Dr. Mohammad Jalali (aka, ‘MJ’) is an Associate Professor at Harvard Medical School and a senior scientist at MGH Institute for Technology Assessment. He was previously a research faculty at MIT Sloan School of Management and a consultant at the World Bank. MJ uses analytics and simulation-based approaches to help policymakers identify and develop high-leverage policies that not only are effective over the long haul, but also are not thwarted by unanticipated side effects. To achieve this goal, he spends a great deal of time working with decision-makers and policymakers, doing fieldwork and collecting different types of data that can inform richer models and analyses.
MJ’s work has been featured by various national and international media outlets, including Associated Press, The Hill, Newsweek, Scientific American, Business Insider, and NPR. He is an associate editor of System Dynamics Review and is on the editorial board of the Journal on Policy and Complex Systems. He is the recipient of the 2015 Dana Meadows Award, the 2015 WINFORMS Excellence Award, and the 2014 Lupina Young Researcher Award. MJ received his PhD in Systems Engineering, with a concentration on management and health care systems, from Virginia Tech in 2015.
Research approach and areas:
In his research trajectory, MJ follows three goals. First, he conducts simulation modeling and informatics research for various population-based health policies, focusing on health outcomes and cost-effectiveness. In his modeling research—drawn on theories of optimization and strategy—he analyzes the impacts of large-scale policies for prevention, screening, and treatment. MJ has developed models for obesity, post-traumatic stress disorder, and depression. He is currently working with the FDA to develop an opioid systems model, informing opioid policies at the FDA and other government agencies. Other areas of his modeling research include drug-shortages in pharmaceutical supply chains, organizational cybersecurity in health care, and the diffusion of medical technologies.
Second, MJ focuses his research on mechanisms that connect human decision-making to health care systems, because that is where many important policy-resistant problems lie. In particular, he aims to understand how and why many health policies fail to produce lasting results or create results counter to their goals.
Third, he wants his research to rigorously connect models with quantitative data. The growing complexity of health care issues, combined with the ubiquity of large amounts of data, requires increasingly sophisticated analytical methods. MJ complements his phenomenological research with methodological contributions that build bridges across methodological and application domains. For example, he has contributed to adapting various simulation-optimization approaches for model calibration and parameter estimation in dynamic models (e.g., the method of simulated moments and indirect inference), improving systematic review techniques, and developing a novel method for aggregation of prior stochastic and heterogeneous statistical findings.
Selected media coverage:
New York Times: Will Hot Weather Kill the Coronavirus Where You Live?
Washington Post: Summer weather could help fight coronavirus spread but won’t halt the pandemic
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Selected Publications
Stringfellow, Erin J; Dong, Huiru; Khatami, Seyedeh Nazanin; Lee, Hannah; Jalali, Mohammad S
In: Addiction, vol. 120, iss. 6, pp. 1198-1206, 2025, ISSN: 1360-0443.
@article{pmid39994821,
title = {The association between buprenorphine doses above 16 milligrams and treatment retention in a multi-payer national sample in the United States, 2014 to 2021},
author = {Erin J Stringfellow and Huiru Dong and Seyedeh Nazanin Khatami and Hannah Lee and Mohammad S Jalali},
doi = {10.1111/add.70002},
issn = {1360-0443},
year = {2025},
date = {2025-06-01},
urldate = {2025-02-01},
journal = {Addiction},
volume = {120},
issue = {6},
pages = {1198-1206},
abstract = {BACKGROUND AND AIMS: Buprenorphine-naloxone reduces overdose deaths in people with opioid use disorder (OUD). Treatment retention increases with higher daily doses. No national studies exist on retention\'s association with 24, 32 and 40 mg. This study aimed to: (1) estimate the effect on treatment retention of buprenorphine-naloxone doses between 4 and 40 mg compared with 16; and (2) compare the effect on treatment retention of 24, 32 and 40 mg doses.nnDESIGN: Observational cohort study in a national, multi-payer sample of prescription claims (IQVIA) of episodes involving buprenorphine-naloxone for OUD. Incident episodes started between 1 January 2014 and 31 March 2020, with a washout of 180 days. New episodes started with a 14+ day gap between prescriptions.nnSETTING: United States of America.nnPARTICIPANTS: The sample involved 620 229 episodes across 498 879 patients [42.3% female; mean age 37.9 (standard deviaion: 11.9)] who were dispensed prescriptions of buprenorphine-naloxone for OUD.nnMEASUREMENTS: The exposure was the maximum daily dose of buprenorphine-naloxone reached in the first 30 days of an episode, ranging from 4 to 40 mg. The outcome, treatment retention, was defined as having an active prescription at 1, 3, 6, 12, or 18 months. Covariates were age, sex, race and ethnicity, primary payer, and year of episode initiation.nnFINDINGS: Daily doses of 24, 32 and 40 mg increased retention compared with 16 mg at 1-18 months [adjusted odds ratio (aOR) range = 1.17; 95% confidence interval (CI) = 1.14, 1.20 at 18 months to 1.52 (CI = 1.49, 1.54) at 1 month, both for 24 mg]. In pairwise comparisons, 32 mg was favorable to 24 mg at 6, 12 and 18 months [aOR = 1.06 (95% CI = 1.02, 1.10) at 6 months; aOR = 1.09 (95% CI = 1.04, 1.14) at 12 months; aOR = 1.12 (95% CI = 1.06, 1.19) at 18 months], and 40 mg was favorable to 24 mg at 12 and 18 months [aOR = 1.10 (95% CI = 1.01, 1.21) at 12 months; aOR = 1.18 (95% CI = 1.06, 1.30) at 18 months].nnCONCLUSIONS: Daily buprenorphine-naloxone doses of 24 mg appear to be associated with increased treatment retention compared with 16 mg and, for 6+ month episodes, 32 and 40 mg appear to be associated with increased retention compared with 24 mg.},
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BACKGROUND AND AIMS: Buprenorphine-naloxone reduces overdose deaths in people with opioid use disorder (OUD). Treatment retention increases with higher daily doses. No national studies exist on retention's association with 24, 32 and 40 mg. This study aimed to: (1) estimate the effect on treatment retention of buprenorphine-naloxone doses between 4 and 40 mg compared with 16; and (2) compare the effect on treatment retention of 24, 32 and 40 mg doses.nnDESIGN: Observational cohort study in a national, multi-payer sample of prescription claims (IQVIA) of episodes involving buprenorphine-naloxone for OUD. Incident episodes started between 1 January 2014 and 31 March 2020, with a washout of 180 days. New episodes started with a 14+ day gap between prescriptions.nnSETTING: United States of America.nnPARTICIPANTS: The sample involved 620 229 episodes across 498 879 patients [42.3% female; mean age 37.9 (standard deviaion: 11.9)] who were dispensed prescriptions of buprenorphine-naloxone for OUD.nnMEASUREMENTS: The exposure was the maximum daily dose of buprenorphine-naloxone reached in the first 30 days of an episode, ranging from 4 to 40 mg. The outcome, treatment retention, was defined as having an active prescription at 1, 3, 6, 12, or 18 months. Covariates were age, sex, race and ethnicity, primary payer, and year of episode initiation.nnFINDINGS: Daily doses of 24, 32 and 40 mg increased retention compared with 16 mg at 1-18 months [adjusted odds ratio (aOR) range = 1.17; 95% confidence interval (CI) = 1.14, 1.20 at 18 months to 1.52 (CI = 1.49, 1.54) at 1 month, both for 24 mg]. In pairwise comparisons, 32 mg was favorable to 24 mg at 6, 12 and 18 months [aOR = 1.06 (95% CI = 1.02, 1.10) at 6 months; aOR = 1.09 (95% CI = 1.04, 1.14) at 12 months; aOR = 1.12 (95% CI = 1.06, 1.19) at 18 months], and 40 mg was favorable to 24 mg at 12 and 18 months [aOR = 1.10 (95% CI = 1.01, 1.21) at 12 months; aOR = 1.18 (95% CI = 1.06, 1.30) at 18 months].nnCONCLUSIONS: Daily buprenorphine-naloxone doses of 24 mg appear to be associated with increased treatment retention compared with 16 mg and, for 6+ month episodes, 32 and 40 mg appear to be associated with increased retention compared with 24 mg.
Pan, Fenglian; Zhou, You; Vivas-Valencia, Carolina; Kong, Nan; Ott, Carol; Jalali, Mohammad S; Liu, Jian
Modeling opioid overdose events recurrence with a covariate-adjusted triggering point process Journal Article
In: PLoS Comput Biol, vol. 21, no. 5, pp. e1012889, 2025, ISSN: 1553-7358.
@article{pmid40324024,
title = {Modeling opioid overdose events recurrence with a covariate-adjusted triggering point process},
author = {Fenglian Pan and You Zhou and Carolina Vivas-Valencia and Nan Kong and Carol Ott and Mohammad S Jalali and Jian Liu},
doi = {10.1371/journal.pcbi.1012889},
issn = {1553-7358},
year = {2025},
date = {2025-05-01},
journal = {PLoS Comput Biol},
volume = {21},
number = {5},
pages = {e1012889},
abstract = {Substance use disorder, particularly opioid-related, is a serious public health challenge in the U.S. Accurately predicting opioid overdose events and stratifying the risk of having such an event are critical for healthcare providers to deliver effective interventions in patients with opioid overdose. Despite a large body of literature investigating various risk factors for the prediction, the existing research to date has not explicitly investigated and quantitatively modeled how an individual's past opioid overdose events affect future occurrences. In this paper, we proposed a covariate-adjusted triggering point process to simultaneously model the effect of various risk factors on opioid overdose events and the triggering mechanism among opioid overdose events. The prediction performance was assessed by the U.S. state-wise Medicaid reimbursement claims data. Compared with commonly used prediction models, the proposed model achieved the lowest Mean Absolute Errors and Mean Absolute Percentage Errors on 30-, 60-, 90, 120-, 150-, and 180-day-ahead predictions. In addition, our results showed the statistical significance of considering the triggering mechanism for recurrent opioid overdose events prediction. On average, around 47% of the event recurrence were explained by the triggering mechanism.},
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Substance use disorder, particularly opioid-related, is a serious public health challenge in the U.S. Accurately predicting opioid overdose events and stratifying the risk of having such an event are critical for healthcare providers to deliver effective interventions in patients with opioid overdose. Despite a large body of literature investigating various risk factors for the prediction, the existing research to date has not explicitly investigated and quantitatively modeled how an individual's past opioid overdose events affect future occurrences. In this paper, we proposed a covariate-adjusted triggering point process to simultaneously model the effect of various risk factors on opioid overdose events and the triggering mechanism among opioid overdose events. The prediction performance was assessed by the U.S. state-wise Medicaid reimbursement claims data. Compared with commonly used prediction models, the proposed model achieved the lowest Mean Absolute Errors and Mean Absolute Percentage Errors on 30-, 60-, 90, 120-, 150-, and 180-day-ahead predictions. In addition, our results showed the statistical significance of considering the triggering mechanism for recurrent opioid overdose events prediction. On average, around 47% of the event recurrence were explained by the triggering mechanism.
Dong, Huiru; Stringfellow, Erin J; Jalali, Mohammad S
State-level racial and ethnic disparities in buprenorphine treatment duration in the United States Journal Article
In: Am J Addict, vol. 34, no. 1, pp. 69-74, 2025, ISSN: 1521-0391.
@article{pmid39107678,
title = {State-level racial and ethnic disparities in buprenorphine treatment duration in the United States},
author = {Huiru Dong and Erin J Stringfellow and Mohammad S Jalali},
doi = {10.1111/ajad.13638},
issn = {1521-0391},
year = {2025},
date = {2025-01-01},
urldate = {2024-08-01},
journal = {Am J Addict},
volume = {34},
number = {1},
pages = {69-74},
abstract = {BACKGROUND AND OBJECTIVES: National trends reveal a concerning escalation in racial and ethnic disparities in buprenorphine treatment duration for opioid use disorder. However, the extent of such disparities at the state level remains largely unexplored. This study aims to examine such disparities at the state level.nnMETHODS: We analyzed 9,040,620 buprenorphine prescriptions dispensed between January 2011 and December 2020 from IQVIA Longitudinal Prescription data. The primary outcome was the difference in median treatment duration between White people and racial and ethnic minorities. We also included a second outcome measurement to quantify the difference in median treatment duration among episodes lasting ≥180 days. Using quantile regressions, we examined racial and ethnic disparities in treatment duration, adjusting for the patient\'s age, sex, payment type, and calendar year of the treatment episode. All analyses were conducted at the state level.nnRESULTS: Our study revealed substantial statewide variations in racial and ethnic disparities. Specifically, 21 states showed longer treatment durations for White people across all episodes, and eight states displayed similar trends among episodes lasting ≥180 days. Five states exhibited longer treatment durations for White people in both overall and long-term episodes. Fifteen states showed no racial and ethnic disparities.nnCONCLUSION AND SCIENTIFIC SIGNIFICANCE: These results are among the first to indicate substantial statewide variations in racial and ethnic disparities in buprenorphine treatment episode duration, providing a critical foundation for targeted interventions to enhance buprenorphine treatment, especially in states confronting such pronounced racial and ethnic disparities.},
keywords = {},
pubstate = {published},
tppubtype = {article}
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BACKGROUND AND OBJECTIVES: National trends reveal a concerning escalation in racial and ethnic disparities in buprenorphine treatment duration for opioid use disorder. However, the extent of such disparities at the state level remains largely unexplored. This study aims to examine such disparities at the state level.nnMETHODS: We analyzed 9,040,620 buprenorphine prescriptions dispensed between January 2011 and December 2020 from IQVIA Longitudinal Prescription data. The primary outcome was the difference in median treatment duration between White people and racial and ethnic minorities. We also included a second outcome measurement to quantify the difference in median treatment duration among episodes lasting ≥180 days. Using quantile regressions, we examined racial and ethnic disparities in treatment duration, adjusting for the patient's age, sex, payment type, and calendar year of the treatment episode. All analyses were conducted at the state level.nnRESULTS: Our study revealed substantial statewide variations in racial and ethnic disparities. Specifically, 21 states showed longer treatment durations for White people across all episodes, and eight states displayed similar trends among episodes lasting ≥180 days. Five states exhibited longer treatment durations for White people in both overall and long-term episodes. Fifteen states showed no racial and ethnic disparities.nnCONCLUSION AND SCIENTIFIC SIGNIFICANCE: These results are among the first to indicate substantial statewide variations in racial and ethnic disparities in buprenorphine treatment episode duration, providing a critical foundation for targeted interventions to enhance buprenorphine treatment, especially in states confronting such pronounced racial and ethnic disparities.
Lee, Hannah; Otero-Leon, Daniel; Dong, Huiru; Stringfellow, Erin J; Jalali, Mohammad S
Uncovering Patterns in Overdose Deaths: An Analysis of Spike Identification in Fatal Drug Overdose Data in Massachusetts, 2017-2023 Journal Article
In: Public Health Rep, pp. 333549241299613, 2024, ISSN: 1468-2877.
@article{pmid39717009,
title = {Uncovering Patterns in Overdose Deaths: An Analysis of Spike Identification in Fatal Drug Overdose Data in Massachusetts, 2017-2023},
author = {Hannah Lee and Daniel Otero-Leon and Huiru Dong and Erin J Stringfellow and Mohammad S Jalali},
doi = {10.1177/00333549241299613},
issn = {1468-2877},
year = {2024},
date = {2024-12-01},
journal = {Public Health Rep},
pages = {333549241299613},
abstract = {OBJECTIVES: Yearly rolling aggregate trends or rates are commonly used to analyze trends in overdose deaths, but focusing on long-term trends can obscure short-term fluctuations (eg, daily spikes). We analyzed data on spikes in daily fatal overdoses and how various spike detection thresholds influence the identification of spikes.nnMATERIALS AND METHODS: We used a spike detection algorithm to identify spikes among 16 660 drug-related overdose deaths (from any drug) reported in Massachusetts' vital statistics from 2017 through 2023. We adjusted the parameters of the algorithm to define spikes in 3 distinct scenarios: deaths exceeding 2 adjusted moving SDs above the 7-, 30-, and 90-day adjusted moving average.nnRESULTS: Our results confirmed the on-the-ground observation that there are days when many more people die of overdoses than would be expected based on fluctuations due to differences among people alone. We identified spikes on 5.8% to 20.6% of the days across the 3 scenarios, annually, constituting 11.1% to 31.6% of all overdose deaths. The absolute difference in percentage points of days identified as spikes varied from 5.2 to 11.5 between 7- and 30-day lags and from 0 to 4.6 between 30- and 90-day lags across years. When compared with the adjusted moving average across the 3 scenarios, in 2017 an average of 3.9 to 5.5 additional deaths occurred on spike days, while in 2023 the range was 3.7 to 6.0.nnPRACTICE IMPLICATIONS: A substantial percentage of deaths occurred annually on spike days, highlighting the need for effectively monitoring short-term overdose trends. Moreover, our study serves as a foundational analysis for future research into exogenous events that may contribute to spikes in overdose deaths, aiming to prevent future deaths.},
keywords = {},
pubstate = {published},
tppubtype = {article}
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OBJECTIVES: Yearly rolling aggregate trends or rates are commonly used to analyze trends in overdose deaths, but focusing on long-term trends can obscure short-term fluctuations (eg, daily spikes). We analyzed data on spikes in daily fatal overdoses and how various spike detection thresholds influence the identification of spikes.nnMATERIALS AND METHODS: We used a spike detection algorithm to identify spikes among 16 660 drug-related overdose deaths (from any drug) reported in Massachusetts' vital statistics from 2017 through 2023. We adjusted the parameters of the algorithm to define spikes in 3 distinct scenarios: deaths exceeding 2 adjusted moving SDs above the 7-, 30-, and 90-day adjusted moving average.nnRESULTS: Our results confirmed the on-the-ground observation that there are days when many more people die of overdoses than would be expected based on fluctuations due to differences among people alone. We identified spikes on 5.8% to 20.6% of the days across the 3 scenarios, annually, constituting 11.1% to 31.6% of all overdose deaths. The absolute difference in percentage points of days identified as spikes varied from 5.2 to 11.5 between 7- and 30-day lags and from 0 to 4.6 between 30- and 90-day lags across years. When compared with the adjusted moving average across the 3 scenarios, in 2017 an average of 3.9 to 5.5 additional deaths occurred on spike days, while in 2023 the range was 3.7 to 6.0.nnPRACTICE IMPLICATIONS: A substantial percentage of deaths occurred annually on spike days, highlighting the need for effectively monitoring short-term overdose trends. Moreover, our study serves as a foundational analysis for future research into exogenous events that may contribute to spikes in overdose deaths, aiming to prevent future deaths.
Lim, Tse Yang; Dong, Huiru; Stringfellow, Erin; Hasgul, Zeynep; Park, Ju; Glos, Lukas; Kazemi, Reza; Jalali, Mohammad S.
Temporal and spatial trends of fentanyl co-occurrence in the illicit drug supply in the United States: a serial cross-sectional analysis Journal Article
In: The Lancet Regional Health - Americas, vol. 39, 2024, ISSN: 2667-193X.
@article{Lim2024,
title = {Temporal and spatial trends of fentanyl co-occurrence in the illicit drug supply in the United States: a serial cross-sectional analysis},
author = {Tse Yang Lim and Huiru Dong and Erin Stringfellow and Zeynep Hasgul and Ju Park and Lukas Glos and Reza Kazemi and Mohammad S. Jalali},
doi = {10.1016/j.lana.2024.100898},
issn = {2667-193X},
year = {2024},
date = {2024-11-00},
journal = {The Lancet Regional Health - Americas},
volume = {39},
publisher = {Elsevier BV},
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Hasgul, Zeynep; Spanjaart, Anne; Javed, Sumreen; Akhavan, Ali; Kersten, Marie José; Jalali, Mohammad S
Health-related quality of life dynamics: modeling insights from immunotherapy Journal Article
In: Qual Life Res, 2024, ISSN: 1573-2649.
@article{pmid39476201,
title = {Health-related quality of life dynamics: modeling insights from immunotherapy},
author = {Zeynep Hasgul and Anne Spanjaart and Sumreen Javed and Ali Akhavan and Marie Jos\'{e} Kersten and Mohammad S Jalali},
doi = {10.1007/s11136-024-03810-0},
issn = {1573-2649},
year = {2024},
date = {2024-10-01},
journal = {Qual Life Res},
abstract = {BACKGROUND: Understanding health-related quality of life (HRQoL) dynamics is essential for assessing and improving treatment experiences; however, clinical and observational studies struggle to capture their full complexity. We use simulation modeling and the case of Chimeric Antigen Receptor T-cell therapy-a type of cancer immunotherapy that can prolong survival, but carries life-threatening risks-to study HRQoL dynamics.nnMETHODS: We developed an exploratory system dynamics model with mathematical equations and parameter values informed by literature and expert insights. We refined its feedback structure and evaluated its dynamic behavior through iterative interviews. Model simulated HRQoL from treatment approval through six months post-infusion. Two strategies-reducing the delay to infusion and enhancing social support-were incorporated into the model. To dynamically evaluate the effect of these strategies, we developed four metrics: post-treatment HRQoL decline, recovery time to pre-treatment HRQoL, post-treatment HRQoL peak, and durability of the peak.nnRESULTS: Model captures key interactions within HRQoL, providing a nuanced analysis of its continuous temporal dynamics, particularly physical well-being, psychological well-being, tumor burden, receipt and efficacy of treatment, side effects, and their management. Model analysis shows reducing infusion delays enhanced HRQoL across all four metrics. While enhanced social support improved the first three metrics for patients who received treatment, it did not change durability of the peak.nnCONCLUSIONS: Simulation modeling can help explore the effects of strategies on HRQoL while also demonstrating the dynamic interactions between its key components, offering a powerful tool to investigate aspects of HRQoL that are difficult to assess in real-world settings.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Understanding health-related quality of life (HRQoL) dynamics is essential for assessing and improving treatment experiences; however, clinical and observational studies struggle to capture their full complexity. We use simulation modeling and the case of Chimeric Antigen Receptor T-cell therapy-a type of cancer immunotherapy that can prolong survival, but carries life-threatening risks-to study HRQoL dynamics.nnMETHODS: We developed an exploratory system dynamics model with mathematical equations and parameter values informed by literature and expert insights. We refined its feedback structure and evaluated its dynamic behavior through iterative interviews. Model simulated HRQoL from treatment approval through six months post-infusion. Two strategies-reducing the delay to infusion and enhancing social support-were incorporated into the model. To dynamically evaluate the effect of these strategies, we developed four metrics: post-treatment HRQoL decline, recovery time to pre-treatment HRQoL, post-treatment HRQoL peak, and durability of the peak.nnRESULTS: Model captures key interactions within HRQoL, providing a nuanced analysis of its continuous temporal dynamics, particularly physical well-being, psychological well-being, tumor burden, receipt and efficacy of treatment, side effects, and their management. Model analysis shows reducing infusion delays enhanced HRQoL across all four metrics. While enhanced social support improved the first three metrics for patients who received treatment, it did not change durability of the peak.nnCONCLUSIONS: Simulation modeling can help explore the effects of strategies on HRQoL while also demonstrating the dynamic interactions between its key components, offering a powerful tool to investigate aspects of HRQoL that are difficult to assess in real-world settings.
Wongseree, Peeradon; Hasgul, Zeynep; Jalali, Mohammad S
Cost-Effectiveness of Increasing Access to Colorectal Cancer Diagnosis: Analysis From Thailand Journal Article
In: Value Health Reg Issues, vol. 43, pp. 101010, 2024, ISSN: 2212-1102.
@article{pmid38848611,
title = {Cost-Effectiveness of Increasing Access to Colorectal Cancer Diagnosis: Analysis From Thailand},
author = {Peeradon Wongseree and Zeynep Hasgul and Mohammad S Jalali},
doi = {10.1016/j.vhri.2024.101010},
issn = {2212-1102},
year = {2024},
date = {2024-09-01},
urldate = {2024-06-01},
journal = {Value Health Reg Issues},
volume = {43},
pages = {101010},
abstract = {OBJECTIVES: The purpose of this study is to evaluate the cost-effectiveness of increasing access to colorectal cancer (CRC) diagnosis, considering resource limitations in Thailand.nnMETHODS: We analyzed the cost-effectiveness of increasing access to fecal immunochemical test screening (strategy I), symptom evaluation (strategy II), and their combination through healthcare and societal perspectives using Colo-Sim, a simulation model of CRC care. We extended our analysis by adding a risk-stratification score (RS) to the strategies. We analyzed all strategies under the currently limited annual colonoscopy capacity and sufficient capacity. We estimated quality-adjusted life-years (QALYs) and costs over 2023 to 2047 and performed sensitivity analyses.nnRESULTS: Annual costs for CRC care will increase over 25 years in Thailand, resulting in a cumulative cost of 323B Thai baht (THB). Each strategy results in higher QALYs gained and additional costs. With the current colonoscopy capacity and willingness-to-pay threshold of 160 000 THB, strategy I with and without RS is not cost-effective. Strategy II + RS is the most cost-effective, resulting in 0.68 million QALYs gained with additional costs of 66B THB. Under sufficient colonoscopy capacity, all strategies are deemed cost-effective, with the combined approach (strategy I + II + RS) being the most favorable, achieving the highest QALYs (1.55 million) at an additional cost of 131 billion THB. This strategy also maintains the highest probability of being cost-effective at any willingness-to-pay threshold above 96 000 THB.nnCONCLUSIONS: In Thailand, fecal immunochemical test screening, symptom evaluation, and RS use can achieve the highest QALYs; however, boosting colonoscopy capacity is essential for cost-effectiveness.},
keywords = {},
pubstate = {published},
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OBJECTIVES: The purpose of this study is to evaluate the cost-effectiveness of increasing access to colorectal cancer (CRC) diagnosis, considering resource limitations in Thailand.nnMETHODS: We analyzed the cost-effectiveness of increasing access to fecal immunochemical test screening (strategy I), symptom evaluation (strategy II), and their combination through healthcare and societal perspectives using Colo-Sim, a simulation model of CRC care. We extended our analysis by adding a risk-stratification score (RS) to the strategies. We analyzed all strategies under the currently limited annual colonoscopy capacity and sufficient capacity. We estimated quality-adjusted life-years (QALYs) and costs over 2023 to 2047 and performed sensitivity analyses.nnRESULTS: Annual costs for CRC care will increase over 25 years in Thailand, resulting in a cumulative cost of 323B Thai baht (THB). Each strategy results in higher QALYs gained and additional costs. With the current colonoscopy capacity and willingness-to-pay threshold of 160 000 THB, strategy I with and without RS is not cost-effective. Strategy II + RS is the most cost-effective, resulting in 0.68 million QALYs gained with additional costs of 66B THB. Under sufficient colonoscopy capacity, all strategies are deemed cost-effective, with the combined approach (strategy I + II + RS) being the most favorable, achieving the highest QALYs (1.55 million) at an additional cost of 131 billion THB. This strategy also maintains the highest probability of being cost-effective at any willingness-to-pay threshold above 96 000 THB.nnCONCLUSIONS: In Thailand, fecal immunochemical test screening, symptom evaluation, and RS use can achieve the highest QALYs; however, boosting colonoscopy capacity is essential for cost-effectiveness.
Dong, Huiru; Stringfellow, Erin J; Russell, Alton; Jalali, Mohammad S
State Mandates On Naloxone Coprescribing Associated With Short-Term Increase In Naloxone Codispensing Journal Article
In: Health Aff (Millwood), vol. 43, no. 9, pp. 1319–1328, 2024, ISSN: 2694-233X.
@article{pmid39226505,
title = {State Mandates On Naloxone Coprescribing Associated With Short-Term Increase In Naloxone Codispensing},
author = {Huiru Dong and Erin J Stringfellow and Alton Russell and Mohammad S Jalali},
doi = {10.1377/hlthaff.2023.01667},
issn = {2694-233X},
year = {2024},
date = {2024-09-01},
journal = {Health Aff (Millwood)},
volume = {43},
number = {9},
pages = {1319--1328},
abstract = {In the midst of the opioid crisis in the US, efforts to mitigate overdose risks have become paramount, leading some states to introduce mandates for coprescribing the life-saving overdose reversal drug naloxone. These mandates were designed to specifically address people receiving opioid analgesics who had an elevated risk for overdose. This included people receiving high opioid dosages, those concurrently using benzodiazepines, or those with a history of substance use disorder or overdose. Using a nationally representative, multipayer cohort of patients receiving prescription opioids, we investigated how naloxone codispensing rates changed at the state level from 2016 to 2021 among patients with an elevated risk for overdose. Then we used controlled interrupted time series analyses to assess mandates' longitudinal impact on naloxone codispensing in ten states that implemented mandates. We observed an immediate and significant increase in the naloxone codispensing rates in eight states after the implementation of mandates. Nevertheless, in five of these states, the codispensing rates exhibited a subsequent downward trend after the initial increase. State mandates show potential for improving naloxone codispensing; however, mandates alone might not be adequate for sustained change. Further research is needed to identify strategies complementing and enhancing the impact of mandates in combating the overdose crisis.},
keywords = {},
pubstate = {published},
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In the midst of the opioid crisis in the US, efforts to mitigate overdose risks have become paramount, leading some states to introduce mandates for coprescribing the life-saving overdose reversal drug naloxone. These mandates were designed to specifically address people receiving opioid analgesics who had an elevated risk for overdose. This included people receiving high opioid dosages, those concurrently using benzodiazepines, or those with a history of substance use disorder or overdose. Using a nationally representative, multipayer cohort of patients receiving prescription opioids, we investigated how naloxone codispensing rates changed at the state level from 2016 to 2021 among patients with an elevated risk for overdose. Then we used controlled interrupted time series analyses to assess mandates' longitudinal impact on naloxone codispensing in ten states that implemented mandates. We observed an immediate and significant increase in the naloxone codispensing rates in eight states after the implementation of mandates. Nevertheless, in five of these states, the codispensing rates exhibited a subsequent downward trend after the initial increase. State mandates show potential for improving naloxone codispensing; however, mandates alone might not be adequate for sustained change. Further research is needed to identify strategies complementing and enhancing the impact of mandates in combating the overdose crisis.
Lim, Tse Yang; Keyes, Katherine M; Caulkins, Jonathan P; Stringfellow, Erin J; Cerdá, Magdalena; Jalali, Mohammad S
Improving Estimates of the Prevalence of Opioid Use Disorder in the United States: Revising Keyes et al Journal Article
In: J Addict Med, vol. 18, no. 6, pp. 705-710, 2024, ISSN: 1935-3227.
@article{pmid39221814,
title = {Improving Estimates of the Prevalence of Opioid Use Disorder in the United States: Revising Keyes et al},
author = {Tse Yang Lim and Katherine M Keyes and Jonathan P Caulkins and Erin J Stringfellow and Magdalena Cerd\'{a} and Mohammad S Jalali},
doi = {10.1097/ADM.0000000000001375},
issn = {1935-3227},
year = {2024},
date = {2024-09-01},
urldate = {2024-09-01},
journal = {J Addict Med},
volume = {18},
number = {6},
pages = {705-710},
abstract = {OBJECTIVES: The United States faces an ongoing drug overdose crisis, but accurate information on the prevalence of opioid use disorder (OUD) remains limited. A recent analysis by Keyes et al used a multiplier approach with drug poisoning mortality data to estimate OUD prevalence. Although insightful, this approach made stringent and partly inconsistent assumptions in interpreting mortality data, particularly synthetic opioid (SO)-involved and non-opioid-involved mortality. We revise that approach and resulting estimates to resolve inconsistencies and examine several alternative assumptions.nnMETHODS: We examine 4 adjustments to Keyes and colleagues\' estimation approach: (A) revising how the equations account for SO effects on mortality, (B) incorporating fentanyl prevalence data to inform estimates of SO lethality, (C) using opioid-involved drug poisoning data to estimate a plausible range for OUD prevalence, and (D) adjusting mortality data to account for underreporting of opioid involvement.nnRESULTS: Revising the estimation equation and SO lethality effect (adj. A and B) while using Keyes and colleagues\' original assumption that people with OUD account for all fatal drug poisonings yields slightly higher estimates, with OUD population reaching 9.3 million in 2016 before declining to 7.6 million by 2019. Using only opioid-involved drug poisoning data (adj. C and D) provides a lower range, peaking at 6.4 million in 2014-2015 and declining to 3.8 million in 2019.nnCONCLUSIONS: The revised estimation equation presented is feasible and addresses limitations of the earlier method and hence should be used in future estimations. Alternative assumptions around drug poisoning data can also provide a plausible range of estimates for OUD population.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
OBJECTIVES: The United States faces an ongoing drug overdose crisis, but accurate information on the prevalence of opioid use disorder (OUD) remains limited. A recent analysis by Keyes et al used a multiplier approach with drug poisoning mortality data to estimate OUD prevalence. Although insightful, this approach made stringent and partly inconsistent assumptions in interpreting mortality data, particularly synthetic opioid (SO)-involved and non-opioid-involved mortality. We revise that approach and resulting estimates to resolve inconsistencies and examine several alternative assumptions.nnMETHODS: We examine 4 adjustments to Keyes and colleagues' estimation approach: (A) revising how the equations account for SO effects on mortality, (B) incorporating fentanyl prevalence data to inform estimates of SO lethality, (C) using opioid-involved drug poisoning data to estimate a plausible range for OUD prevalence, and (D) adjusting mortality data to account for underreporting of opioid involvement.nnRESULTS: Revising the estimation equation and SO lethality effect (adj. A and B) while using Keyes and colleagues' original assumption that people with OUD account for all fatal drug poisonings yields slightly higher estimates, with OUD population reaching 9.3 million in 2016 before declining to 7.6 million by 2019. Using only opioid-involved drug poisoning data (adj. C and D) provides a lower range, peaking at 6.4 million in 2014-2015 and declining to 3.8 million in 2019.nnCONCLUSIONS: The revised estimation equation presented is feasible and addresses limitations of the earlier method and hence should be used in future estimations. Alternative assumptions around drug poisoning data can also provide a plausible range of estimates for OUD population.
Dong, Huiru; Stringfellow, Erin J; Russell, W Alton; Bearnot, Benjamin; Jalali, Mohammad S
Impact of Alternative Ways to Operationalize Buprenorphine Treatment Duration on Understanding Continuity of Care for Opioid Use Disorder Journal Article
In: Int J Ment Health Addict, vol. 22, no. 4, pp. 2285–2290, 2024, ISSN: 1557-1874.
@article{pmid39629044,
title = {Impact of Alternative Ways to Operationalize Buprenorphine Treatment Duration on Understanding Continuity of Care for Opioid Use Disorder},
author = {Huiru Dong and Erin J Stringfellow and W Alton Russell and Benjamin Bearnot and Mohammad S Jalali},
doi = {10.1007/s11469-022-00985-w},
issn = {1557-1874},
year = {2024},
date = {2024-08-01},
journal = {Int J Ment Health Addict},
volume = {22},
number = {4},
pages = {2285--2290},
keywords = {},
pubstate = {published},
tppubtype = {article}
}