IRAIS 2026 Proceedings
Abstract
Information technology monitoring systems govern behavior by raising detection certainty within jurisdictions, yet their effectiveness depends on whether suppressed demand is eliminated or merely displaced. Prescription Drug Monitoring Programs (PDMPs) are a central IT instrument against opioid overprescription: they make prescription histories visible to every physician, reducing within-state controlled substance prescribing by 9% to over 30% (Bao et al., 2016) and lowering overdose deaths (Pardo, 2017). Yet PDMPs operate within jurisdictional limits—what they cannot observe, they cannot deter. Prior work shows PDMPs reshape rather than suppress demand, with substitution toward heroin (Kc et al., 2022) and cross-border seeking (Shen et al., 2026), but examines only a single offline environment. The COVID-19 pandemic introduced a new digital channel: telehealth. Regulators relaxed restrictions to allow physicians to prescribe controlled substances remotely without a prior in-person visit (Drug Enforcement Administration, 2020), coinciding with staggered PDMP mandate adoption across U.S. states from 2020 to 2022. This creates a natural experiment to examine how a digital prescribing channel fundamentally alters the displacement geometry of IT-enabled monitoring.
Research Objective
We ask: when a jurisdiction-bounded IT monitoring system suppresses demand, where does that demand go—and how does an observable digital channel alter each displacement pathway? Specifically, we examine (1) whether PDMP mandates reduce within-state prescribing and doctor shopping; (2) whether they generate cross-border spillovers in neighboring-state border regions; (3) whether they drive demand into black markets; and (4) how telehealth access moderates each pathway.
Method
We use anonymized pharmacy claims covering over 107 million U.S. patients who filled a controlled substance prescription between January 2020 and December 2022 (over 11 billion observations), supplemented with crowdsourced black-market price data spanning 2018–2022. Outcomes include controlled substance prescription counts, doctor shopping flags (prescriptions overlapping an existing fill by five or more days from a different prescriber), and mean street prices aggregated at the state-month level. For within-state effects, we use cohort-based Synthetic Difference-in-Differences (Arkhangelsky et al., 2021), which constructs synthetic controls matching treated states' pre-treatment trajectories, relaxing parallel trends and addressing negative-weighting concerns in staggered designs. For cross-border spillovers, we focus on ZIP codes within 10 miles of focal-state borders in neighboring states and employ a stacked DiD design (Wing et al., 2024) to handle overlapping treatment exposure. Telehealth moderation is tested by stratifying treated states into those permitting and those not permitting telehealth prescribing for controlled substances during their PDMP-mandate period.
Findings
Within focal states, PDMP mandates reduce total prescriptions by 1.8% (approximately 7,750 fewer per state per month) and doctor shopping by 1.5% (roughly 412 fewer cases per state per month). However, this within-state suppression generates countervailing spillovers: cross-border doctor shopping rises 1.1% in neighboring-state border regions, and black-market prices for controlled substances rise 36.9% (from a pretreatment mean of $0.66 per unit). Monitoring succeeds locally while displacing demand outward. Telehealth fundamentally moderates this pattern. Where telehealth prescribing is permitted, PDMP mandates are associated with larger within-state reductions—2.2% in prescriptions and 1.9%–2.1% in doctor shopping—yet neither cross-border doctor shopping nor black-market prices rise significantly. Where telehealth is unavailable, within-state deterrence weakens but displacement escapes into riskier, less observable channels. This joint pattern is the signature of containment: telehealth offers a channel that outperforms cross-border travel and illicit purchase on cost and access while keeping every transaction visible, absorbing persistent demand within the legitimate prescribing system.
Contribution and Implications
This paper makes three contributions. First, we provide the first comprehensive evidence that PDMP mandates simultaneously displace demand across cross-border, black-market, and digital channels, rather than along a single pathway. Second, we contribute to the IS literature on telehealth by shifting focus from access to governance under risk, showing that telehealth's dual role—attenuating within-state deterrence while preventing displacement into harmful channels—constitutes a deterrence-observability tradeoff not previously identified. Third, we demonstrate that jurisdiction-specific monitoring interventions cannot be evaluated apart from digital channels operating alongside them. These findings imply that PDMP and telehealth policy should be designed jointly. Tightening PDMP enforcement without considering accompanying digital channels risks either driving demand into the black market, absent such a channel, or quietly losing deterrent power, where one exists. As digital prescribing channels continue to expand beyond the pandemic conditions that motivated this study, coordinating PDMP mandates and telehealth access as a single policy instrument is likely to matter more, not less.
References
Arkhangelsky, D., Athey, S., Hirshberg, D. A., Imbens, G. W., & Wager, S. (2021). Synthetic difference-in-differences. American Economic Review, 111(12), 4088–4118.
Bao, Y., Pan, Y., Taylor, A., Radakrishnan, S., Luo, F., Pincus, H. A., & Schackman, B. R. (2016). Prescription drug monitoring programs are associated with sustained reductions in opioid prescribing by physicians. Health Affairs, 35(6), 1045–1051.
Drug Enforcement Administration. (2020). COVID-19 frequently asked questions. U.S. Department of Justice, Diversion Control Division.
Kc, D., Kim, T. T., & Liu, J. (2022). Electronic prescription monitoring and the opioid epidemic. Production and Operations Management, 31(11), 4057–4074.
Pardo, B. (2017). Do more robust prescription drug monitoring programs reduce prescription opioid overdose? Addiction, 112(10), 1773–1783.
Shen, Y., Jiang, D. L., Andritsos, D. A., & Li, X. (2026). Spillover effects from health information systems integration: Evidence from prescription drug monitoring programs. Journal of Operations Management, 72(2), 176–196.
Wing, C., Freedman, S. M., & Hollingsworth, A. (2024). Stacked difference-in-differences. NBER Technical Report.
Recommended Citation
Pan, Xiru; Yaraghi, Niam; and Ghose, Anindya, "From Booze to Blues: Prohibition, Prescription Monitoring, and Persistent Demand" (2026). IRAIS 2026 Proceedings. 1.
https://aisel.aisnet.org/irais2026/1
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