Association Between Nurse Copatient Illness Severity and Mortality in the ICU.

OBJECTIVES: In the context of traditional nurse-to-patient ratios, ICU patients are typically paired with one or more copatients, creating interdependencies that may affect clinical outcomes. We aimed to examine the effect of copatient illness severity on ICU mortality. DESIGN: We conducted a retrospective cohort study using electronic health records from a multihospital health system from 2018 to 2020. We identified nurse-to-patient assignments for each 12-hour shift using a validated algorithm. We defined copatient illness severity as whether the index patient's copatient received mechanical ventilation or vasoactive support during the shift. We used proportional hazards regression with time-varying covariates to assess the relationship between copatient illness severity and 28-day ICU mortality. SETTING: Twenty-four ICUs in eight hospitals. PATIENTS: Patients hospitalized in the ICU between January 1, 2018, and August 31, 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The main analysis included 20,650 patients and 84,544 patient-shifts. Regression analyses showed a patient's risk of death increased when their copatient received both mechanical ventilation and vasoactive support (hazard ratio [HR]: 1.30; 95% CI, 1.05-1.61; p = 0.02) or vasoactive support alone (HR: 1.82; 95% CI, 1.39-2.38; p < 0.001), compared with situations in which the copatient received neither treatment. However, if the copatient was solely on mechanical ventilation, there was no significant increase in the risk of death (HR: 1.03; 95% CI, 0.86-1.23; p = 0.78). Sensitivity analyses conducted on cohorts with varying numbers of copatients consistently showed an increased risk of death when a copatient received vasoactive support. CONCLUSIONS: Our findings suggest that considering copatient illness severity, alongside the existing practice of considering individual patient conditions, during the nurse-to-patient assignment process may be an opportunity to improve ICU outcomes.

Work Environment and Operational Failures Associated With Nurse Outcomes, Patient Safety, and Patient Satisfaction.

BACKGROUND: Operational failures, defined as the inability of the work system to reliably provide information, services, and supplies needed when, where, and to who, are a pervasive problem in U.S. hospitals that disrupt nurses' ability to provide safe and effective care. OBJECTIVES: We examined the relationship between operational failures, patient satisfaction, nurse-reported quality and safety, and nurse job outcomes (e.g., burnout and job satisfaction) and whether differences in hospital work environments explained the relationship. METHODS: We conducted a cross-sectional analysis using population-based survey data from 11,709 registered nurses in 415 hospitals who participated in the RN4CAST-US nurse survey (2015-2016) and the 2016 Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey. The RN4CAST-US nurse survey focused on hospital quality and safety, job outcomes, and hospital work environments. The HCAHPS survey collected publicly reported patient data on their satisfaction with their care. Operational failures were evaluated using an eight-item composite measure that assessed missing supplies, orders, medication, missing/wrong patient diet, electronic documentation problems, insufficient staff, and time spent on workarounds and nonnursing tasks. Multilevel regression models were used to test the hypothesized relationships. RESULTS: Operational failures were associated with low patient satisfaction scores, poor quality and safety outcomes, and poor nurse job outcomes, and those associations were partly accounted for by hospital work environments. DISCUSSION: Operational failures prevent high-quality care and positive patient and nurse outcomes. Operational failures and the hospital work environment should be targeted simultaneously to maximize quality improvement efforts. Hospital leadership should work with frontline staff to identify and target the sources of operational failures in nursing units. Improvements to hospital work environments may reduce the occurrence of operational failures.

Nurse Education and Hospital Readmissions for Children With and Without a Mental Health Condition.

OBJECTIVES: In adults, receiving care in a hospital with more baccalaureate-prepared nurses improves outcomes. This relationship is magnified in adults with serious mental illness or cognitive impairment. Whether the same is true in children with and without a mental health condition is unknown. The study purposes were to determine 1) whether the proportion of baccalaureate-prepared nurses affected the odds of readmission in children; and 2) whether this relationship differed for children with a mental health condition. PATIENTS AND METHODS: We linked cross-sectional data from the 2016 Healthcare Cost and Utilization Project State Inpatient Databases, the RN4CAST-US nurse survey in Florida, and the American Hospital Association. Inclusion criteria were ages 3 to 21 years. Mental health conditions were defined as psychiatric or developmental/behavioral diagnoses. These were identified using the Child and Adolescent Mental Health Disorders Classification System. We used multivariable, hierarchical logistic regression models to assess the relationship between nurse training and readmissions. RESULTS: In 35 081 patients admitted to 122 hospitals with 4440 nurses, 21.0% of patients had a mental health condition and 4.2% had a 7-day readmission. For individuals without a mental health condition, each 10% increase in the proportion of baccalaureate-prepared nurses was associated with 8.0% lower odds of readmission (odds ratio = 0.92, 95% confidence interval = 0.87-0.97). For those with a mental health condition, each 10% increase in the proportion of baccalaureate-prepared nurses was associated with 16.0% lower odds of readmission (odds ratio = 0.84, 95% confidence interval = 0.78-0.91). CONCLUSIONS: A higher proportion of baccalaureate-educated nurses is associated with lower odds of readmission for pediatric patients. This association has a larger magnitude in patients with a mental health condition.

The Use of Electronic Health Record Metadata to Identify Nurse-Patient Assignments in the Intensive Care Unit: Algorithm Development and Validation.

BACKGROUND: Nursing care is a critical determinant of patient outcomes in the intensive care unit (ICU). Most studies of nursing care have focused on nursing characteristics aggregated across the ICU (eg, unit-wide nurse-to-patient ratios, education, and working environment). In contrast, relatively little work has focused on the influence of individual nurses and their characteristics on patient outcomes. Such research could provide granular information needed to create evidence-based nurse assignments, where a nurse's unique skills are matched to each patient's needs. To date, research in this area is hindered by an inability to link individual nurses to specific patients retrospectively and at scale. OBJECTIVE: This study aimed to determine the feasibility of using nurse metadata from the electronic health record (EHR) to retrospectively determine nurse-patient assignments in the ICU. METHODS: We used EHR data from 38 ICUs in 18 hospitals from 2018 to 2020. We abstracted data on the time and frequency of nurse charting of clinical assessments and medication administration; we then used those data to iteratively develop a deterministic algorithm to identify a single ICU nurse for each patient shift. We examined the accuracy and precision of the algorithm by performing manual chart review on a randomly selected subset of patient shifts. RESULTS: The analytic data set contained 5,479,034 unique nurse-patient charting times; 748,771 patient shifts; 87,466 hospitalizations; 70,002 patients; and 8,134 individual nurses. The final algorithm identified a single nurse for 97.3% (728,533/748,771) of patient shifts. In the remaining 2.7% (20,238/748,771) of patient shifts, the algorithm either identified multiple nurses (4,755/748,771, 0.6%), no nurse (14,689/748,771, 2%), or the same nurse as the prior shift (794/748,771, 0.1%). In 200 patient shifts selected for chart review, the algorithm had a 93% accuracy (ie, correctly identifying the primary nurse or correctly identifying that there was no primary nurse) and a 94.4% precision (ie, correctly identifying the primary nurse when a primary nurse was identified). Misclassification was most frequently due to patient transitions in care location, such as ICU transfers, discharges, and admissions. CONCLUSIONS: Metadata from the EHR can accurately identify individual nurse-patient assignments in the ICU. This information enables novel studies of ICU nurse staffing at the individual nurse-patient level, which may provide further insights into how nurse staffing can be leveraged to improve patient outcomes.

Characterizing intensive care unit rounding teams using meta-data from the electronic health record.

PURPOSE: Teamwork is an important determinant of outcomes in the intensive care unit (ICU), yet the nature of individual ICU teams remains poorly understood. We examined whether meta-data in the form of digital signatures in the electronic health record (EHR) could be used to identify and characterize ICU teams. METHODS: We analyzed EHR data from 27 ICUs over one year. We linked intensivist physicians, nurses, and respiratory therapists to individual patients based on selected EHR meta-data. We then characterized ICU teams by their members' overall past experience and shared past experience; and used network analysis to characterize ICUs by their network's density and centralization. RESULTS: We identified 2327 unique providers and 30,892 unique care teams. Teams varied based on their average team member experience (median and total range: 262.2 shifts, 9.0-706.3) and average shared experience (median and total range: 13.2 shared shifts, 1.0-99.3). ICUs varied based on their network's density (median and total range: 0.12, 0.07-0.23), degree centralization (0.50, 0.35-0.65) and closeness centralization (0.45, 0.11-0.60). In a regression analysis, this variation was only partially explained by readily observable ICU characteristics. CONCLUSIONS: EHR meta-data can assist in the characterization of ICU teams, potentially providing novel insight into strategies to measure and improve team function in critical care.

Hospital nurse staffing and sepsis protocol compliance and outcomes among patients with sepsis in the USA: a multistate cross-sectional analysis.

OBJECTIVES: Sepsis is a serious inflammatory response to infection with a high death rate. Timely and effective treatment may improve sepsis outcomes resulting in mandatory sepsis care protocol adherence reporting. How the impact of patient-to-nurse staffing compares to sepsis protocol compliance and patient outcomes is not well understood. This study aimed to determine the association between hospital sepsis protocol compliance, patient-to-nurse staffing ratios and patient outcomes. DESIGN: A cross-sectional study examining hospital nurse staffing, sepsis protocol compliance and sepsis patient outcomes, using linked data from nurse (2015-2016, 2020) and hospital (2017) surveys, and Centers for Medicare and Medicaid Services Hospital Compare (2017) and corresponding MedPAR patient claims. SETTING: 537 hospitals across six US states (California, Florida, Pennsylvania, New York, Illinois and New Jersey). PARTICIPANTS: 252 699 Medicare inpatients with sepsis present on admission. MEASURES: The explanatory variables are nurse staffing and SEP-1 compliance. Outcomes are mortality (within 30 and 60 days of index admission), readmissions (within 7, 30, and 60 days of discharge), admission to the intensive care unit (ICU) and lengths of stay (LOS). RESULTS: Sepsis protocol compliance and nurse staffing vary widely across hospitals. Each additional patient per nurse was associated with increased odds of 30-day and 60-day mortality (9% (OR 1.09, 95% CI 1.05 to 1.13) and 10% (1.10, 95% CI 1.07 to 1.14)), 7-day, 30-day and 60-day readmission (8% (OR 1.08, 95% CI 1.05 to 1.11, p<0.001), 7% (OR 1.07, 95% CI 1.05 to 1.10, p<0.001), 7% (OR 1.07, 95% CI 1.05 to 1.10, p<0.001)), ICU admission (12% (OR 1.12, 95% CI 1.03 to 1.22, p=0.007)) and increased relative risk of longer LOS (10% (OR 1.10, 95% CI 1.08 to 1.12, p<0.001)). Each 10% increase in sepsis protocol compliance was associated with shorter LOS (2% ([OR 0.98, 95% CI 0.97 to 0.99, p<0.001)) only. CONCLUSIONS: Outcomes are more strongly associated with improved nurse staffing than with increased compliance with sepsis protocols.

The association between hospital nursing resource profiles and nurse and patient outcomes.

AIMS: To identify and describe profiles of nursing resources and compare nurse and patient outcomes among the identified nursing resource profiles. BACKGROUND: Research linking nurse education, staffing, and the work environment treats these nursing resources as separate variables. Individual hospitals exhibit distinct profiles of these resources. METHODS: This cross-sectional secondary analysis used 2006 data from 692 hospitals in four states. Latent class mixture modelling was used to identify resource profiles. Regression models estimated the associations among the profiles and outcomes. RESULTS: Three profiles were identified (better, mixed and poor) according to their nursing resource levels. Hospitals with poor profiles were disproportionately mid-sized, for-profit, and had lower technology capability. Nurse job outcomes, patient mortality and care experiences were significantly improved in hospitals with better resource profiles. CONCLUSIONS: Hospitals exhibit distinct profiles of nursing resources that reflect investments into nursing. Nurse and patient outcomes and patients' experiences are improved in hospitals with better nursing resource profiles. This finding is consistent with the literature that has examined these resources independently. IMPLICATIONS FOR NURSING MANAGEMENT: Nurse managers can identify their nursing resource profile and the associated outcomes. Our results show the advantages of improving one's hospital nursing resource profile, motivating managers to make an informed decision regarding investments in nursing resources.

The Association of Hospital Magnet® Status and Pay-for-Performance Penalties.

The Centers for Medicare and Medicaid Services' Pay-for-Performance (P4P) programs aim to improve hospital care through financial incentives for care quality and patient outcomes. Magnet® recognition-a potential pathway for improving nurse work environments-is associated with better patient outcomes and P4P program scores, but whether these indicators of higher quality are substantial enough to avoid penalties and thereby impact hospital reimbursements is unknown. This cross-sectional study used a national sample of 2,860 hospitals to examine the relationship between hospital Magnet® status and P4P penalties under P4P programs: Hospital Readmission Reduction Program, Hospital-Acquired Conditions (HAC) Reduction Program, Hospital Value-Based Purchasing (VBP) Program. Magnet® hospitals were matched 1:1 with non-Magnet hospitals accounting for 13 organizational characteristics including hospital size and location. Post-match logistic regression models were used to compute a hospital's odds of penalties. In a national sample of hospitals, 77% of hospitals experienced P4P penalties. Magnet® hospitals were less likely to be penalized in the VBP program compared to their matched non-Magnet counterparts (40% vs. 48%). Magnet® status was associated with 30% lower odds of VBP penalties relative to non-Magnet hospitals. Lower P4P program penalties is one benefit associated with achieving Magnet® status or otherwise maintaining high-quality nurse work environments.

Comparing medication adherence using a smartphone application and electronic monitoring among patients with acute coronary syndrome.

AIM: The purpose of this study was to determine the extent of agreement between adherence measures obtained using two technological interventions, electronic monitoring (EM) and a smartphone application (App). BACKGROUND: Clinicians, patients, and researchers depend on valid measurements of medication adherence to inform the delivery of preemptive care when needed. Technology is routinely used for monitoring medication adherence in both clinical practice and research, yet there is a dearth of research comparing novel App based approaches to traditional approaches used for assessing medication adherence. METHODS: Adherence rates were captured on both the EM and the App for 3697 daily observations from 44 participants with acute coronary syndrome over 90 days immediately following discharge from acute care. For EM, adherence was measured using EM equipped pill bottles. For the App, adherence was measured by having participants upload daily photos to the App prior to taking their daily aspirin. Agreement was assessed using a Bland-Altman analysis. RESULTS: The mean adherence rate was higher on the App, 92%, than the EM, 78% (p < 0.001). The mean difference in adherence rates between these methods was 14% (95% Confidence Interval: -23%, -5%). CONCLUSIONS: These findings illustrate a lack of agreement between technological interventions used for measuring adherence in cardiovascular patient populations, with higher adherence rates observed with the App compared to EM. These findings are salient given the increased reliance on telehealth due to the ongoing COVID-19 pandemic.

Predictors of specialty certification among paediatric hospital nurses.

AIMS AND OBJECTIVES: To evaluate differences in hospitals' proportion of specialty certified nurses and to determine whether and to what extent individual nurse characteristics and organisational hospital characteristics are associated with a nurse's likelihood of having specialty certification. BACKGROUND: Prior research has shown that patients in hospitals with high proportions of specialty certified nurses have better outcomes including lower mortality and fewer adverse events, yet less is known about what motivates nurses to obtain specialty certification. METHODS AND DESIGN: Cross-sectional study of paediatric nurses in 119 acute care hospitals. Multivariate logistic regression models were used to determine the association between individual nurse characteristics, organisational hospital characteristics and an individual nurses' likelihood of holding a specialty certification. STROBE was followed. RESULTS: The proportion of certified nurses varies substantially among hospitals, with Magnet® hospitals being significantly more likely, on average, to have higher proportions of certified nurses. Nurses in children's hospitals were no more likely than paediatric nurses in general hospitals to be certified. A nurse's years of experience and bachelors-preparation were significantly associated with higher odds of having certification. The strongest predictors of certification were favourable nurse work environments and Magnet® -designation of the hospital. CONCLUSIONS: While individual attributes of the nurse were associated with a nurse's likelihood of having a specialty certification, the strongest predictors of certification were modifiable attributes of the hospital-a favourable nurse work environment and Magnet® -designation. RELEVANCE TO CLINICAL PRACTICE: Hospital administrators seeking to increase the proportion of specialty certified nurses in their organisation should look to improvements in the organisation's nurse work environment as a possible mechanism.

Evaluation of hospital nurse-to-patient staffing ratios and sepsis bundles on patient outcomes.

BACKGROUND: Despite nurses' responsibilities in recognition and treatment of sepsis, little evidence documents whether patient-to-nurse staffing ratios are associated with clinical outcomes for patients with sepsis. METHODS: Using linked data sources from 2017 including MEDPAR patient claims, Hospital Compare, American Hospital Association, and a large survey of nurses, we estimate the effect of hospital patient-to-nurse staffing ratios and adherence to the Early Management Bundle for patients with Severe Sepsis/Septic Shock SEP-1 sepsis bundles on patients' odds of in-hospital and 60-day mortality, readmission, and length of stay. Logistic regression is used to estimate mortality and readmission, while zero-truncated negative binomial models are used for length of stay. RESULTS: Each additional patient per nurse is associated with 12% higher odds of in-hospital mortality, 7% higher odds of 60-day mortality, 7% higher odds of 60-day readmission, and longer lengths of stay, even after accounting for patient and hospital covariates including hospital adherence to SEP-1 bundles. Adherence to SEP-1 bundles is associated with lower in-hospital mortality and shorter lengths of stay; however, the effects are markedly smaller than those observed for staffing. DISCUSSION: Improving hospital nurse staffing over and above implementing sepsis bundles holds promise for significant improvements in sepsis patient outcomes.

Safety and Quality of Pediatric Care in Freestanding Children's and General Hospitals.

OBJECTIVES: The purpose of this study was to evaluate quality and safety of care in acute pediatric settings from the perspectives of nurses working at the bedside and to investigate hospital-level factors associated with more favorable quality and safety. METHODS: Using data from a large survey of registered nurses in 330 acute care hospitals, we described nurses' assessments of safety and quality of care in inpatient pediatric settings, including freestanding children's hospitals (FCHs) (n = 21) and general hospitals with pediatric units (n = 309). Multivariate logistic regression models were used to estimate the effects of being a FCH on favorable reports on safety and quality before and after adjusting for hospital-level and nurse characteristics and Magnet status. RESULTS: Nurses in FCHs were more likely to report favorably on quality and safety after we accounted for hospital-level and individual nurse characteristics; however, adjusting for a hospital's Magnet status rendered associations between FCHs and quality and safety insignificant. Nurses in Magnet hospitals were more likely to report favorably on quality and safety. CONCLUSIONS: Quality and safety of pediatric care remain uneven; however, the organizational attributes of Magnet hospitals explain, in large part, more favorable quality and safety in FCHs compared with pediatric units in general acute care hospitals. Modifiable features of the nurse work environment common to Magnet hospitals hold promise for improving quality and safety of care. Transforming nurse work environments to keep patients safe, as recommended by the National Academy of Medicine 20 years ago, remains an unfinished agenda in pediatric inpatient settings.

Staffing Trends in Magnet and Non-Magnet Hospitals After State Legislation.

BACKGROUND: Evidence suggests that Magnet and non-Magnet hospitals differ with respect to quality of care. PURPOSE: Our study examined registered nurse (RN) staffing over time in Magnet and non-Magnet hospitals using unit-level, publicly available data in New Jersey. METHODS: A secondary analysis of longitudinal RN staffing data was conducted using mandated, publicly reported data of 64 hospitals representing 12 nursing specialties across 8 years (2008-2015). Staffing ratios were trended over time to compare RN staffing changes in Magnet and non-Magnet hospitals. RESULTS: Staffing was comparable in Magnet and non-Magnet hospitals for 9 of 12 specialties. On average, from 2008 until 2015, RN staffing slightly increased, with a greater percent increase in Magnet hospitals (6.9%) than in non-Magnet hospitals (4.7%). CONCLUSIONS: Over 8 years in New Jersey, RN staffing improved in Magnet and non-Magnet hospitals. Although there was a slight increase for Magnet hospitals, there was no meaningful difference in staffing for all 12 specialties.

Improved work environments and staffing lead to less missed nursing care: A panel study.

AIM: To document how changes in the hospital work environment and nurse staffing over time are associated with changes in missed nursing care. BACKGROUND: Missed nursing care is considered an indicator of poorer care quality and has been associated with worse patient care experiences and health outcomes. Several systematic reviews of cross-sectional studies report that nurses in hospitals with supportive work environments and higher staffing miss less care. Causal evidence demonstrating these relationships is needed. METHODS: This panel study utilized secondary data from 23,650 nurses surveyed in 2006 and 14,935 surveyed in 2016 in 458 hospitals from a four-state survey of random samples of licensed nurses. RESULTS: Over the 10-year period, most hospitals exhibited improved work environments, better nurse staffing and more missed care. In hospitals with improved work environments or nurse staffing, the prevalence and frequency of missed care decreased significantly. The effect on missed care of changes in the work environment was greater than that of nurse staffing. CONCLUSIONS: Changes in the hospital work environment and staffing influence missed care. IMPLICATIONS FOR NURSING MANAGEMENT: Modifications in the work environment and staffing are strategies to mitigate care compromise. Nurse managers should investigate work settings in order to identify weaknesses.