Dr. Mohammad Jalali (aka, ‘MJ’) is an Assistant 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
Garcia, Gian-Gabriel P; Stringfellow, Erin J; DiGennaro, Catherine; Poellinger, Nicole; Wood, Jaden; Wakeman, Sarah; Jalali, Mohammad S
Opioid overdose decedent characteristics during COVID-19 Journal Article
In: Ann Med, vol. 54, no. 1, pp. 1081–1088, 2022, ISSN: 1365-2060.
@article{pmid35467475,
title = {Opioid overdose decedent characteristics during COVID-19},
author = {Gian-Gabriel P Garcia and Erin J Stringfellow and Catherine DiGennaro and Nicole Poellinger and Jaden Wood and Sarah Wakeman and Mohammad S Jalali},
doi = {10.1080/07853890.2022.2067350},
issn = {1365-2060},
year = {2022},
date = {2022-12-01},
journal = {Ann Med},
volume = {54},
number = {1},
pages = {1081--1088},
abstract = {INTRODUCTION: Alongside the emergence of COVID-19 in the United States, several reports highlighted increasing rates of opioid overdose from preliminary data. Yet, little is known about how state-level opioid overdose death trends and decedent characteristics have evolved using official death records.
METHODS: We requested vital statistics data from 2018-2020 from all 50 states and the District of Columbia, receiving data from 14 states. Accounting for COVID-19, we excluded states without data past March 2020, leaving 11 states for analysis. We defined state-specific analysis periods from March 13 until the latest reliable date in each state's data, then conducted retrospective year-over-year analyses comparing opioid-related overdose death rates, the presence of specific opioids and other psychoactive substances, and decedents' sex, race, and age from 2020 to 2019 and 2019 to 2018 within each state's analysis period. We assessed whether significant changes in 2020 vs. 2019 in opioid overdose deaths were new or continuing trends using joinpoint regression.
RESULTS: We found significant increases in opioid-related overdose death rates in Alaska (55.3%), Colorado (80.2%), Indiana (40.1%), Nevada (50.0%), North Carolina (30.5%), Rhode Island (29.6%), and Virginia (66.4%) - all continuing previous trends. Increases in synthetic opioid-involved overdose deaths were new in Alaska (136.5%), Indiana (27.6%), and Virginia (16.5%), whilst continuing in Colorado (44.4%), Connecticut (3.6%), Nevada (75.0%), and North Carolina (14.6%). We found new increases in male decedents in Indiana (12.0%), and continuing increases in Colorado (15.2%). We also found continuing increases in Black non-Hispanic decedents in Massachusetts (43.9%) and Virginia (33.7%).
CONCLUSION: This research analyzes vital statistics data from 11 states, highlighting new trends in opioid overdose deaths and decedent characteristics across 10 of these states. These findings can inform state-specific public health interventions and highlight the need for timely and comprehensive fatal opioid overdose data, especially amidst concurrent crises such as COVID-19. Key messages:Our results highlight shifts in opioid overdose trends during the COVID-19 pandemic that cannot otherwise be extracted from aggregated or provisional opioid overdose death data such as those published by the Centres for Disease Control and Prevention.Fentanyl and other synthetic opioids continue to drive increases in fatal overdoses, making it difficult to separate these trends from any possible COVID-19-related factors.Black non-Hispanic people are making up an increasing proportion of opioid overdose deaths in some states.State-specific limitations and variations in data-reporting for vital statistics make it challenging to acquire and analyse up-to-date data on opioid-related overdose deaths. More timely and comprehensive data are needed to generate broader insights on the nature of the intersecting opioid and COVID-19 crises.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
INTRODUCTION: Alongside the emergence of COVID-19 in the United States, several reports highlighted increasing rates of opioid overdose from preliminary data. Yet, little is known about how state-level opioid overdose death trends and decedent characteristics have evolved using official death records.
METHODS: We requested vital statistics data from 2018-2020 from all 50 states and the District of Columbia, receiving data from 14 states. Accounting for COVID-19, we excluded states without data past March 2020, leaving 11 states for analysis. We defined state-specific analysis periods from March 13 until the latest reliable date in each state's data, then conducted retrospective year-over-year analyses comparing opioid-related overdose death rates, the presence of specific opioids and other psychoactive substances, and decedents' sex, race, and age from 2020 to 2019 and 2019 to 2018 within each state's analysis period. We assessed whether significant changes in 2020 vs. 2019 in opioid overdose deaths were new or continuing trends using joinpoint regression.
RESULTS: We found significant increases in opioid-related overdose death rates in Alaska (55.3%), Colorado (80.2%), Indiana (40.1%), Nevada (50.0%), North Carolina (30.5%), Rhode Island (29.6%), and Virginia (66.4%) - all continuing previous trends. Increases in synthetic opioid-involved overdose deaths were new in Alaska (136.5%), Indiana (27.6%), and Virginia (16.5%), whilst continuing in Colorado (44.4%), Connecticut (3.6%), Nevada (75.0%), and North Carolina (14.6%). We found new increases in male decedents in Indiana (12.0%), and continuing increases in Colorado (15.2%). We also found continuing increases in Black non-Hispanic decedents in Massachusetts (43.9%) and Virginia (33.7%).
CONCLUSION: This research analyzes vital statistics data from 11 states, highlighting new trends in opioid overdose deaths and decedent characteristics across 10 of these states. These findings can inform state-specific public health interventions and highlight the need for timely and comprehensive fatal opioid overdose data, especially amidst concurrent crises such as COVID-19. Key messages:Our results highlight shifts in opioid overdose trends during the COVID-19 pandemic that cannot otherwise be extracted from aggregated or provisional opioid overdose death data such as those published by the Centres for Disease Control and Prevention.Fentanyl and other synthetic opioids continue to drive increases in fatal overdoses, making it difficult to separate these trends from any possible COVID-19-related factors.Black non-Hispanic people are making up an increasing proportion of opioid overdose deaths in some states.State-specific limitations and variations in data-reporting for vital statistics make it challenging to acquire and analyse up-to-date data on opioid-related overdose deaths. More timely and comprehensive data are needed to generate broader insights on the nature of the intersecting opioid and COVID-19 crises.
METHODS: We requested vital statistics data from 2018-2020 from all 50 states and the District of Columbia, receiving data from 14 states. Accounting for COVID-19, we excluded states without data past March 2020, leaving 11 states for analysis. We defined state-specific analysis periods from March 13 until the latest reliable date in each state's data, then conducted retrospective year-over-year analyses comparing opioid-related overdose death rates, the presence of specific opioids and other psychoactive substances, and decedents' sex, race, and age from 2020 to 2019 and 2019 to 2018 within each state's analysis period. We assessed whether significant changes in 2020 vs. 2019 in opioid overdose deaths were new or continuing trends using joinpoint regression.
RESULTS: We found significant increases in opioid-related overdose death rates in Alaska (55.3%), Colorado (80.2%), Indiana (40.1%), Nevada (50.0%), North Carolina (30.5%), Rhode Island (29.6%), and Virginia (66.4%) - all continuing previous trends. Increases in synthetic opioid-involved overdose deaths were new in Alaska (136.5%), Indiana (27.6%), and Virginia (16.5%), whilst continuing in Colorado (44.4%), Connecticut (3.6%), Nevada (75.0%), and North Carolina (14.6%). We found new increases in male decedents in Indiana (12.0%), and continuing increases in Colorado (15.2%). We also found continuing increases in Black non-Hispanic decedents in Massachusetts (43.9%) and Virginia (33.7%).
CONCLUSION: This research analyzes vital statistics data from 11 states, highlighting new trends in opioid overdose deaths and decedent characteristics across 10 of these states. These findings can inform state-specific public health interventions and highlight the need for timely and comprehensive fatal opioid overdose data, especially amidst concurrent crises such as COVID-19. Key messages:Our results highlight shifts in opioid overdose trends during the COVID-19 pandemic that cannot otherwise be extracted from aggregated or provisional opioid overdose death data such as those published by the Centres for Disease Control and Prevention.Fentanyl and other synthetic opioids continue to drive increases in fatal overdoses, making it difficult to separate these trends from any possible COVID-19-related factors.Black non-Hispanic people are making up an increasing proportion of opioid overdose deaths in some states.State-specific limitations and variations in data-reporting for vital statistics make it challenging to acquire and analyse up-to-date data on opioid-related overdose deaths. More timely and comprehensive data are needed to generate broader insights on the nature of the intersecting opioid and COVID-19 crises.
Dong, Huiru; Stringfellow, Erin J; Russell, W Alton; Jalali, Mohammad S
Racial and Ethnic Disparities in Buprenorphine Treatment Duration in the US Journal Article
In: JAMA Psychiatry, 2022, ISSN: 2168-6238.
@article{pmid36350592,
title = {Racial and Ethnic Disparities in Buprenorphine Treatment Duration in the US},
author = {Huiru Dong and Erin J Stringfellow and W Alton Russell and Mohammad S Jalali},
doi = {10.1001/jamapsychiatry.2022.3673},
issn = {2168-6238},
year = {2022},
date = {2022-11-01},
journal = {JAMA Psychiatry},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Weiner, Scott G; Carroll, Aleta D; Brisbon, Nicholas M; Rodriguez, Claudia P; Covahey, Charles; Stringfellow, Erin J; DiGennaro, Catherine; Jalali, Mohammad S; Wakeman, Sarah E
Evaluating disparities in prescribing of naloxone after emergency department treatment of opioid overdose Journal Article
In: J Subst Abuse Treat, vol. 139, pp. 108785, 2022, ISSN: 1873-6483.
@article{pmid35537918,
title = {Evaluating disparities in prescribing of naloxone after emergency department treatment of opioid overdose},
author = {Scott G Weiner and Aleta D Carroll and Nicholas M Brisbon and Claudia P Rodriguez and Charles Covahey and Erin J Stringfellow and Catherine DiGennaro and Mohammad S Jalali and Sarah E Wakeman},
doi = {10.1016/j.jsat.2022.108785},
issn = {1873-6483},
year = {2022},
date = {2022-08-01},
urldate = {2022-04-01},
journal = {J Subst Abuse Treat},
volume = {139},
pages = {108785},
abstract = {INTRODUCTION: Patients who initially survive opioid-related overdose are at high risk for subsequent mortality. Our health system aimed to evaluate the presence of disparities in prescribing naloxone following opioid overdose.
METHODS: This was a retrospective cohort study of patients seen in our health system, which comprises two academic centers and eight community hospitals. Eligible patients had at least one visit to any of our hospital's emergency departments (EDs) with a diagnosis code indicating opioid-related overdose between May 1, 2018, and April 30, 2021. The primary outcome measure was prescription of nasal naloxone after at least one visit for opioid-related overdose during the study period.
RESULTS: The health system had 1348 unique patients who presented 1593 times to at least one of the EDs with opioid overdose. Of included patients, 580 (43.2%) received one or more prescriptions for naloxone. The majority (68.9%, n = 925) were male. For race/ethnicity, 74.5% (1000) were Non-Hispanic White, 8.0% (n = 108) were Non-Hispanic Black, and 13.0% (n = 175) were Hispanic/Latinx. Compared with the reference age group of 16-24 years, only those 65+ were less likely to receive naloxone (adjusted odds ratio [aOR] 0.41, 95% confidence interval [CI] 0.20-0.84). The study found no difference for gender (male aOR 1.23, 95% CI 0.97-1.57 compared to female). Hispanic/Latinx patients were more likely to receive a prescription when compared to Non-Hispanic White patients (aOR 1.72, 95% CI 1.22-2.44), while no difference occurred between Non-Hispanic Black compared to Non-Hispanic White patients (aOR 1.31, 95% CI 0.87-1.98).
CONCLUSIONS: Naloxone prescribing after overdose in our system was suboptimal, with fewer than half of patients with an overdose diagnosis code receiving this lifesaving and evidence-based intervention. Patients who were Hispanic/Latinx were more likely to receive naloxone than other race and ethnicity groups, and patients who were older were less likely to receive it. Health systems need ongoing equity-informed implementation of programs to expand access to naloxone to all patients at risk.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
INTRODUCTION: Patients who initially survive opioid-related overdose are at high risk for subsequent mortality. Our health system aimed to evaluate the presence of disparities in prescribing naloxone following opioid overdose.
METHODS: This was a retrospective cohort study of patients seen in our health system, which comprises two academic centers and eight community hospitals. Eligible patients had at least one visit to any of our hospital's emergency departments (EDs) with a diagnosis code indicating opioid-related overdose between May 1, 2018, and April 30, 2021. The primary outcome measure was prescription of nasal naloxone after at least one visit for opioid-related overdose during the study period.
RESULTS: The health system had 1348 unique patients who presented 1593 times to at least one of the EDs with opioid overdose. Of included patients, 580 (43.2%) received one or more prescriptions for naloxone. The majority (68.9%, n = 925) were male. For race/ethnicity, 74.5% (1000) were Non-Hispanic White, 8.0% (n = 108) were Non-Hispanic Black, and 13.0% (n = 175) were Hispanic/Latinx. Compared with the reference age group of 16-24 years, only those 65+ were less likely to receive naloxone (adjusted odds ratio [aOR] 0.41, 95% confidence interval [CI] 0.20-0.84). The study found no difference for gender (male aOR 1.23, 95% CI 0.97-1.57 compared to female). Hispanic/Latinx patients were more likely to receive a prescription when compared to Non-Hispanic White patients (aOR 1.72, 95% CI 1.22-2.44), while no difference occurred between Non-Hispanic Black compared to Non-Hispanic White patients (aOR 1.31, 95% CI 0.87-1.98).
CONCLUSIONS: Naloxone prescribing after overdose in our system was suboptimal, with fewer than half of patients with an overdose diagnosis code receiving this lifesaving and evidence-based intervention. Patients who were Hispanic/Latinx were more likely to receive naloxone than other race and ethnicity groups, and patients who were older were less likely to receive it. Health systems need ongoing equity-informed implementation of programs to expand access to naloxone to all patients at risk.
METHODS: This was a retrospective cohort study of patients seen in our health system, which comprises two academic centers and eight community hospitals. Eligible patients had at least one visit to any of our hospital's emergency departments (EDs) with a diagnosis code indicating opioid-related overdose between May 1, 2018, and April 30, 2021. The primary outcome measure was prescription of nasal naloxone after at least one visit for opioid-related overdose during the study period.
RESULTS: The health system had 1348 unique patients who presented 1593 times to at least one of the EDs with opioid overdose. Of included patients, 580 (43.2%) received one or more prescriptions for naloxone. The majority (68.9%, n = 925) were male. For race/ethnicity, 74.5% (1000) were Non-Hispanic White, 8.0% (n = 108) were Non-Hispanic Black, and 13.0% (n = 175) were Hispanic/Latinx. Compared with the reference age group of 16-24 years, only those 65+ were less likely to receive naloxone (adjusted odds ratio [aOR] 0.41, 95% confidence interval [CI] 0.20-0.84). The study found no difference for gender (male aOR 1.23, 95% CI 0.97-1.57 compared to female). Hispanic/Latinx patients were more likely to receive a prescription when compared to Non-Hispanic White patients (aOR 1.72, 95% CI 1.22-2.44), while no difference occurred between Non-Hispanic Black compared to Non-Hispanic White patients (aOR 1.31, 95% CI 0.87-1.98).
CONCLUSIONS: Naloxone prescribing after overdose in our system was suboptimal, with fewer than half of patients with an overdose diagnosis code receiving this lifesaving and evidence-based intervention. Patients who were Hispanic/Latinx were more likely to receive naloxone than other race and ethnicity groups, and patients who were older were less likely to receive it. Health systems need ongoing equity-informed implementation of programs to expand access to naloxone to all patients at risk.
Beaulieu, Elizabeth; Naumann, Rebecca B; Deveaux, Genevieve; Wang, Lindsay; Stringfellow, Erin J; Lich, Kristen Hassmiller; Jalali, Mohammad S
Impacts of alcohol and opioid polysubstance use on road safety: Systematic review Journal Article
In: Accid Anal Prev, vol. 173, pp. 106713, 2022, ISSN: 1879-2057.
@article{pmid35640366,
title = {Impacts of alcohol and opioid polysubstance use on road safety: Systematic review},
author = {Elizabeth Beaulieu and Rebecca B Naumann and Genevieve Deveaux and Lindsay Wang and Erin J Stringfellow and Kristen Hassmiller Lich and Mohammad S Jalali},
doi = {10.1016/j.aap.2022.106713},
issn = {1879-2057},
year = {2022},
date = {2022-08-01},
urldate = {2022-05-01},
journal = {Accid Anal Prev},
volume = {173},
pages = {106713},
abstract = {Connections between substance use, impairment, and road safety have been frequently researched. Yet, little is known about how simultaneous use of opioids and alcohol affects road safety outcomes, which is an increasingly critical link within the current landscape of the substance use environment and public health. Lack of this understanding is partly due to testing complications and data limitations. We define polysubstance use here as alcohol and opioids consumed together or within a small-time window such that both are present in the system. This polysubstance use is on the rise and produces greater health risks than when the substances are consumed separately. Given the increasing rate of opioid use, high prevalence of alcohol use, and dangers of polysubstance use, we aim to synthesize literature on the prevalence and impact of this polysubstance on road safety-related outcomes. We performed a systematic review of studies published between 1974 and 2020 that examined opioid and alcohol use exposures and road safety-related outcomes. Out of 644 initial findings, 20 studies were included in this review. Outcomes included motor vehicle crash injuries, deaths, or driver culpability; suspected driving under the influence; and simulated driving performance. Evidence from multiple sources showed a significant rise, approximately 1% to 7%, in the prevalence of opioids among fatally injured drivers in the U.S. from 1995 to 2016. Information published on the simultaneous presence of opioids and alcohol in people involved in crashes was scarce. The limited available findings point toward an overlap where up to 30% of opioid-positive people involved in a crash were also positive for alcohol. Studies also suggest a possibly elevated risk presented by this polysubstance use relative to the substances used alone, though the majority of identified studies did not estimate this association. The synthesized research indicates that alcohol and opioid use is not uncommon and may be increasing among people involved in adverse driving events. More research and better data are needed to improve estimates of association with road traffic-related outcomes, potentially improving substance testing in current surveillance systems or using linked data sets and other novel data sources to improve estimates.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Connections between substance use, impairment, and road safety have been frequently researched. Yet, little is known about how simultaneous use of opioids and alcohol affects road safety outcomes, which is an increasingly critical link within the current landscape of the substance use environment and public health. Lack of this understanding is partly due to testing complications and data limitations. We define polysubstance use here as alcohol and opioids consumed together or within a small-time window such that both are present in the system. This polysubstance use is on the rise and produces greater health risks than when the substances are consumed separately. Given the increasing rate of opioid use, high prevalence of alcohol use, and dangers of polysubstance use, we aim to synthesize literature on the prevalence and impact of this polysubstance on road safety-related outcomes. We performed a systematic review of studies published between 1974 and 2020 that examined opioid and alcohol use exposures and road safety-related outcomes. Out of 644 initial findings, 20 studies were included in this review. Outcomes included motor vehicle crash injuries, deaths, or driver culpability; suspected driving under the influence; and simulated driving performance. Evidence from multiple sources showed a significant rise, approximately 1% to 7%, in the prevalence of opioids among fatally injured drivers in the U.S. from 1995 to 2016. Information published on the simultaneous presence of opioids and alcohol in people involved in crashes was scarce. The limited available findings point toward an overlap where up to 30% of opioid-positive people involved in a crash were also positive for alcohol. Studies also suggest a possibly elevated risk presented by this polysubstance use relative to the substances used alone, though the majority of identified studies did not estimate this association. The synthesized research indicates that alcohol and opioid use is not uncommon and may be increasing among people involved in adverse driving events. More research and better data are needed to improve estimates of association with road traffic-related outcomes, potentially improving substance testing in current surveillance systems or using linked data sets and other novel data sources to improve estimates.
Beaulieu, Elizabeth; Spanjaart, Anne; Roes, Ashley; Rachet, Bernard; Dalle, Stéphane; Kersten, Marie José; Maucort-Boulch, Delphine; Jalali, Mohammad S
Health-related quality of life in cancer immunotherapy: a systematic perspective, using causal loop diagrams Journal Article
In: Qual Life Res, vol. 31, iss. 8, pp. 2357-2366, 2022, ISSN: 1573-2649.
@article{pmid35298735,
title = {Health-related quality of life in cancer immunotherapy: a systematic perspective, using causal loop diagrams},
author = {Elizabeth Beaulieu and Anne Spanjaart and Ashley Roes and Bernard Rachet and St\'{e}phane Dalle and Marie Jos\'{e} Kersten and Delphine Maucort-Boulch and Mohammad S Jalali},
doi = {10.1007/s11136-022-03110-5},
issn = {1573-2649},
year = {2022},
date = {2022-08-01},
urldate = {2022-03-01},
journal = {Qual Life Res},
volume = {31},
issue = {8},
pages = {2357-2366},
abstract = {PURPOSE: System science offers a unique set of tools, including causal loop diagrams (CLDs), for stakeholders to better grasp the complexity of factors surrounding quality of life. Because the health-related quality of life (HRQoL) of cancer immunotherapy patients exists within an intricate system affected by and affecting many factors across multiple dimensions, the development of a systems-level model can provide a powerful framework to aid the understanding of this complexity. We developed a CLD for HRQoL of cancer immunotherapy patients.
METHODS: We first applied a literature-based approach to construct a CLD for patients following immunotherapy. We then iteratively reviewed and enhanced the CLD through interviews with subject matter experts.
RESULTS: Based on the reviewed literature and subject matter expert input, we produced a CLD representing the system surrounding cancer immunotherapy patients' HRQoL. Several feedback loops are identified that span clinical experiences, oncology teams' perceptions about immunotherapy, social support structures, and further research and development in cancer immunotherapy, in addition to other components. The CLD enables visualization of thought experiments regarding how a change anywhere in the system can ultimately worsen or improve patients' HRQoL.
CONCLUSION: The CLD illustrates the valuable contribution of a systems perspective to quality-of-life research. This systems-based qualitative representation gives insight on strategies to inhibit harmful effects, enhance beneficial effects, and inherent tradeoffs within the system. The CLD identifies gaps in the literature and offers a communication tool for diverse stakeholders. Our research method provides an example for studying the complexities of quality of life in other health domains.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
PURPOSE: System science offers a unique set of tools, including causal loop diagrams (CLDs), for stakeholders to better grasp the complexity of factors surrounding quality of life. Because the health-related quality of life (HRQoL) of cancer immunotherapy patients exists within an intricate system affected by and affecting many factors across multiple dimensions, the development of a systems-level model can provide a powerful framework to aid the understanding of this complexity. We developed a CLD for HRQoL of cancer immunotherapy patients.
METHODS: We first applied a literature-based approach to construct a CLD for patients following immunotherapy. We then iteratively reviewed and enhanced the CLD through interviews with subject matter experts.
RESULTS: Based on the reviewed literature and subject matter expert input, we produced a CLD representing the system surrounding cancer immunotherapy patients' HRQoL. Several feedback loops are identified that span clinical experiences, oncology teams' perceptions about immunotherapy, social support structures, and further research and development in cancer immunotherapy, in addition to other components. The CLD enables visualization of thought experiments regarding how a change anywhere in the system can ultimately worsen or improve patients' HRQoL.
CONCLUSION: The CLD illustrates the valuable contribution of a systems perspective to quality-of-life research. This systems-based qualitative representation gives insight on strategies to inhibit harmful effects, enhance beneficial effects, and inherent tradeoffs within the system. The CLD identifies gaps in the literature and offers a communication tool for diverse stakeholders. Our research method provides an example for studying the complexities of quality of life in other health domains.
METHODS: We first applied a literature-based approach to construct a CLD for patients following immunotherapy. We then iteratively reviewed and enhanced the CLD through interviews with subject matter experts.
RESULTS: Based on the reviewed literature and subject matter expert input, we produced a CLD representing the system surrounding cancer immunotherapy patients' HRQoL. Several feedback loops are identified that span clinical experiences, oncology teams' perceptions about immunotherapy, social support structures, and further research and development in cancer immunotherapy, in addition to other components. The CLD enables visualization of thought experiments regarding how a change anywhere in the system can ultimately worsen or improve patients' HRQoL.
CONCLUSION: The CLD illustrates the valuable contribution of a systems perspective to quality-of-life research. This systems-based qualitative representation gives insight on strategies to inhibit harmful effects, enhance beneficial effects, and inherent tradeoffs within the system. The CLD identifies gaps in the literature and offers a communication tool for diverse stakeholders. Our research method provides an example for studying the complexities of quality of life in other health domains.
Stafford, Celia; Marrero, Wesley J; Naumann, Rebecca B; Lich, Kristen Hassmiller; Wakeman, Sarah; Jalali, Mohammad S
Identifying key risk factors for premature discontinuation of opioid use disorder treatment in the United States: A predictive modeling study Journal Article
In: Drug Alcohol Depend, vol. 237, pp. 109507, 2022, ISSN: 1879-0046.
@article{pmid35660221,
title = {Identifying key risk factors for premature discontinuation of opioid use disorder treatment in the United States: A predictive modeling study},
author = {Celia Stafford and Wesley J Marrero and Rebecca B Naumann and Kristen Hassmiller Lich and Sarah Wakeman and Mohammad S Jalali},
doi = {10.1016/j.drugalcdep.2022.109507},
issn = {1879-0046},
year = {2022},
date = {2022-08-01},
urldate = {2022-05-01},
journal = {Drug Alcohol Depend},
volume = {237},
pages = {109507},
abstract = {BACKGROUND: Treatment for opioid use disorder (OUD), particularly medication for OUD, is highly effective; however, retention in OUD treatment is a significant challenge. We aimed to identify key risk factors for premature exit from OUD treatment.
METHODS: We analyzed 2,381,902 cross-sectional treatment episodes for individuals in the U.S., discharged between Jan/1/2015 and Dec/31/2019. We developed classification models (Random Forest, Classification and Regression Trees (CART), Bagged CART, and Boosted CART), and analyzed 31 potential risk factors for premature treatment exit, including treatment characteristics, substance use history, socioeconomic status, and demographic characteristics. We stratified our analysis based on length of stay in treatment and service setting. Models were compared using cross-validation and the receiver operating characteristic area under the curve (ROC-AUC).
RESULTS: Random Forest outperformed other methods (ROC-AUC: 74%). The most influential risk factors included characteristics of service setting, geographic region, primary source of payment, and referral source. Race, ethnicity, and sex had far weaker predictive impacts. When stratified by treatment setting and length of stay, employment status and delay (days waited) to enter treatment were among the most influential factors. Their importance increased as treatment duration decreased. Notably, importance of referral source increased as the treatment duration increased. Finally, age and age of first use were important factors for lengths of stay of 2-7 days and in detox treatment settings.
CONCLUSIONS: The key factors of OUD treatment attrition identified in this analysis should be more closely explored (e.g., in causal studies) to inform targeted policies and interventions to improve models of care.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Treatment for opioid use disorder (OUD), particularly medication for OUD, is highly effective; however, retention in OUD treatment is a significant challenge. We aimed to identify key risk factors for premature exit from OUD treatment.
METHODS: We analyzed 2,381,902 cross-sectional treatment episodes for individuals in the U.S., discharged between Jan/1/2015 and Dec/31/2019. We developed classification models (Random Forest, Classification and Regression Trees (CART), Bagged CART, and Boosted CART), and analyzed 31 potential risk factors for premature treatment exit, including treatment characteristics, substance use history, socioeconomic status, and demographic characteristics. We stratified our analysis based on length of stay in treatment and service setting. Models were compared using cross-validation and the receiver operating characteristic area under the curve (ROC-AUC).
RESULTS: Random Forest outperformed other methods (ROC-AUC: 74%). The most influential risk factors included characteristics of service setting, geographic region, primary source of payment, and referral source. Race, ethnicity, and sex had far weaker predictive impacts. When stratified by treatment setting and length of stay, employment status and delay (days waited) to enter treatment were among the most influential factors. Their importance increased as treatment duration decreased. Notably, importance of referral source increased as the treatment duration increased. Finally, age and age of first use were important factors for lengths of stay of 2-7 days and in detox treatment settings.
CONCLUSIONS: The key factors of OUD treatment attrition identified in this analysis should be more closely explored (e.g., in causal studies) to inform targeted policies and interventions to improve models of care.
METHODS: We analyzed 2,381,902 cross-sectional treatment episodes for individuals in the U.S., discharged between Jan/1/2015 and Dec/31/2019. We developed classification models (Random Forest, Classification and Regression Trees (CART), Bagged CART, and Boosted CART), and analyzed 31 potential risk factors for premature treatment exit, including treatment characteristics, substance use history, socioeconomic status, and demographic characteristics. We stratified our analysis based on length of stay in treatment and service setting. Models were compared using cross-validation and the receiver operating characteristic area under the curve (ROC-AUC).
RESULTS: Random Forest outperformed other methods (ROC-AUC: 74%). The most influential risk factors included characteristics of service setting, geographic region, primary source of payment, and referral source. Race, ethnicity, and sex had far weaker predictive impacts. When stratified by treatment setting and length of stay, employment status and delay (days waited) to enter treatment were among the most influential factors. Their importance increased as treatment duration decreased. Notably, importance of referral source increased as the treatment duration increased. Finally, age and age of first use were important factors for lengths of stay of 2-7 days and in detox treatment settings.
CONCLUSIONS: The key factors of OUD treatment attrition identified in this analysis should be more closely explored (e.g., in causal studies) to inform targeted policies and interventions to improve models of care.
Deutsch, Arielle R; Jalali, Mohammad S; Stout, Sarah; Frerichs, Leah
Equitable Policies Need Equitable Practices: Alcohol- and Substance-Exposed Pregnancy as a Case Study Journal Article
In: Health Promot Pract, pp. 15248399221107605, 2022, ISSN: 1524-8399.
@article{pmid35778898,
title = {Equitable Policies Need Equitable Practices: Alcohol- and Substance-Exposed Pregnancy as a Case Study},
author = {Arielle R Deutsch and Mohammad S Jalali and Sarah Stout and Leah Frerichs},
doi = {10.1177/15248399221107605},
issn = {1524-8399},
year = {2022},
date = {2022-07-01},
journal = {Health Promot Pract},
pages = {15248399221107605},
abstract = {There is clear need for more effective public health policies. Coupled with calls for more effective policies, increasing demand to address public health disparities experienced by systemically marginalized and historically oppressed groups emphasizes the long-standing need for policies that improve public health equity. Such need is highlighted when examining public health issues such as alcohol- and substance-exposed pregnancy (ASEP): Current policies are ineffective at reducing ASEP, and marginalized groups experience disproportionately lower benefits and higher negative consequences as a result of such policies. Powerful strategies to develop more effective policies that can account for the complexity of such issues, such as systems science methods (SSMs), are becoming popular. However, current best practices for such methods often do not emphasize the additional efforts that will be required to develop equitable, not just effective policies. Using ASEP as an example of a crucial complex issue requiring new policy, we suggest additional steps to include in SSM projects for developing more effective policies that will also help stakeholders determine high-equity policies to reduce health disparities. These steps include modeling structural differences experienced by marginalized groups via systemic racism and oppression, incorporating existing cultural and community sources of strength and resilience as key areas for policy development, and evaluating the sustainability of policies as a dimension of efficacy. We also discuss using community-based participatory approaches as a framework for all SSM processes to ensure that policy development itself is grounded in equitable shared decision-making for marginalized individuals.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
There is clear need for more effective public health policies. Coupled with calls for more effective policies, increasing demand to address public health disparities experienced by systemically marginalized and historically oppressed groups emphasizes the long-standing need for policies that improve public health equity. Such need is highlighted when examining public health issues such as alcohol- and substance-exposed pregnancy (ASEP): Current policies are ineffective at reducing ASEP, and marginalized groups experience disproportionately lower benefits and higher negative consequences as a result of such policies. Powerful strategies to develop more effective policies that can account for the complexity of such issues, such as systems science methods (SSMs), are becoming popular. However, current best practices for such methods often do not emphasize the additional efforts that will be required to develop equitable, not just effective policies. Using ASEP as an example of a crucial complex issue requiring new policy, we suggest additional steps to include in SSM projects for developing more effective policies that will also help stakeholders determine high-equity policies to reduce health disparities. These steps include modeling structural differences experienced by marginalized groups via systemic racism and oppression, incorporating existing cultural and community sources of strength and resilience as key areas for policy development, and evaluating the sustainability of policies as a dimension of efficacy. We also discuss using community-based participatory approaches as a framework for all SSM processes to ensure that policy development itself is grounded in equitable shared decision-making for marginalized individuals.
Lim, Tse Yang; Stringfellow, Erin J; Stafford, Celia A; DiGennaro, Catherine; Homer, Jack B; Wakeland, Wayne; Eggers, Sara L; Kazemi, Reza; Glos, Lukas; Ewing, Emily G; Bannister, Calvin B; Humphreys, Keith; Throckmorton, Douglas C; Jalali, Mohammad S
Modeling the evolution of the US opioid crisis for national policy development Journal Article
In: Proc Natl Acad Sci U S A, vol. 119, no. 23, pp. e2115714119, 2022, ISSN: 1091-6490.
@article{pmid35639699,
title = {Modeling the evolution of the US opioid crisis for national policy development},
author = {Tse Yang Lim and Erin J Stringfellow and Celia A Stafford and Catherine DiGennaro and Jack B Homer and Wayne Wakeland and Sara L Eggers and Reza Kazemi and Lukas Glos and Emily G Ewing and Calvin B Bannister and Keith Humphreys and Douglas C Throckmorton and Mohammad S Jalali},
doi = {10.1073/pnas.2115714119},
issn = {1091-6490},
year = {2022},
date = {2022-06-01},
urldate = {2022-06-01},
journal = {Proc Natl Acad Sci U S A},
volume = {119},
number = {23},
pages = {e2115714119},
abstract = {Significance: The opioid crisis remains one of the greatest public health challenges in the United States. The crisis is complex, with long delays and feedbacks between policy actions and their effects, which creates a risk of unintended consequences and complicates policy decision-making. We present SOURCE (Simulation of Opioid Use, Response, Consequences, and Effects), an operationally detailed national-level model of the opioid crisis, intended to enhance understanding of the crisis and guide policy decisions. Drawing on multiple data sources, SOURCE replicates how risks of opioid misuse initiation and overdose have evolved over time in response to behavioral and other changes and suggests how those risks may evolve in the future, providing a basis for projecting and analyzing potential policy impacts and solutions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Significance: The opioid crisis remains one of the greatest public health challenges in the United States. The crisis is complex, with long delays and feedbacks between policy actions and their effects, which creates a risk of unintended consequences and complicates policy decision-making. We present SOURCE (Simulation of Opioid Use, Response, Consequences, and Effects), an operationally detailed national-level model of the opioid crisis, intended to enhance understanding of the crisis and guide policy decisions. Drawing on multiple data sources, SOURCE replicates how risks of opioid misuse initiation and overdose have evolved over time in response to behavioral and other changes and suggests how those risks may evolve in the future, providing a basis for projecting and analyzing potential policy impacts and solutions.
Stringfellow, Erin J; Lim, Tse Yang; Humphreys, Keith; DiGennaro, Catherine; Stafford, Celia; Beaulieu, Elizabeth; Homer, Jack; Wakeland, Wayne; Bearnot, Benjamin; McHugh, R Kathryn; Kelly, John; Glos, Lukas; Eggers, Sara L; Kazemi, Reza; Jalali, Mohammad S
Reducing opioid use disorder and overdose deaths in the United States: A dynamic modeling analysis Journal Article
In: Sci Adv, vol. 8, no. 25, pp. eabm8147, 2022, ISSN: 2375-2548.
@article{pmid35749492,
title = {Reducing opioid use disorder and overdose deaths in the United States: A dynamic modeling analysis},
author = {Erin J Stringfellow and Tse Yang Lim and Keith Humphreys and Catherine DiGennaro and Celia Stafford and Elizabeth Beaulieu and Jack Homer and Wayne Wakeland and Benjamin Bearnot and R Kathryn McHugh and John Kelly and Lukas Glos and Sara L Eggers and Reza Kazemi and Mohammad S Jalali},
doi = {10.1126/sciadv.abm8147},
issn = {2375-2548},
year = {2022},
date = {2022-06-01},
journal = {Sci Adv},
volume = {8},
number = {25},
pages = {eabm8147},
abstract = {Opioid overdose deaths remain a major public health crisis. We used a system dynamics simulation model of the U.S. opioid-using population age 12 and older to explore the impacts of 11 strategies on the prevalence of opioid use disorder (OUD) and fatal opioid overdoses from 2022 to 2032. These strategies spanned opioid misuse and OUD prevention, buprenorphine capacity, recovery support, and overdose harm reduction. By 2032, three strategies saved the most lives: (i) reducing the risk of opioid overdose involving fentanyl use, which may be achieved through fentanyl-focused harm reduction services; (ii) increasing naloxone distribution to people who use opioids; and (iii) recovery support for people in remission, which reduced deaths by reducing OUD. Increasing buprenorphine providers' capacity to treat more people decreased fatal overdose, but only in the short term. Our analysis provides insight into the kinds of multifaceted approaches needed to save lives.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Opioid overdose deaths remain a major public health crisis. We used a system dynamics simulation model of the U.S. opioid-using population age 12 and older to explore the impacts of 11 strategies on the prevalence of opioid use disorder (OUD) and fatal opioid overdoses from 2022 to 2032. These strategies spanned opioid misuse and OUD prevention, buprenorphine capacity, recovery support, and overdose harm reduction. By 2032, three strategies saved the most lives: (i) reducing the risk of opioid overdose involving fentanyl use, which may be achieved through fentanyl-focused harm reduction services; (ii) increasing naloxone distribution to people who use opioids; and (iii) recovery support for people in remission, which reduced deaths by reducing OUD. Increasing buprenorphine providers' capacity to treat more people decreased fatal overdose, but only in the short term. Our analysis provides insight into the kinds of multifaceted approaches needed to save lives.
Garcia, Gian-Gabriel P; Dehghanpoor, Ramin; Stringfellow, Erin J; Gupta, Marichi; Rochelle, Jillian; Mason, Elizabeth; Pujol, Toyya A; Jalali, Mohammad S
Identifying and Characterizing Medical Advice-Seekers on a Social Media Forum for Buprenorphine Use Journal Article
In: Int J Environ Res Public Health, vol. 19, no. 10, 2022, ISSN: 1660-4601.
@article{pmid35627818,
title = {Identifying and Characterizing Medical Advice-Seekers on a Social Media Forum for Buprenorphine Use},
author = {Gian-Gabriel P Garcia and Ramin Dehghanpoor and Erin J Stringfellow and Marichi Gupta and Jillian Rochelle and Elizabeth Mason and Toyya A Pujol and Mohammad S Jalali},
doi = {10.3390/ijerph19106281},
issn = {1660-4601},
year = {2022},
date = {2022-05-01},
journal = {Int J Environ Res Public Health},
volume = {19},
number = {10},
abstract = {BACKGROUND: Online communities such as Reddit can provide social support for those recovering from opioid use disorder. However, it is unclear whether and how advice-seekers differ from other users. Our research addresses this gap by identifying key characteristics of r/suboxone users that predict advice-seeking behavior.
OBJECTIVE: The objective of this analysis is to identify and describe advice-seekers on Reddit for buprenorphine-naloxone use using text annotation, social network analysis, and statistical modeling techniques.
METHODS: We collected 5258 posts and their comments from Reddit between 2014 and 2019. Among 202 posts which met our inclusion criteria, we annotated each post to determine which were advice-seeking ( = 137) or not advice-seeking ( = 65). We also annotated each posting user's buprenorphine-naloxone use status (current versus formerly taking and, if currently taking, whether inducting or tapering versus other stages) and quantified their connectedness using social network analysis. To analyze the relationship between Reddit users' advice-seeking and their social connectivity and medication use status, we constructed four models which varied in their inclusion of explanatory variables for social connectedness and buprenorphine use status.
RESULTS: The stepwise model containing "total degree" ( = 0.002), "using: inducting/tapering" ( < 0.001), and "using: other" ( = 0.01) outperformed all other models. Reddit users with fewer connections and who are currently using buprenorphine-naloxone are more likely to seek advice than those who are well-connected and no longer using the medication, respectively. Importantly, advice-seeking behavior is most accurately predicted using a combination of network characteristics and medication use status, rather than either factor alone.
CONCLUSIONS: Our findings provide insights for the clinical care of people recovering from opioid use disorder and the nature of online medical advice-seeking overall. Clinicians should be especially attentive (e.g., through frequent follow-up) to patients who are inducting or tapering buprenorphine-naloxone or signal limited social support.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Online communities such as Reddit can provide social support for those recovering from opioid use disorder. However, it is unclear whether and how advice-seekers differ from other users. Our research addresses this gap by identifying key characteristics of r/suboxone users that predict advice-seeking behavior.
OBJECTIVE: The objective of this analysis is to identify and describe advice-seekers on Reddit for buprenorphine-naloxone use using text annotation, social network analysis, and statistical modeling techniques.
METHODS: We collected 5258 posts and their comments from Reddit between 2014 and 2019. Among 202 posts which met our inclusion criteria, we annotated each post to determine which were advice-seeking ( = 137) or not advice-seeking ( = 65). We also annotated each posting user's buprenorphine-naloxone use status (current versus formerly taking and, if currently taking, whether inducting or tapering versus other stages) and quantified their connectedness using social network analysis. To analyze the relationship between Reddit users' advice-seeking and their social connectivity and medication use status, we constructed four models which varied in their inclusion of explanatory variables for social connectedness and buprenorphine use status.
RESULTS: The stepwise model containing "total degree" ( = 0.002), "using: inducting/tapering" ( < 0.001), and "using: other" ( = 0.01) outperformed all other models. Reddit users with fewer connections and who are currently using buprenorphine-naloxone are more likely to seek advice than those who are well-connected and no longer using the medication, respectively. Importantly, advice-seeking behavior is most accurately predicted using a combination of network characteristics and medication use status, rather than either factor alone.
CONCLUSIONS: Our findings provide insights for the clinical care of people recovering from opioid use disorder and the nature of online medical advice-seeking overall. Clinicians should be especially attentive (e.g., through frequent follow-up) to patients who are inducting or tapering buprenorphine-naloxone or signal limited social support.
OBJECTIVE: The objective of this analysis is to identify and describe advice-seekers on Reddit for buprenorphine-naloxone use using text annotation, social network analysis, and statistical modeling techniques.
METHODS: We collected 5258 posts and their comments from Reddit between 2014 and 2019. Among 202 posts which met our inclusion criteria, we annotated each post to determine which were advice-seeking ( = 137) or not advice-seeking ( = 65). We also annotated each posting user's buprenorphine-naloxone use status (current versus formerly taking and, if currently taking, whether inducting or tapering versus other stages) and quantified their connectedness using social network analysis. To analyze the relationship between Reddit users' advice-seeking and their social connectivity and medication use status, we constructed four models which varied in their inclusion of explanatory variables for social connectedness and buprenorphine use status.
RESULTS: The stepwise model containing "total degree" ( = 0.002), "using: inducting/tapering" ( < 0.001), and "using: other" ( = 0.01) outperformed all other models. Reddit users with fewer connections and who are currently using buprenorphine-naloxone are more likely to seek advice than those who are well-connected and no longer using the medication, respectively. Importantly, advice-seeking behavior is most accurately predicted using a combination of network characteristics and medication use status, rather than either factor alone.
CONCLUSIONS: Our findings provide insights for the clinical care of people recovering from opioid use disorder and the nature of online medical advice-seeking overall. Clinicians should be especially attentive (e.g., through frequent follow-up) to patients who are inducting or tapering buprenorphine-naloxone or signal limited social support.