Estimating the Relationship Between Nurse Staffing and Medication Pass Workload Using National Barcode Data.

BACKGROUND: Measuring and assessing the relationship between inpatient nurse staffing and workload across a national health system is difficult due to challenges in systematically observing inpatient workload at the unit level. OBJECTIVE: The objective of this study was to apply a novel measure of inpatient nurse workload to estimate the relationship between inpatient nurse staffing and nurse workload at the unit level during a key nursing activity: the peak-time medication pass. METHODS: A retrospective observational study was conducted in the Veterans Health Administration, the largest employer of nurses in the U.S. The sample included all patients (n= 1,578,399 patient days) admitted to 311 non-intensive care unit inpatient acute care units in 112 hospitals in 2019 (104,588 unit days). Staffing was measured as the unit-level, nurse-to-patient ratio, and workload was measured using average time (duration) for RNs to complete the peak-time medication pass. RESULTS: We found a negative relationship between the RN-to-patient ratio and average peak time medication pass duration after adjusting for unit-level patient volume and average patient severity of illness and other unit-level factors. This relationship was non-linear: the marginal effect of staffing on workload decreased as staffing increased. DISCUSSION: As unit-level nurse staffing increased, average RN workload decreased. This result suggests that interventions to improve nurse staffing may have larger non-linear effects for units with lower staffing levels. Understanding the effect of differing staffing decisions on variations in nursing workload is critical for adopting models of care that effectively use scarce staffing resources and contribute to retaining nurses in the inpatient workforce. This work provides evidence that peak time medication pass duration is a valid process-based measure of workload and highlights the potential diminishing returns to increasing staffing.

Novel Automated Self-adjusting Subcutaneous Insulin Algorithm Improves Glycemic Control and Physician Efficiency in Hospitalized Patients.

BACKGROUND: Hyperglycemia occurs in 22% to 46% of hospitalized patients, negatively affecting patient outcomes, including mortality, inpatient complications, length of stay, and hospital costs. Achieving inpatient glycemic control is challenging due to inconsistent caloric intake, changes from home medications, a catabolic state in the setting of acute illness, consequences of acute inflammation, intercurrent infection, and limitations in labor-intensive glucose monitoring and insulin administration. METHOD: We conducted a retrospective cross-sectional analysis at the University of California San Francisco hospitals between September 3, 2020 and September 2, 2021, comparing point-of-care glucose measurements in patients on nil per os (NPO), continuous total parenteral nutrition, or continuous tube feeding assigned to our novel automated self-adjusting subcutaneous insulin algorithm (SQIA) or conventional, physician-driven insulin dosing. We also evaluated physician efficiency by tracking the number of insulin orders placed or modified. RESULTS: The proportion of glucose in range (70-180 mg/dL) was higher in the SQIA group than in the conventional group (71.0% vs 69.0%, P = .153). The SQIA led to a lower proportion of severe hyperglycemia (>250 mg/dL; 5.8% vs 7.2%, P = .017), hypoglycemia (54-69 mg/dL; 0.8% vs 1.2%, P = .029), and severe hypoglycemia (<54 mg/dL; 0.3% vs 0.5%, P = .076) events. The number of orders a physician had to place while a patient was on the SQIA was reduced by a factor of more than 12, when compared with while a patient was on conventional insulin dosing. CONCLUSIONS: The SQIA reduced severe hyperglycemia, hypoglycemia, and severe hypoglycemia compared with conventional insulin dosing. It also improved physician efficiency by reducing the number of order modifications a physician had to place.

Beyond Hospital-Level Aggregated Data: A Methodology to Adapt Clinical Data From the Electronic Health Record for Nursing Unit-Level Research.

BACKGROUND: Studies of nurse staffing frequently use data aggregated at the hospital level that do not provide the appropriate context to inform unit-level decisions, such as nurse staffing. OBJECTIVES: Describe a method to link patient data collected during the provision of routine care and recorded in the electronic health record (EHR) to the nursing units where care occurred in a national dataset. RESEARCH DESIGN: We identified all Veterans Health Administration acute care hospitalizations in the calendar year 2019 nationwide. We linked patient-level EHR and bar code medication administration data to nursing units using a crosswalk. We divided hospitalizations into segments based on the patient's time-stamped location (ward stays). We calculated the number of ward stays and medication administrations linked to a nursing unit and the unit-level and facility-level mean patient risk scores. RESULTS: We extracted data on 1117 nursing units, 3782 EHR patient locations associated with 1,137,391 ward stays, and 67,772 bar code medication administration locations associated with 147,686,996 medication administrations across 125 Veterans Health Administration facilities. We linked 89.46% of ward stays and 93.10% of medication administrations to a nursing unit. The average (standard deviation) unit-level patient severity across all facilities is 4.71 (1.52), versus 4.53 (0.88) at the facility level. CONCLUSIONS: Identification of units is indispensable for using EHR data to understand unit-level phenomena in nursing research and can provide the context-specific information needed by managers making frontline decisions about staffing.

Sampling methods in personality pathology research: Some data and recommendations.

The field of personality disorder research has grown since the publication of the Diagnostic and Statistical Manual of Mental Disorders, Third Edition, in 1980; with a notable evolution in the way that personality disorders are defined and operationalized. In evaluating this research, it is necessary to consider the range of sampling practices used. The goal of this study was to describe current sampling methods in personality disorder research and provide recommendations to guide sample design in future personality disorder research. To do this, we coded sampling practices described in recent empirical articles published in four journals that showcase research on personality disorders. We summarized aspects of sampling design including the combination of study question and sample characteristics (e.g., sample size, sample source, and use of screening), study design, and demographic representation of samples. Findings reveal a need for studies to better consider whether their samples are fit for purpose and to make explicit their target population and sampling frame, as well as the specific procedures (i.e., recruitment) used to carry out sampling. We also discuss issues that arise when attempting to capture low-base rate pathology, which is often associated with high comorbidity. We emphasize a process-oriented approach to developing a sampling strategy for personality disorders research. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Improving Artificial Intelligence-Based Diagnosis on Pediatric Skin Lesions.

Artificial intelligence algorithms to classify melanoma are dependent on their training data, which limits generalizability. The objective of this study was to compare the performance of an artificial intelligence model trained on a standard adult-predominant dermoscopic dataset before and after the addition of additional pediatric training images. The performances were compared using held-out adult and pediatric test sets of images. We trained two models: one (model A) on an adult-predominant dataset (37,662 images from the International Skin Imaging Collaboration) and the other (model A+P) on an additional 1,536 pediatric images. We compared performance between the two models on adult and pediatric held-out test images separately using the area under the receiver operating characteristic curve. We then used Gradient-weighted Class Activation Maps and background skin masking to understand the contributions of the lesion versus background skin to algorithm decision making. Adding images from a pediatric population with different epidemiological and visual patterns to current reference standard datasets improved algorithm performance on pediatric images without diminishing performance on adult images. This suggests a way that dermatologic artificial intelligence models can be made more generalizable. The presence of background skin was important to the pediatric-specific improvement seen between models. Our study highlights the importance of carefully curated and labeled data from diverse inputs to improve the generalizability of AI models for dermatology, in this case applied to dermoscopic images of adult and pediatric lesions to improve melanoma detection.

A Novel Use of Bar Code Medication Administration Data to Assess Nurse Staffing and Workload.

OBJECTIVE: The aim of the study is to introduce an innovative use of bar code medication administration (BCMA) data, medication pass analysis, that allows for the examination of nurse staffing and workload using data generated during regular nursing workflow. METHODS: Using 1 year (October 1, 2014-September 30, 2015) of BCMA data for 11 acute care units in one Veterans Affairs Medical Center, we determined the peak time for scheduled medications and included medications scheduled for and administered within 2 hours of that time in analyses. We established for each staff member their daily peak-time medication pass characteristics (number of patients, number of peak-time scheduled medications, duration, start time), generated unit-level descriptive statistics, examined staffing trends, and estimated linear mixed-effects models of duration and start time. RESULTS: As the most frequent (39.7%) scheduled medication time, 9:00 was the peak-time medication pass; 98.3% of patients (87.3% of patient-days) had a 9:00 medication. Use of nursing roles and number of patients per staff varied across units and over time. Number of patients, number of medications, and unit-level factors explained significant variability in registered nurse (RN) medication pass duration (conditional R2 = 0.237; marginal R2 = 0.199; intraclass correlation = 0.05). On average, an RN and a licensed practical nurse (LPN) with four patients, each with six medications, would be expected to take 70 and 74 minutes, respectively, to complete the medication pass. On a unit with median 10 patients per LPN, the median duration (127 minutes) represents untimely medication administration on more than half of staff days. With each additional patient assigned to a nurse, average start time was earlier by 4.2 minutes for RNs and 1.4 minutes for LPNs. CONCLUSION: Medication pass analysis of BCMA data can provide health systems a means for assessing variations in staffing, workload, and nursing practice using data generated during routine patient care activities.

Pancreatic cancer: Cutaneous metastases, clinical descriptors and outcomes.

BACKGROUND: Cutaneous metastases in pancreatic cancer (PC) are rare. Herein, we evaluate the clinical, genomic, and other descriptors of patients with PC and cutaneous metastases. METHODS: Institutional databases were queried, and clinical history, demographics, PC cutaneous metastasis details, and overall survival (OS) from cutaneous metastasis diagnosis were abstracted. OS was estimated using Kaplan-Meier methods. RESULTS: Forty patients were identified, and median age (Q1-Q3, IQR) of PC diagnosis was 66.0 (59.3-72.3, 12.9) years. Most patients had Stage IV disease at diagnosis (n = 26, 65%). The most common location of the primary tumor was the tail of the pancreas (n = 17, 43%). The most common cutaneous metastasis site was the abdomen (n = 31, 78%), with umbilical lesions occurring in 74% (n = 23) of abdominal lesions. The median OS (95% CI) was 11.4 months (7.0, 20.4). Twenty-three patients had umbilical metastases (58%), and 17 patients had non-umbilical metastases (43%). The median OS (95% CI) was 13.7 (7.0, 28.7) months in patients with umbilical metastases and 8.9 (4.1, Not reached) months in patients with non-umbilical metastases (p = 0.1). Sixteen of 40 (40%) patients underwent somatic testing, and findings were consistent with known profiles. Germline testing in 12 (30%) patients identified pathogenic variants in patients: CHEK2, BRCA1, and ATM. CONCLUSION: Cutaneous metastases from PC most frequently arise from a pancreas tail primary site and most frequently occur in the umbilicus. Cutaneous metastases may generally be categorized as umbilical or non-umbilical metastases.

In vivo tumor immune microenvironment phenotypes correlate with inflammation and vasculature to predict immunotherapy response.

Response to immunotherapies can be variable and unpredictable. Pathology-based phenotyping of tumors into 'hot' and 'cold' is static, relying solely on T-cell infiltration in single-time single-site biopsies, resulting in suboptimal treatment response prediction. Dynamic vascular events (tumor angiogenesis, leukocyte trafficking) within tumor immune microenvironment (TiME) also influence anti-tumor immunity and treatment response. Here, we report dynamic cellular-level TiME phenotyping in vivo that combines inflammation profiles with vascular features through non-invasive reflectance confocal microscopic imaging. In skin cancer patients, we demonstrate three main TiME phenotypes that correlate with gene and protein expression, and response to toll-like receptor agonist immune-therapy. Notably, phenotypes with high inflammation associate with immunostimulatory signatures and those with high vasculature with angiogenic and endothelial anergy signatures. Moreover, phenotypes with high inflammation and low vasculature demonstrate the best treatment response. This non-invasive in vivo phenotyping approach integrating dynamic vasculature with inflammation serves as a reliable predictor of response to topical immune-therapy in patients.

Inpatient Perioperative Euglycemic Diabetic Ketoacidosis Due to Sodium-Glucose Cotransporter-2 Inhibitors - Lessons From a Case Series and Strategies to Decrease Incidence.

OBJECTIVE: To identify clinical characteristics and factors associated with the development of euglycemic diabetic ketoacidosis (eDKA), and develop suitable strategies to reduce such events. METHODS: Electronic health record (EHR) data were extracted to identify all patients between December 1, 2013, and March 30, 2021, who underwent surgical procedures and had been prescribed a sodium-glucose cotransporter 2 inhibitor (SGLT2i) before these procedures. The resulting list was streamlined to a subset of patients who either had diabetic ketoacidosis (DKA) listed as a hospital diagnosis, postoperative serum bicarbonate ≤ 16 mmol/L, or postoperative serum pH ≤ 7.20. Clinical documentation and laboratory data were reviewed to determine the patients with eDKA. RESULTS: A total of 2183 procedures conducted on 1307 patients, met the inclusion criteria with the majority (1726, 79.1%) being nonemergent patients. Among 1307 patients, 625 (47.8%) were prescribed empagliflozin, 447 (34.2%) canagliflozin, 214 (16.4%) dapagliflozin, and 21 (1.6%) ertugliflozin, respectively. A total of 8 incidences pertaining to eDKA were noted for 8 unique patients; 5 had undergone emergency surgery whereas 3 had undergone nonemergent procedures. In the 3 nonemergent cases, only 1 patient had received counseling to stop the SGLT2i 3 days before the procedure. In perioperative patients who were prescribed an SGLT2i over 6 years, the incidence of eDKA was 0.17% and 1.1% for nonemergent and emergent procedures, respectively. CONCLUSION: Euglycemic DKA was rare in patients undergoing nonemergent procedures, likely because of preoperative instructions to stop their SGLT2i 3 days before the procedure. Euglycemic DKA was more likely to occur in patients undergoing emergency surgery when the SGLT2i could not be prophylactically stopped.

Inflammation and dry eye disease-where are we?

The presence of inflammation in dry eye disease (DED) results in increased patient symptomatology, ocular surface damage and worsening tear dysfunction. It also affects the health of meibomian glands and their secretions which further aggravates ocular surface disease. This article reviews current knowledge regarding ocular surface inflammation in DED and explores the relationships between the vicious cycles of DED, inflammation and meibomian gland dysfunction (MGD). The clinical evaluation of eyes with such changes, markers that identify the presence of inflammation on the ocular surface and current treatment options are discussed.

Immune checkpoint inhibitors in patients with pre-existing psoriasis: safety and efficacy.

BACKGROUND: Immune checkpoint inhibitors (ICIs) are approved to treat multiple cancers. Retrospective analyses demonstrate acceptable safety of ICIs in most patients with autoimmune disease, although disease exacerbation may occur. Psoriasis vulgaris is a common, immune-mediated disease, and outcomes of ICI treatment in patients with psoriasis are not well described. Thus we sought to define the safety profile and effectiveness of ICIs in patients with pre-existing psoriasis. METHODS: In this retrospective cohort study, patients from eight academic centers with pre-existing psoriasis who received ICI treatment for cancer were evaluated. Main safety outcomes were psoriasis exacerbation and immune-related adverse events (irAEs). We also assessed progression-free survival (PFS) and overall survival. RESULTS: Of 76 patients studied (50 (66%) male; median age 67 years; 62 (82%) with melanoma, 5 (7%) with lung cancer, 2 (3%) with head and neck cancer, and 7 (9%) with other cancers; median follow-up 25.1 months (range=0.2-99 months)), 51 (67%) received anti-PD-1 antibodies, 8 (11%) anti-CTLA-4, and 17 (22%) combination of anti-PD-1/CTLA-4. All patients had pre-existing psoriasis, most frequently plaque psoriasis (46 patients (61%)) and 15 (20%) with psoriatic arthritis. Forty-one patients (54%) had received any prior therapy for psoriasis although only two (3%) were on systemic immunosuppression at ICI initiation. With ICI treatment, 43 patients (57%) experienced a psoriasis flare of cutaneous and/or extracutaneous disease after a median of 44 days of receiving ICI. Of those who experienced a flare, 23 patients (53%) were managed with topical therapy only; 16 (21%) needed systemic therapy. Only five patients (7%) required immunotherapy discontinuation for psoriasis flare. Forty-five patients (59%) experienced other irAEs, 17 (22%) of which were grade 3/4. PFS with landmark analysis was significantly longer in patients with a psoriasis flare versus those without (39 vs 8.7 months, p=0.049). CONCLUSIONS: In this multicenter study, ICI therapy was associated with frequent psoriasis exacerbation, although flares were manageable with standard psoriasis treatments and few required ICI discontinuation. Patients who experienced disease exacerbation performed at least as well as those who did not. Thus, pre-existing psoriasis should not prevent patients from receiving ICIs for treatment of malignancy.

Characteristics and outcomes of 627 044 COVID-19 patients living with and without obesity in the United States, Spain, and the United Kingdom.

BACKGROUND: A detailed characterization of patients with COVID-19 living with obesity has not yet been undertaken. We aimed to describe and compare the demographics, medical conditions, and outcomes of COVID-19 patients living with obesity (PLWO) to those of patients living without obesity. METHODS: We conducted a cohort study based on outpatient/inpatient care and claims data from January to June 2020 from Spain, the UK, and the US. We used six databases standardized to the OMOP common data model. We defined two non-mutually exclusive cohorts of patients diagnosed and/or hospitalized with COVID-19; patients were followed from index date to 30 days or death. We report the frequency of demographics, prior medical conditions, and 30-days outcomes (hospitalization, events, and death) by obesity status. RESULTS: We included 627 044 (Spain: 122 058, UK: 2336, and US: 502 650) diagnosed and 160 013 (Spain: 18 197, US: 141 816) hospitalized patients with COVID-19. The prevalence of obesity was higher among patients hospitalized (39.9%, 95%CI: 39.8-40.0) than among those diagnosed with COVID-19 (33.1%; 95%CI: 33.0-33.2). In both cohorts, PLWO were more often female. Hospitalized PLWO were younger than patients without obesity. Overall, COVID-19 PLWO were more likely to have prior medical conditions, present with cardiovascular and respiratory events during hospitalization, or require intensive services compared to COVID-19 patients without obesity. CONCLUSION: We show that PLWO differ from patients without obesity in a wide range of medical conditions and present with more severe forms of COVID-19, with higher hospitalization rates and intensive services requirements. These findings can help guiding preventive strategies of COVID-19 infection and complications and generating hypotheses for causal inference studies.

Reproducibility of vaginal immobilization balloons in situ overnight for cervical cancer brachytherapy.

PURPOSE: The use of vaginal immobilization balloons placed into the vagina for immobilization of tandem and ovoid (T+O) applicator during high-dose-rate (HDR) brachytherapy delivery has been used at our institution, and seems to have improved our patient comfort, decreased procedure time, and minimized applicator misplacement. We aimed to show that these balloons, while originally marketed for single-day use, are safe and maintain applicator positioning/dosimetry when left in situ overnight for treatment delivery on sequential days. MATERIAL AND METHODS: Forty-two paired computed tomography (CT) scans from thirteen patients who underwent T+O HDR treatments on sequential days with vaginal immobilization balloons in situ overnight were retrospectively compared to calculate mean change of balloon volumes and balloon/T+O distance to bony landmarks. Dosimetric planning was retroactively performed on day 2 using CT scan of each pair, and the change in estimated radiation delivery to the bladder and rectum was compared. RESULTS: No statistically significant overnight changes were found in balloon volumes or anterior balloon positioning. The posterior balloon shifted -0.29 ±0.46 cm (p = 0.03) to the anterior public symphysis and 0.32 ±0.50 cm (p = 0.01) to the right femoral head. The tandem shifted 0.37 ±0.39 cm (p = 0.002) to the pubic symphysis. There was no significant difference found in radiation delivered to the bladder or rectum between the paired scans. CONCLUSIONS: This study showed minimal change in balloon volumes, balloons/T+O positioning, or in radiation dose to bladder and rectum when the applicator remained overnight. These findings support that inflatable vaginal immobilization balloons remaining in situ overnight for additional HDR T+O treatments on sequential days, is safe and provides stable dosimetry.

Lack of association between either outpatient or inpatient glycemic control and COVID-19 illness severity or mortality in patients with diabetes.

INTRODUCTION: To evaluate whether outpatient insulin treatment, hemoglobin A1c (HbA1c), glucose on admission, or glycemic control during hospitalization is associated with SARS-CoV-2 (COVID-19) illness severity or mortality in hospitalized patients with diabetes mellitus (DM) in a geographical region with low COVID-19 prevalence. RESEARCH DESIGN AND METHODS: A single-center retrospective study of patients hospitalized with COVID-19 from January 1 through August 31, 2020 to evaluate whether outpatient insulin use, HbA1c, glucose on admission, or average glucose during admission was associated with intensive care unit (ICU) admission, mechanical ventilation (ventilator) requirement, or mortality. RESULTS: Among 111 patients with DM, 48 (43.2%) were on outpatient insulin and the average HbA1c was 8.1% (65 mmol/mol). The average glucose on admission was 187.0±102.94 mg/dL and the average glucose during hospitalization was 173.4±39.8 mg/dL. Use of outpatient insulin, level of HbA1c, glucose on admission, or average glucose during hospitalization was not associated with ICU admission, ventilator requirement, or mortality among patients with COVID-19 and DM. CONCLUSIONS: Our findings in a region with relatively low COVID-19 prevalence suggest that neither outpatient glycemic control, glucose on admission, or inpatient glycemic control is predictive of illness severity or mortality in patients with DM hospitalized with COVID-19.

An Alternative Method of Public Reporting of Comparative Hospital Quality and Performance Data for Transparency Initiatives.

BACKGROUND: Hospital performance comparisons for transparency initiatives may be inadequate if peer comparison groups are poorly defined. OBJECTIVE: The objective of this study was to evaluate a new approach identifying hospital peers for comparison. DESIGN/SETTING: We used Mahalanobis distance as a new method of developing peer-specific groupings for hospitals to incorporate both external and internal complexity. We compared the overlap in groups with an existing method used by the Veterans' Health Administration's Office for Productivity, Efficiency, and Staffing (OPES). PARTICIPANTS: One hundred twenty-two acute-care Veterans' Health Administration's Medical Facilities as defined in the OPES fiscal year 2014 report. MEASURES: Using 15 variables in 9 categories developed from expert input, including both hospital internal measures and community-based external measures, we used principal components analysis and calculated Mahalanobis distance between each hospital pair. This method accounts for correlation between variables and allows for variables having different variances. We identified the 50 closest hospitals, then eliminated any potential peer whose score on the first component was >1 SD from the reference hospital. We compared overlap with OPES measures. RESULTS: Of 15 variables, 12 have SDs exceeding 25% of their means. The first 2 components of our analysis explain 24.8% and 18.5% of variation among hospitals. Eight of 9 variables scaling positively on the first component measure internal complexity, aligning with OPES groups. Four of 5 variables scaling positively on the second component but not the first are factors from the policy environment; this component reflects a dimension not considered in OPES groups. CONCLUSION: Individualized peers that incorporate external complexity generate more nuanced comparators to evaluate quality.