scholarly journals Robotic Pharmacy Implementation and Outcomes in Saudi Arabia. A Twenty-One Month Review. (Preprint)

2021 ◽  
Author(s):  
James Waterson ◽  
Hisham Momattin ◽  
Shokry Arafa ◽  
Shahad Momattin ◽  
Rayan Rahal

BACKGROUND We describe the introduction, use and evaluation of an automation and integration pharmacy development program in a private facility in Saudi Arabia. The project was undertaken to meet specific challenges of increasing throughput, reducing medication dispensing error, increasing patient satisfaction, and freeing up pharmacists’ time for increased face-to-face consultations with patients. OBJECTIVE To reduce outpatient waiting times for dispensing of medications, to help to free up time to meet patient expectations for pharmacy services including medication education, to reduce the volume of non-value-added pharmacist tasks, to reduce dispensing error rates, and to aid with the rapid development of a reputation in the served community for patient-centred care for a new facility. METHODS Pre-implementation data for patient wait-time for dispensing of prescribed medications as one measure of patient satisfaction, pharmacist activity and productivity in terms of patient interaction time were gathered. Reported and discovered dispensing errors per 1,000 prescriptions were also aggregated. All pre-implementation data was gathered over an eleven- month period. Initial project goals were set as a 50% reduction in the average patient wait-time, a 15% increase in patient satisfaction regarding pharmacy waiting time and pharmacy services, a 25% increase in pharmacist productivity and zero dispensing errors. This was expected to be achieved within ten months of go-live. RESULTS From go-live, data was gathered on the above metrics in one-month increments. At the 10-month point there had been a 53% reduction in the average waiting time, a 20% increase in patient satisfaction regarding pharmacy waiting time, with a 22% increase in overall patient satisfaction regarding pharmacy services, and a 33% increase in pharmacist productivity. There was a zero-rate dispensing error reported. CONCLUSIONS The robotic pharmacy solution studied was highly effective, but upstream supply chain is vital to throughput maintenance, particularly when automated filling is planned. The automation solution must also be seamlessly and completely integrated into the facility’s software systems for appointments, medication records and prescription in order to garner its full benefits. Patient overall satisfaction with pharmacy services is strongly influenced by waiting time and follow up studies ae required to identify how to use this positive effect and how to optimally use ‘freed-up’ pharmacist time. The extra time spent with patients by pharmacists, and the complete overview of the patient’s medication history, that full integration gives, creates opportunities for tackling challenging issues such as medication nonadherence. Reduced waiting times may also allow for smaller prescription fill volumes, and more frequent outpatient department visits, allowing increased contact time with pharmacists.

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 6099-6099 ◽  
Author(s):  
H. W. Hirte ◽  
S. Kagoma ◽  
L. Zhong ◽  
I. Collins ◽  
D. Burns ◽  
...  

6099 Background: As the number and complexity of chemotherapy regimens increase, the demands on pharmacy services to reduce chemotherapy preparation and checking times continues to increase. Dose banding, a system whereby doses of intravenous cytotoxic drugs calculated on an individual basis are rounded up or down to predetermined standard doses (the maximum variation of the adjustment between standard dose and doses constituting each band is 5% or less) was identified as a strategy that could be used to address some of the issues around time pressures to help reduce patient waiting times for treatment. Methods: The project consisted of 3 phases; Phase I - literature review to identify dose banding publications; Phase II - selection of drugs to be banded for the pilot. The two drugs selected were 5FU and leukovorin, and Phase III - Time studies pre-, interim and post dose banding implementation to determine drug dispensing time and patients’ wait time for pharmacy related procedures. This occurred for a 2 week period (10 working days) either prior to implementation (pre- 819 patients studied), 4 days after implementation (interim - 854 patients studied) and 4 weeks after implementation (post - 785 patients studied). Results: Drug dispensing time did not decrease with dose banding (pre- 7.9 min, interim - 7.6 min and post - 9.4 min). However, the average patient wait time decreased after piloting the dose banding project (pre - 31.6 min, interim 23.7 min, and post - 27.8 min). The percentage of doses that were banded were 37.8% in the interim time study and 58.2% in the post time study. Conclusions: Although dose banding did not reduce dispensing time in this study, likely because the preparation for dispensing 5FU and leukovorin syringes is normally very simple and quick, patient’s wait time for pharmacy related procedures did decrease. This was probably due to contributions of other factors in the pharmacy process. A reduction in dispensing time could likely be achieved if more complex regimens were considered for dose banding. Dose banding could be used to increase capacity within the chemotherapy suite on the day of administration. It also allows for a better work schedule and increases efficiencies within the chemotherapy preparation and administration areas. (Sponsored by funds from Cancer Care Ontario) No significant financial relationships to disclose.


2019 ◽  
Vol 65 (12) ◽  
pp. 1476-1481
Author(s):  
Fábio Ferreira Amorim ◽  
Karlo Jozefo Quadros de Almeida ◽  
Sanderson Cesar Macedo Barbalho ◽  
Vanessa de Amorim Teixeira Balieiro ◽  
Arnaldo Machado Neto ◽  
...  

SUMMARY OBJECTIVE Exploring the use of forecasting models and simulation tools to estimate demand and reduce the waiting time of patients in Emergency Departments (EDs). METHODS The analysis was based on data collected in May 2013 in the ED of Recanto das Emas, Federal District, Brasil, which uses a Manchester Triage System. A total of 100 consecutive patients were included: 70 yellow (70%) and 30 green (30%). Flow patterns, observed waiting time, and inter-arrival times of patients were collected. Process maps, demand, and capacity data were used to build a simulation, which was calibrated against the observed flow times. What-if analysis was conducted to reduce waiting times. RESULTS Green and yellow patient arrival-time patterns were similar, but inter-arrival times were 5 and 38 minutes, respectively. Wait-time was 14 minutes for yellow patients, and 4 hours for green patients. The physician staff comprised four doctors per shift. A simulation predicted that allocating one more doctor per shift would reduce wait-time to 2.5 hours for green patients, with a small impact in yellow patients’ wait-time. Maintaining four doctors and allocating one doctor exclusively for green patients would reduce the waiting time to 1.5 hours for green patients and increase it in 15 minutes for yellow patients. The best simulation scenario employed five doctors per shift, with two doctors exclusively for green patients. CONCLUSION Waiting times can be reduced by balancing the allocation of doctors to green and yellow patients and matching the availability of doctors to forecasted demand patterns. Simulations of EDs’ can be used to generate and test solutions to decrease overcrowding.


2016 ◽  
Vol 11 (9) ◽  
pp. 272 ◽  
Author(s):  
AlaEddin Mohammad Khalaf Ahmad ◽  
Mohammad Ali Saleh Alghamdi ◽  
Saleh Ali Saleh Alghamdi ◽  
Omar Zayyan Alsharqi ◽  
Hussein Mohammad Al-Borie

The current research investigates the factors influencing patient satisfaction with pharmacy services at King Fahd Armed Forces Hospital (KFAFH). This research proposes and tests a three-factor model that influence patient satisfaction. These factors include accessibility, availability of medications, and pharmacy staff attitude as independent variables, while the dependent variable is patient satisfaction. In order to explore this issue, a quantitative method was used in the form of a questionnaire issued in KFAFH in Jeddah city in Saudi Arabia. The research targeted 333 patients as a representative sample, rather than the whole population. A random sample was used to choose the participants in this research. The research retrieved 290 valid questionnaires, which represented a reponse rate of 87%. The results confirm significant differences in the influence of these factors on patient satisfaction. The research concludes that there are significant influences from accessibility and availability of pharmacy services, whereas there is no significant influence of staff attitudes on patient satisfaction. The research recommends improving the accessibility and availability of medication regularly and continuously. It is also recommended that pharmacy services should conduct training courses to improve staff skills and attitudes to deal with patients.


2019 ◽  
Vol 8 (1) ◽  
pp. 32-38
Author(s):  
Yousef Ahmed Alomi ◽  
Hawazen Abdullah Al-Kammash ◽  
Aroub Alhamidi ◽  
Walaa Aboziad ◽  
Kairat Imad Al-Hennawi ◽  
...  

Author(s):  
Dilek Orbatu ◽  
Oktay Yıldırım ◽  
Eminullah Yaşar ◽  
Ali Rıza Şişman ◽  
Süleyman Sevinç

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.


2022 ◽  
Vol 18 (1) ◽  
pp. 101-131
Author(s):  
Komang Adhi Restudana ◽  
Gede Sri Darma

  Pharmacy services in a hospital are an inaccessible part of the hospital services as a whole. The accumulation of prescriptions in the pharmacy will cause the prescription process to be long and long, which has an impact on customer waiting times, which of course will have a major impact on customer satisfaction. From the standard time set as Quality Indicators at Bali Jimbaran Hospital, namely: drug processing at the outpatient pharmacy of Bali Jimbaran Hospital is 60 minutes of concocted drugs, 30 minutes of non-concocted drugs. The purpose of this research is to identify activities starting from the input, process and results generated through the Lean approach. The method used is an observational action process research, using lean methods to photograph the outpatient pharmacy service process flow through document review, direct interviews, interviews. The result of the research is an improvement in waiting time, it can be seen that the NVA activities can be eliminated by 66% and VA activities show an increase of 44%. With the many activities that are VA and the elimination of NVA activities, it will accelerate the process of outpatient pharmacy services at the Bali Jimbaran Hospital and improve customer satisfaction, which can be seen from the decrease in customer complaints against outpatient pharmacy services by up to 50%, which was previously 80%. Keywords: Lean, Pharmacist, Waiting time, Value Added, Non-Value Added


2019 ◽  
Vol 8 (2) ◽  
pp. 129-134
Author(s):  
Yousef Ahmed Alomi ◽  
Malika Alshamari ◽  
Hawazen Abdullah Al-Kammash ◽  
Aroub Alhamidi ◽  
Walaa Aboziad ◽  
...  

Author(s):  
Jose Antonio Vazquez-Ibarra ◽  
Rodolfo Rafael Medina-Ramirez ◽  
Irma Jimenez-Saucedo

Public healthcare services face a growing demand and Emergency department is the main entrance to these services. Waiting times at Emergency departments are increasing at risky levels, causing that people die in wait rooms due to a lack of staff to serve timely every patient. Present chapter describes one research project conducted in a mexican public hospital which was in the process of adopting a triage systems in order to reach the goal of a maximum wait time in department. Design of experiments is the tool proposed to analyze waiting time factors and define the best levels to reduce the response variable value.


Author(s):  
Jose Antonio Vazquez-Ibarra ◽  
Rodolfo Rafael Medina-Ramirez ◽  
Irma Jimenez-Saucedo

Public healthcare services face a growing demand and Emergency department is the main entrance to these services. Waiting times at Emergency departments are increasing at risky levels, causing that people die in wait rooms due to a lack of staff to serve timely every patient. Present chapter describes one research project conducted in a mexican public hospital which was in the process of adopting a triage systems in order to reach the goal of a maximum wait time in department. Design of experiments is the tool proposed to analyze waiting time factors and define the best levels to reduce the response variable value.


2019 ◽  
Vol 8 (3) ◽  
pp. e000542 ◽  
Author(s):  
Alexandra von Guionneau ◽  
Charlotte M Burford

BackgroundLong waiting times in accident and emergency (A&E) departments remain one of the largest barriers to the timely assessment of critically unwell patients. In order to reduce the burden on A&Es, some trusts have introduced ambulatory care areas (ACAs) which provide acute assessment for general practitioner referrals. However, ACAs are often based on already busy acute medical wards and the availability of clinical space for clerking patients means that these patients often face long waiting times too. A cheap and sustainable method to reducing waiting times is to evaluate current space utilisation with the view to making use of underutilised workspace. The aim of this quality improvement project was to improve accessibility to pre-existing clinical spaces, and in doing so, reduce waiting times in acute admissions.MethodsData were collected retrospectively from electronic systems and used to establish a baseline wait time from arrival to having blood taken (primary outcome). Quality improvement methods were used to identify potential implementations to reduce waiting time, by increasing access to clinical space, with serial measurements of the primary outcome being used to monitor change.ResultsData were collected over 54 consecutive days. The median wait time increased by 55 min during the project period. However, this difference in waiting time was not deemed significant between the three PDSA cycles (p=0.419, p=0.270 and p=0.350, Mann-Whitney U). Run chart analysis confirmed no significant changes occurred.ConclusionIn acute services, one limiting factor to seeing patients quickly is room availability. Quality improvement projects, such as this, should consider facilitating better use of available space and creating new clinical workspaces. This offers the possibility of reducing waiting times for both staff and patients alike. We recommend future projects focus efforts on integration of their interventions to generate significant improvements.


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