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Patients admitted via interhospital transfer (IHT) experience increased risk-adjusted mortality, adverse events, length of stay, and discharge to facility; however, the etiology is not well understood. We hypothesize that IHTs are more likely to experience in-hospital delirium as compared with admissions to the hospital via the emergency department (ED) and clinic. This is a cross-sectional study of all adult admissions to medical, surgical, neurological, and obstetrics and gynecology services at an academic medical center who were screened for delirium between August 2018 and January 2020. Unit of analysis was admission source (IHT vs ED vs clinic) as the independent variable and the primary outcome was in-hospital delirium, assessed with initial brief confusion assessment method (bCAM) screening. 30,100 hospitalizations were included in this study with 3925 admissions (13.0%) screening positive for delirium at the initial bCAM assessment. The prevalence of delirium was much higher in IHTs at 22.3% (1334/5971) when compared with clinic at 5.8% (244/4214) and ED at 11.8% (2347/19,915) admissions. Multivariable logistic regression adjusting for demographics and comorbidities showed that IHT admissions had higher odds (OR 1.91, 95% CI 1.74 to 2.10) and clinic admissions had lower odds (OR 0.56, 95% CI 0.48 to 0.64) of in-hospital delirium compared with ED admissions. Increased odds of delirium in IHT admissions may contribute to the observed increased length of stay, discharge to facility, and mortality. These results emphasize the importance of routine screening and possible intervention prior to patient transfer.

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.

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.

AIMS: We sought to determine whether underserved patients enrolled in a statewide remote patient monitoring (RPM) program for diabetes achieve sustained improvements in hemoglobin A(1c) at 6 and 12 months and whether those improvements are affected by demographic and clinical variables. METHODS: Demographic and clinical variables were obtained at baseline, 6 months and 12 months. Baseline HbA1c values were compared with those obtained at 6 and 12 months via paired t-tests. A multivariable regression model was developed to identify patient-level variables associated with HbA(1c) change at 12 months. RESULTS: HbA(1c) values were obtained for 302 participants at 6 months and 125 participants at 12 months. Compared to baseline, HbA(1c) values were 1.8% (19mmol/mol) lower at 6 months (p

Retrospective administrative database review.Analyze patterns of opioid use in patients undergoing lumbar surgery and determine associated risk factors in a Medicaid population.Opioid use in patients undergoing surgery for degenerative lumbar spine conditions is prevalent and impacts outcomes. There is limited information defining the scope of this problem in Medicaid patients.Longitudinal cohort study of adult South Carolina (SC) Medicaid patients undergoing lumbar surgery from 2014 to 2017. All patients had continuous SC Medicaid coverage for 15 consecutive months, including six months before and nine months following surgery. The primary outcome was a longitudinal assessment of postoperative opioid use to determine trajectories and group-based membership using latent modeling. Univariate and multivariable modeling was conducted to assess risk factors for group-based trajectory modeling and chronic opioid use (COU).A total of 1455 surgeries met inclusion criteria. Group-based trajectory model demonstrated patients fit into five groups; very low use (23.4%), rapid wean following surgery (18.8%), increasing use following surgery (12.9%), slow wean following surgery (12.6%) and sustained high use (32.2%). Variables predicting membership in high opioid use included preoperative opioid use, younger age, longer length of stay, concomitant medications, and readmissions. More than three quarter of patients were deemed COUs (76.4%). On bivariate analysis, patients with degenerative disk disease were more likely to be COUs (24.8% vs. 18.6%; P =0.0168), more likely to take opioids before surgery (88.5% vs. 61.9%; P0.001) and received higher amounts of opioids during the 30 days following surgery (mean morphine milligram equivalents 59.6 vs. 25.1; P0.001).Most SC Medicaid patients undergoing lumbar elective lumbar spine surgery were using opioids preoperatively and continued long-term use postoperatively at a higher rate than previously reported databases. Preoperative and perioperative intake, degenerative disk disease, multiple prescribers, depression, and concomitant medications were significant risk factors.

Background Acute myocardial infarction (AMI) carries a substantial mortality and morbidity burden. The purpose of this study is to provide annual mean cost per patient and national level estimates of direct and indirect costs (lost productivity from morbidity and premature mortality) associated with AMI. Methods Nationally representative data spanning 12 years (2003-2014) with a sample of 324,869 patients with AMI from the Medical Expenditure Panel Survey (MEPS) were analyzed. A novel 2-part model was used to examine the excess direct cost associated with AMI, controlling for covariates. To estimate lost productivity from morbidity, an adjusted Generalized Linear Model was used for the differential in wage earnings between participants with and without AMI. Lost productivity from premature mortality was estimated based on published data. Results The total annual cost of AMI in 2016 dollars was estimated to be $84.9 billion, including $29.8 billion in excess direct medical expenditures, $14.6 billion in lost productivity from morbidity and $40.5 billion in lost productivity from premature mortality between 2003 and 2014. In the adjusted regression, the overall excess direct medical expenditure of AMI was $7,076 (95% confidence interval [CI] $6,028-$8,125) higher than those without AMI. After adjustment, annual wages for patients with AMI were $10,166 (95% CI −$12,985 to −$7,347) lower and annual missed work days were 5.9 days (95% CI 3.57-8.27) higher than those without AMI. Conclusions The study finds that the economic burden of AMI is substantial, for which effective prevention could result in significant health and productivity cost savings.

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.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.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.FIB-4 scores with indeterminate- and high-risk values are associated with an increased incidence of SLD in primary care patients without known CLD.

Patients with delirium have increased hospital length of stay (LOS), morbidity and mortality. Impact of delirium on postacute care (PAC) utilization is not fully characterized. Impact of screening for delirium on general medicine patients is unknown. The objective of this study was to assess impact of screening for delirium on inpatient PAC utilization.This was a single center, retrospective cohort study at an academic tertiary care center in Charleston, SC. Patients were selected from adults hospitalized from home and discharged alive between June 2014 and June 2018. The brief confusion assessment method (bCAM) screening was conducted and documented by nursing on admission and every shift thereafter. Outcome measure was the proportion of patients discharged to facility.Of 93,388 non-ICU adult admission between June 2014 and June 2018, 4.4% of those not screened for delirium were discharged to facility versus 15.0% in those screened and 41.4% in those screening positive. Multivariable regression analysis showed that patients screened for delirium were 2.3 times more likely to discharge to facility (95% CI (2.145, 2.429)) while those with a positive bCAM were 3.3 times more likely than those with a negative bCAM to discharge to facility (95% CI (2.949, 3.712)).After adjusting for demographics, medication orders and comorbidities there was an association between screening for delirium, positive delirium screen and discharge to facility. An appreciation of where and why patients are discharged is imperative to optimize both patient care and cost utilization.

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

Background Many guidelines addressing the approach to abnormal liver chemistries, including bilirubin, transaminases and alkaline phosphatase, recommend repeating the tests. However, when clinicians repeat testing is unknown. Material and Methods This retrospective study followed adult patients with abnormal liver chemistries in a patient-centered medical home (PCMH) from 2007 to 2016. All PCMH patients possessing at least 1 abnormal liver test (total bilirubin, aminotransferases and alkaline phosphatase) were included. Patients were followed from the index abnormal liver chemistry until the next liver test result, or the end of the study period. The primary predictor variable of interest was the number of abnormal chemistries (out of 4) on index testing. Demographic and clinical variables served as other potential predictors of outcome. A Cox proportional hazards model was applied to investigate associations between the predictor variables and the time to repeat liver chemistry testing. Results Of 9,545 patients with at least 2 PCMH visits and 1 liver test abnormality, 6,489 (68%) obtained repeat testing within 1 year, and 80% of patients had follow-up tests within 2 years. Patients with multiple abnormal liver tests and those with higher degrees of abnormality were associated with shorter time to repeat testing. Conclusions A large proportion of patients with abnormal liver tests still lack repeat testing at 1 year. The number of liver abnormal liver tests and degree of elevation were inversely associated with the time to repeat testing.

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.To evaluate the association of FIB-4 risk with hazard of severe liver outcomes in primary care patients with and without diagnosed CLD.Retrospective cohort study of primary care data from 2007 to 2018.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.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.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).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.

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.

Background: The Fibrosis-4 Index (FIB-4) non-invasively assesses fibrosis risk in chronic liver disease, but underdiagnosis limits FIB-4’s application in primary care. This study evaluates the association of FIB-4 risk with severe liver outcomes in primary care patients with and without diagnosed chronic liver disease. Methods: This retrospective cohort study of primary care data from 2007 to 2018 Included adult patients with qualifying aminotransferase and platelet count results. A single FIB-4 score was calculated for each patient using the first of these values. Patients with a chronic liver disease diagnosis or outcome prior to their FIB-4 score were excluded. 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 with hazard risk of a severe liver outcome using stratified Cox regression models, stratifying patients by known chronic liver disease. Findings: 20,556 patients were followed for a mean 2,978 days (8·2 years; 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 6·54; 95% CI 5·49-7·77). High risk FIB-4 scores were associated with severe liver outcomes for patients with known NAFLD (HR 7·71; 95% CI 3·62-16·45), other liver disease (HR 11·12; 95% CI 8·33-14·82), and no known chronic liver disease (HR 4·04; 95% CI 3·10-5·28). Interpretation: High risk FIB-4 scores were strongly associated with risk of severe liver outcomes in patients with and without known chronic liver disease. Comprehensive FIB-4 application in primary care may signal silently advancing liver fibrosis. Funding Information: National Institute of Diabetes and Digestive and Kidney Diseases (NIH/NIDDKK23DK118200 PI: Schreiner). Declaration of Interests: All authors report no conflicts of interest with this work. Ethics Approval Statement: The Institutional Review Board at the Medical University of South Carolina (MUSC) approved this study.

Objectives Tonsillectomy (with or without adenoidectomy) is a common pediatric surgical procedure requiring post-operative analgesia. Because of the respiratory depression effects of opioids, clinicians strive to limit the use of these drugs for analgesia post-tonsillectomy. The objective of this study was to identify demographic and medication use patterns predictive of persistent opioid dispensing (as a proxy for opioid use) to pediatric patients post-tonsillectomy. Patients and methods Retrospective cohort of South Carolina (USA) Medicaid-insured children and adolescents 0–18 years old without malignancy who had tonsillectomy in 2014–2017. We evaluated opioid dispensing pre-surgery and in the 30 days exposure period after hospital discharge. The main outcome, persistent opioid dispensing, was defined as any subject dispensed ≥1 opioid prescription 90–270 days after discharge. Group-based trajectory analyses described post-procedure opioid dispensing trajectories. Results There were 11,578 subjects representing 12,063 tonsillectomy procedures. Few (3.5%) procedures were followed by persistent opioid dispensing. Any opioid dispensing during the exposure period was associated with an increased odds of persistent opioid dispensing status during the follow up period (OR 1.51 for 1–6 days of exposure and OR 1.65 for 7–30 days of opioid exposure), as was pre-procedure opioid dispensing, having >1 tonsillectomy procedure, and having complex chronic medical conditions. Group-based trajectory analyses identified 4 distinct patterns of post-discharge opioid dispensing. Conclusions Any opioid dispensing during the 30 days after tonsillectomy increased the odds of persistent opioid dispensing by > 50%. Multivariable and group-based trajectory analyses identified patient and procedure variables that correlate with persistent opioid dispensing, primarily driven by groups receiving pre-tonsillectomy opioids and a second group who experienced multiple episodes of tonsillectomy.

Quality gaps exist in the hepatitis C virus (HCV) care process from diagnosis to cure. To better understand current gaps and to identify targets for quality improvement, we constructed an HCV care cascade in a patient-centered medical home (PCMH) with an emphasis on the specialty referral process. We performed a retrospective study of HCV-infected patients in a PCMH using electronic health record (EPIC) data. Patients with a first positive HCV RNA between 2012 and 2019 were included. With an adaptation to analyze linkage to specialty care, we created an HCV care cascade that included the following: (1) a positive HCV RNA, (2) referral to a specialty provider, (3) a scheduled specialty appointment, (4) attendance at a specialty visit, (5) prescription for HCV therapy, and (6) evidence of sustained virological response (SVR). Patient and referring clinician characteristics were analyzed at each step of the care pathway, and the proportion of patients completing each step was calculated. Of the 256 HCV RNA-positive patients, 229 (89.5%) received a specialty referral; 215 (84.0%) had an appointment scheduled; 178 (69.5%) attended the specialty appointment; 116 (45.3%) were prescribed antiviral therapy; and 87 (34.1%) had documented SVR during the study period. Of the 178 patients attending a specialty visit, 62 (34.8%) did not receive a prescription, and the barrier most often noted was the desire for further workup (40.3%). Gaps occur at all stages of the HCV care continuum, with drop-offs in care occurring both before and after linkage to specialty care.

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.

Abnormal liver tests are extremely common in clinical practice, present with varying patterns and degrees of elevation, and can signal liver injury from a variety of causes. Responding to these abnormalities requires complex medical decision-making and merits investigation in primary care. This retrospective study investigates the association of patterns of liver test abnormality with follow-up in primary care. Using administrative data, this study includes patients with abnormal liver tests seen between 2007 and 2016 in a patient-centered medical home. Liver tests examined include serum bilirubin, aspartate aminotransferase, alanine aminotransferase, and alkaline phosphatase. Patients entered the cohort on the first liver test elevation. The outcome examined was completion of repeat testing, and the proportions of patients without follow-up were compared by patterns of index abnormality. 9545 patients met the inclusion criteria. Of these, 6155 (64.5%) possessed one liver test abnormality and 3390 (35.5%) possessed multiple abnormalities on index testing. Overall 1119 (11.7%) patients did not have repeat testing performed during the study period. A greater proportion of patients with lone abnormalities lacked repeat testing compared with those patients with multiple abnormalities. Differences in repeat testing appeared when comparing clinical patterns of abnormality, with higher proportions of follow-up in patients with testing suggestive of cholestasis. Over 11% of patients with abnormal liver tests did not undergo repeat testing during the study period. Repeat testing occurred more often in patients with multiple abnormalities and in clinical patterns suggestive of cholestasis. This study highlights a potential opportunity to improve quality of care.

Aim: The effects of frailty and multiple chronic conditions (MCCs) on cost of care are rarely disentangled in archival data studies. We identify the marginal contribution of frailty to medical care cost estimates using Medicare data. Materials & methods: Use of the Faurot frailty score to identify differences in acute medical events and cost of care for patients, controlling for MCCs and medication use. Results: Estimated marginal cost of frailty was US$10,690 after controlling for demographics, comorbid conditions, polypharmacy and use of potentially inappropriate medications. Conclusion: Frailty contributes greatly to cost of care, but while often correlated, is not synonymous with MCCs. Thus, it is important to control separately for frailty in studies that compare medical care use and cost.

Objective Periods of economic instability may increase preventable hospitalizations because of increased barriers to accessing primary care. For underserved populations such as the homeless, these barriers may be more pronounced due to limited resources in the health care safety net. This study examined the impact of the global financial crisis of 2007–2008 on access to care for the homeless in New York State. Methods Hospitalizations for ambulatory care sensitive conditions (ACSCs) were used as a proxy measure for primary care access. Admissions for ACSCs were identified in the New York State Inpatient Database from 2006 to 2012. Hospitalization rates for ACSCs were calculated for the homeless and nonhomeless. Multivariable linear regression was used to investigate the impact of the financial crisis on hospitalization rates for ACSCs. Results The findings indicate that during the financial crisis, homeless adults had significantly higher preventable hospitalizations than nonhomeless adults, and the uninsured homeless had significantly higher preventable hospitalizations when compared to other homeless subgroups. After the financial crisis, preventable hospitalizations for the homeless stabilized but remained at higher rates than those for the nonhomeless. Conclusions These findings are important to developing health policies designed to provide effective care for underserved population such as the homeless.

We sought proof of concept of a Big Data Solution incorporating longitudinal structured and unstructured patient-level data from electronic health records (EHR) to predict graft loss (GL) and mortality. For a quality improvement initiative, GL and mortality prediction models were constructed using baseline and follow-up data (0-90 days posttransplant; structured and unstructured for 1-year models; data up to 1 year for 3-year models) on adult solitary kidney transplant recipients transplanted during 2007-2015 as follows: Model 1: United Network for Organ Sharing (UNOS) data; Model 2: UNOS & Transplant Database (Tx Database) data; Model 3: UNOS, Tx Database & EHR comorbidity data; and Model 4: UNOS, Tx Database, EHR data, Posttransplant trajectory data, and unstructured data. A 10% 3-year GL rate was observed among 891 patients (2007-2015). Layering of data sources improved model performance; Model 1: area under the curve (AUC), 0.66; (95% confidence interval [CI]: 0.60, 0.72); Model 2: AUC, 0.68; (95% CI: 0.61-0.74); Model 3: AUC, 0.72; (95% CI: 0.66-077); Model 4: AUC, 0.84, (95 % CI: 0.79-0.89). One-year GL (AUC, 0.87; Model 4) and 3-year mortality (AUC, 0.84; Model 4) models performed similarly. A Big Data approach significantly adds efficacy to GL and mortality prediction models and is EHR deployable to optimize outcomes.

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.

BACKGROUND: Clinical review of a Prescription Drug Monitoring Program (PDMP) is considered a valuable tool for opioid prescribing risk mitigation; however, PDMP utilization is often low, even in states with mandatory registration and use policies. OBJECTIVE: 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 one 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 number of monthly report requests. We compared means between pre and post intervention using a paired t-test and plotted the monthly average reports over time to assess trend of mean reports over time. Generalized linear mixed model (GLMM) 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 based on adoption status of PDMP. RESULTS: The monthly mean of reports by combined prescribers and delegates significantly increased following the AD intervention (mean 28.1 pre vs. 53.0 post; p

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.

Aims Healthcare organizations are increasingly using technology to assist in diabetes management based on telemedicine’s proven ability to improve glycemic regulation, decrease cost, and overcome barriers to effective healthcare. Nevertheless, it remains unclear how telemedicine intersects with primary care. We aim to measure the impact of a remote monitoring program for diabetes on primary care delivery through analysis of primary care office visit frequency. Methods Patients eligible to participate in our institution’s remote diabetes monitoring program were identified and classified as enrolled or not enrolled (i.e. “usual care”). The number of scheduled and completed primary care office visits in the 12 months prior to and after the index date were measured for both groups. The index date was the enrollment date or, for the patients who received usual care, the next available enrollment session after eligibility screen. Two-sample t-tests were used to examine the change in frequency of office visits prior to and after enrollment for participants, as well as the difference in visit frequency between enrolled patients versus patients receiving usual care. Results There was no statistical difference in the number of scheduled or completed primary care clinic visits before or after enrollment in telehealth. Furthermore, there was no difference in the number of scheduled or completed primary care visits between patients enrolled in telehealth versus those receiving usual care. Conclusion Participation in telehealth has been shown to be associated with significant HbA1c reductions in prior work, yet our data suggest that remote monitoring is not associated with a change in primary care office visit frequency. This suggests that telehealth may improve diabetes management independently of primary care visits.

Background As hepatitis C virus birth cohort (1945-1965) screening in primary care improves, testing patterns in response to persistently abnormal liver tests are less well known. Methods This retrospective cohort study of a patient-centered medical home between 2007 and 2016 evaluates the association of abnormal liver chemistries and other clinical and demographic factors with hepatitis C antibody (HCV Ab) testing in patients with persistently abnormal liver tests. Patients with at least 2 consecutive abnormal liver tests were categorized by the clinical pattern of liver chemistry abnormality, including cholestatic, hepatocellular, and mixed patterns. The primary outcomes were: 1) completed HCV Ab tests; and 2) positive HCV Ab results for those patients tested. Results Of 4512 patients with consecutive abnormal liver tests, only 730 (16%) underwent HCV Ab testing within 1 year of the second abnormality; 81/730 (11%) had HCV Ab detected. A logistic regression model revealed that mixed (odds ratio [OR] 2.20; 95% confidence interval [CI], 1.72-2.82) and hepatocellular (OR 1.43; 95% CI, 1.15-1.79) patterns of liver test abnormality, female sex, and alcohol and tobacco abuse were associated with higher odds of HCV Ab testing. Hepatocellular (OR 7.51; 95% CI, 2.18-25.94) and mixed patterns (OR 5.88; 95% CI, 1.64-21.15) of liver test abnormalities, male sex, Medicaid enrollment, and drug and tobacco abuse had higher odds of positive HCV Ab results. Conclusions There is opportunity to improve hepatitis C diagnostic testing in patients with consecutively elevated liver tests, and hepatocellular and mixed patterns of abnormality should prompt primary care providers to action.

As the prevalence of obesity increases, the prevalence of associated comorbid diseases, obesity-related mortality rates and healthcare costs rise concordantly. Two main factors that hinder efforts to treat obesity include a lack of recognition by patients and documentation by physicians. This study evaluates the relationship between patient perception of obese weight and physician documentation of obesity. This quality improvement observational study surveyed patients of an academic internal medicine clinic on their perception of obesity. Responses were compared to longitudinal physician documentation of obesity and body mass index (BMI). A total of 59.9% of patients with obesity perceived their weight as obese. While 33.7% of patients with a BMI of 30 to 34.9 kg/m2 perceived themselves as having obesity, 71.4% of patients with a BMI of 45 to 49.9 kg/m2 perceived themselves as having obesity. A total of 42.4% of patients with obesity had physician documentation of obesity in the last year. While 25% of patients with a BMI of 30 to 34.9 kg/m2 had physician documentation of obesity, 85.7% of patients with a BMI of 45 to 49.9 kg/m2 had physician documentation of obesity. For patients with a BMI ≥50 kg/m2 , 52.9% perceived their weight to be obese and 76.5% had physician documentation of obesity in the last year. Both patient perception and physician documentation of obesity were significantly less than the prevalence of obesity. Patient perception of obesity and provider documentation of obesity increased as BMI increased until a BMI ≥50 kg/m2 . Both patients and providers must improve recognition of this disease.

Background One in 3 US adults has high blood pressure, or hypertension. As prior projections suggest hypertension is the costliest of all cardiovascular diseases, it is important to define the current state of healthcare expenditures related to hypertension. Methods and Results We used a nationally representative database, the Medical Expenditure Panel Survey, to calculate the estimated annual healthcare expenditure for patients with hypertension and to measure trends in expenditure longitudinally over a 12‐year period. A 2‐part model was used to estimate adjusted incremental expenditures for individuals with hypertension versus those without hypertension. Sex, race/ethnicity, education, insurance status, census region, income, marital status, Charlson Comorbidity Index, and year category were included as covariates. The 2003–2014 pooled data include a total sample of 224 920 adults, of whom 36.9% had hypertension. Unadjusted mean annual medical expenditure attributable to patients with hypertension was $9089. Relative to individuals without hypertension, individuals with hypertension had $1920 higher annual adjusted incremental expenditure, 2.5 times the inpatient cost, almost double the outpatient cost, and nearly triple the prescription medication expenditure. Based on the prevalence of hypertension in the United States, the estimated adjusted annual incremental cost is $131 billion per year higher for the hypertensive adult population compared with the nonhypertensive population. Conclusions Individuals with hypertension are estimated to face nearly $2000 higher annual healthcare expenditure compared with their nonhypertensive peers. This trend has been relatively stable over 12 years. Healthcare costs associated with hypertension account for about $131 billion. This warrants intense effort toward hypertension prevention and management.

Primary care access (PCA) for the homeless can prove challenging, especially during periods of economic distress. In the United States, the most recent recession may have presented additional barriers to accessing care. Limited safety-net resources traditionally used by the homeless may have also been used by the non-homeless, resulting in delays in seeking treatment for the homeless. Using hospitalizations for ambulatory care sensitivity (ACS) conditions as a proxy measure for PCA, this study investigated the recession's impact on PCA for the homeless and non-homeless in four states. The State Inpatient Databases were used to identify ACS admissions. Findings from this study indicate the recession was a barrier to PCA for homeless people who were uninsured. Ensuring that economically-disadvantaged populations have the ability to obtain insurance coverage is crucial to facilitating PCA. With targeted outreach efforts, the Affordable Care Act provides an opportunity for expanding coverage to the homeless.

Low tacrolimus concentrations have been associated with higher risk of acute rejection, particularly within African American (AA) kidney transplant recipients; little is known about intrapatient tacrolimus variabilities impact on racial disparities.Ten year, single-center, longitudinal cohort study of kidney recipients. Intrapatient tacrolimus variability was assessed using the coefficient of variation (CV) measured between 1 month posttransplant and the clinical event, with a comparable period assessed in those without events. Pediatrics, nontacrolimus/mycophenolate regimens, and nonrenal transplants were excluded. Multivariable Cox regression models were used to analyze data.One thousand four hundred eleven recipients were included (54.4% AA) with 39 521 concentrations used to assess intrapatient tacrolimus CV. Overall, intrapatient tacrolimus CV was higher in AAs versus non-AAs (39.9 ± 19.8 % vs 34.8 ± 15.8% P0.001). Tacrolimus variability was a significant risk factor for deleterious clinical outcomes. A 10% increase in tacrolimus CV augmented the risk of acute rejection by 20% (adjusted hazard ratio, 1.20, 1.13-1.28; P0.001) and the risk of graft loss by 30% (adjusted hazard ratio, 1.30, 1.23-1.37; P0.001), with significant effect modification by race for acute rejection, but not graft loss. High tacrolimus variability (CV40%) was a significant explanatory variable for disparities in AAs; the crude relative risk of acute rejection in AAs was reduced by 46% when including tacrolimus variability in modeling and reduced by 40% for graft loss.These data demonstrate that intrapatient tacrolimus variability is strongly associated with acute rejection in AAs and graft loss in all patients. Tacrolimus variability is a significant explanatory variable for disparities in AA recipients.

Primary care clinicians encounter abnormal liver function tests (LFTs) frequently. This study assesses the prevalence of abnormal LFTs and patient follow-up patterns in response.This is a retrospective study from 2007-2016 of adult patients with abnormal LFTs seen in an internal medicine clinic. The proportion of patients with follow-up testing and the time (in days) to repeat LFTs were the primary outcomes measured. Results were evaluated before and after the implementation of the institution's electronic health record (EHR).This study identified a period prevalence for abnormal LFTs of 39%. Of these, 9,545 unique patients met inclusion criteria, with 8,415 patients (88.2%) possessing follow-up LFTs and no significant difference in the proportion of patients receiving follow-up by degree of initial abnormality. Median time to follow-up in mild abnormalities (1-2 times normal) was 138 days, compared to 21 days for severe abnormalities (4 times normal, P0.0001). Reduced time to repeat testing across all spectrums of abnormality was observed following EHR implementation, but proportions of missing follow-up did not improve. A multivariable logistic regression model identified younger age, poverty, living over 50 miles from clinic, recent cohort entry and a lower magnitude of abnormality as predictors for missing repeat LFT testing (area under the curve = 0.838 [95% CI: 0.827-0.849]).Abnormal LFTs were detected in 39% of all patients seen. The degree of LFT abnormality did not influence rates of follow-up testing, but does appear to play a role in the timing of repeat testing, when obtained. Follow-up rates did not improve with EHR implementation.

Background Adults aged 65 years and older account for more than 33% of annual visits to internal medicine (IM) generalists and specialists. Geriatrics experiences are not standardized for IM residents. Data are lacking on IM residents' continuity experiences with older adults and competencies relevant to their care. Objective To explore patient demographics and the prevalence of common geriatric conditions in IM residents' continuity clinics. Methods We collected data on age and sex for all IM residents' active clinic patients during 2011–2012. Academic site continuity panels for 351 IM residents were drawn from 4 academic medical center sites. Common geriatric conditions, defined by Assessing Care of Vulnerable Elders measures and the American Geriatrics Society IM geriatrics competencies, were identified through International Classification of Disease, ninth edition, coded electronic problem lists for residents' patients aged 65 years and older and cross-checked by audit of 20% of patients' charts across 1 year. Results Patient panels for 351 IM residents (of a possible 411, 85%) were reviewed. Older adults made up 21% of patients in IM residents' panels (range, 14%–28%); patients ≥ 75 (8%) or 85 (2%) years old were relatively rare. Concordance between electronic problem lists and chart audit was poor for most core geriatric conditions. On chart audit, active management of core geriatric conditions was variable: for example, memory loss (10%–25%), falls/gait abnormality (26%–42%), and osteoporosis (11%–35%). Conclusions The IM residents' exposure to core geriatric conditions and management of older adults was variable across 4 academic medical center sites and often lower than anticipated in community practice.

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.

Objectives: Patients with coexisting mental health disorder and chronic disease are more at risk for poor outcomes, including increased acute care utilization. This study was performed to assess the association of mental health disorders on acute care utilization (emergency department [ED] use, hospitalization, and rehospitalization within 30 days) using disease clustering. Methods: A retrospective cohort analysis was performed on 10 408 patients. Adult patients >18 years of age were included in the study if they were seen at least twice in University Internal Medicine primary care clinic at the Medical University of South Carolina from October 10, 2010 through September 30, 2013. The main outcome measure was a count of acute care use (hospital or ED). A linear regression model was used to fit a predictive model for ED and hospital utilization, and agglomerative hierarchical clustering was used to identify patients with similar comorbidities. Results: Covariates associated with increased risk of ED and hospital utilization include non-white race (rate ratio [RR] = 1.35, P < .0001), resident physician (RR = 1.30, P < .0001), and public insurance (RR = 1.56, P < .0001). Patients within the multiple chronic conditions (MCC), chronic obstructive pulmonary disease (COPD)/asthma, or renal disease clusters had 1.80 ( P < .0001), 1.50 ( P < .0001), and 2.57 ( P < .0001) times, respectively, the amount of predicted utilization compared with healthy patients, whereas patients with a mental health diagnosis had 1.41 ( P < .0001) times the predicted utilization. There was a significant association with increased utilization in patients with coexisting mental health disorder and chronic disease within the COPD/asthma (RR = 1.20, P = .0038), renal disease (RR = 1.27, P < .0001), and MCC (RR = 1.34, P < .0001) clusters. Conclusions: Patients with co-occurring chronic medical conditions and mental health disorders have higher rates of acute care utilization compared with patients with chronic medical conditions alone. Improving access to mental health care at the primary care clinic may have a positive impact on utilization.

BACKGROUND: Studies have shown that approximately one third of community-dwelling people aged 65 years and older will experience a fall each year. Many studies indicate that use of multiple medications may put patients at an increased risk of falling, but few studies have been conducted to correlate the number of medications with the risk of falls. OBJECTIVE: To determine the medications most frequently used in patients aged 65 years or older who have experienced a fall within the past year, with particular attention to type or number of medications most commonly associated with multiple falls or a fall with injury. METHODS: We conducted a chart review in an outpatient internal medicine clinic over a 13-month period. A total of 118 patients 65 years of age or older who were taking 4 or more medications and had experienced at least 1 fall in the previous 12 months were included. Data relating to sex, age, race, diagnoses, medications, and number and type of falls were obtained during the chart review. The primary end point of the study was number and type of medications most commonly used in patients experiencing a fall. RESULTS: A total of 116 patients were examined for trends in fall risk. A logistic regression model and receiver operating characteristic curve demonstrated significant fall risk with the addition of medications, with patients experiencing a 14% increase in fall risk with the addition of each medication beyond a 4-medication regimen (OR 1.14; 95% CI 1.02 to 1.27; p = 0.027). CONCLUSIONS: The addition of medications is associated with a significant increase in risk of falls in elderly patients, regardless of drug class. Further studies are needed to assess the possible increased risk of falls with increasing number of medications.

A growing number of older adults coupled with a limited number of physicians trained in geriatrics presents a major challenge to ensuring quality medical care for this population. Innovations to incorporate geriatrics education into internal medicine residency programs are needed. To meet this need, in 2009, faculty at the Medical University of South Carolina developed Aging Q(3)-Quality Education, Quality Care, and Quality of Life. This multicomponent initiative recognizes the need for improved geriatrics educational tools and faculty development as well as systems changes to improve the knowledge and clinical performance of residents. To achieve these goals, faculty employ multiple intervention strategies, including lectures, rounds, academic detailing, visual cues, and electronic medical record prompts and decision support. The authors present examples from specific projects, based on care areas including vision screening, fall prevention, and caring for patients with dementia, all of which are based on the Assessing Care of Vulnerable Elders quality indicators. The authors describe the principles driving the design, implementation, and evaluation of the Aging Q(3) program. They present data from multiple sources that illustrate the effectiveness of the interventions to meet the knowledge, skill level, and behavior goals. The authors also address major challenges, including the maintenance of the teaching and modeling interventions over time within the context of demanding primary care and inpatient settings. This organized, evidence-based approach to quality improvement in resident education, as well as faculty leadership development, holds promise for successfully incorporating geriatrics education into internal medicine residencies.

Falls are a major problem in older adults, and physicians receive inadequate training in falls evaluation. A multicomponent program (lecture, academic detailing, and case studies) was implemented to enhance medical residents' knowledge, skills, decisions, and interventions made about falls as part of a larger project to improve assessment and care of older adults. Electronic medical record (EMR) template modifications provided cues and reminders, decision support, and documentation into the visit note. Nursing staff and the EMR prompted residents to evaluate patients with a history of falls. Knowledge and confidence were assessed using a pre- and postintervention questionnaire, and an attending physician assessed skills by direct observation of the Timed Up and Go Test (TUG). Effect on clinical actions was assessed using the EMR database. Participation in training of faculty and staff was high. Over the 3-month intervention period, an attending physician reviewed the detailing sheet outlining important points of the training with 86% of residents, and 64% demonstrated a TUG to an attending physician. Of 895 older adults seen, 15% (134) had a positive screen for falls, of whom 92% (123) had an EMR falls template completed, and 42% (56) had a TUG performed. Of the patients evaluated with the TUG, 53% (29) failed. A review of charts for patients who failed the screen or TUG revealed that the majority had special circumstances limiting their participation, even after a physical therapy evaluation. Education and system changes facilitated improvements in resident knowledge, skill, self-efficacy, and clinical action in screening, evaluating, and managing falls in older adults.

Objective: To determine whether drug samples are associated with physicians prescribing fewer generic, less costly medications. Methods: We conducted a retrospective study at a large university-affiliated internal medicine practice containing over 70 physicians. Using a pharmacy database, we identified all prescriptions written to uninsured or Medicaid patients that belonged to one of four classes of chronic medications. For the 9 months before and after the clinic closed its drug sample closet, we calculated the percentage of medications prescribed as generics and the mean cost of a 30-day supply of a prescription. Results: Of 8911 prescriptions, 1973 met inclusion criteria. For uninsured patients, the percentage of medications prescribed as generics rose from 12% to 30% after the clinic closed its drug sample closet (P = 0.004). By consecutive three month periods, the percentage of prescribed generic medications rose steadily to a maximum of 40% (P < 0.001). For Medicaid patients, there was no significant change in generic prescribing (63% generic with samples versus 65% generic without samples, P = 0.42). Two factors were associated with generic prescribing in logistic regression: the absence of drug samples (OR 4.54, 95% Cl 1.37-15.0) and the prescriber being an attending physician (OR 5.26, 95% CI 2.24-12.4). There was no statistically significant change in cost for either group. Conclusions: Physicians were three times more likely to prescribe generic medications to uninsured patients after drug samples were removed from the office. Drug samples may paradoxically lead to higher costs if physicians with access to samples prescribe more brand-name only drugs.

The synthesis of basic and clinical science knowledge during the clerkship years has failed to meet educational expectations.We hypothesized that a small-group course emphasizing the basic science underpinnings of disease, Foundations of Clinical Medicine (FCM), could be integrated into third year clerkships and would not negatively impact the United States Medical Licensure Examination (USMLE) step 2 scores.In 2001-2002, all third year students met weekly in groups of 8-12 clustered within clerkships to discuss the clinical and basic science aspects of prescribed, discipline-specific cases.Students completing USMLE step 2 between 1999 and 2004 (n = 743).Course evaluations were compared with the overall institutional average. Bivariate analyses compared the mean USMLE steps 1 and 2 scores across pre- and post-FCM student cohorts. We used multiple linear regression to assess the association between USMLE step 2 scores and FCM cohort controlling for potential confounders.Students' average course evaluation score rose from 66 to 77 (2001-2004) compared to an institutional average of 73. The unadjusted mean USMLE step 1 score was higher for the post-FCM cohort (212.9 vs 207.5, respectively, p.001) and associated with step 2 scores (estimated coefficient = 0.70, p.001). Post-FCM cohort (2002-2004; n = 361) mean step 2 scores topped pre-FCM (1999-2001; n = 382) scores (215.9 vs 207.7, respectively, p.001). FCM cohort remained a significant predictor of higher step 2 scores after adjustment for USMLE step 1 and demographic characteristics (estimated coefficient = 4.3, p = .002).A curriculum integrating clinical and basic sciences during third year clerkships is feasible and associated with improvement in standardized testing.