Children's understanding of inherited resemblance: The case of two parents. [IF 1.0]

Four-, 6-, and 10-year-old children were tested in a forced-choice procedure about their beliefs on the inheritance of physical characteristics. They were presented with pictures of two biological parents, and then asked to select the most likely descendant out of three alternatives: a father look-alike, a mother look-alike, and an alternative representing the combined influence of both parents. In several question pairs, additional information was given about the parent-child relationship that was clearly irrelevant to the principles of heredity to examine the extent to which domain confusions were likely to occur. The majority of the 10-year-olds consistently preferred the alternative in which the combined influence of both parents was shown and domain confusions hardly ever occurred. Four- and 6-year-olds, in contrast, were still influenced by information from alien domains, although even their reasoning about inheritance seemed to be theory-like. Overall, the results suggest that with age, children develop a more restricted and better-defined conception of the principles of heredity, in which the combined influence of both parents is acknowledged

“Cookbook medicine”: Exploring the impact of opioid prescribing limits legislation on clinical practice and patient experiences

Opioid dependence and overdose are serious public health concerns. States have responded by enacting legislation regulating opioid-prescribing practices. Through in-depth interviews with clinicians, state officials, and organizational stakeholders, this paper examines opioid prescribing limits legislation (PLL) in North Carolina and how it impacts clinical practice. Since the advent of PLL, clinicians report being more mindful when prescribing opioids and as expected, writing for shorter durations for both acute and postoperative pain. But clinicians also report prescribing opioids less frequently for acute pain, refusing to write second opioid prescriptions, foisting responsibility for patient pain care onto other clinicians, and no longer writing opioid prescriptions for chronic pain patients. They directly credit PLL for these changes, including institutional policies enacted in response to PLL, and, to a lesser degree, notions of “do no harm.” However, we argue that misapplication of and ambiguities in PLL along with defensive medicine practices whereby clinicians and their institutions center their legal interests over patient care, amplify these restrictive changes in clinical practice. Clinicians’ narratives reveal downstream consequences for patients including undertreated pain, being viewed as drug-seeking when questioning opioid-prescribing decisions, and having to overuse the medical system to achieve pain relief

Association of household opioid availability and prescription opioid initiation among household members

Importance Increases in prescription opioid use in the United States have been attributed to changing prescribing guidelines and attitudes toward pain relief; however, the spread of opioid use within households through drug diversion may also be a contributing factor. Objective To investigate whether individuals living in a household with a prescription opioid user are more likely to initiate prescription opioids themselves, compared with individuals in households with a prescription nonsteroidal anti-inflammatory drug (NSAID) user. Design, Setting, and Participants This was a retrospective cohort study using administrative health care claims data from 2000 to 2014 of commercial insurance beneficiaries sharing a health plan with continuous prescription drug coverage, without opioid or NSAID use in the prior year. Enrollees were followed from the date of the first prescription filled by a household member for an eligible opioid or NSAID until initiation of prescription opioids, disenrollment, or administrative censoring after 1 year or the end of follow-up on December 31, 2014. Risk of opioid initiation was derived from inverse probability-weighted (IPW) Kaplan-Meier estimators that adjusted for potential confounders, prognostic factors, and predictors of censoring. Exposure Outpatient pharmacy dispensing of a prescription opioid or prescription NSAID. Main Outcomes and Measures Incident outpatient pharmacy fill for a prescription opioid by a household member. Results From 2000 to 2014, 12 695 280 individuals were exposed to prescription opioids and 6 359 639 to prescription NSAIDS through an index prescription to a household member. The IPW estimated risk of opioid initiation in the subsequent year was 11.83% (95% CI, 11.81%-11.85%) among individuals exposed to prescription opioids in the household, compared with 11.11% (95% CI, 11.09%-11.14%) among individuals exposed to prescription NSAIDs, resulting in a risk difference of 0.71% (95% CI, 0.68%-0.74%). An unmeasured confounder that is modestly associated with the exposure (eg, prevalence difference = 0.9%) and the outcome (eg, risk difference = 0.9) after adjustment for all measured variables could explain our observed estimate of the overall risk difference (0.71%). Conclusions and Relevance Living in a household with a prescription opioid user may increase risk of prescription opioid use, which may reflect both increased access to these products as well as shared risk factors, such as prescriber preference and prescription drug monitoring

Health promotion: results of focus groups with African-American men

http://dx.doi.org/10.1016/j.jomh.2010.11.00

Implementation of mandatory opioid prescribing limits in North Carolina: healthcare administrator and prescriber perspectives

Background: Recent increases in state laws to reduce opioid prescribing have demonstrated a need to understand how they are interpreted and implemented in healthcare systems. The purpose of this study was to explore the systems, strategies, and resources that hospital administrators and prescribers used to implement the 2017 North Carolina Strengthen Opioid Prevention (STOP) Act opioid prescribing limits, which limited initial prescriptions to a five (for acute) or seven (for post-surgical) days’ supply. Methods: We interviewed 14 hospital administrators and 38 prescribers with degrees in medicine, nursing, pharmacy, business administration and public health working across North Carolina. Interview guides, informed by the Consolidated Framework for Implementation Research, explored barriers and facilitators to implementation. Interview topics included communication, resources, and hospital system support. Interviews were recorded and transcribed, then analyzed using flexible coding, integrating inductive and deductive coding, to inform analytic code development and identify themes. Results: We identified three main themes around implementation of STOP act mandated prescribing limits: organizational communication, prescriber education, and changes in the electronic medical record (EMR) systems. Administrators reflected on implementation in the context of raising awareness and providing reminders to facilitate changes in prescriber behavior, operationalized through email and in-person communications as well as dedicated resources to EMR changes. Prescribers noted administrative communications about prescribing limits often focused on legality, suggesting a directive of the organization’s policy rather than a passive reminder. Prescribers expressed a desire for more spaces to have their questions answered and resources for patient communications. While hospital administrators viewed compliance with the law as a priority, prescribers reflected on concerns for adequately managing their patients’ pain and limited time for clinical care. Conclusions: Hospital administrators and prescribers approached implementation of the STOP act prescribing limits with different mindsets. While administrators were focused on policy compliance, prescribers were focused on their patients’ needs. Strategies to implement the mandate then had to balance patient needs with policy compliance. As states continue to legislate to prevent opioid overdose deaths, understanding how laws are implemented by healthcare systems and prescribers will improve their effectiveness through tailoring and maximizing available resources

Hurricane Florence and suicide mortality in North Carolina: A controlled interrupted time-series analysis

Background Natural disasters are associated with increased mental health disorders and suicidal ideation; however, associations with suicide deaths are not well understood. We explored how Hurricane Florence, which made landfall in September 2018, may have impacted suicide deaths in North Carolina (NC). Methods We used publicly available NC death records data to estimate associations between Hurricane Florence and monthly suicide death rates using a controlled, interrupted time series analysis. Hurricane exposure was determined by using county-level support designations from the Federal Emergency Management Agency. We examined effect modification by sex, age group, and race/ethnicity. Results 8363 suicide deaths occurred between January 2014 and December 2019. The overall suicide death rate in NC between 2014 and 2019 was 15.53 per 100 000 person-years (95% CI 15.20 to 15.87). Post-Hurricane, there was a small, immediate increase in the suicide death rate among exposed counties (0.89/100 000 PY; 95% CI -2.69 to 4.48). Comparing exposed and unexposed counties, there was no sustained post-Hurricane Florence change in suicide death rate trends (0.02/100 000 PY per month; 95% CI -0.33 to 0.38). Relative to 2018, NC experienced a statewide decline in suicides in 2019. An immediate increase in suicide deaths in Hurricane-affected counties versus Hurricane-unaffected counties was observed among women, people under age 65 and non-Hispanic black individuals, but there was no sustained change in the months after Hurricane Florence. Conclusions Although results did not indicate a strong post-Hurricane Florence impact on suicide rates, subgroup analysis suggests differential impacts of Hurricane Florence on several groups, warranting future follow-up

Innovations in suicide prevention research (INSPIRE): a protocol for a population-based case–control study

Background Suicide deaths have been increasing for the past 20 years in the USA resulting in 45 979 deaths in 2020, a 29% increase since 1999. Lack of data linkage between entities with potential to implement large suicide prevention initiatives (health insurers, health institutions and corrections) is a barrier to developing an integrated framework for suicide prevention. Objectives Data linkage between death records and several large administrative datasets to (1) estimate associations between risk factors and suicide outcomes, (2) develop predictive algorithms and (3) establish long-term data linkage workflow to ensure ongoing suicide surveillance. Methods We will combine six data sources from North Carolina, the 10th most populous state in the USA, from 2006 onward, including death certificate records, violent deaths reporting system, large private health insurance claims data, Medicaid claims data, University of North Carolina electronic health records and data on justice involved individuals released from incarceration. We will determine the incidence of death from suicide, suicide attempts and ideation in the four subpopulations to establish benchmarks. We will use a nested case–control design with incidence density-matched population-based controls to (1) identify short-term and long-term risk factors associated with suicide attempts and mortality and (2) develop machine learning-based predictive algorithms to identify individuals at risk of suicide deaths. Discussion We will address gaps from prior studies by establishing an in-depth linked suicide surveillance system integrating multiple large, comprehensive databases that permit establishment of benchmarks, identification of predictors, evaluation of prevention efforts and establishment of long-term surveillance workflow protocols

Development and validation of an electronic health records-based opioid use disorder algorithm by expert clinical adjudication among patients with prescribed opioids

Background: In the US, over 200 lives are lost from opioid overdoses each day. Accurate and prompt diagnosis of opioid use disorders (OUD) may help prevent overdose deaths. However, international classification of disease (ICD) codes for OUD are known to underestimate prevalence, and their specificity and sensitivity are unknown. We developed and validated algorithms to identify OUD in electronic health records (EHR) and examined the validity of OUD ICD codes. Methods: Through four iterations, we developed EHR-based OUD identification algorithms among patients who were prescribed opioids from 2014 to 2017. The algorithms and OUD ICD codes were validated against 169 independent “gold standard” EHR chart reviews conducted by an expert adjudication panel across four healthcare systems. After using 2014–2020 EHR for validating iteration 1, the experts were advised to use 2014–2017 EHR thereafter. Results: Of the 169 EHR charts, 81 (48%) were reviewed by more than one expert and exhibited 85% expert agreement. The experts identified 54 OUD cases. The experts endorsed all 11 OUD criteria from the Diagnostic and Statistical Manual of Mental Disorders-5, including craving (72%), tolerance (65%), withdrawal (56%), and recurrent use in physically hazardous conditions (50%). The OUD ICD codes had 10% sensitivity and 99% specificity, underscoring large underestimation. In comparison our algorithm identified OUD with 23% sensitivity and 98% specificity. Conclusions and relevance: This is the first study to estimate the validity of OUD ICD codes and develop validated EHR-based OUD identification algorithms. This work will inform future research on early intervention and prevention of OUD