scholarly journals 1460 Spot the difference? Suspected Skin Cancer Referral Clinic 2020 Impact Audit

2021 ◽  
Vol 108 (Supplement_6) ◽  
Author(s):  
K Kumaresan ◽  
C McGuinness
Keyword(s):  
Skin Cancer ◽  
Cancer Detection ◽  
Waiting Time ◽  
Wait Time ◽  
Definitive Treatment ◽  
Significant Drop ◽  
Detection Rates ◽  
Face To Face ◽  
Number Of Patients ◽  
Biopsy Rate

Abstract Introduction According to the 2018 WHO statistics nearly 18,000 people were diagnosed with melanoma in the UK and nearly 3000 died from this. We did this audit to study our skin cancer detection rates in the department of plastic surgery in Salisbury hospital before and during COVID. During COVID, our practise included telephone consultations, image reviews and some face-to-face consultations. Method We did two snapshot audits in January and May 2020. Based on Cancer Waiting time guidelines our hospital operational standard for patient to be seen in 2WW was 93% and Time for definitive treatment target is 96% (where the clock stops) Result There was significant drop in the number of patients presenting overall but the case load for plastics remained similar in both cycles. Audit showed compliance with 2WW waiting time except in 1 case in January owing to patient factors. 2% increase in biopsy rate. 24% of biopsied patient had cancer in January compared to 16% in May. Majority were squamous cell carcinomas. Average wait time to biopsy was longer in May by a week. Conclusions Although there has been a drastic reduction in the number of presentations there was no significant variation in the cancer detection rates. Biopsy rate was 2% higher, likely owing to a more cautious approach when using visual/ telephone consultations and image review. The audit highlights the pros and cons of using non face to face consultations in clinical practice.

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 Clinically Significant Prostate Cancer Detection with Various Prostate Sampling Schemes Based on Different csPCa Definitions

2021 ◽  
Author(s):  
Fei Wang ◽  
Tong Chen ◽  
Meng Wang ◽  
Hanbing Chen ◽  
Caishan Wang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Detection ◽  
Detection Rate ◽  
First Line ◽  
Detection Rates ◽  
Sampling Schemes ◽  
Number Of Patients ◽  
Clinically Significant ◽  
Magnetic Resonance Imaging Mri ◽  
Biopsy Method

Abstract Background Combining targeted biopsy (TB) with systematic biopsy (SB) is currently recommended as the first-line biopsy method by the European Association of Urology (EAU) guidelines in patients diagnosed with prostate cancer (PCa) with an abnormal magnetic resonance imaging (MRI). The combined SB and TB indeed detected an additional number of patients with clinically significant prostate cancer (csPCa); however, it did so at the expense of a concomitant increase in biopsy cores. Our study aimed to evaluate if ipsilateral SB (ipsi-SB) + TB or contralateral SB (contra-SB) + TB could achieve almost equal csPCa detection rates as SB + TB using fewer cores based on a different csPCa definition.Methods Patients with at least one positive prostate lesion were prospectively diagnosed by MRI. The combination of TB and SB was conducted in all patients. We compared the csPCa detection rates of the following four hypothetical biopsy sampling schemes with those of SB + TB: SB, TB, ipsi-SB + TB, and contra-SB + TB. Results The study enrolled 279 men. The median core of SB, TB, ipsi-SB + TB, and contra-SB + TB was 10, 2, 7 and 7, respectively; they all differed significantly from SB + TB (P < 0.001). ipsi-SB + TB detected significantly more patients with csPCa than contra-SB + TB based on the EAU guidelines (P = 0.042). ipsi-SB + TB and contra-SB + TB detected almost equal number of csPCa on the basis of the Epstein criteria (P = 1.000). Compared with SB + TB, each remaining method detected significantly fewer patients with csPCa regardless of the definition (P < 0.001) except ipsi-SB + TB, which achieved an almost equivalent csPCa detection rate to that of SB + TB on the grounds of D1 (P = 0.066).Conclusions ipsi-SB + TB could detect significantly more patients with csPCa than contra-SB + TB and acquire an almost equivalent csPCa detection rate to that of SB + TB using significantly fewer cores when csPCa was defined as International Society for Urological Pathology (ISUP) 2 or higher.

Can teledermatology meet the needs of the remote and rural population?

2021 ◽  
Vol 30 (10) ◽  
pp. 574-579
Author(s):  
Angela Woodley
Keyword(s):  
Skin Cancer ◽  
Cancer Detection ◽  
Cochrane Review ◽  
Rural Setting ◽  
High Quality ◽  
Specialist Service ◽  
Face To Face ◽  
Improve Accuracy ◽  
Skin Cancer Detection ◽  
Robust Evidence

Background: Teledermatology has been in use as a supplemental tool in dermatology for many years. This study will focus on its use for dermatology patients with suspected skin cancer, in the remote and rural setting. Objectives: Evaluation of the efficacy and accuracy of skin cancer detection using teledermatology. Methods: Literature review from last inclusion date of The Cochrane review of 2016 to August 2020. Due to high heterogeneity, resulting data were synthesised narratively. Results: All 6 studies agreed that ‘high-quality’ and dermoscopy images improve accuracy of diagnosis. All 6 studies showed its potential usage as 1) supplemental to face-to-face, 2) triage, or 3) a way of providing a specialist service where none is available. None considered it an adequate replacement for a traditional clinic setting. Conclusion: Teledermatology has enormous potential but more robust evidence is required.

scholarly journals Can a supervised algorithmic assessment of men for prostate cancer improve the quality of care? A retrospective evaluation of a prostate assessment pathway in Saskatchewan

2017 ◽  
Vol 11 (9) ◽  
pp. E338-43
Author(s):  
Bonnie Liu ◽  
Kunal Jana ◽  
Gary Groot
Keyword(s):  
Prostate Cancer ◽  
Risk Stratification ◽  
Cancer Detection ◽  
Prostate Biopsy ◽  
Wait Time ◽  
Low Risk ◽  
Time Data ◽  
Significant Difference ◽  
High Risk Cancer ◽  
Biopsy Rate

Introduction: The Saskatoon Prostate Assessment Pathway (SPAP) was developed in 2013 in part to decrease the wait times between physician referral and biopsy for patients with suspected prostate cancer. Using an algorithm carefully designed to optimize appropriate prostate biopsy rates, physicians can directly refer patients for biopsy through the SPAP without seeing a urologist. All other patients are referred to the Saskatoon Urology Associates (SUA). The present study evaluates the performance of the algorithm.Methods: 971 patients seen at the SUA and 302 patients seen through the SPAP were identified. Information on age, biopsy status and outcome, risk stratification, and time between referral and biopsy was collected. Biopsy wait time data was analyzed using gamma distribution. Association between referral method and biopsy rate, and between referral method and risk stratification, was analyzed using Z-test.Results: The expected wait time from referral to biopsy for patients seen through SUA was 2.63 times longer than those seen through SPAP (34 vs. 91 days). The biopsy rate of patients seen in the SPAPwas significantly higher than those by SUA (88% vs. 69%, 95% confidence interval [CI] 0.14–0.26; p<0.00001). There was no significant difference in positive biopsy rates for patients seen through the SPAP vs. SUA (81% vs. 74%, 95% CI -0.011,0.14; p=0.095), for detection of low-risk cancer, (12% vs. 10%, 95% CI -0.034,0.080; p=0.44), or for clinically relevant cancer, i.e., intermediate- and high-risk cancer, for SPAP vs. SUA (56.54% vs. 56.68%, 95% CI -0.091,0.089; p=0.49).Conclusions: The algorithm used in the SPAP is effective in decreasing wait time to prostate biopsy and has the same cancer/pre-cancer detection rate, but at the cost of a higher biopsy rate. Both referralmechanisms result in few low-risk cancer detection biopsies, finding primarily cases of high- or intermediate-risk cancer.

Automated Skin Cancer Detection Web-Based Application and Review of Some Image Classification Algorithm

2020 ◽  
Author(s):  
Siddhesh Bhojane ◽  
Krishna Shrestha ◽  
Sanghmitra Bharadwaj ◽  
Ritul Yadav ◽  
Fenil Ribinwala ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Image Classification ◽  
Cancer Detection ◽  
Classification Algorithm ◽  
Web Based ◽  
Skin Cancer Detection

scholarly journals Patients’ expectations on medicines information

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
A Sevikyan ◽  
I Kazaryan
Keyword(s):  
Storage Conditions ◽  
Community Pharmacies ◽  
Duration Of Treatment ◽  
Pharmacy Staff ◽  
Medicine Price ◽  
Expiry Date ◽  
Face To Face ◽  
Medicines Information ◽  
Number Of Patients ◽  
Effective Use

Abstract Background Medicines information is important for patients as it assists them in achieving more safe and effective use of pharmaceuticals. Many patients seek information from community pharmacies' staff. The objectives of this study were to identify specific topics of medicines information which patients expect to receive at community pharmacies. Methods Face-to-face interviews were conducted with 1059 visitors of community pharmacies in Armenia. Previously developed questionnaire was used for interviewing patients. Data were analysed with the SPSS statistical software. Results Most of participants acknowledged importance of receiving from community pharmacies' staff information on therapeutic indications of medicines (91.1%), dosage and method of administration (90.8%), the duration of treatment (86.3%), expiry date (85.7%), adverse reactions (85.0%), contraindications (84.6%), storage conditions (77.5%) and type of activity (76.0%). Importance of receiving information on some specific topics depends on patients' age. Participants' acknowledgement of information on interaction with other medicines, certain categories of users, and potential effects on the ability to drive is decreasing with patients' age increasing (p &lt; 0.001). The opposite trend was observed with attitude to receiving information on medicine price that was mostly valued by elderly patients (p = 0.046). The number of patients who trust the information provided was higher among those who more often received comprehensive responses from pharmacists and pharmacy assistants (p &lt; 0.001). Conclusions Receiving medicines information from the staff of community pharmacies is important for patients, and the majority of them trust to information received. Patients are mainly provided with comprehensive responses to their questions about medicines, and there was dependence between a frequency of receiving comprehensive responses and a level of patients' trust the information provided by pharmacy staff. Key messages Increasing patients’ awareness on their right to get medicines information can be beneficial. Comprehensive responses increase patients trust medicines information provided by pharmacists.

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