A qualitative exploration of patient flow in a developing Caribbean emergency department

Objectives Emergency departments (EDs) are complex adaptive systems and improving patient flow requires understanding how ED processes work. This is important for developing countries where flow concerns are compounded by resource constraints. The Caribbean is one region with developing emergency care systems and limited research in the area. This study aimed to explore the patient flow process in an emergency department in Trinidad and Tobago, identifying organizational factors influencing patient flow. Methods Multiple qualitative methods, including non-participant observations, observational process mapping and informal conversational interviews were used to explore patient flow. The process maps were generated from the observational process mapping. Thematic analysis was used to analyze the data. Setting The study was conducted at a major tertiary level emergency department in Trinidad and Tobago. Participants Patient and staff journeys in the emergency department were observed. Results Six broad categories were identified- 1) ED organizational work processes, 2) ED design and layout, 3) material resources, 4) nursing staff levels, roles, skill mix and use 5) non-clinical ED staff and 6) external clinical and non-clinical departments. The study findings were combined with existing literature to produce a model of factors influencing ED patient flow. Barriers and facilitators to patient flow were highlighted. Conclusion The knowledge gained may be used to strengthen the emergency care system in the local context. The model of ED patient flow may be used to systematically examine factors influencing patient flow, informing policy and practice. However, the study findings should be validated in other settings

Qualitative exploration of patient flow in a Caribbean emergency department

Objectives Emergency departments (EDs) are complex adaptive systems and improving patient flow requires understanding how ED processes work. This study aimed to explore the patient flow process in an ED in Trinidad and Tobago, identifying organisational factors influencing patient flow. Methods Multiple qualitative methods, including non-participant observations, observational process mapping and informal conversational interviews were used to explore patient flow. The process maps were generated from the observational process mapping. Thematic analysis was used to analyse the data. Setting The study was conducted at a major tertiary level ED in Trinidad and Tobago. Participants Patient and staff journeys in the ED were directly observed. Results Six broad categories were identified: (1) ED organisational work processes, (2) ED design and layout, (3) material resources, (4) nursing staff levels, roles, skill mix and use, (5) non-clinical ED staff and (6) external clinical and non-clinical departments. Within each category there were individual factors that appeared to either facilitate or hinder patient flow. Organisational processes such as streaming, front loading of investigations and the transfer process were pre-existing strategies in the ED while staff actions to compensate for limitations with flow were more intuitive. A conceptual framework of factors influencing ED patient flow is also presented. Conclusion The knowledge gained may be used to strengthen the emergency care system in the local context. However, the study findings should be validated in other settings

Research paradigms and useful inventions in medicine : patents and licensing by teams of clinical and basic scientists in Academic Medical Centers

In recent decades, teams that combine basic scientists with clinical researchers have become an important organizational mechanism to translate knowledge made in basic science (“the bench”) to tangible medical innovations (“the bedside”). Our study explores whether inventing teams that span basic and clinical research are more effective at licensing than teams comprised of inventors from only one domain. We propose that laboratory science and clinical research represent fundamentally different research paradigms that defy a simple arithmetic of combining the skills of individuals on teams. Clinical and basic researchers inhabit distinct cultures of work that yield different, and sometimes conflicting, beliefs and approaches to problem-solving. We claim that the complexity and variability of most human medical problems limits the role of basic science in medical innovation. Instead, we argue that clinical research remains an important engine of innovation, even in a period of rapid advances in molecular and genetics sciences, and advanced analytical techniques, because clinical researchers have unique opportunities for insights that emerge from the joint activities of research and close observations of living patients. Our empirical analysis focuses on patents and licenses from two prominent Academic Medical Centers (AMCs) over a 30 year period. In hazard models of licensing we find, controlling for a range of effects, that inventions by teams composed of clinical researchers (MDs) are more likely to be licensed than inventions by teams of basic scientists (PhDs), and that inventions that include both MDs and PhDs are not more likely to be licensed. This leads us to question the translational model of combining expertise to bridge different domains. We also find that the training of the team leader has an effect on licensing that is independent of team composition, lending support to our interpretation. Our results help inform policy about the relationship between research paradigms, team composition, and successful innovation in bio-medicine

The organizational implications of medical imaging in the context of Malaysian hospitals

This research investigated the implementation and use of medical imaging in the context of Malaysian hospitals. In this report medical imaging refers to PACS, RIS/HIS and imaging modalities which are linked through a computer network. The study examined how the internal context of a hospital and its external context together influenced the implementation of medical imaging, and how this in turn shaped organizational roles and relationships within the hospital itself. It further investigated how the implementation of the technology in one hospital affected its implementation in another hospital. The research used systems theory as the theoretical framework for the study. Methodologically, the study used a case-based approach and multiple methods to obtain data. The case studies included two hospital-based radiology departments in Malaysia. The outcomes of the research suggest that the implementation of medical imaging in community hospitals is shaped by the external context particularly the role played by the Ministry of Health. Furthermore, influences from both the internal and external contexts have a substantial impact on the process of implementing medical imaging and the extent of the benefits that the organization can gain. In the context of roles and social relationships, the findings revealed that the routine use of medical imaging has substantially affected radiographers’ roles, and the social relationships between non clinical personnel and clinicians. This study found no change in the relationship between radiographers and radiologists. Finally, the approaches to implementation taken in the hospitals studied were found to influence those taken by other hospitals. Overall, this study makes three important contributions. Firstly, it extends Barley’s (1986, 1990) research by explicitly demonstrating that the organization’s internal and external contexts together shape the implementation and use of technology, that the processes of implementing and using technology impact upon roles, relationships and networks and that a role-based approach alone is inadequate to examine the outcomes of deploying an advanced technology. Secondly, this study contends that scalability of technology in the context of developing countries is not necessarily linear. Finally, this study offers practical contributions that can benefit healthcare organizations in Malaysia

Big Data Analytic Framework for Organizational Leverage

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Advancing Precision Medicine: Unveiling Disease Trajectories, Decoding Biomarkers, and Tailoring Individual Treatments

Chronic diseases are not only prevalent but also exert a considerable strain on the healthcare system, individuals, and communities. Nearly half of all Americans suffer from at least one chronic disease, which is still growing. The development of machine learning has brought new directions to chronic disease analysis. Many data scientists have devoted themselves to understanding how a disease progresses over time, which can lead to better patient management, identification of disease stages, and targeted interventions. However, due to the slow progression of chronic disease, symptoms are barely noticed until the disease is advanced, challenging early detection. Meanwhile, chronic diseases often have diverse underlying causes and can manifest differently among patients. Besides the external factors, the development of chronic disease is also influenced by internal signals. The DNA sequence-level differences have been proven responsible for constant predisposition to chronic diseases. Given these challenges, data must be analyzed at various scales, ranging from single nucleotide polymorphisms (SNPs) to individuals and populations, to better understand disease mechanisms and provide precision medicine. Therefore, this research aimed to develop an automated pipeline from building predictive models and estimating individual treatment effects based on the structured data of general electronic health records (EHRs) to identifying genetic variations (e.g., SNPs) associated with diseases to unravel the genetic underpinnings of chronic diseases. First, we used structured EHRs to uncover chronic disease progression patterns and assess the dynamic contribution of clinical features. In this step, we employed causal inference methods (constraint-based and functional causal models) for feature selection and utilized Markov chains, attention long short-term memory (LSTM), and Gaussian process (GP). SHapley Additive exPlanations (SHAPs) and local interpretable model-agnostic explanations (LIMEs) further extended the work to identify important clinical features. Next, I developed a novel counterfactual-based method to predict individual treatment effects (ITE) from observational data. To discern a “balanced” representation so that treated and control distributions look similar, we disentangled the doctor’s preference from the covariance and rebuilt the representation of the treated and control groups. We use integral probability metrics to measure distances between distributions. The expected ITE estimation error of a representation was the sum of the standard generalization error of that representation and the distance between the distributions induced. Finally, we performed genome-wide association studies (GWAS) based on the stage information we extracted from our unsupervised disease progression model to identify the biomarkers and explore the genetic correction between the disease and its phenotypes

The Translational Status of Cancer Liquid Biopsies

Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. This can be achieved by leveraging omics information for accurate molecular characterization of tumors. Tumor tissue biopsies are currently the main source of information for molecular profiling. However, biopsies are invasive and limited in resolving spatiotemporal heterogeneity in tumor tissues. Alternative non-invasive liquid biopsies can exploit patient’s body fluids to access multiple layers of tumor-specific biological information (genomes, epigenomes, transcriptomes, proteomes, metabolomes, circulating tumor cells, and exosomes). Analysis and integration of these large and diverse datasets using statistical and machine learning approaches can yield important insights into tumor biology and lead to discovery of new diagnostic, predictive, and prognostic biomarkers. Translation of these new diagnostic tools into standard clinical practice could transform oncology, as demonstrated by a number of liquid biopsy assays already entering clinical use. In this review, we highlight successes and challenges facing the rapidly evolving field of cancer biomarker research. Lay Summary: Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. The discovery of biomarkers for precision oncology has been accelerated by high-throughput experimental and computational methods, which can inform fine-grained characterization of tumors for clinical decision-making. Moreover, advances in the liquid biopsy field allow non-invasive sampling of patient’s body fluids with the aim of analyzing circulating biomarkers, obviating the need for invasive tumor tissue biopsies. In this review, we highlight successes and challenges facing the rapidly evolving field of liquid biopsy cancer biomarker research

Incidence of myocardial injury in patients submitted to carotid endarterectomy: a systematic review

INTRODUÇÃO Lesão miocárdica após cirurgia não cardíaca (MINS) está associada a maiores taxas de mortalidade e de eventos adversos cardiovasculares major a curto e longo prazo em doentes submetidos a endarterectomia carotídea (CEA). No entanto, a sua incidência ainda não é clara neste subgrupo de doentes. Neste sentido, esta revisão sistemática com meta-análise visa determinar a incidência de MINS em doentes submetidos a CEA. MATERIAIS E MÉTODOS Três bases de dados eletrónicas MEDLINE, Scopus e Web of Science foram utilizadas para procurar estudos que avaliassem a ocorrência de MINS no período pós-operatório de doentes submetidos a CEA. A incidência de MINS foi agrupada por meta-análise de efeitos aleatórios, com exploração de fontes de heterogeneidade por meta-regressão. Adicionalmente, a incidência de MINS relativa a subgrupos de doentes (anestesia geral vs. regional) foi analisada. A avaliação da qualidade dos estudos foi realizada utilizando National Heart, Lung, and Blood Institute (NHLBI) Study Quality Assessment Tool for Observational Cohorts and Cross-Sectional Studies e Risk of Bias 2 tools. RESULTADOS Vinte estudos foram incluídos, com um total de 117.933 participantes. Quatro desses eram ensaios clínicos randomizados controlados (RCT), sendo os restantes estudos de coorte. Todos os estudos observacionais apresentavam um risco de viés global alto, excetuando Pereira Macedo et al. Três desses tinham população repetida, pelo que só os dados do estudo mais recente foram considerados. Por outro lado, todos os RCT tinham um risco de viés global baixo. Em doentes submetidos a anestesia regional, a incidência de MINS em estudos primários variava entre 2% e 15,3%, comparando com 0-42,5% para anestesia geral. A incidência meta-analítica de MINS após CEA foi de 6,3% [95% CI 2,0%-10,6%], mas foi observada heterogeneidade severa (I2 = 99,1%). CONCLUSÃO MINS aparenta ser relativamente comum em doentes submetidos a CEA. A heterogeneidade severa observada aponta para a necessidade de estudos adicionais maiores adotando definições de MINS consistentes e valores de corte equivalentes.BACKGROUND Myocardial injury following noncardiac surgery (MINS) is associated with higher mortality and major adverse cardiovascular event rates in the short- and long-term in patients undergoing carotid endarterectomy (CEA). However, its incidence is still unclear in this subset of patients. Therefore, this systematic review with meta-analysis aims to determine the incidence of MINS in patients undergoing CEA. MATERIALS AND METHODS Three electronic databases MEDLINE, Scopus, and Web of Science were used to search for studies assessing the occurrence of MINS in the postoperative setting of patients undergoing CEA. The incidence of MINS was pooled by random-effects meta-analysis, with sources of heterogeneity being explored by meta-regression. Additionally, the incidence of MINS regarding subgroups of patients (general anesthesia vs. regional anesthesia) was also analysed. Assessment of studies' quality was performed using National Heart, Lung, and Blood Institute (NHLBI) Study Quality Assessment Tool for Observational Cohorts and Cross-Sectional Studies, and Risk of Bias 2 tools. RESULTS Twenty studies were included, with a total of 117,933 participants. Four of them were randomized controlled trials (RCT), while the remaining were cohort studies. All observational cohorts had an overall high risk of bias, except for Pereira Macedo et al. Three of them had repeated population, thus only data from the most recent one was considered. On the other hand, all RCT had an overall low risk of bias. In patients under regional anesthesia, the incidence of MINS in primary studies ranged between 2% and 15.3%, compared to 0-42.5% for general anesthesia. The meta-analytical incidence of MINS after CEA was of 6.3% [95% CI 2.0%-10.6%], but severe heterogeneity was observed (I2 = 99.1%). CONCLUSION MINS appears to be relatively common among patients undergoing CEA. The observed severe heterogeneity points to the need for further larger studies adopting consistent definitions of MINS and equivalent cut-off values

Assessing the implementation and effectiveness of the Electronic Patient Reported Outcome Tool for Seniors with Complex Care Needs:Mixed Methods Study

BACKGROUND: Goal-oriented care is being adopted to deliver person-centered primary care to older adults with multimorbidity and complex care needs. Although this model holds promise, its implementation remains a challenge. Digital health solutions may enable processes to improve adoption; however, they require evaluation to determine feasibility and impact. OBJECTIVE: This study aims to evaluate the implementation and effectiveness of the electronic Patient-Reported Outcome (ePRO) mobile app and portal system, designed to enable goal-oriented care delivery in interprofessional primary care practices. The research questions driving this study are as follows: Does ePRO improve quality of life and self-management in older adults with complex needs? What mechanisms are likely driving observed outcomes? METHODS: A multimethod, pragmatic randomized controlled trial using a stepped-wedge design and ethnographic case studies was conducted over a 15-month period in 6 comprehensive primary care practices across Ontario with a target enrollment of 176 patients. The 6 practices were randomized into either early (3-month control period; 12-month intervention) or late (6-month control period; 9-month intervention) groups. The primary outcome measure of interest was the Assessment of Quality of Life-4D (AQoL-4D). Data were collected at baseline and at 3 monthly intervals for the duration of the trial. Ethnographic data included observations and interviews with patients and providers at the midpoint and end of the intervention. Outcome data were analyzed using linear models conducted at the individual level, accounting for cluster effects at the practice level, and ethnographic data were analyzed using qualitative description and framework analysis methods. RESULTS: Recruitment challenges resulted in fewer sites and participants than expected; of the 176 target, only 142 (80.6%) patients were identified as eligible to participate because of lower-than-expected provider participation and fewer-than-expected patients willing to participate or perceived as ready to engage in goal-setting. Of the 142 patients approached, 45 (32%) participated. Patients set a variety of goals related to self-management, mental health, social health, and overall well-being. Owing to underpowering, the impact of ePRO on quality of life could not be definitively assessed; however, the intervention group, ePRO plus usual care (mean 15.28, SD 18.60) demonstrated a nonsignificant decrease in quality of life (t(24)=−1.20; P=.24) when compared with usual care only (mean 21.76, SD 2.17). The ethnographic data reveal a complex implementation process in which the meaningfulness (or coherence) of the technology to individuals’ lives and work acted as a key driver of adoption and tool appraisal. CONCLUSIONS: This trial experienced many unexpected and significant implementation challenges related to recruitment and engagement. Future studies could be improved through better alignment of the research methods and intervention to the complex and diverse clinical settings, dynamic goal-oriented care process, and readiness of provider and patient participants. TRIAL REGISTRATION: ClinicalTrials.gov NCT02917954; https://clinicaltrials.gov/ct2/show/NCT0291795