Formative Exploration of the Relationship Between Waiting Times and Attendance at General Adult Psychiatry Clinics, at a Hospital in Pennine Care NHS Foundation Trust

2017 ◽  
Vol 41 (S1) ◽  
pp. S607-S607
Author(s):  
M. Gan ◽  
S. Salujha
Keyword(s):  
Waiting Times ◽  
Wait Time ◽  
Wait Times ◽  
Clinic Attendance ◽  
Outpatient Psychiatry ◽  
Adult Psychiatry ◽  
Adult Outpatient ◽  
Competing Interest ◽  
The Relationship ◽  
Patient Referrals

IntroductionAn audit was done to assess new patient wait times. As part of this project we reviewed possible relationships between wait times and clinic attendance.ObjectiveTo examine available data, for possible explanations of patients’ attendance behaviour at outpatient clinics.AimsTo identify possible correlation between length of waiting time for adult psychiatry appointments and status of attendance.MethodService Line: New patient referrals to adult outpatient psychiatry (January–December 2015)Sample size: 401.ResultsFig. 1 and Table 1 show wait times compared with clinic attendance outcome. Percentage attendance appeared to gradually fall as wait times increased; while cancellation (%) by the NHS, and DNAs (did not attend) by the patient, appeared to rise over time.ConclusionsThis review has demonstrated a possible correlation between wait time for a clinic appointment and how patients behave. The shorter a patient has to wait; it appears they are more likely to actually attend clinic. If so, this potentially has implications for discussions around possible reorganization of services, to improve engagement and outcomes, by coming up with innovative ways of reducing wait times.Disclosure of interestThe authors have not supplied their declaration of competing interest.

scholarly journals Online Ratings of Primary Care Physicians: Comparison of Gender, Training, and Specialty

2021 ◽  
Vol 8 ◽  
pp. 237437352110077
Author(s):  
Daliah Wachs ◽  
Victoria Lorah ◽  
Allison Boynton ◽  
Amanda Hertzler ◽  
Brandon Nichols ◽  
...  
Keyword(s):  
Primary Care ◽  
Primary Care Physicians ◽  
Waiting Times ◽  
Wait Time ◽  
Primary Care Providers ◽  
Wait Times ◽  
Care Providers ◽  
Female Physicians ◽  
Online Ratings ◽  
And Gender

The purpose of this study was to explore patient perceptions of primary care providers and their offices relative to their physician’s philosophy (medical degree [MD] vs doctorate in osteopathic medicine [DO]), specialty (internal medicine vs family medicine), US region, and gender (male vs female). Using the Healthgrades website, the average satisfaction rating for the physician, office parameters, and wait time were collected and analyzed for 1267 physicians. We found female doctors tended to have lower ratings in the Midwest, and staff friendliness of female physicians were rated lower in the northwest. In the northeast, male and female MDs were rated more highly than DOs. Wait times varied regionally, with northeast and northwest regions having the shortest wait times. Overall satisfaction was generally high for most physicians. Regional differences in perception of a physician based on gender or degree may have roots in local culture, including proximity to a DO school, comfort with female physicians, and expectations for waiting times.

scholarly journals An Audit of Wait Times for Service Offered by the Gynaecology Oncology Unit at the University Hospital in Jamaica: Are We Meeting the Standards?

2016 ◽  
Vol 2 (3_suppl) ◽  
pp. 74s-74s
Author(s):  
Ian Bambury ◽  
Christopher Fletcher ◽  
Carole Rattray ◽  
Matthew Taylor ◽  
Charmaine Mitchell ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Conflicts Of Interest ◽  
Waiting Times ◽  
Wait Time ◽  
International Standards ◽  
University Hospital ◽  
Wait Times ◽  
Oncology Unit ◽  
The University ◽  
Mean Time

Abstract 53 Background: The European Board and College of Obstetrics and Gynaecology recommends that time from referral of suspected or proven gynaecological cancers to consultation should be within two weeks and that initiation of treatment should occur within six weeks. It is has been shown that a delay in waiting times beyond these international standards results in significantly increased morbidity and mortality. Methods: An audit of wait times was performed for all patients who presented to the gynaecology oncology unit at the University Hospital in Jamaica for consultation between January 1, 2013 and December 31, 2013. Wait time for consultation was calculated as the date of first referral to the date of initial consultation. Wait time for treatment was calculated as time from consultation to either surgery or initiation of radiation therapy or chemotherapy. Primary site, stage, and the region from which the referrals came were abstracted from the medical record. Results: A total of 1,289 unique patients were seen at least once during the audit period; of these, 108 were new consultations and 1,219 were patients seen for follow-up. 72% were from the greater metropolitan area (Kingston & St. Andrew), while the others were from the surrounding parishes of Jamaica. Of the 108 new patients, malignancy was confirmed in 70 (65%). Case make-up included 23 cases of endometrial cancer (33%); 20 cases of cervical cancer (29%); 16 cases of ovarian cancer (23%); and 11 cases of other gynecologic cancers (vulvar, vaginal, choriocarcinoma) (15%). At presentation, there were 23 patients with stage 1 disease (33%), 16 patients with stage 2 disease (23%), 27 patients with stage 3 disease (38%); and 4 patients with stage 4 disease (6%). 39 out of 70 patients with malignancy (56%) underwent surgery; 11 (15.7%) were treated with radiation therapy; and 22 (31%) were treated with chemotherapy. Among patients with a cancer diagnosis, the mean time from referral to consultation was 2.1 weeks. Mean time from consultation to surgery was 7.6 weeks; mean time from consultation to start of radiotherapy was 16 weeks; and mean time from consultation to start of chemotherapy was 11.6 weeks. 66% of patients underwent surgery within the international standard of six weeks from referral. Only 36% initiated radiation therapy and 14% initiated chemotherapy within six weeks from referral. Conclusion: While the majority of patients met international standards for time to consultation to surgery, wait times for initiation of radiation and chemotherapy were sub-standard. This audit has provided information that will help us to assess the inadequacy of available services and could potentially inform national cancer policies in Jamaica. AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST: No COIs from the authors.

scholarly journals Waiting for Treatment for Chronic Pain – a Survey of Existing Benchmarks: Toward Establishing Evidence-Based Benchmarks for Medically Acceptable Waiting Times

2007 ◽  
Vol 12 (4) ◽  
pp. 245-248 ◽  
Author(s):  
Mary E Lynch ◽  
Fiona A Campbell ◽  
Alexander J Clark ◽  
Michael J Dunbar ◽  
David Goldstein ◽  
...  
Keyword(s):  
Systematic Review ◽  
Chronic Pain ◽  
Time Management ◽  
Task Force ◽  
International Association ◽  
Waiting Times ◽  
Wait Time ◽  
Wait Times ◽  
Pain Clinics ◽  
The World

As medical costs escalate, health care resources must be prioritized. In this context, there is an increasing need for benchmarks and best practices in wait time management. In December 2005, the Canadian Pain Society struck a Task Force to identify benchmarks for acceptable wait times for treatment of chronic pain. The task force mandate included a systematic review and survey to identify national or international wait time benchmarks for chronic pain, proposed or in use, along with a review of the evidence upon which they are based. An extensive systematic review of the literature and a survey of International Association for the Study of Pain Chapter Presidents and key informants has identified that there are no established benchmarks or guidelines for acceptable wait times for the treatment of chronic pain in use in the world. In countries with generic guidelines or wait time standards that apply to all outpatient clinics, there have been significant challenges faced by pain clinics in meeting the established targets. Important next steps are to ensure appropriate additional research and the establishment of international benchmarks or guidelines for acceptable wait times for the treatment of chronic pain. This will facilitate advocacy for improved access to appropriate care for people suffering from chronic pain around the world.

scholarly journals P.017 Results of a Pilot feasibility study to develop reduce wait times strategy in the evaluation of children with new onset epilepsy

2018 ◽  
Vol 45 (s2) ◽  
pp. S20-S20
Author(s):  
JA Mailo ◽  
M Diebold ◽  
E Mazza ◽  
P Guertjens ◽  
H Gangam ◽  
...  
Keyword(s):  
Patient Flow ◽  
Waiting Times ◽  
Wait Time ◽  
Febrile Seizures ◽  
Limiting Factors ◽  
Wait Times ◽  
Timely Access ◽  
Flow Through ◽  
Pilot Feasibility Study ◽  
New Onset

Background: The goal was to understand factors leading to prolonged wait times for neurological assessment of children with new onset seizures. A second objective was to develop an innovative approach to patient flow through and achieve a reduction in waiting times utilizing limited resources.Methods:Audit of the referrals, flow through, wait timesIdentification of bottlenecksDevelopment of triaging strategy:Suspected Febrile seizures and non-epileptic events;Suspected benign and absence epilepsies;Suspected other Focal epilepsies, generalized epilepsies, epilepsy under 2 yearsInitiation of early telephone contact and supportDevelopment of a ketogenic dietResults: Using a triaging strategy and focusing on timely access to investigations, wait times for clinic evaluations were shortened despite larger numbers of referrals (mean wait time reductions from 179 to 91 days). Limiting factors such increase in referral numbers, attrition in support staff, interfered with sustainability of reduced wait times achieved in the initial phase of the program. Conclusions: This pilot study highlights the effectiveness of an innovative triaging strategy and improvements in patient flow through in achieving the goals of reduction in wait times for clinical evaluation and timely investigations to improve care for children with new onset seizures. Insights into limitations of such strategies and factors determining sustainability are discussed.

scholarly journals Impact of procedural capacity on transcatheter aortic valve replacement wait times and outcomes: a study of regional variation in Ontario, Canada

Open Heart ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. e001241 ◽  
Author(s):  
Kayley A Henning ◽  
Mithunan Ravindran ◽  
Feng Qiu ◽  
Neil P Fam ◽  
Tej N Seth ◽  
...  
Keyword(s):  
Aortic Valve ◽  
Aortic Valve Replacement ◽  
Valve Replacement ◽  
Transcatheter Aortic Valve Replacement ◽  
Wait Time ◽  
Adverse Outcomes ◽  
Policy Implications ◽  
Wait Times ◽  
Transcatheter Aortic Valve ◽  
The Relationship

BackgroundThere has been rapid growth in the demand for transcatheter aortic valve replacement (TAVR), which has the potential to overwhelm current capacity. This imbalance between demand and capacity may lead to prolonged wait times, and subsequent adverse outcomes while patients are on the waitlist. We sought to understand the relationship between regional differences in capacity, TAVR wait times and morbidity/mortality on the waitlist.Methods and resultsWe modelled the effect of TAVR capacity, defined as the number of TAVR procedures per million residents/region, on the hazard of having a TAVR in Ontario from April 2012 to March 2017. Our primary outcome was the time from referral to a TAVR procedure or other off-list reasons on the waitlist/end of the observation period as measured in days. Clinical outcomes of interest were all-cause mortality, all-cause hospitalisations or heart failure-related hospitalisations while on the waitlist for TAVR. There was an almost fourfold difference in TAVR capacity across the 14 regions in Ontario, ranging from 31.5 to 119.5 TAVR procedures per million residents. The relationship between TAVR capacity and wait times was complex and non-linear. In general, increased capacity was associated with shorter wait times (p<0.001), reduced mortality (HR 0.94; p=0.08) and all-cause hospitalisations (p=0.009).ConclusionsThe results of the present study have important policy implications, suggesting that there is a need to improve TAVR capacity, as well as develop wait-time strategies to triage patients, in order to decrease wait times and mitigate the hazard of adverse patient outcomes while on the waitlist.

Non-Clinical Factors Associated with Variation in Cataract Surgery Waiting Times in Manitoba

2005 ◽  
Vol 24 (S1) ◽  
pp. 47-58 ◽  
Author(s):  
Carolyn De Coster
Keyword(s):  
Health Status ◽  
Cataract Surgery ◽  
Economic Status ◽  
Waiting Times ◽  
Wait Times ◽  
Clinical Factors ◽  
Factors Associated ◽  
Socio Economic Status ◽  
Region Of Residence ◽  
The Relationship

ABSTRACTCataract surgery is the highest-volume surgical procedure in Canada, with over 200,000 performed annually, mostly (85%) on persons aged 65 or older. Concerns have been raised about wait times to access this procedure. This study explores the relationship between waiting times for cataract surgery in Manitoba and a variety of characteristics, including age, sex, socio-economic status, region of residence, health status, surgeon, and surgeon's caseload. The study included 6,114 individuals who had first-eye cataract surgery between November 1, 1998, and March 31, 2000, in Winnipeg, MB. Significant predictors of variation in wait times were age, sex, having a hospitalization while waiting, and surgeon. The model explained 32.5 per cent of the variance in wait times; specific surgeon independently explained 29.5 per cent of the variance. Median waiting times varied widely by surgeon, ranging from 61 to 399 days. Differences in surgeons' expected wait times should be available to patients and referring clinicians.

scholarly journals Predicting Patient Wait Times in the Phlebotomy Unit

2020 ◽  
pp. 1-5
Author(s):  
Dilek Orbatu ◽  
Oktay Yıldırım ◽  
Eminullah Yaşar ◽  
Ali Rıza Şişman ◽  
Süleyman Sevinç
Keyword(s):  
Waiting Time ◽  
Waiting Times ◽  
Wait Time ◽  
High Accuracy ◽  
Wait Times ◽  
Blood Collection ◽  
Time Prediction ◽  
Number Of Patients ◽  
Patient Will ◽  
Patient Waiting Time

Patients frequently complain of long waiting times in phlebotomy units. Patients try to predict how long they will stay in the phlebotomy unit according to the number of patients in front of them. If it is not known how fast the queue is progressing, it is not possible to predict how long a patient will wait. The number of prior patients who will come to the phlebotomy unit is another important factor that changes the waiting time prediction. We developed an artificial intelligence (AI)-based system that predicts patient waiting time in the phlebotomy unit. The system can predict the waiting time with high accuracy by considering all the variables that may affect the waiting time. In this study, the blood collection performance of phlebotomists, the duration of the phlebotomy in front of the patient, and the number of prior patients who could come to the phlebotomy unit was determined as the main parameters affecting the waiting time. For two months, actual wait times and predicted wait times were compared. The wait time for 95 percent of the patients was predicted with a variance of ± 2 minutes. An AI-based system helps patients make predictions with high accuracy, and patient satisfaction can be increased.

scholarly journals 635 Can Virtual Clinics Streamline Urology Referrals from Primary to Secondary Care?

2021 ◽  
Vol 108 (Supplement_2) ◽  
Author(s):  
S C Madathilethu ◽  
P B Sarmah ◽  
M F Khan
Keyword(s):  
Primary Care ◽  
Secondary Care ◽  
Wait Time ◽  
Outpatient Clinics ◽  
Wait Times ◽  
Retrospective Data ◽  
Imaging Findings ◽  
Flexible Cystoscopy ◽  
The Uk ◽  
Patient Referrals

Abstract Introduction The COVID-19 pandemic caused the UK to enter lockdown from 23rd March to 8th May 2020, necessitating Urology clinics to be conducted virtually. Our study aimed to assess whether new Urology referrals could be triaged and have an outcome arranged virtually before being seen by a specialist in clinic, thereby reducing referral to investigation wait-times. Method Retrospective data was collected from 23rd March to 8th May 2020 of new patient referrals consulted virtually in Urology outpatient clinics. Referrals were grouped into categories of presentation and outcome. Results 642 new patients were consulted virtually during the study period. 181 (28.1%) had further imaging requested; of these, the presentations with the greatest proportion of patients with this outcome were those referred with imaging findings (50%), UTI/cystitis (43.1%) and scrotal symptoms (34.3%). 116 patients (18.1%) were added to the waiting list for procedures; 85 were for flexible cystoscopy, for which the commonest indications were UTI/cystitis (36; 55.4%) and haematuria (15; 55.5%). Conclusions Certain urological presentations can be triaged straight to investigation by when directly referred from Primary Care, thus reducing referral to investigation wait-time and increasing outpatient protocol efficiency.

An experimental study of Web switching behavior

2003 ◽  
Vol 22 (2) ◽  
pp. 87-93
Author(s):  
James Otto ◽  
Mohammad Najdawi ◽  
William Wagner
Keyword(s):  
Experimental Study ◽  
Electronic Commerce ◽  
Web Site ◽  
Waiting Times ◽  
Switching Behavior ◽  
The Internet ◽  
Wait Times ◽  
Web Page ◽  
Extensive Growth ◽  
The Impact

With the extensive growth of the Internet and electronic commerce, the issue of how users behave when confronted with long download times is important. This paper investigates Web switching behavior. The paper describes experiments where users were subjected to artificially delayed Web page download times to study the impact of Web site wait times on switching behavior. Two hypotheses were tested. First, that longer wait times will result in increased switching behavior. The implication being that users become frustrated with long waiting times and choose to go elsewhere. Second, that users who switch will benefit, in terms of decreased download times, from their decision to switch.

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