Uncharted paths: hospital networks in critical care

Examining Perinatal Regionalization in Practice: A Network Analysis of Maternal Transport in Georgia

Objective

The primary objective was to use network analysis to characterize maternal transport patterns in the state of Georgia and compare them with the state's designated perinatal regions (DPRs).

Study Design

Using 2017-2022 birth records in Georgia, we constructed network graphs of maternal transport routes among obstetric facilities. We used multivariate logistic regression to identify factors associated with inter-DPR transports. We applied a community-detection algorithm to cluster facilities and compared the clusters to Georgia's DPRs.

Results

Among 774 639 deliveries, 2 757 (0.36%) involved transports among obstetric facilities. 8 facility clusters were identified and strongly aligned with DPRs (p < 0.001). Inter-DRP transports tended to occur between neighboring DPRs and between facilities belonging to the same healthcare system (p < 0.001).

Conclusion

Network analysis reveals patterns of maternal transports among obstetric facilities. States can improve the design of perinatal regionalization systems by formalizing existing partnership among obstetric facilities.

Return to sender: Unraveling the role of structural and social network ties in patient sharing networks

Healthcare is increasingly delivered through networks of organizations. Well-structured patient sharing networks are known to have positive associations with the quality of delivered services. However, the drivers of patient sharing relations are rarely studied explicitly. In line with recent developments in network and integration theorizing, we hypothesize that structural and social network ties between organizations are uniquely associated with a higher number of shared patients. We test these hypotheses using a Bayesian zero-dispersed Poisson regression model within the Additive and Multiplicative Effects Framework based on administrative claims data from 732,122 dermatological patients from the Netherlands in 2017. Our results indicate that 2.6% of all dermatological patients are shared and that the amount of shared patients is significantly associated with structural (i.e. emergency contracts) and social (i.e. shared physicians) ties between organizations, confirming our hypotheses. We also find some evidence that patients are shared with more capable organizations. Our findings highlight the role of relational ties in the way health services are delivered. At the same time, they also raise some potential anti-trust concerns.

Evaluation of Orthopaedics and Traumatology Patients Referred From a Tertiary Hospital

Background This study aims to determine the rate of interhospital transfer, transfer diagnoses, where they were referred, and the reasons for the transfer of patients who presented to the emergency department and requested orthopaedic and traumatology consultations and to evaluate measures that may be effective in reducing the number of referrals for a more effective health service provision as a result of this information. Material and methods In this descriptive study, 59 patients were transferred to the emergency department of our hospital between January 1, 2019, and January 1, 2022, for whom orthopaedic and traumatology consultations were requested and for whom the orthopaedic physician requested transfer (training and research hospitals, university hospitals and private hospitals), and they were retrospectively evaluated. Results The ages of the study participants ranged from 1 to 91 years, with a mean age of 39.8 ± 20.9 years. Therefore, the majority of referred patients were male and Turkish citizens aged 18-65 years; there were no forensic cases; they were evaluated in the yellow area as a result of triage; and most of the transfers were from training and research hospitals and university hospitals, which are tertiary health institutions. On categorising patients based on their transfer diagnoses, it was found that patients with subtotal amputation of the finger were the most common among the referred patients. Conclusion To reduce the number of referrals, it is recommended to increase the standards in assistant training, especially in pelvis, acetabulum, and hand surgeries. It is also recommended to optimise material supply and skilled labour distribution.

Review of social networks of professionals in healthcare settings-where are we and what else is needed?

Background

Social Network Analysis (SNA) demonstrates great potential in exploring health professional relationships and improving care delivery, but there is no comprehensive overview of its utilization in healthcare settings. This review aims to provide an overview of the current state of knowledge regarding the use of SNA in understanding health professional relationships in different countries.

Methods

We conducted an umbrella review by searching eight academic databases and grey literature up to April 30, 2021, enhanced by citation searches. We completed study selection, data extraction and quality assessment using predetermined criteria. The information abstracted from the reviews was synthesized quantitatively, qualitatively and narratively.

Results

Thirteen reviews were included in this review, yielding 330 empirical studies. The degree of overlaps of empirical studies across included reviews was low (4.3 %), indicating a high diversity of included reviews and the necessity of this umbrella review. Evidence from low- and middle-income countries (LMIC), particularly Asian countries, was limited. The earliest review was published in 2010 and the latest in 2019. Six reviews focused on the construction or description of professional networks and seven reviews reported factors or influences of professional networks. We synthesized existing literature on social networks of health care professionals in the light of (i) theoretical frameworks, (ii) study design and data collection, (iii) network nodes, measures and analysis, and (iv) factors of professional networks and related outcomes. From the perspective of methodology, evidence lies mainly in cross-sectional study design and electronic data, especially administrative data showing “patient-sharing” relationships, which has become the dominant data collection method. The results about the impact of health professional networks on health-related consequences were often contradicting and not truly comparable.

Conclusions

Methodological limitations, inconsistent findings, and lack of evidence from LMIC imply an urgent need for further investigations. The potential for broader utilization of SNA among providers remains largely untapped and the findings of this review may contain important value for building optimal healthcare delivery networks.

PROSPERO registration number

The protocol was published and registered with PROSPERO, the International Prospective Register of Systematic Reviews (CRD42020205996).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12992-021-00772-7.

Making sense of the French public hospital system: a network-based approach to hospital clustering using unsupervised learning methods

BACKGROUND

Hospitals in the public and private sectors tend to join larger organizations to form hospital groups. This increasingly frequent mode of functioning raises the question of how countries should organize their health system, according to the interactions already present between their hospitals. The objective of this study was to identify distinctive profiles of French hospitals according to their characteristics and their role in the French hospital network.

METHODS

Data were extracted from the national hospital database for year 2016. The database was restricted to public hospitals that practiced medicine, surgery or obstetrics. Hospitals profiles were determined using the k-means method. The variables entered in the clustering algorithm were: the number of stays, the effective diversity of hospital activity, and a network-based mobility indicator (proportion of stays followed by another stay in a different hospital of the same Regional Hospital Group within 90 days).

RESULTS

Three hospital groups were identified by the clustering algorithm. The first group was constituted of 34 large hospitals (median 82,100 annual stays, interquartile range 69,004 - 117,774) with a very diverse activity. The second group contained medium-sized hospitals (with a median of 258 beds, interquartile range 164 - 377). The third group featured less diversity regarding the type of stay (with a mean of 8 effective activity domains, standard deviation 2.73), a smaller size and a higher proportion of patients that subsequently visited other hospitals (11%). The most frequent type of patient mobility occurred from the hospitals in group 2 to the hospitals in group 1 (29%). The reverse direction was less frequent (19%).

CONCLUSIONS

The French hospital network is organized around three categories of public hospitals, with an unbalanced and disassortative patient flow. This type of organization has implications for hospital planning and infectious diseases control.

The Role of a Statewide Critical Care Coordination Center in the Coronavirus Disease 2019 Pandemic-and Beyond

Public health emergencies, like the coronavirus disease 2019 pandemic, can cause unprecedented demand for critical care services. We describe statewide implementation of a critical care coordination center designed to optimize ICU utilization. To describe a centralized critical care coordination center designed to ensure appropriate intensive care resource allocation.

Assessment of Hospital Characteristics and Interhospital Transfer Patterns of Adults With Emergency General Surgery Conditions

Importance

Although patients with emergency general surgery (EGS) conditions frequently undergo interhospital transfers, the transfer patterns and associated factors are not well understood.

Objective

To examine whether patients with EGS conditions are consistently directed to hospitals with more resources and better outcomes.

Design, Setting, and Participants

This cohort study performed a network analysis of interhospital transfers among adults with EGS conditions from January 1 to December 31, 2016. The analysis used all-payer claims data from the 2016 Healthcare Cost and Utilization Project state inpatient and emergency department databases in 8 states. A total of 728 hospitals involving 85 415 transfers of 80 307 patients were included. Patients were eligible for inclusion if they were 18 years or older and had an acute care hospital encounter with a diagnosis of an EGS condition as defined by the American Association for the Surgery of Trauma. Data were analyzed from January 1, 2020, to June 17, 2021.

Exposures

Hospital-level measures of size (total bed capacity), resources (intensive care unit [ICU] bed capacity, teaching status, trauma center designation, and presence of trauma and/or surgical critical care fellowships), EGS volume (annual EGS encounters), and EGS outcomes (risk-adjusted failure to rescue and in-hospital mortality).

Main Outcomes and Measures

The main outcome was hospital-level centrality ratio, defined as the normalized number of incoming transfers divided by the number of outgoing transfers. A higher centrality ratio indicated more incoming transfers per outgoing transfer. Multivariable regression analysis was used to test the hypothesis that a higher hospital centrality ratio would be associated with more resources, higher volume, and better outcomes.

Results

Among 80 307 total patients, the median age was 63 years (interquartile range [IQR], 50-75 years); 52.1% of patients were male and 78.8% were White. The median number of outgoing and incoming transfers per hospital were 106 (IQR, 61-157) and 36 (IQR, 8-137), respectively. A higher log-transformed centrality ratio was associated with more resources, such as higher ICU capacity (eg, >25 beds vs 0-10 beds: β = 1.67 [95% CI, 1.16-2.17]; P < .001), and higher EGS volume (eg, quartile 4 [highest] vs quartile 1 [lowest]: β = 0.78 [95% CI, 0-1.57]; P = .01). However, a higher log-transformed centrality ratio was not associated with better outcomes, such as lower in-hospital mortality (eg, quartile 4 [highest] vs quartile 1 [lowest]: β = 0.30 [95% CI, -0.09 to 0.68]; P = .83) and lower failure to rescue (eg, quartile 4 [highest] vs quartile 1 [lowest]: β = -0.50 [95% CI, -1.13 to 0.12]; P = .27).

Conclusions and Relevance

In this study, EGS transfers were directed to high-volume hospitals with more resources but were not necessarily directed to hospitals with better clinical outcomes. Optimizing transfer destination in the interhospital transfer network has the potential to improve EGS outcomes.

[Influence of the blood gas composition and mechanical ventilation parameters of the medical evacuation prognosis of critically ill patients.]

The clinical estimation of the state of patient is one of the basic components of the checking of the state of patient, but more precise and more objective indices today become necessary. The arterial blood gases analysis helps to select the optimum regime of mechanical ventilation. The medical evacuation of the critically ill patients frequently requires the correction of the parameters of respiratory support. The conducted investigations showed that the prognostics of unfavorable outcome within the first three days from the moment of the medical evacuation are hypercapnia, which exists during the process of evacuation in spite of the correction of the parameters of mechanical ventilation, reduction in the saturation of the arterial blood. The forecast of the medical evacuation is located as well in the direct correlation with the manifestation of acidosis, and at the moment of the completion of the transfer of the patient the greatest prognostic significance they possess the low level of the partial tension of oxygen in the artery. The application of a portable express- analyzer of blood gases permits implementation of correction parameters of respiratory support and to increase quality and safety of the medical evacuation of patients.

Modeling peer effect modification by network strength: The diffusion of implantable cardioverter defibrillators in the US hospital network

We develop methodology that allows peer effects (also referred to as social influence and contagion) to be modified by the structural importance of the focal actor's position in the network. The methodology is first developed for a single peer effect and then extended to simultaneously model multiple peer-effects and their modifications by the structural importance of the focal actor. This work is motivated by the diffusion of implantable cardioverter defibrillators (ICDs) in patients with congestive heart failure across a cardiovascular disease patient-sharing network of United States hospitals. We apply the general methodology to estimate peer effects for the adoption of capability to implant ICDs, the number of ICD implants performed by hospitals that are capable, and the number of patients referred to other hospitals by noncapable hospitals. Applying our novel methodology to study ICD diffusion across hospitals, we find evidence that exposure to ICD-capable peer hospitals is strongly associated with the chance a hospital becomes ICD-capable and that the direction and magnitude of the association is extensively modified by the strength of that hospital's position in the network, even after controlling for effects of geography. Therefore, interhospital networks, rather than geography per se, may explain key patterns of regional variations in healthcare utilization.

Taking upstairs care outside

Background: Critical care is a clinically complex and resource intensive discipline, the world over. Consequently, the delivery of these services has been compounded by the need to sustain a specialized workforce, while maintaining consistent and high standards.1,2 The regionalization of critical care resources and the creation of referral networks has been one approach that has led to success in this area.2-7 However, as steps have been made towards regionalization, so too has the need to transfer patients between facilities in order to access these services. The effects of this are already apparent, where estimates in the United States have found that 1 in 20 patients requiring intensive and critical care resulted in transfer to another facility.2 The need for such transfers are equally varied as they are common and include: no critical care facilities at the referring facility; no staffed critical care bed availability at referring facility; requirements for expertise and/or specialists facilitates not available at referring site; and the repatriation of patients back to their original facility.6,8 An increase in the number of patients requiring the continuation of critical care in-transit has led to a need to expand the borders of traditional intensive care beyond the confines of the hospital. Such a concept fits with the assertions of Peter Safar, a pioneer of modern critical care, who proposed that critical care should not be defined by geographic location, but rather a set of principles designed to deliver appropriate and timely care to patients who need it.9 Specialised transfer services: The advent and implementation of critical care transfer and retrieval services has been the bridge to this divide, lying at the confluence of prehospital emergency care, in-hospital emergency medicine, and intensive care. Undertaking the transfer of a patient requiring the initiation or continuation of critical care is no simple task. Variations in patient type and severity of their medical condition, as well as the expectations of the transfer team are significant. Reports regarding the transfer of patients ranging from critical neonates, to the multi-comorbid geriatric; with complex underlying surgical and medical diagnoses; involving the concomitant administration of multiple vasoactive and sedative medications; with a variety of oxygenation and ventilation requirements, are commonplace in the literature.6,8,10-16 Consequently, moving these patients from the safety and security of one facility to another is an immense logistical challenge and fraught with risks. In addition to the severity of the patients underlying condition, limitations in space, personnel and equipment, as well an unpredictable operating environment are several of the potential hazards faced during the transfer of these patients. These hazards are evident in the incidence of adverse events found in the literature. Incorrect referral triage; inadequate transfer team; patients requiring stabilization prior to transfer; equipment and/or technical failures; adverse drug events and medication errors are amongst the most common reported events.6,8,10-17 Further to this, the movement of patients alone has in itself been shown to have an impact on a patient's baseline status, without the occurrence of negative or untoward events.10,13,15,16 As a result, patient safety and quality of care have become essential components of modern critical care transfer and retrieval services, with the role of clinical audit central to their ability to learn and improve from previous cases and events. The local solution: Despite the relatively small size of the State of Qatar, critical care transfer and retrieval has nonetheless become a necessity within the country's healthcare system. Figure 1 highlights the locations of the main hospitals. Starting in 2014, a dedicated program was initiated to facilitate the transfer and retrieval of critical care patients across the country.18 The Specialized High Acuity Adult Retrieval Program (SHAARP) is a joint initiative between the Hamad Medical Corporation Ambulance Service (HMCAS) and the Hamad Medical Corporation (HMC) Critical Care Network (CCN). It consists of a single dedicated purpose-built ambulance, manned and run 24 hours a day, seven days a week by a variety of staff from both HMCAS and the CCN and deployed primarily for the transfer and retrieval of critical care patients across Qatar.19 The program was further developed in 2016 and formalized under the Transfer and Retrieval division of the HMCAS, with dedicated HMCAS and CCN staff receiving bespoke training and continued education;18 the addition of specialized and dedicated communications staff for call taking, dispatch and monitoring; and focused governance and audit to maintain the highest quality of patient safety and quality of care. Since then, the program has seen considerable success and uptake within the country's health system. The activity of the unit echoes much of what can be found in the literature and further reinforces the need for such a specialized service, regardless of setting (Table 1). It further highlights the importance of the relationship and cooperation between the HMCAS and CCN regarding the expertise and resources that each component adds to the overall service. This is particularly evident in the expectations of the team regarding their duties of care whilst in transit. A significant proportion of the patients transferred by the program have required the maintenance of a high-level of care between facilities, under conditions that are far more challenging than that seen in any regular hospital ward or intensive care unit (Table 2). Conclusion: In modern healthcare, to deliver a consistent and high-level critical care service in any setting, the movement of patients is inevitable. However, in order to ensure the continuum of this level of care and maintain the highest standards of patient safety and quality of care in-transit, specialized transfer services are a necessity. The multidisciplinary nature of critical care transfer and retrieval dictates the cooperation between multiple in-hospital and out of hospital specialties and is a fundamental underlying concept in the success of such services.

Quality Improvement and Telemedicine Intensive Care Unit: A Perfect Match

The health care delivery system is complex. New technologies offer new treatment options. The process of quality improvement includes system re-engineering. Telemedicine intensive care is an evolving area of delivery. Its core characteristic is the need for a merger of human and machine activity. Optimal use of quality improvement tools can lead to improved patient-centered outcomes. This article outlines how quality improvement tools can be used to facilitate the patient-centered collaboration with a focus on defining evidence-practice gaps, developing actionable metrics, analyzing the impact of proposed interventions, quantifying resources, prioritizing improvement plans, evaluating results, and diffusing best practices.

A scoping review of patient-sharing network studies using administrative data

There is a robust literature examining social networks and health, which draws on the network traditions in sociology and statistics. However, the application of social network approaches to understand the organization of health care is less well understood. The objective of this work was to examine approaches to conceptualizing, measuring, and analyzing provider patient-sharing networks. These networks are constructed using administrative data in which pairs of physicians are considered connected if they both deliver care to the same patient. A scoping review of English language peer-reviewed articles in PubMed and Embase was conducted from inception to June 2017. Two reviewers evaluated article eligibility based upon inclusion criteria and abstracted relevant data into a database. The literature search identified 10,855 titles, of which 63 full-text articles were examined. Nine additional papers identified by reviewing article references and authors were examined. Of the 49 papers that met criteria for study inclusion, 39 used a cross-sectional study design, 6 used a cohort design, and 4 were longitudinal. We found that studies most commonly theorized that networks reflected aspects of collaboration or coordination. Less commonly, studies drew on the strength of weak ties or diffusion of innovation frameworks. A total of 180 social network measures were used to describe the networks of individual providers, provider pairs and triads, the network as a whole, and patients. The literature on patient-sharing relationships between providers is marked by a diversity of measures and approaches. We highlight key considerations in network identification including the definition of network ties, setting geographic boundaries, and identifying clusters of providers, and discuss gaps for future study.

Characteristics and outcomes of accidental hypothermia in Japan: the J-Point registry

BACKGROUND

Accidental hypothermia (AH) has higher incidence and mortality in geriatric populations. Japan has a rapidly ageing population, and little is known about the epidemiology of hypothermia in this country.

METHODS

We created an AH registry based on retrospective review of patients visiting the ED of 12 institutions with temperature ≤35°C between April 2011 and March 2016. The severity of AH was classified as mild (≤35, ≥32°C), moderate (<32, ≥28°C) or severe (<28°C). The relationship between in-hospital mortality and severity of AH was assessed using a multivariable logistic regression analysis.

RESULTS

A total of 572 patients were registered in this registry and 537 patients were eligible for our analysis. The median age was 79 (IQR 66-87) years and the proportion of men was 51.2% (273/537). AH was more likely to occur in elderly patients aged ≥65 years (424/537, 80.0%) and in indoor settings (418/537, 77.8%). The condition most frequently associated with AH, irrespective of severity, was acute medical illness. A lower mean outside temperature was associated with a higher prevalence of AH, and particularly severe AH (p for trend <0.001). The overall proportion of cases resulting in in-hospital death was 24.4% (131/537), with no significant difference between severity levels observed in a multivariable logistic regression analysis (severe group (37/118, 31.4%) vs mild group (42/192, 21.9%), adjusted OR (AOR) 1.01, 95% CI 0.61 to 1.68; and moderate group (52/227, 22.9%) vs mild group, AOR 1.11, 95% CI 0.58 to 2.14).

CONCLUSION

Active prevention and intervention should occur for this important public health issue.

Strategic proposal for a national trauma system in France

In this road map for trauma in France, we focus on the main challenges for system implementation, surgical and radiology training and upon innovative training techniques. Regarding system organisation: procedures for triage, designation and certification of trauma centres are mandatory to implement trauma networks on a national scale. Data collection with registries must be created, with a core dataset defined and applied through all registries. Regarding surgical and radiology training, diagnostic-imaging processes should be standardised and the role of the interventional radiologist within the trauma team and the trauma network should be clearly defined. Education in surgery for trauma is crucial and recent changes in medical training in France will promote trauma surgery as a specific sub-specialty. Innovative training techniques should be implemented and be based on common objectives, scenarios and evaluation, so as to improve individual and team performances. The group formulated 14 proposals that should help to structure and improve major trauma management in France over the next 10 years.

Exploring the networking behaviors of hospital organizations

Background

Despite an extensive body of knowledge exists on network outcomes and on how hospital network structures may contribute to the creation of outcomes at different levels of analysis, less attention has been paid to understanding how and why hospital organizational networks evolve and change. The aim of this paper is to study the dynamics of networking behaviors of hospital organizations.

Methods

Stochastic actor-based model for network dynamics was used to quantitatively examine data covering six-years of patient transfer relations among 35 hospital organizations. Specifically, the study investigated about determinants of patient transfer evolution modeling partner selection choice as a combination of multiple organizational attributes and endogenous network-based processes.

Results

The results indicate that having overlapping specialties and treating patients with the same case-mix decrease the likelihood of observing network ties between hospitals. Also, results revealed as geographical proximity and membership of the same LHA have a positive impact on the networking behavior of hospitals organizations, there is a propensity in the network to choose larger hospitals as partners, and to transfer patients between hospitals facing similar levels of operational uncertainty.

Conclusions

Organizational attributes (overlapping specialties and case-mix), institutional factors (LHA), and geographical proximity matter in the formation and shaping of hospital networks over time. Managers can benefit from the use of these findings by clearly identifying the role and strategic positioning of their hospital with respect to the entire network. Social network analysis can yield novel information and also aid policy makers in the formation of interventions, encouraging alliances among providers as well as planning health system restructuring.

The role of the anaesthesiologist in air ambulance medicine

PURPOSE OF REVIEW

The care administered on air ambulances has become increasing complex. This has led to a discussion among experts as to whether air ambulance travel should be manned by physicians. This review provides evidence in support of anaesthesiologists being the physician-leaders in air ambulance medicine, because of their training in advanced airway management, critical care, and resuscitation.

RECENT FINDINGS

Successful prehospital care requires the ability to perform a complex set of advanced diagnostics and interventions. These include airway management, haemorrhage control, pain management, point-of-care diagnostics, complex interfacility transport, and advanced interventions. This skill set closely mirrors the training and expertise of anaesthesiologists.

SUMMARY

There are few studies investigating the specific benefit of anaesthesiologists in air ambulance medicine. However, current evidence indicates that their presence does improve patient care and safety. Future studies on this topic should use evidence-based quality indicators and standardized data sets to seek answers to optimal staffing of air ambulance teams.

Applications of network analysis to routinely collected health care data: a systematic review

Objective

To survey network analyses of datasets collected in the course of routine operations in health care settings and identify driving questions, methods, needs, and potential for future research.

Materials and Methods

A search strategy was designed to find studies that applied network analysis to routinely collected health care datasets and was adapted to 3 bibliographic databases. The results were grouped according to a thematic analysis of their settings, objectives, data, and methods. Each group received a methodological synthesis.

Results

The search found 189 distinct studies reported before August 2016. We manually partitioned the sample into 4 groups, which investigated institutional exchange, physician collaboration, clinical co-occurrence, and workplace interaction networks. Several robust and ongoing research programs were discerned within (and sometimes across) the groups. Little interaction was observed between these programs, despite conceptual and methodological similarities.

Discussion

We use the literature sample to inform a discussion of good practice at this methodological interface, including the concordance of motivations, study design, data, and tools and the validation and standardization of techniques. We then highlight instances of positive feedback between methodological development and knowledge domains and assess the overall cohesion of the sample.

Analysis of the U.S. patient referral network

In this paper, we analyze the US Patient Referral Network (also called the Shared Patient Network) and various subnetworks for the years 2009 to 2015. In these networks, two physicians are linked if a patient encounters both of them within a specified time interval, according to the data made available by the Centers for Medicare and Medicaid Services. We find power law distributions on most state-level data as well as a core-periphery structure. On a national and state level, we discover a so-called small-world structure as well as a "gravity law" of the type found in some large-scale economic networks. Some physicians play the role of hubs for interstate referral. Strong correlations between certain network statistics with health care system statistics at both the state and national levels are discovered. The patterns in the referral network evinced using several statistical analyses involving key metrics derived from the network illustrate the potential for using network analysis to provide new insights into the health care system and opportunities or mechanisms for catalyzing improvements.

Impact of Telemedicine Monitoring of Community ICUs on Interhospital Transfers

OBJECTIVES

To study the effects of tele-ICU monitoring on interhospital transfers from community-based ICUs to the quaternary care hospital at Mayo Clinic, Rochester, MN.

DESIGN

This is a retrospective review of data on interhospital transfers comparing trends prior to tele-ICU implementation to those following implementation.

SETTING

Tele-ICU programs are increasingly utilized to fill resource gaps in caring for critically ill patients. How such programs impact population and bed management within a healthcare system are not known. Mayo Clinic serves as quaternary referral care center for hospitals in the region within the Mayo Clinic Health System. In August 2013, we implemented tele-ICU monitoring at six Mayo Clinic Health System hospital ICUs.

SUBJECTS

All adult ICU admissions during the study period (preimplementation phase: January 1, 2012, to December 31, 2012; and postimplementation phase: January 1, 2014, to December 31, 2014) in any of the six specified community ICUs were included in the study.

MEASUREMENTS AND MAIN RESULTS

Interhospital transfers significantly increased post institution of tele-ICU (p = 0.040) and was attributed primarily to transfer from less specialized ICUs (p = 0.037) as compared with more resource-intensive ICUs (p = 0.88). However, for such patient transfers, there were no significant differences before and after severity of illness scores, ICU mortality, or inhospital mortality.

CONCLUSION

In a regional healthcare system, implementation of a tele-ICU program is associated with an increase in interhospital transfers from less resourced ICUs to the referral center, a trend that is not readily explained by increased severity of illness.

Influence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections

Antibiotic-resistant bacterial infections are a substantial source of morbidity and mortality and have a common reservoir in inpatient settings. Transferring patients between facilities could be a mechanism for the spread of these infections. We wanted to assess whether a network of hospitals, linked by inpatient transfers, contributes to the spread of nosocomial infections and investigate how network structure may be leveraged to design efficient surveillance systems. We construct a network defined by the transfer of Medicare patients across US inpatient facilities using a 100% sample of inpatient discharge claims from 2006-2007. We show the association between network structure and C. difficile incidence, with a 1% increase in a facility's C. difficile incidence being associated with a 0.53% increase in C. difficile incidence of neighboring facilities. Finally, we used network science methods to determine the facilities to monitor to maximize surveillance efficiency. An optimal surveillance strategy for selecting "sensor" hospitals, based on their network position, detects 80% of the C. difficile infections using only 2% of hospitals as sensors. Selecting a small fraction of facilities as "sensors" could be a cost-effective mechanism to monitor emerging nosocomial infections.

Exploring interhospital transfers and partnerships in the hospital sector in New South Wales, Australia

Objective The aim of the present study was to explore characteristics of interhospital transfers (IHT) and sharing of care among hospitals in New South Wales (NSW), Australia. Methods Data were extracted from patient-level linked hospital administrative datasets for separations from all NSW acute care hospitals from 1 July 2013 to 30 June 2015. Patient discharge and arrival information was used to identify IHTs. Characteristics of patients and related hospitals were then analysed. Results Transfer-in patients accounted for 3.9% of all NSW admitted patients and, overall, 7.3% of NSW admissions were associated with transfers (IHT rate). Patients with injuries and circulatory system diseases had the highest IHT rate, accounting for one-third of all IHTs. Patients were more often transferred to larger than smaller hospitals (61% vs 29%). Compared with private hospitals, public hospitals had a higher IHT rate (8.4% vs 5.1%) and a greater proportion of transfer-out IHTs (52% vs 28%). Larger public hospitals had lower IHT rates (3–8%) compared with smaller public hospitals (13–26%). Larger public hospitals received and retransferred higher proportions of IHT patients (52–58% and 11% respectively) than their smaller counterparts (26–30% and 2–3% respectively). Less than one-quarter of IHTs were between the public and private sectors or between government health regions. The number of interacting hospitals and their interactions varied across hospital peer groups. Conclusion NSW IHTs were often to hospitals with greater speciality services. The patterns of interhospital interactions could be affected by organisational and regional preferences. What is known about the topic? IHTs aim to provide efficient and effective care. Nonetheless, information on transfers and the sharing of care among hospitals in an Australian setting is lacking. Studies of transfers and hospital partnership patterns will inform efforts to improve patient-centred transfers and hospital accountability in terms of end outcomes for patients. What does this paper add? Transfer-in patients accounted for 3.9% of all NSW admissions; they were often (61%) transferred to hospitals with greater speciality services. The number of IHTs and sharing of care among hospitals varied across hospital peer groups, and could have been affected by organisational and regional preferences. What are the implications for practitioners? The findings of the present study suggest that different patterns of IHTs may not only have resulted from clinical priorities, but that organisational and regional preferences are also likely to be influential factors. Patient-centred IHTs and the development of guidelines need to be pursued to enhance the care and functionality of healthcare. Patient sharing should be acknowledged in hospital and regional performance profiling.

Understanding specialist sharing: A mixed-method exploration in an increasingly price-competitive hospital market

INTRODUCTION

Medical specialists seem to increasingly work in- and be affiliated to- multiple organizations. We define this phenomenon as specialist sharing. This form of inter-organizational cooperation has received scant scholarly attention. We investigate the extent of- and motives behind- specialist sharing, in the price-competitive hospital market of the Netherlands.

METHODS

A mixed-method was adopted. Social network analysis was used to quantitatively examine the extent of the phenomenon. The affiliations of more than 15,000 medical specialists to any Dutch hospital were transformed into 27 inter-hospital networks, one for each medical specialty, in 2013 and in 2015. Between February 2014 and February 2016, 24 semi-structured interviews with 20 specialists from 13 medical specialties and four hospital executives were conducted to provide in-depth qualitative insights regarding the personal and organizational motives behind the phenomenon.

RESULTS

Roughly, 20% of all medical specialists are affiliated to multiple hospitals. The phenomenon occurs in all medical specialties and all Dutch hospitals share medical specialists. Rates of specialist sharing have increased significantly between 2013 and 2015 in 14 of the 27 specialties. Personal motives predominantly include learning, efficiency, and financial benefits. Increased workload and discontinuity of care are perceived as potential drawbacks. Hospitals possess the final authority to decide whether and which specialists are shared. Adhering to volume norms and strategic considerations are seen as their main drivers to share specialists.

DISCUSSION

We conclude that specialist sharing should be interpreted as a form of inter-organizational cooperation between healthcare organizations, facilitating knowledge flow between them. Although quality improvement is an important perceived factor underpinning specialist sharing, evidence of enhanced quality of care is anecdotal. Additionally, the widespread occurrence of the phenomenon and the underlying strategic considerations could pose an antitrust infringement.

Critical Care Medicine Beds, Use, Occupancy, and Costs in the United States: A Methodological Review

This article is a methodological review to help the intensivist gain insights into the classic and sometimes arcane maze of national databases and methodologies used to determine and analyze the ICU bed supply, use, occupancy, and costs in the United States. Data for total ICU beds, use, and occupancy can be derived from two large national healthcare databases: the Healthcare Cost Report Information System maintained by the federal Centers for Medicare and Medicaid Services and the proprietary Hospital Statistics of the American Hospital Association. Two costing methodologies can be used to calculate U.S. ICU costs: the Russell equation and national projections. Both methods are based on cost and use data from the national hospital datasets or from defined groups of hospitals or patients. At the national level, an understanding of U.S. ICU bed supply, use, occupancy, and costs helps provide clarity to the width and scope of the critical care medicine enterprise within the U.S. healthcare system. This review will also help the intensivist better understand published studies on administrative topics related to critical care medicine and be better prepared to participate in their own local hospital organizations or regional critical care medicine programs.

Effect of hospital referral networks on patient readmissions

Previous studies have shown that referral networks encompass important mechanisms of coordination and integration among hospitals, which enhance numerous organizational-level benefits, such as productivity, efficiency, and quality of care. The present study advances previous research by demonstrating how hospital referral networks influence patient readmissions. Data include 360,697 hospitalization events within a regional community of hospitals in the Italian National Health Service. Multilevel hierarchical regression analysis tests the impacts of referral networks' structural characteristics on patient hospital readmissions. The results demonstrate that organizational centrality in the overall referral network and ego-network density have opposing effects on the likelihood of readmission events within hospitals; greater centrality is negatively associated with readmissions, whereas greater ego-network density increases the likelihood of readmission events. Our findings support the (re)organization of healthcare systems and provide important indications for policymakers and practitioners.

Transferring the critically ill patient: are we there yet?

During the past few decades the numbers of ICUs and beds has increased significantly, but so too has the demand for intensive care. Currently large, and increasing, numbers of critically ill patients require transfer between critical care units. Inter-unit transfer poses significant risks to critically ill patients, particularly those requiring multiple organ support. While the safety and quality of inter-unit and hospital transfers appear to have improved over the years, the effectiveness of specific measures to improve safety have not been confirmed by randomized controlled trials. It is generally accepted that critically ill patients should be transferred by specialized retrieval teams, but the composition, training and assessment of these teams is still a matter of debate. Since it is likely that the numbers and complexity of these transfers will increase in the near future, further studies are warranted.

System-level planning, coordination, and communication: care of the critically ill and injured during pandemics and disasters: CHEST consensus statement

BACKGROUND

System-level planning involves uniting hospitals and health systems, local/regional government agencies, emergency medical services, and other health-care entities involved in coordinating and enabling care in a major disaster. We reviewed the literature and sought expert opinions concerning system-level planning and engagement for mass critical care due to disasters or pandemics and offer suggestions for system-planning, coordination, communication, and response. The suggestions in this chapter are important for all of those involved in a pandemic or disaster with multiple critically ill or injured patients, including front-line clinicians, hospital administrators, and public health or government officials.

METHODS

The American College of Chest Physicians (CHEST) consensus statement development process was followed in developing suggestions. Task Force members met in person to develop nine key questions believed to be most relevant for system-planning, coordination, and communication. A systematic literature review was then performed for relevant articles and documents, reports, and other publications reported since 1993. No studies of sufficient quality were identified upon which to make evidence-based recommendations. Therefore, the panel developed expert opinion-based suggestions using a modified Delphi process.

RESULTS

Suggestions were developed and grouped according to the following thematic elements: (1) national government support of health-care coalitions/regional health authorities (HC/RHAs), (2) teamwork within HC/RHAs, (3) system-level communication, (4) system-level surge capacity and capability, (5) pediatric patients and special populations, (6) HC/RHAs and networks, (7) models of advanced regional care systems, and (8) the use of simulation for preparedness and planning.

CONCLUSIONS

System-level planning is essential to provide care for large numbers of critically ill patients because of disaster or pandemic. It also entails a departure from the routine, independent system and involves all levels from health-care institutions to regional health authorities. National government support is critical, as are robust communication systems and advanced planning supported by realistic exercises.

Improved analgesia, sedation, and delirium protocol associated with decreased duration of delirium and mechanical ventilation

RATIONALE

Introduction of sedation protocols has been associated with improved patient outcomes. It is not known if an update to an existing high-quality sedation protocol, featuring increased patient assessment and reduced benzodiazepine exposure, is associated with improved patient process and outcome quality metrics.

METHODS

This was an observational before (n = 703) and after (n = 780) cohort study of mechanically ventilated patients in a 24-bed trauma-surgical intensive care unit (ICU) from 2009 to 2011. The three main protocol updates were: (1) requirement to document Richmond Agitation Sedation Scale (RASS) scores every 4 hours, (2) requirement to document Confusion Assessment Method-ICU (CAM ICU) twice daily, and (3) systematic, protocolized deescalation of excess sedation. Multivariable linear regression was used for the primary analysis. The primary outcome was the duration of mechanical ventilation. Prespecified secondary endpoints included days of delirium; the frequency of patient assessment with the RASS and CAM-ICU instruments; benzodiazepine dosing; durations of mechanical ventilation, ICU stay, and hospitalization; and hospital mortality and ventilator associated pneumonia rate.

RESULTS

Patients in the updated protocol cohort had 1.22 more RASS assessments per day (5.38 vs. 4.16; 95% confidence interval [CI], 1.05-1.39; P < 0.01) and 1.15 more CAM-ICU assessments per day (1.49 vs. 0.35; 95% CI, 1.08-1.21; P < 0.01) than the baseline cohort. The mean hourly benzodiazepine dose decreased by 34.8% (0.08 mg lorazepam equivalents/h; 0.15 vs. 0.23; P < 0.01). In the multivariable model, the median duration of mechanical ventilation decreased by 17.6% (95% CI, 0.6-31.7%; P = 0.04). The overall odds ratio of delirium was 0.67 (95% CI, 0.49-0.91; P = 0.01) comparing updated versus baseline cohort. A 12.4% reduction in median duration of ICU stay (95% CI, 0.5-22.8%; P = 0.04) and a 14.0% reduction in median duration of hospitalization (95% CI, 2.0-24.5%; P = 0.02) were also seen. No significant association with mortality (odds ratio, 1.18; 95% CI, 0.80-1.76; P = 0.40) was seen.

CONCLUSIONS

Implementation of an updated ICU analgesia, sedation, and delirium protocol was associated with an increase in RASS and CAM-ICU assessment and documentation; reduced hourly benzodiazepine dose; and decreased delirium and median durations of mechanical ventilation, ICU stay, and hospitalization.

Engagement and education: care of the critically ill and injured during pandemics and disasters: CHEST consensus statement

BACKGROUND

Engagement and education of ICU clinicians in disaster preparedness is fragmented by time constraints and institutional barriers and frequently occurs during a disaster. We reviewed the existing literature from 2007 to April 2013 and expert opinions about clinician engagement and education for critical care during a pandemic or disaster and offer suggestions for integrating ICU clinicians into planning and response. The suggestions in this article are important for all of those involved in a pandemic or large-scale disaster with multiple critically ill or injured patients, including front-line clinicians, hospital administrators, and public health or government officials.

METHODS

A systematic literature review was performed and suggestions formulated according to the American College of Chest Physicians (CHEST) Consensus Statement development methodology. We assessed articles, documents, reports, and gray literature reported since 2007. Following expert-informed sorting and review of the literature, key priority areas and questions were developed. No studies of sufficient quality were identified upon which to make evidence-based recommendations. Therefore, the panel developed expert opinion-based suggestions using a modified Delphi process.

RESULTS

Twenty-three suggestions were formulated based on literature-informed consensus opinion. These suggestions are grouped according to the following thematic elements: (1) situational awareness, (2) clinician roles and responsibilities, (3) education, and (4) community engagement. Together, these four elements are considered to form the basis for effective ICU clinician engagement for mass critical care.

CONCLUSIONS

The optimal engagement of the ICU clinical team in caring for large numbers of critically ill patients due to a pandemic or disaster will require a departure from the routine independent systems operating in hospitals. An effective response will require robust information systems; coordination among clinicians, hospitals, and governmental organizations; pre-event engagement of relevant stakeholders; and standardized core competencies for the education and training of critical care clinicians.

Quality of care and interhospital collaboration: a study of patient transfers in Italy

OBJECTIVES

We examine the dynamics of patient-sharing relations within an Italian regional community of 35 hospitals serving approximately 1,300,000 people. We test whether interorganizational relations provide individual patients access to higher quality providers of care.

RESEARCH DESIGN AND METHODS

We reconstruct the complete temporal sequence of the 3461 consecutive interhospital patient-sharing events observed between each pair of hospitals in the community during 2005-2008. We distinguish between transfers occurring between and within different medical specialties. We estimate newly derived models for relational event sequences that allow us to control for the most common forms of network-like dependencies that are known to characterize collaborative relations between hospitals. We use 45-day risk-adjusted readmission rate as a proxy for hospital quality.

RESULTS

After controls (eg, geographical distance, size, and the existence of prior collaborative relations), we find that patients flow from less to more capable hospitals. We show that this result holds for patient being shared both between as well as within medical specialties. Nonetheless there are strong and persistent other organizational and relational effects driving transfers.

CONCLUSIONS

Decentralized patient-sharing decisions taken by the 35 hospitals give rise to a system of collaborative interorganizational arrangements that allow the patient to access hospitals delivering a higher quality of care. This result is relevant for health care policy because it suggests that collaborative relations between hospitals may produce desirable outcomes both for individual patients, and for regional health care systems.

ICU occupancy and mechanical ventilator use in the United States

OBJECTIVES

Detailed data on occupancy and use of mechanical ventilators in U. S. ICU over time and across unit types are lacking. We sought to describe the hourly bed occupancy and use of ventilators in U.S. ICUs to improve future planning of both the routine and disaster provision of intensive care.

DESIGN

Retrospective cohort study. We calculated mean hourly bed occupancy in each ICU and hourly bed occupancy for patients on mechanical ventilators. We assessed trends in overall occupancy over the 3 years. We also assessed occupancy and mechanical ventilation rates across different types and sizes of ICUs.

SETTING

Ninety-seven U.S. ICUs participating in Project IMPACT from 2005 to 2007.

PATIENTS

A total of 226,942 consecutive admissions to ICUs.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Over the 3 years studied, total ICU occupancy ranged from 57.4% to 82.1% and the number of beds filled with mechanically ventilated patients ranged from 20.7% to 38.9%. There was no change in occupancy across years and no increase in occupancy during influenza seasons. Mean hourly occupancy across ICUs was 68.2% ± 21.3% (SD) and was substantially higher in ICUs with fewer beds (mean, 75.8% ± 16.5% for 5-14 beds vs 60.9% ± 22.1% for 20+ beds, p = 0.001) and in academic hospitals (78.7% ± 15.9% vs 65.3% ± 21.3% for community not-for-profit hospitals, p < 0.001). More than half of ICUs (53.6%) had 4+ beds available more than half the time. The mean percentage of ICU patients receiving mechanical ventilation in any given hour was 39.5% (± 15.2%), and a mean of 29.0% (± 15.9%) of ICU beds were filled with a patient on a ventilator.

CONCLUSIONS

Occupancy of U.S. ICUs was stable over time, but there is uneven distribution across different types and sizes of units. Only three of 10 beds were filled at any time with mechanically ventilated patients, suggesting substantial surge capacity throughout the system to care for acutely critically ill patients.

Dispersal of antibiotic-resistant high-risk clones by hospital networks: changing the patient direction can make all the difference

BACKGROUND

Patients who seek treatment in hospitals can introduce high-risk clones of hospital-acquired, antibiotic-resistant pathogens from previous admissions. In this manner, different healthcare institutions become linked epidemiologically. All links combined form the national patient referral network, through which high-risk clones can propagate.

AIM

To assess the influence of changes in referral patterns and network structure on the dispersal of these pathogens.

METHODS

Hospital admission data were mapped to reconstruct the English patient referral network, and 12 geographically distinct healthcare collectives were identified. The number of patients admitted and referred to hospitals outside their collective was measured. Simulation models were used to assess the influence of changing network structure on the spread of hospital-acquired pathogens.

FINDINGS

Simulation models showed that decreasing the number of between-collective referrals by redirecting, on average, just 1.5 patients/hospital/day had a strong effect on dispersal. By decreasing the number of between-collective referrals, the spread of high-risk clones through the network can be reduced by 36%. Conversely, by creating supra-regional specialist centres that provide specialist care at national level, the rate of dispersal can increase by 48%.

CONCLUSION

The structure of the patient referral network has a profound effect on the epidemic behaviour of high-risk clones. Any changes that affect the number of referrals between healthcare collectives, inevitably affect the national dispersal of these pathogens. These effects should be taken into account when creating national specialist centres, which may jeopardize control efforts.

Impact of bed availability on requesting and offering in-hospital intensive care unit transfers: a survey study of generalists and intensivists

PURPOSE

To evaluate whether bed availability affects a physician's decision to request or offer an intensive care unit (ICU) transfer.

MATERIALS AND METHODS

We administered mail-based surveys to determine the respondents' probability of either requesting an ICU transfer (generalist respondents) or offering an ICU transfer (intensivist respondents). Respondents randomly received clinical vignettes that were identical except for the number of available ICU beds (one or seven available ICU beds). Respondents also made predictions about the patient's outcomes.

RESULTS

Among generalists and intensivists, there were wide ranges in decisions about ICU transfer. In the Generalist ICU request study, the average probability of transfer with one versus seven available ICU beds was 52.2% and 58.5% (P = .41), respectively. In the Intensivist ICU offer study, the average probability of transfer with one versus seven available ICU beds was 62.5% and 57.4% (P = .24), respectively. The most consistent association with decisions about ICU transfer was the predicted probability that a patient would require an ICU bed in the future if not transferred currently.

CONCLUSIONS

There is high variability in the decision to request or offer ICU beds. There was not a significant association between bed availability and ICU transfer decisions.

International comparisons of intensive care: informing outcomes and improving standards

PURPOSE OF REVIEW

Interest in international comparisons of critical illness is growing, but the utility of these studies is questionable. This review examines the challenges of international comparisons and highlights areas in which international data provide information relevant to clinical practice and resource allocation.

RECENT FINDINGS

International comparisons of ICU resources demonstrate that definitions of critical illness and ICU beds vary due to differences in ability to provide organ support and variable staffing. Despite these limitations, recent international data provide key information to understand the pros and cons of different availability of ICU beds on patient flow and outcomes, and also highlight the need to ensure long-term follow-up due to heterogeneity in discharge practices for critically ill patients. With increasing emphasis on curbing costs of healthcare, systems that deliver lower cost care provide data on alternative options, such as regionalization, flexible allocation of beds, and bed rationing.

SUMMARY

Differences in provision of critical care can be leveraged to inform decisions on allocation of ICU beds, improve interpretation of clinical outcomes, and assess ways to decrease costs of care. International definitions of key components of critical care are needed to facilitate research and ensure rigorous comparisons.

Reasons underlying interhospital transfers to an academic medical intensive care unit

PURPOSE

Interhospital critical care transfers are common, yet few studies address the underlying reasons for transfers. We examined clinician and patient/surrogate perceptions about interhospital transfers and assessed their agreement on these transfers.

MATERIALS AND METHODS

This is a mixed-mode survey of 3 major stakeholders in interhospital transfers to an academic medical intensive care unit from August 2007 to April 2008.

RESULTS

Sixty-two hospitals transferred 138 patients during the study period. Response rates varied among stakeholders (accepting physician, 90%; referring physicians, 20%; patients/surrogates, 33%). All 3 groups frequently endorsed quality of care and need for a specific test/procedure as important. Referring hospital reputation and quality were rarely endorsed. Accepting physicians and patients/surrogates substantially agreed on the need for a specific test (κ = 0.70) and increased survival (κ = 0.78) but, otherwise, had fair to poor agreement. Referring physicians and patients/surrogates rarely agreed and sometimes disagreed greater than expected by chance (κ < 0). Physician pairs strongly agreed on the importance of accepting hospital experience (κ = 0.96) but agreed less on patient satisfaction at the referring hospital (κ = 0.37) and referring hospital reputation (κ = 0.35).

CONCLUSIONS

Stakeholders do not always agree on the reasons for critical care transfers. Efforts to improve communication are warranted to ensure informed patient choices.

Variation in patient-sharing networks of physicians across the United States

CONTEXT

Physicians are embedded in informal networks that result from their sharing of patients, information, and behaviors.

OBJECTIVES

To identify professional networks among physicians, examine how such networks vary across geographic regions, and determine factors associated with physician connections.

DESIGN, SETTING, AND PARTICIPANTS

Using methods adopted from social network analysis, Medicare administrative data from 2006 were used to study 4,586,044 Medicare beneficiaries seen by 68,288 physicians practicing in 51 hospital referral regions (HRRs). Distinct networks depicting connections between physicians (defined based on shared patients) were constructed for each of the 51 HRRs.

MAIN OUTCOMES MEASURES

Variation in network characteristics across HRRs and factors associated with physicians being connected.

RESULTS

The number of physicians per HRR ranged from 135 in Minot, North Dakota, to 8197 in Boston, Massachusetts. There was substantial variation in network characteristics across HRRs. For example, the mean (SD) adjusted degree (number of other physicians each physician was connected to per 100 Medicare beneficiaries) across all HRRs was 27.3 (range, 11.7-54.4); also, primary care physician relative centrality (how central primary care physicians were in the network relative to other physicians) ranged from 0.19 to 1.06, suggesting that primary care physicians were more than 5 times more central in some markets than in others. Physicians with ties to each other were far more likely to be based at the same hospital (69.2% of unconnected physician pairs vs 96.0% of connected physician pairs; adjusted rate ratio, 0.12 [95% CI, 0.12-0.12]; P < .001), and were in closer geographic proximity (mean office distance of 21.1 km for those with connections vs 38.7 km for those without connections, P < .001). Connected physicians also had more similar patient panels in terms of the race or illness burden than unconnected physicians. For instance, connected physician pairs had an average difference of 8.8 points in the percentage of black patients in their 2 patient panels compared with a difference of 14.0 percentage points for unconnected physician pairs (P < .001).

CONCLUSIONS

Network characteristics vary across geographic areas. Physicians tend to share patients with other physicians with similar physician-level and patient-panel characteristics.

Association between hospital volume and network membership and an analgesia, sedation and delirium order set quality score: a cohort study

Introduction

Protocols for the delivery of analgesia, sedation and delirium care of the critically ill, mechanically ventilated patient have been shown to improve outcomes but are not uniformly used. The extent to which elements of analgesia, sedation and delirium guidelines are incorporated into order sets at hospitals across a geographic area is not known. We hypothesized that both greater hospital volume and membership in a hospital network are associated with greater adherence of order sets to sedation guidelines.

Methods

Sedation order sets from all nonfederal hospitals without pediatric designation in Washington State that provided ongoing care to mechanically ventilated patients were collected and their content systematically abstracted. Hospital data were collected from Washington State sources and interviews with ICU leadership in each hospital. An expert-validated score of order set quality was created based on the 2002 four-society guidelines. Clustered multivariable linear regression was used to assess the relationship between hospital characteristics and the order set quality score.

Results

Fifty-one Washington State hospitals met the inclusion criteria and all provided order sets. Based on expert consensus, 21 elements were included in the analgesia, sedation and delirium order set quality score. Each element was equally weighted and contributed one point to the score. Hospital order set quality scores ranged from 0 to 19 (median = 8, interquartile range 6 to 14). In multivariable analysis, a greater number of acute care days (P = 0.01) and membership in a larger hospital network (P = 0.01) were independently associated with a greater quality score.

Conclusions

Hospital volume and membership in a larger hospital network were independently associated with a higher quality score for ICU analgesia, sedation and delirium order sets. Further research is needed to determine whether greater order-set quality is associated with improved outcomes in the critically ill. The development of critical care networks might be one strategy to improve order set quality scores.

Guided transfer of critically ill patients: where patients are transferred can be an informed choice

PURPOSE OF REVIEW

Given increasingly scarce healthcare resources and highly differentiated hospitals, with growing demand for critical care, interhospital transfer is an essential part of the care of many patients. The purpose of this review is to examine the extent to which hospital quality is considered when transferring critically ill patients, and to examine the potential benefits to patients of a strategy that incorporates objective quality data into referral patterns.

RECENT FINDINGS

Interhospital transfer of critically ill patients is now common and safe. Although extensive research has focused on which patients should be transferred and when they should be transferred, recent study has focused on where patients should be transferred. Yet, the choice of destination hospital is rarely recognized as a therapeutic choice with implications for patient outcomes. The recent public release of high-quality, risk-adjusted and reliability-adjusted outcome data for most hospitals now offers physicians an informed basis on which to choose to which destination hospital a patient should be transferred. A strategy of 'guided transfer' that integrates public quality information into critical care transfer decisions is now feasible.

SUMMARY

Although hospitals often transfer patients, there may be substantial room for improvement in transfer patterns. Guiding transfers on the basis of objective quality information may offer substantial benefits to patients, and could be incorporated into quality improvement initiatives.

Dynamic analysis of interhospital collaboration and competition: empirical evidence from an Italian regional health system

BACKGROUND

Policymakers stimulate competition in universalistic health-care systems while encouraging the formation of service provision networks among hospital organizations. This article addresses a gap in the extant literature by empirically analyzing simultaneous collaboration and competition between hospitals within the Italian National Health Service, where important procompetition reforms have been implemented.

PURPOSE

To explore how rising competition between hospitals relates to their propensity to collaborate with other local providers.

METHODS

Longitudinal data on interhospital collaboration and competition collected in an Italian region from 2003 to 2007 are analyzed. Social network analysis techniques are applied to study the structure and dynamics of interhospital collaboration. Negative binomial regressions are employed to explore how interhospital competition relates to the collaborative network over time.

RESULTS

Competition among providers does not hinder interhospital collaboration. Collaboration is primarily local, with resource complementarity and differentials in the volume of activity and hospital performance explaining the propensity to collaborate.

CONCLUSIONS

Formation of collaborative networks among hospitals is not hampered by reforms aimed at fostering market forces. Because procompetition reforms elicit peculiar forms of managed competition in universalistic health systems, studies are needed to clarify whether the positive association between interhospital competition and collaboration can be generalized to other health-care settings.

Limiting the spread of highly resistant hospital-acquired microorganisms via critical care transfers: a simulation study

PURPOSE

Hospital-acquired infections with highly resistant organisms are an important problem among critically ill patients. Control of these organisms has largely focused within individual hospitals. We examine the extent to which transfers of critically ill patients could be a vector for the wide spread of highly resistant organisms, and compare the efficiency of different approaches to targeting infection control resources.

METHODS

We analyzed the network of interhospital transfers of intensive care unit patients in 2005 US Medicare data and 2004-2006 Pennsylvania all-payer data. We simulated the spread of highly resistant hospital-acquired infections by randomly choosing a single hospital to develop a highly resistant organism and following the spread of infection or colonization throughout the network under varying strategies of infection control and varying levels of infectivity.

RESULTS

Critical care transfers could spread a highly resistant organism between any two US hospitals in a median of 3 years. Hospitals varied substantially in their importance to limiting potential spread. Targeting resources to a small subset of hospitals on the basis of their position in the transfer network was 16 times more efficient than distributing infection control resources uniformly. Within any set of targeted hospitals, the best strategy for infection control heavily concentrated resources at a few particularly important hospitals, regardless of level of infectivity.

CONCLUSIONS

Critical care transfers provide a plausible vector for widespread dissemination of highly resistant hospital-acquired microorganisms. Infection control efforts can be made more efficient by selectively targeting hospitals most important for transmission.

Race and timeliness of transfer for revascularization in patients with acute myocardial infarction

OBJECTIVES

Patients with acute myocardial infarction (AMI) who are admitted to hospitals without coronary revascularization are frequently transferred to hospitals with this capability. We sought to determine whether the timeliness of hospital transfer and quality of destination hospitals differed between black and white patients.

METHODS

We evaluated all white and black Medicare beneficiaries admitted with AMI at nonrevascularization hospitals in 2006 who were transferred to a revascularization hospital. We compared hospital length of stay before transfer and the transfer destination's 30-day risk-standardized mortality rate for AMI between black and white patients. We used hierarchical regression to adjust for patient characteristics and examine within and across-hospital effects of race on 30-day mortality and length of stay before transfer.

RESULTS

A total of 25,947 (42%) white and 2345 (37%) black patients with AMI were transferred from 857 urban and 774 rural nonrevascularization hospitals to 928 revascularization hospitals. Median (interquartile range) length of stay before transfer was 1 day (1 to 3 d) for white patients and 2 days (1 to 4 d) for black patients (P<0.001). In adjusted models, black patients tended to be transferred more slowly than white patients, a finding because of both across and within-hospital effects. For example, within a given urban hospital, black patients were transferred an additional 0.24 days (95% confidence interval 0.03-0.44 d) later than white patients. In addition, the lengths of stay before transfer for all patients at urban hospitals increased by 0.37 days (95% confidence interval 0.28-0.47 d) for every 20% increase in the proportion of AMI patients who were black. These results were attenuated in rural hospitals. The risk-standardized mortality rate of the revascularization hospital to which patients were ultimately sent did not differ between black and white patients.

CONCLUSIONS

Black patients are transferred more slowly to revascularization hospitals after AMI than white patients, resulting from both less timely transfers within hospitals and admission to hospitals with greater delays in transfer; however, 30-day mortality of the revascularization hospital to which both groups were sent to appeared similar. Race-based delays in transfer may contribute to known racial disparities in outcomes of AMI.

Which patients and where: a qualitative study of patient transfers from community hospitals

BACKGROUND

Interhospital transfer of patients is a routine part of the care at community hospitals, but the current process may lead to suboptimal patient outcomes. A microlevel analysis of the processes of patient transfer has not earlier been carried out.

RESEARCH DESIGN

We conducted semistructured qualitative interviews with care providers at 3 purposively sampled community hospitals to describe patient transfer mechanisms, focusing on perceptions of transfers and transfer candidates, choice of transfer destination, and perceived process. We interviewed physicians, nurses, and care technicians from emergency departments and intensive care units at the hospitals, and analyzed the resultant transcripts by content analysis.

RESULTS

Appropriate triage and the transfer of patients was a highly valued skill at the community hospitals. On the basis of participant accounts, the transfer process had 4 components: (1) Identifying transfer-eligible patients; (2) Identifying a destination hospital; (3) Negotiating the transfer; and (4) Accomplishing the transfer. There were common challenges at each component across hospitals. Protocolization of care was perceived to substantially facilitate transfers. Informal arrangements played a key role in the identification of the receiving hospital, but patient preferences and hospital quality were not discussed as important in decision making. The process of arranging a patient transfer placed a significant burden on the staff of community hospitals.

CONCLUSIONS

The patient transfer process is often cumbersome, varies by condition, and may not be focused on optimizing patient outcomes. Development of a more fluid transfer infrastructure may aid in implementing policies such as selective referral and regionalization.

Spatio-temporal Structure of US Critical Care Transfer Network

Most Americans are in Intensive Care Units (ICUs) at some point during their lives. There is wide variation in the outcome quality of ICUs and so, thousands of patients who die each year in ICUs may have survived if they were at the appropriate hospital. In spite of a policy agenda from IOM calling for effective transfer of patients to more capable hospitals to improve outcomes, there appear to be substantial inefficiencies in the existing system. In particular, patients recurrently transfer to secondary hospitals rather than to a most-preferred option. We present data mining schemes and significance tests to discover these inefficient cascades. We analyze critical care transfer data in Medicare across nearly 5,000 hospitals in the United States over 10 years and present evidence that these transfers to secondary hospitals repeatedly cascade across multiple transfers, and that some hospitals seem to be involved in many cascades.

Social network analysis of patient sharing among hospitals in Orange County, California

OBJECTIVES

We applied social network analyses to determine how hospitals within Orange County, California, are interconnected by patient sharing, a system which may have numerous public health implications.

METHODS

Our analyses considered 2 general patient-sharing networks: uninterrupted patient sharing (UPS; i.e., direct interhospital transfers) and total patient sharing (TPS; i.e., all interhospital patient sharing, including patients with intervening nonhospital stays). We considered these networks at 3 thresholds of patient sharing: at least 1, at least 10, and at least 100 patients shared.

RESULTS

Geographically proximate hospitals were somewhat more likely to share patients, but many hospitals shared patients with distant hospitals. Number of patient admissions and percentage of cancer patients were associated with greater connectivity across the system. The TPS network revealed numerous connections not seen in the UPS network, meaning that direct transfers only accounted for a fraction of total patient sharing.

CONCLUSIONS

Our analysis demonstrated that Orange County's 32 hospitals were highly and heterogeneously interconnected by patient sharing. Different hospital populations had different levels of influence over the patient-sharing network.

Critical care: the impact of organization and management on outcomes

PURPOSE OF REVIEW

The organization and management of ICUs are key components that can affect delivery and outcome of critical care.

RECENT FINDINGS

At the healthcare system level, the provision of critical care services and the presence of a regionalized system of critical care delivery may improve optimal matching of patient severity with level of care and is associated with improved patient outcomes. In hospitals, rapid response teams and step-down beds affect admission and discharge criteria to and from the ICU, although the influence on outcome is unclear. And within the ICU, the presence of intensivists, physically or via telemedicine, and multidisciplinary teams may promote better use of therapeutic and preventive measures with improved patient outcomes. Recent findings also emphasize that strategies that promote teamwork and communication, standardize processes of care, emphasize engagement in quality improvement, and provide a positive safety culture are associated with improved patient outcomes and staff morale.

SUMMARY

Evidence suggests the implementation of some ICU organizational and managerial patterns are associated with improved patient and staff outcomes. Broader adoption of some of these strategies could, therefore, improve overall critical care delivery.