This sub-study of the African Prospective Study on the Early Detection and Identification of Cardiovascular Disease and Hypertension (African-PREDICT) explored possible early psychological predictors of change in blood pressure. In a sample of normotensive at baseline black and white South Africans ( n = 105; mean age at baseline 24.93), this study investigated the relationship between personality traits, coping strategies, and 24-hour ambulatory blood pressure measured at baseline and 5-year follow-up. Another aim was to investigate a possible mediating effect of coping strategies on the relationship between personality traits and change in blood pressure. Extraversion, agreeableness, openness, and problem-solving skills were identified as possible protective factors against cardiovascular risk, confirming previous research in this regard. However, the effect of these was different for gender and ethnic subgroups. Preconditions for a possible mediation role for coping in the relationship between personality and change in blood pressure were not met. Future research should further explore gender and ethnic differences in the relationship between personality, coping, and cardiovascular health.
Objective Despite growing numbers of initiatives designed to address increasing diabetes prevalence in the U.S., the need remains for effective programs. Because family history is a diabetes risk factor, family focused programs may be a potential strategy to improve the health of the entire family. We present the development process and pretest results of a lifestyle change program for rural-dwelling mothers at risk for diabetes and their children. Methods We completed semistructured interviews with mothers ( N = 17) focusing on program content and activities. Findings informed program development by identifying specific barriers motivators and potential leverage points such as focusing on the intrinsic incentives of health activities. The resulting program was pretested with rural-dwelling mothers ( N = 5) who completed program activities with their families and provided feedback via semistructured interviews. All interviews were audio-recorded, transcribed, and analyzed using thematic analysis. Results While pretest results showed that the program was generally acceptable and feasible, feedback was used to further refine the program. The revised program consists of 8 group sessions with family focused content around physical activity, healthy eating, and making connections while engaging in health activities. Between sessions, mothers tracked the family goals, activity levels, and mood, and documented barriers to discuss during the sessions. Conclusions Our development process engaged intended program users to codesign a program that focuses on wellness and intrinsic incentives of engaging in health-enhancing activities as a family. By providing strategies to change behaviors as a family, this program aims to improve the mother's health while developing healthy habits in their children.
Introduction This study aims to examine (1) the impact of the pandemic phases on overall and preventable hospitalizations and emergency department (ED) visits, and (2) the effect of the pandemic on these outcomes within subgroup populations including gender, race, patients' residence in health professional shortage areas (HPSA), and residence in a federal poverty level.Study Design We used electronic medical record (EMR) data for the year 2019 and 2020 from a large health system predominantly serving medically underserved patients in the South. We used a difference-in-differences approach to examine changes in weekly rates of overall and preventable hospitalizations and ED visits in the pandemic phase 1 (Mid-March to June of 2020) and phase 2 (July-September of 2020) compared to the same period in 2019 after adjusting for weekly outcome rates in the baseline period (January to Mid-March of 2020) compared to the same period in 2019.Results The study sample included 1.4 million hospitalizations and ED encounters. In phase 1 of the pandemic, there were significant reductions in overall (-108) and preventable (-75.3) hospitalizations, and overall (-408) and preventable (-306) ED visits when compared to the same period in 2019. In phase 2 of the pandemic, there were significant reductions in overall (-60) and preventable (-43) hospitalizations and in overall (-360) and preventable (-258) ED visits as compared to 2019. We found greater reductions in ED visits, both overall and preventable, during the early pandemic phases among Black patients than among White patients. Similar patterns in the reduction of ED visits were found in Black versus White patients within subgroups of women, men, and those residing in a HPSA and low-income areas.Discussion Substantial reductions in utilization were observed in Black patients in comparison to white patients and these differences persisted among men, women, and those living in underserved and low-income areas.
Objective Diabetes mellitus is an important chronic disease that is prevalent around the world. Different countries and diverse cultures use varying approaches to dealing with this chronic condition. Also, with the advancement of computation and automated decision-making, many tools and technologies are now available to patients suffering from this disease. In this work, the investigators attempt to analyze approaches taken towards managing this illness in India and the United States. Methods In this work, the investigators have used available literature and data to compare the use of artificial intelligence in diabetes management. Findings The article provides key insights to comparison of diabetes management in terms of the nature of the healthcare system, availability, electronic health records, cultural factors, data privacy, affordability, and other important variables. Interestingly, variables such as quality of electronic health records, and cultural factors are key impediments in implementing an efficiency-driven management system for dealing with this chronic disease. Conclusion The article adds to the body of knowledge associated with the management of this disease, establishing a critical need for using artificial intelligence in diabetes care management.
Introduction Patient self-scheduling of medical appointments is becoming more common in many medical institutions. However, the complexity of scheduling multiple specialties, following scheduling guidelines, and managing appointment access requires a variety of processes for a diverse inventory of self-schedulable appointment types. Methods From 7 unique patient self-scheduling methods, we captured counts of successfully self-scheduled and completed appointments. A process map was created to show the paths of 5 different primary self-scheduling processes (new appointment self-scheduling) and 2 secondary self-scheduling processes (existing appointment self-rescheduling). Results There were 7 unique processes that led to 733,651 successfully self-scheduled completed visits from January 1 to December 31, 2023 at a multisite, multispecialty clinic. The self-scheduling processes consisted of the following: (1) Ticket offer (appointment “ticket” offers for specific visits generated by a provider order or system rules), the software “ticket” sent to the patient permits “admission” to self-schedule calendar templates (341,591 uses, 46.6%); (2) direct self-scheduled visit for prequalified visit types (203,593 uses, 27.6%); (3) self-reschedule option (patient option to reschedule existing appointment, 79,706 uses, 10.9%); (4) new patient self-scheduled visit via clinic website (does not require portal access, 54,367 uses, 7.4%). (5) automated waitlist self-rescheduled visit (38,649 uses, 5.3%); (6) automated waitlist self-scheduled visit of previously unscheduled visit (10,939 uses, 1.5%); and (7) self-triage self-scheduled visit (4806 uses, 0.7%). Conclusion The processes for self-scheduling are expanding. Our multispecialty clinic has implemented 7 different processes to help patients successfully self-schedule medical appointments. Some of the processes occur before initial scheduling (such as self-triage), and some are implemented after successful scheduling has already occurred (self-rescheduling option and self-rescheduling aided by an automated waitlist). Continued research is needed to look for measures of success beyond the ability to complete a self-scheduled visit, including the accuracy of the booking (right provider, location, and length of visit).
Background Childhood stunting has a long-term impact on cognitive development and overall well-being. Understanding varying stunting profiles is crucial for targeted interventions and effective policy-making. Therefore, our study aimed to identify the determinants and stunting risk profiles among 2-year-old children in Ethiopia.Methods and materials A cross-sectional study was conducted on 395 mother-child pairs attending selected public health centers for growth monitoring and promotion under 5 outpatient departments and immunization services. The data were collected by face-to-face interviews, with the anthropometric data collected using the procedure stipulated by the World Health Organization. The data were entered using Epi Data version 4.6 and exported to STATA 16 and Jamovi version 2.3.28 for analysis. Bayesian logistic regression analysis was conducted to identify potential factors of stunting. Likewise, lifecycle assessment analysis (LCA) was used to examine the heterogeneity of the magnitude of stunting.Results The overall prevalence of stunting in children under 24 months was 47.34% (95% confidence interval (CI): 42.44-52.29%). The LCA identified 3 distinct risk profiles. The first profile is Class 1, which is labeled as low-risk, comprised 23.8% of the children, and had the lowest prevalence of stunting (23.4%). This group characterized as having a lower risk to stunting. The second profile is Class 2, which is identified as high-risk, comprised 47.1%, and had a high prevalence of stunting (66.7%), indicating a higher susceptibility to stunting compared to Class 1. The third profile is Class 3, which is categorized as mixed-risk and had a moderate stunting prevalence of 35.7%, indicating a complex interplay of factors contributing to stunting.Conclusion Our study identified 3 distinct risk profiles for stunting in young children. A substantial amount (almost half) is in the high-risk category, where stunting is far more common. The identification of stunting profiles necessitates considering heterogeneity in risk factors in interventions. Healthcare practitioners should screen, provide nutrition counseling, and promote breastfeeding. Policymakers should strengthen social safety nets and support primary education.
Background It is difficult to reach migrant or refugee agricultural workers about pesticide exposure prevention. Here, we describe a community health worker (CHW)-led pesticide exposure prevention workshop and the impact of this program among migrant and refugee workers in Washington state. Methods A focus group of migrants and refugees participated in the development of a CHW-led Spanish language pesticide exposure prevention mobile phone app and workshop. Pre- and post-workshop surveys assessed pesticide training, knowledge, and characteristics. Results Community health workers facilitated 28 workshops attended by 263 participants from 49 agricultural communities. Approximately 79% of participants reported no prior pesticide training. Significant improvements were observed in the proportion familiar with illnesses associated with pesticides, knowledge about pesticide definition, ability to correctly identify the content of pesticide labels, and the correct method to wash fruits and vegetables. Conclusions Community health workers are effective in addressing the gaps in pesticide safety education and awareness among migrant and refugee communities. Further work is needed to assess how to better integrate a mobile phone app into this training and subsequent use of the knowledge.
Introduction Chemotherapy daycare units (CDU) routinely face difficulties, given the waiting time and work pressure. The study objectives include determining the feasibility of a multidisciplinary intervention in facilitating the growth in CDU bed utilization by ∼20%. Methods The quasi-experimental study was conducted during the period 1st May 2021 to 28th February 2022. The strategies of the healthcare improvement project are structured as per the Plan-Do-Study-Act (PDSA) cycle. ‘Lean thinking’ approach using the A3 sheet tool was applied, as its focus is on organization of processes. Benchmarking technique was used to attain more insight into the optimal performance levels. Results Plan phase: The tracks of CDU process were mapped using the ‘process flow diagram’ technique. The reasons for the perceived bed shortage and high work pressure were revealed by the Root cause analysis, which includes the 21 prioritized problem areas. Do phase: Various interventions were implemented in the domains of communication systems, developing standard operating protocols and human resource management. Study phase: 9 of the total 21 problem areas were cumulatively responsible for ∼80% of underutilization of CDU beds. Act phase: The planned intervention resulted in an increase in the proportion of CDU bed utilization from 60% (18-20 patients/day) to 75% (23-25 patients/day). Conclusion The PDSA cycle offered optimal structure to this efficiency improvement initiative. The project outcomes were enhanced by the combination of approaches such as lean thinking and benchmarking.
Background Food protein-induced enterocolitis syndrome (FPIES) is a non-IgE-mediated food allergy, characterized by delayed onset of repetitive vomiting occurring 1 to 4 h following ingestion of a food allergen. Managing FPIES requires strict avoidance of the food trigger. The concern with FPIES is determining the risk of another FPIES food trigger reaction due to potential coassociations with other foods or food groups. An effective statistical approach for analyzing FPIES-related data is essential to identify common coallergens and their associations. Methods This study employed Market Basket Analysis, a data-mining technique, to examine correlations and patterns among allergens in FPIES patients at a Houston, Texas, pediatric tertiary center. A retrospective analysis of electronic medical records from January 2018 to March 2022 for allergist diagnosed FPIES patients was conducted. The analysis utilized R software, specifically the “arules” and “arulesViz” packages, implementing the Apriori algorithm with set minimum support and confidence thresholds. Results The study included 210 FPIES cases over 4 years, with 112 patients reacting to one food trigger and 98 to more than one trigger. In the latter group, the 5 predominant triggers were cow's milk (45.9%), rice (31.6%), oats (30.6%), soy (22.4%), and avocado (19.4%). Market Basket Analysis identified significant associations between food categories, particularly between soy and dairy, egg and dairy, oat and dairy, rice and dairy, and avocado and dairy. Conclusion Market Basket Analysis proved effective in identifying patterns and associations in FPIES data. These insights are crucial for healthcare providers in formulating dietary recommendations for FPIES patients. This approach potentially enhances guidance on food introductions and avoidances, thereby improving management and the quality of life for those affected by FPIES.
Ramadan is the Islamic holy month when Muslims around the world fast from dawn to sunset. This 30-day pattern of intermittent diurnal fasting can have a significant physiologic impact on the body. Importantly, oral intake is forbidden during this time, and many patients do not wish to take medications. From a clinical perspective, this potentially impacts healthcare delivery and chronic disease states. Despite these important changes, awareness of individual patient practices remains limited among healthcare providers in North America, which may worsen health disparities in Muslim patients. A fundamental understanding of the cultural and physiological implications of fasting during Ramadan can improve cultural competence and patient outcomes. In this paper, we review the physiologic changes during fasting, medical exemptions to fasting, and special considerations for the care of Muslim patients with chronic conditions who may fast during Ramadan.
The increasing recognition of adverse childhood experiences as a significant factor in adult health outcomes underscores the need for trauma-informed care (TIC) in healthcare settings. The purpose of this study was to assess the psychometric properties of the TIC Provider Assessment Tool (TIC-PAT) designed for primary care providers. The TIC-PAT aligns with the TIC Pyramid framework and assesses both universal trauma precautions and trauma-specific care. A total of 176 primary care providers in the United States completed the TIC-PAT through an anonymous online survey. Findings through exploratory and confirmatory factor analyses revealed a unidimensional (one-factor) model, consolidating questions into a concise 10-item measure. This study contributes an efficient assessment tool for the provision of TIC by primary care providers in healthcare settings, promoting better patient–provider interactions and enhancing provider awareness of trauma's impact on health.
Background Self-scheduling of medical visits is becoming more common but the complexity of applying multiple requirements for self-scheduling has hampered implementation. Mayo Clinic implemented self-scheduling in 2019 and has been increasing its portfolio of self-schedulable visits since then. Our aim was to show measures quantifying the complexity associated with medical visit scheduling and to describe how opportunities and challenges of scheduling complexity apply in self-scheduling. Methods We examined scheduled visits from January 1, 2022, through August 24, 2023. For seven visit categories, we counted all unique visit types that were scheduled, for both staff-scheduled and self-scheduled. We examined counts of self-scheduled visit types to identify those with highest uptake during the study period. Results There were 9555 unique visit types associated with 20.8 M (million) completed visits. Self-scheduled visit types accounted for 4.0% (838,592/20,769,699) of the completed total visits. Of seven visit categories, self-scheduled established patient visits, testing visits, and procedure visits accounted for 93.5% (784,375/838,592) of all self-scheduled visits. Established patient visits in primary care (10 visit types) accounted for 273,007 (32.6%) of all self-scheduled visits. Testing visits (blood and urine testing, 2 visit types) accounted for 183,870 (21.9%) of all self-scheduled visits. Procedure visits for screening mammograms, bone mineral density, and immunizations (8 visit types) accounted for 147,358 (17.6%) of all self-scheduled visits. Conclusion Large numbers of unique visit types comprise a major challenge for self-scheduling. Some visit types are more suitable for self-scheduling. Guideline-based procedure visits such as screening mammograms, bone mineral density exams, and immunizations are examples of visits that have high volumes and can be standardized for self-scheduling. Established patient visits and laboratory testing visits also can be standardized for self-scheduling. Despite the successes, there remain thousands of specific visit types that may need some staff-scheduler intervention to properly schedule.
Background Around half of the world's population is infected with Helicobacter pylori ( H. pylori), according to data from a recent systematic review. H. pylori infection is extremely common around the world. It is the most prevalent disease in Ethiopia and contributes to both morbidity and mortality. Patients with gastritis, peptic ulcers, and stomach cancer have been reported to harbor H. pylori. Objective The aim of this study was to determine the trends of Helicobacter Pylori infection among patients attending the Bule Hora University Teaching Hospital from 2018–2022, Bule Hora, Ethiopia. Method A hospital-based retrospective study design was conducted to recruit 314 sampled data from the logbook, which were five-year data (2018-2022) from the Bule Hora University Teaching Hospitals. Data were extracted using structured checklists. The sample size was calculated using the single-population proportion formula. Study participants were selected using a systematic random sampling technique. Data were entered in EpiData 4.6 and exported to SPSS Version 26 for analysis. Results Approximately 314 complete data from selected participants were collected and evaluated for the present study. The mean age was 29.01 (SD ± 4.93). Most of the respondents (39.2%) were in the age group of 21 to 30 years. The general prevalence of H. pylori observed in this study is 28% (95% confidence interval [CI], 23-32.9). The prevalence was higher in women (71.6%) than in men (28.4%). In terms of age category, those over 60 years of age were observed with the highest positiveness for H. pylori with 38.1% and the trend of H. pylori prevalence fluctuated from 2018 to 2022. Conclusion In total, 28% of the study participants had H. pylori, but there was variation in the prevalence of H. pylori infection between 2018 and 2022. Compared to other age groups, the 60-year-old age group had a higher prevalence of H. pylori and this prevalence continued to increase annually. The concerned parties must be interested in raising awareness and establishing criteria for the eradication of these bacteria.
Objectives Home blood pressure monitoring (HBPM) is crucial for managing hypertension, but there is a potential trade-off between measurement accuracy and health/economic outcomes due to asymmetric costs associated with misclassifying an individual as having hypertension or not. We assessed whether adjustments to device readings that increased overall accuracy produced net health and economic benefits. Methods We analyzed data from N = 89 Alaska Native individuals who used 2 HBPM devices and a standard aneroid sphygmomanometer. We modeled changes in expected costs associated with individuals being misclassified as hypertensive or not under 3 different models of adjusting HBPM device readings. Results The gains in accuracy produced by adjusting HBPM readings decreased the overall rate of hypertension misclassification but increased the rate of false-negative readings. Adjusting readings led to a net increase in expected health and economic costs. Discussion Ignoring asymmetric costs of misclassification can escalate overall costs and worsen uncontrolled hypertension. Home blood pressure monitoring algorithms must be cautiously designed, considering both false negatives and positives. Greater transparency in HBPM algorithms is needed for effective coordination among manufacturers, clinicians, and patients.
The study aimed at applying Multivariate Generalized Linear Mixed Models to examine factors associated with correlation outcomes, in particular, anthropometric measurements among under-five children in Tanzania. Three anthropometric measurements: weight-for–age (WAZ), height-for–age (HAZ), and weight-for–height (WHZ) among under-five children in Tanzania were jointly modeled to identify common factors associated with childhood malnutrition. A total of 9052 children with valid measures of height and weight were processed and analyzed. The results indicate that WAZ was correlated with HAZ ( P -value < 2e-16) and WHZ ( P -value < 2e-16). The Multivariate Ordered Logit Model has lower AIC = 53213.92 and BIC = 52727.95, indicating better model fit than the Multivariate Ordered Probit Model. In Tanzania, the age of the child, birth order, mother education level, child gender, mother working status, wealth index, marital status, and mother body mass index are important determinants of malnutrition among children under the age of five. Moreover, the common factors were child's age, Birth order, Mother's education attainment, child's sex, Mother working status, wealth index, Marital status, and Mother's Body Mass Index. As a result, emphasis should be placed on analyzing correlated health outcomes in order to draw conclusions about the factors that may have a mutual effect on anthropometric measurements.
Background Self-scheduling of medical visits is becoming available at many medical institutions. We aimed to examine the self-scheduled visit counts and rate of growth of self-scheduled visits in a multispecialty practice. Methods For 85 weeks extending from January 1, 2022 through August 24, 2023, we examined self-scheduled visit counts for over 1500 self-scheduled visit types. We compared completed self-scheduled visit counts to all scheduled completed visit counts for the same visit types. We collected counts of the most frequently self-scheduled visit types for each week and examined the change over time. We also determined the proportion that each visit type was self-scheduled. Results There were 20,769 699 completed visits during the course of the study that met the criteria for inclusion. Self-scheduled visits accounted for 4.0% of all completed visits (838 592/20,769 699). Over the 85-week span, self-scheduled visits rose from 3.0% to 5.3% of the total. There were 1887 unique visit types that were associated with completed visits. There were just 6 appointment visit types of the total 1887 self-scheduled visit types that accounted for 50.7% of the total 838 592 self-scheduled visits. Those 6 visit types were a lab blood test visit (19.5%, 163 K visits), two Family Medicine office visit types (13.0%, 109 K visits), a screening mammogram visit type (6.6%, 55 K visits), a scheduled express care visit type (6%, 50 K visits) and a COVID immunization visit type (5.7%, 48 K visits). Twenty-one visit types that were self-scheduled accounted for 75% of the total self-scheduled visits. Four seasonal visits, accounting for 10.6% of the total self-scheduled visits, were responsible for almost all the non-linear change in self-scheduling. Conclusion Self-scheduling accounted for a small but growing percent of all outpatient scheduled visits in a multispecialty, multisite practice. A wide range of visit types can be successfully self-scheduled.
Background Prolonged hospital stay could lead to increased hospital-acquired infections, and unnecessary utilization of hospital beds, medications, and other resources. However, there is limited evidence regarding the length of hospital stay (LOS) and predictors of prolonged hospital stay in pediatric patients with severe pneumonia. Therefore, this study was conducted to fill the information gap on length of stay and predictors of prolonged hospital stay among pediatric patients with severe pneumonia, in southwest Ethiopia. Objective This study aimed to determine the LOS and predictors of prolonged hospital stay among pediatric patients with severe pneumonia, Southwest Ethiopia/2022. Methods and Materials A Prospective follow-up study was conducted on pediatric patients with severe pneumonia. Data were entered into Epi-data manager Version 4.4.2.1, for coding, editing, and cleaning, then exported to Stata Version 16 for analysis. Bivariate logistic regression analysis at a significance level of 0.25 and multivariate logistic regression analyses with a significance level of 0.05 were conducted to determine the factors associated with prolonged hospital stay among pediatric patients. Results In this study, the median LOS was 5 days and, approximately 38.22% (95% CI [33.66-43.01]) of patients with severe pneumonia had prolonged hospital stays. The presence of underlying comorbidity (adjusted odds ratio [AOR]: 2.64, 95% CI [1.65-4.26]), health insurance status (AOR: 2.22, 95% CI [1.4-3.55]), and incomplete vaccination status (AOR: 4.20, 95% CI [1.04-16.61]) were independent predictors of prolonged hospital stay among pediatric patients with severe pneumonia. Conclusion In this study, more than one-third of pediatric patients with severe pneumonia had a length of stay of more than 5 days, and incomplete vaccination status, insurance status, and underlying comorbidities were independent predictors of prolonged hospital stay. Therefore, healthcare providers, parents, and other stakeholders should work to improve the pneumococcal vaccination rate, timely initiation of advanced diagnosis, and patient management of comorbid diseases to reduce hospital stays for pediatric patients with severe pneumonia.
Background Over the past few years, a growing number of studies have explored massage robots. However, to date, a dedicated systematic review focused solely on robot-assisted massage has not been conducted. Objective To systematically identify and summarize evidence from studies concerning robot-assisted massage in healthcare settings. Methods An extensive literature search, involving electronic databases Ovid and Scopus, was conducted from the inception of the databases up to March 2023. This systematic review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement, and relevant papers were chosen based on the predefined inclusion criteria. Given the substantial methodological diversity among the included studies, a qualitative analysis was conducted. Results Seventeen studies met the inclusion criteria, comprising 15 preliminary trials, one quasi-experimental study, and one randomized controlled trial. Approximately 29% of the studies focused on the application of robotic massage for patients, 24% targeted both healthy volunteers and patients, and the remaining 47% were preclinical trials assessing the effectiveness of robotic massage solely on healthy volunteers. Primary interventions included robotic massage for oral rehabilitation, scalp massage, low back massage, shoulder massage, and full-body massage. All studies provided evidence that robotic massage interventions can enhance health and well-being, indicating a promising future for the integration of robotics in the field of massage therapy. Conclusions In general, robotic massage interventions offer physical and mental health benefits. Robot-assisted massage may be integrated into care provision as an adjunct to enhance human well-being. Nonetheless, further research is needed to confirm these findings.
Background Despite the introduction of the Centers for Disease Control and Prevention's opioid prescribing guidelines, studies indicate that a significant proportion of opioids prescribed at hospital discharge remains unused. Little is known if improved provider awareness of guidelines and metrics would facilitate rightsizing opioid prescriptions at hospital discharge. Our institution created opioid prescribing guidelines and a key metrics dashboard and subsequently disseminated these tools to our institution's leadership and prescribers. We aim to evaluate the effectiveness of these efforts in reducing hospital discharge opioid prescriptions, especially those for acute pain exceeding 100 morphine milligram equivalents (MME). Methods Following the development of practice-specific opioid prescribing guidelines in 2017, a key metrics dashboard was created in 2021 to display the percentage of hospital discharges with opioids prescribed and the percentage of discharges with opioids prescribed for acute pain exceeding 100 MME. These metrics were broken down into calendar years between 2018 and 2022, and by the 7 major practice regions across our institution spanning 5 U.S. States. Results From 2018 to 2022, all regions showed a decline in the percentage of hospital discharges with opioids prescribed (range 2.7%-9.4%). In the same period, 5 of 7 regions showed a decline in discharge opioid prescriptions exceeding 100 MME for acute pain (range 8.8%-23.2%). Two sites showed an increase of 2.4% and 2.7%. Conclusion Downward trends in hospital discharge opioid prescriptions were observed for most practice regions following the introduction of our institution's opioid prescribing guidelines and key metrics dashboard.
