Network analysis of team structure in the neonatal intensive care unit

Shift-Level Team Familiarity Is Associated with Improved Outcomes in Mechanically Ventilated Adults

Rationale: Organizing ICU interprofessional teams is a high priority because of workforce needs, but the role of interprofessional familiarity remains unexplored. Objectives: Determine if mechanically ventilated patients cared for by teams with greater familiarity have improved outcomes, such as lower mortality, shorter duration of mechanical ventilation (MV), and greater spontaneous breathing trial (SBT) implementation. Methods: We used electronic health records data of five ICUs in an academic medical center to map interprofessional teams and their ICU networks, measuring team familiarity as network coreness and mean team value. We used patient-level regression models to link team familiarity with patient outcomes, accounting for patient and unit factors. We also performed a split-sample analysis by using 2018 team familiarity data to predict 2019 outcomes. Measurements and Main Results: Team familiarity was measured as the average number of patients shared by each clinician with all other clinicians in the ICU (i.e., coreness) and the average number of patients shared by any two members of the team (i.e., mean team value). Among 4,485 encounters, unadjusted mortality was 12.9%, average duration of MV was 2.32 days, and SBT implementation was 89%; average team coreness was 467.2 (standard deviation [SD], 96.15), and average mean team value was 87.02 (SD, 42.42). A 1-SD increase in team coreness was significantly associated with a 4.5% greater probability of SBT implementation, 23% shorter MV duration, and 3.8% lower probability of dying; the mean team value was significantly associated with lower mortality. Split-sample results were attenuated but congruent in direction and interpretation. Conclusions: Interprofessional familiarity was associated with improved outcomes; assignment models that prioritize familiarity might be a novel solution.

Shift-to-shift handoffs in the NICU: lessons learned from a large scale audit

OBJECTIVE

Describe the frequency of best practice behaviors during NICU provider and nursing shift-to-shift handoffs and identify strengths and opportunities for improvement.

STUDY DESIGN

Observational study of handoff characteristics among 40 centers participating in a learning collaborative over a 10-month period. Data were gathered using a handoff audit tool that outlined best practices. Comparisons of behaviors between nurse-to-nurse and provider-to-provider handoffs were made where appropriate.

RESULTS

Overall, 946 audits of shift-to-shift handoffs were analyzed. While many behaviors were demonstrated reliably, differences between nurse-to-nurse vs provider-to-provider handoffs were noted. Families were present for 5.9% of handoffs and, among those who were present, 48.2% participated by contributing information, asking questions, and sharing goals.

CONCLUSIONS

Observation and measurement of handoff behaviors can be used to identify opportunities to improve handoff communication, family participation, and human factors that support handoff. Auditing handoffs is feasible and necessary to improve these critical transitions in infants' care.

Enhancing team success in the neonatal intensive care unit: challenges and opportunities for fluid teams

Fluid teams, characterized by frequent changes in team membership, are vital in the neonatal intensive care unit (NICU) due to high patient acuity and the need for a wide range of specialized providers. However, many challenges can hinder effective teamwork in this setting. This article reviews the challenges related to fluid teamwork in the NICU and discusses recommendations from team science to address each challenge. Drawing from the current literature, this paper outlines three challenges that can hinder fluid teamwork in the NICU: incorporating patient families, managing hierarchy among team members, and facilitating effective patient handoffs. The review concludes with recommendations for managing NICU teamwork differently using strategies from team science.

A Qualitative Study of Nurses' Perspectives on Neonatologist Continuity of Care

BACKGROUND

Families and staff in neonatal intensive care units (NICUs) value continuity of care (COC), though definitions, delivery, and impacts of COC are incompletely described. Previously, we used parental perspectives to define and build a conceptual model of COC provided by neonatologists. Nursing perspectives about COC remain unclear.

PURPOSE

To describe nursing perspectives on neonatologist COC and revise our conceptual model with neonatal nurse input.

METHODS

This was a qualitative study interviewing NICU nurses. The investigators analyzed transcripts with directed content analysis guided by an existing framework of neonatologist COC. Codes were categorized according to previously described COC components, impact on infants and families, and improvements for neonatologist COC. New codes were identified, including impact on nurses, and codes were classified into themes.

RESULTS

From 15 nurses, 5 themes emerged: (1) nurses validated parental definitions and benefits of COC; (2) communication is nurses' most valued component of COC; (3) neonatologist COC impact on nurses; (4) factors that modulate the delivery of and need for COC; (5) conflict between the need for COC and the need for change. Suggested improvement strategies included optimizing staffing and transition processes, utilizing clinical guidelines, and enhancing communication at all levels. Our adapted conceptual model describes variables associated with COC.

IMPLICATIONS FOR PRACTICE AND RESEARCH

Interdisciplinary NICU teams need to develop systematic strategies tailored to their unit's and patients' needs that promote COC, focused to improve parent-clinician communication and among clinicians. Our conceptual model can help future investigators develop targeted interventions to improve COC.

A Focused Review of Long-Stay Patients and the Ethical Imperative to Provide Inpatient Continuity

Long-stay patients are an impactful, vulnerable, growing group of inpatients in today's (and tomorrow's) tertiary hospitals. They can outlast dozens of clinicians that necessarily rotate on and off clinical service. Yet, care from such rotating clinicians can result in fragmented care due to a lack of continuity that insufficiently meets the needs of these patients and their families. Using long-stay PICU patients as an example, this focused review discusses the impact of prolonged admissions and how our fragmented care can compound this impact. It also argues that it is an ethical imperative to provide a level of continuity of care beyond what is considered standard of care and offers a number of strategies that can provide such continuity.

Data-Driven Nurse Staffing in the Neonatal Intensive Care Unit

ABSTRACT

The challenge of nurse staffing is amplified in the acute care neonatal intensive care unit (NICU) setting, where a wide range of highly variable factors affect staffing. A comprehensive overview of infant factors (severity, intensity), nurse factors (education, experience, preferences, team dynamics), and unit factors (structure, layout, shift length, care model) influencing pre-shift NICU staffing is presented, along with how intra-shift variability of these and other factors must be accounted for to maintain effective and efficient assignments. There is opportunity to improve workload estimations and acuity measures for pre-shift staffing using technology and predictive analytics. Nurse staffing decisions affected by intra-shift factor variability can be enhanced using novel care models that decentralize decision-making. Improving NICU staffing requires a deliberate, systematic, data-driven approach, with commitment from nurses, resources from the management team, and an institutional culture prioritizing patient safety.

Opportunities to use electronic health record audit logs to improve cancer care

The rapid adoption of electronic health records (EHRs) has created extensive repositories of digitized data that can be used to inform improvements in care delivery, processes, and patient outcomes. While the clinical data captured in EHRs are widely used for such efforts, EHRs also capture audit log data that reflect how users interact with the EHR to deliver care. Automatically collected audit log data provide a unique opportunity for new insights into EHR user behavior and decision‐making processes. Here, we provide an overview of audit log data and examples that could be used to improve oncology care and outcomes in four domains: diagnostic reasoning and consumption, care team collaboration and communication, patient outcomes and experience, and provider burnout/fatigue. This data source could identify gaps in performance and care, physician uptake of EHR features that enhance decision‐making, and integration of data trends for oncology. Ensuring researchers and oncologists are familiar with the data's potential and developing the data engineering capacity to utilize this rich data source, will expand the breadth of research to improve cancer care.

Parental Perspectives on Neonatologist Continuity of Care

BACKGROUND

Continuity of care (COC) is highly regarded; however, data about benefits are mixed. Little is known about components, parental views, or the value COC may provide to neonatal intensive care unit (NICU) infants and families.

PURPOSE

To describe parents' perspectives on definitions, reasons they value, and suggested improvements regarding COC provided by neonatologists.

METHODS

We performed a qualitative study of in-person, semistructured interviews with parents of NICU infants hospitalized for 28 days or more. We analyzed interview transcripts using content analysis, identifying codes of parental experiences, expressed value, and improvement ideas related to neonatologist COC, and categorizing emerging themes.

RESULTS

Fifteen families (15 mothers and 2 fathers) described 4 themes about COC: (1) longitudinal neonatologists: gaining experience with infants and building relationships with parents over time; (2) background knowledge: knowing infants' clinical history and current condition; (3) care plans: establishing patient-centered goals and management plans; and (4) communication: demonstrating consistent communication and messaging. Parents described benefits of COC as decreasing knowledge gaps, advancing clinical progress, and decreasing parental stress. Suggested improvement strategies included optimizing staffing and sign-out/transition processes, utilizing clinical guidelines, and enhancing communication. Using parent input and existing literature, we developed a definition and conceptual framework of COC.

IMPLICATIONS FOR PRACTICE

NICUs should promote practices that enhance COC. Parental suggestions can help direct improvement efforts.

IMPLICATIONS FOR RESEARCH

Our COC definition and conceptual framework can guide development of research and quality improvement projects. Future studies should investigate nursing perspectives on NICU COC and the impact of COC on infant and family outcomes.

Analysis of the relationship between treatment networks and the evolution of patients with Type 2 Diabetes Mellitus

Type 2 Diabetes Mellitus (T2DM) is a chronic disease that has been increasing in prevalence in recent years and that can cause severe complications. To ensure patient care is administered correctly, it is necessary for medical treatment teams to be both multidisciplinary and cohesive. The analysis of health processes is a constant challenge due to their high variability and complexity. This paper proposes a method based on the analysis of social networks to detect treatment networks, and to identify a relationship between these networks and patient evolution, as measured by glycated hemoglobin (HbA1c) levels. The networks were segmented based on patient adherence to their medical appointments and their mean time of delay. We applied this method on a sample of 1574 patients diagnosed with T2DM. Results show that participatory treatment -in which a patient sees a particular group of professionals on a recurrent basis - together with high levels of adherence are associated to those patients who improve their HbA1c levels in the case of high levels of adherence, while those who continually experience referrals to different professionals, remain unstable and, in some cases, get worse. On the other hand, in order to maintain a patient as stable, continuous control of the patient is enough, regardless of the recurrence to the same professionals.

Association between continuity of nursing care and older adults' hospitalization outcomes: A retrospective observational study

AIM

To assess the relationship between continuity in nursing assignment in older adults' acute hospitalization and patient experience and functional decline.

BACKGROUND

In-hospital functional decline affects up to 40% of hospitalized older adults. Nurses are responsible for performing functioning-preserving interventions. Whether continuity of nursing care contributes to patients' functional outcomes is unclear.

METHOD

A retrospective observational study of 609 patients aged ≥70 admitted to internal medicine units. Patients were surveyed on their functional (cognitive and physical) status and satisfaction with the hospital care experience. Dispersion and sequence of nursing assignment were measured by the Continuity of Care Index and Sequential Continuity Index. Multivariate logistic regressions were modelled for each continuity score and outcome.

RESULTS

Achieving 25% of the maximum Continuity of Care Index was associated with lower odds of cognitive decline (OR = 0.64, 95% CI = 0.43-0.94) and higher odds of satisfaction (OR = 1.52, 95% CI = 1.06-2.17). Achieving 25% of the maximum Sequential Continuity Index was associated only with higher odds of satisfaction (OR = 1.43, 95% CI = 1.01-2.02). Continuity scores were not associated with physical functioning decline.

CONCLUSION

Continuity in nursing assignment is related to a positive patient experience and cognitive functioning of hospitalized older adults.

IMPLICATIONS FOR NURSING MANAGEMENT

Continuity should be prioritized in scheduling and assignment algorithms.

Modeling Care Team Structures in the Neonatal Intensive Care Unit through Network Analysis of EHR Audit Logs

BACKGROUND

 In the neonatal intensive care unit (NICU), predefined acuity-based team care models are restricted to core roles and neglect interactions with providers outside of the team, such as interactions that transpire via electronic health record (EHR) systems. These unaccounted interactions may be related to the efficiency of resource allocation, information flow, communication, and thus impact patient outcomes. This study applied network analysis methods to EHR audit logs to model the interactions of providers beyond their core roles to better understand the interaction network patterns of acuity-based teams and relationships of the network structures with postsurgical length of stay (PSLOS).

METHODS

 The study used the EHR log data of surgical neonates from a large academic medical center. The study included 104 surgical neonates, for whom 9,206 unique actions were performed by 457 providers in their EHRs. We applied network analysis methods to model EHR provider interaction networks of acuity-based teams in NICU postoperative care. We partitioned each EHR network into three subnetworks based on interaction types: (1) interactions between known core providers who were documented in scheduling records (core subnetwork); (2) interactions between core and noncore providers (extended subnetwork); and (3) interactions between noncore providers (extended subnetwork). For each core subnetwork, we assessed its capability to replicate predefined core-provider relations as documented in scheduling records. We further compared each EHR network, as well as its subnetworks, using standard network measures to determine its differences in network topologies. We conducted a case study to learn provider interaction networks taking care of 15 neonates who underwent gastrostomy tube placement surgery from EHR log data and measure the effectiveness of the interaction networks on PSLOS by the proportional-odds model.

RESULTS

 The provider networks of four acuity-based teams (two high and two low acuity), along with their subnetworks, were discovered. We found that beyond capturing the predefined core-provider relations, EHR audit logs can also learn a large number of relations between core and noncore providers or among noncore providers. Providers in the core subnetwork exhibited a greater number of connections with each other than with providers in the extended subnetworks. Many more providers in the core subnetwork serve as a hub than those in the other types of subnetworks. We also found that high-acuity teams exhibited more complex network structures than low-acuity teams, with high-acuity team generating 6,416 interactions between 407 providers compared with 931 interactions between 124 providers, respectively. In addition, we discovered that high-acuity and low-acuity teams shared more than 33 and 25% of providers with each other, respectively, but exhibited different collaborative structures demonstrating that NICU providers shift across different acuity teams and exhibit different network characteristics. Results of case study show that providers, whose patients had lower PSLOS, tended to disperse patient-related information to more colleagues within their network than those who treated higher PSLOS patients (p = 0.03).

CONCLUSION

 Network analysis can be applied to EHR log data to model acuity-based NICU teams capturing interactions between providers within the predesigned core team as well as those outside of the core team. In the NICU, dissemination of information may be linked to reduced PSLOS. EHR log data provide an efficient, accessible, and research-friendly way to study provider interaction networks. Findings should guide improvements in the EHR system design to facilitate effective interactions between providers.

Compassion in Pediatric Healthcare: A Scoping Review

PROBLEM

Compassion has been described as a central construct or essential feature of quality healthcare and is as important to patients' and families' overall healthcare experience as the health interventions and treatments they receive. However, there is little shared understanding of what constitutes compassion, how it is delivered within a pediatric setting, and pediatric patients' and families perspectives and preferences for receiving it.

ELIGIBILITY CRITERIA

Studies that (1) described the nature of the existing literature on compassion in pediatric healthcare; (2) summarized key concepts in the existing evidence base that pertain to compassion in pediatric healthcare; and 3) identified factors that are associated with compassion in pediatric healthcare were eligible for inclusion in this review.

SAMPLE

Twenty-nine papers were included in the review.

RESULTS

Findings revealed several factors are associated with compassion in pediatric healthcare, including continuity of care, communication, and coordination of care. Most notably, identified studies treated compassion in a subsidiary fashion, and this review revealed no studies that provided a patient-informed evidence-based definition of compassion in the pediatric healthcare setting.

CONCLUSION

Future research is required to generate a comprehensive and accurate understanding of the terms 'compassion' and 'compassionate care' when used in the context of pediatric healthcare.

IMPLICATIONS

This research will inform the therapeutic processes and ultimately enable the development of strategies to improve the delivery of compassionate healthcare to pediatric patients.

Variability in the systems of care supporting critical neonatal intensive care unit transitions

OBJECTIVE

Assess practices supporting care transitions for infants and families in the neonatal intensive care unit (NICU) using a model of four key drivers: communication, teamwork, family integration, and standardization.

STUDY DESIGN

Single-day audit among NICUs in the Vermont Oxford Network Critical Transitions collaborative addressing policies and practices supporting the four key drivers during admission, discharge, shift-to-shift handoffs, within hospital transfers, and select changes in clinical status.

RESULTS

Among 95 NICUs, the median hospital rate of audited policies in place addressing the four key drivers were 47% (inter-quartile range (IQR) 35-65%) for communication, 67% (IQR 33-83%) for teamwork, 50% (IQR 33-61%) for family integration, and 70% (IQR 56-85%) for standardization. Of the 2462 infants included, 1066 (43%) experienced ≥1 specified transition during the week prior to the audit.

CONCLUSIONS

We identified opportunities for improving NICU transitions in areas of communication, teamwork, family integration, and standardization.

Provider Networks in the Neonatal Intensive Care Unit Associate with Length of Stay

We strive to understand care coordination structures of multidisciplinary teams and to evaluate their effect on post-surgical length of stay (PSLOS) in the Neonatal Intensive Care Unit (NICU). Electronic health record (EHR) data were extracted for 18 neonates, who underwent gastrostomy tube placement surgery at the Vanderbilt University Medical Center NICU. Based on providers' interactions with the EHR (e.g. viewing, documenting, ordering), provider-provider relations were learned and used to build patient-specific provider networks representing the care coordination structure. We quantified the networks using standard network analysis metrics (e.g., in-degree, out-degree, betweenness centrality, and closeness centrality). Coordination structure effectiveness was measured as the association between the network metrics and PSLOS, as modeled by a proportional-odds, logistical regression model. The 18 provider networks exhibited various team compositions and various levels of structural complexity. Providers, whose patients had lower PSLOS, tended to disperse patient-related information to more colleagues within their network than those, who treated higher PSLOS patients (P = 0.0294). In the NICU, improved dissemination of information may be linked to reduced PSLOS. EHR data provides an efficient, accessible, and resource-friendly way to study care coordination using network analysis tools. This novel methodology offers an objective way to identify key performance and safety indicators of care coordination and to study dissemination of patient-related information within care provider networks and its effect on care. Findings should guide improvements in the EHR system design to facilitate effective clinical communications among providers.

Evaluation of multidisciplinary collaboration in pediatric trauma care using EHR data

OBJECTIVES

The study sought to identify collaborative electronic health record (EHR) usage patterns for pediatric trauma patients and determine how the usage patterns are related to patient outcomes.

MATERIALS AND METHODS

A process mining-based network analysis was applied to EHR metadata and trauma registry data for a cohort of pediatric trauma patients with minor injuries at a Level I pediatric trauma center. The EHR metadata were processed into an event log that was segmented based on gaps in the temporal continuity of events. A usage pattern was constructed for each encounter by creating edges among functional roles that were captured within the same event log segment. These patterns were classified into groups using graph kernel and unsupervised spectral clustering methods. Demographics, clinical and network characteristics, and emergency department (ED) length of stay (LOS) of the groups were compared.

RESULTS

Three distinct usage patterns that differed by network density were discovered: fully connected (clique), partially connected, and disconnected (isolated). Compared with the fully connected pattern, encounters with the partially connected pattern had an adjusted median ED LOS that was significantly longer (242.6 [95% confidence interval, 236.9-246.0] minutes vs 295.2 [95% confidence, 289.2-297.8] minutes), more frequently seen among day shift and weekday arrivals, and involved otolaryngology, ophthalmology services, and child life specialists.

DISCUSSION

The clique-like usage pattern was associated with decreased ED LOS for the study cohort, suggesting greater degree of collaboration resulted in shorter stay.

CONCLUSIONS

Further investigation to understand and address causal factors can lead to improvement in multidisciplinary collaboration.

Team Collaboration Networks and Multidisciplinarity in Diabetes Care: Implications for Patient Outcomes

Prevalence of type 2 diabetes mellitus (T2DM) has almost doubled in recent decades and commonly presents comorbidities and complications. T2DM is a multisystemic disease, requiring multidisciplinary treatment provided by teams working in a coordinated and collaborative manner. The application of social network analysis techniques in the healthcare domain has allowed researchers to analyze interaction between professionals and their roles inside care teams. We studied whether the structure of care teams, modeled as complex social networks, is associated with patient progression. For this, we illustrate a data-driven methodology and use existing social network analysis metrics and metrics proposed for this research. We analyzed appointment and HbA1c blood test result data from patients treated at three primary health care centers, representing six different practices. Patients with good metabolic control during the analyzed period were treated by teams that were more interactive, collaborative and multidisciplinary, whereas patients with worsening or unstable metabolic control were treated by teams with less collaboration and more continuity breakdowns. Results from the proposed metrics were consistent with the previous literature and reveal relevant aspects of collaboration and multidisciplinarity.

Nursing Unit Communication During a US Public Health Emergency: Natural Experiment

Background

In the second half of 2014, the first case of Ebola virus disease (EVD) was diagnosed in the United States. During this time period, we were collecting data for the Measuring Network Stability and Fit (NetFIT) longitudinal study, which used social network analysis (SNA) to study relationships between nursing staff communication patterns and patient outcomes. One of the data collection sites was a few blocks away from where the initial EVD diagnosis was made. The EVD public health emergency during the NetFIT data collection time period resulted in the occurrence of a natural experiment.

Objective

The objectives of the NetFIT study were to examine the structure of nursing unit decision-making and information-sharing networks, identify a parsimonious set of network metrics that can be used to measure the longitudinal stability of these networks, examine the relationship between the contextual features of a unit and network metrics, and identify relationships between key network measures and nursing-sensitive patient-safety and quality outcomes. This paper reports on unit communication and outcome changes that occurred during the EVD natural disaster time period on the 10 hospital units that had data collected before, during, and after the crisis period.

Methods

For the NetFIT study, data were collected from nursing staff working on 25 patient care units, in three hospitals, and at four data collection points over a 7-month period: Baseline, Month 1, Month 4, and Month 7. Data collection was staggered by hospital and unit. To evaluate the influence of this public health emergency on nursing unit outcomes and communication characteristics, this paper focuses on a subsample of 10 units from two hospitals where data were collected before, during, and after the EVD crisis period. No data were collected from Hospital B during the crisis period. Network data from individual staff were aggregated to the nursing unit level to create 24-hour networks and three unit-level safety outcome measures-fall rate, medication errors, and hospital-acquired pressure ulcers-were collected.

Results

This analysis includes 40 data collection points and 608 staff members who completed questionnaires. Participants (N=608) included registered nurses (431, 70.9%), licensed vocational nurses (3, 0.5%), patient care technicians (133, 21.9%), unit clerks (28, 4.6%), and monitor watchers (13, 2.1%). Changes in SNA metrics associated with communication (ie, average distance, diffusion, and density) were noted in units that had changes in patient safety outcome measures.

Conclusions

Units in the hospital site in the same city as the EVD case exhibited multiple changes in patient outcomes, network communication metrics, and response rates. Future research using SNA to examine the influence of public health emergencies on hospital communication networks and relationships to patient outcomes is warranted.

Human interaction in the NICU and its association with outcomes on the Brief Infant-Toddler Social and Emotional Assessment (BITSEA)

BACKGROUND

Extremely preterm infants represent one of the highest risk categories for impairments in social competence. Few studies have explored the impact of the neonatal intensive care unit (NICU) environment on social development. However, none have specifically analyzed the effects of the care structure the infant receives during hospitalization on later social competence indicators.

OBJECTIVE

To identify associations between the care structures received by extremely preterm infants in the NICU and scores on the Brief Infant-Toddler Social and Emotional Assessment (BITSEA) post-discharge.

PARTICIPANTS

50 extremely preterm infants (mean gestational age: 25 weeks during hospitalization; mean chronological age during follow-up assessment: 2 years, 4 months).

METHODS

A secondary analysis of BITSEA data was performed exploring its relation to care structure data we extracted from electronic medical records (i.e., how much time infants were engaged in human interaction during their first thirty days of hospitalization and what types of interaction they were exposed to).

RESULTS

Extremely preterm infants spend a considerable amount of time alone during hospitalization (80%) with nursing care comprising the majority of human interaction. Infants who experienced greater human interaction scored significantly higher on the Social Competence (p = 0.01) and lower on the Dysregulation (p = 0.03) BITSEA subscales.

CONCLUSION

Human interaction and isolation in the NICU is associated with social competence and dysregulation outcomes in extremely preterm infants. Further research is needed to understand how various NICU care structures including centralized nursing teams, parental skin-to-skin care, and early therapy may synergistically play a positive role in developing social competence.

Relationship of Staff Information Sharing and Advice Networks to Patient Safety Outcomes

OBJECTIVE

The aim of this study was to compare information sharing and advice networks' relationships with patient safety outcomes.

BACKGROUND

Communication contributes to medical errors, but rarely is it clear what elements of communication are key.

METHODS

We investigated relationships of information-sharing and advice networks to patient safety outcomes in 24 patient care units from 3 hospitals over 7 months. Web-based questionnaires completed via Android tablets provided data to create 2 networks using ORA, a social network analysis application. Each hospital provided nurse-sensitive patient safety outcomes.

RESULTS

In both networks, medication errors correlated positively with node count and average distance and negatively with clustering coefficient. Density and weighted density negatively correlated with medication errors and falls in both networks. Eigenvector and total degree centrality correlated negatively with both safety outcomes, whereas betweenness centrality positively related to falls in the information-sharing network.

CONCLUSION

Technology-enabled social network analysis data collection is feasible and can provide managers actionable system-level information.

Parental experience of interaction with healthcare professionals during their infant's stay in the neonatal intensive care unit

OBJECTIVE

To explore the experiences of parents of infants admitted to the neonatal intensive care unit towards interaction with healthcare professionals during their infants critical care.

DESIGN

Semi-structured interviews were conducted with parents of critically ill infants admitted to neonatal intensive care and prospectively enrolled in a study of communication in critical care decision making. Interviews were transcribed verbatim and uploaded into NVivo V.10 to manage and facilitate data analysis. Thematic analysis identified themes representing the data.

RESULTS

Nineteen interviews conducted with 14 families identified 4 themes: (1) initial impact of admission affecting transition into the neonatal unit; (2) impact of consistency of care, care givers and information giving; (3) impact of communication in facilitating or hindering parental autonomy, trust, parental expectations and interactions; (4) parental perception of respect and humane touches on the neonatal unit.

CONCLUSION

Factors including the context of infant admission, interprofessional consistency, humane touches of staff and the transition into the culture of the neonatal unit are important issues for parents. These issues warrant further investigation to facilitate individualised family needs, attachment between parents and their baby and the professional team.

Multidisciplinary Collaboration in the Treatment of Patients With Type 2 Diabetes in Primary Care: Analysis Using Process Mining

Background

Public health in several countries is characterized by a shortage of professionals and a lack of economic resources. Monitoring and redesigning processes can foster the success of health care institutions, enabling them to provide a quality service while simultaneously reducing costs. Process mining, a discipline that extracts knowledge from information system data to analyze operational processes, affords an opportunity to understand health care processes.

Objective

Health care processes are highly flexible and multidisciplinary, and health care professionals are able to coordinate in a variety of different ways to treat a diagnosis. The aim of this work was to understand whether the ways in which professionals coordinate their work affect the clinical outcome of patients.

Methods

This paper proposes a method based on the use of process mining to identify patterns of collaboration between physician, nurse, and dietitian in the treatment of patients with type 2 diabetes mellitus and to compare these patterns with the clinical evolution of the patients within the context of primary care. Clustering is used as part of the preprocessing of data to manage the variability, and then process mining is used to identify patterns that may arise.

Results

The method is applied in three primary health care centers in Santiago, Chile. A total of seven collaboration patterns were identified, which differed primarily in terms of the number of disciplines present, the participation intensity of each discipline, and the referrals between disciplines. The pattern in which the three disciplines participated in the most equitable and comprehensive manner had a lower proportion of highly decompensated patients compared with those patterns in which the three disciplines participated in an unbalanced manner.

Conclusions

By discovering which collaboration patterns lead to improved outcomes, health care centers can promote the most successful patterns among their professionals so as to improve the treatment of patients. Process mining techniques are useful for discovering those collaborations patterns in flexible and unstructured health care processes.

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.

Provider Connectedness to Other Providers Reduces Risk of Readmission After Hospitalization for Heart Failure

Provider interactions other than explicit care coordination, which is challenging to measure, may influence practice and outcomes. We performed a network analysis using claims data from a commercial payor. Networks were identified based on provider pairs billing outpatient care for the same patient. We compared network variables among patients who had and did not have a 30-day readmission after hospitalization for heart failure. After adjusting for comorbidities, high median provider connectedness-normalized degree, which for each provider is the number of connections to other providers normalized to the number of providers in the region-was the network variable associated with reduced odds of readmission after heart failure hospitalization (odds ratio = 0.55; 95% confidence interval [0.35, 0.86]). We conclude that heart failure patients with high provider connectedness are less likely to require readmission. The structure and importance of provider relationships using claims data merits further study.

Properties of healthcare teaming networks as a function of network construction algorithms

Network models of healthcare systems can be used to examine how providers collaborate, communicate, refer patients to each other, and to map how patients traverse the network of providers. Most healthcare service network models have been constructed from patient claims data, using billing claims to link a patient with a specific provider in time. The data sets can be quite large (106-108 individual claims per year), making standard methods for network construction computationally challenging and thus requiring the use of alternate construction algorithms. While these alternate methods have seen increasing use in generating healthcare networks, there is little to no literature comparing the differences in the structural properties of the generated networks, which as we demonstrate, can be dramatically different. To address this issue, we compared the properties of healthcare networks constructed using different algorithms from 2013 Medicare Part B outpatient claims data. Three different algorithms were compared: binning, sliding frame, and trace-route. Unipartite networks linking either providers or healthcare organizations by shared patients were built using each method. We find that each algorithm produced networks with substantially different topological properties, as reflected by numbers of edges, network density, assortativity, clustering coefficients and other structural measures. Provider networks adhered to a power law, while organization networks were best fit by a power law with exponential cutoff. Censoring networks to exclude edges with less than 11 shared patients, a common de-identification practice for healthcare network data, markedly reduced edge numbers and network density, and greatly altered measures of vertex prominence such as the betweenness centrality. Data analysis identified patterns in the distance patients travel between network providers, and a striking set of teaming relationships between providers in the Northeast United States and Florida, likely due to seasonal residence patterns of Medicare beneficiaries. We conclude that the choice of network construction algorithm is critical for healthcare network analysis, and discuss the implications of our findings for selecting the algorithm best suited to the type of analysis to be performed.

Leveraging electronic health record documentation for Failure Mode and Effects Analysis team identification

OBJECTIVE

Using Failure Mode and Effects Analysis (FMEA) as an example quality improvement approach, our objective was to evaluate whether secondary use of orders, forms, and notes recorded by the electronic health record (EHR) during daily practice can enhance the accuracy of process maps used to guide improvement. We examined discrepancies between expected and observed activities and individuals involved in a high-risk process and devised diagnostic measures for understanding discrepancies that may be used to inform quality improvement planning.

METHODS

Inpatient cardiology unit staff developed a process map of discharge from the unit. We matched activities and providers identified on the process map to EHR data. Using four diagnostic measures, we analyzed discrepancies between expectation and observation.

RESULTS

EHR data showed that 35% of activities were completed by unexpected providers, including providers from 12 categories not identified as part of the discharge workflow. The EHR also revealed sub-components of process activities not identified on the process map. Additional information from the EHR was used to revise the process map and show differences between expectation and observation.

CONCLUSION

Findings suggest EHR data may reveal gaps in process maps used for quality improvement and identify characteristics about workflow activities that can identify perspectives for inclusion in an FMEA. Organizations with access to EHR data may be able to leverage clinical documentation to enhance process maps used for quality improvement. While focused on FMEA protocols, findings from this study may be applicable to other quality activities that require process maps.

Characterizing Teamwork in Cardiovascular Care Outcomes: A Network Analytics Approach

BACKGROUND

The nature of teamwork in healthcare is complex and interdisciplinary, and provider collaboration based on shared patient encounters is crucial to its success. Characterizing the intensity of working relationships with risk-adjusted patient outcomes supplies insight into provider interactions in a hospital environment.

METHODS AND RESULTS

We extracted 4 years of patient, provider, and activity data for encounters in an inpatient cardiology unit from Northwestern Medicine's Enterprise Data Warehouse. We then created a provider-patient network to identify healthcare providers who jointly participated in patient encounters and calculated satisfaction rates for provider-provider pairs. We demonstrated the application of a novel parameter, the shared positive outcome ratio, a measure that assesses the strength of a patient-sharing relationship between 2 providers based on risk-adjusted encounter outcomes. We compared an observed collaboration network of 334 providers and 3453 relationships to 1000 networks with shared positive outcome ratio scores based on randomized outcomes and found 188 collaborative relationships between pairs of providers that showed significantly higher than expected patient satisfaction ratings. A group of 22 providers performed exceptionally in terms of patient satisfaction. Our results indicate high variability in collaboration scores across the network and highlight our ability to identify relationships with both higher and lower than expected scores across a set of shared patient encounters.

CONCLUSIONS

Satisfaction rates seem to vary across different teams of providers. Team collaboration can be quantified using a composite measure of collaboration across provider pairs. Tracking provider pair outcomes over a sufficient set of shared encounters may inform quality improvement strategies such as optimizing team staffing, identifying characteristics and practices of high-performing teams, developing evidence-based team guidelines, and redesigning inpatient care processes.

Social networks in health care teams: evidence from the United States

Purpose

The purpose of this paper is to synthesize existing evidence regarding health care team networks, including their formation and association with outcomes in various health care settings.

Design/methodology/approach

Network theory informed this review. A literature search was conducted in major databases for studies that used social network analysis methods to study health care teams in the USA between 2000 and 2014. Retrieved studies were reviewed against inclusion and exclusion criteria.

Findings

Overall, 25 studies were included in this review. Results demonstrated that health care team members form professional (e.g. consultation) and personal (e.g. friendship) networks. Network formation can be influenced by team member characteristics (i.e. demographics and professional affiliations) as well as by contextual factors (i.e. providers sharing patient populations and physical proximity to colleagues). These networks can affect team member practice such as adoption of a new medication. Network structures can also impact patient and organizational outcomes, including occurrence of adverse events and deficiencies in health care delivery.

Practical implications

Administrators and policy makers can use knowledge of health care networks to leverage relational structures in teams and tailor interventions that facilitate information exchange, promote collaboration, increase diffusion of evidence-based practices, and potentially improve individual and team performance as well as patient care and outcomes.

Originality/value

Most health services research studies have investigated health care team composition and functioning using traditional social science methodologies, which fail to capture relational structures within teams. Thus, this review is original in terms of focusing on dynamic relationships among team members.

An Outcome-Weighted Network Model for Characterizing Collaboration

Shared patient encounters form the basis of collaborative relationships, which are crucial to the success of complex and interdisciplinary teamwork in healthcare. Quantifying the strength of these relationships using shared risk-adjusted patient outcomes provides insight into interactions that occur between healthcare providers. We developed the Shared Positive Outcome Ratio (SPOR), a novel parameter that quantifies the concentration of positive outcomes between a pair of healthcare providers over a set of shared patient encounters. We constructed a collaboration network using hospital emergency department patient data from electronic health records (EHRs) over a three-year period. Based on an outcome indicating patient satisfaction, we used this network to assess pairwise collaboration and evaluate the SPOR. By comparing this network of 574 providers and 5,615 relationships to a set of networks based on randomized outcomes, we identified 295 (5.2%) pairwise collaborations having significantly higher patient satisfaction rates. Our results show extreme high- and low-scoring relationships over a set of shared patient encounters and quantify high variability in collaboration between providers. We identified 29 top performers in terms of patient satisfaction. Providers in the high-scoring group had both a greater average number of associated encounters and a higher percentage of total encounters with positive outcomes than those in the low-scoring group, implying that more experienced individuals may be able to collaborate more successfully. Our study shows that a healthcare collaboration network can be structurally evaluated to characterize the collaborative interactions that occur between healthcare providers in a hospital setting.

Do You Know My Child? Continuity of Nursing Care in the Pediatric Intensive Care Unit

BACKGROUND

Parents of children with complex, chronic conditions report a desire for continuity of care, but relatively little is known about the ways in which nursing continuity of care occurs and the extent to which it is delivered in the inpatient setting.

OBJECTIVES

The objective of this analysis, which arose from a study on best practices in parent/nurse interactions in the pediatric intensive care unit (PICU), was to explore the delivery of continuity of nursing care in the PICU from the perspective of both parents and nurses.

METHODS

A qualitative, grounded theory study using situational analysis was conducted with seven parents and 12 nurse participants from a single PICU. Data sources included in-depth interviews, observation, and organizational written materials. Data were coded and analyzed using memoing and situational and positional maps to highlight emerging themes, context, and positions within the data.

RESULTS

Parents repeatedly endorsed a desire for continuity of nursing care, wanting to ensure that the bedside nurse valued their child as an individual and understood the complexities of the child's care regimen. Nurses understood this need but faced both contextual and personal challenges to achieving continuity, including fluctuations in staffing needs, training demands, fear of emotional entanglement, and concern for missed learning opportunities.

DISCUSSION

Continuity of nursing care is highly valued by parents of children with complex chronic condition in the PICU, but significant barriers to optimal delivery exist within the current critical care environment. Mechanisms for supporting nurses to deliver continuity of care are needed, as are alternative ways to help parents feel that all nurses caring for their child have the knowledge necessary to deliver safe and compassionate care.

Continuity of Nurse Caregivers in the Neonatal Intensive Care Unit

There is growing evidence that continuity of nurse caregivers (CNC) has an effect on outcomes for infants admitted to neonatal intensive care units. Using Levine’s conservation model, the relationship of infant acuity and CNC for 50 infants born between 24 and 40 weeks gestation was explored. A statistically significant difference was found between the variable acuity and CNC (F = 8.65, p = .01). Results suggest that high infant acuity is strongly related to high CNC but may be the effect of a third variable. CNC may support the emergence of physiological, structural, and social competencies for convalescing premature infants.

Patient Mortality Is Associated With Staff Resources and Workload in the ICU: A Multicenter Observational Study

OBJECTIVE

Matching healthcare staff resources to patient needs in the ICU is a key factor for quality of care. We aimed to assess the impact of the staffing-to-patient ratio and workload on ICU mortality.

DESIGN

We performed a multicenter longitudinal study using routinely collected hospital data.

SETTING

Information pertaining to every patient in eight ICUs from four university hospitals from January to December 2013 was analyzed.

PATIENTS

A total of 5,718 inpatient stays were included.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We used a shift-by-shift varying measure of the patient-to-caregiver ratio in combination with workload to establish their relationships with ICU mortality over time, excluding patients with decision to forego life-sustaining therapy. Using a multilevel Poisson regression, we quantified ICU mortality-relative risk, adjusted for patient turnover, severity, and staffing levels. The risk of death was increased by 3.5 (95% CI, 1.3-9.1) when the patient-to-nurse ratio was greater than 2.5, and it was increased by 2.0 (95% CI, 1.3-3.2) when the patient-to-physician ratio exceeded 14. The highest ratios occurred more frequently during the weekend for nurse staffing and during the night for physicians (p < 0.001). High patient turnover (adjusted relative risk, 5.6 [2.0-15.0]) and the volume of life-sustaining procedures performed by staff (adjusted relative risk, 5.9 [4.3-7.9]) were also associated with increased mortality.

CONCLUSIONS

This study proposes evidence-based thresholds for patient-to-caregiver ratios, above which patient safety may be endangered in the ICU. Real-time monitoring of staffing levels and workload is feasible for adjusting caregivers' resources to patients' needs.

Visualizing collaborative electronic health record usage for hospitalized patients with heart failure

Objective To visualize and describe collaborative electronic health record (EHR) usage for hospitalized patients with heart failure.

Materials and methods We identified records of patients with heart failure and all associated healthcare provider record usage through queries of the Northwestern Medicine Enterprise Data Warehouse. We constructed a network by equating access and updates of a patient’s EHR to a provider-patient interaction. We then considered shared patient record access as the basis for a second network that we termed the provider collaboration network. We calculated network statistics, the modularity of provider interactions, and provider cliques.

Results We identified 548 patient records accessed by 5113 healthcare providers in 2012. The provider collaboration network had 1504 nodes and 83 998 edges. We identified 7 major provider collaboration modules. Average clique size was 87.9 providers. We used a graph database to demonstrate an ad hoc query of our provider-patient network.

Discussion Our analysis suggests a large number of healthcare providers across a wide variety of professions access records of patients with heart failure during their hospital stay. This shared record access tends to take place not only in a pairwise manner but also among large groups of providers.

Conclusion EHRs encode valuable interactions, implicitly or explicitly, between patients and providers. Network analysis provided strong evidence of multidisciplinary record access of patients with heart failure across teams of 100+ providers. Further investigation may lead to clearer understanding of how record access information can be used to strategically guide care coordination for patients hospitalized for heart failure.

A systematic review of nurse-related social network analysis studies

BACKGROUND

Nurses frequently work as part of both uni- and multidisciplinary teams. Communication between team members is critical in the delivery of quality care. Social network analysis is increasingly being used to explore such communication.

AIM

To explore the use of social network analysis involving nurses either as subjects of the study or as researchers.

METHODS

Standard systematic review procedures were applied to identify nurse-related studies that utilize social network analysis. A comparative thematic approach to synthesis was used. Both published and grey literature written in English, Spanish and Portuguese between January 1965 and December 2013 were identified via a structured search of CINAHL, SciELO and PubMed. In addition, Google and Yahoo search engines were used to identify additional grey literature using the same search strategy.

RESULTS

Forty-three primary studies were identified with literature from North America dominating the published work. So far it would appear that no author or group of authors have developed a programme of research in the nursing field using the social network analysis approach although several authors may be in the process of doing so.

LIMITATIONS

The dominance of literature from North America may be viewed as problematic as the underlying structures and themes may be an artefact of cultural communication norms from this region.

CONCLUSIONS

The use of social network analysis in relation to nursing and by nurse researchers has increased rapidly over the past two decades. The lack of longitudinal studies and the absence of replication across multiple sites should be seen as an opportunity for further research.

IMPLICATION FOR NURSING AND HEALTH POLICY

This analytical approach is relatively new in the field of nursing but does show considerable promise in offering insights into the way information flows between individuals, teams, institutions and other structures. An understanding of these structures provides a means of improving communication.

Medically complex pregnancies and early breastfeeding behaviors: a retrospective analysis

BACKGROUND

Breastfeeding is beneficial for women and infants, and medical contraindications are rare. Prenatal and labor-related complications may hinder breastfeeding, but supportive hospital practices may encourage women who intend to breastfeed. We measured the relationship between having a complex pregnancy (entering pregnancy with hypertension, diabetes, or obesity) and early infant feeding, accounting for breastfeeding intentions and supportive hospital practices.

METHODS

We performed a retrospective analysis of data from a nationally-representative survey of women who gave birth in 2011-2012 in a US hospital (N = 2400). We used logistic regression to examine the relationship between pregnancy complexity and breastfeeding. Self-reported prepregnancy diabetes or hypertension, gestational diabetes, or obesity indicated a complex pregnancy. The outcome was feeding status 1 week postpartum; any breastfeeding was evaluated among women intending to breastfeed (N = 1990), and exclusive breastfeeding among women who intended to exclusively breastfeed (N = 1418). We also tested whether breastfeeding intentions or supportive hospital practices mediated the relationship between pregnancy complexity and infant feeding status.

RESULTS

More than 33% of women had a complex pregnancy; these women had 30% lower odds of intending to breastfeed (AOR = 0.71; 95% CI, 0.52-0.98). Rates of intention to exclusively breastfeed were similar for women with and without complex pregnancies. Women who intended to breastfeed had similar rates of any breastfeeding 1 week postpartum regardless of pregnancy complexity, but complexity was associated with >30% lower odds of exclusive breastfeeding 1 week among women who intended to exclusively breastfeed (AOR = 0.68; 95% CI, 0.47-0.98). Supportive hospital practices were strongly associated with higher odds of any or exclusive breastfeeding 1 week postpartum (AOR = 4.03; 95% CI, 1.81-8.94; and AOR = 2.68; 95% CI, 1.70-4.23, respectively).

CONCLUSIONS

Improving clinical and hospital support for women with complex pregnancies may increase breastfeeding rates and the benefits of breastfeeding for women and infants.

Nursing clinical handover in neonatal care

BACKGROUND

Clinical handover ensures continuity of care, providing the opportunity to transfer responsibility and accountability for the care of a patient from nurse to nurse.

AIM

The aim of this study was to examine afternoon nursing clinical handover from the perspective of nurses, exploring the quality of information, the interactions and support, the efficiency and the involvement of parents in a private neonatal unit.

METHODS/DESIGN

An exploratory, descriptive, prospective quantitative survey with qualitative elements was undertaken using The Handover Evaluation Scale (O'Connell, MacDonald, & Kelly, 2008). All nurses working in the Neonatal unit who attend afternoon handover, were invited to participate in the study (N = 22), with N = 16 responses received.

RESULTS/FINDINGS

The quantitative and qualitative results indicate that the quality of the information handed over in neonatal care units can be maintained despite intrinsic limitations. Additionally, high levels of support and interaction between nursing staff in this stressful practice environment occur during the handover period.

CONCLUSION

Given the vulnerability of neonates it is important that accurate information is efficiently handed over. In order to do this distractions should be minimised. Finally, parental involvement in handover should be actively encouraged whenever feasible.

Team working in intensive care: current evidence and future endeavors

PURPOSE OF REVIEW

It has recently been argued that the future of intensive care medicine will rely on high quality management and teamwork. Therefore, this review takes an organizational psychology perspective to examine the most recent research on the relationship between teamwork, care processes, and patient outcomes in intensive care.

RECENT FINDINGS

Interdisciplinary communication within a team is crucial for the development of negotiated shared treatment goals and short-team patient outcomes. Interventions for maximizing team communication have received substantial interest in recent literature. Intensive care coordination is not a linear process, and intensive care teams often fail to discuss how to implement goals, trigger and align activities, or reflect on their performance. Despite a move toward interdisciplinary team working, clinical decision-making is still problematic and continues to be perceived as a top-down and authoritative process. The topic of team leadership in intensive care is underexplored and requires further research.

SUMMARY

Based on findings from the most recent research evidence in medicine and management, four principles are identified for improving the effectiveness of team working in intensive care: engender professional efficacy, create stable teams and leaders, develop trust and participative safety, and enable frequent team reflexivity.

Improving recovery time following heart transplantation: the role of the multidisciplinary health care team

BACKGROUND

The care of cardiac transplant patients is complex requiring a finely orchestrated endeavor to save a patient's life. Given the chronic and complex nature of these patients, multiple disciplines are involved in their care. Recognizing difficulties with communication among team members and striving for improved efficiencies in our pretransplant listing process and in our inpatient care, our team was prompted to change the existing approach to patient care related to heart transplantation.

METHODS

Daily multidisciplinary rounds were instituted and the format of the weekly Multidisciplinary Review Committee (MDRC) meetings was modified with the list of attendees broadened to include a larger interdisciplinary team. Additionally, the approach to patient care was analyzed for process improvement.

RESULTS

The quality improvements are improved communication and throughput, quantified in an 85% decrease in time to complete transplant evaluation, a 37% decrease in median length of stay posttransplantation, and a 33% reduction in the 30 day readmission rate. In addition, pre- and posttransplant caregivers now participate in MDRC in person or via an electronic meeting platform to support the continuum of care. Quality metrics were chosen and tracked via a transparent electronic platform allowing all involved to assess progress toward agreed upon goals. These were achieved in an 18 month time period following the recruitment of new leadership and invested team members working together as a multidisciplinary team to improve the quality of cardiac transplant care.

DISCUSSION

Implementation of daily multidisciplinary rounds and expansion of the attendees for the MDRC meetings improved care related to heart transplantation.

Care transitions: integrating transition theory and complexity science concepts

Care transitions, defined as hospital discharge or movement from one health care setting to another, are currently a major concern of health care providers and policy makers. Extensive empirical research has been conducted on care transitions, but the theoretical foundations are rarely made explicit. We propose that integrating concepts on complex adaptive systems from complexity science with classic theory on transitions in nursing provides a powerful new lens through which to study care transitions and improve transition outcomes. We summarize concepts from both theoretical approaches, propose an expanded model of transitions, and apply the model to the transition from hospital to home.

The relationship between organizational culture and family satisfaction in critical care

OBJECTIVES

Family satisfaction with critical care is influenced by a variety of factors. We investigated the relationship between measures of organizational and safety culture, and family satisfaction in critical care. We further explored differences in this relationship depending on intensive care unit survival status and length of intensive care unit stay of the patient.

DESIGN

Cross-sectional surveys.

SETTING

Twenty-three tertiary and community intensive care units within three provinces in Canada.

SUBJECTS

One thousand two-hundred eighty-five respondents from 2374 intensive care unit clinical staff, and 880 respondents from 1381 family members of intensive care unit patients.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Intensive care unit staff completed the Organization and Management of Intensive Care Units survey and the Hospital Survey on Patient Safety Culture. Family members completed the Family Satisfaction in the Intensive Care Unit 24, a validated survey of family satisfaction. A priori, we analyzed adjusted relationships between each domain score from the culture surveys and either satisfaction with care or satisfaction with decision-making for each of four subgroups of family members according to patient descriptors: intensive care unit survivors who had length of intensive care unit stay <14 days or >14 days, and intensive care unit nonsurvivors who had length of stay <14 days or ≥14 days. We found strong positive relationships between most domains of organizational and safety culture, and satisfaction with care or decision-making for family members of intensive care unit nonsurvivors who spent at least 14 days in the intensive care unit. For the other three groups, there were only a few weak relationships between domains of organizational and safety culture and family satisfaction.

CONCLUSIONS

Our findings suggest that the effect of organizational culture on care delivery is most easily detectable by family members of the most seriously ill patients who interact frequently with intensive care unit staff, who are intensive care unit nonsurvivors, and who spend a longer time in the intensive care unit. Positive relationships between measures of organizational and safety culture and family satisfaction suggest that by improving organizational culture, we may also improve family satisfaction.

Neonatal Informatics: Information Technology to Support Handoffs in Neonatal Care

Communication failures during physician handoffs represent a significant source of preventable adverse events. Computerized sign-out tools linked to hospital electronic medical record systems and customized for neonatal care can facilitate standardization of the handoff process and access to clinical information, thereby improving communication and reducing adverse events. It is important to note, however, that adoption of technological tools alone is not sufficient to remedy flawed communication processes. OBJECTIVES: After completing this article, readers should be able to: Identify key elements of a computerized sign-out tool.Describe how an electronic tool might be customized for neonatal care.Appreciate that technological tools are only one component of the handoff process they are designed to facilitate.

Failure to rescue in neonatal care

Failure to rescue (FTR) has been described as the end result of a series of events relating to the environment of care and nursing quality. Only recently has FTR as a process measure been applied to perinatal care settings. Nurses' continuous presence at the bedside puts them in a privileged position to recognize signs of clinical deterioration and to take action. Many factors contribute to nurses' ability to save lives when infants develop complications. Although such factors are often system-related, nurses may be held responsible if they do not act according to an acceptable standard of care. In the neonatal intensive care unit, FTR has not been applied or adopted as a measure of nursing quality. This article describes how FTR is relevant in the neonatal intensive care unit and outlines nursing and system actions that can be taken to rescue some of the hospital's most vulnerable patients.

Learning relational policies from electronic health record access logs

Modern healthcare organizations (HCOs) are composed of complex dynamic teams to ensure clinical operations are executed in a quick and competent manner. At the same time, the fluid nature of such environments hinders administrators' efforts to define access control policies that appropriately balance patient privacy and healthcare functions. Manual efforts to define these policies are labor-intensive and error-prone, often resulting in systems that endow certain care providers with overly broad access to patients' medical records while restricting other providers from legitimate and timely use. In this work, we propose an alternative method to generate these policies by automatically mining usage patterns from electronic health record (EHR) systems. EHR systems are increasingly being integrated into clinical environments and our approach is designed to be generalizable across HCOs, thus assisting in the design and evaluation of local access control policies. Our technique, which is grounded in data mining and social network analysis theory, extracts a statistical model of the organization from the access logs of its EHRs. In doing so, our approach enables the review of predefined policies, as well as the discovery of unknown behaviors. We evaluate our approach with 5 months of access logs from the Vanderbilt University Medical Center and confirm the existence of stable social structures and intuitive business operations. Additionally, we demonstrate that there is significant turnover in the interactions between users in the HCO and that policies learned at the department-level afford greater stability over time.