Effect of Delirium on Interhospital Transfer Outcomes.

OBJECTIVES: Interhospital transfer (IHT) and in-hospital delirium are both independently associated with increased length of stay (LOS), mortality, and discharge to facility. Our objective was to investigate the joint effects between IHT and the presence of in-hospital delirium on the outcomes of LOS, discharge to a facility, and in-hospital mortality. METHODS: This was a single-center retrospective cohort study of 25,886 adult hospital admissions at a tertiary-care academic medical center. Staged multivariable logistic and linear regression models were used to evaluate the association between IHT status and the outcomes of discharge to a facility, LOS, and mortality while considering the joint impact of delirium. The joint effects of IHT status and delirium were evaluated by categorizing patients into one of four categories: emergency department (ED) admissions without delirium, ED admissions with delirium, IHT admissions without delirium, and IHT admissions with delirium. The primary outcomes were LOS, in-hospital mortality, and discharge disposition. RESULTS: The odds of discharge to a facility were 4.48 times higher in admissions through IHT with delirium when compared with ED admissions without delirium. IHT admissions with delirium had a 1.97-fold (95% confidence interval 1.88-2.06) longer LOS when compared with admission through the ED without delirium. Finally, admissions through IHT with delirium had 3.60 (95% confidence interval 2.36-5.49) times the odds of mortality when compared with admissions through the ED without delirium. CONCLUSIONS: The relationship between IHT and delirium is complex, and patients with IHT combined with in-hospital delirium are at high risk of longer LOS, discharge to a facility, and mortality.

Real-World Primary Care Data Comparing ALT and FIB-4 in Predicting Future Severe Liver Disease Outcomes.

BACKGROUND: Alanine aminotransferase (ALT) has long provided a cue for chronic liver disease (CLD) diagnostic evaluation, but the Fibrosis-4 Index (FIB-4), a serologic score used for predicting advanced fibrosis risk in CLD, may provide an alternative signal. OBJECTIVE: Compare the predictive performance of FIB-4 with ALT for severe liver disease (SLD) events while adjusting for potential confounders. DESIGN: Retrospective cohort study of primary care electronic health record data from 2012 to 2021. PATIENTS: Adult primary care patients with at least two sets of ALT and other lab values necessary for calculating two unique FIB-4 scores, excluding those patients with an SLD prior to their index FIB-4 value. MAIN MEASURES: The occurrence of an SLD event, a composite of cirrhosis, hepatocellular carcinoma, and liver transplantation, was the outcome of interest. Categories of ALT elevation and FIB-4 advanced fibrosis risk were the primary predictor variables. Multivariable logistic regression models were developed to evaluate the association of FIB-4 and ALT with SLD, and the areas under the curve (AUC) for each model were compared. KEY RESULTS: The cohort of 20,828 patients included 14% with an abnormal index ALT (≥40 IU/L) and 8% with a high-risk index FIB-4 (≥2.67). During the study period, 667 (3%) patients suffered an SLD event. Adjusted multivariable logistic regression models demonstrated an association between high-risk FIB-4 (OR 19.34; 95%CI 15.50-24.13), persistently high-risk FIB-4 (OR 23.85; 95%CI 18.24-31.17), abnormal ALT (OR 7.07; 95%CI 5.81-8.59), and persistently abnormal ALT (OR 7.58; 95%CI 5.97-9.62) with SLD outcomes. The AUC of the index FIB-4 (0.847, p < 0.001) and combined FIB-4 (0.849, p < 0.001) adjusted models exceeded the index ALT adjusted model (0.815). CONCLUSIONS: High-risk FIB-4 scores demonstrated superior performance compared to abnormal ALT in predicting future SLD outcomes.

FIB-4 and incident severe liver outcomes in patients with undiagnosed chronic liver disease: A Fine-Gray competing risk analysis.

BACKGROUND AND AIMS: The Fibrosis-4 index (FIB-4) can reliably assess fibrosis risk in patients with chronic liver disease, and advanced fibrosis is associated with severe liver disease (SLD) outcomes. However, CLD is underdiagnosed in primary care. We examined the association between FIB-4 risk strata and the incidence of SLD preceding a CLD diagnosis while considering incident CLD diagnoses as competing risks. METHODS: Using primary care clinic data between 2007 and 2018, we identified patients with two FIB-4 scores and no liver disease diagnoses preceding the index FIB-4. Patients were followed from index FIB-4 until an incident SLD (a composite of cirrhosis, hepatocellular carcinoma or liver transplantation), CLD or were censored. Hazard ratios were computed using a Fine-Gray competing risk model. RESULTS: Of 20 556 patients, there were 54.8% in the low, 34.8% in the indeterminate, 6.6% in the high and 3.8% in the persistently high-risk FIB-4 strata. During a mean 8.2 years of follow-up, 837 (4.1%) patients experienced an SLD outcome and 11.5% of the sample received a CLD diagnosis. Of patients with an SLD event, 49% received no preceding CLD diagnosis. In the adjusted Fine-Gray model, the indeterminate (HR 1.41, 95% CI 1.17-1.71), high (HR 4.65, 95% CI 3.76-5.76) and persistently high-risk (HR 7.60, 95% CI 6.04-9.57) FIB-4 risk strata were associated with a higher incidence of SLD compared to the low-risk stratum. CONCLUSIONS: FIB-4 scores with indeterminate- and high-risk values are associated with an increased incidence of SLD in primary care patients without known CLD.

FIB-4 as a Time-varying Covariate and Its Association With Severe Liver Disease in Primary Care: A Time-dependent Cox Regression Analysis.

BACKGROUND AND GOALS: The Fibrosis-4 Index (FIB-4) has demonstrated a strong association with severe liver disease (SLD) outcomes in primary care, but previous studies have only evaluated this relationship using 1 or 2 FIB-4 scores. In this study, we determined the association of FIB-4 as a time-varying covariate with SLD risk using time-dependent Cox regression models. STUDY: This retrospective cohort study included primary care patients with at least 2 FIB-4 scores between 2012 and 2021. The outcome was the occurrence of an SLD event, a composite of cirrhosis, complications of cirrhosis, hepatocellular carcinoma, and liver transplantation. The primary predictor was FIB-4 advanced fibrosis risk, categorized as low-(<1.3), indeterminate-(1.3≤FIB to 4<2.67), and high-risk (≥2.67). FIB-4 scores were calculated and the index, last, and maximum FIB-4s were identified. Time-dependent Cox regression models were used to estimate hazard ratios (HR) and their corresponding 95% CI with adjustment for potentially confounding covariates. RESULTS: In the cohort, 20,828 patients had a median of 5 (IQR: 3 to 11) FIB-4 scores each and 3% (n=667) suffered an SLD outcome during follow-up. Maximum FIB-4 scores were indeterminate-risk for 34% (7149) and high-risk for 24% (4971) of the sample, and 32% (6692) of patients had an increase in fibrosis risk category compared with their index value. The adjusted Cox regression model demonstrated an association between indeterminate- (hazard ratio 3.21; 95% CI 2.33-4.42) and high-risk (hazard ratio 20.36; 95% CI 15.03-27.57) FIB-4 scores with SLD outcomes. CONCLUSIONS: Multiple FIB-4 values per patient are accessible in primary care, FIB-4 fibrosis risk assessments change over time, and high-risk FIB-4 scores (≥2.67) are strongly associated with severe liver disease outcomes when accounting for FIB-4 as a time-varying variable.

Identifying Patients at Risk for Fibrosis in a Primary Care NAFLD Cohort.

GOALS AND BACKGROUND: Using natural language processing to create a nonalcoholic fatty liver disease (NAFLD) cohort in primary care, we assessed advanced fibrosis risk with the Fibrosis-4 Index (FIB-4) and NAFLD Fibrosis Score (NFS) and evaluated risk score agreement. MATERIALS AND METHODS: In this retrospective study of adults with radiographic evidence of hepatic steatosis, we calculated patient-level FIB-4 and NFS scores and categorized them by fibrosis risk. Risk category and risk score agreement was analyzed using weighted κ, Pearson correlation, and Bland-Altman analysis. A multinomial logistic regression model evaluated associations between clinical variables and discrepant FIB-4 and NFS results. RESULTS: Of the 767 patient cohorts, 71% had a FIB-4 or NFS score in the indeterminate-risk or high-risk category for fibrosis. Risk categories disagreed in 43%, and scores would have resulted in different clinical decisions in 30% of the sample. The weighted κ statistic for risk category agreement was 0.41 [95% confidence interval (CI): 0.36-0.46] and the Pearson correlation coefficient for log FIB-4 and NFS was 0.66 (95% CI: 0.62-0.70). The multinomial logistic regression analysis identified black race (odds ratio=2.64, 95% CI: 1.84-3.78) and hemoglobin A1c (odds ratio=1.37, 95% CI: 1.23-1.52) with higher odds of having an NFS risk category exceeding FIB-4. CONCLUSIONS: In a primary care NAFLD cohort, many patients had elevated FIB-4 and NFS risk scores and these risk categories were often in disagreement. The choice between FIB-4 and NFS for fibrosis risk assessment can impact clinical decision-making and may contribute to disparities of care.

Gaps in Confirmatory Fibrosis Risk Assessment in Primary Care Patients with Nonalcoholic Fatty Liver Disease.

BACKGROUND: As recommendations for non-invasive fibrosis risk assessment in nonalcoholic fatty liver disease (NAFLD) emerge, it is not known how often they are performed in primary care. AIMS: We investigated the completion of confirmatory fibrosis risk assessment in primary care patients with NAFLD and indeterminate-risk or greater Fibrosis-4 Index (FIB-4) and NAFLD Fibrosis Scores (NFS). METHODS: This retrospective cohort study of electronic health record data from a primary care clinic identified patients with diagnoses of NAFLD from 2012 through 2021. Patients with a diagnosis of a severe liver disease outcome during the study period were excluded. The most recent FIB-4 and NFS scores were calculated and categorized by advanced fibrosis risk. Charts were reviewed to identify the outcome of a confirmatory fibrosis risk assessment by liver elastography or liver biopsy for all patients with indeterminate-risk or higher FIB-4 (≥ 1.3) and NFS (≥ - 1.455) scores. RESULTS: The cohort included 604 patients diagnosed with NAFLD. Two-thirds of included patients (399) had a FIB-4 or NFS score greater than low-risk, 19% (113) had a high-risk FIB-4 (≥ 2.67) or NFS (≥ 0.676) score, and 7% (44) had high-risk FIB-4 and NFS values. Of these 399 patients with an indication for a confirmatory fibrosis test, 10% (41) underwent liver elastography (24) or liver biopsy (18) or both (1). CONCLUSIONS: Advanced fibrosis is a key indicator of future poor health outcomes in patients with NAFLD and a critical signal for referral to hepatology. Significant opportunities exist to improve confirmatory fibrosis risk assessment in patients with NAFLD.

Alignment of an interprofessional student learning experience with a hospital quality improvement initiative.

Assessment of interprofessional education (IPE) frequently focuses on students' learning outcomes including changes in knowledge, skills, and/or attitudes. While a foundational education in the values and information of their chosen profession is critical, interprofessional learning follows a continuum from formal education to practice. The continuum increases in significance and complexity as learning becomes more relationship based and dependent upon the ability to navigate complex interactions with patients, families, communities, co-workers, and others. Integrating IPE into collaborative practice is critical to enhancing students' experiential learning, developing teamwork competencies, and understanding the complexity of teams. This article describes a project that linked students with a hospital-based quality-improvement effort to focus on the acquisition and practice of teamwork skills and to determine the impact of teamwork on patient and quality outcome measures. A hospital unit was identified with an opportunity for improvement related to quality care, patient satisfaction, employee engagement, and team behaviours. One hundred and thirty-seven students from six health profession colleges at the Medical University of South Carolina underwent TeamSTEPPS® training and demonstrated proficiency of their teamwork-rating skills with the TeamSTEPPS® Team Performance Observation Tool (T-TPO). Students observed real-time team behaviours of unit staff before and after staff attended formal TeamSTEPPS® training. The students collected a total of 778 observations using the T-TPO. Teamwork performance on the unit improved significantly across all T-TPO domains (team structure, communication, leadership, situation monitoring, and mutual support). Significant improvement in each domain continued post-intervention and at 15-month follow-up, improvement remained significant compared to baseline. Student engagement in TeamSTEPPS® training and demonstration of their reliability as teamwork-observers was a valuable learning experience and also yielded an opportunity to gather unique, and otherwise difficult to attain, data from a hospital unit for use by quality managers and administrators.

The Association of Fibrosis-4 Index Scores with Severe Liver Outcomes in Primary Care.

BACKGROUND: The Fibrosis-4 Index (FIB-4)non-invasively assesses fibrosis risk in chronic liver disease (CLD), but underdiagnosis limits FIB-4's application in primary care. OBJECTIVE: To evaluate the association of FIB-4 risk with hazard of severe liver outcomes in primary care patients with and without diagnosed CLD. DESIGN: Retrospective cohort study of primary care data from 2007 to 2018. PARTICIPANTS: Adult patients with qualifying aminotransferase and platelet count results were included and a single FIB-4 score was calculated for each patient using the first of these values. Patients with a CLD diagnosis or outcome prior to their FIB-4 score were excluded. MEASURES: FIB-4 advanced fibrosis risk categorization (low, indeterminate, and high) was the primary predictor variable. Patients were followed from FIB-4 score to a severe liver outcome, a composite of cirrhosis, liver transplantation, and hepatocellular carcinoma. We analyzed the association of FIB-4 risk categories with hazard risk of a severe liver outcome using stratified Cox regression models, stratifying patients by known CLD. KEY RESULTS: A total of 20,556 patients were followed for a mean 2,978 days (SD 1,201 days), and 4% of patients experienced a severe liver outcome. Of patients with low-, indeterminate-, and high-risk FIB-4 scores, 2%, 4%, and 20% suffered a severe liver outcome, respectively. In the overall adjusted model, high-risk FIB-4 scores were associated with hazard of severe liver disease (HR 6.64; 95% CI 5.58-7.90). High-risk FIB-4 scores were associated with severe liver outcomes for patients with known NAFLD (HR 7.32; 95% CI 3.44-15.58), other liver disease (HR 11.39; 95% CI 8.53-15.20), and no known CLD (HR 4.05; 95% CI 3.10-5.28). CONCLUSIONS: High-risk FIB-4 scores were strongly associated with risk of severe liver outcomes in patients with and without known CLD. Comprehensive FIB-4 application in primary care may signal silently advancing liver fibrosis.

High-risk opioid analgesic dispensing to adolescents 12-18 years old in South Carolina: 2010-2017.

PURPOSE: To evaluate "high-risk" opioid dispensing to adolescents, including daily morphine milligram equivalents (MME) above recommended amounts, the percentage of extended-release opioid prescriptions dispensed to opioid-naïve adolescents, and concurrent use of opioids and benzodiazepines, and to evaluate changes in those rates over time. METHODS: Retrospective cohort study of one state's prescription drug monitoring program data (2010-2017), evaluating adolescents 12-18 years old dispensed opioid analgesic prescriptions. Outcomes of interest were the quarterly frequencies of the high-risk measures. We utilized generalized linear regression to determine whether the rate of the outcomes changed over time. RESULTS: The quarterly percentage of adolescents ages 12-18 years old dispensed an opioid who received ≥90 daily MME declined from 4.1% in the first quarter (Q1) of 2010 to 3.4% in the final quarter (Q4) of 2017 (p < 0.0001). The frequency of adolescents dispensed ≥50 daily MME changed little over time. In 2010, the percentage of adolescents receiving an extended-release opioid who were opioid naïve was 60.7%, declining to 50.6% by Q4 of 2017 (p > 0.10 overall change 2010-2017). The percentage of adolescent opioid days overlapping with benzodiazepine days was 1.6% in Q1 of 2010, declining to 1.1% by Q4 of 2017 (p < 0.001). CONCLUSIONS: Among persons 12-18 years old dispensed an opioid analgesic, receipt of ≥90 daily MME declined during the years 2010-2017, as did the percentage of adolescent opioid days that overlapped with benzodiazepines. More than half of the individuals who received extended-release opioid analgesics were identified as opioid naïve and, counter to guidelines, received products intended for opioid-tolerant individuals.

Preventive Care Utilization by Patients Who Use Virtual Urgent Care.

Introduction: The use of direct to patient (DTP) telemedicine for common acute conditions is widespread. It provides certain advantages over in-person visits, but has led to concerns about fragmentation of care. It is unknown whether use of DTP telemedicine decreases use of primary care services in a way that leads to missed preventive screenings and immunizations. Methods: Virtual urgent care (VUC) is a DTP telemedicine service to treat common acute conditions. All VUC encounters completed at an academic health system from July 2018 to December 2019 were evaluated and analyzed in 2020. Only patients established with primary care (at least one primary care visit in the same year as VUC encounter) were included. Specific preventive screenings (breast cancer, gonorrhea/chlamydia, and cervical cancer) and immunizations (tetanus and influenza) were characterized as up to date based on national guidelines. Chi-squares and multivariate logistic regressions were used to assess receipt of screenings and immunizations. Regressions included VUC and primary care utilization and demographic factors. Results: Patients evaluated (N = 1025) were mostly 25-50 years old (69.7%), women (81.8%), and white (74.9%). More than half (56.5%) had only used VUC once. In multivariate analyses, VUC utilization was not negatively associated with any of the preventive services evaluated, whereas primary care utilization was associated with receipt of both immunizations and gonorrhea/chlamydia screening. Conclusions: Higher VUC utilization is not negatively associated with receipt of preventive services, as long as a primary care relationship is established. VUC may provide a useful method of encouraging receipt of preventive services, especially for younger patients.

Significant hospitalization cost savings to the payer with a pharmacist-led mobile health intervention to improve medication safety in kidney transplant recipients.

This was an economic analysis of a 12-month, parallel arm, randomized controlled trial in adult kidney recipients 6 to 36 months posttransplant (NCT03247322). All participants received usual posttransplant care, while the intervention arm received supplemental clinical pharmacist-led medication therapy monitoring and management, via a smartphone-enabled mHealth app, integrated with risk-based televisits. Hospitalization charges were captured from the study institution accounts payable and non-study institution hospitalization charges were estimated using multiple imputation. Multivariable modeling was used to assess the impact of the intervention on charges. The intervention significantly reduced rates of hospitalization (1.08 per patient-year in the control arm vs 0.65 per patient-year in the intervention arm, p = .007). The control arm had estimated hospitalization costs of $870,468 vs $390,489 in the intervention arm. Modeling demonstrated a 49% lower hospitalization charge risk in the intervention arm (RR 0.51, 95% CI 0.28-0.91; p = .022). From a payer or societal perspective, the net estimated cost savings, after accounting for intervention delivery costs, was $368,839, with a return on investment (ROI) of $4.30 for every $1 spent. These results demonstrate that a mHealth-enabled, pharmacist-led intervention significantly reduced hospitalization costs for payers over a 12-month period and has a positive ROI.

Advanced liver fibrosis and the metabolic syndrome in a primary care setting.

AIMS: The fibrosis-4 index (FIB-4) and NAFLD fibrosis score (NFS) are noninvasive and accessible methods for assessing advanced liver fibrosis risk in primary care. We evaluated the distribution of FIB-4 and NFS scores in primary care patients with clinical signals for nonalcoholic fatty liver disease (NAFLD). MATERIALS AND METHODS: This retrospective cohort study of electronic record data between 2007 and 2018 included adults with at least one abnormal aminotransferase and no known (non-NAFLD) liver disease. We calculated patient-level FIB-4 and NFS scores, the proportion of patients with mean values exceeding advanced fibrosis thresholds (indeterminate risk: FIB-4 > 1.3, NFS > -1.455; high-risk: FIB-4 > 2.67, NFS > 0.676), and the proportion of patients with a NAFLD International Classification of Diseases-9/10 code. Logistic regression models evaluated the associations of metabolic syndrome (MetS) components with elevated FIB-4 and NFS scores. RESULTS: The cohort included 6506 patients with a median of 6 (interquartile range: 3-13) FIB-4 and NFS scores per patient. Of these patients, 81% had at least two components of MetS, 29% had mean FIB-4 and NFS scores for indeterminate fibrosis risk, and 11% had either mean FIB-4 or NFS scores exceeding the high advanced fibrosis risk thresholds. Regression models identified associations of low high-density lipoprotein, hyperglycemia, Black race and male gender with high-risk FIB-4 and NFS values. Only 5% of patients had existing diagnoses for NAFLD identified. CONCLUSIONS: Many primary care patients have FIB-4 and NFS scores concerning for advanced fibrosis, but rarely a diagnosis of NAFLD. Elevated FIB-4 and NFS scores may provide signals for further clinical evaluation of liver disease in primary care settings.

Academic detailing increases prescription drug monitoring program use among primary care practices.

OBJECTIVE: Clinical review of a prescription drug monitoring program (PDMP) is considered a valuable tool for opioid prescribing risk mitigation; however, PDMP use is often low, even in states with mandatory registration and use policies. The objective was to evaluate the impact of an academic detailing (AD) outreach intervention on PDMP use among primary care prescribers. METHODS: AD intervention was delivered to primary care based controlled substance prescribers (N = 87) and their associated PDMP delegates (n = 42) by a clinical pharmacist as 1 component of a large-scale, statewide initiative to improve opioid prescribing safety. Prescriber PDMP use behavior was assessed by prescriber self-report and analysis of objective 2016-2018 PDMP data regarding the number of monthly report requests. We compared means between pre- and postintervention using a paired t test and plotted the monthly average reports over time to assess the trend of mean reports over time. Generalized linear mixed model with a negative binomial distribution was used to assess the difference in the trend and magnitude of the combined count of reports for the entire sample and prescriber subsets that were segmented on the basis of the adoption status of PDMP. RESULTS: The monthly mean of reports by combined prescribers and delegates significantly increased after the AD intervention (mean 28.1 pre vs. 53.0 post; P < 0.001), with the increase in delegate reports (mean 17.1 pre vs. 60.0 post; P < 0.001) driving the overall increase. Reports were requested 40.4 times more often than in the preintervention period (P < 0.001). Patterns of pre- to postchanges in mean monthly report requests differed by baseline PDMP adoption status. CONCLUSION: The AD intervention was transformative in facilitating practice change to use delegates to run reports. Visits with both prescribers and delegates, including hands-on PDMP training and registration assistance, can be viewed as beneficial for practice facilitation.

Patient Demographics and Clinic Type Are Associated With Patient Engagement Within a Remote Monitoring Program.

Background: Remote physiological monitoring (RPM) is accessible, convenient, relatively inexpensive, and can improve clinical outcomes. Yet, it is unclear in which clinical setting or target population RPM is maximally effective. Objective: To determine whether patients' demographic characteristics or clinical settings are associated with data transmission and engagement. Methods: This is a prospective cohort study of adults enrolled in a diabetes RPM program for a minimum of 12 months as of April 2020. We developed a multivariable logistic regression model for engagement with age, gender, race, income, and primary care clinic type as variables and a second model to include first-order interactions for all demographic variables by time. The participants included 549 adults (mean age 53 years, 63% female, 54% Black, and 75% very low income) with baseline hemoglobin A1c ≥8.0% and enrolled in a statewide diabetes RPM program. The main measure was the transmission engagement over time, where engagement is defined as a minimum of three distinct days per week in which remote data are transmitted. Results: Significant predictors of transmission engagement included increasing age, academic clinic type, higher annual household income, and shorter time-in-program (p < 0.001 for each). Self-identified race and gender were not significantly associated with transmission engagement (p = 0.729 and 0.237, respectively). Conclusions: RPM appears to be an accessible tool for minority racial groups and for the aging population, yet engagement is impacted by primary care location setting and socioeconomic status. These results should inform implementation of future RPM studies, guide advocacy efforts, and highlight the need to focus efforts on maintaining engagement over time.

High-Risk Opioid Prescribing Trends: Prescription Drug Monitoring Program Data From 2010 to 2018.

OBJECTIVE: Deaths due to opioids have continued to increase in South Carolina, with 816 opioid-involved overdose deaths reported in 2018, a 9% increase from the prior year. The objective of the current study is to examine longitudinal trends (quarter [Q] 1 2010 through Q4 2018) of opioid prescribing volume and high-risk opioid prescribing behaviors in South Carolina using comprehensive dispensing data available in the South Carolina Prescription Drug Monitoring Program (SC PDMP). DESIGN: Retrospective analyses of SC PDMP data were performed using general linear models to assess quarterly time trends and change in rate of each outcome Q1 2010 through Q4 2018. PARTICIPANTS: Opioid analgesic prescription fills from SC state residents between Q1 2010 and Q4 2018. MAIN OUTCOME MEASURES: High-risk prescribing behaviors included (1) opioid prescribing rate; (2) percentage of patients receiving opioids dispensed 90 or more average morphine milligram equivalents daily; (3) percentage of opioid prescribed days with overlapping opioid and benzodiazepine prescriptions; (4) rate per 100 000 residents of multiple provider episodes; and (5) percentage of patients prescribed extended release opioids who were opioid naive. RESULTS: A total of 33 027 461 opioid prescriptions were filled by SC state residents within the time period of Q1 2010 through Q4 2018. A 41% decrease in the quarterly prescribing rate of opioids occurred from Q1 2010 to Q4 2018. The decrease in overall opioid prescribing was mirrored by significant decreases in all 4 high-risk prescribing behaviors. CONCLUSION: PDMPs may represent the most complete data regarding the dispensing of opioid prescriptions and as such be valuable tools to inform and monitor the supply of licit opioids. Our results indicate that public health policy, legislative action, and multiple clinical interventions aimed at reducing high rates of opioid prescribing across the health care ecosystem appear to be succeeding in the state of South Carolina.

Impact of Patient-Level Characteristics on In-hospital Mortality After Interhospital Transfer to Medicine Services: an Observational Study.

BACKGROUND: National administrative datasets have demonstrated increased risk-adjusted mortality among patients undergoing interhospital transfer (IHT) compared to patients admitted through the emergency department (ED). OBJECTIVE: To investigate the impact of patient-level data not available in larger administrative datasets on the association between IHT status and in-hospital mortality. DESIGN: Retrospective cohort study with logistic regression analyses to examine the association between IHT status and in-hospital mortality, controlling for covariates that were potential confounders. Model 1: IHT status, admit service. Model 2: model 1 and patient demographics. Model 3: model 2 and disease-specific conditions. Model 4: model 3 and vital signs and laboratory data. PARTICIPANTS: Nine thousand three hundred twenty-eight adults admitted to Medicine services. MAIN MEASURES: Interhospital transfer status, coded as an unordered categorical variable (IHT vs ED vs clinic), was the independent variable. The primary outcome was in-hospital mortality. Secondary outcomes included unadjusted length of stay and total cost. KEY RESULTS: IHT patients accounted for 180 out of 484 (37%) in-hospital deaths, despite accounting for only 17% of total admissions. Unadjusted mean length of stay was 8.4 days vs 5.6 days (p < 0.0001) and mean total cost was $22,647 vs $12,968 (p < 0.0001) for patients admitted via IHT vs ED respectively. The odds ratios (OR) for in-hospital mortality for patients admitted via IHT compared to the ED were as follows: model 1 OR, 2.06 (95% CI 1.66-2.56, p < 0.0001); model 2 OR, 2.07 (95% CI 1.66-2.58, p < 0.0001); model 3 OR, 2.07 (95% CI 1.63-2.61, p < 0.0001); model 4 OR, 1.70 (95% CI 1.31-2.19, p < 0.0001). The AUCs of the models were as follows: model 1, 0.74; model 2, 0.76; model 3, 0.83; model 4, 0.88, consistent with a good prediction model. CONCLUSIONS: Patient-level characteristics affect the association between IHT and in-hospital mortality. After adjusting for patient-level clinical characteristics, IHT status remains associated with in-hospital mortality.

The effect of targeted insurer-mandated prescription monitoring on opioid prescribing patterns.

OBJECTIVES: The purpose of this study was to determine the impact of a mandate from 2 large insurers in South Carolina for mandatory review of the state's prescription drug monitoring program (PDMP) for controlled substance (CS) prescriptions for more than 5 days' supply on the proportion of opioid prescriptions for less than or equal to 5 days in a statewide adult population. In addition, changes in the mean morphine milligram equivalents (MME) per day for prescriptions for 5 days or less were described to evaluate prescribing changes. DESIGN, SETTING AND PARTICIPANTS: All prescriptions for opioids written for and filled by adults (≥ 18 years of age) and reported to the PDMP from January 1, 2010, to December 31, 2017, were included in an interrupted time series analysis. OUTCOME MEASURES: An interrupted time series analysis was performed to determine if there was a significant change in the proportion of opioid prescriptions for less than or equal to 5 days' supply. RESULTS: Overall opioid prescriptions decreased over the time period by 11.5%, including a decreasing rate of opioid prescriptions for less than or equal to 5 days' supply. There was no statistical difference in the slope between the pre- and postmandate cohorts (P = 0.077, r2 = 0.951). There was not an identified corresponding increase in the MME per day of prescriptions. CONCLUSION: Our analysis found that 2 major insurer mandates that occurred in South Carolina in 2016, which required a review of the state PDMP for CS prescriptions for more than 5 days' supply, did not have a significant impact on the proportion of opioid prescriptions for less than or equal to 5 days' supply in the statewide population. In addition, we did not find any concern that prescribers attempted to circumvent the requirement by inappropriately adjusting dosing instructions.

Hospital admissions and emergency department visits among kidney transplant recipients.

Reducing acute care utilization is a means of improving long-term patient outcomes. We sought to assess high inpatient (IP) admission and standalone emergency department (ED) utilization within a 9-month period post-kidney transplantation and to identify mutable factors to reduce utilization. In this ten-year retrospective study, 1599 adult kidney transplant recipients were identified. A previous transplant, graft loss, or death within 3 months post-transplantation excluded 319 patients. Comprehensive resource utilization data were obtained from a statewide database. Those with ≥2 IP admissions or standalone ED visits 4-12 months post-transplantation were classified as high utilizers. Multivariable logistic regression models were used for examining associations of predictors with high IP or ED utilization. Of 1280 kidney recipients, 209 and 183 were categorized as IP and ED high utilizers, respectively. Factors significantly associated with high IP utilization included valvular disease, body mass index ≥35, and IP or ED use <3 months post-transplantation; while factors associated with high ED utilization included IP or ED use <3 months post-transplantation, younger age, female, smoker, congestive heart failure, depression, and IP or ED use 1 year pre-transplantation. Inpatient and standalone ED utilization within a 9-month period after kidney transplantation is high and associated with sociodemographic factors, mutable comorbidities, and healthcare utilization.

The impact of time-varying clinical surrogates on disparities in African-American kidney transplant recipients - a retrospective longitudinal cohort study.

An improved understanding of the impact of clinical surrogates on disparities in African-American (AA) kidney transplantation (KTX) is needed. We conducted a 10-year retrospective longitudinal cohort study of electronically abstracted clinical data assessing the impact of surrogates on disparities in KTX. Clinical surrogates were assessed by posttransplant year (1, 2, 3 or 4) and defined as acute rejection (Banff ≥1A), mean SBP >140 mmHg, tacrolimus variability (CV) >40%, mean glucose >160 mg/dl and mean hemoglobin <10 g/dl. We utilized landmark methodology to minimize immortal time bias and logistic and survival regression to assess outcomes; 1610 KTX were assessed (54.2% AAs), with 1000, 468, 368 and 303 included in the year 1, 2, 3 and 4 complete case analyses, respectively. AAs had significantly higher odds of developing a clinical surrogate, which increased in posttransplant years three and four [OR year 1 1.99 (1.38-2.88), year 2 1.77 (1.20-2.62), year 3 2.35 (1.49-3.71), year 4 2.85 (1.72-4.70)]. Adjusting for the five clinical surrogates in survival models explained a significant portion of the higher risks of graft loss in AAs in post-transplant years three and four. Results suggest focusing efforts on improving late clinical surrogate management within AAs may help mitigate racial disparities in KTX.

Development and future deployment of a 5 years allograft survival model for kidney transplantation.

AIM: Identifying kidney transplant patients at highest risk for graft loss prior to loss may allow for effective interventions to improve 5 years survival. METHODS: We performed a 10 years retrospective cohort study of adult kidney transplant recipients (n = 1747). We acquired data from electronic health records, United Network of Organ Sharing, social determinants of health, natural language processing data extraction, and real-time capture of dynamically evolving clinical data obtained within 1 year of transplant; from which we developed a 5 years graft survival model. RESULTS: Total of 1439 met eligibility; 265 (18.4%) of them experienced graft loss by 5 years. Graft loss patients were characterized by: older age, being African-American, diabetic, unemployed, smokers, having marginal donor kidneys and cardiovascular comorbidities. Predictive dynamic variables included: low mean blood pressure, higher pulse pressures, higher heart rate, anaemia, lower estimated glomerular filtration rate peak, increased tacrolimus variability, rejection and readmissions. This Big Data analysis generated a 5 years graft loss model with an 82% predictive capacity, versus 66% using baseline United Network of Organ Sharing data alone. CONCLUSION: Our analysis yielded a 5 years graft loss model demonstrating superior predictive capacity compared with United Network of Organ Sharing data alone, allowing post-transplant individualized risk-assessed care prior to transitioning back to community care.