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Progress and Compliance in Alcohol Abuse Treatment

Author

Listed:
  • Hsien-Ming Lien

    (National Cheng-Chi University, Department of Public Finance)

  • Mingshan Lu

    (University of Calgary, Department of Economics)

  • Ching-To Albert Ma

    (Boston University Department of Economics)

  • Thomas G. McGuire

    (Harvard Medical School, Department of Health Care Policy)

Abstract

Improving patient compliance with physicians’ treatment or prescription recommendations is an important goal in medical practice. This paper examines the causal relationship between treatment progress and patient compliance. We hypothesize that patients balance expected benefits and costs during a treatment episode when deciding on compliance; a patient is more likely to follow medical advice if doing so results in an expected net gain in his welfare or health benefit. We use a unique data set of outpatient alcohol abuse treatment to identify a causal effect between treatment progress and compliance. Treatment progress is measured by the clinician’s comments after each attended visit. Compliance is measured by a client attending a scheduled appointment, as well as continuing with the treatment episode. We find that a patient making progress is less likely to drop out of treatment. However, we find no evidence that treatment progress raises the likelihood of a patient attending the next scheduled visit. Our results are robust to controls for unobserved patient heterogeneity.

Suggested Citation

  • Hsien-Ming Lien & Mingshan Lu & Ching-To Albert Ma & Thomas G. McGuire, 2006. "Progress and Compliance in Alcohol Abuse Treatment," Boston University - Department of Economics - Working Papers Series WP2006-043, Boston University - Department of Economics.
    • Handle: RePEc:bos:wpaper:wp2006-043
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    2. Briscese, Guglielmo & Lacetera, Nicola & Macis, Mario & Tonin, Mirco, 2023. "Expectations, reference points, and compliance with COVID-19 social distancing measures," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 103(C).
    3. Sarracino, Francesco & Greyling, Talita & O'Connor, Kelsey J. & Peroni, Chiara & Rossouw, Stephanie, 2024. "Trust predicts compliance with COVID-19 containment policies: Evidence from ten countries using big data," Economics & Human Biology, Elsevier, vol. 54(C).

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