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1.
J Health Organ Manag ; ahead-of-print(ahead-of-print)2021 Oct 26.
Artigo em Inglês | MEDLINE | ID: mdl-34693670

RESUMO

PURPOSE: Studies demonstrate how patient roles in system redesign teams reflect a continuum of involvement and influence. This research shows the process by which patients move through this continuum and effectively engage within redesign projects. DESIGN/METHODOLOGY/APPROACH: The authors studied members of redesign teams, consisting of 5-10 members: clinicians, systems engineers, health system staff and patient(s), from three health systems working on separate projects in a patient safety learning lab. Weekly team meetings were observed, January 2016-April 2018, 17 semi-structured interviews were conducted and findings through a patient focus group were refined. Grounded theory was used to analyze field notes and transcripts. FINDINGS: Results show how the social identity process enables patients to move through stages in a patient engagement continuum (informant, partner and active change agent). Initially, patient and team member perceptions of the patient's role influence their respective behaviors (activating, directing, framing and sharing). Subsequently, patient and team member behaviors influence patient contributions on the team, which can redefine patient and team member perceptions of the patient's role. ORIGINALITY/VALUE: As health systems grow increasingly complex and become more interested in responding to patient expectations, understanding how to effectively engage patients on redesign teams gains importance. This research investigates how and why patient engagement on redesign teams changes over time and what makes different types of patient roles valuable for team objectives. Findings have implications for how redesign teams can better prepare, anticipate and support the changing role of engaged patients.

2.
J Ambul Care Manage ; 44(4): 293-303, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34319924

RESUMO

COVID-19 necessitated significant care redesign, including new ambulatory workflows to handle surge volumes, protect patients and staff, and ensure timely reliable care. Opportunities also exist to harvest lessons from workflow innovations to benefit routine care. We describe a dedicated COVID-19 ambulatory unit for closing testing and follow-up loops characterized by standardized workflows and electronic communication, documentation, and order placement. More than 85% of follow-ups were completed within 24 hours, with no observed staff, nor patient infections associated with unit operations. Identified issues include role confusion, staffing and gatekeeping bottlenecks, and patient reluctance to visit in person or discuss concerns with phone screeners.


Assuntos
Instituições de Assistência Ambulatorial/organização & administração , COVID-19/terapia , Continuidade da Assistência ao Paciente/organização & administração , Pneumonia Viral/terapia , Unidades de Cuidados Respiratórios/organização & administração , Adulto , Idoso , Boston/epidemiologia , COVID-19/epidemiologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Pneumonia Viral/epidemiologia , Pneumonia Viral/virologia , Encaminhamento e Consulta/estatística & dados numéricos , SARS-CoV-2 , Análise de Sistemas , Fluxo de Trabalho
3.
J Adv Nurs ; 77(1): 355-366, 2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-33098350

RESUMO

AIMS: To identify significant patient and system access barriers and facilitators to dermatology care in one rural health system with limited dermatology appointment availability. DESIGN: Mixed methods study using data from electronic medical records, patient surveys, stakeholder semi-structured interviews, and service area dermatologist demographics. Retrospective data were collected between 1 January 2017-1 March 2018, and interviews and surveys were conducted between June 1-August 31, 2018. Participants were recruited from two primary care practices in one rural Maine regional health system. METHODS: Findings from thematic analyses, descriptive statistics, and statistical modelling were integrated using Chi-square tests for homogeneity to develop a unified understanding. Statistical modelling using odd-ratio logistic and linear regression were performed for each outcome variable of interest. RESULTS: Urgent referrals by primary care increased the likelihood of dermatology care overall (OR: 6.771; p = .007) and at nearby sites with limited availability (OR: 4.024; p = .024), but not at geographically further sites with higher capacities (p = .844). Referral under-diagnosis occurred in 20.8% of those biopsied. Older (p = .041) or non-working (p = .021) patients were more likely to remain unevaluated than seek more available but geographically further care. CONCLUSIONS: In rural areas with scarce appointment availability, primary care provider diagnostic accuracy may be an important barrier of dermatology care receipt and health outcomes, especially among at-risk populations. IMPACT: Although melanoma mortality rates are decreasing throughout the US, little is known about why rates in Maine continue to rise. This study applied a comprehensive approach to identify several patient and system access barriers to dermatology care in one underserved rural regional health system. While specific to this population and large service area, these findings will inform improvement efforts here and support broader future research efforts aimed at understanding and improving health outcomes in this rural state.


Assuntos
Dermatologia , Serviços de Saúde Rural , Acesso aos Serviços de Saúde , Humanos , Atenção Primária à Saúde , Estudos Retrospectivos , População Rural , Inquéritos e Questionários
4.
Appl Ergon ; 90: 103242, 2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-32861088

RESUMO

Antibiotic-resistant infections cause over 20 thousand deaths and $20 billion annually in the United States. Antibiotic prescribing decision making can be described as a "tragedy of the commons" behavioral economics problem, for which individual best interests affecting human decision-making lead to suboptimal societal antibiotic overuse. In 2015, the U.S. federal government announced a $1.2 billion National Action Plan to combat resistance and reduce antibiotic use by 20% in inpatient settings and 50% in outpatient settings by 2020. We develop and apply a behavioral economics model based on game theory and "tragedy of the commons" concepts to help illustrate why rational individuals may not practice ideal stewardship and how to potentially structure three specific alternate approaches to accomplish these objectives (collective cooperative management, usage taxes, resistance penalties), based on Ostrom's economic governance principles. Importantly, while each approach can effectively incentivize ideal stewardship, the latter two do so with 10-30% lower utility to all providers. Encouraging local or state-level self-managed cooperative stewardship programs thus is preferred to national taxes and penalties, in contrast with current trends and with similar implications in other countries.


Assuntos
Gestão de Antimicrobianos , Antibacterianos/uso terapêutico , Economia Comportamental , Humanos , Motivação , Estados Unidos
5.
Trials ; 21(1): 894, 2020 Oct 28.
Artigo em Inglês | MEDLINE | ID: mdl-33115527

RESUMO

BACKGROUND: Surgical site infections (SSIs) cause significant patient suffering. Surveillance and feedback of SSI rates is an evidence-based strategy to reduce SSIs, but traditional surveillance methods are slow and prone to bias. The objective of this cluster randomized controlled trial (RCT) is to determine if using optimized statistical process control (SPC) charts for SSI surveillance and feedback lead to a reduction in SSI rates compared to traditional surveillance. METHODS: The Early 2RIS Trial is a prospective, multicenter cluster RCT using a stepped wedge design. The trial will be performed in 29 hospitals in the Duke Infection Control Outreach Network (DICON) and 105 clusters over 4 years, from March 2016 through February 2020; year one represents a baseline period; thereafter, 8-9 clusters will be randomized to intervention every 3 months over a 3-year period using a stepped wedge randomization design. All patients who undergo one of 13 targeted procedures at study hospitals will be included in the analysis; these procedures will be included in one of six clusters: cardiac, orthopedic, gastrointestinal, OB-GYN, vascular, and spinal. All clusters will undergo traditional surveillance for SSIs; once randomized to intervention, clusters will also undergo surveillance and feedback using optimized SPC charts. Feedback on surveillance data will be provided to all clusters, regardless of allocation or type of surveillance. The primary endpoint is the difference in rates of SSI between the SPC intervention compared to traditional surveillance and feedback alone. DISCUSSION: The traditional approach for SSI surveillance and feedback has several major deficiencies because SSIs are rare events. First, traditional statistical methods require aggregation of measurements over time, which delays analysis until enough data accumulate. Second, traditional statistical tests and resulting p values are difficult to interpret. Third, analyses based on average SSI rates during predefined time periods have limited ability to rapidly identify important, real-time trends. Thus, standard analytic methods that compare average SSI rates between arbitrarily designated time intervals may not identify an important SSI rate increase on time unless the "signal" is very strong. Therefore, novel strategies for early identification and investigation of SSI rate increases are needed to decrease SSI rates. While SPC charts are used throughout industry and healthcare to improve and optimize processes, including other types of healthcare-associated infections, they have not been evaluated as a tool for SSI surveillance and feedback in a randomized trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT03075813 , Registered March 9, 2017.


Assuntos
Infecção Hospitalar , Infecção da Ferida Cirúrgica , Infecção Hospitalar/diagnóstico , Infecção Hospitalar/prevenção & controle , Humanos , Controle de Infecções , Medição de Risco , Infecção da Ferida Cirúrgica/diagnóstico , Infecção da Ferida Cirúrgica/prevenção & controle
6.
medRxiv ; 2020 Sep 02.
Artigo em Inglês | MEDLINE | ID: mdl-32908993

RESUMO

BACKGROUND: Significant uncertainty exists about the safety of, and best strategies for, reopening colleges and universities while the Covid-19 pandemic is not well-controlled. Little also is known about the effects that on-campus outbreaks may have on local non-student and/or higher-risk communities. Model-based analysis can help inform decision and policy making across a wide range of assumptions and uncertainties. OBJECTIVE: To evaluate the potential range of campus and community Covid-19 exposures, infections, and mortality due to various university and college reopening plans and precautions. METHODS: We developed and calibrated campus-only, community-only, and campus-x-community epidemic models using standard susceptible-exposed-infected-recovered differential equation and agent-based modeling methods. Input parameters for campus and surrounding communities were estimated via published and grey literature, scenario development, expert opinion, Monte Carlo simulation, and accuracy optimization algorithms; models were cross-validated against each other using February-June 2020 county, state, and country data. Campus opening plans (spanning various fully open, hybrid, and fully virtual approaches) were identified from websites, publications, communications, and surveys. All scenarios were simulated assuming 16-week semesters and best/worst case ranges for disease prevalence among community residents and arriving students, precaution compliance, contact frequency, virus attack rates, and tracing and isolation effectiveness. Day-to-day student and community differences in exposures, infections, and mortality were estimated under each scenario as compared to regular and no re-opening; 10% trimmed medians, standard deviations, and probability intervals were computed to omit extreme outlier scenarios. Factorial analyses were conducted to identify inputs with largest and smallest impacts on outcomes. RESULTS: As a base case, predicted 16-week student infections and mortality under normal operations with no precautions (or no compliance) ranged from 472 to 9,484 (4.7% to 94.8%) and 2 to 61 (0.02% to 0.61%) per 10,000 student population, respectively. In terms of contact tracing and isolation resources, as many as 17 to 1,488 total exposures per 10,000 students could occur on a given day throughout the semester needing to be located, tested, and if warranted quarantined. Attributable total additional predicted community exposures, infections, and mortality ranged from 1 to 187, 13 to 820, and 1 to 21, respectively, assuming the university takes no additional precautions to limit exposure risk. The mean (SD) number of days until 1% and 5% of on-campus students are infected was 11 (3) and 76 (17) days, respectively; 34.8% of replications resulted in more than 10% students infected by semester end. The diffusion first inflection point occurred on average on day 84 (+/- 20 days, 95% interval). Common re-opening precaution strategies reduced the above consequences by 24% to 26% fewer infections (now 360 to 6,976 per 10,000 students) and 36% to 50% fewer deaths (now 1 to 39 per 10,000 students). Perfect testing and immediate quarantining of all students on arrival to campus at semester start further reduced infections by 58% to 95% (now 200 to 468 per 10,000 students) and deaths by 95% to 100% (now 0 to 3 per 10,000 students). Uncertainties in many factors, however, produced tremendous variability in all median estimates, ranging by -67% to +370%. CONCLUSIONS: Consequences of reopening college and university physical campuses on student and community Covid-19 exposures, infections, and mortality are very highly unpredictable, depending on a combination of random chance, controllable (e.g. physical layouts), and uncontrollable (e.g. human behavior) factors. Important implications at government and academic institution levels include clear needs for specific criteria to adapt campus operations mid-semester, methods to detect when this is necessary, and well-executed contingency plans for doing so.

8.
Appl Ergon ; 85: 103047, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-32174343

RESUMO

For health information technology to realize its potential to improve flow, care, and patient safety, applications should be intuitive to use and burden neutral for frontline clinicians. We assessed the impact of a patient safety dashboard on clinician cognitive and work load within a simulated information-seeking task for safe inpatient opioid medication management. Compared to use of an electronic health record for the same task, the dashboard was associated with significantly reduced time on task, mouse clicks, and mouse movement (each p < 0.001), with no significant increases in cognitive load nor task inaccuracy. Cognitive burden was higher for users with less experience, possibly partly attributable to usability issues identified during this study. Findings underscore the importance of assessing the usability, cognitive, and work load analysis during the design and implementation of health information technology applications.


Assuntos
Pessoal de Saúde/psicologia , Conduta do Tratamento Medicamentoso , Interface Usuário-Computador , Trabalho/psicologia , Carga de Trabalho/psicologia , Adulto , Analgésicos Opioides/uso terapêutico , Registros Eletrônicos de Saúde , Feminino , Humanos , Masculino , Segurança do Paciente , Análise e Desempenho de Tarefas
9.
Appl Clin Inform ; 11(1): 34-45, 2020 01.
Artigo em Inglês | MEDLINE | ID: mdl-31940670

RESUMO

BACKGROUND: Preventable adverse events continue to be a threat to hospitalized patients. Clinical decision support in the form of dashboards may improve compliance with evidence-based safety practices. However, limited research describes providers' experiences with dashboards integrated into vendor electronic health record (EHR) systems. OBJECTIVE: This study was aimed to describe providers' use and perceived usability of the Patient Safety Dashboard and discuss barriers and facilitators to implementation. METHODS: The Patient Safety Dashboard was implemented in a cluster-randomized stepped wedge trial on 12 units in neurology, oncology, and general medicine services over an 18-month period. Use of the Dashboard was tracked during the implementation period and analyzed in-depth for two 1-week periods to gather a detailed representation of use. Providers' perceptions of tool usability were measured using the Health Information Technology Usability Evaluation Scale (rated 1-5). Research assistants conducted field observations throughout the duration of the study to describe use and provide insight into tool adoption. RESULTS: The Dashboard was used 70% of days the tool was available, with use varying by role, service, and time of day. On general medicine units, nurses logged in throughout the day, with many logins occurring during morning rounds, when not rounding with the care team. Prescribers logged in typically before and after morning rounds. On neurology units, physician assistants accounted for most logins, accessing the Dashboard during daily brief interdisciplinary rounding sessions. Use on oncology units was rare. Satisfaction with the tool was highest for perceived ease of use, with attendings giving the highest rating (4.23). The overall lowest rating was for quality of work life, with nurses rating the tool lowest (2.88). CONCLUSION: This mixed methods analysis provides insight into the use and usability of a dashboard tool integrated within a vendor EHR and can guide future improvements and more successful implementation of these types of tools.


Assuntos
Registros Eletrônicos de Saúde , Segurança do Paciente , Humanos , Pesquisa
10.
Infect Control Hosp Epidemiol ; 41(3): 306-312, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-31852562

RESUMO

BACKGROUND: The reported incidence of Clostridoides difficile infection (CDI) has increased in recent years, partly due to broadening adoption of nucleic acid amplification tests (NAATs) replacing enzyme immunoassay (EIA) methods. Our aim was to quantify the impact of this switch on reported CDI rates using a large, multihospital, empirical dataset. METHODS: We analyzed 9 years of retrospective CDI data (2009-2017) from 47 hospitals in the southeastern United States; 37 hospitals switched to NAAT during this period, including 24 with sufficient pre- and post-switch data for statistical analyses. Poisson regression was used to quantify the NAAT-over-EIA incidence rate ratio (IRR) at hospital and network levels while controlling for longitudinal trends, the proportion of intensive care unit patient days, changes in surveillance methodology, and previously detected infection cluster periods. We additionally used change-point detection methods to identify shifts in the mean and/or slope of hospital-level CDI rates, and we compared results to recorded switch dates. RESULTS: For hospitals that transitioned to NAAT, average unadjusted CDI rates increased substantially after the test switch from 10.9 to 23.9 per 10,000 patient days. Individual hospital IRRs ranged from 0.75 to 5.47, with a network-wide IRR of 1.75 (95% confidence interval, 1.62-1.89). Reported CDI rates significantly changed 1.6 months on average after switching to NAAT testing (standard deviation, 1.9 months). CONCLUSION: Hospitals that switched from EIA to NAAT testing experienced an average postswitch increase of 75% in reported CDI rates after adjusting for other factors, and this increase was often gradual or delayed.


Assuntos
Clostridioides difficile/isolamento & purificação , Infecções por Clostridium/diagnóstico , Infecções por Clostridium/epidemiologia , Técnicas Imunoenzimáticas/métodos , Técnicas de Amplificação de Ácido Nucleico/métodos , Hospitais , Humanos , Técnicas de Diagnóstico Molecular/métodos , Vigilância de Evento Sentinela , Sudeste dos Estados Unidos/epidemiologia
11.
BMJ Qual Saf ; 29(6): 472-481, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-31704893

RESUMO

OBJECTIVE: Surgical site infections (SSIs) are common costly hospital-acquired conditions. While statistical process control (SPC) use in healthcare has increased, limited rigorous empirical research compares and optimises these methods for SSI surveillance. We sought to determine which SPC chart types and design parameters maximise the detection of clinically relevant SSI rate increases while minimising false alarms. DESIGN: Systematic retrospective data analysis and empirical optimisation. METHODS: We analysed 12 years of data on 13 surgical procedures from a network of 58 community hospitals. Statistically significant SSI rate increases (signals) at individual hospitals initially were identified using 50 different SPC chart variations (Shewhart or exponentially weighted moving average, 5 baseline periods, 5 baseline types). Blinded epidemiologists evaluated the clinical significance of 2709 representative signals of potential outbreaks (out of 5536 generated), rating them as requiring 'action' or 'no action'. These ratings were used to identify which SPC approaches maximised sensitivity and specificity within a broader set of 3600 individual chart variations (additional baseline variations and chart types, including moving average (MA), and five control limit widths) and over 32 million dual-chart combinations based on different baseline periods, reference data (network-wide vs local hospital SSI rates), control limit widths and other calculation considerations. Results were validated with an additional year of data from the same hospital cohort. RESULTS: The optimal SPC approach to detect clinically important SSI rate increases used two simultaneous MA charts calculated using lagged rolling baseline windows and 1 SD limits. The first chart used 12-month MAs with 18-month baselines and best identified small sustained increases above network-wide SSI rates. The second chart used 6-month MAs with 3-month baselines and best detected large short-term increases above individual hospital SSI rates. This combination outperformed more commonly used charts, with high sensitivity (0.90; positive predictive value=0.56) and practical specificity (0.67; negative predictive value=0.94). CONCLUSIONS: An optimised combination of two MA charts had the best performance for identifying clinically relevant small but sustained above-network SSI rates and large short-term individual hospital increases.


Assuntos
Auditoria Clínica/métodos , Infecção da Ferida Cirúrgica/epidemiologia , Hospitais Comunitários , Humanos , Vigilância em Saúde Pública , Análise de Regressão , Estudos Retrospectivos
12.
BMC Health Serv Res ; 19(1): 974, 2019 Dec 18.
Artigo em Inglês | MEDLINE | ID: mdl-31852493

RESUMO

BACKGROUND: Access to healthcare is a poorly defined construct, with insufficient understanding of differences in facilitators and barriers between US urban versus rural specialty care. We summarize recent literature and expand upon a prior conceptual access framework, adapted here specifically to urban and rural specialty care. METHODS: A systematic review was conducted of literature within the CINAHL, Medline, PubMed, PsycInfo, and ProQuest Social Sciences databases published between January 2013 and August 2018. Search terms targeted peer-reviewed academic publications pertinent to access to US urban or rural specialty healthcare. Exclusion criteria produced 67 articles. Findings were organized into an existing ten-dimension care access conceptual framework where possible, with additional topics grouped thematically into supplemental dimensions. RESULTS: Despite geographic and demographic differences, many access facilitators and barriers were common to both populations; only three dimensions did not contain literature addressing both urban and rural populations. The most commonly represented dimensions were availability and accommodation, appropriateness, and ability to perceive. Four new identified dimensions were: government and insurance policy, health organization and operations influence, stigma, and primary care and specialist influence. CONCLUSIONS: While findings generally align with a preexisting framework, they also suggest several additional themes important to urban versus rural specialty care access.


Assuntos
Acesso aos Serviços de Saúde/estatística & dados numéricos , Serviços de Saúde Rural , Serviços Urbanos de Saúde , Humanos , Estados Unidos
13.
BMJ Qual Saf ; 27(8): 600-610, 2018 08.
Artigo em Inglês | MEDLINE | ID: mdl-29175853

RESUMO

BACKGROUND: Traditional strategies for surveillance of surgical site infections (SSI) have multiple limitations, including delayed and incomplete outbreak detection. Statistical process control (SPC) methods address these deficiencies by combining longitudinal analysis with graphical presentation of data. METHODS: We performed a pilot study within a large network of community hospitals to evaluate performance of SPC methods for detecting SSI outbreaks. We applied conventional Shewhart and exponentially weighted moving average (EWMA) SPC charts to 10 previously investigated SSI outbreaks that occurred from 2003 to 2013. We compared the results of SPC surveillance to the results of traditional SSI surveillance methods. Then, we analysed the performance of modified SPC charts constructed with different outbreak detection rules, EWMA smoothing factors and baseline SSI rate calculations. RESULTS: Conventional Shewhart and EWMA SPC charts both detected 8 of the 10 SSI outbreaks analysed, in each case prior to the date of traditional detection. Among detected outbreaks, conventional Shewhart chart detection occurred a median of 12 months prior to outbreak onset and 22 months prior to traditional detection. Conventional EWMA chart detection occurred a median of 7months prior to outbreak onset and 14 months prior to traditional detection. Modified Shewhart and EWMA charts additionally detected several outbreaks earlier than conventional SPC charts. Shewhart and SPC charts had low false-positive rates when used to analyse separate control hospital SSI data. CONCLUSIONS: Our findings illustrate the potential usefulness and feasibility of real-time SPC surveillance of SSI to rapidly identify outbreaks and improve patient safety. Further study is needed to optimise SPC chart selection and calculation, statistical outbreak detection rules and the process for reacting to signals of potential outbreaks.


Assuntos
Infecção Hospitalar/epidemiologia , Vigilância em Saúde Pública/métodos , Infecção da Ferida Cirúrgica/epidemiologia , Bases de Dados Factuais , Surtos de Doenças/estatística & dados numéricos , Monitoramento Epidemiológico , Hospitais Comunitários , Humanos , Controle de Infecções , Projetos Piloto , Estudos Retrospectivos , Sudeste dos Estados Unidos/epidemiologia
14.
Lung Cancer ; 112: 156-164, 2017 10.
Artigo em Inglês | MEDLINE | ID: mdl-29191588

RESUMO

The Institute of Medicine recently called for increased understanding of and commitment to timely care. Lung cancer can be difficult to diagnose, resulting in delays that may adversely affect survival; rapid diagnosis and treatment therefore is critical for enabling improved patient outcomes. This scoping review provides an update on timeliness of lung cancer care over the past decade. We searched PubMed for English-language articles published from 2007 to 2016 that report wait time intervals related to diagnosis and treatment of lung cancer. Two authors independently reviewed titles and abstracts for inclusion. Abstracted data included sample size, patient population, study type, dates of study, wait times, and information on disparities, survival, costs, healthcare utilization, and interventions. The final review included 65 studies from 21 different countries. A total of 96 unique variations of wait intervals were reported (e.g., time to diagnosis from first pulmonologist visit, imaging, or initial evaluation), making comparisons across studies difficult. The most common interval was diagnosis to treatment initiation, with reported medians ranging from 6 to 45 days. Fourteen articles reported information on survival, 14 on healthcare utilization, 18 on disparities, and 14 on interventions; results varied by study. Significant variation exists in how access to care time delays are reported. Many patients across different facilities and countries appear to be facing substantial waits to receive lung cancer diagnosis and care. Further research, using common wait-interval metrics, is needed to evaluate and improve timeliness of lung cancer diagnosis and treatment.


Assuntos
Neoplasias Pulmonares/diagnóstico , Neoplasias Pulmonares/terapia , Gerenciamento Clínico , Humanos , Neoplasias Pulmonares/mortalidade , Prognóstico , Fatores de Tempo , Tempo para o Tratamento
15.
Risk Anal ; 36(8): 1644-65, 2016 08.
Artigo em Inglês | MEDLINE | ID: mdl-26882074

RESUMO

Despite the many touted benefits of nanomaterials, concerns remain about their possible environmental, health, and safety (EHS) risks in terms of their toxicity, long-term accumulation effects, or dose-response relationships. The published studies on EHS risks of nanomaterials have increased significantly over the past decade and half, with most focused on nanotoxicology. Researchers are still learning about health consequences of nanomaterials and how to make environmentally responsible decisions regarding their production. This article characterizes the scientific literature on nano-EHS risk analysis to map the state-of-the-art developments in this field and chart guidance for the future directions. First, an analysis of keyword co-occurrence networks is investigated for nano-EHS literature published in the past decade to identify the intellectual turning points and research trends in nanorisk analysis studies. The exposure groups targeted in emerging nano-EHS studies are also assessed. System engineering methods for risk, safety, uncertainty, and system reliability analysis are reviewed, followed by detailed descriptions where applications of these methods are utilized to analyze nanomaterial EHS risks. Finally, the trends, methods, future directions, and opportunities of system engineering methods in nano-EHS research are discussed. The analysis of nano-EHS literature presented in this article provides important insights on risk assessment and risk management tools associated with nanotechnology, nanomanufacturing, and nano-enabled products.


Assuntos
Saúde Ambiental , Nanotecnologia , Humanos , Nanoestruturas , Reprodutibilidade dos Testes , Medição de Risco , Segurança
16.
Neurol Clin Pract ; 6(6): 498-505, 2016 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-29849236

RESUMO

Background: Delayed access to specialty care may increase inappropriate emergency department (ED) visits. However, the details of this relationship after referral to a specialist are unknown. Methods: The correlations in an academic medical center between time to new neurology patient appointments and nonurgent ED use are explored in this study. Access was measured as the number of days between the scheduling and outpatient appointment dates. A series of statistical analyses including correlation analysis, regressions, and hypothesis tests were conducted to investigate possible associations between delayed access to specialty care and ED visits, as well as the effect of ED visits on specialty care cancellation and no-show rates. Results: Of 19,505 new neurology patients, 310 visited an ED prior to their appointment, 95.2% (295) of whom had poor access (defined here as exceeding 21 days). Patients with access >21 days for new visits were 6.6 times more likely to visit the ED before their appointment date, 19% within the first week after scheduling. Patients who visited the ED between their booking and appointment dates were 2.3 times more likely to cancel or fail to attend their appointment. Conclusion: These results suggest that long access delays in specialty referrals can significantly increase ED costs and congestion. Further studies in other specialties to explore this relationship are warranted.

17.
J Child Psychol Psychiatry ; 56(9): 936-48, 2015 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-26096036

RESUMO

BACKGROUND: The accuracy of any screening instrument designed to detect psychopathology among children is ideally assessed through rigorous comparison to 'gold standard' tests and interviews. Such comparisons typically yield estimates of what we refer to as 'standard indices of diagnostic accuracy', including sensitivity, specificity, positive predictive value (PPV), and negative predictive value. However, whereas these statistics were originally designed to detect binary signals (e.g., diagnosis present or absent), screening questionnaires commonly used in psychology, psychiatry, and pediatrics typically result in ordinal scores. Thus, a threshold or 'cut score' must be applied to these ordinal scores before accuracy can be evaluated using such standard indices. To better understand the tradeoffs inherent in choosing a particular threshold, we discuss the concept of 'threshold probability'. In contrast to PPV, which reflects the probability that a child whose score falls at or above the screening threshold has the condition of interest, threshold probability refers specifically to the likelihood that a child whose score is equal to a particular screening threshold has the condition of interest. METHOD: The diagnostic accuracy and threshold probability of two well-validated behavioral assessment instruments, the Child Behavior Checklist Total Problem Scale and the Strengths and Difficulties Questionnaire total scale were examined in relation to a structured psychiatric interview in three de-identified datasets. RESULTS: Although both screening measures were effective in identifying groups of children at elevated risk for psychopathology in all samples (odds ratios ranged from 5.2 to 9.7), children who scored at or near the clinical thresholds that optimized sensitivity and specificity were unlikely to meet criteria for psychopathology on gold standard interviews. CONCLUSIONS: Our results are consistent with the view that screening instruments should be interpreted probabilistically, with attention to where along the continuum of positive scores an individual falls.


Assuntos
Diagnóstico Precoce , Transtornos Mentais/diagnóstico , Escalas de Graduação Psiquiátrica/normas , Psicometria/normas , Adolescente , Criança , Pré-Escolar , Humanos , Sensibilidade e Especificidade
18.
Am J Med Qual ; 30(2): 161-6, 2015.
Artigo em Inglês | MEDLINE | ID: mdl-24586025

RESUMO

Industrial engineering and related disciplines have been used widely in improvement efforts in many industries. These approaches have been less commonly attempted in health care. One factor limiting application is the limited workforce resulting from a lack of specific education and professional development in health systems engineering (HSE). The authors describe the development of an HSE fellowship within the United States Department of Veterans Affairs, Veterans Health Administration (VA). This fellowship includes a novel curriculum based on specifically established competencies for HSE. A 1-year HSE curriculum was developed and delivered to fellows at several VA engineering resource centers over several years. On graduation, a majority of the fellows accepted positions in the health care field. Challenges faced in developing the fellowship are discussed. Advanced educational opportunities in applied HSE have the potential to develop the workforce capacity needed to improve the quality of health care.


Assuntos
Currículo , Atenção à Saúde/normas , Bolsas de Estudo , Melhoria de Qualidade , Hospitais de Veteranos , Desenvolvimento de Programas , Estados Unidos
19.
Acad Emerg Med ; 20(11): 1156-63, 2013 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-24238319

RESUMO

OBJECTIVES: The objective was to test the generalizability, across a range of hospital sizes and demographics, of a previously developed method for predicting and aggregating, in real time, the probabilities that emergency department (ED) patients will be admitted to a hospital inpatient unit. METHODS: Logistic regression models were developed that estimate inpatient admission probabilities of each patient upon entering an ED. The models were based on retrospective development (n = 4,000 to 5,000 ED visits) and validation (n = 1,000 to 2,000 ED visits) data sets from four heterogeneous hospitals. Model performance was evaluated using retrospective test data sets (n = 1,000 to 2,000 ED visits). For one hospital the developed model also was applied prospectively to a test data set (n = 910 ED visits) coded by triage nurses in real time, to compare results to those from the retrospective single investigator-coded test data set. RESULTS: The prediction models for each hospital performed reasonably well and typically involved just a few simple-to-collect variables, which differed for each hospital. Areas under receiver operating characteristic curves (AUC) ranged from 0.80 to 0.89, R(2) correlation coefficients between predicted and actual daily admissions ranged from 0.58 to 0.90, and Hosmer-Lemeshow goodness-of-fit statistics of model accuracy had p > 0.01 with one exception. Data coded prospectively by triage nurses produced comparable results. CONCLUSIONS: The accuracy of regression models to predict ED patient admission likelihood was shown to be generalizable across hospitals of different sizes, populations, and administrative structures. Each hospital used a unique combination of predictive factors that may reflect these differences. This approach performed equally well when hospital staff coded patient data in real time versus the research team retrospectively.


Assuntos
Serviço Hospitalar de Emergência/estatística & dados numéricos , Hospitalização/estatística & dados numéricos , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Admissão do Paciente/estatística & dados numéricos , Valor Preditivo dos Testes , Estudos Retrospectivos , Triagem , Estados Unidos
20.
Acad Emerg Med ; 19(9): E1045-54, 2012 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-22978731

RESUMO

OBJECTIVES: The objectives were to evaluate three models that use information gathered during triage to predict, in real time, the number of emergency department (ED) patients who subsequently will be admitted to a hospital inpatient unit (IU) and to introduce a new methodology for implementing these predictions in the hospital setting. METHODS: Three simple methods were compared for predicting hospital admission at ED triage: expert opinion, naïve Bayes conditional probability, and a generalized linear regression model with a logit link function (logit-linear). Two months of data were gathered from the Boston VA Healthcare System's 13-bed ED, which receives approximately 1,100 patients per month. Triage nurses were asked to estimate the likelihood that each of 767 triaged patients from that 2-month period would be admitted after their ED treatment, by placing them into one of six categories ranging from low to high likelihood. Logit-linear regression and naïve Bayes models also were developed using retrospective data and used to estimate admission probabilities for each patient who entered the ED within a 2-month time frame, during triage hours (1,160 patients). Predictors considered included patient age, primary complaint, provider, designation (ED or fast track), arrival mode, and urgency level (emergency severity index assigned at triage). RESULTS: Of the three methods considered, logit-linear regression performed the best in predicting total bed need, with a receiver operating characteristic (ROC) area under the curve (AUC) of 0.887, an R(2) of 0.58, an average estimation error of 0.19 beds per day, and on average roughly 3.5 hours before peak demand occurred. Significant predictors were patient age, primary complaint, bed type designation, and arrival mode (p < 0.0001 for all factors). The naïve Bayesian model had similar positive predictive value, with an AUC of 0.841 and an R(2) of 0.58, but with average difference in total bed need of approximately 2.08 per day. Triage nurse expert opinion also had some predictive capability, with an R(2) of 0.52 and an average difference in total bed need of 1.87 per day. CONCLUSIONS: Simple probability models can reasonably predict ED-to-IU patient volumes based on basic data gathered at triage. This predictive information could be used for improved real-time bed management, patient flow, and discharge processes. Both statistical models were reasonably accurate, using only a minimal number of readily available independent variables.


Assuntos
Serviço Hospitalar de Emergência/organização & administração , Pacientes Internados/estatística & dados numéricos , Admissão do Paciente/estatística & dados numéricos , Transferência de Pacientes/organização & administração , Triagem , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Teorema de Bayes , Boston , Criança , Medicina de Emergência/organização & administração , Feminino , Hospitalização/estatística & dados numéricos , Humanos , Tempo de Internação , Modelos Lineares , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Gestão da Qualidade Total , Listas de Espera , Adulto Jovem
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