Objective: Pancreatic cancer (PC) is one of the deadliest cancers worldwide. This study examines trends and relationships in PC patients’ hospital admissions, length of stay (LOS), and in-hospital mortality in Florida, while exploring associations of patient, hospital, and county characteristics. Methods: Retrospective data from the Florida Agency for Health Care Administration, American Hospital Association Annual Survey, and Area Health Resource Files were merged from 2010 to 2020. A total of 117,278 patients with primary PC diagnosis were analyzed. Mixed effects models analyzed the LOS and in-hospital mortality. All acute general medical and surgical hospitals in Florida were included. Results: PC admissions increased significantly from 4.68% to 7.09% of total hospital admissions (p < .001), representing a 51% relative increase. Patient age increased from 68.75 to 70.99 years, while LOS decreased from 6.89 to 5.9 days. In-hospital mortality remained stable at 5.13%. Mixed effects regression models demonstrated complex county-level social determinants relationships between population health factors and individual clinical outcomes, and significant racial disparities in mortality outcomes. Black patients exhibited 18% higher odds of in-hospital mortality compared to Non-Hispanic White patients. Federal insurance provided protective effects against mortality. Comorbidity burden strongly predicted mortality risk along with market concentration. Conclusions: Persistent racial disparities in outcomes and pronounced volume-outcome relationships highlight the need for targeted interventions addressing healthcare equity and continued tailored treatment of PC. Policymakers should address these equity issues while supporting regionalization efforts for complex cancer care.
Objective: This is the second study in a series to validate an outcome measure for inpatient psychiatry using outcome scales from the interRAI Mental Health (MH). To further validate the Composite Index of Inpatient Mental Health Status (CIIMHS) and its cross-cutting symptom domains by evaluating the relationship between the CIIMHS, its Domain Scores, and the Global Assessment of Functioning (GAF) (convergent validity). To evaluate the responsiveness of the interRAI MH scale scores and the CIIMHS and its Domain Scores to treatment effects. To use the CIIMHS to calculate an effect size (ES) for entry into a hospital’s Balanced Scorecard (BSC). Methods: We collected pre- and post-treatment scores on eight outcome scales from all RAI-MH assessments of hospital inpatients conducted over two fiscal years, along with GAF scores for one fiscal year, at a large mental health specialty hospital. Building on our previous work, which included a Principal Components Analysis (PCA) of the eight scales, yielding four standardized domain scores (psychosis, depression, impairment, and aggression), we combined these into the CIIMHS. To assess convergent validity, we calculated both parametric and nonparametric correlations between these measures and the GAF scores recorded during the same assessments. To evaluate construct validity, we analyzed changes in scale and domain scores from pre- to post-inpatient treatment across the hospital as a whole and separately for its acute care and addiction inpatient programs. Results: Among all hospital patients and within the acute care program, pre- and post-treatment differences were statistically significant for seven of the eight RAI-MH scale scores, the composite measure, and the four domain scores (construct validity). Correlations between the GAF and the composite measure, as well as GAF and the impairment domain, approached or exceeded 0.60 (convergent validity). Correlations between GAF and other domains were smaller but were statistically significant, especially after treatment. The addiction program showed pre- and post-treatment differences in the scales with pre-treatment elevations, the composite measure, and the depression domain. Pre- and post-treatment outcome scales in the RAI-MH assessment platform demonstrated treatment effects, confirming good construct validity. Relationships with GAF indicated strong convergent validity. We suggest a methodology based on the CIIMHS to calculate a treatment ES for inclusion in the hospital’s BSC.The CIIMHS is a common measure of illness severity. Conclusions: T1vT2 differences, calculated quarterly, can be entered into hospital BSCs indicating quality of care.
Professional nurses, defined in this paper as licensed registered nurses, are a cornerstone of the U.S. healthcare workforce, serving as frontline caregivers and advocates across diverse settings. This is a narrative synthesis which examines the multifaceted challenges currently facing the nursing profession, including workforce shortages, burnout, and inflexibility in skill distribution, which are issues magnified by the COVID-19 pandemic and other public health crises. We examine how demographic shifts, such as an aging population and retiring nurses, along with rapid technological advancements, particularly in digital health and artificial intelligence, are reshaping nursing roles and responsibilities. The evidence presented highlights the critical importance of industry partnerships in addressing these challenges, emphasizing collaboration between nurses and stakeholders in healthcare technology, pharmaceuticals, and medical device manufacturing to develop tools and resources that align with evolving care needs. Additionally, we discuss opportunities for innovation in nursing education, workforce development, and entrepreneurial endeavors aimed at improving workplace conditions and patient outcomes. By analyzing current workforce composition, educational trends, and pathways for strengthening professional practice, the authors aim to inform policy makers, healthcare leaders, and educators about strategies to enhance the future of nursing and ensure the resilience of the broader healthcare system.
Objective: To understand shared-use mobile device deployment, management and usage challenges in healthcare delivery organizations (HDOs), including capabilities and unmet needs in Australia, Canada, the United Kingdom and the United States. Methods: Online survey of 400 HDO clinical and health information technology leaders with institutional responsibilities for the management of shared-use mobile devices. How the challenges identified in the survey can be overcome is explored by examining the deployment of a mobile device management platform. Results: Across nations 92% of respondents agreed that mobile devices are essential tools, yet only 56% had fully implemented shared-use device policies and procedures. Respondents stated improvement is needed in auditing facility device usage: 16% have no consistent policy/process for assigning devices at shift start; 46% use verbal or informal processes. Perceived mobile device benefits include: facilitates delivery of high-quality (94%) and accelerated care (51%) enabling reduced length of stay (86%); increased clinician satisfaction (94%) and reduced burnout (90%); enhanced care team coordination/communication (67%); and improved clinical application access (54%). Challenges in ease of use were endemic, including: securing sensitive information (44%); sharing of access credentials (79%); devices left logged in (74%); and ensuring rapid, frictionless access. Clinicians experience access issues, with frequent helpdesk contact (87%) for lockouts. Clinician frustration occurs when devices are unavailable (87%) or broken, uncharged, or missing applications (86%), delaying care delivery. Management issues included lack of visibility into mobile device usage (40%), assignment (48%), and applications accessed (55%); no centralized system for managing devices (39%); and time-consuming device setup (35%), with little variability by nation. When devices are unavailable or access difficult, 81% stated personal devices are used, an unsafe workaround. Substantial minorities across nations reported still relying on manual paper or digital log of device sign-out. A high mean annual rate of mobile device loss (23% across nations) ensures the negative impact of missing/unavailable devices is substantial, increasing risk of information security breach, delays in care communications and delivery, reduced productivity, shift change disruption, and increased staff frustration. Differences in responses by facility size (bed count) were few and modest. HDOs reported meaningful savings of $1.1 million per year on average by deploying shared-use mobile devices, with 92% indicating improved return on investment and reduced manual management workload. Conclusions: HDOs reported significant perceived challenges in effectively managing shared-use devices, but recognize they facilitate efficient clinical-operational workflows and increased clinician satisfaction. Need exists to overcome substantial capability gaps to systematically manage device fleets while ensuring a friction free, secure and efficient user experience.
Background: Inventory inefficiency remains a systemic barrier to responsive care delivery in low- and middle-income countries (LMICs), particularly in tertiary pediatric hospitals. Challenges include rigid procurement cycles, fragmented data architecture, and insufficient alignment between clinical needs and supply planning. These structural limitations are exacerbated by demand volatility and resource constraints, leading to recurrent stock-outs and waste. Objective: This study evaluates a hybrid inventory management approach combining ABC–XYZ classification, discrete-event simulation (DES), and a context-adapted Just-in-Time (JIT) strategy. The objective is to assess whether these integrated tools can improve inventory responsiveness and cost-effectiveness within the administrative constraints of a public hospital system. Additionally, the study explores how risk-based stratification and simulation modeling can inform pragmatic policy adaptation in LMIC settings. Methods: A mixed-methods study was conducted at Children’s Hospital 1 (Vietnam) from 2019 to 2025. Inventory data were stratified using ABC–XYZ analysis, and a DES model was applied to simulate the effects of JIT policies under real-world constraints. A pilot implementation was performed in the interventional cardiology unit, focusing on high-value, low-variability items.Triangulated data sources included retrospective performance indicators, audit reports, and stakeholder interviews to identify systemic bottlenecks and assess organizational readiness. Results: Simulation projected a 46% reduction in stock-outs, a 35% decrease in inventory days, and over 30% in cost savings. The JIT pilot confirmed feasibility, showing a 72.7% reduction in stock-outs and no clinical delays. However, systemic constraints—procurement inflexibility, data fragmentation, and weak supplier accountability—were identified as key bottlenecks to scalability.Feedback from clinical and logistics personnel further indicated improved predictability and coordination under the hybrid model. Conclusions: The findings highlight that technical innovations in inventory control must be embedded within broader administrative reform. Strategic procurement agility, digital integration, and governance restructuring are essential for sustainable inventory modernization in LMIC hospitals. JIT is most effective when selectively applied within a hybrid governance framework that balances operational efficiency with clinical risk mitigation.
Objective: To identify key hospital food service attributes that influence patient satisfaction and inform actionable improvements in meal delivery and service quality. Methods: This cross-sectional study assessed patient satisfaction with hospital food service using a modified SERVQUAL-based survey instrument. Inpatients rated both expectations and experiences across multiple service dimensions. Descriptive statistics and regression analysis were conducted to identify food service features linked to satisfaction. Results: Food quality, perceived value, empathy, and meal diversity showed strong positive influence, while longer hospital stays and slower service were associated with lower ratings. Responsiveness also played a role in shaping overall satisfaction. These findings highlight actionable opportunities for improving patient-centered care. Conclusions: Enhancing menu design, staff engagement, and delivery efficiency may elevate meal satisfaction and support broader institutional quality goals.
Objective: Evaluate if artificial intelligence (AI)-based virtual triage and care referral (VTCR) improved care acuity alignment and has the potential to reduce unwarranted, avoidable care costs when integrated into the patient engagement capabilities of an Australian private health insurance company. Methods: A cross-sectional study compared patient pre- and post-VTCR care intent across 4,471 encounters to evaluate the degree of clinical care acuity re-alignment (or divergence) which occurred and potential associated cost savings. Results: Overall compliance or alignment with triage recommendations was high (74.0%), and VTCR was effective in educating patients about the most appropriate care to meet their actual clinical needs. One-half of patients (50.5%) changed their care intent. Following VTCR there was a 91.3% reduction of patients with uncertain care intent (39.8 percentage points [PP]); a 56.5% (6.2 PP) increase in intent to engage self-care, and a 35.7% (0.5 PP) decrease in emergency care intent (all p < .05). This yielded a potential $4.27 (8.6%) overall net savings per completed VTCR encounter, with potential savings of $284.55 (72.2%) per completed encounter among patients initially intending to seek emergency care, and 35 unnecessary outpatient visits potentially avoided per 1,000 encounters producing potential savings of $3.39 (6.5%) per completed encounter among patients initially intending to seek outpatient care. Almost 10% of patients intended to book a clinically appropriate telemedicine consultation following VTCR. Conclusions: VTCR was found to be potentially clinically and cost-effective in re-directing patients who had an initial care intent not supported by their actual clinical acuity, reducing patient care uncertainty and potentially avoidable care utilization. Future research should include clinical validation of patient diagnosis and care services delivered as a primary outcome in order to confirm the potential savings identified in this study.
Objective: To adapt and psychometrically evaluate the SERVQUAL-HF instrument for hospital food service quality assessment by validating its dimensional structure, reliability, and ability to identify key predictors of patient satisfaction. Methods: This study uses the SERVQUAL framework to assess hospital food service quality, adding variables geared toward meal-specific aspects. A 7-point Likert-scale survey was performed in two hospitals to compare patient expectations to actual reality. Results: Statistical validation, including multilinear regression and correlation analysis, revealed that responsiveness, food quality, perceived value, empathy, and meal variety are all significant predictors of customer satisfaction. SERVQUAL for Hospital Food Service (SERVQUAL-HF)’s dependability in assessing service quality across hospital settings was proven by a psychometric examination. The study emphasizes methodological modifications, such as the significance of empathy and perceived value, and suggests directions for future research in healthcare service measuring. Conclusions: The findings add to the literature by improving the use of SERVQUAL in non-traditional hospital settings, ensuring comprehensive evaluation of patient-centered food service models.
Background: Sepsis increases mortality and is a global healthcare concern. In the United States evidence-based early identification and treatment protocols are required in some states. Predictive analytics is one option to meet this requirement. Objective: The purpose of this system-wide initiative was to develop an interprofessional team to implement, evaluate, and optimize an early alert system for patients at high risk for sepsis utilizing predictive analytics to improve patient outcomes. Methods: The Sepsis Predictive Model and customized Best Practice Advisory (BPA) were evaluated utilizing a phased-rollout and pilot-testing. Regular meetings were conducted to analyze data and strategize iterative changes. End users were educated. Results: Pilot tests established the most effective alert-sepsis trigger scores; scores > 5 resulted in a 54% decrease in alerts. The Concordance Statistic (C-Stat) for the system-wide roll out was 0.765. The proportion of patients who had a BPA alert, had sepsis and an intervention (18.83%) was significantly greater than the proportion of patients who had a BPA alert had sepsis, and did not have an intervention (4.35%, p-value < .001). Similar results were found for the proportion of patients with a final diagnosis of infection who had a BPA alert, and an intervention, compared to those who did not. Early warning of potential sepsis resulted in a reduction in sepsis mortality rates not present on admission. Conclusions: An interprofessional team approach to leveraging established evidence and harnessing predictive analytics, fostered a customized collaborative protocol that improved sepsis care. Predictive analytics, tailored to clinical settings, is a powerful tool for advancing sepsis management.
Objective: Effective interprofessional collaboration (IPC) is a cornerstone of high-quality healthcare delivery. Given the complexity of healthcare systems, optimal patient outcomes depend on the ability of professionals across disciplines to work cohesively. Conversely, weak collaboration among health workers contributes to poor service quality, a challenge evident in Nigeria. This study explored the perceptions and practices of IPC among healthcare professionals at the Federal Medical Centre, Owo, Ondo State, Nigeria. Methods: A cross-sectional survey was conducted using the validated Assessment of Interprofessional Collaboration Scale questionnaire, rated on a five-point Likert scale. Data analysis involved mean ± standard deviation for continuous variables and proportions/percentages for categorical data. Results: A total of 185 respondents participated, with the majority (77.3%) aged between 20–39 years. Females accounted for 61.1% of the sample, though gender distribution varied by profession: nursing remained predominantly female (91.2%), while medical laboratory science was male-dominated (87.5%). Among specialists, laboratory scientists (37.5%), physiotherapists (35%), and doctors (33.3%) had the highest proportions. Doctors and nurses recorded the highest mean scores across most IPC domains, particularly role clarity (4.40 and 4.33, respectively) and trust (4.45 and 4.34). Administrators and “others” consistently recorded the lowest scores (3.12–3.74). ANOVA revealed significant differences across all parameters (p < .001). Post-hoc analysis confirmed stronger doctor–nurse collaboration compared to other groups. Conclusions: Findings revealed that doctors demonstrated the strongest interprofessional collaboration, followed by nurses and pharmacists. In contrast, physiotherapists, laboratory scientists, administrators, and other cadres reported lower levels of collaboration. Notably, doctors consistently rated themselves highly and were similarly rated by other professional groups. Strengthening IPC across all healthcare professions remains essential to improving teamwork and ensuring better patient outcomes.
Background:Global climate change has increased the likelihood of natural disasters, including hurricanes, floods, wildfires, tornadoes, and earthquakes; this increased risk presents acute socioecological disturbances that generate cascading impacts across healthcare systems, social structures, and economic frameworks. Forty-three percent of Atlantic hurricanes that make U.S. landfall hit the southeastern United States, and their increasing intensity threatens the healthcare infrastructure. Hospital cost-to-charge ratios (CCRs) vary between rural and urban facilities, but hurricane risk impacts on hospital financial performance remain poorly understood. Objective:To examine relationships among hurricane risk, geographic location, and hospital CCRs among southeastern hospitals. Methods:A cross-sectional analysis was used to merge 2021 CMS Cost Report data with 2023 FEMA National Risk Index data for 1,030 hospitals across eight southeastern states. All hospitals within this region were included except for federally funded hospitals due to their unique funding model. Each hospital self-reports its categorization of urban or rural on the CMS Cost Report. Multivariate regression was used to examine associations among log-transformed CCR and hurricane risk percentile, rural/urban location, and hospital quick ratio. Results:Among 1,030 hospitals analyzed, 52% were rural and 48% urban. The regression model explained 24.7% of CCR variation (adjusted R 2 = 0.2465, F = 85.18, p < .0001). All predictors were statistically significant (p < .0001). Counter to expectations, each 1-point increase in hurricane risk percentile was associated with a 0.1% decrease in CCR, indicating improved cost efficiency in higher-risk areas. LOGCCR = - .75714 - .00840 (NAPCT) - .26551 (RURAL) + .01491 (QUICK) - .00011 (QUICK2). Rural hospitals as indicated by the CMS Cost Report demonstrated 26.5% lower CCR compared to urban hospitals. Hospital quick ratio showed a curvilinear relationship with CCR; at the mean quick ratio (3.819), each 1-unit increase was associated with a 1.4% increase in CCR. No significant multicollinearity was detected among predictor variables. Conclusions:Hurricane risk is paradoxically associated with lower hospital CCR, suggesting complex financial adaptations in high-risk areas. Rural hospitals maintain more favorable cost structures than urban facilities, and policymakers should consider these geographic variations in disaster preparedness strategies.
Objective: Occupational sharps and needlestick injuries (SNSI) are a significant and persistent challenge in the U.S. healthcare work environment. With the purpose of better delineating contributing factors for a ubiquitous occupational injury among healthcare workers, we undertook a two-component study of SNSIs among physician residents and nurses at an academic health center. Methods: Retrospective injury data among nurses (N = 58) and medical residents (N = 63) were analyzed. A 35-item crosssectional survey was used to evaluate the prevalence, non-reporting, and contributing factors among physician residents who sustained a SNSI (N = 76). Results: Physician residents had a rate of injury that was 11.0 SNSIs/100 medical residents/year compared to nurses at 3.2 SNSIs/100 nurses/year; a rate three-fold higher. Physician residents in neurosurgery, otolaryngology, obstetrics and gynecology, and general surgery reported the highest rates of injury. Conclusions: Our results underscore the need for a more comprehensive study to better identify injury drivers specific to the operating room environment.
Objective: The number of telemedicine solutions is growing, and studies are focusing on feasibility assessments. It is time to consider the fundamentals of deploying telemedicine solutions and provide recommendations for effective implementation.Methods: A qualitative data collection through observation and interview was conducted at our tertiary academic hospital after 2 years of experience with a telemedicine solution. The data underwent semantic analysis, and hypotheses were compared with a literature review to provide recommendations for implementation. Between February 2021 and October 2022, patients’ opinions were gathered through feedback questionnaires using the institutional mHealth application, a key component of the deployed telemedicine solution. Satisfaction results guided conclusions and reevaluations.Results: During April 2021, 14 interviews were conducted with 7 medical department chairs, 2 head nurses and 5 administrative leaders. Between February 2021 and October 2022, a total of 760 surgical patients used the mobile application CHUV@home and 478 (62.9%) answered the feedback questionnaire. During this period, 1,226 surgical patients were included, and 760 used the mobile application, generating 1,693 alerts with an average resolution time of 130 minutes per alert. Feedback questionnaires were answered by 478 (62.9%) patients, with global satisfaction. Patients and healthcare workers opinions were aligned to foster a design of telemedicine experience. Results were presented in the form of a risk matrix. Five major risks and their mitigation recommendations were highlighted.Conclusions: With the growing number of telemedicine solutions, many studies focus on feasibility assessment. The present study suggests that a holistic approach, engaging healthcare workers and patients, is essential for developing a meaningful and sustainable telemedicine strategy at a broader systemic level.
Objective: The evolving healthcare landscape, driven by digital transformation and increasing reliance on emerging Artificial Intelligence-derived tools, calls for a reassessment of the competencies required for effective healthcare leadership. Traditional healthcare administration and informatics programs may no longer meet the current and future complexity of the contemporary healthcare system. This study examines how graduate healthcare administration programs could adapt to better equip future leaders with leadership, management, and technical skills.Methods: The research draws on three sources of information that were analyzed by the authors: (1) a comparison of the National Center for Health Leadership Competency Model 3.0TM and the American Medical Informatics Association Health Informatics Core Competencies; (2) analyses of opportunities to integrate health informatics in general and artificial intelligence (AI), in particular - into healthcare administration education competencies; and (3) insights from interviews with 55 C suite executives from 33 U.S. nonprofit health systems.Results: There are areas for integrating and synthesizing competencies from health care and informatics disciplines. In addition, AI may be integrated across a variety of competencies and learning activities. Future executives will require the ability to integrate technology and informatics knowledge and skills into management and leadership competencies, skills, and behaviors.Conclusions: To prepare healthcare leaders for the digital age, educational programs must integrate informatics and AI-driven technologies into their curricula. This includes a focus on data analytics, financial training, regulatory knowledge, and change management. The study calls for a reimagined approach to healthcare education that ensures leaders are equipped to thrive in an increasingly data-driven and regulated environment.
Objective: The case aimed to highlight the increasing absenteeism among pregnant medical workers employed at the Clinical Hospital Centre Rijeka, Croatia. The paper proposed and implemented measures to reduce this trend through coordinated efforts involving the contracted outpatient Occupational Medicine, the Hospital Personnel Department, and the Occupational Safety Department. Methods: A descriptive approach was used to assess the current state of pregnancy-related absenteeism, which fluctuated up to 3% annually of the total 3,500 hospital employees, of whom 81% were females. Results: Immediate action by contracted outpatient Occupational Medicine introduced a selective approach to granting temporary incapacity leave only when the workplace posed a genuine threat to maternal and fetal health. In collaboration with the Occupational Safety Department, temporary reassignment to less hazardous roles was implemented, minimizing absenteeism. Conclusions: The implementation of governmental measures in March 2025, granting significant benefits to pregnant employees, risked straining hospital operations, possibly leading to department closures given the female-dominated workforce. Adhering to Occupational Medicine evaluations and strategically reassigning pregnant workers helped mitigate these risks.
Objective: Music therapy is a credentialed and established allied health profession with increasing prevalence in medical settings across the United States. The field is evidence-based, guided by research and best practice, and music therapy clinicians collaborate inter-professionally to support patients and families during hospitalization. Pediatric music therapists are uniquely situated to improve patient and family care and positively impact the hospital experience. This cross-sectional survey focused on capturing current trends in pediatric music therapy, comparing current data with previously captured data, identifying unique clinical needs of pediatric music therapists; and providing guidance for current clinical considerations.Methods: The REDCap survey yielded 84 responses (n = 84) from pediatric music therapists. Survey data were analyzed using a modified exploratory sequential mixed methods design, incorporating an initial data review, followed by an inductive qualitative analysis, and concluding with a quantitative phase. The approach was selected to provide a comprehensive understanding of current trends in pediatric music therapy, allowing for comparisons with findings from a previous survey, identification of unique clinical needs, and the development of insights to inform current clinical practice considerations.Results: The analyzed data showed significant trends within the pediatric music therapy workforce. The comparison between the previous survey conducted in 2020 and the results from 2023 shows that the demand for music therapy services continues, particularly in the clinical areas of emotional support, coping, rehabilitation, palliative care, and pain management. The data suggest that clarifying career progression opportunities, improving institutional backing, and addressing workload distribution could play a pivotal role in therapist retention and long-term service effectiveness.Conclusions: Music therapists, creative arts therapists, and hospital administrators can use this data to understand resource allocation better and continue growth and support of music therapy within their respective facilities.
Objective: This study examines the impact of telehealth nursing interventions on length of stay (LOS) and ratio of LOS to risk-adjusted length of stay comparing tele-acute and traditional units.Methods: Retrospective data from 6,999 patient visits at tele-acute and traditional hospital units between Q2 2020 and Q4 2022 were collected. Bivariate analysis and the Mann-Whitney U Test were used to determine statistical significance. Multivariate regression was conducted to analyze the factors affecting both LOS and the ratio.Results: Regardless of the model, the findings suggest that LOS was greater in the traditional unit. In the LOS model, the stay was 7 hours and 39 minutes longer per admission in the traditional unit. In the risk-adjusted ratio model, the LOS was 5 hours and 14 minutes longer per admission than in the tele-acute unit.Conclusions: This study contributes to a body of literature that is lacking in the use of telehealth nursing in the acute care setting. Our research offers new perspectives on how telehealth can affect operational measures like LOS and discharge times. This contribution is important as it broadens the scope of telehealth’s benefits beyond traditional remote care, highlighting its potential in fast-paced, acute care settings.
Objective: The purpose of this study was to evaluate nurse knowledge about the risks of exposure to patient bodily waste, nurse perceptions about procedures and reporting, and current levels of satisfaction with how risks of exposure to patient waste are managed. Patient bodily waste management impacts healthcare workers and healthcare organizations. For nurses and other healthcare workers, the risk of exposure to pathogens can have adverse health effects, increase stress, and reduce satisfaction with their job, potentially leading to issues related to retention. Evidence suggests that proper training and using devices to reduce exposure risks and improve shorter bedside toileting, may reduce stress, and improve work satisfaction. Reducing risk of increased healthcare associated infections of patients and healthcare workers may have a positive impact on the organization with reduced cost of care.Methods: A survey focused on nurses’ knowledge about their risk of exposure, nurse understanding of procedures and incident reporting, and morale and satisfaction with their job was conducted. Results. The findings suggest that there were conflicting responses related to the acknowledgement of risk, reporting incidents, and the use of personal protective equipment.Results: The findings suggest that there were conflicting responses related to the acknowledgement of risk, reporting incidents, and the use of personal protective equipment.Conclusions: Organizations benefit from addressing these concerns to improve morale and satisfaction, nurse retention, healthcare worker dignity, and the quality of patient care.
Objective: The study examines whether patient health portal usage significantly increased during the COVID-19 pandemic between 2019 and 2022.Methods: In order to measure patient usage of patient portals before and during the first year of the COVID-19 pandemic, this study used the Health Information National Trends Survey results for 2019, 2020, 2021, and 2022. It was compared, using a least square regression model, to see if there was a significant relationship between increased use of telehealth, the usage of health portals, and the number of times seen by a regular healthcare provider.Results: The number of patients who saw their health care provider thrice a year and used their patient portal pre- and postpandemic increased. However, the overall increase in patients using their portals before and during the first two years of the pandemic remains below 50%.Conclusions: Overall, the pandemic increased patients’ use of telemedicine but only significantly increased their usage of patient portals for those patients who saw their provider three or more times a year. These findings indicate that more interaction with providers might impact future portal usage.
Objective: We sought to analyze public and private hospital patient cohorts in New York City (NYC) to assess differences in hospital access and outcomes from 2009-2022.Methods: Inpatient neurosurgical discharges, as determined by APR-DRG codes, from 2009-2022 were aggregated for seven NYC hospitals, four private and three public, via the Statewide Planning and Research Cooperative System (SPARCS). Statistical analyses (Z-tests) were performed in Python.Results: 325,351 patients were identified, 223,361 private and 101,990 public. Private hospitals had lower high-severity to low-severity and higher high-mortality to low-mortality risk ratios relative to public hospitals (p < .001). Public hospitals treated a higher proportion of stroke and trauma (p < .001). Average length of stay (LOS) was shorter at private hospitals compared to public (5.3 vs. 7.1 days, p < .001). Statistical significance remained when stratifying for illness severity and elective versus non-elective surgery status. Interestingly, cranial trauma cases were associated with a longer LOS in private hospitals relative to public (7.9 vs. 5.7 days, p < .001).Conclusions: While many factors influence outcomes in private versus public hospitals, LOS can mark the efficiency of care. LOS was shorter at private hospitals in all instances except with cranial trauma. Care efficiency is important for hospital reimbursement, which can directly impact available resources for patient care. These findings emphasize the need to further analyze patient accessibility to neurosurgical care at private hospitals and the resources necessary to support neurosurgical practices within public hospitals.
