Predictive modelling of transport decisions and resources optimisation in pre-hospital setting using machine learning techniques.

BACKGROUND: The global evolution of pre-hospital care systems faces dynamic challenges, particularly in multinational settings. Machine learning (ML) techniques enable the exploration of deeply embedded data patterns for improved patient care and resource optimisation. This study's objective was to accurately predict cases that necessitated transportation versus those that did not, using ML techniques, thereby facilitating efficient resource allocation. METHODS: ML algorithms were utilised to predict patient transport decisions in a Middle Eastern national pre-hospital emergency medical care provider. A comprehensive dataset comprising 93,712 emergency calls from the 999-call centre was analysed using R programming language. Demographic and clinical variables were incorporated to enhance predictive accuracy. Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and Adaptive Boosting (AdaBoost) algorithms were trained and validated. RESULTS: All the trained algorithm models, particularly XGBoost (Accuracy = 83.1%), correctly predicted patients' transportation decisions. Further, they indicated statistically significant patterns that could be leveraged for targeted resource deployment. Moreover, the specificity rates were high; 97.96% in RF and 95.39% in XGBoost, minimising the incidence of incorrectly identified "Transported" cases (False Positive). CONCLUSION: The study identified the transformative potential of ML algorithms in enhancing the quality of pre-hospital care in Qatar. The high predictive accuracy of the employed models suggested actionable avenues for day and time-specific resource planning and patient triaging, thereby having potential to contribute to pre-hospital quality, safety, and value improvement. These findings pave the way for more nuanced, data-driven quality improvement interventions with significant implications for future operational strategies.

Epidemiology of prehospital emergency calls according to patient transport decision in a middle eastern emergency care environment: Retrospective cohort-based.

Background and Aim: Though emergency medical services (EMS) respond to all types of emergency calls, they do not always result in the patient being transported to the hospital. This study aimed to explore the determinants influencing emergency call-response-based conveyance decisions in a Middle Eastern ambulance service. Methods: This retrospective quantitative analysis of 93,712 emergency calls to the Hamad Medical Corporation Ambulance Service (HMCAS) between January 1 and May 31, 2023, obtained from the HMCAS electronic system, was analyzed to determine pertinent variables. Sociodemographic, emergency dispatch-related, clinical, and miscellaneous predictors were analyzed. Descriptive, bivariate, ridge logistic regression, and combination analyses were evaluated. Results: 23.95% (N = 21,194) and 76.05% (N = 67,285) resulted in patient nontransport and transportation, respectively. Sociodemographic analysis revealed that males predominantly activated EMS resources, and 60% of males (n = 12,687) were not transported, whilst 65% of females (n = 44,053) were transported. South Asians represented a significant proportion of the transported patients (36%, n = 24,007). "Home" emerged as the primary emergency location (56%, n = 37,725). Bivariate analysis revealed significant associations across several variables, though multicollinearity was identified as a challenge. Ridge regression analysis underscored the role of certain predictors, such as missing provisional diagnoses, in transportation decisions. The upset plot shows that hypertension and diabetes mellitus were the most common combinations in both groups. Conclusions: This study highlights the nuanced complexities governing conveyance decisions. By unveiling patterns such as male predominance, which reflects Qatar's expatriate population, and specific temporal EMS activity peaks, this study accentuates the importance of holistic patient assessment that transcends medical histories.

Exploring factors influencing time from dispatch to unit availability according to the transport decision in the pre-hospital setting: an exploratory study.

BACKGROUND: Efficient resource distribution is important. Despite extensive research on response timings within ambulance services, nuances of time from unit dispatch to becoming available still need to be explored. This study aimed to identify the determinants of the duration between ambulance dispatch and readiness to respond to the next case according to the patients' transport decisions. METHODS: Time from ambulance dispatch to availability (TDA) analysis according to the patients' transport decision (Transport versus Non-Transport) was conducted using R-Studio™ for a data set of 93,712 emergency calls managed by a Middle Eastern ambulance service from January to May 2023. Log-transformed Hazard Ratios (HR) were examined across diverse parameters. A Cox regression model was utilised to determine the influence of variables on TDA. Kaplan-Meier curves discerned potential variances in the time elapsed for both cohorts based on demographics and clinical indicators. A competing risk analysis assessed the probabilities of distinct outcomes occurring. RESULTS: The median duration of elapsed TDA was 173 min for the transported patients and 73 min for those not transported. The HR unveiled Significant associations in various demographic variables. The Kaplan-Meier curves revealed variances in TDA across different nationalities and age categories. In the competing risk analysis, the 'Not Transported' group demonstrated a higher incidence of prolonged TDA than the 'Transported' group at specified time points. CONCLUSIONS: Exploring TDA offers a novel perspective on ambulance services' efficiency. Though promising, the findings necessitate further exploration across diverse settings, ensuring broader applicability. Future research should consider a comprehensive range of variables to fully harness the utility of this period as a metric for healthcare excellence.

Factors Associated With the Ability of US Nursing Homes to Accept Residents With Severe Obesity.

OBJECTIVES: Severe obesity in nursing home (NH) residents is associated with specialized care needs, limited mobility, and challenges in daily living. The COVID-19 pandemic strained NH resources and exacerbated staffing shortages. This study aimed to assess the ability of US NHs to accept and care for residents with severe obesity post-COVID, as well as associated NH factors. DESIGN: Cross-sectional nationwide survey of NH administrators (2021-2022). SETTING AND PARTICIPANTS: 290 NHs from a national sample (n = 224) and a targeted sample in Massachusetts and New Jersey (n = 66). METHODS: A survey designed to assess how NHs approach admitting and caring for people with severe obesity before and after COVID was fielded from 2021 to 2022. Responses were linked to facility information from the Certification and Survey Provider Enhanced Reports, Minimum Data Set, Nursing Home Compare, Area Health Resources File, and US Diabetes Surveillance System. Multivariable logistic regression was used to assess the effect of organizational and survey response variables. RESULTS: Of the 2503 surveys sent to US NHs, 1923 were sent to the national NH stratified sample, and 580 were sent to the MA/NJ sample. Overall, 12% (301 of 2503) of NHs surveyed responded. The response rates were similar between the 2 samples. Of 290 NHs with complete data, 34% reported being unlikely to accept residents with severe obesity after COVID-19, compared with 25% before the pandemic (P < .001). The main barriers to acceptance were staffing shortages and difficulties meeting equipment and space needs. NHs with higher proportions of Black residents were more likely to admit individuals with severe obesity. CONCLUSIONS AND IMPLICATIONS: The decline in acceptance of residents with severe obesity during and after COVID-19 highlights potential challenges that this population faces in accessing care. Our results also raise concerns that an intersection of disparities may exist in Black patients with severe obesity.

Enhancing Patient Safety in Prehospital Environment: Analyzing Patient Perspectives on Non-Transport Decisions With Natural Language Processing and Machine Learning.

OBJECTIVE: This research explored the experiences and perspectives of patients declining hospital transportation after receiving prehospital emergency care using advanced computational techniques. METHOD: Between 15th June and 1st August 2023, 210 patients in Qatar, treated by Hamad Medical Corporation Ambulance Service (HMCAS) but refusing transportation to hospital, were interviewed. Key outcome variables stratified by demographics included "reasons for refusing transport," "satisfaction with HMCAS service," and "postrefusal actions." Responses underwent sentiment analysis and topic modeling using latent Dirichlet allocation. Machine learning models, such as Naïve Bayes, K-nearest neighboring, random forest, and support vector machine, were used to predict patients' subsequent actions. RESULTS: Participants had an average age of 38.61 ± 19.91 years. The chief complaints were primarily chest and abdominal pains (18.49%; n = 39). Sentiment Analysis revealed a generally favorable perception of HMCAS-provided service. Latent Dirichlet allocation identified two main topics pertaining to refusal reasons and service satisfaction. Naïve Bayes and support vector machine algorithms were most effective in predicting postrefusal actions with an accuracy rate of 81.58%. CONCLUSIONS: This study highlighted the utility of Natural Language Processing and ML in enhancing our understanding of patient behaviors and sentiments in prehospital settings. These advanced computational methodologies allowed for a nuanced exploration of patient demographics and sentiments, providing insights for Quality Improvement initiatives. The study also advocates for continuously integrating automated feedback mechanisms to improve patient-centered care in the prehospital context. Continuous integration of automated feedback systems is recommended to improve prehospital patient-centered care.

Perspectives on Preparedness for Chemical, Biological, Radiological, and Nuclear Threats in the Middle East and North Africa Region: Application of Artificial Intelligence Techniques.

Over the past 3 decades, the diversity of ethnic, religious, and political backgrounds worldwide, particularly in countries of the Middle East and North Africa (MENA), has led to an increase in the number of intercountry conflicts and terrorist attacks, sometimes involving chemical and biological agents. This warrants moving toward a collaborative approach to strengthening preparedness in the region. In disaster medicine, artificial intelligence techniques have been increasingly utilized to allow a thorough analysis by revealing unseen patterns. In this study, the authors used text mining and machine learning techniques to analyze open-ended feedback from multidisciplinary experts in disaster medicine regarding the MENA region's preparedness for chemical, biological, radiological, and nuclear (CBRN) risks. Open-ended feedback from 29 international experts in disaster medicine, selected based on their organizational roles and contributions to the academic field, was collected using a modified interview method between October and December 2022. Machine learning clustering algorithms, natural language processing, and sentiment analysis were used to analyze the data gathered using R language accessed through the RStudio environment. Findings revealed negative and fearful sentiments about a lack of accessibility to preparedness information, as well as positive sentiments toward CBRN preparedness concepts raised by the modified interview method. The artificial intelligence analysis techniques revealed a common consensus among experts about the importance of having accessible and effective plans and improved health sector preparedness in MENA, especially for potential chemical and biological incidents. Findings from this study can inform policymakers in the region to converge their efforts to build collaborative initiatives to strengthen CBRN preparedness capabilities in the healthcare sector.

A Virtual Inner Ear Model Selects Ramped Pulse Shapes for Vestibular Afferent Stimulation.

Bilateral vestibular deficiency (BVD) results in chronic dizziness, blurry vision when moving the head, and postural instability. Vestibular prostheses (VPs) show promise as a treatment, but the VP-restored vestibulo-ocular reflex (VOR) gain in human trials falls short of expectations. We hypothesize that the slope of the rising ramp in stimulation pulses plays an important role in the recruitment of vestibular afferent units. To test this hypothesis, we utilized customized programming to generate ramped pulses with different slopes, testing their efficacy in inducing electrically evoked compound action potentials (eCAPs) and current spread via bench tests and simulations in a virtual inner model created in this study. The results confirmed that the slope of the ramping pulses influenced the recruitment of vestibular afferent units. Subsequently, an optimized stimulation pulse train was identified using model simulations, exhibiting improved modulation of vestibular afferent activity. This optimized slope not only reduced the excitation spread within the semicircular canals (SCCs) but also expanded the neural dynamic range. While the model simulations exhibited promising results, in vitro and in vivo experiments are warranted to validate the findings of this study in future investigations.

Paying A Heavy Price: Costs of Care for People with Severe Obesity in Nursing Homes.

BACKGROUND AND OBJECTIVES: The prevalence of resident obesity in nursing homes has increased dramatically from 22% to 28% between 2005 and 2015. To provide care for people with obesity, nursing homes have changed their admissions, staffing, and equipment, but underlying these changes are increased resources and financial costs of care. The purpose of this study is to describe nursing home organizational aspects of caring for older adults with obesity, with a focus on economic factors, from the perspective of nursing home staff and leadership. RESEARCH DESIGN AND METHODS: This qualitative study used descriptive approaches; data were collected through semi-structured telephone interviews. Of 77 nursing home staff and leaders identified as potential study participants, 6 were ineligible, and 71 participated in the study through interviews conducted from 2019 to 2022. RESULTS: Four primary themes described the issues surrounding cost of care for obesity in nursing homes: inefficient and risky use of staff time in a setting of persistent staff shortage, expensive and unique equipment needs, inadequate general reimbursement with an absence of obesity-specific reimbursement supplements, and competing short and long-term management solutions. DISCUSSION AND IMPLICATIONS: This qualitative study of nursing home staff and leadership underscores a need for improved approaches to funding obesity care within existing nursing payment models. The increasing prevalence of obesity and the burden of the costs of obesity care for nursing homes will escalate this need over the coming decade.

Environmental and structural factors driving poor quality of care: An examination of nursing homes serving Black residents.

BACKGROUND: Poor quality of care in nursing homes (NHs) with high proportions of Black residents has been a problem in the US and even more pronounced during the COVID-19 pandemic. Federal and state agencies are devoting attention to identifying the best means of improving care in the neediest facilities. It is important to understand environmental and structural characteristics that may have led to poor healthcare outcomes in NHs serving high proportions of Black residents pre-pandemic. METHODS: We conducted a cross-sectional observational study using multiple 2019 national datasets. Our exposure was the proportion of Black residents in a NH (i.e., none, <5%, 5%-19.9%, 20-49.9%, ≥50%). Healthcare outcomes examined were hospitalizations and emergency department (ED) visits, both observed and risk-adjusted. Structural factors included staffing, ownership status, bed count (0-49, 50-149, or ≥150), chain organization membership, occupancy, and percent Medicaid as a payment source. Environmental factors included region and urbanicity. Descriptive and multivariable linear regression models were estimated. RESULTS: In the 14,121 NHs, compared to NHs with no Black residents, NHs with ≥50% Black residents tended to be urban, for-profit, located in the South, have more Medicaid-funded residents, and have lower ratios of registered-nurse (RN) and aide hours per resident per day (HPRD) and greater ratios of licensed practical nurse HPRD. In general, as the proportion of Black residents in a NH increased, hospitalizations and ED visits also increased. DISCUSSION/IMPLICATIONS: As lower use of RNs has been associated with increased ED visits and hospitalizations in NHs generally, it is likely low RN use largely drove the differences in hospitalizations and ED visits in NHs with greater proportions of Black residents. Staffing is an area in which state and federal agencies should take action to improve the quality of care in NHs with larger proportions of Black residents.

Finite Element Modeling of Residual Hearing after Cochlear Implant Surgery in Chinchillas.

Cochlear implant (CI) surgery is one of the most utilized treatments for severe hearing loss. However, the effects of a successful scala tympani insertion on the mechanics of hearing are not yet fully understood. This paper presents a finite element (FE) model of the chinchilla inner ear for studying the interrelationship between the mechanical function and the insertion angle of a CI electrode. This FE model includes a three-chambered cochlea and full vestibular system, accomplished using µ-MRI and µ-CT scanning technologies. This model's first application found minimal loss of residual hearing due to insertion angle after CI surgery, and this indicates that it is a reliable and helpful tool for future applications in CI design, surgical planning, and stimuli setup.

Retrospective identification of medication related adverse events in the emergency medical services through the analysis of a patient safety register.

Adverse drug events encompass a wide range of potential unintended and harmful events, from adverse drug reactions to medication errors, many of which in retrospect, are considered preventable. However, the primary challenge towards reducing their burden lies in consistently identifying and monitoring these occurrences, a challenge faced across the spectrum of healthcare, including the emergency medical services. The aim of this study was to identify and describe medication related adverse events (AEs) in the out-of-hospital setting. The medication components of a dedicated patient safety register were analysed and described for the period Jan 2017-Sept 2020. Univariate descriptive analysis was used to summarize and report on basic case and patient demographics, intervention related AEs, medication related AEs, and AE severity. Multivariable logistic regression was used to assess the odds of AE severity, by AE type. A total of 3475 patient records were assessed where 161 individual medication AEs were found in 150 (4.32%), 12 of which were categorised as harmful. Failure to provide a required medication was found to be the most common error (1.67%), followed by the administration of medications outside of prescribed practice guidelines (1.18%). There was evidence to suggest a 63% increase in crude odds of any AE severity [OR 1.63 (95% CI 1.03-2.6), p = 0.035] with the medication only AEs when compared to the intervention only AEs. Prehospital medication related adverse events remain a significant threat to patient safety in this setting and warrant greater widespread attention and future identification of strategies aimed at their reduction.

Efficacy and safety of the second in-hospital dose of tranexamic acid after receiving the prehospital dose: double-blind randomized controlled clinical trial in a level 1 trauma center.

BACKGROUND: Prehospital administration of tranexamic acid (TXA) to injured patients is increasing worldwide. However, optimal TXA dose and need of a second infusion on hospital arrival remain undetermined. We investigated the efficacy and safety of the second in-hospital dose of TXA in injured patients receiving 1 g of TXA in the prehospital setting. We hypothesized that a second in-hospital dose of TXA improves survival of trauma patients. METHODS: A prospective, double-blind, placebo-controlled randomized, clinical trial included adult trauma patients receiving 1 g of TXA in the prehospital settings. Patients were then blindly randomized to Group I (second 1-g TXA) and Group II (placebo) on hospital arrival. The primary outcome was 24-h (early) and 28-day (late) mortality. Secondary outcomes were thromboembolic events, blood transfusions, hospital length of stay (HLOS) and organs failure (MOF). RESULTS: A total of 220 patients were enrolled, 110 in each group. The TXA and placebo groups had a similar early [OR 1.000 (0.062-16.192); p = 0.47] and late mortality [OR 0.476 (95% CI 0.157-1.442), p = 0.18].The cause of death (n = 15) was traumatic brain injury (TBI) in 12 patients and MOF in 3 patients. The need for blood transfusions in the first 24 h, number of transfused blood units, HLOS, thromboembolic events and multiorgan failure were comparable in the TXA and placebo groups. In seriously injured patients (injury severity score > 24), the MTP activation was higher in the placebo group (31.3% vs 11.10%, p = 0.13), whereas pulmonary embolism (6.9% vs 2.9%, p = 0.44) and late mortality (27.6% vs 14.3%, p = 0.17) were higher in the TXA group but did not reach statistical significance. CONCLUSION: The second TXA dose did not change the mortality rate, need for blood transfusion, thromboembolic complications, organ failure and HLOS compared to a single prehospital dose and thus its routine administration should be revisited in larger and multicenter studies. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03846973.

Measuring Caregiver Retention in Nursing Homes.

BACKGROUND AND OBJECTIVES: Retention of nursing home caregivers is examined. This represents the concept of continuously employing the same caregivers in the same facility for a defined period of time. In this research, several measures of caregiver retention are examined and the utility of these measures for practitioners and policy makers is discussed. RESEARCH DESIGN AND METHODS: A survey of nursing home administrators conducted in 2016 was used to collect staffing data from 2,898 facilities. This was matched with Nursing Home Compare and the Certification and Survey Provider Enhanced Reporting data. The association of four measures of retention for each of three types of caregivers with six quality indicators was examined. RESULTS: The descriptive statistics show rates of retention at 5 years for nurse aides (NAs), registered nurses (RNs), and licensed practical nurses to be low. The regression estimates show some support for the relationship that high caregiver retention is associated with better overall quality. The relationship was strongest for NAs and RNs. Support was also found for the notion that different measures of retention were more/less associated with quality. The 3- and 5-year retention measures had the strongest associations with the quality indicators. DISCUSSION AND IMPLICATIONS: The findings presented provide some evidence that caregiver retention may be an important metric that can be used as a means of improving quality of care in nursing homes. However, the findings also show practitioners and policy makers should be more nuanced in the use of caregiver retention metrics.

Application of a Healthcare Failure Modes and Effects Analysis to Identify and Mitigate Potential Risks in the Implementation of a National Prehospital Pediatric Rapid Sequence Intubation Program.

INTRODUCTION: Rapid sequence intubation (RSI) has become the de facto airway method of choice in the emergency airway management of adult and pediatric patients. There is significant controversy regarding pediatric RSI in the prehospital setting, given not only the complexities inherent in both the procedure and patient population, but in variations in emergency medical service models, prehospital qualifications, scope of practice, and patient exposure too. METHODS: A Healthcare Failure Mode and Effects Analysis was conducted to identify and mitigate potential hazards in the national implementation of a prehospital pediatric RSI program. A process map and potential failure points were developed and identified. Probabilities, severity, and hazards scores were calculated for each failure point, and actions items developed to address these. RESULTS: One hundred four potential failure points were identified among 44 subprocesses, divided between nine major processes. In terms of severity, most were classified as either major (n = 39 [37.5%]) or catastrophic (n = 35 [33.7%]) with just more than half falling within the uncommon category (n = 56 [53.9%]) in terms of probability. Five strategic actions items were identified to mitigate against the failure points meeting criteria for action. To monitor the success of these, 11 quality and performance indicators were developed for concurrent implementation. CONCLUSIONS: The Healthcare Failure Mode and Effects Analysis represents a simple yet comprehensive first step toward risk analysis of complex procedures within the prehospital emergency care setting. Application of the methodology provided guidance for the consensus identification of hazards associated with prehospital pediatric RSI and appropriate actions to mitigate them.

The CoreQ: Development and Testing of a Nursing Facility Resident Satisfaction Survey.

The development and testing of a nursing facility resident satisfaction survey (i.e., CoreQ) that could be used for public reporting purposes is presented here. This is important as very little satisfaction with care information is publicly available for nursing facility consumers. Validity testing is reported detailing the development of the CoreQ: Short Stay Discharge questionnaire and a measure that was calculated from the items in the questionnaire. This questionnaire resulted in four items whose combined score gives a measure representing participants' overall satisfaction with the nursing facility. The measure parsimoniously reports this satisfaction as a score (ranging from 0 to 100) and was recently endorsed by the National Quality Forum (NQF). The measure may have significance for report cards and payment metrics, as it incorporates the consumers' opinion.

Barriers to the implementation of prehospital thrombolysis in the treatment of ST-segment elevation myocardial infarction in South Africa: An exploratory inquiry.

INTRODUCTION: Evidence-based guidelines advocate percutaneous coronary intervention (PCI) as the mainstay reperfusion strategy for ST-segment elevation myocardial infarction (STEMI). However, the South African health system is not well positioned to provide PCI as a 'mainstay strategy'. In response, the Health Professions Council of South Africa approved the use of prehospital thrombolysis (PHT) for emergency care practitioners in 2009. However, since its approval, prehospital thrombolysis has failed to reach a level of systematic uptake indicative of successful implementation. The current study aimed to explore, through a qualitative inquiry, barriers to PHT for the treatment of myocardial infarction within a South African context. METHODS: A qualitative single-case study design was used where a series of semi-structured interviews were conducted involving purposefully selected participants. The case comprised a nationalised private emergency medical service, and participants were selected in view of relevant experience and knowledge. Requisite data was conceptualised through the consolidated framework for implementation research, and thematic analysis outlined the data coding procedures of the study. RESULTS: The study identified potential barriers to the implementation of PHT. These comprised cost, logistics, inter-professional collaboration, leadership engagement, and beliefs or scepticism associated with PHT. CONCLUSION: A lack of strategic implementation has resulted in a poor introduction of evidenced-based prehospital cardiac care, affecting vulnerable populations who may have otherwise benefited from receiving this level of care. Given the time-sensitive nature of STEMI management, and severely limited access to 'primary reperfusion', PHT resembles not only a logical but also appealing solution in the South African context.

Nurse Aide Retention in Nursing Homes.

BACKGROUND AND OBJECTIVES: The association of nurse aide retention with three quality indicators is examined. Retention is defined as the proportion of staff continuously employed in the same facility for a defined period of time. RESEARCH DESIGN AND METHODS: Data used in this investigation came from survey responses from 3,550 nursing facilities, Certification and Survey Provider Enhanced Reporting data, and the Area Resource File. Staffing characteristics, quality indicators, facility, and market information from these data sources were all measured in 2016. Nurse aide retention was measured at 1, 2, and 3 years of employment. The quality indicators examined were a count of all deficiency citations, quality of care deficiency citations, and J, K, L deficiency citations. Negative binomial regression analyses were used to study the associations between the three different retention measures and these three quality indicators. RESULTS: The 1-, 2-, and 3-year nurse aide retention measures were 53.2%, 41.4%, and 36.1%, respectively. The regression analyses show low levels of retention to be generally associated with poor performance on the three deficiency citation quality indicators examined. DISCUSSION AND IMPLICATIONS: The research presented starts to provide information on nurse aide retention as an important workforce challenge and its potential impact on quality. Retention may be an additional staffing characteristic of nursing facilities with substantial policy and practice relevance.

Effective Care Practices in Patients Receiving Prolonged Mechanical Ventilation. An Ethnographic Study.

Rationale: Patients receiving prolonged mechanical ventilation experience low survival rates and incur high healthcare costs. However, little is known about how to optimally organize and manage their care.Objectives: To identify a set of effective care practices for patients receiving prolonged mechanical ventilation.Methods: We performed a focused ethnographic evaluation at eight long-term acute care hospitals in the United States ranking in either the lowest or highest quartile of risk-adjusted mortality in at least four of the five years between 2007 and 2011.Measurements and Main Results: We conducted 329 hours of direct observation, 196 interviews, and 39 episodes of job shadowing. Data were analyzed using thematic content analysis and a positive-negative deviance approach. We found that high- and low-performing hospitals differed substantially in their approach to care. High-performing hospitals actively promoted interdisciplinary communication and coordination using a range of organizational practices, including factors related to leadership (e.g., leaders who communicate a culture of quality improvement), staffing (e.g., lower nurse-to-patient ratios and ready availability of psychologists and spiritual care providers), care protocols (e.g., specific yet flexible respiratory therapy-driven weaning protocols), team meetings (e.g., interdisciplinary meetings that include direct care providers), and the physical plant (e.g., large workstations that allow groups to interact). These practices were believed to facilitate care that is simultaneously goal directed and responsive to individual patient needs, leading to more successful liberation from mechanical ventilation and improved survival.Conclusions: High-performing long-term acute care hospitals employ several organizational practices that may be helpful in improving care for patients receiving prolonged mechanical ventilation.

Organizational and Geographic Nursing Home Characteristics Associated With Increasing Prevalence of Resident Obesity in the United States.

Nursing home resident obesity increases the complexity of nursing care, and nursing homes report avoiding residents with obesity when choosing which prospective residents to accept. The objective of this study was to examine the associations between nursing home obesity prevalence rate and nursing home organizational, staffing, resident, and geographic factors within a profit maximization framework. The study cohort included U.S. Centers for Medicare and Medicaid Services data from U.S. nursing homes in 2013. Study findings supported hypothesized associations between obesity prevalence rate and higher occupancy, higher bed capacity, and multi-facility affiliation, but findings did not support a relationship between obesity prevalence rate and for-profit status.