Utilization Patterns Research Articles

Antibiotic utilization patterns in Tanzania: a retrospective longitudinal study comparing pre- and intra-COVID-19 pandemic era using Tanzania Medicines and Medical Devices Authority data.

Antimicrobial resistance (AMR) is a growing public health concern globally, and misuse of antibiotics is a major contributor. This study investigated antibiotic utilization patterns before and during the COVID-19 pandemic in Tanzania using data from the Tanzania Medicines and Medical Devices Authority (TMDA). This retrospective longitudinal study analysed secondary data. The study compared antibiotics consumption in defined daily doses per 1000 inhabitants per day (DID) in two distinct eras: 2018-2019 as the pre-COVID-19 era and 2020-2021 as the intra-COVID-19 era. A sample t-test was conducted using Statistical Package for the Social Sciences. The study analysed 10 614 records and found an overall increase in antibiotics consumption from 2018 to 2021. We found that the consumption was 61.24 DID in the intra-COVID-19 era and 50.32 DID in the pre-COVID-19 era. Levofloxacin had the highest percentage increase in use, with a 700% increase in DID during the intra-COVID-19 era. Azithromycin had a 163.79% increase, while cefotaxime had a 600% increase. By contrast, some antibiotics exhibited a decrease in usage during the intra-COVID-19 era, such as nalidixic acid, which had a 100% decrease, and cefpodoxime, which had a 66.67% decrease. Increased antibiotic consumption during the COVID-19 pandemic highlights the importance of implementing effective antimicrobial stewardship strategies to prevent AMR, especially during pandemics.

Soil organic carbon pool in diverse land utilization patterns in North-East India: an implication for carbon sequestration

Soil organic carbon pool in diverse land utilization patterns in North-East India: an implication for carbon sequestration

F.6 Opportunities for improvement: understanding drivers of emergency department visits within 90 days of posterior spinal decompression surgery

Background: Canadian Emergency Departments (EDs) are overburdened. Understanding the drivers for postoperative patients to attend the ED allows for targeted interventions thereby reducing demand. We sought to identify “bounce back” patterns for subsequent QI initiatives. Methods: From April 1, 2016 to March 31, 2022, all provincial ED datasets (EDIS, STAR, Meditech) identified patients presenting within 90 days post-spine surgery. Using Canadian Classification of Health Interventions codes, laminectomies (1SC80) and discectomies (1SE87) demonstrated the highest ED visit rates. Comprehensive chart reviews were conducted identifying surgical and medical reasons for presentation within this timeframe. Results: Reviewing a cohort of 2165 post-decompression patients, 42.1% presented to the ED (n=912) with 62.8% of these directly related to surgery. Primary reasons included wound care (31.6%), pain management (31.6%), and bladder issues (retention or UTI, 11.0%). Simple wound evaluation constituted 49.7% of wound-related visits, with surgical site infection 37.6% and dehiscence 6.6% accounting for the remainder. Pain-related presentations resulted in 72.3% discharge with additional medications, and 27.7% necessitating hospital admission. New or worsening neurologic deficits were reported in 8.9% of ED visits. Conclusions: These findings illuminate crucial aspects of postoperative care and ED utilization patterns. Prioritizing patient education, pain management, and wound care could help alleviate the national ED crisis.

Understanding health service utilisation patterns for care home residents during the COVID-19 pandemic using routinely collected healthcare data

BackgroundHealthcare in care homes during the COVID-19 pandemic required a balance, providing treatment while minimising exposure risk. Policy for how residents should receive care changed rapidly throughout the pandemic. A lack of accessible data on care home residents over this time meant policy decisions were difficult to make and verify. This study investigates common patterns of healthcare utilisation for care home residents in relation to COVID-19 testing events, and associations between utilisation patterns and resident characteristics.MethodsDatasets from County Durham and Darlington NHS Foundation Trust including secondary care, community care and a care home telehealth app are linked by NHS number used to define daily healthcare utilisation sequences for care home residents. We derive four 10-day sets of sequences related to Pillar 1 COVID-19 testing; before [1] and after [2] a resident’s first positive test and before [3] and after [4] a resident’s first test. These sequences are clustered, grouping residents with similar healthcare patterns in each set. Association of individual characteristics (e.g. health conditions such as diabetes and dementia) with healthcare patterns are investigated.ResultsWe demonstrate how routinely collected health data can be used to produce longitudinal descriptions of patient care. Clustered sequences [1,2,3,4] are produced for 3,471 care home residents tested between 01/03/2020–01/09/2021. Clusters characterised by higher levels of utilisation were significantly associated with higher prevalence of diabetes. Dementia is associated with higher levels of care after a testing event and appears to be correlated with a hospital discharge after a first test. Residents discharged from inpatient care within 10 days of their first test had the same mortality rate as those who stayed in hospital.ConclusionWe provide longitudinal, resident-level data on care home resident healthcare during the COVID-19 pandemic. We find that vulnerable residents were associated with higher levels of healthcare usage despite the additional risks. Implications of findings are limited by the challenges of routinely collected data. However, this study demonstrates the potential for further research into healthcare pathways using linked, routinely collected datasets.

Healthcare Resource Utilization, Costs, Clinical Events, and Treatment Patterns in Extreme High-Risk Patients for Cardiovascular Events Undergoing Lipoprotein Apheresis: A German Claims Data Analysis

Abstract Aim Insights into treatment patterns, clinical and economic burden of patients undergoing Lipoprotein apheresis (LA). 3 cohorts were characterized: newly treated [Cohort A], experienced [B], matched cohort [C, high CV risk without LA]. Method Clinical burden was assessed by cardiovascular-related hospitalizations and procedures. Economic and clinical outcomes were described over a 12-month baseline period up to 3 years after LA initiation. Results Absolute LA cases decreased from 1.7 to 1.1 per 100,000 patients. In Cohort A, rate of major cardiovascular hospitalizations decreased, while annual healthcare expenditure increased. Cohort B had significantly higher costs than C. Conclusion LA may be associated with a reduced frequency of myocardial infarction-related hospitalizations. However, it is expensive. Alternatives are needed to reduce its high economic burden.

Variations in healthcare utilization for mental health problems prior to suicide by socioeconomic status: a Norwegian register-based population study

BackgroundSuicide poses a major public health challenge, claiming around 650 lives annually in Norway. There is limited understanding of mental healthcare utilization patterns preceding suicide, particularly relating to socioeconomic status (SES). This study analyzes mental health service use among Norwegian citizens aged 20–64 from 2009 to 2021, emphasizing disparities related to SES.MethodsThis is a population-wide registry-based study. We include mental health consultations with both primary and specialist healthcare services, and investigate patterns of service use regarding educational attainment, employment status and income and compare this to the population in general. All suicides in the period (N = 4731) are included in the study. The aim is to investigate potential discrepancies in service use the year and month preceding suicide, seeking to enhance targeted preventive interventions.ResultsOur results show significant variations in healthcare use for mental health problems the last year preceding suicide, according to the components of SES, for both men and women. Those with higher education utilize the mental healthcare services prior to suicide to a higher degree than men and women with high school education or less, whereas employed men and men with high income level have significantly lower mental healthcare usage prior to suicide both the last year and month compared to the non-employed men and men with low-income level. Employed women also had a lower mental healthcare usage, whereas the results regarding income are not significant for women.ConclusionMental healthcare use prior to suicide varies across the SES components. Notably, the SES groups exhibit heterogeneity, with gendered patterns. Targeted interventions for low consultation rates among employed men, and men with high income and lower education are needed, while women, and men in at-risk groups, such as the non-employed and those with low income, demonstrate higher mental healthcare utilization, warranting comprehensive suicide prevention measures.

Using Activity Measures and GNSS Data from a Virtual Fencing System to Assess Habitat Preference and Habitat Utilisation Patterns in Cattle.

There has been an increased focus on new technologies to monitor habitat use and behaviour of cattle to develop a more sustainable livestock grazing system without compromising animal welfare. One of the currently used methods for monitoring cattle behaviour is tri-axial accelerometer data from systems such as virtual fencing technology or bespoke monitoring technology. Collection and transmission of high-frequency accelerometer and GNSS data is a major energy cost, and quickly drains the battery in contemporary virtual fencing systems, making it unsuitable for long-term monitoring. In this paper, we explore the possibility of determining habitat preference and habitat utilisation patterns in cattle using low-frequency activity and location data. We achieve this by (1) calculating habitat selection ratios, (2) determining daily activity patterns, and (3) based on those, inferring grazing and resting sites in a group of cattle wearing virtual fencing collars in a coastal setting with grey, wooded, and decalcified dunes, humid dune slacks, and salt meadows. We found that GNSS data, and a measure of activity, combined with accurate mapping of habitats can be an effective tool in assessing habitat preference. The animals preferred salt meadows over the other habitats, with wooded dunes and humid dune slacks being the least preferred. We were able to identify daily patterns in activity. By comparing general trends in activity levels to the existing literature, and using a Gaussian mixture model, it was possible to infer resting and grazing behaviour in the different habitats. According to our inference of behaviour the herd predominantly used the salt meadows for resting and ruminating. The approach used in this study allowed us to use GNSS location data and activity data and combine it with accurate habitat mapping to assess habitat preference and habitat utilisation patterns, which can be an important tool for guiding management decisions.

Proactive Resource Allocation for Cloud Manufacturing: A Dynamic Approach with DNN-Based Hybrid Many Objective Leopard Seal Algorithm

In the domain of cloud manufacturing, diverse services and the escalating demand for efficient and cost-effective service composition selection in cloud manufacturing have spurred day by day. Traditional methods face several challenges such as the risk of convergence issues and suboptimal solutions, high dimensionality of decision space, increased computational complexity, and scalability issues. To overcome these complexities, this paper proposed a novel method named the Deep Neural Network (DNN) based Hybrid Many Objective Leopard Seal (HMOLS) algorithm. In this study, DNN is employed to predict future Quality of Service (QoS) for each service based on historical data and integrated features. These predictions are fed back into the optimization model, influencing the dynamic weight calculation for each objective function. In this work, the Leopard Seal Optimization is implemented for hyperparameter optimization to enhance the performance of the HMOLS algorithm. Various evaluation metrics namely accuracy, throughput, reliability, resource utilization, and scalability are utilized to evaluate the performance of the HMOLS method and compare its performance with existing methods. The experimental outcomes depict the effectiveness of the HMOLS approach for the effective selection of services and fusion for cloud manufacturing. DNN-based predictions utilize deep neural networks to predict resource demand or utilization patterns and enable more accurate allocation decisions. These predictions optimize resource allocation by reallocating resources accordingly and address the challenges of resource utilization. Meanwhile, this method is required to overcome the computational overhead for applicability in cloud manufacturing.

Sociodemographic Characteristics and Clinical Profile of Inpatients in the Psychiatry Unit of a Tertiary Care Hospital in Assam: A Retrospective Study

Objectives Recent years have seen a significant evolution in the understanding pertaining to mental health issues. The analysis of the intricate interplay between an individual’s sociodemographic factors, genetic makeup, the environment, and clinical profile (diagnosis and treatment) of patients will help us understand the prevalence and types of mental health disorders prevalent in Assam, which is a culturally, ethnically and socially diverse state. The pattern of utilization of electroconvulsive therapy has also been analyzed. The aims and objectives of the study is to analyze the sociodemographic characteristics and clinical profile of patients admitted in Psychiatry ward, Assam Medical College and Hospital. Material and Methods An analysis on the case records of all individuals admitted to the hospital’s Psychiatry ward between August 1, 2022 and July 31, 2023 was done. Data on socio-demographic details such as age, gender, domicile and clinical profile (diagnosis, mode of discharge, duration of stay and treatment) was compiled using semi-structured format designed by authors. Information regarding patients undergoing electroconvulsive therapy was also gathered from the records. Statistical analysis: The data were subjected to analysis utilizing the Statistical Package for Social Sciences (IBM SPSS Statistics for Windows, version 25.0). Results A total of 680 patients got admitted of which higher proportion constituted of male (77.58%) and majority individuals were aged between 30 and 39 years (29.65%). The predominant diagnosis among the inpatients was substance use disorders (39.09%). Out of all the psychotropic drugs, olanzapine (17.94%) was mostly prescribed on discharged followed by risperidone (10.15%). Escitalopram (3.97%) was the mostly prescribed antidepressant on discharge. Patients diagnosed as substance use disorders were mostly discharged on lorazepam (5%), baclofen (14.26%) and received an average number of 1.8 sessions of Motivational Enhancement Therapy (MET). Whereas, schizophrenia and related disorders was the most common diagnosis among inpatients receiving ECT (51.52%). Conclusion Our study helped to understand the socio-demographic attributes and clinical profile of the inpatients to foster better management approaches.

Emergency medical services in Armenia: national call trends and future directions.

Emergency medical services (EMS) are paramount to boosting health indices in lower-middle income countries (LMICs); however, lack of uniform data collection and analysis hinders system improvement efforts. In the present study, we describe patterns of EMS utilization in the Republic of Armenia and provide key insight into the quality of digital data collection methods. For calls logged in the capital city, Yerevan, the majority had at least one missing field. The predominant complaint was high blood pressure among adults (34.4%) and fever among pediatrics (65.9%). A majority of patients were female (57.6%), adults (90.2%), and not transported to a hospital (85.0%). In the rural provinces, the data was largely intact. The predominant complaints were unspecified acute condition (27.4%) and high blood pressure (26.2%) among adults, and fever (43.9%) and unspecified acute condition (22.1%) among pediatrics. A majority of patients were female (57.1%), adults (94.2%), and not transported to a hospital (78.9%). Our study reveals that the majority of calls to the EMS system are for concerns not needing in-hospital treatment and for acute exacerbation of chronic conditions. Our study also provides a critical foundation for the improvement of EMS systems in Armenia and in other nations in transition. The Locator software has the potential to be a valuable tool to the MoH if it is improved for surveillance purposes, and future synchronization of digital systems would provide easy access to critical information on population health needs and the effectiveness of public health interventions.

Local Variation in Feeding Ground Utilization of Dugongs (Dugong dugon) Across Two Intertidal Seagrass Beds in Talibong Island, Thailand

In this study, we describe the population characteristics and residency patterns of dugongs (Dugong dugon) across two intertidal seagrass beds in Talibong Island, Thailand: Site A, covering an area of 2.0 × 105 m2, and Site B, covering an area of 2.8 × 105 m2. Transect and individual identification surveys were conducted under clear water conditions using drones: 16 separate days over 11 months at Site A and 10 separate days over 3 months at Site B. Sixty-four individuals were identified from 180 videography sessions. The results confirmed at least two distinct patterns of seagrass habitat utilization among sites located approximately 5 km apart. Site A was characterized by a lower population density, higher year-round site fidelity, occupancy by relatively large individuals, and an absence of feeding aggregations. In contrast, Site B was characterized by a higher population density, lower site fidelity, occupancy by individuals with a wider range of body lengths, and the presence of feeding aggregations. The average population density at Site B was three to five times higher than that at Site A. Site A had a median nearest neighbor distance of 320 m with no significant bias in its distribution, whereas Site B had a median of 20 m with a significant bias. The mean site fidelity index for Site A (0.62 ± 0.08; n = 16) was significantly higher than that for Site B (0.39 ± 0.14; n = 10). Dugongs at Site A might have monopolized this site to some extent, while those at Site B might have benefited from increased opportunities for social interaction provided by aggregations. These findings highlight the importance of fine-scale monitoring of feeding ground utilization by dugongs, taking into consideration individual-specific details such as body lengths and resighting rates for a better understanding of their spatial distribution.

The digital revolution in India: bridging the gap in rural technology adoption

This study investigates the factors that influence the adoption of digital technology in rural areas of India, with a focus on the Digital India Program (DIP). By analyzing the age distribution, education levels, technology adoption rates, and utilization patterns among rural populations, this research provides insights into the effectiveness of the DIP in targeting specific demographics and promoting digital inclusion. Quantitative data were collected from 400 respondents in Kalahandi District in the Odisha state of India. The data collected were analyzed using SPSS. The findings reveal a predominantly young population in rural India, indicating a workforce with significant economic potential and a higher likelihood of embracing digital technologies. Moreover, the study highlights the high levels of education among respondents, indicating a population well-equipped to understand and benefit from digital initiatives. Unexpectedly, the research shows a higher rate of digital technology adoption among female respondents, challenging the perception of gender disparities in technology access. This finding suggests that the DIP has played a vital role in bridging the gender gap and empowering women in rural areas. Additionally, the study uncovers a trend towards mobile-based services over computer-based services, signaling a shift in technology utilization patterns. This emphasizes the need to prioritize mobile technology and improve connectivity in rural areas to ensure wider access to digital platforms.

The Impact of Work Desk Shapes on the Utilisation of an Activity-Based-Working Environment

The design of Activity-Based Working (ABW) environments embraces workers’ continuous mobility enabled by technology and the mindset of seeking work zones that best support the task at hand. This paper focuses on aspects of workspace selection within a facility designed to support ABW, focusing on the overall occupancy dynamics, temporal context, and information capturing less-explored details of the physical environment. This study analyses the active use of a workspace in relation to work desk shapes, rectangular and trapezial. Drawing from a longitudinal dataset spanning 12 months from an ABW facility, capturing the active workstation usage of 964 occupants through individual computer logins, this study employs descriptive statistics to analyse the active use of workspace relative to total work hours over the year. Inferential statistical techniques are utilised to compare active use measurements between and within specific workspace areas, revealing significant differences and highlighting the importance of temporal and spatial contexts in workspace utilisation patterns. The presented results demonstrate both tendencies and statistically significant differences, confirming the relevance of the studied variables in examining workspace utilisation. The results show significant usage variations throughout the day across different zones of the observed workspace, with peak activity between 11:00 and 13:00 h for both work desk shapes. This study’s insights are relevant to improving the utilisation of facilities designed for ABW and contribute to a longstanding interest in designing and arranging workplaces to better fit the people who use them.

A Study on Prescription Pattern of Drugs in Orthopaedics Inpatient Department of Navodaya Medical College Hospital and Research Centre in Raichur

A Study on Prescription Pattern of Drugs in Orthopaedics Inpatient Department of Navodaya Medical College Hospital and Research Centre in Raichur

Implementing Foundry: A cohort study describing the regional and virtual expansion of a youth integrated service in British Columbia, Canada.

Integrated youth services (IYS) have been identified as a national priority in response to the youth mental health and substance use (MHSU) crisis in Canada. In British Columbia (BC), an IYS initiative called Foundry expanded to 11 physical centres and launched a virtual service. The aim of the study was to describe the demographics of Foundry clients and patterns of service utilization during this expansion, along with the impact of the COVID-19 pandemic. Data were analysed for all youth (ages 12-24) accessing both in-person (April 27th, 2018-March 31st, 2021) and virtual (May 1st, 2020-March 31st, 2021) services. Cohorts containing all clients from before (April 27th, 2018-March 16th, 2020) and during (March 17th, 2020-March 31st, 2021) the COVID-19 pandemic were also examined. A total of 23 749 unique youth accessed Foundry during the study period, with 110 145 services provided. Mean client age was 19.54 years (SD = 3.45) and 62% identified as female. Over 60% of youth scored 'high' or 'very high' for distress and 29% had a self-rated mental health of 'poor', with similar percentages seen for all services and virtual services. These ratings stayed consistent before and during the COVID-19 pandemic. Foundry has continued to reach the target age group, with a 65% increase in number of clients during the study period compared with the pilot stage. This study highlights lessons learned and next steps to promote youth-centred data capture practices over time within an integrated youth services context.

Web-based Dashboard on ECMO Utilization in Germany: An Interactive Visualization, Analyses, and Prediction Based on Real-life Data

In Germany, a comprehensive reimbursement policy for extracorporeal membrane oxygenation (ECMO) results in the highest per capita use worldwide, although benefits remain controversial. Public ECMO data is unstructured and poorly accessible to healthcare professionals, researchers, and policymakers. In addition, there are no uniform policies for ECMO allocation which confronts medical personnel with ethical considerations during health crises such as respiratory virus outbreaks.Retrospective information on adult and pediatric ECMO support performed in German hospitals was extracted from publicly available reimbursement data and hospital quality reports and processed to create the web-based ECMO Dashboard built on Open-Source software. Patient-level and hospital-level data were merged resulting in a solid base for ECMO use analysis and ECMO demand forecasting with high spatial granularity at the level of 413 county and city districts in Germany.The ECMO Dashboard (https://www.ecmo-dash.de/), an innovative visual platform, presents the retrospective utilization patterns of ECMO support in Germany. It features interactive maps, comprehensive charts, and tables, providing insights at the hospital, district, and national levels. This tool also highlights the high prevalence of ECMO support in Germany and emphasizes districts with ECMO surplus – where patients from other regions are treated, or deficit – origins from which ECMO patients are transferred to other regions. The dashboard will evolve iteratively to provide stakeholders with vital information for informed and transparent resource allocation and decision-making.Accessible public routine data could support evidence-informed, forward-looking resource management policies, which are urgently needed to increase the quality and prepare the critical care infrastructure for future pandemics.

Uptake and factors associated with HIV self-testing among women in South Africa

Background: Human immunodeficiency virus (HIV) self-testing (ST) is a convenient and discreet practice to know HIV status. It is required to reach the underserved population subgroups. We examined the uptake and factors associated with HIVST among reproductive-aged South African women.Methods: A sample of 8182 women from 2016 South African Demographic and Health Survey data were analysed. Percentage and multivariable logistic regression model were conducted. The significance level was set at p 0.05.Results: Approximately 3.1% of women had HIVST uptake. Respondents with primary education had a 75% reduction in the odds of HIVST, compared with women who had no formal education. Women who are employed were 1.44 times as likely to have HIVST uptake compared to those not employed. Women aged 20–24 years, 25–29 years, 30–34 years, and 40–44 years had about two times higher odds of HIVST, when compared with women aged 15–19 years. Women who read newspaper or magazine less than once a week or at least once a week were 1.90 and 2.25 times as likely to have HIVST uptake, respectively, when compared with those who do not read at all.Conclusion: The prevalence of HIVST uptake was low. HIVST was associated with women’s sociodemographic characteristics. The findings highlight the importance of addressing women’s needs to know their HIV status.Contribution: This study adds to the body of literature in understanding the utilisation patterns of HIVST across women in South Africa.

Patterns of Service Utilization across the Full Continuum of Care: Using Patient Journeys to Assess Disparities in Access to Health Services

Healthcare organizations have a contractual obligation to the public to address population-level inequities to health services access and shed light on them. Various studies have focused on achieving equitable access to healthcare services for vulnerable patients. However, these studies do not provide a nuanced perspective based on the local reality across the full continuum of care. In previous work, graph topology was used to provide visual depictions of the dynamics of patients’ movement across a complex healthcare system. Using patients’ encounters data represented as a graph, this study expands on previous work and proposes a methodology to identify and quantify cohort-specific disparities in accessing healthcare services across the continuum of care. The result has demonstrated that a more nuanced approach to assessing access-to-care disparity is doable using patients’ patterns of service utilization from a longitudinal cross-continuum healthcare dataset. The proposed method can be used as part of a toolkit to support healthcare organizations that wish to structure their services to provide better care to their vulnerable populations based on the local realities. This provides a first step in addressing inequities for vulnerable patients in accessing healthcare services. However, additional steps need to be considered to fully address these inequities.

Foster Care and Health in Medicaid-Enrolled Children Experiencing Parental Opioid Use Disorder

The burden of the US opioid crisis has fallen heavily on children, a vulnerable population increasingly exposed to parental opioid use disorder (POUD) in utero or during childhood. A paucity of studies have investigated foster care involvement among those experiencing parental opioid use during childhood and the associated health and health care outcomes. To examine the health and health care outcomes of children experiencing POUD with and without foster care involvement. This population-based cohort study used nationwide Medicaid claims data from January 1, 2014, to December 31, 2020. Participants included Medicaid-enrolled children experiencing parental opioid use-related disorder during ages 4 to 18 years. Data were analyzed between January 2023 and February 2024. Person-years with (exposed) and without (nonexposed) foster care involvement, identified using Medicaid eligibility, procedure, and diagnostic codes. The main outcomes included physical and mental health conditions, developmental disorders, substance use, and health care utilization. The Pearson χ2 test, the t test, and linear regression were used to compare outcomes in person-years with (exposed) and without (nonexposed) foster care involvement. An event study design was used to examine health care utilization patterns before and after foster care involvement. In a longitudinal sample of 8 939 666 person-years from 1 985 180 Medicaid-enrolled children, 49% of children were females and 51% were males. Their mean (SD) age was 10 (4.2) years. The prevalence of foster care involvement was 3% (276 456 person-years), increasing from 1.5% in 2014 to 4.7% in 2020. Compared with those without foster care involvement (8 663 210 person-years), foster care involvement was associated with a higher prevalence of developmental delays (12% vs 7%), depression (10% vs 4%), trauma and stress (35% vs 7%), and substance use-related disorders (4% vs 1%; P < .001 for all). Foster children had higher rates of health care utilization across a wide array of preventive services, including well-child visits (64% vs 44%) and immunizations (41% vs 31%; P < .001 for all). Health care utilization increased sharply in the first year entering foster care but decreased as children exited care. In this cohort study of Medicaid-enrolled children experiencing parental opioid use-related disorder, foster care involvement increased significantly between 2014 and 2020. Involvement was associated with increased rates of adverse health outcomes and health care utilization. These findings underscore the importance of policies that support children and families affected by opioid use disorder, as well as the systems that serve them.

Association of Patient-Reported Social Needs with Emergency Department Visits and Hospitalizations Among Federally Qualified Health Center Patients.

Health care systems are increasingly screening for unmet social needs. The association between patient-reported social needs and health care utilization is not well understood. To investigate the association between patient-reported social needs, measured by the Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences (PRAPARE), and inpatient and emergency department (ED) utilization. This cohort study analyzed merged 2017-2019 electronic health record (EHR) data across multiple health systems. Adult patients from a federally qualified health center (FQHC) in central North Carolina who completed PRAPARE as part of a primary care visit with behavioral health services. The count of up to 12 unmet social needs, aggregated as 0, 1, 2, or 3 + . Outcomes include the probability of an ED visit and hospitalization 12months after PRAPARE assessment, modeled by logistic regressions controlling for age, sex, race, ethnicity, comorbidity burden, being uninsured, and prior utilization in the past 12months. The study population consisted of 1924 adults (38.7% male, 50.1% Black, 36.3% Hispanic, 55.9% unemployed, 68.2% of patients reported 1 + needs). Those with more needs were younger, more likely to be unemployed, and experienced greater comorbidity burden. 35.3% of patients had ED visit(s) and 36.3% had hospitalization(s) 1year after PRAPARE assessment. In adjusted analysis, having 3 + needs was associated with a percentage point increase in the predicted probability of hospitalization (average marginal effect 0.06, SE 0.03, p < 0.05) compared with having 0 needs. Similarly, having 2 needs (0.07, SE 0.03, p < 0.05) or 3 + needs (0.06, SE 0.03, p < 0.05) was associated with increased probability of ED visits compared to 0 needs. Patient-reported social needs were common and associated with health care utilization patterns. Future research should identify interventions to address unmet social needs to improve health and avoid potentially preventable escalating medical intervention.