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OBJECTIVE: Describe the screening, referral, and treatment delivery associated with an opt-out tobacco treatment program (TTP) implemented in six hospitals varying in size, rurality and patient populations. METHODS: Between March 6, 2021 and December 17, 2021, adult patients (≥ 18 years) admitted to six hospitals affiliated with the Medical University of South Carolina were screened for smoking status. The hospitals ranged in size from 82 to 715 beds. Those currently smoking were automatically referred to one of two tobacco treatment options: 1) Enhanced care (EC) where patients could receive a bedside consult by a trained tobacco treatment specialist plus an automated post-discharge follow-up call designed to connect those smoking to the South Carolina Quitline (SCQL); or 2) Basic care (BC) consisting of the post-discharge follow-up call only. An attempt was made to survey patients at 6-weeks after hospitalization to assess smoking status. RESULTS: Smoking prevalence ranged from 14 to 49% across the six hospitals; 6,000 patients were referred to the TTP.The delivery of the bedside consult varied across the hospitals with the lowest in the Charleston hospitals which had the highest caseload of referred patients per specialist. Among patients who received a consult visit during their hospitalization, 50% accepted the consult, 8% opted out, 3% claimed not to be current smokers, and 38% were unavailable at the time of the consult visit. Most of those enrolled in the TTP were long-term daily smokers.Forty-three percent of patients eligible for the automated post-discharge follow-up call answered the call, of those, 61% reported smoking in the past seven days, and of those, 34% accepted the referral to theSCQL. Among the 986 of patients surveyed at 6-weeks after hospitalization quit rates ranged from 20%-30% based on duration of reported cessation and were similar between hospitals and for patients assigned to EC versus BC intervention groups. CONCLUSION: Findings demonstrate the broad reach of an opt-out TTP. Elements of treatment delivery can be improved by addressing patient-to-staffing ratios, improving systems to prescribe stop smoking medications for patients at discharge and linking patients to stop smoking services after hospital discharge.
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Abandono do Hábito de Fumar , Humanos , South Carolina , Masculino , Feminino , Adulto , Pessoa de Meia-Idade , Abandono do Hábito de Fumar/métodos , Abandono do Hábito de Fumar/estatística & dados numéricos , Encaminhamento e Consulta/estatística & dados numéricos , IdosoRESUMO
OBJECTIVE: To describe the workflow, reach, cost, and self-reported quit rates for an opt-out tobacco treatment program (TTP) for patients seen in 43 oncology outpatient clinics. METHODS: Between May 25, 2021, and December 31, 2022, adult patients (≥18 years) visiting clinics affiliated with the Medical University of South Carolina Hollings Cancer Center were screened for smoking status. Those currently smoking were referred to a telehealth pharmacy-assisted TTP. An attempt was made to contact referred patients by phone. Patients reached were offered free smoking cessation counseling and a 2-week starter kit of nicotine replacement medication. A random sample of 420 patients enrolled in the TTP were selected to participate in a telephone survey to assess smoking status 4 to 12 months after enrollment. RESULTS: During the reference period 35,756 patients were screened and 9.3% were identified as currently smoking. Among the 3319 patients referred to the TTP at least once, 2393 (72.1%) were reached by phone, of whom 426 (12.8%) were ineligible for treatment, 458 (13.8%) opted out of treatment, and 1509 (45.5%) received treatment. More than 90% of TTP enrollees smoked daily, with an average of 13.1 cigarettes per day. Follow-up surveys were completed on 167 of 420 patients, of whom 23.4% to 33.5% reported not smoking; if all nonresponders to the survey are counted as smoking, the range of quit rates is 9.3% to 13.3%. CONCLUSION: The findings demonstrate the feasibility of reaching and delivering smoking cessation treatments to patients from a diverse set of geographically dispersed oncology clinics.
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Abandono do Hábito de Fumar , Telemedicina , Humanos , Masculino , Feminino , Pessoa de Meia-Idade , Abandono do Hábito de Fumar/métodos , Adulto , Idoso , Neoplasias/terapia , Farmacêuticos , Instituições de Assistência Ambulatorial , Dispositivos para o Abandono do Uso de TabacoRESUMO
Objective: To describe the implementation an opt-out tobacco treatment program (TTP) in 6 diverse hospitals located in different regions of South Carolina. Methods: Between March 8, 2021 and December 17, 2021, adult patients (≥ 18 years) admitted to 6 hospitals affiliated with the Medical University of South Carolina (MUSC) were screened for their cigarette status. Patients who smoked cigarettes were referred to an TTP offering a brief bedside consult and automated post-discharge follow-up calls with an opportunity to receive a referral to the South Carolina Quitline (SCQL). The hospitals included in this study ranged in size from 82 to 715 beds with diverse patient populations. Herein, we report on the results of screening and referring patients to the TTP, delivery of smoking cessation treatments, and patient smoking status assessed in a sample of patients followed 6-weeks after discharge from the hospital. Results: Smoking prevalence ranged from 14-49% across the 6 hospitals. Among eligible patients reached, 85.6% accepted the bedside consult. Only 3.4% of patients reached were deemed ineligible because they claimed not to be currently smoking cigarettes. The automated post-discharge follow-up calls were answered by 43% of patients, with about a third of those who had relapsed back to smoking accepting the offer of a referral to the SCQL. Overall, about half of the 6,000 patients referred to the TTP received some type of treatment. Self-reported smoking abstinence rates assessed 6-weeks after discharge were similar across the five acute care hospitals ranging from about 20-30%. Conclusion: The findings demonstrate the broad reach of implementing an opt-out TTP for patients in hospitals of varying size, rurality and patient populations.
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BACKGROUND: Interactive voice response (IVR) systems are computer programs that interact with people to provide a number of services from business to healthcare. The healthcare applications are particularly relevant to older adults because they are important consumers of medical services. However, research has found that older adults can experience significant difficulties with IVR and have more negative attitudes toward the technology. SUBJECTS AND METHODS: Seniors' attitudes appear to be related to their most recent experiences with IVR systems. The objective of this study was to examine attitudes toward four commercial or governmental IVR systems and how these attitudes relate to participants' ability to interact with the technology in a sample of 185 community-dwelling older (>65-year-old) adults. We also examined the effects of several demographic factors on both success and attitudes toward automated systems. RESULTS: We found a significant positive correlation between IVR success and attitudes toward IVR. However, a large subset of our sample gave high ratings despite experiencing significant difficulties with the systems. These participants tended to have lower full scale IQ. No gender differences emerged in terms of attitudes and ability to interact with IVR systems. CONCLUSIONS: Results also indicated that older adults in our sample viewed the IVR interaction as particularly demanding on attention and concentration abilities.
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Atitude Frente aos Computadores , Serviços de Saúde , Interface para o Reconhecimento da Fala , Interface Usuário-Computador , Idoso , Idoso de 80 Anos ou mais , Automação , Canadá , Feminino , Humanos , Serviços de Informação , Masculino , TelefoneRESUMO
Interactive voice response (IVR) systems are computer programs, which interact with people to provide a number of services from business to health care. We examined the ability of an IVR system to administer and score a verbal fluency task (fruits) and the digit span forward and backward in 158 community dwelling people aged between 65 and 92 years of age (full scale IQ of 68-134). Only six participants could not complete all tasks mostly due to early technical problems in the study. Participants were also administered the Wechsler Intelligence Scale fourth edition (WAIS-IV) and Wechsler Memory Scale fourth edition subtests. The IVR system correctly recognized 90% of the fruits in the verbal fluency task and 93-95% of the number sequences in the digit span. The IVR system typically underestimated the performance of participants because of voice recognition errors. In the digit span, these errors led to the erroneous discontinuation of the test: however the correlation between IVR scoring and clinical scoring was still high (93-95%). The correlation between the IVR verbal fluency and the WAIS-IV Similarities subtest was 0.31. The correlation between the IVR digit span forward and backward and the in-person administration was 0.46. We discuss how valid and useful IVR systems are for neuropsychological testing in the elderly.
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OBJECTIVES: Interactive voice response (IVR) systems are computer programs that can interact with people to provide a number of services from business to health care. However, surveys examining people's attitudes toward these systems have consistently found that people in general and older people in particular strongly dislike these systems. We wanted to determine the memory and cognitive abilities that predict successful IVR interactions for older people. METHOD: We compared the performance of 185 older adults (aged 65 and older) on normed cognitive tests (the Wechsler Adult Intelligence Scale fourth edition and the Wechsler Memory Scale fourth edition) with their performance on 4 real-life IVR systems that included fact-finding at governmental agencies and plane ticket reservation. RESULTS: The results indicated that adults aged 65 and older experience significant difficulties in interacting with IVR systems. A significant number of people (20.5%) could not complete any of the tasks. Participants who could not complete any task were older and had the lowest full-scale IQ. However, there was little difference between the age of participants who completed 1, 2, 3, or 4 tasks. Rather, auditory memory and working memory were the best overall predictors for success in IVR tasks. DISCUSSION: The impact of poorer auditory memory and working memory is compounded by programming practices that increase the demand on these abilities and create unnecessary difficulties. Successful use of IVR systems could eventually complement in person health services.
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Envelhecimento/fisiologia , Interface Usuário-Computador , Voz , Idoso , Idoso de 80 Anos ou mais , Percepção Auditiva , Feminino , Humanos , Masculino , Memória de Curto Prazo/fisiologia , Testes Neuropsicológicos , Valor Preditivo dos Testes , Inquéritos e Questionários , Telefone , Escalas de WechslerRESUMO
BACKGROUND: Interactive voice response (IVR) systems use computer-based voice recognition and software algorithms to conduct human/computer interactions. In recent years, there has been a proliferation of IVR applications in business and healthcare. The available evidence suggests that older people have negative attitudes towards IVR and experience significant difficulties using these systems. OBJECTIVE: The goal of this project was to identify areas of difficulties in IVR use by older people and propose strategies for improvement. MATERIALS AND METHODS: During two focus groups, we examined older people's perceptions of IVR systems and the most common difficulties experienced by seniors in interacting with these systems. We also recorded their suggestions for improvement of IVR. RESULTS: Frequency and chi square analyses were performed on the focus groups data. Some of the difficulties reported by participants in this study were congruent with previous findings, but we also uncovered some additional problems, such as frustration for not being able to reach an operator, being asked to wait too long on hold, being unable to recover from mistakes, and an absence of shortcuts in the systems. In addition, significant number of participants indicated that they prefer a system that adjusts to them automatically as opposed to a system that allows for adjustment. CONCLUSION: Generally, our findings suggest that the poor acceptability of IVR systems by older people could be improved by designing IVR algorithms that detect difficulties during an ongoing IVR exchange and direct people to different algorithms adapted for each person.