Nevin Manimala

Inquiry. 2024 Jan-Dec;61:469580241309903. doi: 10.1177/00469580241309903.

ABSTRACT

This study investigates the relationship between out-of-pocket (OOP) healthcare spending, economic growth, population growth, and government health expenditure as a proportion of general government expenditure using National Health Accounts (NHA) estimates. Out-of-Pocket (OOP) healthcare spending imposes a substantial financial burden on households, especially in developing economies such as India. Understanding the factors that influence OOP payments is crucial for policymakers seeking to enhance healthcare systems and achieve Universal Health Coverage (UHC). High OOP expenditures often lead to impoverishment and inequitable access to healthcare, making it a critical area for reform. Despite the well-known negative economic and social consequences of high OOP spending, there is limited research that thoroughly examines the interplay between key economic variables such as economic growth, population growth, and government healthcare expenditure (GHE) as a proportion of general government expenditure (GGE) in shaping OOP healthcare spending. Furthermore, although the National Health Accounts (NHA) offers comprehensive data across Indian states, few studies have leveraged this data to explore the dynamics of these factors. This study aims to fill this gap by providing empirical insights into how these economic and demographic elements influence OOP healthcare spending in India. The analysis employed fixed and random effects models on data from 19 Indian states spanning the years 2013-14 and 2019-20. Fixed effects models were selected based on the results of the Hausman test, which indicated that these models were more effective for controlling unobserved heterogeneity across states.The results indicate that a 1% increase in Gross State Domestic Product is associated with a 0.5% reduction in OOP payments. No significant relationship was identified between population growth or GHE/GGE ratio and OOP healthcare spending. These results imply that while economic growth can contribute to lowering healthcare costs, other factors, such as public health spending, may not be as effective unless they are more strategically targeted. The study underscores the vital role of economic growth in reducing OOP healthcare spending, especially in states facing significant financial burdens. Policymakers should consider aligning economic growth strategies with healthcare reforms to ensure that the benefits of development lead to reduced OOP expenditures. As the findings also suggest that GHE/GGE does not significantly affect OOP costs, policymakers should enhance the targeting and efficiency of public health expenditures while expanding health insurance coverage, and strengthening primary healthcare systems to mitigate OOP costs.

PMID:39720888 | DOI:10.1177/00469580241309903

Ann Otol Rhinol Laryngol. 2024 Dec 25:34894241308411. doi: 10.1177/00034894241308411. Online ahead of print.

ABSTRACT

BACKGROUND: An endoscopic screening program following successful weaning from prolonged mechanical ventilation maintained through endotracheal tube (ET; prolonged intubation) may be justified to assess the upper (laryngotracheal) airway in children who may not always be symptomatic for intubation-related complications.

OBJECTIVES: To evaluate effects of prolonged intubation in children through endoscopic screening of the laryngotracheal airway.

METHODS: In this cross-sectional pilot project, children (2 months-12 years) successfully extubated following prolonged intubation were selected, irrespective of having symptoms, for a 1-time flexible nasolaryngoscopy at third to sixth month post-extubation (follow-up window). Laryngotracheal airway changes, if present, were noted.

RESULTS: Out of 122 children, 42 developed symptoms of complications. Five of them attended within 3 months post-extubation, the rest were evaluated in the follow-up window. Eighty children aged ≤6 years and 4 children >6 years were intubated with uncuffed ET. Symptoms, when present, included respiratory distress (100%), noisy breathing (~36%), cough (~29%), and dysphagia (~12%). Screening revealed positive findings in 40 out of 42 symptomatic children, and in 8 out of 80 asymptomatic children (χ² = 80.314; after Yate’s correction; significant at P < .0001). The commonest lesion was subglottic stenosis (~54%) and intubation granuloma (~48%). Relationship between the nature of ET (cuffed/uncuffed) and complications of prolonged intubation was statistically significant (χ²46.553; significant at P < .0001).

CONCLUSION: The present study proposes the potential utility of follow-up endoscopic screening of upper (laryngotracheal) airway in children successfully weaned from prolonged intubation. A statistically significant relationship existed between prolonged intubation and upper airway complications that were not always symptomatic.

PMID:39720852 | DOI:10.1177/00034894241308411

Med Decis Making. 2024 Dec 25:272989X241305414. doi: 10.1177/0272989X241305414. Online ahead of print.

ABSTRACT

PURPOSE: Individual-level state-transition microsimulations (iSTMs) have proliferated for economic evaluations in place of cohort state transition models (cSTMs). Probabilistic economic evaluations quantify decision uncertainty and value of information (VOI). Previous studies show that iSTMs provide unbiased estimates of expected incremental net monetary benefits (EINMB), but statistical properties of iSTM-produced estimates of decision uncertainty and VOI remain uncharacterized.

METHODS: We compare iSTM-produced estimates of decision uncertainty and VOI to corresponding cSTMs. For a 2-alternative decision and normally distributed incremental costs and benefits, we derive analytical expressions for the probability of being cost-effective and the expected value of perfect information (EVPI) for cSTMs and iSTMs, accounting for correlations in incremental outcomes at the population and individual levels. We use numerical simulations to illustrate our findings and explore the impact of relaxing normality assumptions or having >2 decision alternatives.

RESULTS: iSTM estimates of decision uncertainty and VOI are biased but asymptotically consistent (i.e., bias approaches 0 as number of microsimulated individuals approaches infinity). Decision uncertainty depends on 1 tail of the INMB distribution (e.g., P[INMB <0]), which depends on estimated variance (larger with iSTMs given first-order noise). While iSTMs overestimate EVPI, their direction of bias for the probability of being cost-effective is ambiguous. Bias is larger when uncertainties in incremental costs and effects are negatively correlated since this increases INMB variance.

CONCLUSIONS: iSTMs are useful for probabilistic economic evaluations. While more samples at the population uncertainty level are interchangeable with more microsimulations for estimating EINMB, minimizing iSTM bias in estimating decision uncertainty and VOI depends on sufficient microsimulations. Analysts should account for this when allocating their computational budgets and, at minimum, characterize such bias in their reported results.

HIGHLIGHTS: Individual-level state-transition microsimulation models (iSTMs) produce biased but consistent estimates of the probability that interventions are cost-effective.iSTMs also produce biased but consistent estimates of the expected value of perfect information.The biases in these decision uncertainty and value-of-information measures are not reduced by more parameter sets being sampled from their population-level uncertainty distribution but rather by more individuals being microsimulated for each parameter set sampled.Analysts using iSTMs to quantify decision uncertainty and value of information should account for these biases when allocating their computational budgets and, at minimum, characterize such bias in their reported results.

PMID:39720850 | DOI:10.1177/0272989X241305414

Clin Trials. 2024 Dec 25:17407745241304331. doi: 10.1177/17407745241304331. Online ahead of print.

ABSTRACT

Unlocking the power of personalised medicine in oncology hinges on the integration of clinical trial data with translational data (i.e. biospecimen-derived molecular information). This combined analysis allows researchers to tailor treatments to a patient’s unique biological makeup. However, current practices within UK Clinical Trials Units present challenges. While clinical data are held in standardised formats, translational data are complex, diverse, and requires specialised storage. This disparity in format creates significant hurdles for researchers aiming to curate, integrate and analyse these datasets effectively. This article proposes a novel solution: an open-source SQL database schema designed specifically for the needs of academic trial units. Inspired by Cancer Research UK’s commitment to open data sharing and exemplified by the Southampton Clinical Trials Unit’s CONFIRM trial (with over 150,000 clinical data points), this schema offers a cost-effective and practical ‘middle ground’ between raw data and expensive Secure Data Environments/Trusted Research Environments. By acting as a central hub for both clinical and translational data, the schema facilitates seamless data sharing and analysis. Researchers gain a holistic view of trials, enabling exploration of connections between clinical observations and the molecular underpinnings of treatment response. Detailed instructions for setting up the database are provided. The open-source nature and straightforward design ensure ease of implementation and affordability, while robust security measures safeguard sensitive data. We further showcase how researchers can leverage popular statistical software like R to directly query the database. This approach fosters collaboration within the academic discovery community, ultimately accelerating progress towards personalised cancer therapies.

PMID:39720844 | DOI:10.1177/17407745241304331

Liver Int. 2025 Jan;45(1):e16226. doi: 10.1111/liv.16226.

ABSTRACT

INTRODUCTION: Racial/ethnic disparities have been previously reported in renal and hepatic disease care; however, acute kidney injury (AKI) in the setting of cirrhosis (hepatorenal syndrome [HRS]-AKI) despite its complexity requiring a multidisciplinary approach, remains understudied.

METHODS: To identify unique associations of clinical and sociodemographic factors with mortality and length of stay (LOS) among patients hospitalised with HRS-AKI, hierarchical regression analysis was conducted, along with a mediation analysis to estimate how race-related differences in in-hospital mortality were influenced by payer type, area household income, and clinical severity.

RESULTS: Black patients demonstrated a significantly higher odds of in-hospital mortality, compared to their white counterparts, adjusting for (1) sex and age, (2) sex, age, payer type, and area household income and (3) sex, age, and clinical severity [OR 1.16-1.20, 95% confidence intervals (CI) > 1]. Higher mortality rates among Black patients were partially mediated by clinical severity and area household income [proportion mediated (PM): _0.1890.19_0.192 and _0.160.17_0.18, respectively]. Black patients with HRS-AKI had longer LOS than White patients. Hispanic patients tended to have lower odds of in-hospital mortality [OR: _0.770.86_0.97] despite their lower income and more severe illness.

CONCLUSION: Our nationwide US study demonstrated that, partly due to higher clinical severity and lower household income, Black patients with HRS-AKI experience higher inpatient mortality, compared to White patients. On the other hand, Hispanics with HRS-AKI have a survival advantage. More awareness is warranted to address racial disparities in HRS-AKI outcomes.

PMID:39720837 | DOI:10.1111/liv.16226

Front Public Health. 2024 Dec 10;12:1394060. doi: 10.3389/fpubh.2024.1394060. eCollection 2024.

ABSTRACT

INTRODUCTION: Low birth weight, defined as a birth weight below 2,500 g, represents a significant public health concern with a multifactorial risk dimension. Socio-demographic factors and individual characteristics of women and their social environment could influence low birth weight. This study aimed to analyze the association between the socio-demographic and reproductive characteristics of women living in low-income households and low birth weight in Serbia, Kosovo, and Montenegro.

METHODS: This study was conducted as secondary data analysis during the Multiple Indicator Cluster Survey – Round 6 in Serbia, Kosovo, and Montenegro. The household questionnaire and the individual questionnaire for women aged 15-49 were used as standard research instruments. We analyzed 1,019 women whose households belonged to the first (poorest) or second (poor) wealth index quintiles and who had given birth to a live child within the 2 years preceding the study. A multivariate logistic regression was applied with low birth weight in newborns as the outcome variable.

RESULTS: The univariate regression analysis showed that women with low birth weight newborns were significantly more likely to live in settlements mainly inhabited by Roma, reside in urban areas, marry or enter a union before age 18, have lower education levels, experience higher illiteracy rates, and receive antenatal care not provided by a medical doctor compared to women whose newborns weighed 2.5 kg or more. A multivariate logistic regression model with a low birth weight of newborns as an outcome variable showed the association between women’s illiteracy (OR: 1.741; 95% CI: 1.060-2.859) and antenatal care not provided by a medical doctor (OR: 2.735; 95% CI: 1.229-6.087).

DISCUSSION: Illiteracy and limited access to medical doctor services during pregnancy were factors that increased the likelihood of low birth weight in newborns born to women living in low-income households in the selected Western Balkans populations. The cross-sectional design of this study does not allow the establishment of causal relationships among variables, but it can provide important evidence for future prevention strategies. Interventions are needed to enhance the education of women and to improve access to antenatal care across Serbia, Kosovo, and Montenegro.

PMID:39720813 | PMC:PMC11666434 | DOI:10.3389/fpubh.2024.1394060

Front Public Health. 2024 Dec 10;12:1387255. doi: 10.3389/fpubh.2024.1387255. eCollection 2024.

ABSTRACT

In the rapid urbanization process in China, due to reasons such as employment, education, and family reunification, the number of mobile population without registered residence in the local area has increased significantly. By 2020, the group had a population of 276 million, accounting for over 20% of the total population, making significant contributions to urban economic development and resource optimization. However, the health status of migrant populations is affected by unique issues such as occupational risks and socio-economic disparities, which play an important role in personal welfare, social stability, and sustainable economic growth. The deterioration of the health of the floating population will lead to a decrease in productivity, an increase in medical expenses, and an increase in pressure on the public health system. In order to analyze and predict the main elements affecting the well-being of transient population, this study uses advanced machine learning algorithms such as principal component analysis, backpropagation (BP) neural networks, community analysis, random forest models, etc. Principal component analysis will identify and extract the most important variables that affect the health status of mobile populations. The BP neural network models the nonlinear interaction between health determinants and health outcomes. Community analysis divides the floating population into different health records and promotes targeted intervention measures. The random forest model improves the accuracy and universality of predictions. The insights generated by these models will help develop health policies and intervention policies to improve the health status of mobile populations, narrow disparities, and promote social and economic stability. Integrating data-driven methods and emphasizing a shift towards correct, effective, and impactful public health management provides a robust framework for understanding and addressing the complex health issues faced by mobile populations.

PMID:39720812 | PMC:PMC11666355 | DOI:10.3389/fpubh.2024.1387255

Front Public Health. 2024 Dec 10;12:1455395. doi: 10.3389/fpubh.2024.1455395. eCollection 2024.

ABSTRACT

OBJECTIVE: Individuals with Limited English Proficiency (LEP), including Spanish-preferred patients, face healthcare challenges due to language barriers. Despite the potential of digital health technologies to improve access and outcomes, there is a “digital divide” with underutilization among vulnerable populations, including Spanish-speaking LEP individuals, highlighting a need for increased understanding and equitable digital health solutions.

MATERIALS AND METHODS: A multi-mode, multi-language cross-sectional survey was built based on the Technology Acceptance Model and deployed from a multi-state healthcare practice. Measures included patient-reported comfort level with reading and speaking English, internet and computer access and satisfaction, ability to perform healthcare-related online tasks, and the eHEALS scale of digital health literacy.

RESULTS: A total of 212 Spanish-preferred patients completed the survey (response rate, 212/2,726 = 7.8%), of which 73.6% indicated lack of comfort in reading or writing in English (LEP n = 156). Spanish-speaking individuals with LEP reported higher rates of needing help when learning how to use new technology or devices, reporting difficulty in the evaluation of health information on the internet and being able to differentiate high-quality information from low-quality online health resources, feeling confident in using health information found online to make health decisions, and having lower access to health-related online services than Spanish-speaking individuals without LEP.

DISCUSSION: Improving equitable accessibility to digital tools for individuals with LEP seeking healthcare can help to improve their engagement with their providers and promote self-efficacy in their care. Opportunities exist with emerging technologies to develop language-concordant healthcare resources that will improve outcomes for Spanish-preferred patients.

PMID:39720810 | PMC:PMC11666482 | DOI:10.3389/fpubh.2024.1455395

Front Public Health. 2024 Dec 10;12:1457921. doi: 10.3389/fpubh.2024.1457921. eCollection 2024.

ABSTRACT

INTRODUCTION: Common prosperity holds significant importance in ensuring social equity, promoting sustainable economic growth, and achieving long-term national security. The management of multidimensional relative poverty is a crucial pathway to realizing the common prosperity of all individuals. It is worthwhile to investigate whether the formal and informal financial involvement of rural households can synergistically alleviate multidimensional relative poverty, ultimately contributing to the realization of common prosperity.

METHODS: Using data from 5,303 farm households in the 2018 China Family Panel Studies, this study employs multiple linear regression, instrumental variable methods, and propensity score matching to empirically analyze the common prosperity effect of formal and informal financial participation from the perspective of multidimensional relative poverty.

RESULTS: The research demonstrates that both formal and informal financial participation can alleviate multidimensional relative poverty, with formal financial participation exhibiting a more pronounced poverty reduction effect compared to informal financial participation. Mechanism analysis reveals that both forms of financial participation mitigate multidimensional relative poverty by facilitating land transfer and non-farm employment. Heterogeneity analysis reveals that formal financial participation yields a more pronounced poverty reduction effect among rural households experiencing lower levels of multidimensional relative poverty, whereas informal financial participation is more effective in reducing poverty among rural households facing higher levels of multidimensional relative poverty.

DISCUSSION: To achieve common prosperity and enhance the precision of financial interventions for poverty alleviation, it is recommended to leverage the strengths of formal finance over informal finance, enhance financial assistance for land transfer and non-farm employment, and implement tailored financial support policies.

PMID:39720809 | PMC:PMC11666490 | DOI:10.3389/fpubh.2024.1457921

Front Public Health. 2024 Dec 10;12:1497745. doi: 10.3389/fpubh.2024.1497745. eCollection 2024.

ABSTRACT

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD), mainly caused by cigarette smoking, is one of the leading causes of death in the United States (US) and frequent asthma attacks are often exacerbated by cigarette use. Electronic cigarettes (e-cigarettes) are often used to quit cigarette smoking. Prevalence of COPD, asthma, cigarette use, and e-cigarette use differs between racial/ethnic groups. The overall objective was to assess the associations between e-cigarette use and COPD and asthma and how race/ethnicity and cigarette smoking modifies these associations.

METHODS: Data were retrieved from the 2016-2018 and 2020-2021 Behavioral Risk Factor Surveillance System datasets, a national annual health survey representing the US general adult population. Frequency and weighted percentages or means and standard deviations were obtained. Rao-Scott Chi-square test, two-sample t tests, and logistic regression were used to evaluate binary associations between current e-cigarette use and lifetime diagnosis of COPD and asthma. Multivariable analyses using logistic regression were conducted to assess associations between variables. Interaction effects between e-cigarette use and race/ethnicity were assessed and stratified analyses were performed as indicated. All multivariate analyses were stratified by cigarette smoking status.

RESULTS: Prevalence of e-cigarette use was 5.1%, COPD was 6.7%, and asthma was 9.2%. Individuals who currently smoked cigarettes among all racial/ethnic groups, excluding non-Hispanic (NH) American Indian/Alaska Native individuals, were more likely to report current asthma if using e-cigarettes compared to non-use (p < 0.05). Among individuals who never smoked, Non-Hispanic White (NHW), NH-Black and Hispanic individuals using e-cigarettes had greater odds of COPD compared to NHW, NH-Black and Hispanic individuals who did not use these products, respectively (p < 0.05). Among NHW, Hispanic, and NH-Other persons who currently used cigarettes, individuals currently using e-cigarettes had greater odds of COPD compared to NHW, Hispanic, and NH-Hispanic individuals who did not use e-cigarettes, respectively (p < 0.05). Among individuals who formerly used cigarettes, current e-cigarette use was associated with COPD and asthma. Among individuals who never used cigarettes, current e-cigarette use was associated with reporting current asthma.

CONCLUSION: The association between e-cigarette use and COPD and asthma was dependent on smoking status and racial/ethnic groups. Further studies should be conducted to explore this association.

PMID:39720808 | PMC:PMC11666483 | DOI:10.3389/fpubh.2024.1497745