6 research outputs found

    Outpatient visits for psychiatric disorders in Peru: a nationwide analysis using administrative data

    Get PDF
    Objetivo: Cuantificar la frecuencia de trastornos psiquiátricos en el ámbito ambulatorio en Perú, del 2018 al 2021. Métodos: Estudio observacional transversal utilizando información de la Superintendencia Nacional de Salud del Perú. Los diagnósticos psiquiátricos se identificaron mediante códigos de CIE-10. La frecuencia de trastornos psiquiátricos mayores se describe mediante variables demográficas. También se presentan las tendencias mensuales, así como elnúmero de visitas ambulatorias por cada 10.000 habitantes a nivel subnacional. Resultados: Entre 2018-2021, los trastornos psiquiátricos presentaron 3.142.685 visitas ambulatorias (2,3% del total) en el Perú. En todos los grupos de edad laboral, los trastornos de ansiedad y depresión representaron aproximadamente 6 de cada 10 visitas ambulatorias psiquiátricas en mujeres y 4 de cada 10 en hombres. Las tendencias mensuales mostraron dos picos en el número absoluto de visitas ambulatorias psiquiátricas durante el período prepandémico: abril-mayo y septiembre. Las provincias de la sierra tuvieron la frecuencia más baja de visitas ambulatorias por cada 10.000 habitantes. Conclusiones: Los trastornos psiquiátricos representan una pequeña fracción de las consultas ambulatorias en el Perú, con los trastornos de ansiedad y depresivos como los más frecuentes. Estrategias nacionales en relación a pacientes ambulatorios con trastornos psiquiátricos deben considerar diferencias demográficas, tendencias mensuales y el impacto de la pandemia.   COVID-19.Objective: To quantify the frequency of psychiatric disorders in the outpatient setting in Peru, from 2018 to 2021. Methods: Observational cross-sectional study using outpatient morbidity data from Perú’s National Superintendence of Health. Psychiatric diagnoses were identified using ICD-10 codes. The frequency of major psychiatric disorder groups is described by demographic variables. Monthly trends, as well as the number of outpatient visits per 10,000 population at the subnational level, are also presented. Results: Between 2018-2021, psychiatric disorders accounted for 3,142,685 outpatient visits (2.3% of all) in Peru. Across working age groups, anxiety and depressive disorders comprised approximately 6 out of 10 psychiatric outpatient visits in women, and 4 out of 10 in men. Monthly trends showed two peaks in the absolute number of psychiatric outpatient visits during the pre-pandemic period: April-Mayand September. Provinces in the Highlands had the lowest outpatient visits per 10,000 population. Conclusions: Psychiatric disorders represent a small fraction of the outpatient visits in Peru, with anxiety and depressive disordersas the most frequent. National strategies targeting outpatients with psychiatric disorders should consider demographic differences, monthly trends, and the impact of the COVID-19 pandemic

    Process evaluation of complex interventions in non-communicable and neglected tropical diseases in low- and middle-income countries: a scoping review

    Get PDF
    Objectives: The aim of this review is to map out the use of process evaluation (PE) in complex interventions that address non-communicable diseases (NCDs) and neglected tropical diseases (NTDs) to identify gaps in the design and conduct, as well as strengths, limitations and implications, of this type of research in low- and middle-income countries (LMICs). Design: Scoping review of PE studies of complex interventions implemented in LMICs. Six databases were searched focused on studies published since 2008. Data sources: Embase, PubMed, EbscoHost, Web of Science (WOS), Virtual Health Library (VHL) Regional Portal and Global Index Medicus: Regional Indexes AIM (AFRO), LILACS (AMRO/PAHO), IMEMR (EMRO), IMSEAR (SEARO), WPRIM (WPRO) Global Index Regional Indexes, MEDLINE, SciELO. Eligibility criteria: Studies conducted in LMICs on PEs of randomised controlled trials (RCTs) and non-RCTs published between January 2008 and January 2020. Other criteria were studies of interventions for people at risk or having physical and mental NCDs, and/or NTDs, and/or their healthcare providers and/or others related to achieve better health for these two disease groups. Studies were excluded if they were not reported in English or Spanish or Portuguese or French, not peer-reviewed articles, not empirical research and not human research. Data extraction and synthesis: Data extracted to be evaluated were: available evidence in the utilisation of PE in the areas of NCDs and NTDs, including frameworks and theories used; methods applied to conduct PEs; and in a subsample, the barriers and facilitators to implement complex interventions identified through the PE. Variables were extracted and categorised. The information was synthesised through quantitative analysis by reporting frequencies and percentages. Qualitative analysis was also performed to understand facilitators and barriers presented in these studies. The implications for PEs, and how the information from the PE was used by researchers or other stakeholders were also assessed in this approach. Results: 303 studies were identified, 79% were for NCDs, 12% used the label ‘PE’, 27% described a theory or framework for the PE, and 42% used mixed methods to analyse their findings. Acceptability, barriers and facilitators to implement the interventions, experiences and perceptions, and feasibility were the outcomes most frequently evaluated as part of the PEs. Barriers and facilitators themes identified were contextual factors, health system factors, human resources, attitudes and policy factors. Conclusions: PEs in NCDs and NTDs are used in LMICs with a wide variety of methods. This review identified many PEs that were not labelled by the authors as such, as well as a limited application of PE-related theories and frameworks, and heterogeneous reporting of this type of study

    Simplified hypertension screening methods across 60 countries: An observational study.

    No full text
    BackgroundSimplified blood pressure (BP) screening approaches have been proposed. However, evidence is limited to a few countries and has not documented the cardiovascular risk amongst missed hypertension cases, limiting the uptake of these simplified approaches. We quantified the proportion of missed, over-diagnosed, and consistently identified hypertension cases and the 10-year cardiovascular risk in these groups.Methods and findingsWe used 60 WHO STEPS surveys (cross-sectional and nationally representative; n = 145,174) conducted in 60 countries in 6 world regions between 2004 and 2019. Nine simplified approaches were compared against the standard (average of the last 2 of 3 BP measurements). The 10-year cardiovascular risk was computed with the 2019 World Health Organization Cardiovascular Risk Charts. We used t tests to compare the cardiovascular risk between the missed and over-diagnosed cases and the consistent hypertension cases. We used Poisson multilevel regressions to identify risk factors for missed cases (adjusted for age, sex, body mass index, and 10-year cardiovascular risk). Across all countries, compared to the standard approach, the simplified approach that missed the fewest cases was using the second BP reading if the first BP reading was 130-145/80-95 mm Hg (5.62%); using only the second BP reading missed 5.82%. The simplified approach with the smallest over-diagnosis proportion was using the second BP reading if the first BP measurement was ≥140/90 mm Hg (3.03%). In many countries, cardiovascular risk was not significantly different between the missed and consistent hypertension groups, yet the mean was slightly lower amongst missed cases. Cardiovascular risk was positively associated with missed hypertension depending on the simplified approach. The main limitation of the work is the cross-sectional design.ConclusionsSimplified BP screening approaches seem to have low misdiagnosis rates, and cardiovascular risk could be lower amongst missed cases than amongst consistent hypertension cases. Simplified BP screening approaches could be included in large screening programmes and busy clinics

    Development, validation, and application of a machine learning model to estimate salt consumption in 54 countries

    Get PDF
    Global targets to reduce salt intake have been proposed, but their monitoring is challenged by the lack of population-based data on salt consumption. We developed a machine learning (ML) model to predict salt consumption at the population level based on simple predictors and applied this model to national surveys in 54 countries. We used 21 surveys with spot urine samples for the ML model derivation and validation; we developed a supervised ML regression model based on sex, age, weight, height, and systolic and diastolic blood pressure. We applied the ML model to 54 new surveys to quantify the mean salt consumption in the population. The pooled dataset in which we developed the ML model included 49,776 people. Overall, there were no substantial differences between the observed and ML-predicted mean salt intake (p<0.001). The pooled dataset where we applied the ML model included 166,677 people; the predicted mean salt consumption ranged from 6.8 g/day (95% CI: 6.8–6.8 g/day) in Eritrea to 10.0 g/day (95% CI: 9.9–10.0 g/day) in American Samoa. The countries with the highest predicted mean salt intake were in the Western Pacific. The lowest predicted intake was found in Africa. The country-specific predicted mean salt intake was within reasonable difference from the best available evidence. An ML model based on readily available predictors estimated daily salt consumption with good accuracy. This model could be used to predict mean salt consumption in the general population where urine samples are not available

    Vulnerable newborn phenotypes in Peru:a population-based study of 3,841,531 births at national and subnational levels from 2012 to 2021

    Get PDF
    Background: We aimed to examine the national and subnational prevalence of vulnerable newborn phenotypes in Peru, 2012–2021. Methods: Newborn phenotypes were defined using gestational age (preterm [PT], term [T]), birthweight for gestational age using INTERGROWTH-21st standards (small for gestational age [SGA], appropriate for gestational age [AGA] or large for gestational age [LGA]), and birthweight (low birthweight [LBW], non-LBW) using the Peruvian National Birth Registry as six (by excluding birthweight) and ten newborn phenotypes (using all three outcomes). Small phenotypes (with at least one classification of PT, SGA, or LBW) were further considered. Using individual-level data, we stratified the phenotypes by maternal educational level, maternal age, healthcare insurance, altitude of residence, and geographic region (Coast, Andes, and Amazon). Findings: The prevalence of the five vulnerable newborn phenotypes for the study period was LGA+T (15.2%), AGA+PT (5.2%), SGA+T (4.6%), LGA+PT (0.8%), and SGA+PT (0.7%). The Coast had a higher prevalence of newborns with large phenotypes (19.4%) and the Highlands a higher prevalence of newborns with small phenotypes (12.5%). Mothers with poor socioeconomic status, extreme ages and living at high altitude had a higher prevalence of newborns with small phenotypes, and mothers who were wealthier, more educated, and older had a higher prevalence of infants with large phenotypes. Interpretation: Our findings cautiously suggest that socioeconomic and geographic disparities may play a crucial role in shaping vulnerable newborn phenotypes at national and subnational level in Peru. Further studies using longitudinal data are needed to corroborate our findings and to identify individual-level risk factors.</p
    corecore