journal of Health Economics, Elsevier, vol. 31(3), pages 502-520.
    20. Carrera, Mariana & Hasan, Syeda A. & Prina, Silvia, 2020. "Do health risk assessments change eating habits at the workplace?," Journal of Economic Behavior & Organization, Elsevier, vol. 172(C), pages 236-246.
    21. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Roc ́ıo Titiunik, 2017. "rdrobust: Software for regression-discontinuity designs," Stata Journal, StataCorp LP, vol. 17(2), pages 372-404, June.
    22. McCrary, Justin, 2008. "Manipulation of the running variable in the regression discontinuity design: A density test," Journal of Econometrics, Elsevier, vol. 142(2), pages 698-714, February.
    23. Pascaline Dupas, 2011. "Health Behavior in Developing Countries," Annual Review of Economics, Annual Reviews, vol. 3(1), pages 425-449, September.
    24. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881.
    25. Will Cook, 2019. "The effect of personalised weight feedback on weight loss and health behaviours: Evidence from a regression discontinuity design," Health Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 161-172, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gaggero, Alessio & Gil, Joan & Jiménez-Rubio, Dolores & Zucchelli, Eugenio, 2022. "Does health information affect lifestyle behaviours? The impact of a diabetes diagnosis," Social Science & Medicine, Elsevier, vol. 314(C).
    2. Gaggero, A. & Gil, J. & Jiménez-Rubio, D. & Zucchelli, E., 2021. "Health information and lifestyle behaviours: the impact of a diabetes diagnosis," Health, Econometrics and Data Group (HEDG) Working Papers 21/02, HEDG, c/o Department of Economics, University of York.
    3. Chu, Yu-Wei Luke & Cuffe, Harold E, 2020. "Do Struggling Students Benefit From Continued Student Loan Access? Evidence From University and Beyond," Working Paper Series 21067, Victoria University of Wellington, School of Economics and Finance.
    4. Blaise Melly & Rafael Lalive, 2020. "Estimation, Inference, and Interpretation in the Regression Discontinuity Design," Diskussionsschriften dp2016, Universitaet Bern, Departement Volkswirtschaft.
    5. Albert Whata & Charles Chimedza, 2021. "Credibility of Causal Estimates from Regression Discontinuity Designs with Multiple Assignment Variables," Stats, MDPI, vol. 4(4), pages 1-23, November.
    6. Luciana Juvenal & Paulo Santos Monteiro, 2021. "Risky Gravity," Discussion Papers 21/02, Department of Economics, University of York.
    7. ZHAO Meng & YIN Ting & SEKIZAWA Yoichi, 2023. "Make Behavioral Changes for a Healthier Liver? Evidence from a liver function test in Japan," Discussion papers 23010, Research Institute of Economy, Trade and Industry (RIETI).
    8. Ciancio, Alberto & Kämpfen, Fabrice & Kohler, Hans-Peter & Kohler, Iliana V., 2021. "Health screening for emerging non-communicable disease burdens among the global poor: Evidence from sub-Saharan Africa," Journal of Health Economics, Elsevier, vol. 75(C).
    9. Burgherr, David, 2022. "Behavioral Responses to a Pension Savings Mandate : Quasi-experimental Evidence from Swiss Tax Data," CAGE Online Working Paper Series 645, Competitive Advantage in the Global Economy (CAGE).
    10. Mellace, Giovanni & Ventura, Marco, 2019. "Intended and unintended effects of public incentives for innovation. Quasi-experimental evidence from Italy," Discussion Papers on Economics 9/2019, University of Southern Denmark, Department of Economics.
    11. Vanessa Cirulli & Giuliano Resce & Marco Ventura, 2021. "Co-payment exemption and healthcare consumption. Quasi-experimental evidence from Italy," Working Papers in Public Economics 203, University of Rome La Sapienza, Department of Economics and Law.
    12. Simona Helmsmüller & Andreas Landmann, 2022. "Does free hospitalization insurance change health care consumption of the poor? Short-term evidence from Pakistan," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 47(1), pages 238-275, March.
    13. Bhalotra, Sonia R. & Britto, Diogo & Pinotti, Paolo & Sampaio, Breno, 2021. "Job Displacement, Unemployment Benefits and Domestic Violence," IZA Discussion Papers 14543, Institute of Labor Economics (IZA).
    14. Pasquini, Ricardo A., 2021. "Effects of regulating the brokerage commission in the rental market: Evidence from Buenos Aires," Journal of Housing Economics, Elsevier, vol. 54(C).
    15. Iizuka, Toshiaki & Nishiyama, Katsuhiko & Chen, Brian & Eggleston, Karen, 2021. "False alarm? Estimating the marginal value of health signals," Journal of Public Economics, Elsevier, vol. 195(C).
    16. Myerson, Rebecca & Lu, Tianyi & Yuan, Yong & Liu, Gordon, 2020. "The impact of government income transfers on tobacco and alcohol use: Evidence from China," Economics Letters, Elsevier, vol. 186(C).
    17. Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
    18. Powdthavee, Nattavudh, 2021. "Education and pro-environmental attitudes and behaviours: A nonparametric regression discontinuity analysis of a major schooling reform in England and Wales," Ecological Economics, Elsevier, vol. 181(C).
    19. Kim, Hyuncheol Bryant & Lee, Suejin & Lim, Wilfredo, 2017. "Knowing Is Not Half the Battle: Impacts of the National Health Screening Program in Korea," IZA Discussion Papers 10650, Institute of Labor Economics (IZA).
    20. Christopher Erwin, 2019. "Low-performing student responses to state merit scholarships," Working Papers 2019-02, Auckland University of Technology, Department of Economics.

    More about this item

    Keywords

    clinical referral; blood pressure; false positive; sub-saharan africa;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:yor:hectdg:23/15. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Jane Rawlings (email available below). General contact details of provider: https://edirc.repec.org/data/deyoruk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.