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Existe en Colombia un aval constitucional para llevar a cabo la muerte digna. Sin embargo, a pesar de que fue desarrollado por varias resoluciones expedidas por el Ministerio de Salud y Protección Social (Minsalud), su práctica puede ser compleja debido a la intervención de diversos actores frente a los cuales puede incluso darse una colisión de derechos. En este artículo se plantean preguntas como: ¿qué hacer cuando se solicita la práctica de un procedimiento eutanásico y entran en conflicto derechos fundamentales de los actores involucrados?, ¿es clara, completa, precisa y efectiva la regulación frente al tema?, ¿los actores que intervienen en estos conflictos como prestadores de servicios, pacientes, médicos, ven sus derechos en conflicto en el procedimiento eutanásico en Colombia? Para dar respuestas a estos interrogantes, se abordó un estudio de los conceptos de derecho a la muerte digna, objeción de conciencia, eutanasia activa y pasiva, suicidio asistido y homicidio por piedad, así como la prueba de razonabilidad y principio de proporcionalidad, en aras de dar respuesta a estos interrogantes.

We examined a natural history of opioid overdose deaths from 1999-2021 in the United States to describe state-level spatio-temporal heterogeneity in the waves of the epidemic. We obtained overdose death counts by state from 1999-2021, categorized as involving prescription opioids, heroin, synthetic opioids, or unspecified drugs. We developed a Bayesian multivariate multiple change point model to flexibly estimate the timing and magnitude of state-specific changes in death rates involving each drug type. We found substantial variability around the timing and severity of each wave across states. The first wave of prescription-involved deaths started between 1999 and 2005, the second wave of heroin-involved deaths started between 2010 and 2014, and the third wave of synthetic opioid-involved deaths started between 2014 and 2021. The severity of the second and third waves was greater in states in the eastern half of the country. Our study highlights state-level variation in the timing and severity of the waves of the opioid epidemic by presenting a 23-year natural history of opioid overdose mortality in the United States. While reinforcing the general notion of three waves, we find that states did not uniformly experience the impacts of each wave.

El objetivo general del presente estudio fue determinar la percepción de los estudiantes de la Carrera de Obstetricia y Puericultura de la Universidad de Antofagasta sobre el uso de simulación clínica en su formación. Se llevó a cabo una investigación cualitativa de tipo interpretativa que se sustentó en las experiencias vividas por los discentes durante sus talleres preclínicos. El diseño metodológico se basó en la teoría fundamentada. Se entrevistaron 10 estudiantes de quinto año de la carrera, quienes participaron de manera voluntaria. El estudio fue aprobado por el Comité de Ética e Investigación Científica de esta Institución. La codificación inductiva y el método de comparación constante permitieron la saturación teórica de los datos procesados en Atlas.ti. Dentro de los resultados, se evidenciaron que la simulación clínica es una metodología de aprendizaje adecuada para desarrollar habilidades clínicas y blandas sin dañar a personas, sin embargo, no reemplaza el campo clínico real. Por otra parte, el docente facilita la autorreflexión, aumenta la motivación y disminuye la distancia entre la situación actual en la que se encuentra el aprendiz y la situación ideal a la que debe llegar, siempre y cuando posea una preparación técnica adecuada. Como conclusión, si bien, los estudiantes de esta carrera reconocieron el aporte de la simulación clínica en su formación, se mantiene el desafío de consolidar esta metodología de aprendizaje en la matronería.

BackgroundPrescription drug monitoring programs (PDMPs) that collect and distribute information on dispensed controlled substances have been adopted by nearly all US states. We know little about program characteristics that modify PDMP impact on prescription opioid (PO) overdose deaths.MethodsWe measured associations between adoption of any PDMP and changes in fatal PO overdoses in 2002-2016 across 3109 counties in 49 states and D.C. We then measured changes related to the adoption of "proactive PDMPs," which report outlying prescribing/dispensing patterns and provide broader access to PDMP data by law enforcement. Comparisons were made within 3 time intervals that broadly represent the evolution of PDMPs (2002-2004, 2005-2009, and 2010-2016). We modeled overdoses using Bayesian space-time models.ResultsAdoption of electronic PDMP access was associated with 9% lower rates of fatal PO overdoses after three years (rate ratio [RR] = 0.91, 95% credible interval [CI]: 0.88-0.93) with well-supported effects for methadone (RR = 0.86,95% CI: 0.82-0.90) and other synthetic opioids (RR = 0.82, 95% CI: 0.77-0.86). Compared with states with no/weak PDMPs, proactive PDMPs were associated with fewer deaths attributed to natural/semi-synthetic opioids (2002-2004: RR = 0.72 [0.66-0.78]; 2005-2009: RR = 0.93 [0.90-0.97]; 2010-2016: 0.89 [0.86-0.92]) and methadone (2002-2004: RR = 0.77 [0.69-0.85]; 2010-2016: RR = 0.90 [0.86-0.94]). Unintended effects were observed for synthetic opioids other than methadone (2005-2009: RR = 1.29 [1.21-1.38]; 2010-2016: RR = 1.22 [1.16-1.29]).ConclusionsState adoption of PDMPs was associated with fewer PO deaths overall while proactive PDMPs alone were associated with fewer deaths related to natural/semisynthetic opioids and methadone, the specific targets of these programs. See video abstract at, http://links.lww.com/EDE/B619.

BACKGROUND:Prescription drug monitoring programs (PDMP), by reducing access to prescribed opioids (POs), may contribute to a policy environment in which some people with opioid dependence are at increased risk for transitioning from POs to heroin/other illegal opioids. This study examines how PDMP adoption and changes in the characteristics of PDMPs over time contribute to changes in fatal heroin poisoning in counties within states from 2002 to 2016. METHODS:Latent transition analysis to classify PDMPs into latent classes (Cooperative, Proactive, and Weak) for each state and year, across three intervals (1999-2004, 2005-2009, 2010-2016). We examined the association between probability of PDMP latent class membership and the rate of county-level heroin poisoning death. RESULTS:After adjustment for potential county-level confounders and co-occurring policy changes, adoption of a PDMP was significantly associated with increased heroin poisoning rates (22% increase by third year post-adoption). Findings varied by PDMP type. From 2010-2016, states with Cooperative PDMPs (those more likely to share data with other states, to require more frequent reporting, and include more drug schedules) had 19% higher heroin poisoning rates than states with Weak PDMPs (adjusted rate ratio [ARR] = 1.19; 95% CI = 1.14, 1.25). States with Proactive PDMPs (those more likely to report outlying prescribing and dispensing and provide broader access to law enforcement) had 6% lower heroin poisoning rates than states with No/Weak PDMPs (ARR = 0.94; 95% CI = 0.90, 0.98). CONCLUSION:There is a consistent, positive association between state PDMP adoption and heroin poisoning mortality. However, this varies by PDMP type, with Proactive PDMPs associated with a small reduction in heroin poisoning deaths. This raises questions about the potential for PDMPs to support efforts to decrease heroin overdose risk, particularly by using proactive alerts to identify patients in need of treatment for opioid use disorder. Future research on mechanisms explaining the reduction in heroin poisonings after enactment of Proactive PDMPs is merited.

AimsAmid changing marijuana policies in the Southern Cone, we examined relationships between marijuana-related risk factors and marijuana use among adolescents in Argentina, Chile, and Uruguay from 2001 to 2016.MethodsUsing cross-sectional surveys from 8th, 10th, and 12th graders and weighted time-varying effect models, we estimated associations between perceived risk (no/low risk versus moderate/great risk) and perceived availability (easy/very easy versus difficult/very difficult/not able to obtain) of marijuana, and any past-month marijuana use.ResultsIn all countries, marijuana use increased over time and adolescents who perceived no/low risk and easy availability had higher odds of use. In Argentina, the bivariate risk/use association weakened from 2001 (OR = 15.24, 95%CI = 9.63, 24.12) to 2004 [OR = 3.86 (2.72, 5.48)] and strengthened until 2011 [OR = 8.22 (7.56, 10.30)]; the availability/use association strengthened from 2005 [OR = 5.32 (4.05, 6.98)] to 2009 [OR = 20.77 (15.57, 27.70)] and weakened until 2014 [OR = 11.00 (9.11, 13.27)]. In Chile, the risk/use association weakened from 2001 [OR = 7.22 (6.57, 7.95)] to 2015 [OR = 5.58 (4.82, 6.48)]; the availability/use association weakened from 2001 [OR = 5.92 (4.96, 7.06)] to 2015 [OR = 4.10 (3.15, 5.34)]. In Uruguay, the risk/use association weakened from 2003 [OR = 34.22 (22.76, 51.46)] to 2016 [OR = 6.23 (4.96, 7.83)]; the availability/use association weakened from 2005 [OR = 29.13 (13.39, 63.39) to 2007 [OR = 9.42 (3.85, 23.07)], and strengthened until 2016 [OR = 22.68 (12.03, 42.76)].ConclusionsOverall, the association between risk and use weakened in all countries, suggesting risk perceptions became a weaker determinant of marijuana use. Perceived availability remained strongly associated with use and may become an increasingly important driver of use (particularly in Uruguay and Argentina).

BACKGROUND:Prescription drug monitoring program are designed to reduce harms from prescription opioids; however, little is known about what populations benefit the most from these programs. We investigated how the relation between implementation of online prescription drug monitoring programs and rates of hospitalizations related to prescription opioids and heroin overdose changed over time, and varied across county levels of poverty and unemployment, and levels of medical access to opioids. METHODS:Ecologic county-level, spatiotemporal study, including 990 counties within 16 states, in 2001-2014. We modeled overdose counts using Bayesian hierarchical Poisson models. We defined medical access to opioids as the county-level rate of hospital discharges for noncancer pain conditions. RESULTS:In 2010-2014, online prescription drug monitoring programs were associated with lower rates of prescription opioid-related hospitalizations (rate ratio 2014 = 0.74; 95% credible interval = 0.69, 0.80). The association between online prescription drug monitoring programs and heroin-related hospitalization was also negative but tended to increase in later years. Counties with lower rates of noncancer pain conditions experienced a lower decrease in prescription opioid overdose and a faster increase in heroin overdoses. No differences were observed across different county levels of poverty and unemployment. CONCLUSIONS:Areas with lower levels of noncancer pain conditions experienced the smallest decrease in prescription opioid overdose and the faster increase in heroin overdose following implementation of online prescription drug monitoring programs. Our results are consistent with the hypothesis that prescription drug monitoring programs are most effective in areas where people are likely to access opioids through medical providers.

BackgroundPrescription opioid overdose (POD) and heroin overdose (HOD) rates have quadrupled since 1999. Community-level socioeconomic characteristics are associated with opioid overdoses, but whether this varies by urbanicity is unknown.MethodsIn this serial cross-sectional study of zip codes in 17 states, 2002-2014 (n = 145,241 space-time units), we used hierarchical Bayesian Poisson space-time models to analyze the association between zip code-level socioeconomic features (poverty, unemployment, educational attainment, and income) and counts of POD or HOD hospital discharges. We tested multiplicative interactions between each socioeconomic feature and zip code urbanicity measured with Rural-Urban Commuting Area codes.ResultsPercent in poverty and of adults with ≤ high school education were associated with higher POD rates (Rate Ratio [RR], 5% poverty: 1.07 [95% credible interval: 1.06-1.07]; 5% low education: 1.02 [1.02-1.03]), while median household income was associated with lower rates (RR, $10,000: 0.88 [0.87-0.89]). Urbanicity modified the association between socioeconomic features and HOD. Poverty and unemployment were associated with increased HOD in metropolitan areas (RR, 5% poverty: 1.12 [1.11-1.13]; 5% unemployment: 1.04 [1.02-1.05]), and median household income was associated with decreased HOD (RR, $10,000: 0.88 [0.87-0.90]). In rural areas, low educational attainment alone was associated with HOD (RR, 5%: 1.09 [1.02-1.16]).ConclusionsRegardless of urbanicity, elevated rates of POD were found in more economically disadvantaged zip codes. Economic disadvantage played a larger role in HOD in urban than rural areas, suggesting rural HOD rates may have alternative drivers. Identifying social determinants of opioid overdoses is particularly important for creating effective population-level interventions.

Background and aimsPrescription drug monitoring programs (PDMP), defined as state-level databases used in the United States that collect prescribing information when controlled substances are dispensed, have varied substantially between states and over time. Little is known about the combinations of PDMP features that, collectively, may produce the greatest impact on prescribing and overdose. We aimed to (1) identify the types of PDMP models that have developed from 1999 to 2016, (2) estimate whether states have transitioned across PDMP models over time and (3) examine whether states have adopted different types of PDMP models in response to the burden of opioid overdose.MethodsA latent transition analysis of PDMP models based on an adaptation of nine PDMP characteristics classified by prescription opioid policy experts as potentially important determinants of prescribing practices and prescription opioid overdose events.ResultsWe divided the time-period into three intervals (1999-2004, 2005-09, 2010-16), and found three distinct PDMP classes in each interval. The classes in the first and second interval can be characterized as 'no/weak', 'proactive' and 'reactive' types of PDMPs, and in the third interval as 'weak', 'cooperative' and 'proactive'. The meaning of these classes changed over time: until 2009, states in the 'no/weak' class had no active PDMP, whereas states in the 'proactive' class were more likely to proactively provide unsolicited information to PDMP users, provide open access to law enforcement, and require more frequent data reporting than states in the 'reactive' class. In 2010-16, the 'weak' class resembled the 'reactive' class in previous intervals. States in the 'cooperative' class in 2010-16 were less likely than states in the 'proactive' class to provide unsolicited reports proactively or to provide open access to law enforcement; however, they were more likely than those in the 'proactive' class to share PDMP data with other states and to report more federal drug schedules.ConclusionsSince 1999, US states have tended to transition to more robust classes of prescription drug monitoring programs. Opioid overdose deaths in prior years predicted the state's prescription drug monitoring program class but did not predict transitions between prescription drug monitoring program classes over time.

BackgroundPrescription drug monitoring programs (PDMPs) are a key component of the president's Prescription Drug Abuse Prevention Plan to prevent opioid overdoses in the United States.PurposeTo examine whether PDMP implementation is associated with changes in nonfatal and fatal overdoses; identify features of programs differentially associated with those outcomes; and investigate any potential unintended consequences of the programs.Data sourcesEligible publications from MEDLINE, Current Contents Connect (Clarivate Analytics), Science Citation Index (Clarivate Analytics), Social Sciences Citation Index (Clarivate Analytics), and ProQuest Dissertations indexed through 27 December 2017 and additional studies from reference lists.Study selectionObservational studies (published in English) from U.S. states that examined an association between PDMP implementation and nonfatal or fatal overdoses.Data extraction2 investigators independently extracted data from and rated the risk of bias (ROB) of studies by using established criteria. Consensus determinations involving all investigators were used to grade strength of evidence for each intervention.Data synthesisOf 2661 records, 17 articles met the inclusion criteria. These articles examined PDMP implementation only (n = 8), program features only (n = 2), PDMP implementation and program features (n = 5), PDMP implementation with mandated provider review combined with pain clinic laws (n = 1), and PDMP robustness (n = 1). Evidence from 3 studies was insufficient to draw conclusions regarding an association between PDMP implementation and nonfatal overdoses. Low-strength evidence from 10 studies suggested a reduction in fatal overdoses with PDMP implementation. Program features associated with a decrease in overdose deaths included mandatory provider review, provider authorization to access PDMP data, frequency of reports, and monitoring of nonscheduled drugs. Three of 6 studies found an increase in heroin overdoses after PDMP implementation.LimitationFew studies, high ROB, and heterogeneous analytic methods and outcome measurement.ConclusionEvidence that PDMP implementation either increases or decreases nonfatal or fatal overdoses is largely insufficient, as is evidence regarding positive associations between specific administrative features and successful programs. Some evidence showed unintended consequences. Research is needed to identify a set of "best practices" and complementary initiatives to address these consequences.Primary funding sourceNational Institute on Drug Abuse and Bureau of Justice Assistance.

Background: Medications for opioid use disorder are associated with a lower risk of drug overdoses at the individual level. However, little is known about whether these effects translate to population-level reductions. We investigated whether county-level efforts to increase access to medication for opioid use disorder in 2012–2014 were associated with opioid overdose deaths in New York State during the first years of the synthetic opioid crisis. Methods: We performed an ecologic county-level study including data from 60 counties (2010–2018). We calculated rates of people receiving medication for opioid use disorder among the population misusing opioids in 2012–2014 and categorized counties into quartiles of this exposure. We modeled synthetic and nonsynthetic opioid overdose death rates using Bayesian hierarchical models. Results: Counties with higher rates of receiving medications for opioid use disorder in 2012-2014 had lower synthetic opioid overdose deaths in 2016 (highest vs. lowest quartile: rate ratio [RR] = 0.33, 95% credible interval [CrI] = 0.12, 0.98; and second-highest vs. lowest: RR = 0.20, 95% CrI = 0.07, 0.59) and 2017 (quartile second-highest vs. lowest: RR = 0.22, 95% CrI = 0.06, 0.83), but not 2018. There were no differences in nonsynthetic opioid overdose death rates comparing higher quartiles versus lowest quartile of exposure. Conclusions: A spatio-temporal modeling approach incorporating counts of the population misusing opioids provided information about trends and interventions in the target population. Higher rates of receiving medications for opioid use disorder in 2012–2014 were associated with lower rates of synthetic opioid overdose deaths early in the crisis. [ABSTRACT FROM AUTHOR]

We examined a natural history of opioid overdose deaths from 1999-2021 in the United States to describe state-level spatio-temporal heterogeneity in the waves of the epidemic. We obtained overdose death counts by state from 1999-2021, categorized as involving prescription opioids, heroin, synthetic opioids, or unspecified drugs. We developed a Bayesian multivariate multiple change point model to flexibly estimate the timing and magnitude of state-specific changes in death rates involving each drug type. We found substantial variability around the timing and severity of each wave across states. The first wave of prescription-involved deaths started between 1999 and 2005, the second wave of heroin-involved deaths started between 2010 and 2014, and the third wave of synthetic opioid-involved deaths started between 2014 and 2021. The severity of the second and third waves was greater in states in the eastern half of the country. Our study highlights state-level variation in the timing and severity of the waves of the opioid epidemic by presenting a 23-year natural history of opioid overdose mortality in the United States. While reinforcing the general notion of three waves, we find that states did not uniformly experience the impacts of each wave. [ABSTRACT FROM AUTHOR]

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El presente artículo analiza las consecuencias que trae para el sistema de salud colombiano el cambio de la variable sexo en el documento de identidad de una persona transgénero, quien puede identificarse legalmente con un sexo, pero conservar la biología de otro. A partir de una investigación de tipo documental y exploratoria, fue posible concluir que para el sistema es importante la identidad biológica de las personas, ya que se utiliza para realizar gestión de riesgo en salud, y se usa para calcular los ingresos en capitación para las entidades promotoras de salud, por lo cual se recomienda tener esta variable en cuenta en el sistema.

Coffee farmers are already experiencing the impacts of climate change, yet recommended resilience strategies are often cost-prohibitive for smallholder producers and/or maladapted to local conditions and contexts. We collaborated with smallholder coffee cooperatives in Latin America to assess the feasibility of climate change resilience strategies they selected: crop diversification; rainwater collection systems; pest monitoring and management; collective coffee seed banks and nurseries; and solar coffee dryers. Data was collected through key actor and cooperative leader semi-structured interviews and focus groups with cooperative members. Our results provide criteria that can be used to determine if these five resilience strategies are appropriate for given environmental, socioeconomic, and political contexts. They also demonstrate the need for tailoring resilience strategies to fit local conditions. The framework we applied serves to select appropriate, effective and equitable resilience strategies, combining a participatory action research approach to incorporate local knowledge, capital assets analysis for a holistic and realistic understanding of feasibility, and access analysis for an assessment of who will benefit and who will not. This framework can be applied to assess the feasibility of climate change resilience strategies with smallholders in a wide variety of geographies, contexts and agroecosystems.

The authors offer a response to the commentary by M. V. Kiang and M. J. Alexander on their study "Motivating better methods--and better data collection--for measuring the prevalence of drug misuse." Topics include the use of bayesian models to generate local prevalence of estimates of opioid misuse using multiple data sources providing indirect information, the importance of highlighting that available data can vary by state, and the need to develop methodology to better use available data.