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.

Dissemination of Remote Patient Monitoring: An Academic-Community Primary Care Partnership in South Carolina.

CONTEXT: Remote patient monitoring (RPM) for diabetes and hypertension may reduce barriers to patient care, leading to improved disease control and decreased morbidity and mortality. PROGRAM: We describe the implementation of a community-academic partnership to improve diabetes and hypertension control for underserved populations using RPM. IMPLEMENTATION: In 2014, our academic medical center (AMC) began working with community health centers (CHCs) to implement a centrally monitored RPM program for patients with diabetes. AMC nurses recruited, trained, and supported community partners through regular communication. Community sites were responsible for enrollment, follow-up visits, and all treatment adjustments. EVALUATION: More than 1350 patients have been enrolled across 19 counties and 16 predominantly rural CHCs. The majority of patients reported low annual household income and African American or Hispanic background. It took about 6 to 9 months of planning at each CHC prior to first enrolled patient. More than 30% of patients utilizing the newer device continued to transmit glucose readings regularly at week 52 of enrollment. Hemoglobin A 1c data reporting was completed for more than 90% of patients at 6 and 12 months postenrollment. DISCUSSION: Partnering of our AMC with CHCs enabled dissemination of an effective, inexpensive tool that engaged underserved populations in rural South Carolina and improved chronic disease management. We supported implementation of clinically effective diabetes RPM programs at several CHCs, reaching a large number of historically underserved and underresourced rural CHC patients with diabetes. We summarize key steps to achieving a successful, collaborative RPM program through AMC-CHC partnerships.

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.

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.

Sustained Improvement in Blood Pressure Control for a Multiracial Cohort: Results of a Patient-centered Medical Home Quality Improvement Initiative.

BACKGROUND: Patient-centered medical homes incorporate strategies to increase healthcare access as a means of improving health at the patient and population level. We hypothesized that quality improvement initiatives based in a patient-centered medical home would improve hypertension control for adult patients, regardless of race. METHODS: This prospective cohort study included patients of a hospital-based Internal Medicine practice in the southeastern U.S. whose systolic blood pressure was uncontrolled (criteria ≥140mmHg) prior to patient-centered medical home certification. Mean systolic blood pressure and hypertension control rates were calculated from the average of the four quarterly means prior to patient-centered medical home designation and again from the last 4 quarters of the five-year study period (final). Quality improvement interventions included patient identification, multidisciplinary team meetings, targeted outreach, and dedicated office visits for addressing hypertension. Primary outcomes included the change in systolic blood pressure and the change in the proportion of the cohort with hypertension control. Chi-square, two sample t-tests, and ANOVA were used for comparison (SAS 9.3). RESULTS: The inception cohort had 1,702 patients (64% nonwhite, 36% white) with systolic blood pressure ≥140mmHg. Mean systolic blood pressure significantly decreased while hypertension control rates increased in both races after patient-centered medical home certification. White adults had lower mean systolic blood pressure and higher control rates at baseline and study conclusion compared to nonwhite adults. Similar trends persisted regardless of the number of office visits. CONCLUSIONS: The analysis of blood pressure before and after designation of an Internal Medicine clinic as a patient-centered medical home reveals disparities in rates of chronic disease control. Team-based outreach improves hypertension control for patients regardless of race or visit number. These findings suggest that patient-centered medical homes and a multidisciplinary care approach, not limited to increased access, improve chronic disease control and should be considered for diverse outpatient clinics.

When Should ED Physicians Use an HIE? Predicting Presence of Patient Data in an HIE.

OBJECTIVES: Health information exchanges (HIEs) make possible the construction of databases to characterize patients as multisystem users (MSUs), those visiting emergency departments (EDs) of more than one hospital system within a region during a 1-year period. HIE data can inform an algorithm highlighting patients for whom information is more likely to be present in the HIE, leading to a higher yield HIE experience for ED clinicians and incentivizing their adoption of HIE. Our objective was to describe patient characteristics that determine which ED patients are likely to be MSUs and therefore have information in an HIE, thereby improving the efficacy of HIE use and increasing ED clinician perception of HIE benefit. METHODS: Data were extracted from a regional HIE involving four hospital systems (11 EDs) in the Charleston, South Carolina area. We used univariate and multivariable regression analyses to develop a predictive model for MSU status. RESULTS: Factors associated with MSUs included younger age groups, dual-payer insurance status, living in counties that are more rural, and one of at least six specific diagnoses: mental disorders; symptoms, signs, and ill-defined conditions; complications of pregnancy, childbirth, and puerperium; diseases of the musculoskeletal system; injury and poisoning; and diseases of the blood and blood-forming organs. For patients with multiple ED visits during 1 year, 43.8% of MSUs had ≥4 visits, compared with 18.0% of non-MSUs (P < 0.0001). CONCLUSIONS: This predictive model accurately identified patients cared for at multiple hospital systems and can be used to increase the likelihood that time spent logging on to the HIE will be a value-added effort for emergency physicians.

A Comprehensive View of Frequent Emergency Department Users Based on Data from a Regional HIE.

OBJECTIVES: A small but significant number of patients make frequent emergency department (ED) visits to multiple EDs within a region. We have a unique health information exchange (HIE) that includes every ED encounter in all hospital systems in our region. Using our HIE we were able to characterize all frequent ED users in our region, regardless of hospital visited or payer class. The objective of our study was to use data from an HIE to characterize patients in a region who are frequent ED users (FEDUs). METHODS: We constructed a database from a cohort of adult patients (18 years old or older) with information in a regional HIE for a 1-year period beginning in April 2012. Patients were defined as FEDUs (those who made four or more visits during the study period) and non-FEDUs (those who made fewer than four ED visits during the study period). Predictor variables included age, race, sex, payer class, county of residence, and International Classification of Diseases, Ninth Revision codes. Bivariate (χ(2)) and multivariate (logistic regression) analyses were performed to determine associations between predictor variables and the outcome of being a FEDU. RESULTS: The database contained 127,672 patients, 12,293 (9.6%) of whom were FEDUs. Logistic regression showed the following patient characteristics to be significantly associated with the outcome of being a FEDU: age 35 to 44 years; African American race; Medicaid, Medicare, and dual-pay payer class; and International Classification of Diseases, Ninth Revision codes 630 to 679 (complications of pregnancy, childbirth, and puerperium), 780 to 799 (ill-defined conditions), 280 to 289 (diseases of the blood), 290-319 (mental disorders), 680 to 709 (diseases of the skin and subcutaneous tissue), 710 to 739 (musculoskeletal and connective tissue disease), 460 to 519 (respiratory disease), and 520 to 579 (digestive disease). No significant differences were noted between men and women. CONCLUSIONS: Data from an HIE can be used to describe all of the patients within a region who are FEDUs, regardless of the hospital system they visited. This information can be used to focus care coordination efforts and link appropriate patients to a medical home. Future studies can be designed to learn the reasons why patients become FEDUs, and interventions can be developed to address deficiencies in health care that result in frequent ED visits.

Is hospitalization a missed opportunity to intervene on tobacco cessation?

BACKGROUND: Although tobacco use is associated with elevated morbidity and mortality, its use remains widespread among adults within the United States. Nicotine Replacement Therapy (NRT) products are effective aids that improve rates of tobacco cessation. Many smokers interact with the medical system, such as during hospitalization, without their tobacco use addressed. Hospitalization is a teachable moment for patients to make health-related changes, including tobacco cessation. METHODS: Retrospective cohort study of adult patients in a university-based patient-centered medical home from 2012 to 2021 evaluating the proportion of adults who smoke who received at least one prescription for NRT. Logistic regression models were used to analyze the association of being hospitalized and receipt of a NRT prescription. RESULTS: Of the 4,072 current smokers identified, 1,182 (29%) received at least one prescription for NRT during the study period. Hospitalization was associated with increased odds of receiving a NRT prescription (OR 1.68). Of 1,844 current smokers with a hospitalization during the study period, 1,078 (58%) never received a prescription for NRT at any point. Only 87 (5%) of the smokers received a prescription for NRT during hospitalization or at the time of hospital discharge. CONCLUSIONS: Despite hospitalization being associated with NRT prescribing, most patients who use tobacco and are hospitalized are not prescribed NRT. Hospitalization is an underutilized opportunity for both hospitalists and primary care physicians to intervene on smoking cessation through education and prescription of tobacco cessation aids.

Hospitalization as an opportunity to improve lung cancer screening in high-risk patients.

BACKGROUND: Lung cancer screening with annual low-dose computed tomography (LDCT) in high-risk patients with exposure to smoking reduces lung cancer-related mortality, yet the screening rate of eligible adults is low. As hospitalization is an opportune moment to engage patients in their overall health, it may be an opportunity to improve rates of lung cancer screening. Prior to implementing a hospital-based lung cancer screening referral program, this study assesses the association between hospitalization and completion of lung cancer screening. METHODS: A retrospective cohort study of evaluated completion of at least one LDCT from 2014 to 2021 using electronic health record data using hospitalization as the primary exposure. Patients aged 55-80 who received care from a university-based internal medicine clinic and reported cigarette use were included. Univariate analysis and logistic regression evaluated the association of hospitalization and completion of LDCT. Cox proportional hazard model examined the time relationship between hospitalization and LDCT. RESULTS: Of the 1935 current smokers identified, 47% had at least one hospitalization, and 21% completed a LDCT during the study period. While a higher proportion of patients with a hospitalization had a LDCT (24%) compared to patients without a hospitalization (18%, p<0.001), there was no association between hospitalization and completion of a LDCT after adjusting for potentially confounding covariates (95%CI 0.680 - 1.149). There was an association between hospitalization time to event and LDCT completion, with hospitalized patients having a lower probability of competing LDCT compared to non-hospitalized patients (HR 0.747; 95% CI 0.611 - 0.914). CONCLUSIONS: In a cohort of patients at risk for lung cancer and established within a primary care clinic, only 1 in 4 patients who had been hospitalized completed lung cancer screening with LDCT. Hospitalization events were associated with a lower probability of LDCT completion. Hospitalization is a missed opportunity to refer at-risk patients to lung cancer screening.