Deriving a Model for Predicting Hospital Falls

Background: In the United States 700,000 to 1,000,000 people fall in the hospital annually, 1/3 result in injury. One single fall averages $14,000, resulting in an increase in hospital length of stay and burden on hospital budget. In St. Joseph Hospital of Orange, from calendar year 2019 to 2020, there was an increase in falls from 178 to 185 falls, despite the use of a telesitter. At time of data collection, 12 telesitter cameras were initiated after a fall. An investigation was deemed necessary to determine the cause of the increase and the factors related to patient falls. Purpose: The purpose is to derive and validate predictors of falls by identifying criteria responsible for falls in a population of in-patients in an acute care setting. Compare research findings responsible for falls with current fall scales. Lastly, increase awareness with bedside nurses of patients most at risk for falls. Methods: The study utilized a retrospective cross-sectional design with a review of the electronic health records from calendar years of 2018 and 2019. Patients included are over the age of 18 and who were admitted to inpatient units in the hospital. A comprehensive literature review and comparison of current fall scales provided for identification of similarities, differences, and gaps among fall scales and identified common fall factors. Findings from the literature review were used to select variables for this study. The statistical methods and modeling used were descriptive statistics, continuous variables, categorical variables and bivariate analysis. Results: A total of 1,247 patient records, 929 records were randomized, while the other 318 records represented patients who fell during the hospital stay. Patient demographics shown to be statistically significant were age, gender, length of stay, and diagnosis. Identified patient behavior at most risk for falls are withdrawn, restless, anxious, and agitated. Lastly, if patient takes sedatives, anti-convulsants, anti-psychotics, and anticoagulants put a patient at risk for falls. Statistical analysis identified the factors posing the greatest risk. The strongest individual predictor was dizziness and vertigo; individuals were 7.2 times more likely to fall than those without dizziness/vertigo. Results also demonstrated a two-level “high” Morse Fall Risk with those with a 65 or greater score having double the risk of falling than those scoring 45-64. The fall predictor model derived from this study predicted 82% of the falls. This was especially significant when compared to the Morse Fall Scale which only predicted 62% of the falls. Conclusions: Results of the study will contribute to changes in policy and procedure on fall interventions for low, moderate, and high fall risk patients. Learning which variables are most likely to be present in a patient who could fall, can increase a bedside nurse awareness, and improve patient safety. Implications for practice: For future research, we would like to utilize the data and create a new model for predicting patient falls. Partner with other ministries to replicate study to see if results are similar. Incorporate the developed model to classify patient\u27s at risk for falls or early visual camera implementation

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

From culture to chromosomes: A mother-child dyadic study of acculturation, telomere lengths and body fat.

Studies suggest that telomere lengths, a biomarker of aging, could also capture the physiological weathering attributable to poor health behaviors and adverse experiences, particularly those experienced in early life. For these reasons, we propose that telomere lengths may be a pivotal biomarker for measuring the heightened susceptibility to illness resulting from the cumulative exposure to acculturation to the US culture. This binational study used an Actor-Partner Interdependence Model to test if maternal acculturation to the US moderates the cross-sectional associations of telomere lengths with percentage of body fat (PBF) among Mexican women, among their children, and the intergenerational associations of mother and children telomere lengths with each others PBF. Low income Mexican child-mother dyads (n ​= ​108 dyads) were recruited to participate in this cross-sectional study in Mexico and the US. The pooled dataset included measurements of maternal acculturation to the US, mother and childrens salivary telomere lengths, PBF measured through bioelectrical impedance, and demographic characteristics. Results showed that the influences of maternal acculturation in the associations of telomere lengths with PBF were different for mothers and their children: Among mothers with higher maternal acculturation to the US, longer salivary telomere lengths were associated with lower PBF. In contrast, among mothers with lower maternal acculturation to the US, salivary telomere lengths were not associated with PBF. There were no significant associations between childrens salivary telomere lengths and PBF, and the null associations did not vary across different levels of maternal acculturation to the US. Future longitudinal studies are needed to determine whether acculturation to the US (experienced through immigration or remotely) influences the association of telomere length attrition with obesity risks among immigrant and non-immigrant Mexican children and adults