About

Magdalena Cerdá is a Professor and Director of the Center for Opioid Epidemiology and Policy at the Department of Population Health at NYU Grossman School of Medicine. She obtained her doctorate from Harvard University School of Public Health in 2006 and is a former Robert Wood Johnson Health and Society Scholar. Her research focuses on the effects that state and national drug and health policies have on substance abuse trends, as well as on how the urban context shapes violence. Her current funded research examines the impact of cannabis laws and opioid policies on substance abuse, mental illness, and related health problems in the United States and South America. Additionally, she is evaluating how firearm disqualifications based on mental illness and substance abuse could influence population-level firearm-related mortality.

Research topics

• Medicine
• Demography
• Environmental health
• Sociology
• Political Science
• Psychiatry
• Emergency medicine
• Internal medicine
• Medical emergency
• Virology
• Family medicine
• Pediatrics
• Law
• Statistics
• Gerontology
• Mathematics
• Business
• Nursing

Selected publications

• Disseminating a Pediatric Oncology Critical Care Intervention in Latin America and Spain: An Integrated-Knowledge-Translation Approach

  Global Implementation Research and Applications · 2026-03-12

  articleOpen access

  PROACTIVE (Pediatric Oncology Capacity Assessment Tool for Intensive Care) is a quality improvement (QI) intervention that assist pediatric onco-critical care teams identify institutional strengths and gaps, but language barriers have limited its global uptake. This study aimed to evaluate the translation, refinement, and dissemination of Spanish-PROACTIVE guided by an integrated knowledge translation (IKT) approach. We conducted a four-phase mixed-methods study including: (1) translating and piloting Spanish-PROACTIVE in 22 centers across 12 countries in Latin America and Spain, (2) identifying institutional and regional pediatric onco-critical care challenges and QI priorities, (3) assessing barriers to disseminating results, and (4) co-developing dissemination tools. The professionally translated and refined Spanish-PROACTIVE identified key institutional and common regional pediatric onco-critical care challenges including lack of multidisciplinary rounds (only 14% availability). Institutional barriers to disseminating results included limited time and resources, gaps in dissemination knowledge and skill, and lack of mentorship. These findings informed the co-development of tailored dissemination tools, including a leadership-focused slide deck and a clinical-staff-targeted infographic to support internal dissemination. Applying an IKT approach effectively addressed language and dissemination barriers, and improved accessibility and local relevance of PROACTIVE. Spanish-PROACTIVE supports consistent multilingual data collection, and its contextually tailored dissemination tools may enhance internal communication and uptake of findings across Spanish-speaking institutions. This approach offers a practical model for strengthening dissemination and accelerating uptake of intervention results in linguistically diverse, resource-constrained settings, supporting global efforts to improve outcomes for children with cancer.

  PublisherOA PDFDOI

• Advancing person-centered care: Protocol for quality measurement and management (QM2) in the New York State system for opioid use disorder treatment

  PLoS ONE · 2025-09-29

  articleOpen accessCorresponding

  INTRODUCTION: The United States is facing an opioid use disorder (OUD) epidemic, marked by unprecedented overdose death rates. In New York State, synthetic opioids significantly contribute to the increasing overdose deaths, disproportionately impacting Black and Latinx communities. There is an urgent need to address issues related to equitable access to and the quality of care provided by substance use disorder (SUD) treatment programs. In light of this, the Quality Measurement and Management Research Center (QM2-RC) brought together an academic-government partnership to develop a person-centered quality measurement system and to assess its impact on a statewide treatment system that serves approximately 180,000 individuals per year. METHODS AND ANALYSIS: The QM2-RC encompasses three interconnected projects (Project 1, 2, and 3) aimed at developing a quality management strategy and evaluating its impact on system performance across New York State. This report specifically focuses on Project 3, which involves a stepped-wedge trial with 35 clinics receiving a quality management intervention that includes performance coaching. This intervention will be compared to a treatment-as-usual (TAU) condition for clinics not participating in the trial. Administrative data will be utilized to monitor outcomes over four years. The coaching intervention, guided by the Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) model, emphasizes interpreting quality measures and applying insights to enhance care. Coaches will provide support on data utilization, patient-centered care, harm reduction strategies, and the use of patient monitoring tools. The trial aims to evaluate clinic staff and leadership attitudes, experiences, and behaviors through surveys, semi-structured interviews, and external facilitator notes. Primary clinic outcomes will be assessed through adverse events, decreased clinic rates of substance use related emergency department visits and hospitalizations as well as mortality among patients within the first 12 months after admission to treatment after adjusting for individual and community level characteristics. This study is being developed over a multi-year period and will be informed by a mixed-methods approach incorporating multiple data sources, qualitative interviews, patient and clinic surveys. The study is being conducted in partnership with New York State Office of Addiction Services and Supports (OASAS) and will be informed by input from patient, providers, health insurers, family members and local governing units. DISCUSSION: Project 3 of the QM2 study specifically targets key barriers in measuring the quality of SUD treatment, including technological limitations, unvalidated measures, workforce data literacy, and concerns about fairness in assessing clinical complexity. Through the implementation of a stepped-wedge trial involving 35 clinics, the project aims to develop new quality measures, offer performance feedback, and engage clinic leadership and staff in efforts to improve practices. The ultimate goal of Project 3 is to overcome these barriers, promote person-centered care, and improve SUD treatment practices across New York State.

  PublisherDOI

• Changes in psychosis-related emergency department and hospitalization rates among youth following cannabis legalization in Colorado

  Drug and Alcohol Dependence · 2025-05-23 · 3 citations

  article
  PublisherDOI

• Trajectories of neighborhood-level overdose risk predictions for prioritization of harm reduction services: Results from the PROVIDENT study

  Drug and Alcohol Dependence · 2025-10-17

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  PublisherDOI

• Opioid dose, duration, and risk of use disorder in Medicaid patients with musculoskeletal pain

  Pain Medicine · 2025-06-20

  articleOpen accessSenior author

  IMPORTANCE: The CDC recommends initiating opioids for pain treatment at the lowest effective dose and duration; however, how dose, duration, and drug type jointly influence opioid use disorder risk remains a critical gap not addressed by current guidelines. OBJECTIVE: We examine how interactions between dose, duration, and other medication factors (eg, drug type) influence opioid use disorder (OUD) risk. DESIGN, SETTING, PARTICIPANTS, INTERVENTIONS: Using Medicaid claims data (2016-2019) from 25 states, we analyzed opioid-naïve adults, newly diagnosed with musculoskeletal pain who initiated opioids within 3 months of diagnosis. A 6-month washout confirmed no prior opioid exposure or musculoskeletal diagnosis. Initial opioids were categorized by "dose-days supplied" (low [>0-20 mg MME] to very high [>90 mg MME] dose, and short [1-7 days] to moderate [>7-30 days] supply) and by opioid type; physical therapy (PT) sessions were also recorded. Using Poisson regression models, we estimated the OUD risk associated with dose-days categories, adjusting for baseline demographics, clinical characteristics, and medications. We separately examined opioid dose-days and PT, and assessed PT's moderating effect on dose-days' impact. RESULTS: Among 30 536 patients, half initiated opioids at 20-50 MME for 1-7 days, and 20% received PT. OUD risk was 2-3 times higher for opioids initiated for >7-30 days compared to 1-7 days across doses, and 5.5 times higher for opioids initiated for >7-30 days at >90 MME versus 1-7 days at <20 MME. PT alone, neither affected OUD risk nor mitigated the increased risk from longer or higher dose opioids. CONCLUSIONS: Our findings support the need for careful opioid prescribing and alternative pain management strategies, as the observed associations between initial prescription characteristics and OUD were not mitigated by adjunctive PT. RELEVANCE: This study demonstrated that initial opioid prescriptions of 7-30 days, especially above 90 MME/day, increased OUD risk in opioid-naïve patients with musculoskeletal pain; physical therapy did not mitigate the risk. Different opioids posed varied risks, even at the same dose and duration. Careful prescribing and alternative pain management are essential.

  PublisherOA PDFDOI

• The effect of lifting eviction moratoria on fatal drug overdoses in the context of the COVID-19 pandemic in the US

  American Journal of Epidemiology · 2025-05-15

  articleOpen accessSenior author

  Between May 2020 and December 2021, there were 159 872 drug overdose deaths in the United States. Higher eviction rates have been associated with higher overdose mortality. Amid the economic turmoil caused by the COVID-19 pandemic, 43 states and Washington, DC, implemented eviction moratoria of varying durations. These moratoria reduced eviction filing rates, but their impact on fatal drug overdoses remains unexplored. We evaluated the effect of these policies on county-level overdose death rates by focusing on the dates the state eviction moratoria were lifted. We obtained mortality data from the National Center for Health Statistics (NCHS) and eviction moratoria dates from the COVID-19 US State Policy Database. We employed a longitudinal targeted minimum-loss-based estimation with Super Learner to flexibly estimate the average treatment effect of never lifting the moratoria. Lifting state eviction moratoria was associated with a 0.14 per 100 000 higher rate of monthly overdose mortality (95% CI, -0.03 to 0.32), although confidence intervals were wide and included zero. Eviction moratoria may not be sufficient to prevent overdose mortality during crises such as the COVID-19 pandemic.

  PublisherOA PDFDOI

• Cannabis legalization and cannabis use disorder in United States Veterans Health Administration patients with and without psychiatric disorders, 2005–2022: a repeated cross-sectional study

  The Lancet Regional Health - Americas · 2025-07-01 · 3 citations

  articleOpen access

  Background: We investigated whether the associations of state medical and recreational cannabis legalization (MCL, RCL enactment) with increasing prevalence of Cannabis Use Disorder (CUD) differed among patients in the United States (US) Veterans Health Administration (VHA) who did or did not have common psychiatric disorders. Methods: Electronic medical record data (2005-2022) were analyzed on patients aged 18-75 with ≥1 VHA primary care, emergency department, or mental health visit and no hospice/palliative care within a given year (sample sizes ranging from 3,234,382 in 2005 to 4,436,883 in 2022). Patients were predominantly male (>80%) and non-Hispanic White (>60%). Utilizing all 18 years of data, CUD prevalence increases attributable to MCL or RCL enactment were estimated among patients with affective, anxiety, psychotic-spectrum disorders, and Any Psychiatric Disorder (APD) using staggered difference-in-difference (DiD) models and 99% Confidence Intervals (CIs), testing differences between patient groups with and without psychiatric disorders via non-overlap in the 99% CIs of their DiD estimates. Findings: Among APD-negative patients, CUD prevalence was <1.0% in all years, while among APD-positive patients, CUD prevalence increased from 3.26% in 2005 to 5.68% in 2022 in no-CL states, from 3.51% to 6.35% in MCL-only states, and from 3.41% to 6.35% in MCL/RCL states. Among the APD group, DiD estimates of MCL-only and MCL/RCL effects were modest-sized, but the lower bound of the 99% CI for the DiD estimate for MCL-only and MCL/RCL effects was larger than the upper bound of the 99% CI among the no-APD group, indicating significantly stronger MCL-only and MCL/RCL effects among patients with APD. Results were similar for MCL-only and MCL/RCL effects among disorder-specific groups (depression, post-traumatic stress disorder [PTSD], anxiety or bipolar disorders) and for MCL/RCL effects among patients with psychotic-spectrum disorders. Interpretation: Cannabis legalization contributed to greater CUD prevalence increases among patients with psychiatric disorders. However, modest-sized DiD estimates suggested operation of other factors, e.g., commercialization, changing attitudes, expectancies. As cannabis legalization widens, recognizing and treating CUD in patients with psychiatric disorders becomes increasingly important. Funding: This study was supported by National Institute on Drug Abuse grant R01DA048860, the New York State Psychiatric Institute, and the VA Centers of Excellence in Substance Addiction Treatment and Education.

  PublisherDOI

• Stemming the Tide of the US Overdose Crisis: How Can We Leverage the Power of Data Science and Artificial Intelligence?

  Milbank Quarterly · 2025-06-04

  articleOpen access1st authorCorresponding

  Policy Points We can leverage data science and artificial intelligence to inform state and local resource allocation for overdose prevention. Data science and artificial intelligence can help us answer four questions: (1) What is the impact of laws on access to interventions and overdose risk? (2) Where should interventions be targeted? (3) Which types of demographic subgroups benefit the most and the least from interventions? and (4) Which types of interventions should they invest in for each setting and population? Advances in data science and artificial intelligence can accelerate the pace at which we can answer these critical questions and help inform an effective overdose prevention response.

  PublisherOA PDFDOI

• Stimulant Use Disorder Diagnoses in Adolescent and Young Adult Medicaid Enrollees

  JAMA Psychiatry · 2025-10-15 · 2 citations

  article

  Importance: There has been a national increase in fatal and nonfatal overdoses involving stimulants, and 4.5 million US individuals meet criteria for stimulant use disorder (UD), with the highest prevalence in young adults. However, limited information exists on trends in diagnosed stimulant UD. Objective: To estimate trends in the proportion of adolescent and young adult Medicaid enrollees diagnosed with a stimulant UD from 2001 to 2020. Design, Setting, and Participants: A repeated cross-sectional study (2001-2020) was conducted using administrative health care claims data from Medicaid (public insurance program in US). Publicly insured adolescents (aged 13-17 years) and young adults (aged 18-24 or 25-29 years) from 42 US states were included. Data were analyzed from January 2025 to July 2025. Main Outcomes and Measures: Stimulant UD was defined as an inpatient or outpatient International Classification of Diseases diagnosis code in the year, with cocaine UD and noncocaine psychostimulant UD evaluated separately. The annual proportion with stimulant UD diagnoses was stratified by age group, sex, race and ethnicity, and presence of attention-deficit/hyperactivity disorder (ADHD) diagnosis or stimulant prescription in the year. Differences comparing 2001 with 2020 were summarized. Characteristics of those diagnosed with stimulant UD in 2020 were described. Results: The sample included 5.7 million (2001) to 16.1 million Medicaid enrollees (2020) per year; in 2020, 54.2% were female, and 7.1 million were adolescents. From 2001 to 2020, the proportion diagnosed with noncocaine psychostimulant UD increased from 0.09% to 0.49% (prevalence ratio [PR], 5.47 [95% CI, 5.20-5.75]) in those aged 18 to 24 years, from 0.13% to 1.63% (PR, 12.55 [95% CI, 11.83-13.31]) for ages 25 to 29 years, and from 0.10% to 0.91% among young adults aged 18 to 29 years. Among adolescents, the proportion diagnosed with noncocaine psychostimulant UD varied between 0.03% and 0.07%. The proportion diagnosed with cocaine UD was stable in young adults (range, 0.17%-0.34% [18-24 years] and 0.53%-0.79% [25-29 years]) and declined in adolescents (from 0.04% to 0.01%). Cocaine and noncocaine psychostimulant UD diagnoses were 2 to 4 times more common in patients with an ADHD diagnosis or stimulant prescription. Most patients diagnosed with a stimulant UD in 2020 were also diagnosed with a mental health disorder (68%-82%) or other substance UD (72%-78%). Conclusions and Relevance: The prevalence of noncocaine psychostimulant UD diagnoses in young adult Medicaid patients increased over the last 2 decades, potentially associated with an increasing use of prescription and illicit stimulants along with increased clinical detection. These trends raise concerns given recent rises in stimulant-involved overdose fatalities and stress the need for evidence-based stimulant UD treatments for young people.

  PublisherDOI

• Prescribing of controlled substances to adolescents and young adults enrolled in Medicaid, 2001–2019

  Drug and Alcohol Dependence · 2025-12-15

  articleOpen access

  OBJECTIVE: To examine nationwide trends in the prescribing of controlled medications to early adolescents, adolescents, and young adults enrolled in public insurance (Medicaid) from 2001 to 2019. METHODS: The study utilized US Medicaid data covering publicly insured enrollees from 43 states (2001-2019). Early adolescents (10-12y), adolescents (13-17y), and young adults (18-24y, 25-29y) with ≥ 10 months enrollment in each calendar year were included. Filled prescription for opioids, stimulants, benzodiazepines, Z-hypnotics, barbiturates, and gabapentin were identified. In each calendar year, annual proportions with 1 + controlled medication, 2 + classes of controlled medications, and each controlled medication were estimated. RESULTS: In 2019, the sample included 17.9 million enrollees (53 % female). The annual proportion prescribed any controlled medication peaked at 17.5 % in early adolescents (2003), 20.6 % in adolescents (2009), and 34.1 % (18-24y) and 47.0 % (25-29y) in young adults (2010). By 2019, the proportions declined to 11.7 % (early adolescents), 12.6 % (adolescents), 16.2 % (18-24y), and 23.9 % (25-29y). Trends varied by medication and age. The largest absolute decline was in the proportion with an opioid filled (2010 =29.8 %, 2019 =11.2 %, young adults 18-24y; 2003 =14.3 %, 2019 =4.4 %, adolescents). In contrast, the proportion with a stimulant fill increased, with eight-fold increases in young adults 25-29y (2001 =0.3 %, 2019 =2.6 %). Benzodiazepine and Z-hypnotic use peaked in 2010 and declined through 2019. CONCLUSIONS: In the past two decades, there were increases in stimulant prescriptions among young Medicaid enrollees. The declines in opioid, benzodiazepines, barbiturate and Z-hypnotic prescribing are encouraging and may indicate more cautious prescribing related to greater awareness of harms such as misuse and overdose, along with policy initiatives.

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Recent grants

• Reducing Drug-Related Mortality Using Predictive Analytics: A Randomized, Statewide, Community Intervention Trial

  NIH · $719k · 2019–2024

• Examining the synergistic effects of cannabis and prescription opioid policies on chronic pain, opioid prescribing, and opioid overdose

  NIH · $4.3M · 2019–2025

• Substance abuse history, mental health and firearm violence: from evidence to action

  NIH · $440k · 2016–2019

• NIH Grant F31HD049332

  NIH · $67k · 2008

• Reducing Drug-Related Mortality Using Predictive Analytics: A Randomized, Statewide, Community Intervention Trial

  NIH · $3.1M · 2019–2025

Frequent coauthors

• Deborah S. Hasin

  Columbia University

  301 shared

• Sílvia S. Martins

  Columbia University

  201 shared

• Sandro Galea

  Boston University

  145 shared

• Katherine M. Keyes

  Columbia University

  140 shared

• Lilian Ghandour

  American University of Beirut

  101 shared

• Navin Kumar

  100 shared

• Kate Nyhan

  Yale University

  100 shared

• Jenny Scott

  University of Bristol

  100 shared

Labs

• Health Tech HubPI