scholarly journals A Study of Determinant of Long Waiting Period in Outpatient Department and Recommendation on reducing waiting time in a Superspecialty Hospital

2017 ◽  
Vol 5 (12) ◽  
Author(s):  
N Junior Sundresh ◽  
Keyword(s):  
Waiting Time ◽  
Outpatient Department ◽  
Waiting Period

scholarly journals A study of waiting time of patients in outpatient department of armed forces Tertiary Hospital in Northern India

2020 ◽  
Vol 7 (4) ◽  
pp. 125-127
Author(s):  
Rajeev Saxena ◽  
◽  
Sartaj Sharma ◽  
Vivek Sharda ◽  
Nalini G ◽  
...  
Keyword(s):  
Waiting Time ◽  
Armed Forces ◽  
Tertiary Hospital ◽  
Outpatient Department ◽  
Northern India

scholarly journals Is patient satisfaction in ENT outpatient department influenced by clinic waiting time?

2013 ◽  
Vol 11 (8) ◽  
pp. 639-640
Author(s):  
Anders Hulme ◽  
Alex Gan ◽  
Meera Beena ◽  
Chidozie Ejikeme ◽  
Surya Narayan
Keyword(s):  
Patient Satisfaction ◽  
Waiting Time ◽  
Outpatient Department

scholarly journals The Relationship Between Waiting Time for Elective Cholecystectomy and Emergency Admission in KFMMC: Single Centre Experience

2021 ◽  
Vol 105 (1-3) ◽  
pp. 411-416
Author(s):  
Emad M. AL-Osail ◽  
Mohammed Bu Bshait ◽  
Hassan Alyami ◽  
Eman Zakarnah ◽  
Mohammed A. Alaklabi ◽  
...  
Keyword(s):  
Waiting Time ◽  
Risk Ratio ◽  
Waiting Times ◽  
Emergency Admission ◽  
Waiting Period ◽  
Ed Visits ◽  
Emergency Cholecystectomy ◽  
Study Participants ◽  
The Relationship ◽  
Elective Cholecystectomy

Introduction Patients with symptomatic cholelithiasis may undergo cholecystectomy, as an emergency or elective, in the outpatient clinic after discharge from the emergency department (ED). Increasing waiting times for elective cholecystectomy may lead to multiple ED visits for pain management or admission for emergency cholecystectomy. The aim of our study was to determine the relationship between waiting time for elective cholecystectomy and emergency admission. Methods This retrospective, observational study was designed and conducted at a single institution. The medical records of 239 patients with gallstone diseases who underwent emergency or elective cholecystectomy between January 2013 to November 2017 were obtained from the clinic. Result Approximately 76% (182/239) of the study participants underwent elective cholecystectomy and ∼24% (57/239) visited the ED during their waiting period, of which 42% (24/57) proceeded with emergency cholecystectomy during the waiting time for elective cholecystectomy and the remaining 58% (33/57) were managed in the ED and eventually underwent elective cholecystectomy. A waiting period of 60 days or more increased the risk of emergency cholecystectomy 5.21 times compared to a waiting period of less than 60 days. A waiting period of 31 to 180 days and above increased the chances of emergency cholecystectomy 4.13 (risk ratio) times and 25.5 (risk ratio) times, respectively, compared to a waiting period of 30 days or less. Conclusion Waiting time for elective cholecystectomy should be less than 30 days to reduce the risk of emergency cholecystectomy and multiple ED visits.

Stimulation Seeking and Hyperactive Behavior in Children with ADHD: A Re-Analysis

2002 ◽  
Vol 95 (1) ◽  
pp. 71-90 ◽  
Author(s):  
Inge Antrop ◽  
Ann Buysse ◽  
Herbert Roeyers ◽  
Paulette van Oost
Keyword(s):  
Behavior Analysis ◽  
Waiting Time ◽  
Fixed Time ◽  
Behavioral Measures ◽  
Waiting Period ◽  
Children With Adhd ◽  
Target Behaviors ◽  
Hyperactive Behavior ◽  
Additional Stimulation ◽  
Perceived Duration

To examine the stimulation-seeking function of hyperactivity in children with ADHD. Antrop and colleagues analyzed the behavior of 30 hyperactive and 30 nonhyperactive children during a waiting situation, either with or without extra stimulation. The behavior was assessed by frequency measures. In their study it was hypothesized that children with ADHD would show a greater decrease in activity in the presence of stimulation than control children. Since confirmation for this hypothesis was only found for 2 of 25 target behaviors, the present re-analysis included other behavioral measures to assess two relationships: first, how hyperactivity varies under fixed time conditions, using measures of duration and intensity of behavior instead of frequency measures, and second, how the perceived duration of waiting time affects behavior. Analysis indicated that children with ADHD showed a greater decrease in behavior in the presence of stimulation for touching objects and movements of trunk, as reported. Further, children who underestimated the waiting period were more apt to seek additional stimulation in its absence than those who overestimated the waiting period.

scholarly journals Review on Queueing Problem in Healthcare

2018 ◽  
Vol 7 (4.30) ◽  
pp. 304
Author(s):  
Hajar Ariff ◽  
M Ghazali Kamardan ◽  
Suliadi Sufahani ◽  
Maselan Ali
Keyword(s):  
Emergency Department ◽  
Healthcare System ◽  
Waiting Time ◽  
Patient Flow ◽  
Outpatient Department ◽  
Scheduling Theory ◽  
Appointment System

This article shows the application of queueing, simulation and scheduling used in the field of healthcare. A summary of queueing, simulation and scheduling theory used in waiting time, appointment system and patient flow are summarised in this article. Different departments in the healthcare system are also considered in this article such as emergency department, outpatient department and the pharmacy. The aim is to provide the reader a general background into queueing, simulation and scheduling in the healthcare.

P1659SURVIVAL OF PATIENTS WAITING FOR KIDNEY TRANSPLANTATION IN TERMS OF COMPETING RISKS

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Aleksei Zulkarnaev ◽  
Vadim Stepanov ◽  
Andrey Vatazin
Keyword(s):  
Kidney Transplantation ◽  
Competing Risks ◽  
Waiting Time ◽  
Cumulative Incidence ◽  
Graft Loss ◽  
Waiting List ◽  
Waiting Period ◽  
Risk Of Death ◽  
End Point ◽  
Kaplan Meier

Abstract Background and Aims In Russia, when choosing a donor-recipient pair, the “waiting time” factor has very little weight. Aim: to analyze the survival of patients on the waiting list for kidney transplantation and the results of transplantation depending on the duration of waiting. Method We performed a retrospective observational analysis that included 1,197 patients on the waiting list. The end point was exclusion from the waiting list (WL). The causes for exclusion (death, exclusion due to deterioration of the comorbid background or transplantation) were considered in terms of competing risks. Results In total, 72.5% of patients reached the end point: 21.1% of them died, 11% were excluded, and 40.4% underwent transplantation. Kaplan-Meier estimate showed that cumulative risk of death was 80.4% [95% CI 77.9; 88.6], of exclusion – 77.9% [95% CI 65.4; 88.2], of transplantation – 63.6% [95% CI 58.3; 69] after 10 years on the waiting list. However, such an assessment cannot be directly interpreted as a prediction of the relevant event risk for the patient in the WL, because it does not take into account competing events. According to a balanced assessment of the competing risks (Fine and Gray regression model), cumulative incidence was 30.9% [95% CI 27.7; 34.2] for death, 18.2% [95% CI 15.5; 21.1] for exclusion and 49.4% [95% CI 46; 52.6] for transplantation after 10 years on WL. The probability of transplantation was significantly higher than the risk of death up to and including 5 years of waiting (incidents rate ratio – IRR 1.769 [95% CI 1.098; 2.897]). When waiting 7 to 8 years, the probability of transplantation was less than the risk of death: IRR 0.25 (95% CI 0.093; 0.588; p=0.0009) – fig 1. Of the 483 recipients, 61 died and 119 returned to dialysis. The risk of graft loss after 10 years was 68.5% [95% CI 57.5; 79.1] and the risk of death of a recipient with a functioning graft was 48.3% [95% CI 34.7; 63] according to Kaplan-Meier estimate. The cumulative incidence was 30.8% [95% CI 23.3; 38.5] and 55.7% [95% CI 46.6; 63.5] according to Fine and Gray estimate, respectively. The risk of death after transplantation increases significantly when waiting for more than 6 years – IRR 4.325 [95% CI 1.649; 10.47], p=0.0045 relative to a shorter waiting period – fig 2. With an increase in the waiting period, the comorbid background (CIRS scale) deteriorates significantly, even adjusted for the initial patient condition: the partial correlation r=0.735; p<0.0001. The deteriorating comorbid background reduces the expediency of transplantation – fig 3 (the potential patient`s benefit is significantly reduced). Conclusion : 1. In the context of competing risks, the Fine and Gray estimate gives a more balanced risk assessment compared to the Kaplan-Meier method. 2. Increasing the waiting time for transplantation significantly increases the risk of death of the candidate on the waiting list and reduces the probability of transplantation, as well as increases the risk of death of the recipient after transplantation. Apparently, this is mainly due to the deterioration of the comorbid background.

The Effect of Early Education on Patient Anxiety While Waiting for Elective Cardiac Catheterization

2003 ◽  
Vol 2 (2) ◽  
pp. 113-121 ◽  
Author(s):  
Karen Harkness ◽  
Lydia Morrow ◽  
Kelly Smith ◽  
Michele Kiczula ◽  
Heather M. Arthur
Keyword(s):  
Quality Of Life ◽  
Cardiac Catheterization ◽  
Waiting Time ◽  
Nursing Intervention ◽  
Control Group ◽  
Patient Anxiety ◽  
Waiting Period ◽  
Mean Waiting Time ◽  
Significant Difference

Background: A supply–demand mismatch with respect to cardiac catheterization (CATH) often results in patients experiencing waiting times that vary from a few weeks to several months. Long delays can impose both physical and psychological distress for patients. Purpose: The purpose of this study was to examine the effect of a psychoeducational nursing intervention at the beginning of the waiting period on patient anxiety during the waiting time for elective CATH. Methods: This was a 2-group randomized controlled trial. Intervention patients received a nurse-delivered, detailed information/education session within 2 weeks of being placed on the waiting list for elective CATH. Control group patients received usual care. Results: The mean waiting time for CATH was 13.4±7.2 weeks, which did not differ between groups ( P=0.509). Anxiety increased in both groups over the waiting time ( P=0.028). Health-related quality of life deteriorated over the waiting time in both groups ( P<0.05). On a visual analogue scale, there was a significant difference ( P=0.002) between the intervention (4.0±2.7) and control (5.2±3.0) groups in self-reported anxiety 2 weeks prior to CATH. Conclusions: The waiting period prior to elective CATH has a negative impact on patients’ perceived anxiety and quality of life and a simple intervention, provided at the beginning of the waiting period, may positively affect the experience of waiting.

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