Three educational interventions were simulated in a system dynamics model of the medical use, trafficking, and nonmedical use of pharmaceutical opioids. The study relied on secondary data obtained in the literature for the period of 1995 to 2008 as well as expert panel recommendations regarding model parameters and structure. The behavior of the resulting systems-level model was tested for fit against reference behavior data. After the base model was tested, logic to represent three educational interventions was added and the impact of each intervention on simulated overdose deaths was evaluated over a 7-year evaluation period, 2008 to 2015. Principal findings were that a prescriber education intervention not only reduced total overdose deaths in the model but also reduced the total number of persons who receive opioid analgesic therapy, medical user education not only reduced overdose deaths among medical users but also resulted in increased deaths from nonmedical use, and a “popularity” intervention sharply reduced overdose deaths among nonmedical users while having no effect on medical use. System dynamics modeling shows promise for evaluating potential interventions to ameliorate the adverse outcomes associated with the complex system surrounding the use of opioid analgesics to treat pain.

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BACKGROUND: This study assessed the impact of Affordable Care Act (ACA) Medicaid expansion on health insurance rates and receipt of cardiovascular-related preventive screenings (body mass index, glycated hemoglobin [HbA1c], low-density lipoproteins, and blood pressure) for cancer survivors seen in community health centers (CHCs). METHODS: This study identified cancer survivors aged 19 to 64 years with at least 3 CHC visits in 13 states from the Accelerating Data Value Across a National Community Health Center Network (ADVANCE). Via inverse probability of treatment weighting multilevel multinomial modeling, insurance rates before and after the ACA were estimated by whether a patient lived in a state that expanded Medicaid, and changes between a pre-ACA time period and 2 post-ACA time periods were assessed. RESULTS: The weighted estimated sample size included 409 cancer survivors in nonexpansion states and 2650 in expansion states. In expansion states, the proportion of uninsured cancer survivors decreased significantly from 20.3% in 2012-2013 to 4.5%in 2016-2017, and the proportion of those with Medicaid coverage increased significantly from 38.8% to 55.6%. In nonexpansion states, there was a small decrease in uninsurance rates (from 33.6% in 2012-2013 to 22.5% in 2016-2017). Cardiovascularrelated preventive screening rates increased over time in both expansion and nonexpansion states: HbA1c rates nearly doubled from the pre-ACA period (2012-2013) to the post-ACA period (2016-2017) in expansion states (from 7.2% to 12.8%) and nonexpansion states (from 9.3% to 16.8%). CONCLUSIONS: This study found a substantial decline in uninsured visits among cancer survivors in Medicaid expansion states. Yet, 1 in 5 cancer survivors living in a state that did not expand Medicaid remained uninsured. Several ACA provisions likely worked together to increase cardiovascular-related preventive screening rates for cancer survivors seen in CHCs.

Introduction Community health centers (CHCs) care for vulnerable patients who use tobacco at higher than national rates. States that expanded Medicaid eligibility under the Affordable Care Act (ACA) provided insurance coverage to tobacco users not previously Medicaid-eligible, thereby potentially increasing their odds of receiving cessation assistance. We examined if tobacco users in Medicaid expansion states had increased quit rates, cessation medications ordered, and greater health care utilization compared to patients in non-expansion states. Methods Using electronic health record (EHR) data from 219 CHCs in 10 states that expanded Medicaid as of January 1, 2014, we identified patients aged 19–64 with tobacco use status documented in the EHR within 6 months prior to ACA Medicaid expansion and ≥1 visit with tobacco use status assessed within 24 months post-expansion (January 1, 2014 to December 31, 2015). We propensity score matched these patients to tobacco users from 108 CHCs in six non-expansion states (n = 27 670 matched pairs; 55 340 patients). Using a retrospective observational cohort study design, we compared odds of having a quit status, cessation medication ordered, and ≥6 visits within the post-expansion period among patients in expansion versus non-expansion states. Results Patients in expansion states had increased adjusted odds of quitting (adjusted odds ratio [aOR] = 1.35, 95% confidence interval [CI]: 1.28–1.43), having a medication ordered (aOR = 1.53, 95% CI: 1.44–1.62), and having ≥6 follow-up visits (aOR = 1.34, 95% CI: 1.28–1.41) compared to patients from non-expansion states. Conclusions Increased access to insurance via the ACA Medicaid expansion likely led to increased quit rates within this vulnerable population. Implications CHCs care for vulnerable patients at higher risk of tobacco use than the general population. Medicaid expansion via the ACA provided insurance coverage to a large number of tobacco users not previously Medicaid-eligible. We found that expanded insurance coverage was associated with increased cessation assistance and higher odds of tobacco cessation. Continued provision of insurance coverage could lead to increased quit rates among high-risk populations, resulting in improvements in population health outcomes and reduced total health care costs.

The ability to inhibit host cell apoptosis is important for the intracellular replication of the obligate intracellular pathogen Coxiella burnetii, as it allows the completion of the lengthy bacterial replication cycle. Effector proteins injected into the host cell by the C. burnetii type IVB secretion system (T4BSS) are required for the inhibition of host cell apoptosis. AnkG is one of these anti-apoptotic effector proteins. The inhibitory effect of AnkG requires its nuclear localization, which depends on p32-dependent intracellular trafficking and importin-α1-mediated nuclear entry of AnkG. Here, we compared the sequences of ankG from 37 C. burnetii isolates and classified them in three groups based on the predicted protein size. The comparison of the three different groups allowed us to identify the first 28 amino acids as essential and sufficient for the anti-apoptotic activity of AnkG. Importantly, only the full-length protein from the first group is a bona fide effector protein injected into host cells during infection and has anti-apoptotic activity. Finally, using the Galleria mellonella infection model, we observed that AnkG from the first group has the ability to attenuate pathology during in vivo infection, as it allows survival of the larvae despite bacterial replication.

The system dynamics approach may have potential for opioid-related policy evaluation. However, metrics must be carefully selected, and trade-offs may be involved. For example, it may be difficult to limit negative outcomes associated with pharmaceutical opioids without adversely affecting chronic pain patients' access to pharmaceutical treatment. Ultimately, a combination of metrics and value judgments will be needed to properly evaluate mitigation strategies.

To assess the prevalence of pre-existing conditions for community health center (CHC) patients who gained insurance coverage post-Affordable Care Act (ACA). Methods: We analyzed electronic health record data from 78,059 patients aged 19 to 64 uninsured at their last visit pre-ACA from 386 CHCs in 19 states. We compared the prevalence and types of pre-existing conditions pre-ACA (2012 to 2013) and post-ACA (2014 to 2015), by insurance status and race/ethnicity. Results: Pre-ACA, >50% of patients in the cohort had >1 Pre-existing condition. Post-ACA, >70% of those who gained insurance coverage had >1 condition. Post-ACA, all racial/ethnic subgroups showed an increase in the number of pre-existing conditions, with non-Hispanic Black and Hispanic patients experiencing the largest increases (adjusted prevalence difference, 18.9; 95% CI, 18.2 to 19.6 and 18.3; 95% CI, 17.8 to 18.7, respectively). The most common conditions post-ACA were mental health disorders with the highest prevalence among patients who gained Medicaid (45.6%) and lowest among those who gained private coverage (30.5%). Conclusions: This study emphasizes the high prevalence of pre-existing conditions among CHC patients and the large increase in the proportion of patients with at least 1 of these diagnoses post-ACA. Given how common these conditions are, repealing pre-existing condition protections could be extremely harmful to millions of patients and would likely exacerbate health care and health disparities.

BACKGROUND: Primary care providers must understand the use patterns, clinical complexity, and primary care needs of cancer survivors to provide quality health care services. However, to the authors' knowledge, little is known regarding the prevalence and health care needs of this growing population, particularly in safety net settings. METHODS: The authors identified adults with a history of cancer documented in primary care electronic health records within a network of community health centers (CHCs) in 19 states. The authors estimated cancer history prevalence among >1.2 million patients and compared sex-specific site distributions with national estimates. Each survivor was matched to 3 patients without cancer from the same set of clinics. The demographic characteristics, primary care use, and comorbidity burden then were compared between the 2 groups, assessing differences with absolute standardized mean differences (ASMDs). ASMD values >0.1 denote meaningful differences between groups. Generalized estimating equations yielded adjusted odds ratios (aORs) for select indicators. RESULTS: A total of 40,266 cancer survivors were identified (prevalence of 3.0% of adult CHC patients). Compared with matched cancer-free patients, a higher percentage of survivors had ≥6 primary care visits across 3 years (62% vs 48%) and were insured (83% vs 74%) (ASMD, >0.1 for both). Cancer survivors had excess medical complexity, including a higher prevalence of depression, asthma/chronic obstructive pulmonary disease, and liver disease (ASMD, >0.1 for all). Survivors had higher odds of any opioid prescription (aOR, 1.23; 95% CI, 1.19-1.27) and chronic opioid therapy (aOR, 1.27; 95% CI, 1.23-1.32) compared with matched controls (P < .001 for all). CONCLUSIONS: Identifying cancer survivors and understanding their patterns of utilization and physical and mental comorbidities present an opportunity to tailor primary health care services to this population. Cancer 2019;125:3448-3456.