A multimodal intervention to decrease inappropriate outpatient antibiotic prescribing for upper respiratory tract infections in a large integrated healthcare system.

OBJECTIVE: To evaluate the effectiveness of Carolinas Healthcare Outpatient Antimicrobial Stewardship Empowerment Network (CHOSEN), a multicomponent outpatient stewardship program to reduce inappropriate antibiotic prescribing for upper respiratory infections by 20% over 2 years. DESIGN: Before-and-after interrupted time series of antibiotics prescribed between 2 periods: April 2016-October 2017 and May 2018-March 2020. SETTING: The study included 162 primary-care practices within a large healthcare system in the greater Charlotte, North Carolina region. PARTICIPANTS: Adult and pediatric patients with encounters for upper respiratory infections for which an antibiotic is inappropriate. METHODS: Patient and provider educational materials, along with a web-based provider prescribing dashboard aimed at reducing inappropriate antibiotic prescribing were developed and distributed. Monthly antibiotic prescribing rates were calculated as the number of eligible encounters with an antibiotic prescribed divided by the total number of eligible encounters. A segmented regression analysis compared monthly antibiotic prescribing rates before versus after CHOSEN implementation, while also accounting for practice type and seasonal trends in prescribing. RESULTS: Overall, 286,580 antibiotics were prescribed during 704,248 preintervention encounters and 277,177 during 832,200 intervention encounters. Significant reductions in inappropriate prescribing rates were observed in all outpatient specialties: family medicine (relative difference before and after the intervention, -20.4%), internal medicine (-19.5%), pediatric medicine (-17.2%), and urgent care (-16.6%). CONCLUSIONS: A robust multimodal intervention that combined a provider prescribing dashboard with a targeted education campaign demonstrated significant decreases in inappropriate outpatient antibiotic prescribing for upper respiratory tract infections in a large integrated ambulatory network.

Realizing a learning health system through process, rigor and culture change.

While many healthcare organizations strive to achieve the patient care benefits of being a learning health system (LHS), myriad challenges stand in the way of successful implementation. The reality of creating a true LHS requires top-to-bottom commitment to culture change with the necessary vision, leadership, and investment. The Center for Outcomes Research and Evaluation (CORE) is a multidisciplinary research unit embedded within a large, vertically integrated healthcare system in the southeastern United States. We used a two-pronged approach to: a) methodically recruit a team of experts, while generating early wins that demonstrated real success; and b) build relationships and buy-in across organizational leadership. Building out a team with diverse expertise created the ability to deploy pragmatic, data-driven research designs that fit seamlessly into real-world care delivery, resulting in agile study execution that aligns with health system timelines. Case study examples from hospital readmissions and antibiotic stewardship illustrate how our LHS operationalizes practice-informed research and research-informed practice. Lessons from this experience can serve as a blueprint for other healthcare systems or networks seeking to expand the promise of the LHS framework to improve health for patients and communities.

Modeling COVID-19 Latent Prevalence to Assess a Public Health Intervention at a State and Regional Scale: Retrospective Cohort Study.

BACKGROUND: Emergence of the coronavirus disease (COVID-19) caught the world off guard and unprepared, initiating a global pandemic. In the absence of evidence, individual communities had to take timely action to reduce the rate of disease spread and avoid overburdening their health care systems. Although a few predictive models have been published to guide these decisions, most have not taken into account spatial differences and have included assumptions that do not match the local realities. Access to reliable information that is adapted to local context is critical for policy makers to make informed decisions during a rapidly evolving pandemic. OBJECTIVE: The goal of this study was to develop an adapted susceptible-infected-removed (SIR) model to predict the trajectory of the COVID-19 pandemic in North Carolina and the Charlotte Metropolitan Region, and to incorporate the effect of a public health intervention to reduce disease spread while accounting for unique regional features and imperfect detection. METHODS: Three SIR models were fit to infection prevalence data from North Carolina and the greater Charlotte Region and then rigorously compared. One of these models (SIR-int) accounted for a stay-at-home intervention and imperfect detection of COVID-19 cases. We computed longitudinal total estimates of the susceptible, infected, and removed compartments of both populations, along with other pandemic characteristics such as the basic reproduction number. RESULTS: Prior to March 26, disease spread was rapid at the pandemic onset with the Charlotte Region doubling time of 2.56 days (95% CI 2.11-3.25) and in North Carolina 2.94 days (95% CI 2.33-4.00). Subsequently, disease spread significantly slowed with doubling times increased in the Charlotte Region to 4.70 days (95% CI 3.77-6.22) and in North Carolina to 4.01 days (95% CI 3.43-4.83). Reflecting spatial differences, this deceleration favored the greater Charlotte Region compared to North Carolina as a whole. A comparison of the efficacy of intervention, defined as 1 - the hazard ratio of infection, gave 0.25 for North Carolina and 0.43 for the Charlotte Region. In addition, early in the pandemic, the initial basic SIR model had good fit to the data; however, as the pandemic and local conditions evolved, the SIR-int model emerged as the model with better fit. CONCLUSIONS: Using local data and continuous attention to model adaptation, our findings have enabled policy makers, public health officials, and health systems to proactively plan capacity and evaluate the impact of a public health intervention. Our SIR-int model for estimated latent prevalence was reasonably flexible, highly accurate, and demonstrated efficacy of a stay-at-home order at both the state and regional level. Our results highlight the importance of incorporating local context into pandemic forecast modeling, as well as the need to remain vigilant and informed by the data as we enter into a critical period of the outbreak.

A patient and family reporting system for perceived ambulatory note mistakes: experience at 3 U.S. healthcare centers.

OBJECTIVE: The study sought to test a patient and family online reporting system for perceived ambulatory visit note inaccuracies. MATERIALS AND METHODS: We implemented a patient and family electronic reporting system at 3 U.S. healthcare centers: a northeast urban academic adult medical center (AD), a northeast urban academic pediatric medical center (PED), and a southeast nonprofit hospital network (NET). Patients and families reported potential documentation inaccuracies after reading primary care and subspecialty visit notes. Results were characterized using descriptive statistics and coded for clinical relevance. RESULTS: We received 1440 patient and family reports (780 AD, 402 PED, and 258 NET), and 27% of the reports identified a potential inaccuracy (25% AD, 35% PED, 28% NET). Among these, patients and families indicated that the potential inaccuracy was important or very important in 58% of reports (55% AD, 55% PED, 71% NET). The most common types of potential inaccuracies included description of symptoms (21%), past medical problems (21%), medications (18%), and important information that was missing (15%). Most patient- and family-reported inaccuracies resulted in a change to care or to the medical record (55% AD, 67% PED, data not available at NET). DISCUSSION: About one-quarter of patients and families using an online reporting system identified potential documentation inaccuracies in visit notes and more than half were considered important by patients and clinicians, underscoring the potential role of patients and families as ambulatory safety partners. CONCLUSIONS: Partnering with patients and families to obtain reports on inaccuracies in visit notes may contribute to safer care. Mechanisms to encourage greater use of patient and family reporting systems are needed.

Racial/ethnic differences in healthcare use among patients with uncontrolled and controlled diabetes.

OBJECTIVES: To examine racial/ethnic differences in healthcare use among patients classified as having controlled and uncontrolled diabetes. DESIGN: Data from the Carolinas HealthCare System electronic data warehouse were used. Glycemic control was defined as glycosylated hemoglobin (HbA1c) < 8% (64 mmol/mol) in 2012 (n = 9996). Patients with HbA1c ≥ 8% (64 mmol/mol) in 2012 were classified as uncontrolled (n = 2576). Race and ethnicity were jointly classified as non-Hispanic Black, non-Hispanic White or Other. Separate mixed effects negative binomial models estimated the independent effect of race/ethnicity on the number of emergency department (ED) visits, hospitalizations and physician office visits in 2013, in each patient group, adjusting for significant confounding variables. RESULTS: Rates of diabetes-related ED visits were two to three times higher for non-Hispanic Blacks compared to non-Hispanic Whites (uncontrolled rate ratio [RR]: 3.41 95% CI: 1.41-8.22; controlled RR: 2.95; 95% CI: 1.78-4.91). Similar differences were observed for all-cause ED visits (uncontrolled RR: 1.83, 95% CI: 1.50-2.24; controlled RR: 2.45, 95% CI: 2.17-2.77). Non-Hispanic Blacks with controlled and uncontrolled diabetes also had lower rates of all-cause physician office visits when compared to non-Hispanic Whites (uncontrolled RR: 0.84, 95% CI: 0.77-0.91; controlled RR: 0.81, 95% CI: 0.78-0.84). CONCLUSION: Notable racial/ethnic disparities exist in the use of emergency services and physician offices for diabetes care. Strategies such as patient education and care delivery changes that address healthcare access issues in racial/ethnic minorities should be considered to offer better diabetes management and address diabetes disparities.

Whole Genome Sequencing detects Inter-Facility Transmission of Carbapenem-resistant Klebsiella pneumoniae.

OBJECTIVES: To identify transmission patterns of Carbapenem-resistant Klebsiella pneumoniae infection during an outbreak at a large, tertiary care hospital and to detect whether the outbreak organisms spread to other facilities in the integrated healthcare network. METHODS: We analyzed 71 K. pneumoniae whole genome sequences collected from clinical specimens before, during and after the outbreak and reviewed corresponding patient medical records. Sequence and patient data were used to model probable transmissions and assess factors associated with the outbreak. RESULTS: We identified close genetic relationships among carbapenem-resistant K. pneumoniae isolates sampled during the study period. Transmission tree analysis combined with patient records uncovered extended periods of silent colonization in many study patients and transmission routes that were likely the result of asymptomatic patients transitioning between facilities. CONCLUSIONS: Detecting how and where Carbapenem-resistant K. pneumoniae infections spread is challenging in an environment of rising prevalence, asymptomatic carriage and mobility of patients. Whole genome sequencing improved the precision of investigating inter-facility transmissions. Our results emphasize that containment of Carbapenem-resistant K. pneumoniae infections requires coordinated efforts between healthcare networks and settings of care that acknowledge and mitigate transmission risk conferred by undetected carriage and by patient transfers between facilities.

Not a magic pill: a qualitative exploration of provider perspectives on antibiotic prescribing in the outpatient setting.

BACKGROUND: Inappropriate prescribing of antibiotics poses an urgent public health threat. Limited research has examined factors associated with antibiotic prescribing practices in outpatient settings. The goals of this study were to explore elements influencing provider decisions to prescribe antibiotics, identify provider recommendations for interventions to reduce inappropriate antibiotic use, and inform the clinical management of patients in the outpatient environment for infections that do not require antibiotics. METHODS: This was a qualitative study using semi-structured interviews with key informants. Seventeen outpatient providers (10 medical doctors and 7 advanced care practitioners) within a large healthcare system in Charlotte, North Carolina, participated. Interviews were audio recorded, transcribed, and analyzed for themes. RESULTS: Primary barriers to reducing inappropriate antibiotic prescribing included patient education and expectations, system-level factors, and time constraints. Providers indicated they would be interested in having system-wide, evidence-based guidelines to inform their prescribing decisions and that they would also be receptive to efforts to improve their awareness of their own prescribing practices. Results further suggested that providers experience a high demand for antibiotic prescriptions; consequently, patient education around appropriate use would be beneficial. CONCLUSIONS: Findings suggest that antibiotic prescribing in the outpatient setting is influenced by many pressures, including patient demand and patient satisfaction. Training on appropriate antibiotic prescribing, guideline-based decision support, feedback on prescribing practices, and patient education are recommended interventions to improve levels of appropriate prescribing.

Patient, Provider, and Practice Characteristics Associated with Inappropriate Antimicrobial Prescribing in Ambulatory Practices.

OBJECTIVE To reduce inappropriate antimicrobial prescribing across ambulatory care, understanding the patient-, provider-, and practice-level characteristics associated with antibiotic prescribing is essential. In this study, we aimed to elucidate factors associated with inappropriate antimicrobial prescribing across urgent care, family medicine, and pediatric and internal medicine ambulatory practices. DESIGN, SETTING, AND PARTICIPANTS Data for this retrospective cohort study were collected from outpatient visits for common upper respiratory conditions that should not require antibiotics. The cohort included 448,990 visits between January 2014 and May 2016. Carolinas HealthCare System urgent care, family medicine, internal medicine and pediatric practices were included across 898 providers and 246 practices. METHODS Prescribing rates were reported per 1,000 visits. Indications were defined using the International Classification of Disease, Ninth and Tenth Revisions, Clinical Modification (ICD-9/10-CM) criteria. In multivariable models, the risk of receiving an antibiotic prescription was reported with adjustment for practice, provider, and patient characteristics. RESULTS The overall prescribing rate in the study cohort was 407 per 1,000 visits (95% confidence interval [CI], 405-408). After adjustment, adult patients seen by an advanced practice practitioner were 15% more likely to receive an antimicrobial than those seen by a physician provider (incident risk ratio [IRR], 1.15; 95% CI, 1.03-1.29). In the pediatric sample, older providers were 4 times more likely to prescribe an antimicrobial than providers aged ≤30 years (IRR, 4.21; 95% CI, 2.96-5.97). CONCLUSIONS Our results suggest that patient, practice, and provider characteristics are associated with inappropriate antimicrobial prescribing. Future research should target antibiotic stewardship programs to specific patient and provider populations to reduce inappropriate prescribing compared to a "one size fits all" approach. Infect Control Hosp Epidemiol 2018;39:307-315.

Exploring Patient Awareness and Perceptions of the Appropriate Use of Antibiotics: A Mixed-Methods Study.

In the outpatient setting, estimates suggest that 30% of the antibiotics prescribed are unnecessary. This study explores patient knowledge and awareness of appropriate use of antibiotics and expectations regarding how antibiotics are used for their treatment in outpatient settings. A survey was administered to a convenience sample of patients, parents, and caregivers (n = 190) at seven primary care clinics and two urgent care locations. Fisher's exact tests compared results by patient characteristics. Although 89% of patients correctly believed that antibiotics work well for treating infections from bacteria, 53% incorrectly believed that antibiotics work well for treating viral infections. Patients who incorrectly believed that antibiotics work well for treating viral infections were more than twice as likely to expect a provider to give them an antibiotic when they have a cough or common cold. Patients who completed the survey also participated in semi-structured interviews (n = 4), which were analyzed using thematic analysis. Patients reported experiencing confusion about which illnesses may be treated by antibiotics and unclear communication from clinicians about the appropriate use of antibiotics. Development of easy to understand patient educational materials can help address patients' incorrect perceptions of appropriate antibiotic use and facilitate patient-provider communication.

Retrospective Analysis of Catheter-Acquired Urinary Tract Infection: Relationship to Stroke Diagnosis.

AIMS: The objective of this study was to determine if a diagnosis of stroke was associated with a higher incidence of catheter-associated urinary tract infections (CAUTIs). Secondary aims included examining the effect of healthcare-related variables including antibiotic and steroid use, length of stay before catheter insertion, and duration of catheter use on the incidence of CAUTI in stroke patients. DESIGN: This was a retrospective chart review analysis set in a large teaching hospital in the Southeastern United States. METHODS: A total of 300 patients with indwelling urinary catheter use who also had a stroke diagnosis were randomly selected and matched (on age, gender, race, and admission date) to 300 randomly selected patients with indwelling urinary catheter use and without stroke. Bivariate statistical tests included Wilcoxon signed-rank test and McNemar's test, whereas the multivariate test consisted of generalized estimating equations. RESULTS: The incidence of CAUTIs in stroke patients was significantly higher than that in nonstroke patients (6.0% vs 1.7%, P = .005). In the multivariable generalized estimating equations analysis, stroke patients were found to be approximately 3.5 times more likely to experience CAUTI compared with nonstroke patients (odds ratio = 3.53; 95% confidence interval, 1.24-10.03; P = .018). The proportion of patients who used steroids was greater among stroke patients who experienced CAUTI compared with those who did not experience CAUTI (55.6% vs 24.5%, P = .004). CONCLUSION: Stroke patients were more likely to develop CAUTI compared with nonstroke patients. These patients should be considered as key targets when implementing interventions aimed at reducing CAUTIs. Use of steroids may be associated with a higher likelihood of CAUTI in stroke patients. IMPLICATIONS: Clinical nurse specialists are directly influential in preventing CAUTIs. This study provides evidence regarding the association between stroke and CAUTI to clinical nurse specialists to help them plan CAUTI prevention initiatives.

Predictors of Unplanned Hospitalization in Patients Receiving Outpatient Parenteral Antimicrobial Therapy Across a Large Integrated Healthcare Network.

BACKGROUND: Outpatient parenteral antimicrobial therapy (OPAT) prescribing has increased along with the trend toward early discharge of hospitalized patients who have infections. There is limited literature that assesses unplanned hospitalizations during OPAT. This study aims to elucidate the predictors of unplanned hospitalization in OPAT patients after discharge from acute-care facilities within Carolinas HealthCare System (CHS). Understanding these predictors may inform future interventions to improve treatment efficacy and patient outcomes. METHODS: The study cohort included hospitalized patients aged >19 years who initiated OPAT in an acute-care facility within CHS in 2014-2015. Patients who had OPAT prescribed at an ambulatory-care facility were excluded. The primary outcome was unplanned hospitalization anytime during the at-risk time from discharge through 90 days. RESULTS: The unplanned hospitalization rate for the cohort was 18.5%. In adjusted analysis, having OPAT delivered at a skilled nursing facility was associated with a 46% (incident risk ratio = 1.46; 95% confidence interval = 1.04-2.06) increased risk of an unplanned hospitalization compared with patients receiving OPAT at home after adjustment for demographics, comorbidities, indication, treatment duration, and antimicrobial prescribed. Infusion, dialysis, and rehabilitation centers had the lowest rates of unplanned hospitalizations. CONCLUSIONS: These results suggest that the location of OPAT delivery is associated with unplanned hospitalizations and that older patients need additional support during OPAT.

Prevalence of Metabolic Syndrome in a Large Integrated Health Care System in North Carolina.

BACKGROUND: Metabolic syndrome (MetS) is a cluster of conditions--including abdominal obesity, dyslipidemia, hypertension, and hyperglycemia--that are associated with a significantly increased risk of developing diabetes and cardiovascular diseases. No information currently exists regarding the prevalence of MetS in North Carolina. This study determined the prevalence of MetS among adults receiving care in a large integrated health care system in North Carolina. METHODS: This study used data from the Carolinas HealthCare System's electronic medical record system and included adults receiving care during 2014. The association between patient demographic characteristics and MetS was determined using multivariable logistic regression. RESULTS: The prevalence of MetS was approximately 22.5%. Individuals aged 18-29 years were less likely to have MetS compared with those aged 80 years and older (odds ratio [OR], 0.61; 95% confidence interval [CI], 0.56-0.67). Groups that were more likely to have MetS included women (OR, 1.07; 95% CI, 1.05-1.10), Hispanics (OR, 1.14; 95% CI, 1.05-1.23), individuals with Medicare (OR, 1.38; 95% CI, 1.33-1.42), and those with Medicaid (OR, 1.68; 95% CI, 1.58-1.78) compared with men, whites, and those with commercial insurance, respectively. LIMITATIONS: We excluded individuals with missing data for any of the conditions that define MetS, which may underestimate the actual prevalence of this condition. CONCLUSIONS: The considerable prevalence of MetS in our North Carolina sample suggests that interventions are needed to achieve the state's population health goals.

A targeted metabolomic protocol for short-chain fatty acids and branched-chain amino acids.

Research in obesity and metabolic disorders that involve intestinal microbiota demands reliable methods for the precise measurement of the short-chain fatty acids (SCFAs) and branched-chain amino acids (BCAAs) concentration. Here, we report a rapid method of simultaneously determining SCFAs and BCAAs in biological samples using propyl chloroformate (PCF) derivatization followed by gas chromatography mass spectrometry (GC-MS) analysis. A one-step derivatization using 100 µL of PCF in a reaction system of water, propanol, and pyridine (v/v/v = 8:3:2) at pH 8 provided the optimal derivatization efficiency. The best extraction efficiency of the derivatized products was achieved by a two-step extraction with hexane. The method exhibited good derivatization efficiency and recovery for a wide range of concentrations with a low limit of detection for each compound. The relative standard deviations (RSDs) of all targeted compounds showed good intra- and inter-day (within 7 days) precision (< 10%), and good stability (< 20%) within 4 days at room temperature (23-25 °C), or 7 days when stored at -20 °C. We applied our method to measure SCFA and BCAA levels in fecal samples from rats administrated with different diet. Both univariate and multivariate statistics analysis of the concentrations of these target metabolites could differentiate three groups with ethanol intervention and different oils in diet. This method was also successfully employed to determine SCFA and BCAA in the feces, plasma and urine from normal humans, providing important baseline information of the concentrations of these metabolites. This novel metabolic profile study has great potential for translational research.

Genetic signatures in choline and 1-carbon metabolism are associated with the severity of hepatic steatosis.

Choline metabolism is important for very low-density lipoprotein secretion, making this nutritional pathway an important contributor to hepatic lipid balance. The purpose of this study was to assess whether the cumulative effects of multiple single nucleotide polymorphisms (SNPs) across genes of choline/1-carbon metabolism and functionally related pathways increase susceptibility to developing hepatic steatosis. In biopsy-characterized cases of nonalcoholic fatty liver disease and controls, we assessed 260 SNPs across 21 genes in choline/1-carbon metabolism. When SNPs were examined individually, using logistic regression, we only identified a single SNP (PNPLA3 rs738409) that was significantly associated with severity of hepatic steatosis after adjusting for confounders and multiple comparisons (P=0.02). However, when groupings of SNPs in similar metabolic pathways were defined using unsupervised hierarchical clustering, we identified groups of subjects with shared SNP signatures that were significantly correlated with steatosis burden (P=0.0002). The lowest and highest steatosis clusters could also be differentiated by ethnicity. However, unique SNP patterns defined steatosis burden irrespective of ethnicity. Our results suggest that analysis of SNP patterns in genes of choline/1-carbon metabolism may be useful for prediction of severity of steatosis in specific subsets of people, and the metabolic inefficiencies caused by these SNPs should be examined further.

Association between composition of the human gastrointestinal microbiome and development of fatty liver with choline deficiency.

BACKGROUND & AIMS: Nonalcoholic fatty liver disease affects up to 30% of the US population, but the mechanisms underlying this condition are incompletely understood. We investigated how diet standardization and choline deficiency influence the composition of the microbial community in the human gastrointestinal tract and the development of fatty liver under conditions of choline deficiency. METHODS: We performed a 2-month inpatient study of 15 female subjects who were placed on well-controlled diets in which choline levels were manipulated. We used 454-FLX pyrosequencing of 16S ribosomal RNA bacterial genes to characterize microbiota in stool samples collected over the course of the study. RESULTS: The compositions of the gastrointestinal microbial communities changed with choline levels of diets; each individual's microbiome remained distinct for the duration of the experiment, even though all subjects were fed identical diets. Variations between subjects in levels of Gammaproteobacteria and Erysipelotrichi were directly associated with changes in liver fat in each subject during choline depletion. Levels of these bacteria, change in amount of liver fat, and a single nucleotide polymorphism that affects choline were combined into a model that accurately predicted the degree to which subjects developed fatty liver on a choline-deficient diet. CONCLUSIONS: Host factors and gastrointestinal bacteria each respond to dietary choline deficiency, although the gut microbiota remains distinct in each individual. We identified bacterial biomarkers of fatty liver that result from choline deficiency, adding to the accumulating evidence that gastrointestinal microbes have a role in metabolic disorders.

Correlation analysis of HOX, ErbB and IGFBP family gene expression in ovarian cancer.

Utilizing microarray gene expression data in cancer research possesses the ability to identify deregulated cellular pathways involved in malignant development. This study investigated the relationships of three gene families, HOX, ErbB and IGFBP, with regard to the development of ovarian cancer. These families were of interest because of similar chromosomal locations and their deregulated expression in ovarian cancer. Higher level statistics were used to differentially analyze microarray data in 65 ovarian samples to assess correlation and relationships among the gene families of interest. Fifteen genes in the three families were found to be significantly deregulated. Thirty-eight significant correlations were found within and between the genes of interest. Our data indicates that the significantly modeled relationships between HOX, ErbB and IGFBP gene pairs could provide insight into the underlying biological mechanisms in ovarian cancer.