Pub Date : 2024-07-05DOI: 10.1101/2024.07.03.24309684
Kevin Dick, Emily Kaczmarek, Robin Ducharme, Alexa C Bowie, Alysha L. J. Dingwall-Harvey, Heather Howley, Steven Hawken, Mark C Walker, Christine M Armour
Background Early diagnosis and access to resources, support and therapy are critical for improving long-term outcomes for children with autism spectrum disorder (ASD). ASD is typically detected using a case-finding approach based on symptoms and family history, resulting in many delayed or missed diagnoses. While population-based screening would be ideal for early identification, available screening tools have limited accuracy. This study aims to determine whether machine learning models applied to health administrative and birth registry data can identify young children (aged 18 months to 5 years) who are at increased likelihood of developing ASD. Methods We assembled the study cohort using individually linked maternal-newborn data from the Better Outcomes Registry and Network (BORN) Ontario database. The cohort included all live births in Ontario, Canada between April 1st, 2006, and March 31st, 2018, linked to datasets from Newborn Screening Ontario (NSO), Prenatal Screening Ontario (PSO), and Canadian Institute for Health Information (CIHI) (Discharge Abstract Database (DAD) and National Ambulatory Care Reporting System (NACRS)). The NSO and PSO datasets provided screening biomarker values and outcomes, while DAD and NACRS contained diagnosis codes and intervention codes for mothers and offspring. Extreme Gradient Boosting models and large-scale ensembled Transformer deep learning models were developed to predict ASD diagnosis between 18 and 60 months of age. Leveraging explainable artificial intelligence methods, we determined the impactful factors that contribute to increased likelihood of ASD at both an individual- and population-level. Results The final study cohort included 703,894 mother-offspring pairs, with 10,964 identified cases of ASD. The best-performing ensemble of Transformer models achieved an area under the receiver operating characteristic curve of 69.6% for predicting ASD diagnosis, a sensitivity of 70.9%, a specificity of 56.9%. We determine that our model can be used to identify an enriched pool of children with the greatest likelihood of developing ASD, demonstrating the feasibility of this approach. Conclusions This study highlights the feasibility of employing machine learning models and routinely collected health data to systematically identify young children at high likelihood of developing ASD. Ensemble transformer models applied to health administrative and birth registry data offer a promising avenue for universal ASD screening. Such early detection enables targeted and formal assessment for timely diagnosis and early access to resources, support, or therapy.
{"title":"Predicting Autism Spectrum Disorder: Transformer-Based Deep Learning Ensemble Framework Using Health Administrative & Birth Registry Data","authors":"Kevin Dick, Emily Kaczmarek, Robin Ducharme, Alexa C Bowie, Alysha L. J. Dingwall-Harvey, Heather Howley, Steven Hawken, Mark C Walker, Christine M Armour","doi":"10.1101/2024.07.03.24309684","DOIUrl":"https://doi.org/10.1101/2024.07.03.24309684","url":null,"abstract":"Background\u0000Early diagnosis and access to resources, support and therapy are critical for improving long-term outcomes for children with autism spectrum disorder (ASD). ASD is typically detected using a case-finding approach based on symptoms and family history, resulting in many delayed or missed diagnoses. While population-based screening would be ideal for early identification, available screening tools have limited accuracy. This study aims to determine whether machine learning models applied to health administrative and birth registry data can identify young children (aged 18 months to 5 years) who are at increased likelihood of developing ASD. Methods\u0000We assembled the study cohort using individually linked maternal-newborn data from the Better Outcomes Registry and Network (BORN) Ontario database. The cohort included all live births in Ontario, Canada between April 1st, 2006, and March 31st, 2018, linked to datasets from Newborn Screening Ontario (NSO), Prenatal Screening Ontario (PSO), and Canadian Institute for Health Information (CIHI) (Discharge Abstract Database (DAD) and National Ambulatory Care Reporting System (NACRS)). The NSO and PSO datasets provided screening biomarker values and outcomes, while DAD and NACRS contained diagnosis codes and intervention codes for mothers and offspring. Extreme Gradient Boosting models and large-scale ensembled Transformer deep learning models were developed to predict ASD diagnosis between 18 and 60 months of age. Leveraging explainable artificial intelligence methods, we determined the impactful factors that contribute to increased likelihood of ASD at both an individual- and population-level. Results\u0000The final study cohort included 703,894 mother-offspring pairs, with 10,964 identified cases of ASD. The best-performing ensemble of Transformer models achieved an area under the receiver operating characteristic curve of 69.6% for predicting ASD diagnosis, a sensitivity of 70.9%, a specificity of 56.9%. We determine that our model can be used to identify an enriched pool of children with the greatest likelihood of developing ASD, demonstrating the feasibility of this approach. Conclusions\u0000This study highlights the feasibility of employing machine learning models and routinely collected health data to systematically identify young children at high likelihood of developing ASD. Ensemble transformer models applied to health administrative and birth registry data offer a promising avenue for universal ASD screening. Such early detection enables targeted and formal assessment for timely diagnosis and early access to resources, support, or therapy.","PeriodicalId":501556,"journal":{"name":"medRxiv - Health Systems and Quality Improvement","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141575526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-03DOI: 10.1101/2024.06.27.24309570
Richard Villar, Abdalkarim Alsalqawi
This study describes the patterns of injury observed in a Gaza war hospital, focusing on 110 consecutive patients. Of these, two had conditions unrelated to trauma, so the analysis was of the remaining 108 casualties. No military personnel were seen. The data reveal clear trends, including a high prevalence of explosive injuries (86.36%), a low prevalence of gunshot wounds (8.18%), a notable proportion of female (34.55%) and child (23.64%) casualties, and the occurrence of multiple injuries (1.73 injuries/patient) because of the use of high explosive. There were 187 injuries identified including 128 fractures. Of these fractures, 64.84% were of the lower limb and 28.91% of the upper limb. Of the 128 fractures, 79 (61.72%) were clinically and/or radiologically infected. The most frequently infected fracture was the compound tibial and fibular fracture, which showed an infection rate of 92.86%. These findings highlight the unique and tragic nature of the Gaza conflict, the increasing injuries to civilians, including women and children, and the long-term healthcare that will be needed.
{"title":"Patterns of Injury in a Gaza War Hospital","authors":"Richard Villar, Abdalkarim Alsalqawi","doi":"10.1101/2024.06.27.24309570","DOIUrl":"https://doi.org/10.1101/2024.06.27.24309570","url":null,"abstract":"This study describes the patterns of injury observed in a Gaza war hospital, focusing on 110 consecutive patients. Of these, two had conditions unrelated to trauma, so the analysis was of the remaining 108 casualties. No military personnel were seen. The data reveal clear trends, including a high prevalence of explosive injuries (86.36%), a low prevalence of gunshot wounds (8.18%), a notable proportion of female (34.55%) and child (23.64%) casualties, and the occurrence of multiple injuries (1.73 injuries/patient) because of the use of high explosive. There were 187 injuries identified including 128 fractures. Of these fractures, 64.84% were of the lower limb and 28.91% of the upper limb. Of the 128 fractures, 79 (61.72%) were clinically and/or radiologically infected. The most frequently infected fracture was the compound tibial and fibular fracture, which showed an infection rate of 92.86%. These findings highlight the unique and tragic nature of the Gaza conflict, the increasing injuries to civilians, including women and children, and the long-term healthcare that will be needed.","PeriodicalId":501556,"journal":{"name":"medRxiv - Health Systems and Quality Improvement","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141547756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-02DOI: 10.1101/2024.07.01.24309757
Calandra Feather, Nicholas Appelbaum, Jonathan Clarke, Ara Darzi, Bryony Dean Franklin
Background Medication errors are the leading cause of preventable harm in healthcare. Despite proliferation of medication-related clinical decision support systems (CDSS), current systems have limitations. We therefore developed an indication-based prescribing tool. This performs dose calculations using an underlying formulary and provides patient-specific dosing recommendations. Objectives were to compare the incidence and types of erroneous medication orders, time to prescribe (TTP), and perceived workload using the NASA task load index (TLX), in simulated prescribing tasks with and without this intervention. We also sought to identify workflow steps most vulnerable to error and gain participant feedback. Methods A simulated, randomised, cross-over exploratory study was conducted at a London NHS Trust. Participants completed five simulated prescribing tasks with, and five without, the intervention. Data collection methods comprised direct observation of prescribing tasks, self-reported task load and semi-structured interviews. A concurrent triangulation design combined quantitative and qualitative data. Results 24 participants completed a total of 240 medication orders. The intervention was associated with fewer prescribing errors (6.6% of 120 medications) compared to standard practice (28.3%; relative risk reduction 76.5% p < 0.01), a shorter TTP and lower overall NASA TLX scores (p < 0.01). Control arm workflow vulnerabilities included failures in identifying correct doses, applying maximum dose limits, and calculating patient-specific dosages. Intervention arm errors primarily stemmed from misidentifying patient-specific information from the medication scenario. Thematic analysis of participant interviews identified six themes: Navigating trust and familiarity, addressing challenges and suggestions for improvement, integration of local guidelines and existing CDSS, intervention endorsement, search by indication and targeting specific patient and staff groups. Conclusion The intervention represents a promising advancement in medication safety, with implications for enhancing patient safety and efficiency. Further real-world evaluation and development of the system to meet the needs of more diverse patient groups, users and healthcare settings is now required.
背景用药错误是医疗保健领域可预防伤害的主要原因。尽管与用药相关的临床决策支持系统（CDSS）不断涌现，但目前的系统仍存在局限性。因此，我们开发了一种基于适应症的处方工具。该工具使用基础处方集进行剂量计算，并提供针对患者的剂量建议。我们的目标是比较错误处方的发生率和类型、处方时间 (TTP) 以及使用 NASA 任务负荷指数 (TLX) 在有和没有该干预措施的模拟处方任务中感知到的工作量。我们还试图找出最容易出错的工作流程步骤，并获得参与者的反馈意见。方法 在伦敦一家 NHS 信托公司进行了一项模拟、随机、交叉探索性研究。参与者分别完成了五次有干预措施和五次无干预措施的模拟处方任务。数据收集方法包括直接观察处方任务、自我报告任务负荷和半结构化访谈。同时进行的三角测量设计结合了定量和定性数据。结果 24 名参与者共完成了 240 份处方。与标准实践（28.3%；相对风险降低 76.5% p < 0.01）相比，干预措施减少了处方错误（120 种药物中的 6.6%），缩短了 TTP，降低了 NASA TLX 总分（p < 0.01）。对照组工作流程的漏洞包括未能识别正确剂量、应用最大剂量限制和计算患者特定剂量。干预组的错误主要源于错误识别用药情景中的患者特定信息。对参与者访谈的主题分析确定了六个主题：信任和熟悉度导航、应对挑战和改进建议、整合当地指南和现有 CDSS、干预认可、按适应症搜索以及针对特定患者和员工群体。结论：该干预措施是用药安全领域的一项有希望的进步，对提高患者安全和效率具有重要意义。现在需要对该系统进行进一步的实际评估和开发，以满足更多不同患者群体、用户和医疗机构的需求。
{"title":"Comparing safety, performance and user perceptions of a patient-specific indication-based prescribing tool with current practice: A mixed-methods randomised user testing study","authors":"Calandra Feather, Nicholas Appelbaum, Jonathan Clarke, Ara Darzi, Bryony Dean Franklin","doi":"10.1101/2024.07.01.24309757","DOIUrl":"https://doi.org/10.1101/2024.07.01.24309757","url":null,"abstract":"Background\u0000Medication errors are the leading cause of preventable harm in healthcare. Despite proliferation of medication-related clinical decision support systems (CDSS), current systems have limitations. We therefore developed an indication-based prescribing tool. This performs dose calculations using an underlying formulary and provides patient-specific dosing recommendations. Objectives were to compare the incidence and types of erroneous medication orders, time to prescribe (TTP), and perceived workload using the NASA task load index (TLX), in simulated prescribing tasks with and without this intervention. We also sought to identify workflow steps most vulnerable to error and gain participant feedback. Methods\u0000A simulated, randomised, cross-over exploratory study was conducted at a London NHS Trust. Participants completed five simulated prescribing tasks with, and five without, the intervention. Data collection methods comprised direct observation of prescribing tasks, self-reported task load and semi-structured interviews. A concurrent triangulation design combined quantitative and qualitative data. Results\u000024 participants completed a total of 240 medication orders. The intervention was associated with fewer prescribing errors (6.6% of 120 medications) compared to standard practice (28.3%; relative risk reduction 76.5% p < 0.01), a shorter TTP and lower overall NASA TLX scores (p < 0.01). Control arm workflow vulnerabilities included failures in identifying correct doses, applying maximum dose limits, and calculating patient-specific dosages. Intervention arm errors primarily stemmed from misidentifying patient-specific information from the medication scenario. Thematic analysis of participant interviews identified six themes: Navigating trust and familiarity, addressing challenges and suggestions for improvement, integration of local guidelines and existing CDSS, intervention endorsement, search by indication and targeting specific patient and staff groups. Conclusion\u0000The intervention represents a promising advancement in medication safety, with implications for enhancing patient safety and efficiency. Further real-world evaluation and development of the system to meet the needs of more diverse patient groups, users and healthcare settings is now required.","PeriodicalId":501556,"journal":{"name":"medRxiv - Health Systems and Quality Improvement","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141525536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1101/2024.06.29.24309705
Zahra Rahemi, Juanita-Dawne R. Bacsu, Sophia Z. Shalhout, Maryam S. Sadafipoor, Matthew Lee Smith, Swann Arp Adams
Abstract Background. The purpose was to investigate the impact of sociodemographic factors on healthcare utilization among adults with different cognition levels (normal and impairment/dementia). Methods. We used cross-sectional data from the Health and Retirement Study (N=17,698) to assess healthcare utilization: hospital stay, nursing home stay, hospice care, and doctor visits. Results. A cohort comparison between normal and dementia/impaired cognition groups revealed significant differences. The dementia/impaired group had lower education levels, higher single/widowed status, and more racial and ethnic minorities. They experienced longer hospital and nursing home stays, varied doctor visit frequencies, and had higher mean age, greater loneliness scores, and lower family social support scores. Differences in hospitalization, nursing home, hospice care, and doctor visits were influenced by factors such as race, age, marital status, education, and rurality. Conclusion. There were disparities in healthcare utilization based on participants characteristics and cognition levels, especially in terms of race/ethnicity, education, and rural location.
摘要背景。目的是调查社会人口因素对不同认知水平（正常和受损/痴呆）的成年人使用医疗服务的影响。我们利用健康与退休研究（Health and Retirement Study，N=17,698）的横截面数据评估了医疗保健利用情况：住院、入住疗养院、临终关怀和就医。认知能力正常组与痴呆/认知能力受损组的队列比较显示出显著差异。痴呆症/认知功能受损组的受教育程度较低，单身/丧偶比例较高，少数种族和少数民族较多。他们住院和住疗养院的时间更长，看医生的频率不同，平均年龄更高，孤独感得分更高，家庭社会支持得分更低。住院、疗养院、临终关怀和就医方面的差异受到种族、年龄、婚姻状况、教育程度和居住地等因素的影响。根据参与者的特征和认知水平，尤其是种族/民族、教育程度和农村地区，在医疗保健利用方面存在差异。
{"title":"Healthcare Disparities Among Older Adults: Exploring Social Determinants of Health and Cognition Levels","authors":"Zahra Rahemi, Juanita-Dawne R. Bacsu, Sophia Z. Shalhout, Maryam S. Sadafipoor, Matthew Lee Smith, Swann Arp Adams","doi":"10.1101/2024.06.29.24309705","DOIUrl":"https://doi.org/10.1101/2024.06.29.24309705","url":null,"abstract":"Abstract\u0000Background. The purpose was to investigate the impact of sociodemographic factors on healthcare utilization among adults with different cognition levels (normal and impairment/dementia).\u0000Methods. We used cross-sectional data from the Health and Retirement Study (N=17,698) to assess healthcare utilization: hospital stay, nursing home stay, hospice care, and doctor visits.\u0000Results. A cohort comparison between normal and dementia/impaired cognition groups revealed significant differences. The dementia/impaired group had lower education levels, higher single/widowed status, and more racial and ethnic minorities. They experienced longer hospital and nursing home stays, varied doctor visit frequencies, and had higher mean age, greater loneliness scores, and lower family social support scores. Differences in hospitalization, nursing home, hospice care, and doctor visits were influenced by factors such as race, age, marital status, education, and rurality.\u0000Conclusion. There were disparities in healthcare utilization based on participants characteristics and cognition levels, especially in terms of race/ethnicity, education, and rural location.","PeriodicalId":501556,"journal":{"name":"medRxiv - Health Systems and Quality Improvement","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-28DOI: 10.1101/2024.06.27.24309578
Letizia Pontoriero, Andrea Mazzoni, Giovanni De Santis, Matteo Gentili, Ejner Moltzen, Sabine Puch, Carolin Lange, Gianni D'Errico
Personalized medicine is part of the future frontier of public health and precision healthcare systems have been implemented for years, both within Europe and beyond. To establish the state of the art of Sino-EU science and innovation in Personalized medicine, we have mined the major dedicated databases globally. Here we present the updated mapping on the Sino-EU collaborations. Patents, scientific publications and preprints related to Personalized medicine have been mapped and analyzed after being extracted through databases mining. The integration of the previous mapping provides a more complete overview, which does not show relevant variations, confirming previous trends. In this work we complete the mapping by providing a digital tool for consulting the various data collected.
{"title":"Mapping Of The Sino-European Science And Technology Collaborations On Personalized Medicine: An Updated Overview.","authors":"Letizia Pontoriero, Andrea Mazzoni, Giovanni De Santis, Matteo Gentili, Ejner Moltzen, Sabine Puch, Carolin Lange, Gianni D'Errico","doi":"10.1101/2024.06.27.24309578","DOIUrl":"https://doi.org/10.1101/2024.06.27.24309578","url":null,"abstract":"Personalized medicine is part of the future frontier of public health and precision healthcare systems have been implemented for years, both within Europe and beyond. To establish the state of the art of Sino-EU science and innovation in Personalized medicine, we have mined the major dedicated databases globally. Here we present the updated mapping on the Sino-EU collaborations. Patents, scientific publications and preprints related to Personalized medicine have been mapped and analyzed after being extracted through databases mining. The integration of the previous mapping provides a more complete overview, which does not show relevant variations, confirming previous trends. In this work we complete the mapping by providing a digital tool for consulting the various data collected.","PeriodicalId":501556,"journal":{"name":"medRxiv - Health Systems and Quality Improvement","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141525537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-28DOI: 10.1101/2024.06.28.24309648
Veronika Jatileni, Edward Nicol
Introduction: A robust and well-functioning Health Information System (HIS) is crucial for managing patient care, monitoring health system performance, and informing public health decisions. However, Namibia, like many developing countries, faces challenges in its HIS, such as limited financial and human resources, knowledge gaps, inadequate infrastructure, and behavioural barriers such as resistance to adopting new systems and a lack of supportive policies. Previous studies have not shown significant improvements since 2012. This study in Namibia's Khomas region aims to assess human factors affecting the HIS and evaluate progress made from 2012 to 2022. It will use recommendations from a 2012 assessment by USAID to provide insights and propose ways to enhance healthcare delivery and resource allocation. Methods and analysis: This study utilizes a cross-sectional design employing a multi-method approach to evaluate the performance of the Health Information System (HIS). Qualitative methods include conducting 17 in-depth interviews with key informants, a retrospective document review from the Ministry of Health and Social Services headquarters in Windhoek, supplemented by a modified office/facility checklist from all 14 health facilities in the Khomas region. The quantitative methods involve administering a questionnaire to 330 staff members, utilizing an adapted version of the Performance of Routine Information System Management (PRISM)’s Organizational and Behavioural Assessment Tool (OBAT). Descriptive statistics will be applied to analyse the quantitative data, while a deductive interpretive approach will be used for qualitative data analysis. Ethics and dissemination: The protocol was approved by the Stellenbosch University Health Research Ethics Committee (Reference No: S23/05/119), the Namibia ministry of Health and Social Services (Reference No: 22/3/2/1) and will adhere to the principles of the Declaration of Helsinki (1964). The study aims to identify barriers and facilitators for implementing recommendations across different levels of the Health Information System (HIS), with a focus on improving the HIS in the Khomas region. Outputs will include communicating the findings to the study population, presenting at both local and international conferences, and publishing peer-reviewed journal articles.
{"title":"An assessment of the Health Information System in Khomas region, Namibia","authors":"Veronika Jatileni, Edward Nicol","doi":"10.1101/2024.06.28.24309648","DOIUrl":"https://doi.org/10.1101/2024.06.28.24309648","url":null,"abstract":"Introduction:\u0000A robust and well-functioning Health Information System (HIS) is crucial for managing patient care, monitoring health system performance, and informing public health decisions. However, Namibia, like many developing countries, faces challenges in its HIS, such as limited financial and human resources, knowledge gaps, inadequate infrastructure, and behavioural barriers such as resistance to adopting new systems and a lack of supportive policies. Previous studies have not shown significant improvements since 2012. This study in Namibia's Khomas region aims to assess human factors affecting the HIS and evaluate progress made from 2012 to 2022. It will use recommendations from a 2012 assessment by USAID to provide insights and propose ways to enhance healthcare delivery and resource allocation. Methods and analysis:\u0000This study utilizes a cross-sectional design employing a multi-method approach to evaluate the performance of the Health Information System (HIS). Qualitative methods include conducting 17 in-depth interviews with key informants, a retrospective document review from the Ministry of Health and Social Services headquarters in Windhoek, supplemented by a modified office/facility checklist from all 14 health facilities in the Khomas region. The quantitative methods involve administering a questionnaire to 330 staff members, utilizing an adapted version of the Performance of Routine Information System Management (PRISM)’s Organizational and Behavioural Assessment Tool (OBAT). Descriptive statistics will be applied to analyse the quantitative data, while a deductive interpretive approach will be used for qualitative data analysis. Ethics and dissemination:\u0000The protocol was approved by the Stellenbosch University Health Research Ethics Committee (Reference No: S23/05/119), the Namibia ministry of Health and Social Services (Reference No: 22/3/2/1) and will adhere to the principles of the Declaration of Helsinki (1964). The study aims to identify barriers and facilitators for implementing recommendations across different levels of the Health Information System (HIS), with a focus on improving the HIS in the Khomas region. Outputs will include communicating the findings to the study population, presenting at both local and international conferences, and publishing peer-reviewed journal articles.","PeriodicalId":501556,"journal":{"name":"medRxiv - Health Systems and Quality Improvement","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This work involved diagnosing the Beninese health system based on secondary data from several sources (statistical directories, surveys, censuses, and study reports). The descriptive analysis of the evolution of health indicators in Benin between 2002 and 2021 and in-depth interviews with resource people in the health sector made it possible to assess the efforts and progress made by those in power and system stakeholders. There have been many tangible efforts to improve accessibility to health services (the rates of health coverage and attendance at health facilities have increased from 86% to 96% and from 35% to 56% between 2002 and 2021). These efforts have significantly reduced morbidity and mortality rates. The results also indicate a drop in deaths due to malaria (141 deaths to 86 per 100,000 inhabitants between 2003 and 2021) and a drop in the prevalence of HIV AIDS up to 0.8% from 2019 ahead of several countries—neighbors of the sub-region. Early neonatal mortality fell from 10.1‰ to 4.7‰ as well as deaths of children under 5 years old, thus improving life expectancy at birth from 59.6 years in 2002 to 63.8 years in 2013. Despite these efforts, many challenges remain, adding to the strong demographic growth in the country, which clearly expresses the threats weighing on the daily state of health of the Beninese population and calling for a new way of thinking for a sustainable health system. The study ends with the prioritization of challenges and a proposal for strategies to have an efficient and resilient health system, capable of producing quality, healthy, and productive human capital.
{"title":"Diagnosis of the Beninese Health System: Progress and Challenges for an Effective, Resilient and Sustainable System","authors":"Tchando Ambroise Nahini, Mouhamadou Djima Baranon, Emmanuel N'Koue Sambieni, Mouftaou Amadou Sanni","doi":"10.1101/2024.06.25.24309509","DOIUrl":"https://doi.org/10.1101/2024.06.25.24309509","url":null,"abstract":"This work involved diagnosing the Beninese health system based on secondary data from several sources (statistical directories, surveys, censuses, and study reports). The descriptive analysis of the evolution of health indicators in Benin between 2002 and 2021 and in-depth interviews with resource people in the health sector made it possible to assess the efforts and progress made by those in power and system stakeholders. There have been many tangible efforts to improve accessibility to health services (the rates of health coverage and attendance at health facilities have increased from 86% to 96% and from 35% to 56% between 2002 and 2021). These efforts have significantly reduced morbidity and mortality rates. The results also indicate a drop in deaths due to malaria (141 deaths to 86 per 100,000 inhabitants between 2003 and 2021) and a drop in the prevalence of HIV AIDS up to 0.8% from 2019 ahead of several countries—neighbors of the sub-region. Early neonatal mortality fell from 10.1‰ to 4.7‰ as well as deaths of children under 5 years old, thus improving life expectancy at birth from 59.6 years in 2002 to 63.8 years in 2013. Despite these efforts, many challenges remain, adding to the strong demographic growth in the country, which clearly expresses the threats weighing on the daily state of health of the Beninese population and calling for a new way of thinking for a sustainable health system. The study ends with the prioritization of challenges and a proposal for strategies to have an efficient and resilient health system, capable of producing quality, healthy, and productive human capital.","PeriodicalId":501556,"journal":{"name":"medRxiv - Health Systems and Quality Improvement","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141525538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-24DOI: 10.1101/2024.06.19.24308949
Christine Fahim, Ayaat T. Hassan, Keelia Quinn de Launay, Alyson Takaoka, Elikem Togo, Lisa Strifler, Vanessa Bach, Nimitha Paul, Ana Mrazovac, Jessica Firman, Vincenza Gruppuso, Jamie M. Boyd, Sharon Straus
COVID-19 presented a crisis for long-term care homes (LTCHs) and retirement homes (RHs). This study explored the pandemic-related challenges LTCHs and RHs faced and the strategies they used to mitigate them. Ninety-one key informant interviews were conducted with LTCH and RH leadership across 47 homes (33 LTCHs, 14 RHs) in Ontario, Canada from February 2021 to July 2022. Findings confirmed evidence for three main challenges. First, leaders were challenged to implement infection prevention and control protocols and measures. Second, they needed supports to facilitate COVID-19 vaccine access and to promote vaccine confidence. Third, LTCH/RH staff experienced significant well-being challenges in the face of COVID-19 pressures. Findings also reveal a plethora of strategies implemented by homes, with ranging reports of perceived success. Homes' needs evolved rapidly as the COVID-19 pandemic progressed. The use of a co-creation, responsive and tailored approach to address evolving barriers and meaningfully support homes during emergencies is recommended.
{"title":"Challenges facing Canadian Long-Term Care Homes and Retirement Homes during the COVID-19 pandemic","authors":"Christine Fahim, Ayaat T. Hassan, Keelia Quinn de Launay, Alyson Takaoka, Elikem Togo, Lisa Strifler, Vanessa Bach, Nimitha Paul, Ana Mrazovac, Jessica Firman, Vincenza Gruppuso, Jamie M. Boyd, Sharon Straus","doi":"10.1101/2024.06.19.24308949","DOIUrl":"https://doi.org/10.1101/2024.06.19.24308949","url":null,"abstract":"COVID-19 presented a crisis for long-term care homes (LTCHs) and retirement homes (RHs). This study explored the pandemic-related challenges LTCHs and RHs faced and the strategies they used to mitigate them. Ninety-one key informant interviews were conducted with LTCH and RH leadership across 47 homes (33 LTCHs, 14 RHs) in Ontario, Canada from February 2021 to July 2022. Findings confirmed evidence for three main challenges. First, leaders were challenged to implement infection prevention and control protocols and measures. Second, they needed supports to facilitate COVID-19 vaccine access and to promote vaccine confidence. Third, LTCH/RH staff experienced significant well-being challenges in the face of COVID-19 pressures. Findings also reveal a plethora of strategies implemented by homes, with ranging reports of perceived success. Homes' needs evolved rapidly as the COVID-19 pandemic progressed. The use of a co-creation, responsive and tailored approach to address evolving barriers and meaningfully support homes during emergencies is recommended.","PeriodicalId":501556,"journal":{"name":"medRxiv - Health Systems and Quality Improvement","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-24DOI: 10.1101/2024.06.24.24309361
Barbara Hanratty, Gizdem Akdur, Jennifer Kirsty Burton, Vanessa Kirsty Davey, Claire Goodman, Adam Lee Gordon, Anne L Killett, Jennifer Liddle, Stacey Rand, Karen Spilsbury, Ann-Marie Towers
Background: Care home residents have complex needs, and minimum data sets (MDSs) provide a unique source of information on their health and wellbeing. Although MDSs were first developed to monitor quality and costs of care, they can make an important contribution to research. Aim: To describe the research applications of data from care home MDSs, and identify key outcome variables and measures used. Design: Mapping review of published empirical studies using data generated from minimum data sets in long term care facilities for older adults. Methods: We performed a comprehensive search of electronic databases (Medline OVID, CINAHL, Embase and ASSIA), using bespoke search strategies to identify English language publications 2011 -2024. Articles were screened by two independent reviewers. They were grouped by study topic and data (on publication date, country, MDS, outcome variables and specific items or measures) were charted without quality assessment. The key features of the data are described in a narrative synthesis. Findings Searches identified 18588 articles published 2011-2024, of which 661 met inclusion criteria. 72% were from the USA, 12% from Canada and the remaining 16% from four European countries, South Korea and New Zealand. The studies encompassed individual resident functioning (e.g. mobility, incontinence), health conditions and symptoms (e.g. depression, pain), healthcare in the home (e.g. prescribing, end of life care), hospital attendances and admissions, transitions to and from care homes, quality of care and systemwide issues. Measures used reflected the content of the major MDSs, but there was a mismatch between the importance of some topics to care homes (e.g. incontinence) and the range of published papers, and limited consensus over how to measure quality of life. Conclusions Care home MDSs are a unique resource to support study of care home residents and impact of interventions over time. They are a powerful resource when linked to other datasets, and as an adjunct to primary data collection This analysis may serve as an accessible guide to the content and applications of MDS, allowing researchers to consider the sort of questions that can be posed and the different components of resident care or experience that can be evaluated.
{"title":"Application and content of minimum data sets for care homes: A mapping review","authors":"Barbara Hanratty, Gizdem Akdur, Jennifer Kirsty Burton, Vanessa Kirsty Davey, Claire Goodman, Adam Lee Gordon, Anne L Killett, Jennifer Liddle, Stacey Rand, Karen Spilsbury, Ann-Marie Towers","doi":"10.1101/2024.06.24.24309361","DOIUrl":"https://doi.org/10.1101/2024.06.24.24309361","url":null,"abstract":"Background: Care home residents have complex needs, and minimum data sets (MDSs) provide a unique source of information on their health and wellbeing. Although MDSs were first developed to monitor quality and costs of care, they can make an important contribution to research. Aim: To describe the research applications of data from care home MDSs, and identify key outcome variables and measures used.\u0000Design: Mapping review of published empirical studies using data generated from minimum data sets in long term care facilities for older adults. Methods: We performed a comprehensive search of electronic databases (Medline OVID, CINAHL, Embase and ASSIA), using bespoke search strategies to identify English language publications 2011 -2024. Articles were screened by two independent reviewers. They were grouped by study topic and data (on publication date, country, MDS, outcome variables and specific items or measures) were charted without quality assessment. The key features of the data are described in a narrative synthesis. Findings\u0000Searches identified 18588 articles published 2011-2024, of which 661 met inclusion criteria. 72% were from the USA, 12% from Canada and the remaining 16% from four European countries, South Korea and New Zealand. The studies encompassed individual resident functioning (e.g. mobility, incontinence), health conditions and symptoms (e.g. depression, pain), healthcare in the home (e.g. prescribing, end of life care), hospital attendances and admissions, transitions to and from care homes, quality of care and systemwide issues. Measures used reflected the content of the major MDSs, but there was a mismatch between the importance of some topics to care homes (e.g. incontinence) and the range of published papers, and limited consensus over how to measure quality of life.\u0000Conclusions\u0000Care home MDSs are a unique resource to support study of care home residents and impact of interventions over time. They are a powerful resource when linked to other datasets, and as an adjunct to primary data collection This analysis may serve as an accessible guide to the content and applications of MDS, allowing researchers to consider the sort of questions that can be posed and the different components of resident care or experience that can be evaluated.","PeriodicalId":501556,"journal":{"name":"medRxiv - Health Systems and Quality Improvement","volume":"81 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-21DOI: 10.1101/2024.06.19.24309131
Wei Yang, Lingrui Liu, Jiajia Chen, Run Mao, Tao Yang, Lang Linghu, Lieyu Huang, Dong (Roman) Xu, Yiyuan Cai
Background and Objective Diabetes mellitus (DM) is a mounting public health concern in China, home to the largest number of patients with diabetes globally. A primary challenge has been the integration of high-quality chronic disease services, with poor outcomes and inefficient health management intensifying the disease burden. Shared Medical Appointments (SMAs) offer a promising solution, yet evidence of their practical application in resource-limited settings like China's primary healthcare institutions is scant. This study aims to evaluate the organizational readiness for change (ORC) in implementing SMA services in Guizhou province's primary healthcare institutions and to identify determinants of high-level ORC to foster implementation success. Methods This study employed a mixed-method approach. The validated Chinese version of the Workplace Readiness Questionnaire (WRQ-CN) was used to assess the ORC status across 12 institutions participating in the SMART pilot trial. A Normalization Process Theory (NPT) -guided qualitative interview and quantitative survey were used to collect the conditions. Data analysis encompassed standardized descriptive statistics, Spearman correlation analysis, and qualitative comparative analysis (QCA) to discern condition variables and configurations that are favorable to high-level ORC. Results The study engaged 70 institutional participants, including administrators, clinicians, and public health workers. The median ORC score was 105.20 (101.23-107.33). We identified 12 condition variables through the interview and survey. The Spearman correlation analysis highlighted a moderate correlation between Specific tasks and responsibilities (r=0.393, p=0.206) and Key participants (r=0.316, p=0.317) with ORC. QCA also revealed these condition configurations and pathways that collectively align with heightened ORC, accentuating the pivotal role of key participants. Conclusions This study unveiled a spectrum of dynamic conditions and pathways affecting ORC, which are consistent with the NPT-based theoretical steps. They were essential for attaining high-level ORC in rolling out health service innovations like the SMART study, especially in resource-limited settings.
{"title":"Factors Influencing the Implementing Readiness of Shared Medical Appointments in China's Primary Healthcare Institutions: A Mixed-Method Study Utilizing Qualitative Comparative Analysis","authors":"Wei Yang, Lingrui Liu, Jiajia Chen, Run Mao, Tao Yang, Lang Linghu, Lieyu Huang, Dong (Roman) Xu, Yiyuan Cai","doi":"10.1101/2024.06.19.24309131","DOIUrl":"https://doi.org/10.1101/2024.06.19.24309131","url":null,"abstract":"Background and Objective Diabetes mellitus (DM) is a mounting public health concern in China, home to the largest number of patients with diabetes globally. A primary challenge has been the integration of high-quality chronic disease services, with poor outcomes and inefficient health management intensifying the disease burden. Shared Medical Appointments (SMAs) offer a promising solution, yet evidence of their practical application in resource-limited settings like China's primary healthcare institutions is scant. This study aims to evaluate the organizational readiness for change (ORC) in implementing SMA services in Guizhou province's primary healthcare institutions and to identify determinants of high-level ORC to foster implementation success. Methods This study employed a mixed-method approach. The validated Chinese version of the Workplace Readiness Questionnaire (WRQ-CN) was used to assess the ORC status across 12 institutions participating in the SMART pilot trial. A Normalization Process Theory (NPT) -guided qualitative interview and quantitative survey were used to collect the conditions. Data analysis encompassed standardized descriptive statistics, Spearman correlation analysis, and qualitative comparative analysis (QCA) to discern condition variables and configurations that are favorable to high-level ORC. Results The study engaged 70 institutional participants, including administrators, clinicians, and public health workers. The median ORC score was 105.20 (101.23-107.33). We identified 12 condition variables through the interview and survey. The Spearman correlation analysis highlighted a moderate correlation between Specific tasks and responsibilities (r=0.393, p=0.206) and Key participants (r=0.316, p=0.317) with ORC. QCA also revealed these condition configurations and pathways that collectively align with heightened ORC, accentuating the pivotal role of key participants.\u0000Conclusions This study unveiled a spectrum of dynamic conditions and pathways affecting ORC, which are consistent with the NPT-based theoretical steps. They were essential for attaining high-level ORC in rolling out health service innovations like the SMART study, especially in resource-limited settings.","PeriodicalId":501556,"journal":{"name":"medRxiv - Health Systems and Quality Improvement","volume":"165 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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