Modeling the evolution of the US opioid crisis for national policy development.

The opioid crisis is a major public health challenge in the United States, killing about 70,000 people in 2020 alone. Long delays and feedbacks between policy actions and their effects on drug-use behavior create dynamic complexity, complicating policy decision-making. In 2017, the National Academies of Sciences, Engineering, and Medicine called for a quantitative systems model to help understand and address this complexity and guide policy decisions. Here, we present SOURCE (Simulation of Opioid Use, Response, Consequences, and Effects), a dynamic simulation model developed in response to that charge. SOURCE tracks the US population aged ≥12 y through the stages of prescription and illicit opioid (e.g., heroin, illicit fentanyl) misuse and use disorder, addiction treatment, remission, and overdose death. Using data spanning from 1999 to 2020, we highlight how risks of drug use initiation and overdose have evolved in response to essential endogenous feedback mechanisms, including: 1) social influence on drug use initiation and escalation among people who use opioids; 2) risk perception and response based on overdose mortality, influencing potential new initiates; and 3) capacity limits on treatment engagement; as well as other drivers, such as 4) supply-side changes in prescription opioid and heroin availability; and 5) the competing influences of illicit fentanyl and overdose death prevention efforts. Our estimates yield a more nuanced understanding of the historical trajectory of the crisis, providing a basis for projecting future scenarios and informing policy planning.

Unspoken Truths: Mental Health Among Academic Surgeons.

OBJECTIVE: To characterize the current state of mental health within the surgical workforce in the United States. BACKGROUND: Mental illness and suicide is a growing concern in the medical community; however, the current state is largely unknown. METHODS: Cross-sectional survey of the academic surgery community assessing mental health, medical error, and suicidal ideation. The odds of suicidal ideation adjusting for sex, prior mental health diagnosis, and validated scales screening for depression, anxiety, post-traumatic stress disorder (PTSD), and alcohol use disorder were assessed. RESULTS: Of 622 participating medical students, trainees, and surgeons (estimated response rate=11.4%-14.0%), 26.1% (141/539) reported a previous mental health diagnosis. In all, 15.9% (83/523) of respondents screened positive for current depression, 18.4% (98/533) for anxiety, 11.0% (56/510) for alcohol use disorder, and 17.3% (36/208) for PTSD. Medical error was associated with depression (30.7% vs. 13.3%, P <0.001), anxiety (31.6% vs. 16.2%, P =0.001), PTSD (12.8% vs. 5.6%, P =0.018), and hazardous alcohol consumption (18.7% vs. 9.7%, P =0.022). Overall, 13.2% (73/551) of respondents reported suicidal ideation in the past year and 9.6% (51/533) in the past 2 weeks. On adjusted analysis, a previous history of a mental health disorder (aOR: 1.97, 95% CI: 1.04-3.65, P =0.033) and screening positive for depression (aOR: 4.30, 95% CI: 2.21-8.29, P <0.001) or PTSD (aOR: 3.93, 95% CI: 1.61-9.44, P =0.002) were associated with increased odds of suicidal ideation over the past 12 months. CONCLUSIONS: Nearly 1 in 7 respondents reported suicidal ideation in the past year. Mental illness and suicidal ideation are significant problems among the surgical workforce in the United States.

Planning, implementing and governing systems-based co-creation: the DISCOVER framework.

BACKGROUND: Increasingly, public health faces challenges requiring complex, multifaceted and multi-sectoral responses. This calls for systems-based approaches that facilitate the kind of collective and collaborative thinking and working required to address complexity. While the literature on systems thinking, system dynamics and the associated methodologies is extensive, there remains little clear guidance on how to plan, govern and implement participatory systems approaches within a co-creation process. METHODS: We used a three-step process to develop DISCOVER, a framework for implementing, and governing systems-based co-creation: Stage 1: We conducted a literature analysis of key texts to identify well-documented methods and phases for co-creation using a systems approach, as well as areas where gaps existed. Stage 2: We looked for the most appropriate methods and approaches to fill the gaps in the knowledge production chain. Stage 3: We developed the framework, identifying how the different tools and approaches fit together end-to-end, from sampling and recruiting participants all the way through to responding with an action plan. RESULTS: We devised DISCOVER to help guide researchers and stakeholders to collectively respond to complex social, health and wider problems. DISCOVER is a strategic research planning and governance framework that provides an actionable, systematic way to conceptualise complex problems and move from evidence to action, using systems approaches and co-creation. In this article, we introduce the eight-step framework and provide an illustrative case study showcasing its potential. The framework integrates complementary approaches and methods from social network analysis, systems thinking and co-creation literature. The eight steps are followed sequentially but can overlap. CONCLUSIONS: DISCOVER increases rigour and transparency in system approaches to tackling complex issues going from planning to action. It is being piloted in environmental health research but may be suitable to address other complex challenges and could be incorporated into research proposals and protocols for future projects.

Dynamics of colorectal cancer screening in low and middle-income countries: A modeling analysis from Thailand.

BACKGROUND: Low and middle-income countries face constraints for early colorectal cancer (CRC) detection, including restricted access to care and low colonoscopy capacity. Considering these constraints, we studied strategies for increasing access to early CRC detection and reducing CRC progression and mortality rates in Thailand. METHODS: We developed a system dynamics model to simulate CRC death and progression trends. We analyzed the impacts of increased access to screening via fecal immunochemical test and colonoscopy, improving access to CRC diagnosis among symptomatic individuals, and their combination. RESULTS: Projecting the status quo (2023-2032), deaths per 100K people increase from 87.5 to 115.4, and CRC progressions per 100K people rise from 131.8 to 159.8. In 2032, improved screening access prevents 2.5 CRC deaths and 2.5 progressions per 100K people, with cumulative prevented 7K deaths and 9K progressions, respectively. Improved symptom evaluation access prevents 7.5 CRC deaths per 100K with no effect on progression, totaling 35K saved lives. A combined approach prevents 9.3 deaths and 1.8 progressions per 100K, or 41K and 7K cumulatively. The combined strategy prevents most deaths; however, there is a tradeoff: It prevents fewer CRC progressions than screening access improvement. Increasing the current annual colonoscopy capacity (200K) to sufficient capacity (681K), the combined strategy achieves the best results, preventing 15.0 CRC deaths and 10.3 CRC progressions per 100K people, or 54K and 30K cumulatively. CONCLUSION: Until colonoscopy capacity increases, enhanced screening and symptom evaluation are needed simultaneously to curb CRC deaths, albeit not the best strategy for CRC progression prevention.

Social vulnerability predictors of drug poisoning mortality: A machine learning analysis in the United States.

BACKGROUND AND OBJECTIVES: Drug poisoning is a leading cause of unintentional deaths in the United States. Despite the growing literature, there are a few recent analyses of a wide range of community-level social vulnerability features contributing to drug poisoning mortality. Current studies on this topic face three limitations: often studying a limited subset of vulnerability features, focusing on small sample sizes, or solely including local data. To address this gap, we conducted a national-level analysis to study the impacts of several social vulnerability features in predicting drug mortality rates in the United States. METHODS: We used machine learning to investigate the role of 16 social vulnerability features in predicting drug mortality rates for US counties in 2014, 2016, and 2018-the most recent available data. We estimated each vulnerability feature's gain relative contribution in predicting drug poisoning mortality. RESULTS: Among all social vulnerability features, the percentage of noninstitutionalized persons with a disability is the most influential predictor, with a gain relative contribution of 18.6%, followed by population density and the percentage of minority residents (13.3% and 13%, respectively). Percentages of households with no available vehicles, mobile homes, and persons without a high school diploma are the following features with gain relative contributions of 6.3%, 5.8%, and 5.1%, respectively. CONCLUSION AND SCIENTIFIC SIGNIFICANCE: We identified social vulnerability features that are most predictive of drug poisoning mortality. Public health interventions and policies targeting vulnerable communities may increase the resilience of these communities and mitigate the overdose death and drug misuse crisis.

Evolution and Reproducibility of Simulation Modeling in Epidemiology and Health Policy Over Half a Century.

Simulation models are increasingly being used to inform epidemiologic studies and health policy, yet there is great variation in their transparency and reproducibility. In this review, we provide an overview of applications of simulation models in health policy and epidemiology, analyze the use of best reporting practices, and assess the reproducibility of the models using predefined, categorical criteria. We identified and analyzed 1,613 applicable articles and found exponential growth in the number of studies over the past half century, with the highest growth in dynamic modeling approaches. The largest subset of studies focused on disease policy models (70%), within which pathological conditions, viral diseases, neoplasms, and cardiovascular diseases account for one-third of the articles. Model details were not reported in almost half of the studies. We also provide in-depth analysis of modeling best practices, reporting quality and reproducibility of models for a subset of 100 articles (50 highly cited and 50 randomly selected from the remaining articles). Only 7 of 26 in-depth evaluation criteria were satisfied by more than 80% of samples. We identify areas for increased application of simulation modeling and opportunities to enhance the rigor and documentation in the conduct and reporting of simulation modeling in epidemiology and health policy.

A Systematic Review of Simulation Models to Track and Address the Opioid Crisis.

The opioid overdose crisis is driven by an intersecting set of social, structural, and economic forces. Simulation models are a tool to help us understand and address thiscomplex, dynamic, and nonlinear social phenomenon. We conducted a systematic review of the literature on simulation models of opioid use and overdose up to September 2019. We extracted modeling types, target populations, interventions, and findings; created a database of model parameters used for model calibration; and evaluated study transparency and reproducibility. Of the 1,398 articles screened, we identified 88 eligible articles. The most frequent types of models were compartmental (36%), Markov (20%), system dynamics (16%), and agent-based models (16%). Intervention cost-effectiveness was evaluated in 40% of the studies, and 39% focused on services for people with opioid use disorder (OUD). In 61% of the eligible articles, authors discussed calibrating their models to empirical data, and in 31%, validation approaches used in the modeling process were discussed. From the 63 studies that provided model parameters, we extracted the data sources on opioid use, OUD, OUD treatment, cessation or relapse, emergency medical services, and death parameters. From this database, potential model inputs can be identified and models can be compared with prior work. Simulation models should be used to tackle key methodological challenges, including the potential for bias in the choice of parameter inputs, investment in model calibration and validation, and transparency in the assumptions and mechanics of simulation models to facilitate reproducibility.

Health-related quality of life in cancer immunotherapy: a systematic perspective, using causal loop diagrams.

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.

Impact of Florida's prescription drug monitoring program on drug- related fatal vehicle crashes: a difference-in-differences approach.

BACKGROUND: Prescription drug use has soared in the USA within the last two decades. Prescription drugs can impair motor skills essential for the safe operation of a motor vehicle, and therefore can affect traffic safety. As one of the epicentres of the opioid epidemic, Florida has been struck by high opioid misuse and overdose rates, and has concurrently suffered major threats to traffic disruptions safety caused by driving under the influence of drugs. To prevent prescription opioid misuse in Florida, Prescription Drug Monitoring Programs (PDMPs) were implemented in September 2011. OBJECTIVE: To examine the impact of Florida's implementation of a mandatory PDMP on drug-related MVCs occurring on public roads. METHODS: We employed a difference-in-differences approach to estimate the difference in prescription drug-related fatal crashes in Florida associated with its 2011 PDMP implementation relative to those in Georgia, which did not use PDMPs during the same period (2009-2013). The analyses were conducted in 2020. RESULTS: In Florida, there was a significant decline in drug-related vehicle crashes during the 22 months post-PDMP. PDMP implementation was associated with approximately two (-2.21; 95% CI -4.04 to -0.37; p<0.05) fewer prescribed opioid-related fatal crashes every month, indicating 25% reduction in the number of monthly crashes. We conducted sensitivity analyses to investigate the impact of PDMP implementation on central nervous system depressants and stimulants as well as cocaine and marijuana-related fatal crashes but found no robust significant reductions. CONCLUSIONS: The implementation of PDMPs in Florida provided important benefits for traffic safety, reducing the rates of prescription opioid-related vehicle crashes.

Equitable Policies Need Equitable Practices: Alcohol- and Substance-Exposed Pregnancy as a Case Study.

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.

Insights into vaccine hesitancy from systems thinking, Rwanda.

OBJECTIVE: To investigate vaccine hesitancy leading to underimmunization and a measles outbreak in Rwanda and to develop a conceptual, community-level model of behavioural factors. METHODS: Local immunization systems in two Rwandan communities (one recently experienced a measles outbreak) were explored using systems thinking, human-centred design and behavioural frameworks. Data were collected between 2018 and 2020 from: discussions with 11 vaccination service providers (i.e. hospital and health centre staff); interviews with 161 children's caregivers at health centres; and nine validation interviews with health centre staff. Factors influencing vaccine hesitancy were categorized using the 3Cs framework: confidence, complacency and convenience. A conceptual model of vaccine hesitancy mechanisms with feedback loops was developed. FINDINGS: A comparison of service providers' and caregivers' perspectives in both rural and peri-urban settings showed that similar factors strengthened vaccine uptake: (i) high trust in vaccines and service providers based on personal relationships with health centre staff; (ii) the connecting role of community health workers; and (iii) a strong sense of community. Factors identified as increasing vaccine hesitancy (e.g. service accessibility and inadequate follow-up) differed between service providers and caregivers and between settings. The conceptual model could be used to explain drivers of the recent measles outbreak and to guide interventions designed to increase vaccine uptake. CONCLUSION: The application of behavioural frameworks and systems thinking revealed vaccine hesitancy mechanisms in Rwandan communities that demonstrate the interrelationship between immunization services and caregivers' vaccination behaviour. Confidence-building social structures and context-dependent challenges that affect vaccine uptake were also identified.

Economic Evaluation in Opioid Modeling: Systematic Review.

OBJECTIVES: The rapid increase in opioid overdose and opioid use disorder (OUD) over the past 20 years is a complex problem associated with significant economic costs for healthcare systems and society. Simulation models have been developed to capture and identify ways to manage this complexity and to evaluate the potential costs of different strategies to reduce overdoses and OUD. A review of simulation-based economic evaluations is warranted to fully characterize this set of literature. METHODS: A systematic review of simulation-based economic evaluation (SBEE) studies in opioid research was initiated by searches in PubMed, EMBASE, and EbscoHOST. Extraction of a predefined set of items and a quality assessment were performed for each study. RESULTS: The screening process resulted in 23 SBEE studies ranging by year of publication from 1999 to 2019. Methodological quality of the cost analyses was moderately high. The most frequently evaluated strategies were methadone and buprenorphine maintenance treatments; the only harm reduction strategy explored was naloxone distribution. These strategies were consistently found to be cost-effective, especially naloxone distribution and methadone maintenance. Prevention strategies were limited to abuse-deterrent opioid formulations. Less than half (39%) of analyses adopted a societal perspective in their estimation of costs and effects from an opioid-related intervention. Prevention strategies and studies' accounting for patient and physician preference, changing costs, or result stratification were largely ignored in these SBEEs. CONCLUSION: The review shows consistently favorable cost analysis findings for naloxone distribution strategies and opioid agonist treatments and identifies major gaps for future research.

Why Employees (Still) Click on Phishing Links: Investigation in Hospitals.

BACKGROUND: Hospitals have been one of the major targets for phishing attacks. Despite efforts to improve information security compliance, hospitals still significantly suffer from such attacks, impacting the quality of care and the safety of patients. OBJECTIVE: This study aimed to investigate why hospital employees decide to click on phishing emails by analyzing actual clicking data. METHODS: We first gauged the factors that influence clicking behavior using the theory of planned behavior (TPB) and integrating trust theories. We then conducted a survey in hospitals and used structural equation modeling to investigate the components of compliance intention. We matched employees' survey results with their actual clicking data from phishing campaigns. RESULTS: Our analysis (N=397) reveals that TPB factors (attitude, subjective norms, and perceived behavioral control), as well as collective felt trust and trust in information security technology, are positively related to compliance intention. However, compliance intention is not significantly related to compliance behavior. Only the level of employees' workload is positively associated with the likelihood of employees clicking on a phishing link. CONCLUSIONS: This is one of the few studies in information security and decision making that observed compliance behavior by analyzing clicking data rather than using self-reported data. We show that, in the context of phishing emails, intention and compliance might not be as strongly linked as previously assumed; hence, hospitals must remain vigilant with vulnerabilities that cannot be easily managed. Importantly, given the significant association between workload and noncompliance behavior (ie, clicking on phishing links), hospitals should better manage employees' workload to increase information security. Our findings can help health care organizations augment employees' compliance with their cybersecurity policies and reduce the likelihood of clicking on phishing links.

Patients' Perceptions of Barriers and Facilitators to the Adoption of E-Hospitals: Cross-Sectional Study in Western China.

BACKGROUND: As an innovative approach to providing web-based health care services from physical hospitals to patients at a distance, e-hospitals (ie, extended care hospitals through the internet) have been extensively developed in China. This closed health care delivery chain was developed by combining e-hospitals with physical hospitals; treatment begins with web-based consultation and registration, and then, patients are diagnosed and treated in a physical hospital. This approach is promising in its ability to improve accessibility, efficiency, and quality of health care. However, there is limited research on end users' acceptance of e-hospitals and the effectiveness of strategies aimed to prompt the adoption of e-hospitals in China. OBJECTIVE: This study aimed to provide insights regarding the adoption of e-hospitals by investigating patients' willingness to use e-hospitals and analyzing the barriers and facilitators to the adoption of this technology. METHODS: We used a pretested self-administered questionnaire and performed a cross-sectional analysis in 1032 patients across three hierarchical hospitals in West China from June to August 2019. Patients' sociodemographic characteristics, medical history, current disease status, proficiency with electronic devices, previous experience with web-based health services, willingness to use e-hospitals, and perceived facilitators and barriers were surveyed. Multiple significance tests were employed to examine disparities across four age groups, as well as those between patients who were willing to use e-hospitals and those who were not. Multivariate logistic regression was also performed to identify the potential predictors of willingness to use e-hospitals. RESULTS: Overall, it was found that 65.6% (677/1032) of participants were willing to use e-hospitals. The significant predictors of willingness to use e-hospitals were employment status (P=.02), living with children (P<.001), education level (P=.046), information technology skills (P<.001), and prior experience with web-based health care services (P<.001), whereas age, income, medical insurance, and familiarity with e-hospitals were not predictors. Additionally, the prominent facilitators of e-hospitals were convenience (641/677, 94.7%) and accessibility to skilled medical experts (489/677, 72.2%). The most frequently perceived barrier varied among age groups; seniors most often reported their inability to operate technological devices as a barrier (144/166, 86.7%), whereas young participants most often reported that they avoided e-hospital services because they were accustomed to face-to-face consultation (39/52, 75%). CONCLUSIONS: We identified the variables, facilitators, and barriers that play essential roles in the adoption of e-hospitals. Based on our findings, we suggest that efforts to increase the adoption of e-hospitals should focus on making target populations accustomed to web-based health care services while maximizing ease of use and providing assistance for technological inquiries.

The opioid crisis: need for systems science research.

The opioid epidemic in the United States has had a devastating impact on millions of people as well as on their families and communities. The increased prevalence of opioid misuse, use disorder and overdose in recent years has highlighted the need for improved public health approaches for reducing the tremendous harms of this illness. In this paper, we explain and call for the need for more systems science approaches, which can uncover the complexities of the opioid crisis, and help evaluate, analyse and forecast the effectiveness of ongoing and new policy interventions. Similar to how a stream of systems science research helped policy development in infectious diseases and obesity, more systems science research is needed in opioids.

The opioid crisis: a contextual, social-ecological framework.

The prevalence of opioid use and misuse has provoked a staggering number of deaths over the past two and a half decades. Much attention has focused on individual risks according to various characteristics and experiences. However, broader social and contextual domains are also essential contributors to the opioid crisis such as interpersonal relationships and the conditions of the community and society that people live in. Despite efforts to tackle the issue, the rates of opioid misuse and non-fatal and fatal overdose remain high. Many call for a broad public health approach, but articulation of what such a strategy could entail has not been fully realised. In order to improve the awareness surrounding opioid misuse, we developed a social-ecological framework that helps conceptualise the multivariable risk factors of opioid misuse and facilitates reviewing them in individual, interpersonal, communal and societal levels. Our framework illustrates the multi-layer complexity of the opioid crisis that more completely captures the crisis as a multidimensional issue requiring a broader and integrated approach to prevention and treatment.

Adoption of New Medical Technologies: The Case of Customized Individually Made Knee Implants.

OBJECTIVES: To investigate the impact of insurance coverage on the adoption of customized individually made (CIM) knee implants and to compare patient outcomes and cost effectiveness of off-the-shelf and CIM implants. METHODS: A system dynamics simulation model was developed to study adoption dynamics of CIM and meet the research objectives. The model reproduced the historical data on primary and revision knee replacement implants obtained from the literature and the Nationwide Inpatient Sample. Then the dynamics of adoption of CIM implants were simulated from 2018 to 2026. The rate of 90-day readmission, 3-year revision surgery, recovery period, time savings in operating rooms, and the associated cost within 3 years of primary knee replacement implants were used as performance metrics. RESULTS: The simulation results indicate that by 2026, an adoption rate of 90% for CIM implants can reduce the number of readmissions and revision surgeries by 62% and 39%, respectively, and can save hospitals and surgeons 6% on procedure time and cut down cumulative healthcare costs by approximately $38 billion. CONCLUSIONS: CIM implants have the potential to deliver high-quality care while decreasing overall healthcare costs, but their adoption requires the expansion of current insurance coverage. This work presents the first systematic study to understand the dynamics of adoption of CIM knee implants and instrumentation. More broadly, the current modeling approach and systems thinking perspective could be used to consider the adoption of any emerging customized therapies for personalized medicine.

Health Care and Cybersecurity: Bibliometric Analysis of the Literature.

BACKGROUND: Over the past decade, clinical care has become globally dependent on information technology. The cybersecurity of health care information systems is now an essential component of safe, reliable, and effective health care delivery. OBJECTIVE: The objective of this study was to provide an overview of the literature at the intersection of cybersecurity and health care delivery. METHODS: A comprehensive search was conducted using PubMed and Web of Science for English-language peer-reviewed articles. We carried out chronological analysis, domain clustering analysis, and text analysis of the included articles to generate a high-level concept map composed of specific words and the connections between them. RESULTS: Our final sample included 472 English-language journal articles. Our review results revealed that majority of the articles were focused on technology: Technology-focused articles made up more than half of all the clusters, whereas managerial articles accounted for only 32% of all clusters. This finding suggests that nontechnological variables (human-based and organizational aspects, strategy, and management) may be understudied. In addition, Software Development Security, Business Continuity, and Disaster Recovery Planning each accounted for 3% of the studied articles. Our results also showed that publications on Physical Security account for only 1% of the literature, and research in this area is lacking. Cyber vulnerabilities are not all digital; many physical threats contribute to breaches and potentially affect the physical safety of patients. CONCLUSIONS: Our results revealed an overall increase in research on cybersecurity and identified major gaps and opportunities for future work.

Cybersecurity in Hospitals: A Systematic, Organizational Perspective.

BACKGROUND: Cybersecurity incidents are a growing threat to the health care industry in general and hospitals in particular. The health care industry has lagged behind other industries in protecting its main stakeholder (ie, patients), and now hospitals must invest considerable capital and effort in protecting their systems. However, this is easier said than done because hospitals are extraordinarily technology-saturated, complex organizations with high end point complexity, internal politics, and regulatory pressures. OBJECTIVE: The purpose of this study was to develop a systematic and organizational perspective for studying (1) the dynamics of cybersecurity capability development at hospitals and (2) how these internal organizational dynamics interact to form a system of hospital cybersecurity in the United States. METHODS: We conducted interviews with hospital chief information officers, chief information security officers, and health care cybersecurity experts; analyzed the interview data; and developed a system dynamics model that unravels the mechanisms by which hospitals build cybersecurity capabilities. We then use simulation analysis to examine how changes to variables within the model affect the likelihood of cyberattacks across both individual hospitals and a system of hospitals. RESULTS: We discuss several key mechanisms that hospitals use to reduce the likelihood of cybercriminal activity. The variable that most influences the risk of cyberattack in a hospital is end point complexity, followed by internal stakeholder alignment. Although resource availability is important in fueling efforts to close cybersecurity capability gaps, low levels of resources could be compensated for by setting a high target level of cybersecurity. CONCLUSIONS: To enhance cybersecurity capabilities at hospitals, the main focus of chief information officers and chief information security officers should be on reducing end point complexity and improving internal stakeholder alignment. These strategies can solve cybersecurity problems more effectively than blindly pursuing more resources. On a macro level, the cyber vulnerability of a country's hospital infrastructure is affected by the vulnerabilities of all individual hospitals. In this large system, reducing variation in resource availability makes the whole system less vulnerable-a few hospitals with low resources for cybersecurity threaten the entire infrastructure of health care. In other words, hospitals need to move forward together to make the industry less attractive to cybercriminals. Moreover, although compliance is essential, it does not equal security. Hospitals should set their target level of cybersecurity beyond the requirements of current regulations and policies. As of today, policies mostly address data privacy, not data security. Thus, policy makers need to introduce policies that not only raise the target level of cybersecurity capabilities but also reduce the variability in resource availability across the entire health care system.

Cost-Effectiveness of Increasing Access to Colorectal Cancer Diagnosis: Analysis From Thailand.

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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.