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Individuals with mental illness have a high incidence of comorbid substance use, with one of the most prevalent being alcohol use disorder (AUD). Naltrexone, FDA-approved for AUD, decreases reward associated with alcohol-related social cues. This study aimed to determine if a pharmacist-driven screening tool would increase the use of extended-release naltrexone (XR-NTX) in patients with AUD and a comorbid psychiatric condition. Pharmacists screened and recommended XR-NTX for adults admitted to the inpatient psychiatric unit, who had a DSM-5 diagnosis of AUD, a negative urine drug screen for opioids, and were hospitalized for at least 1 day. Endpoints evaluated included the number of XR-NTX doses administered during the screening period to the prescreening period, 30-day readmission rates, recommendation acceptance rates, and reasons for not administering XR-NTX. Pharmacists identified 66 of 641 screened patients who met the inclusion criteria and were candidates for XR-NTX. Compared to the preintervention period, more patients received XR-NTX for AUD (2 vs. 8). Readmission rates were similar between those with AUD who received XR-NTX and those who did not. Pharmacist-driven screening for AUD led to greater administration of XR-NTX when compared to the same 4-month period the year prior to initiating the study.
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PURPOSE: To identify prevalence of and risk factors for loss to follow up (LTFU) among a national cohort of patients with primary open-angle glaucoma (POAG). METHODS: This retrospective cohort study analyzed data from the IRIS® Registry (Intelligent Research in Sight) database from 2014 through 2019 to assess LTFU among adult patients with POAG. POAG patients with at least one clinical encounter in 2014 were included. LTFU was defined as exceeding one year without a clinical encounter during the study period. RESULTS: Among 553,663 glaucoma patients, 277,019 (50%) became LTFU, of whom 184,548 (67%) never returned to care and 92,471 (33%) re-established follow-up after a lapse. Risk of LTFU was greatest among those younger than 60 years (RR = 1.38; 95% CI: 1.36-1.39) or older than 80 years (RR = 1.39; 95% CI: 1.38-1.40) compared to those in their 60s. Compared to White race, risk for LTFU was highest among Native Hawaiian/Pacific Islander (RR = 1.24; 95% CI: 1.17-1.31), Hispanic ethnicity (RR = 1.19; 95% CI: 1.18-1.20), and Black race (RR = 1.10; 95% CI: 1.09-1.11). Medicare insurance was associated with lower risk of LTFU (RR = 0.79; 95% CI: 0.78-0.79), whereas unknown/missing/no insurance was associated with greater risk (RR = 1.33; 95% CI: 1.32-1.34), compared to private insurance. Compared to mild-stage POAG, risk of LTFU was higher for moderate-stage (RR = 1.10; 95% CI: 1.08-1.13) and severe-stage disease (RR = 1.35; 95% CI: 1.32-1.38). CONCLUSION: We found a 50% prevalence of LTFU among POAG patients in the IRIS Registry over a 6-year study period, with greater risk among minority groups and those with more advanced disease.
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PURPOSE: Loss to follow-up (LTFU) in primary open-angle glaucoma (POAG) can lead to undertreatment, disease progression, and irreversible vision loss. Patients who become LTFU either eventually re-establish glaucoma care after a lapse or never return to the clinic. The purpose of this study is to examine a large population of POAG patients who became LTFU to determine the proportion that return to care and to identify demographic and clinical factors associated with non-return after LTFU. DESIGN: Retrospective longitudinal cohort study PARTICIPANTS: Patients with a diagnosis of POAG with a clinical encounter in 2014 in the IRIS® Registry (Intelligent Research in Sight) METHODS: We examined follow-up patterns for 553,663 patients with POAG who had an encounter in the IRIS Registry in 2014 by following their documented clinic visits through 2019. LTFU was defined as exceeding one calendar year without an encounter. Within the LTFU group, patients were classified as returning after a lapse in care (return after LTFU) or not (non-return after LTFU). MAIN OUTCOME MEASURES: Proportion of patients with non-return after LTFU and baseline demographic and clinical characteristics associated with non-return among LTFU POAG patients. RESULTS: Among 553,663 POAG patients, 277,019 (50%) had at least one episode of LTFU over the 6-year study period. Within the LTFU group, 33% (92,471) returned to care and 67% (184,548) did not return to care. Compared to those who returned to care, LTFU patients with non-return were more likely to be older (age >80 years; RR=1.48; 95% CI: 1.47-1.50), to have unknown/missing insurance (RR=1.31; 95% CI: 1.30-1.33), and to have severe-stage POAG (RR=1.13; 95% CI: 1.11-1.15). Greater POAG severity and visual impairment were associated with non-return with a dose-dependent relationship in the adjusted model that accounted for demographic characteristics. Among those with return after LTFU, almost all returned within 2 years of last appointment (82,201; 89%) rather than 2 or more years later. CONCLUSION: Half of POAG patients in the IRIS Registry had at least one period of LTFU, and two-thirds of LTFU POAG patients did not return to care. More effort is warranted to re-engage the vulnerable POAG patients who become LTFU.
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PURPOSE: To assess the efficacy of electronic health record (EHR) messaging for re-engaging patients with ophthalmology care after a missed appointment. DESIGN: Prospective, randomized clinical trial. METHODS: The study setting was an academic ophthalmology department. The patient population comprised of return patients age 18 years or older with an appointment "no show," or missed appointment. Over 2 phases of recruitment, 362 patients with an active patient portal in the EHR were selected consecutively each business day. Patients were randomized using a web-based tool to receive a reminder to reschedule via a standard mailed letter only (control) or the mailed letter plus an electronic message through the EHR within 1 business day of the missed appointment (intervention). Reengagement with eye care was defined as attendance of a rescheduled appointment within 30 days of the no-show visit. Patient charts were reviewed for demographic and clinical data. RESULTS: The average age of recruited patients was 59.9 years, just under half of the sample was male (42.5%, 154/362), and most patients were White (56.9%, 206/362) or Black (36.2%, 131/362). Patients were most commonly recruited from the retina service (39.2%, 142/362) followed by the glaucoma service (29.3%, 106/362). Many patients in this study had previous no-show appointments, with an average no-show rate of 18.8% out of all scheduled visits across our health system. In total, 22.2% (42/189) of patients in the intervention group attended a follow-up appointment within 30 days of their no-show visit compared to 11.6% (20/173) of the control group (OR, 2.186; 95% CI, 1.225-3.898; P = .008). When including only the 74 patients in the intervention group who read the intervention message in the patient portal, 28.4% (21/74) attended a follow-up compared to 11.6% (20/173) of the control group (P = .001). CONCLUSIONS: EHR-based reminder messages sent within a business day of a missed appointment may promote re-engagement in ophthalmology care after appointment no-show.
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Agendamento de Consultas , Pacientes não Comparecentes , Oftalmologia , Portais do Paciente , Sistemas de Alerta , Humanos , Masculino , Pessoa de Meia-Idade , Feminino , Estudos Prospectivos , Oftalmologia/organização & administração , Pacientes não Comparecentes/estatística & dados numéricos , Idoso , Adulto , Cooperação do Paciente/estatística & dados numéricos , Registros Eletrônicos de SaúdeRESUMO
Purpose The aim of this study was to determine whether a patient navigator program can address patient-reported barriers to eye care and to understand patient perceptions of a patient navigator program in ophthalmology. Design This is a retrospective cohort study and cross-sectional patient survey. Subjects and Methods A cohort of patients was recruited from a single academic ophthalmology department in the Mid-Atlantic region. Patients included in the study had received referral to the patient navigator program in the first quarter of 2022. Our patient navigator program provided patients with resources to address barriers to care such as transportation and financial assistance. Outcomes of the study included indications for referral, case resolution rate, and patient satisfaction. Results In total, 130 referrals for 125 adult patients were included. The mean ± standard deviation age was 59 ± 17 years, 54 (44%) were male, 77 were white (62%), and 17 patients (14%) were uninsured. Common reasons for referral were transportation (52, 40%), insurance (34, 26%), and financial assistance (18, 14%). Among the 130 cases referred, 127 (98%) received an intervention from the patient navigator, who was able to resolve the referring issue in 90% of cases (117/130). Among 113 patients contacted for a follow-up telephone survey, 56 (50%) responded. Patients rated the program highly at a mean Likert rating of 4.87 out of 5. Moreover, 72% (31/43) of respondents stated their interactions with the patient navigator assisted them with taking care of their eyes. Conclusions A patient navigator program can address barriers to eye care by connecting patients with community resources.