The Effects of Distance, Time, and Nonspatial Factors on Hemodialysis Access in Qatar.

Background A long distance and time spent traveling to a hemodialysis (HD) center and other factors, such as comorbidities, can significantly impact HD patient compliance, satisfaction, and cost. Uncertainty about HD-dependent patients' geographical location may lead to inappropriate distribution of HD centers. The present study investigates travel time, distance, and nonspatial factors affecting HD center accessibility within a 30-km radius in the State of Qatar. Materials and methods The study included all HD-dependent patients residing in Qatar between March 1, 2020, and December 31, 2021. There were 921 patients dialyzed in six HD centers across Qatar. Our methodology incorporated descriptive and analytical cross-sectional designs to accurately identify the shortest routes and quickest travel times. We used two applications (Maptive {Vancouver, WA: BatchGeo LLC} and Google Maps {Mountain View, CA: Google LLC}) and marked a driving distance of 30 km as the main assessment scale and measurement standard, allowing optimum spatial accessibility determination. Results On average, patients traveled approximately 19±4.2 km, requiring almost 17.6±3.4 minutes to reach the assigned HD center three times per week. Based on geographic-spatial accessibility analysis, patients living in Umm Salal drove 31.4±3.5 km in 32.4±4.7 minutes, Al Daayen patients drove 30.2 km in 25.3 minutes, and others even drove more than 70 km to access HD sessions. Approximately 37.8% of Qatar's municipalities had no HD centers within their boundaries, but nearly 47% of HD-dependent patients lived in those municipalities. Additionally, some municipalities had HD centers; however, their general population density was less than 100 inhabitants/km2, and they had relatively few patients requiring regular HD. We noted a statistically significant correlation between the patients' residences and the locations of HD centers, whether they were located within or outside municipalities. Also, nonspatial factors may have affected the likelihood of reaching a hemodialysis center within a 30-km distance, including two or more comorbid conditions, having HD for at least five years, living in a municipality with more than 1,000 inhabitants/km2, being female, and attending dialysis centers that are more than 30 km away. Conclusion Although the available HD centers were sufficient for the present number of patients requiring HD, HD center locations did not match the patients' distribution, leading to difficulties for some patients. Understanding the impact of this geographic mismatch, population density, and other spatial factors helps significantly improve patient care and satisfaction at minimal cost. Furthermore, considering all these factors is crucial when planning new centers to achieve higher satisfaction and compliance as well as better health care.

Time Spent on Medical Round Activities, Distance Walked, and Time-Motion in the General Medicine Department at Hamad General Hospital in Qatar.

Background The daily morning round is a routine activity performed by medical teams. During the morning round, updates on the patient's clinical condition, new laboratory results, and other test results are reviewed and discussed between team members, the patient, and at times the family. Completing these tasks takes time. The design of the patient location differs between hospitals, and significant distance between patients can considerably affect round times. This study assesses physicians' time spent on clinical activities, the distance traveled, and the time they spend walking between patients during daily morning rounds to identify better reorganization methods to reduce wasted time. Methodology The survey was self-administered and had no intervention needing ethical approval. The research team's leader engaged two observers (a general practitioner from another department and a general internal medicine department case manager) to collect the data. The general practitioner was a medical graduate doctor, while the bed manager was not a medical college graduate. They observed 10 rounds over 10 non-consecutive days from July 1 to July 30, 2022. They recorded daily activities during the daily morning round, including time spent with patients, family conversations, bedside education, medication, social issues, and the time and distance required to move from patient to patient and from one location to location. The informal conversations about age, work history, and other small talk were recorded and converted into quantitative data. In each round, records were given to a statistician for rechecking. Subsequently, the records were imported into a Microsoft Excel spreadsheet for further statistical analysis. For continuous variables, the data were summarized as mean, median, and standard deviation. For categorical variables, the data were summarized as counts or proportions. Results On average, the duration of the daily morning round was 161.7 ± 17.3 minutes. The average number of patients seen by the general internal medicine round team was 14. The median patient encounter time per patient was 14 minutes (11-19 minutes), with an average of 12 minutes. An average of 8.6 employees participated in the 10-day rounds. The physician spent 41.2% of the time in direct contact with the patient during the morning round, 11.4% in maintaining electronic medical records, and 18.20% in bedside teaching. Additionally, 7.1% of the round time was spent because of interruptions by clinical and non-clinical staff other than team members or family members who were not in the room. Furthermore, a team member walked an average of 763 ± 54.5 m (667-872 m) per round, costing 35.7 minutes (22.1%) of the total round time. Conclusions The daily morning round time was significantly longer compared with the reported round times. Relocating patient beds to a common location reduced the rounding time by 22.30%. Disruption, teaching, and medical instruction must also be considered and shortened to reduce the morning round time.

An Evaluation of Healthcare Safety Culture Among Healthcare Professionals in Secondary and Tertiary Public Hospitals in the Middle East Region.

Background and aim The provision of quality healthcare is initiated by a culture of patient safety. Understanding the patient safety culture (PSC) is a critical concept for all healthcare workers. We conducted this study to evaluate the PSC understanding among the Hamad Medical Corporation (HMC) staff members. Furthermore, to establish a local (HMC) reference point for providing quality health care based on a culture of patient safety. Method A Hospital Patient Safety Culture Survey (HSOPSC) was presented to our health system employees to assess their perceptions and understandings of PSC. The survey was self-administered. STATA Package version 12.0 culture software was used to analyze these data in terms of descriptive, correlational, and multivariate ordinal regression. Results This study targeted to survey 6,538 employees in HMC facilities, but only 5,583 responded, resulting in a percentage response rate of 85.4%. Ten facilities achieved 100% participation, and other HMC facilities had response rates ranging from 71.2% to 97.5%. Approximately 88.0% of the responders had direct patient contact. The HSOPSC survey resulted in an overall positive response rate of 62.4%. The dimensions with the highest positive response score were "teamwork within the Unit" followed by "organizational learning/continuous improvement" and "management support for patient safety" with a mean percent positive response (PPR) of 83.1%, 82.0%, and 79.2%, respectively. Conversely, there are three dimensions with the lowest positive response score, including "communication openness," "staffing," and "nonpunitive response to errors," with a mean PPR of 46.6%, 40.1%, and 27.7%, respectively. ANOVA and the student t-test revealed that men (64.3% ± 8.1%), employees with 11-15 years of experience in their specialty (65.8% ± 6.5%), and general hospital type (64.4% ±7.2%), were all significantly associated with differences in the overall perceptions of PSC. According to the study results, there was a moderate correlation between perceptions of PSC at the hospital and the following: Teamwork Across Units (RS= 0.43; p < 0.05), and Frequency of Events Reported (RS= 0.40; p < 0.05.). A regression analysis found that men, workers under 40 years of age, professionals with no direct contact with patients, employees with 11-15 years of experience in their specialty, intensive care staff, and general hospital staff were all significant predictors of overall favorable perceptions of the PSC. Conclusion PSC's understanding of HMC staff is moderate. Furthermore, this is the first study conducted for PSC understanding by the HMC staff in Qatar State. It is eligible to be considered a backbone and reference for new research projects about PSC in Qatari health facilities, if not worldwide.

Time-Series Forecasting of Hemodialysis Population in the State of Qatar by 2030.

BACKGROUND: There are few statistics on dialysis-dependent individuals with end-stage kidney disease (ESKD) in Qatar. Having access to this information can aid in better understanding the dialysis development model, aiding higher-level services in future planning. In order to give data for creating preventive efforts, we thus propose a time-series with a definitive endogenous model to predict ESKD patients requiring dialysis. METHODS: In this study, we used four mathematical equations linear, exponential, logarithmic decimal, and polynomial regression, to make predictions using historical data from 2012 to 2021. These equations were evaluated based on time-series analysis, and their prediction performance was assessed using the mean absolute percentage error (MAPE), coefficient of determination (R2), and mean absolute deviation (MAD). Because it remained largely steady for the population at risk of ESKD in this investigation, we did not consider the population growth factor to be changeable. (FIFA World Cup 2022 preparation workforce associated growth was in healthy and young workers that did not influence ESKD prevalence). RESULT: The polynomial has a high R2 of 0.99 and is consequently the best match for the prevalence dialysis data, according to numerical findings. Thus, the MAPE is 2.28, and the MAD is 9.87%, revealing a small prediction error with good accuracy and variability. The polynomial algorithm is the simplest and best-calculated projection model, according to these results. The number of dialysis patients in Qatar is anticipated to increase to 1037 (95% CI, 974-1126) in 2022, 1245 (95% CI, 911-1518) in 2025, and 1611 (95% CI, 1378-1954) in 2030, with a 5.67% average yearly percentage change between 2022 and 2030. CONCLUSION: Our research offers straightforward and precise mathematical models for predicting the number of patients in Qatar who will require dialysis in the future. We discovered that the polynomial technique outperformed other methods. Future planning for the need for dialysis services can benefit from this forecasting.

Scenarios to Improve the Patient Experience Time in a Tertiary Academic Hospital Using Simulation.

Background Shortening the patient experience time (PET) in the emergency department (ED) improves patient quality and satisfaction and reduces mortality and morbidity. Worldwide, the PET target in the ED is ≤ 6 hours; however, the PET awaiting admission to inpatient Medicine at Hamad General Hospital (HGH) in the Qatar State, through ED is currently 15.3±6.4 (mean ± SD) hours. Aim Identify solutions to reduce the PET duration at HGH-ED to the international target. Method A cohort study was done using the Discrete-event simulation (DES) model, utilizing a commercial simulation software package (Process Model Inc., Utah, version 5.2.0). One-year data, January 1, 2019 - December 30, 2019, was analyzed and found to follow seven subprocesses. The duration of each subprocess was recorded, and the average time was calculated. A computer simulation scheme was developed for all the subprocesses of the actual PET duration. The simulated PET was validated, and scenarios were proposed and assessed for each subprocess separately and in combination, A constructed simulatory design using an iterative process involving a construction model. This model starts with the logical organization of submitted tasks based on their cycle times. A subject-matter expert interview was conducted to determine the appropriateness and frequency of actions. The duration of each activity in the considered process was defined using a triangular distribution. Results The actual PET duration for the Medical Department was 15.3±6.4 (mean + SD) hours. The three most prolonged PET subprocess durations were in the referral to internal medicine, the decision to admit, and finding a free bed; these represent 17.9%, 53.8%, and 16.7% of the PET, respectively. Adding two physicians to each shift, which shortens the subprocess of the decision to admit, reduced the PET duration by 27.5%. Moreover, creating a new admitting team (unit) that takes care of new patients admitted to the ED reduced PET duration by another 12.5%. Combining these two scenarios reduced the average PET duration to only 10.2±0.5 hours. In addition to these scenarios, the PET can be further decreased to six hours by increasing the number of inpatient beds. Conclusions The simulated scenarios indicated that restructuring the medical teams, adding two physicians to each shift, and creating an admissions team dedicated to the ED would reduce the total PET duration to 10.2 hours, Furthermore, PET's further reduction to six hours is predictable by increasing the bed number.

Redistribution of Doctors and Decentralization of Clinics Improved Utilization of Services, Demand, and Capacity of Hamad Medical Corporation's Staff Clinic.

BACKGROUND:  The Staff Medical Clinic (SMC) of the Hamad Medical Corporation (HMC) serves the staff members who require healthcare services, but in a crowded environment, the SMC can only meet 75% of that demand. Overcrowding reduces productivity and service quality and increases waiting time. Furthermore, overcrowding in healthcare facilities decreases the experience and satisfaction of patients and healthcare providers. AIM: The main objective of this study was to use simulation modeling to evaluate interventions that could improve SMC waiting time and efficiency. METHOD:  Eighteen months of data on SMC patient flow, staffing, and clinical sessions were collected (January 2018 to June 2019). The patient's journey through the SMC was modeled as a series of processes with assigned durations defined mathematically using the appropriate probability distribution. A simulation flow model was developed considering the locations of the staff and nearby main hospital facilities. An intervention was proposed and evaluated through a simulation. The intervention involved redistributing 25% of the SMC staff into three main satellite clinics located at the facilities where most of the SMC patients came.  Results: The proposed intervention decreased crowding by 37%, reduced staffing requirements by 28%, and increased the number of patient slots by 22%, resulting in a net increase in the number of patients served by an average of 1250 monthly, without the need for hiring new additional staffing. CONCLUSION:  Redistribution of the available medical staff to three new satellite clinics reduces workload pressure at all sites and increases clinic capacity without additional costs.