Faculty Bibliography

Objective/UNASSIGNED:We assessed factors related to the integration of an office-based diet quality screener: nutrition counselling, cardiometabolic risk factors and patient/physician satisfaction. Methods/UNASSIGNED:We evaluated the impact of a 10-item diet quality measure (self-rated diet quality question and a 9-item Mediterranean Diet Score (MDS)) prior to the cardiology visit on assessment of nutrition counselling, cardiometabolic risk factors and patient/provider satisfaction. Study staff trained the nine participating physicians on the purpose and use of the screener. To assess physician uptake of the diet quality screener, we reviewed all charts having a documented dietitian referral or visit and a 20% random sample of remaining participants that completed the screener at least once to determine the proportion of notes that referenced the diet quality screener and documented specific counselling based on the screener. Results/UNASSIGNED:. Almost one-fifth (18.5%) of participants rated their diet as fair or poor, and mean MDS (range 0-9) was moderate (mean 5.6±1.8 SD). Physicians referred 22 patients (2.5%) to a dietitian. Conclusion/UNASSIGNED:Integrating the screener into the electronic health record did not increase dietitian referrals, and improvements in screener scores were modest among the subset of patients completing multiple screeners. Future work could develop best practices for physicians in using diet quality screeners to allow for some degree of standardisation of nutrition referral and counselling received by the patients.

BACKGROUND:The European Medicines Agency (EMA) requires vaccine manufacturers to conduct enhanced real-time surveillance of seasonal influenza vaccination. The EMA has specified a list of adverse events of interest to be monitored. The EMA sets out 3 different ways to conduct such surveillance: (1) active surveillance, (2) enhanced passive surveillance, or (3) electronic health record data mining (EHR-DM). English general practice (GP) is a suitable setting to implement enhanced passive surveillance and EHR-DM. OBJECTIVE:This study aimed to test the feasibility of conducting enhanced passive surveillance in GP using the yellow card scheme (adverse events of interest reporting cards) to determine if it has any advantages over EHR-DM alone. METHODS:A total of 9 GPs in England participated, of which 3 tested the feasibility of enhanced passive surveillance and the other 6 EHR-DM alone. The 3 that tested EPS provided patients with yellow (adverse events) cards for patients to report any adverse events. Data were extracted from all 9 GPs' EHRs between weeks 35 and 49 (08/24/2015 to 12/06/2015), the main period of influenza vaccination. We conducted weekly analysis and end-of-study analyses. RESULTS:Our GPs were largely distributed across England with a registered population of 81,040. In the week 49 report, 15,863/81,040 people (19.57% of the registered practice population) were vaccinated. In the EPS practices, staff managed to hand out the cards to 61.25% (4150/6776) of the vaccinees, and of these cards, 1.98% (82/4150) were returned to the GP offices. Adverse events of interests were reported by 113 /7223 people (1.56%) in the enhanced passive surveillance practices, compared with 322/8640 people (3.73%) in the EHR-DM practices. CONCLUSIONS:Overall, we demonstrated that GPs EHR-DM was an appropriate method of enhanced surveillance. However, the use of yellow cards, in enhanced passive surveillance practices, did not enhance the collection of adverse events of interests as demonstrated in this study. Their return rate was poor, data entry from them was not straightforward, and there were issues with data reconciliation. We concluded that customized cards prespecifying the EMA's adverse events of interests, combined with EHR-DM, were needed to maximize data collection. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)/UNASSIGNED:RR2-10.1136/bmjopen-2016-015469.

Early recognition, identification and treatment of children with attention deficit hyperactivity disorder (ADHD) can reduce detrimental outcomes and redirect their developmental trajectory. We aimed to describe variations in age of ADHD diagnosis and stimulant prescribing among general practitioner practices in a nationwide network and identify child, parental, household and general practice factors that might account for these variations. Cross-sectional study of children aged under 19 years registered within a general practice in the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) network in 2016, RCGP RSC has a household key allowing parent and child details to be linked. Data from 158 general practices and 353 774 children under 19 were included. The mean age of first ADHD diagnosis was 10.5 years (95% CI 10.1 to 10.9, median 10, IQR 9.0-11.9) and the mean percentage of children with ADHD prescribed stimulant medications among RCGP RSC practices was 41.2% (95% CI 38.7 to 43.6). There was wide inter-practice variation in the prevalence of diagnosis of ADHD, the age of diagnosis and stimulant prescribing. ADHD diagnosis is more likely to be made later in households with a greater number of children and with a larger age difference between adults and children. Stimulant prescribing for children with ADHD was higher in less deprived practices. Older parents and families with more children fail to recognise ADHD and may need more support. Practices in areas of higher socio-economic status are associated with greater prescribing of stimulants for children with ADHD.

BACKGROUND:Reducing costs while increasing or maintaining quality is crucial to delivering high value care. OBJECTIVE:To assess the impact of a hospital value-based management programme on cost and quality. DESIGN/METHODS:Time series analysis of non-psychiatric, non-rehabilitation, non-newborn patients discharged between 1 September 2011 and 31 December 2017 from a US urban, academic medical centre. INTERVENTION/METHODS:NYU Langone Health instituted an institution-wide programme in April 2014 to increase value of healthcare, defined as health outcomes achieved per dollar spent. Key features included joint clinical and operational leadership; granular and transparent cost accounting; dedicated project support staff; information technology support; and a departmental shared savings programme. MEASUREMENTS/METHODS:Change in variable direct costs; secondary outcomes included changes in length of stay, readmission and in-hospital mortality. RESULTS:The programme chartered 74 projects targeting opportunities in supply chain management (eg, surgical trays), operational efficiency (eg, discharge optimisation), care of outlier patients (eg, those at end of life) and resource utilisation (eg, blood management). The study cohort included 160 434 hospitalisations. Adjusted variable costs decreased 7.7% over the study period. Admissions with medical diagnosis related groups (DRG) declined an average 0.20% per month relative to baseline. Admissions with surgical DRGs had an early increase in costs of 2.7% followed by 0.37% decrease in costs per month. Mean expense per hospitalisation improved from 13% above median for teaching hospitals to 2% above median. Length of stay decreased by 0.25% per month relative to prior trends (95% CI -0.34 to 0.17): approximately half a day by the end of the study period. There were no significant changes in 30-day same-hospital readmission or in-hospital mortality. Estimated institutional savings after intervention costs were approximately $53.9 million. LIMITATIONS/CONCLUSIONS:Observational analysis. CONCLUSION/CONCLUSIONS:A systematic programme to increase healthcare value by lowering the cost of care without compromising quality is achievable and sustainable over several years.

Background: Clinical decision support (CDS) tools which incorporate clinical prediction rules (CPRs) have the potential to successfully deliver accurate information and guide decision-making at the point of care. Our previously validated integrated clinical prediction rule (iCPR) was designed to guide evidence-based treatment within an electronic health record for streptococcal pharyngitis and pneumonia based on chief complaints of sore throat, cough or upper respiratory infection. In initial testing at a single site, it resulted in high provider tool adoption (58%) and decreased antibiotic prescribing rates (35%) for acute respiratory infections. Our objective for this study was to assess the impact of this tool when adapted and implemented in diverse primary care settings.
Method(s): This was a randomized controlled trial including 33 primary care practices at two large academic health systems in Wisconsin and Utah. Between October 2015 and June 2018 providers in the intervention group were prompted to complete either Centor Score or Heckerling Rule for Pneumonia based onthe chief complaint of the patient encounter. EHR data on provider and patient demographics, tool use rates, and antibiotic order rates from 541 providers and 100,573 monitored patient encounters were collected for analysis. Risk ratios, CIs, and P values are calculated from a generalized estimating equation log-binomial model adjusting for clustering of orders or visits by provider and using robust standard error estimators.
Result(s): The tool was triggered 42,126 times among 214 intervention providers and was completed in 6.9% of eligible visits. The intervention and control groups prescribed antibiotics in 35% and 36% of visits respectively and were not significantly different. There were no differences in rates for rapid streptococcal test or chest X-ray orders between groups (Strep: relative risk, 1.0; P=.11; Pneumonia: relative risk, 1.8; P=.64).
Conclusion(s): In diverse primary care settings, the tool was not effective at reducing unnecessary antibiotic prescription and diagnostic testing. This outcome was possibly driven by low overall use of CDS tools highlighting the growing impact of " alert fatigue" and the need for new approaches to enhance provider engagement with CDS tools. New strategies for reducing the persistently high rates of inappropriate antibiotic prescribing for acute respiratory infections are needed. Novel approaches in future studies are necessary for reducing barriers to CDS tools in order to increase use and engagement

Statement of Problem Or Question (One Sentence): Underutilization of clinical prediction rules and poor uptake of provider-oriented clinical decision support (CDS) has contributed to overuse of antibiotics for sore throat. Objectives of Program/Intervention (No More Than Three Objectives): 1. Adapt CDS for registered nurses (RNs) to evaluate and treat patients with sore throat 2. Demonstrate the feasibility of RN visits using CDS to evaluate and treat patients with sore throat Description of Program/Intervention, Including Organizational Context (E.G. Inpatient Vs. Outpatient, Practice or Community Characteristics): We performed a 12-week pilot study to evaluate the feasibility of RN visits using an integrated clinical prediction rule (iCPR) tool to determine patient risk for strep throat and provide appropriate treatment at a family medicine clinic in a Midwest academic healthcare system. iCPR, originally developed for use by primary care physicians (PCPS), includes a risk calculator using Centor strep throat criteria and ordersets based on patient's risk for strep throat: education for low-risk, testing for intermediate-risk, and testing or antibiotics for high-risk. To adapt the process for RN visits, we developed triage protocols so appropriate patients received nurse visits, very low risk received education and more complex patients received provider visits. No major changes were made to the risk calculator or ordersets. Four RNs, with 2-24 years of experience, received a 10-minute online training session on sore throat evaluation followed by a 45-minute in-person training on physical examination and iCPR use. RNs triaged patients by phone and conducted RN visits using iCPR and following orderset recommendations. RNs could transition to a PCP visit if they were uncomfortable evaluating the patient. Measures of Success (DISCUSS QUALITATIVE AND/OR QUANTITATIVE METRICS WHICH WILL BE USED TO EVALUATE PROGRAM/INTERVENTION): Electronic health record data was used to determine the number of nurse visits, frequency of tool use and antibiotic and diagnostic test ordering. RNs completed a self-efficacy survey prior to training and 8-weeks after implementation. At 12 weeks, we interviewed RNs to understand barriers and facilitators to using the tool. Findings To Date (It Is Not Sufficient To State Findings Will Be Discussed): 162 triage calls for sore throat resulted in 77(48%) patients with RN-only visits, 45(28%) with provider visits, 38(23%) with no visit. Only 2 RN visits (< 3%) converted to provider visit due to patient complexity. RNs completed the risk calculator for 99% of visits and followed recommendations in all cases except for ordering antibiotics in 1 high-risk patient with a negative rapid strep. RN confidence in their ability to evaluate and treat a patient with sore throat was 85 (SD 5.8) (0 cannot do at all; 100 highly certain I can do) prior to training and 97.5 (SD 5.0) at 8-weeks. RNs felt the tool decreased provider visits and strep testing in patients. RN's also felt that the tool increased patient and RN satisfaction. Key Lessons For Dissemination (What Can Others Take Away For Implementation To Their Practice Or Community?): This pilot study demonstrates that RNs can use CDS to appropriately triage, evaluate and treat acute low-complexity sore throat patients. Implementation of an RN-driven iCPR tool shows promise to reduce inappropriate antibiotic prescribing and represents a potential model for expanding RN practice using CDS

Background: Discharge to skilled nursing facilities (SNF) is common in patients with heart failure (HF). The goal of a SNF stay is to improve functional status to allow patients to return home safely. However, the second transition from SNF to home may also be risky. Here, we examine the association between receipt of home health care (HHC) and readmission risk among patients discharged from SNF to home following HF hospitalization.
Method(s): We examined all Medicare fee-for-service beneficiaries 65 and older admitted 2012-2015 with a HF diagnosis discharged to SNF then subsequently discharged home. The primary outcome was unplanned read-mission within 30 days of SNF to home discharge, using CMS's HF read-mission methodology. We plotted time to readmission with Kaplan-Meier curves and compared these groups with a log-rank test. Then, we compared time to readmission using an adjusted Cox model; this model included a frailty term to account for correlation of patient outcome by SNF.
Result(s): There were 67,585 HF hospitalizations discharged to SNF and subsequently discharged home; 13,257 (19.6%) were discharged with HHC, 54,328 (80.4%) without. Patients discharged home from SNF with HHC had lower 30-day readmission rates than patients discharged without HHC (22.8% vs 24.5%, p< 0.0001). Kaplan-Meier curves demonstrated that patients discharged home from SNF with HHC have a longer unadjusted time to readmission. Of those readmitted within 30 days, median time to readmission for those discharged home from SNF with HHC was 11 days and 9 days for those discharged home without HHC (p< 0.0001). After risk-adjustment, patients discharged home with HHC still had a lower hazard of 30-day readmission.
Conclusion(s): Patients who received HHC were less likely to be readmitted within 30 days compared to those discharged home without HHC. This is unexpected as patients discharged with HHC likely have more functional impairments and therefore at higher readmission risk. Since patients requiring a SNF stay after hospital discharge may have additional needs, they may be especially likely to benefit from restorative therapy through HHC; however only about 20% received such services

OBJECTIVE:Discharge to skilled nursing facilities (SNFs) is common in patients with heart failure (HF). It is unknown whether the transition from SNF to home is risky for these patients. Our objective was to study outcomes for the 30 days after discharge from SNF to home among Medicare patients hospitalized with HF who had subsequent SNF stays of 30 days or less. DESIGN/METHODS:Retrospective cohort study. SETTING AND PARTICIPANTS/METHODS:All Medicare fee-for-service beneficiaries 65 and older admitted during 2012-2015 with a HF diagnosis discharged to SNF then subsequently discharged home. MEASURES/METHODS:Patients were followed for 30 days following SNF discharge. We categorized patients by SNF length of stay: 1 to 6 days, 7 to 13 days, and 14 to 30 days. For each group, we modeled time to a composite outcome of unplanned readmission or death after SNF discharge. Our model examined 0-2 days and 3-30 days post-SNF discharge. RESULTS:Our study included 67,585 HF hospitalizations discharged to SNF and subsequently discharged home. Overall, 16,333 (24.2%) SNF discharges to home were readmitted within 30 days of SNF discharge. The hazard rate of the composite outcome for each group was significantly increased on days 0 to 2 after SNF discharge compared to days 3 to 30, as reflected in their hazard rate ratios: for patients with SNF length of stay 1 to 6 days, 4.60 (4.23-5.00); SNF length of stay 7 to 13 days, 2.61 (2.45-2.78); SNF length of stay 14 to 30 days, 1.70 (1.62-1.78). CONCLUSIONS/IMPLICATIONS/CONCLUSIONS:The hazard rate of readmission after SNF discharge following HF hospitalization is highest during the first 2 days home. This risk attenuated with longer SNF length of stay. Interventions to improve postdischarge outcomes have primarily focused on hospital discharge. This evidence suggests that interventions to reduce readmissions may be more effective if they also incorporate the SNF-to-home transition.