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Objective Using a physician‐directed, patient “opt‐out” approach to prescriptive smoking cessation in the emergency department (ED) setting, we set out to describe patient actions as they related to smoking cessation behaviors. Methods A convenience sample of smokers at 2 Pennsylvania hospital EDs who met inclusion/exclusion criteria were approached to participate in a brief intervention known as screening, treatment initiation, and referral (STIR) counseling that included phone follow‐up. Demographic information, current smoking status, and specific physician prescription and follow‐up recommendations were collected. Approximately 3 months later, patients were contacted to determine current smoking status and actions taken since their ED visit. Results One hundred six patients were approached and 7 (6.6%) opted out of the intervention. Patients who did not opt out were evaluated for appropriate use of smoking cessation‐related medications; 35 (35.4%) opted out of the prescription(s) and 6 (6.1%) were not indicated. Twenty‐one (21.2%) patients opted out of ambulatory referral follow‐ups with primary care and/or tobacco treatment program; one (1.0%) was not indicated for referral. Nineteen (32.8%) patients who received prescription(s) for smoking cessation‐related medications initially also followed the prescription(s). Seventeen (22.1%) patients participated in referral follow‐up. Conclusion In this small ED pilot, using the STIR concepts in an opt‐out method, few smokers opted out of the smoking cessation intervention. About one‐third of the patients declined prescriptions for smoking cessation‐related medications and less than one‐quarter declined ambulatory referrals for follow‐up. These findings support a willingness of patients to participate in STIR and the benefits of intervention in this setting.

Introduction Osteoarthritis (OA) is a complex disease, and prior studies have documented the health and economic burdens of patients with OA compared to those without OA. Our goal was to use two strategies to further stratify OA patients based on both pain and treatment intensity to examine healthcare utilization and costs using electronic records from 2001 to 2018 at a large integrated health system. Methods Adult patients with ≥1 pain numerical rating scale (NRS) and diagnosis of OA were included. Pain episodes of ≥90 days were defined as mild (0–3), moderate (4–6), or severe (7–10) based on initial NRS. Patients were initially classified as mild and moved to moderate-severe OA if any of eight treatment-based criteria were met. Outpatient visits (OP), emergency department visits (ED), inpatient days, and healthcare costs (both all-cause and OA-specific) were compared among pain levels and OA severity levels as frequencies and per-member-per-year rates, using generalized linear regression models adjusting for age, sex, and body mass index, with contrasts of p < 0.05 considered significant. Results We identified 127,656 patients, 92,576 with pain scores. Moderate and severe pain were associated with significantly higher rates of OA-related utilization and costs, and all-cause ED visits and pharmacy costs. Moderate-severe OA patients had significantly higher OA-related utilization and costs, and all-cause OP, ED and pharmacy costs. Conclusions Pain and treatment intensity were both strongly associated with OA-related utilization but not consistently with all-cause utilization. Our results provide promising evidence of better criteria and approaches for predicting disease burden and costs in the future. Supplementary Information The online version contains supplementary material available at 10.1007/s40744-022-00448-7.

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Introduction: A strong relationship exists between the Time in Therapeutic Range (TTR), bleeding and thromboembolic events. The TTR percentage can be calculated by the following three methods. The Rosendaal method assumes a linear relationship between two INR values, the Cross Section method uses INR values that are within a specified range and at a specific point in time, and the Fraction of INR Results method measures the number of INRs in a specified range over the total number of INRs. Objectives: Compare the TTR between Point of Care (POC) and Tele-Management (TELE) Non-Valvular Atrial Fibrillation (NVAF) patients calculated by the Rosendaal, Cross Section, and Fraction of INR Results methods. Methods: Data was collected retrospectively during the 2014 calendar year for 100 randomly selected patients ≥ 18 years, received warfarin without interruption, and were monitored by the Penn State Hershey Medical Center Anticoagulation Clinic. INR lab values were obtained 14 days after initiating warfarin therapy and the interval between 2 consecutive INR lab values was ≤ 56 days. All patients in this study had a target INR range of (2.0-3.0). There was a total number of 1,889 INR lab values collected for the POC (n=826) and TELE (n=1,063) cohort groups respectively. The mean TTR value was calculated for each patient. When comparing TTR between the POC and TELE cohorts, the two-sample t-test was used for both the Rosendaal and Fraction of INR Results methods and the Chi-Square test was used for the Cross Section method. Results: Illustrated in Table 1, the mean TTR for the entire study sample (n=100) was (72.4%, 70.0%, and 67.6%) for the Rosendaal, Cross Section, and Fraction of INR Results methods respectively. When comparing between the POC and TELE cohorts, the TTR was 72.8% for the POC cohort and 72.0% for the TELE cohort by the Rosendaal method (p=0.81); the TTR was 64.0% for the POC cohort and 76.0% for the TELE cohort by the Cross Section method (p=0.19); and the TTR was 68.3% for the POC cohort and 67.0% for the TELE cohort by the Fraction of INR Results method (p=0.69). Conclusion: The mean TTR percentage did not provide a consistent pattern among the different TTR calculation methods or between the POC and TELE cohort groups. The differences observed between the POC and TELE cohort groups were not statistically significant (all p > 0.05).