Wait Times Research Articles

Minimizing the Total Waiting Time for Fuzzy Two-Machine Flow Shop Scheduling Problem with Uncertain Processing Time

تتضمن الجدولة تخصيص الموارد للوظائف ضمن قيود محددة مع مرور الوقت. تقليديا، كان وقت المعالجة لكل مهمة يعتبر قيمة ثابتة. ومع ذلك، في السيناريوهات العملية، يمكن أن تتقلب أوقات معالجة الوظائف ديناميكيًا بناءً على الظروف السائدة. في هذه المقالة، يتم تقديم أسلوب جديد لمشكلة جدولة متجر التدفق الضبابي (FSSP) في بيئة غامضة، حيث يتم تمثيل أوقات معالجة الوظيفة بأرقام غامضة شبه منحرفة. بالإضافة إلى ذلك، تم اقتراح وتطوير خوارزمية جديدة تعتمد على نهج جويال لـ FSSP المكون من جهازين مع أوقات معالجة غامضة. وفي الوقت نفسه، تم تعزيز الخوارزمية الموجودة لتحسين أدائها في هذا السياق المحدد. تهدف الدراسة إلى تقليل إجمالي وقت الانتظار للوظائف. يتم استخدام وظيفة إزالة الضبابية لترتيب الأرقام الغامضة، بهدف نهائي هو تقليل إجمالي وقت الانتظار. علاوة على ذلك، يقوم المقال بتقييم أداء هذه الأساليب من حيث جودة الحلول، وذلك باستخدام مشاكل الاختبار مع 10، 20، 30، 40، 50، 60، 80، 90، 100، 120، 200، 250، 300، و 500 وظيفة، جنبا إلى جنب مع 2 آلات. تتم مقارنة متوسط ​​إجمالي وقت الانتظار بالخوارزميات الموجودة، بما في ذلك خوارزمية NEH، وطريقة Palmer، وطريقة Johnson، وB. Goyal وB. Kaur، والخوارزمية المقترحة. بالإضافة إلى ذلك، فإن النتائج التي تم الحصول عليها، إلى جانب اختبار ANOVA جيد التنظيم، تسلط الضوء على فعالية الطريقة المقترحة في معالجة مشكلة الجدولة قيد التحقيق. توضح النتائج التجريبية أن الخوارزمية المقترحة يمكنها تقليل وقت الانتظار بشكل فعال في FSSP ثنائي الجهاز وتحقيق نتائج متفوقة بالمقارنة مع الخوارزميات المختلفة الموجودة.

Revived Role of Pulmonary Artery Band in Management of Heart Failure in Pediatric Dilated Cardiomyopathy.

Lack of appropriate durable Ventricular Assist Devices (VADs) that can be managed at home for very young children, and long wait times for transplant have led to search for alternate easily reproducible therapies. In the past decade or more, pulmonary artery banding (PAB), as a new indication of an old technology, has been gradually carried out worldwide as an alternative to mechanical circulatory support in children with end-stage left ventricular dilated cardiomyopathy (DCM) complicated with heart failure(HF), and has achieved encouraging early and mid-term outcomes. Technically, PAB is simple, safe, and effective. This is a promising therapeutic strategy, especially in developing countries where heart transplantation is difficult to implement. As a transition before transplantation, and even a potential treatment, PAB brings more options and hope for children with heart failure who are waiting for transplantation and are refractory to drug therapy. This article reviews the past and current situation, the mechanism, the surgical timing, and application prospect of PAB in the treatment of DCM complicated with heart failure.

Statistical Analysis of Telehealth Use and Pre- and Postpandemic Insurance Coverage in Selected Health Care Specialties in a Large Health Care System in Arkansas: Comparative Cross-Sectional Study.

The COVID-19 pandemic triggered policy changes in 2020 that allowed insurance companies to reimburse telehealth services, leading to increased telehealth use, especially in rural and underserved areas. However, with many emergency rules ending in 2022, patients and health care providers face potential challenges in accessing these services. This study analyzed telehealth use across specialties in Arkansas before and after the pandemic (2017-2022) using data from electronic medical records from the University of Arkansas for Medical Sciences Medical Center. We explored trends in insurance coverage for telehealth visits and developed metrics to compare the performance of telehealth versus in-person visits across various specialties. The results inform insurance coverage decisions for telehealth services. We used pre- and postpandemic data to determine the impacts of the COVID-19 pandemic and changes in reimbursement policies on telehealth visits. We proposed a framework to calculate 3 appointment metrics: indirect waiting time, direct waiting time, and appointment length. Statistical analysis tools were used to compare the performance of telehealth and in-person visits across the following specialties: obstetrics and gynecology, psychiatry, family medicine, gerontology, internal medicine, neurology, and neurosurgery. We used data from approximately 4 million in-person visits and 300,000 telehealth visits collected from 2017 to 2022. Our analysis revealed a statistically significant increase in telehealth visits across all specialties (P<.001), showing an 89% increase from 51,589 visits in 2019 to 97,461 visits in 2020, followed by a 21% increase to 117,730 visits in 2021. Around 92.57% (134,221/145,001) of telehealth patients from 2020 to 2022 were covered by Medicare, Blue Cross and Blue Shield, commercial and managed care, Medicaid, and Medicare Managed Care. In-person visits covered by Medicare and Medicaid decreased by 15%, from 313,196 in 2019 to 264,696 in 2022. During 2020 to 2022, about 22.84% (33,123/145,001) of total telehealth visits during this period were covered by Medicare and 53.58% (86,317/161,092) were in psychiatry, obstetrics and gynecology, and family medicine. We noticed a statistically significant decrease (P<.001) in the average indirect waiting time for telehealth visits, from 48.4 to 27.7 days, and a statistically significant reduction in appointment length, from 93.2 minutes in 2020 to 39.59 minutes in 2022. The indirect waiting time for psychiatry telehealth visits was almost 50% shorter than that for in-person visits. These findings highlight the potential benefits of telehealth in providing access to health care, particularly for patients needing psychiatric care. Reverting to prepandemic regulations could negatively affect Arkansas, where many live in underserved areas. Our analysis shows that telehealth use remained stable beyond 2020, with psychiatry visits continuing to grow. These findings may guide insurance and policy decisions in Arkansas and other regions facing similar access challenges.

Improved access and care through the implementation of virtual Hallway, a consultation platform in Nova Scotia: preliminary findings from a feasibility evaluation

BackgroundWhile previous studies have examined various platforms that enable providers to connect, Virtual Hallway (VH) stands out with its unique features. The value add is that this online platform connects primary care providers and specialists for synchronous phone-based conversations and aims to reduce referrals and enhance the quality of referrals. VH allows providers to easily log in, select the required specialty, book call times, receive reminders, and have calls documented, ensuring a high connection rate. In May 2022, the provincial health authority in Nova Scotia, a Canadian province, and VH initiated a feasibility study facilitated through the Health Innovation Hub in Nova Scotia. The goal was to enable primary care providers to connect with specialists, thereby reducing wait times and unnecessary referrals, and facilitating timely access to relevant clinical direction for patients. The current evaluation assessed utilization, value for money in economic analysis, and consultation experiences.MethodsThe study used post, cross-sectional, and cost-benefit study designs. We collected data through various methods, including administratively recorded utilization, theory-driven surveys, and cost data. Utilization was measured by the number of completed consults and the number of healthcare professionals using the VH platform. We analyzed the data using a combination of descriptive statistics and a cost-benefit analysis, which also involved conducting probabilistic sensitivity analysis.ResultsThe study found that approximately 84% of the VH consultations avoided needing in-person specialist referrals. The return on investment was 1.8 (95% CI: 0.8 to 3.0), indicating that the monetary value of the measurable benefits associated with VH exceeded the value of the resources invested. The provider experience survey revealed high satisfaction levels with VH across user groups, with 92% of specialists and 96% of primary care providers reporting being satisfied or highly satisfied with their experience. These positive indicators of provider experience were further supported by the fact that 97% of respondents agreed or strongly agreed that they intended to continue to use VH in their practice, and 97% of respondents agreed or strongly agreed that they would recommend VH to a colleague.ConclusionsThe study suggests that VH was well-received by users, with high levels of satisfaction reported and a reduced need for in-person referrals. It also represented value for money. Further research could explore how the availability of virtual health services can lead to reduced utilization of healthcare resources among different groups of patients.

Using artificial intelligence and machine learning to reduce patient wait times and increase patient satisfaction.

Madam, Prolonged patient waiting time has long been a significant source of dissatisfaction among patients. Waiting time has been recognized by WHO as one of the key elements of a responsive healthcare system [1]. A study conducted by Bleustein et al. suggested that longer wait times negatively impacted the patient’s confidence in the care provider and the perceived quality of care.[2] Furthermore, in large hospital settings, patients are expected to queue up multiple times before meeting with their physician, which amplifies their stress. We would like to highlight that the incorporation of artificial intelligence (AI) in healthcare can help reduce patient and physician stress. Strategies such as telemedicine and online registration have been acquired in efforts to resolve this issue but these techniques may burden doctors with extra responsibilities. However, introducing an AI-based physician assistance programme, which was able to model itself on the decision-making requirements of the doctor significantly reduced the wait time and the burden on the hospital [3]. Xiaoqing Li et al developed an AI-based model that helped patients automatically order any investigations. Implementation of the model reduces waiting time while also playing a pivotal role in creating alternative methods to improve patient flow. [4] The results of these studies prove that implementation of an AI-based model in daily medicine has helped improve patient experience and minimize hospital burden. The implementation of AI in place of traditional methods, helps enhance patient satisfaction by not only significantly reducing waiting time but also ensuring that patients receive care appropriate to their condition. Moreover, it helps reduce, the workload on the physician and enables them to focus more on the patient. Being a new concept in healthcare AI may not be free of error. This might lead to inaccuracies in medication prescription, investigations, imaging, scheduling of appointments and diagnosis in atypical cases. Patient confidentiality is also an extremely important aspect of healthcare and in an attempt to protect the privacy of the patients, AI models may not have free reign over the patients’ data which may prevent them from assisting in medical practices. Furthermore, there are no organizations that customize the AI models according to the needs of the individual hospital or clinic. Moreover, human interaction is a critical aspect of healthcare which would be significantly impacted by the use of AI which could result in patients being unable to express themselves or feeling a sense of apathy. Furthermore, developing countries are not well equipped to implement AI in daily practice, hence it would not be a practical solution for them. [5] Further research needs to be conducted with regards to the use of AI models in hospitals to understand how they impact patient wait times and satisfaction, alongside their ability to optimize healthcare.

Discharge communication during transitions from emergency care to home.

The healthcare system in Canada is overwhelmed and requires reform. Good discharge communication is a cornerstone of patient safety and quality care. In the Emergency Department (ED), good discharge communications means that patients leave with a clear understanding of their health condition, and the steps they need to take to continue their recovery at home. The fragmented nature of communication in the ED coupled with long wait times and high noise levels pose significant risks to the continuity of information exchange. Additional communication barriers arise for many patients due to a lack of control, language differences, low health literacy, and feelings of fear and uncertainty. Multiple interventions have been evaluated to improve ED discharge communication, but further work is needed to engage all end users in a theory-based approach. Addressing challenges related to successful discharge communication requires a multifaceted approach that includes improving institutional policies, adopting innovative co-designed interventions, and leveraging technology.

How accurately can supervised machine learning model predict a targeted psychiatric disorder?

BackgroundHoarding disorder (HD) is characterized by a compulsion to collect belongings, and to experience significant distress when parting from them. HD is often misdiagnosed for several reasons. These include patient and family lack of recognition that it is a psychiatric disorder and professionals’ lack of relevant expertise with it. This study evaluates the ability of a supervised machine learning (ML) model to match the diagnostic skills of psychiatrists when presented with equivalent information pertinent to symptoms of HD.MethodsFive hundred online participants were randomly recruited and completed the Hoarding Rating Scale-Self Report (HRS-SR) and the Generalized Anxiety Disorder 7-item (GAD-7) scale. Responses to the questionnaires were read by an ML model. Responses to the HRS-SR were then converted into anonymized, random-equivalent texts. Each of these individual texts was presented in random order to two experienced psychiatrists who were independently asked for a provisional diagnosis - e.g.; the presence or absence of HD. In case of disagreement between the two assessors, a third psychiatrist broke the tie. A decision tree classification model was employed to predict clinical HD using self-report data from two psychological tests, the HRS-SR and GAD-7. The target variable was whether a participant had clinical HD, while the predictive variables were the continuous scores from the HRS-SR and GAD-7 tests. The model’s performance was evaluated using a confusion matrix, which compared the observed diagnoses with the predicted diagnoses to assess accuracy.ResultsAccording to the psychiatrists, approximately 10% of the participants fulfilled DSM-5 diagnostic criteria for HD. 93% of the clinician-identified cases were identified by the ML model based on HRS-SR and GAD-7 scores. A decision tree plot model demonstrated that about 60% of the cases could be detected by the HRS-SR alone while the rest required a combination of HRS-SR and GAD-7 scores. ML evaluation metrics showed satisfactory performance, with a Matthews Correlation Coefficient of 55%; Area Under Curve (AUC), 79%; a Negative Predictive Value of 76%; and a False Negative Rate of 24%.ConclusionsStudy findings strongly suggest that ML can, in the future, play a significant role in the risk assessment of psychiatric disorders prior to face-to-face consultation. By using AI to scan big data questionnaire responses, wait time for seriously ill patients can be substantially cut, and prognoses substantially improved.

Implementation of K-Nearest Neigbors for Prediction of Motorcycle Service Waiting Times in Develop Tech

This research examines the application of the K-Nearest Neighbors (KNN) algorithm to predict wait times at Develop Tech, a workshop that offers affordable services but has longer spare parts wait times compared to official workshops. The research method used is descriptive quantitative, involving data collection and processing. In this study, the KNN algorithm is utilized to predict wait times by measuring distances between data points using and performing voting based on the K value to determine the final prediction. Testing on 100 data points demonstrated that KNN could predict wait times very accurately, achieving 100% accuracy, precision, and recall at certain K values. The data was split into 80% for training and 20% for testing, a method commonly used in machine learning research to ensure a balance between training data and validation. The results indicate that the KNN algorithm is reliable for predicting wait times with optimal performance at K values between 3 and 10. These findings support the conclusion that the KNN algorithm functions effectively in predicting wait times at the workshop.

Pediatric pain physician workforce: an assessment of supply and demand.

Many youth with pain lack access to pediatric pain expertise. There is a critical shortage of pediatric pain physicians, due partly to a paucity of training programs in Pediatric Pain Medicine. Pain fellowships are Anesthesiology-based and there is no pathway to fellowship training or Pain Medicine board certification for pediatricians. This workforce assessment sought to examine the current state of Pediatric Pain Medicine in the United States and future interest in pursuing Pain Medicine among pediatricians. A multidisciplinary working group of Pain Medicine clinicians designed three surveys to examine pediatric comprehensive pain programs in the US, practice patterns of pediatricians and their motivations and opinions regarding Pain Medicine board certification, and current residents' exposure to and interest in Pediatric Pain Medicine. Wait times for initial evaluations are two months or longer for two-thirds of responding centers, and barriers to increase staff size and resources were reported, including an inadequate number of trained or available physicians. Pediatricians expressed interest in earning board certification in Pain Medicine, given the opportunity. Additionally, there is interest among pediatric residents in pursuing Pediatric Pain Medicine, and qualitative data highlight information residents perceived needing in order to pursue a career in the field. Results demonstrate the need for increased training opportunities in pediatric pain medicine. A formal pathway to Pain Medicine for Pediatricians should be developed to increase the potential workforce and to address the lack of trained pediatric pain specialists, thereby improving access to care for youth with pain.

Improving Patient Wait Times on the First Day of Radiotherapy Treatment

Long wait times on starting day of radiotherapy (day 1) can cause dissatisfaction among both patients and healthcare providers. Reducing these wait times will decrease stress and decongest hospital facilities especially in current coronavirus disease 2019 times. A multidisciplinary core team was formed during the Stanford-India Collaborative Quality Improvement training to reduce the median wait times on day 1 of treatment from 6 to 4.5 hours (a 25% reduction). Several factors were identified on the fishbone diagram, and key causes were identified using a Pareto chart and action prioritization matrix. The Plan-Do-Study-Act Cycle strategy was undertaken for the identified interventions. The outcome measure was time from arrival at the hospital to entry into a treatment room. Data were obtained from time charts at various stations and electronic records. The secondary measures were visual analog scale (VAS) scores, 80th percentile wait times, and the day-2 delay percentage. The balancing measure was “new errors” due to interventions. The interventions included the completion of all administrative tasks not needing patients' presence on the day before day 1. Baseline data from 198 patients and postintervention data from 160 patients were compared and analyzed. The median wait time at baseline, which was 6 hours, was reduced to 4.2 hours. The VAS score showed 70.4, 67.7, and 71.9% satisfaction for the resident physician, therapists, and patients, respectively. The 80th percentile wait times reduced from 8 to 5.7 hours; and the day 2 starting rate decreased from 22.5 to 2.04%, with no new errors reported. Radiotherapy day 1 wait times can be safely decreased, leading to improved satisfaction among patients and healthcare providers, by utilizing classic quality improvement methods and tools.

American emergency room wait times for psychiatric conditions from 2019 to 2021

Use of Emergency Departments (EDs) for psychiatric complaints has increased significantly in past decades. The onset of the COVID-19 pandemic saw large shifts in ED usage, with a relative increase in mental health complaints in EDs. This paper will investigate the difference in ED wait times for psychiatric and non-psychiatric complaints over this period. Utilized National Hospital Ambulatory Medical Care Survey (NHAMCS), from 2019 to 2021, for average wait times for psychiatric versus non-psychiatric complaints. Compared the average wait times for psychiatric complaints by region, triage status, and ICD-10 F code. There was no significant difference in the average wait times overall between these conditions (P = 0.57). People with schizophrenia or psychosis had a significantly higher wait time (P = 0.03) compared to mental health symptoms secondary to physiologic conditions. Northeastern American EDs also had prolonged wait times for psychiatric conditions (P &lt; 0.01) Research into factors of prolonged wait times can advise quality improvements such as the implementation of evidence-based triage and workup tools, and directed psychiatric education.

The Intersecting Time, Administrative and Financial Burdens of a Cancer Diagnosis.

Cancer and its care create substantial financial, time, and administrative burdens both for patients and their loved ones. While cancer-related financial burdens have been well documented in the past decade, time and administrative burdens of cancer care have received substantially less attention. We define time burdens as the burden patients and caregivers experience due to the time needed to complete cancer-related treatment and tasks that take away from other life responsibilities. Relatedly, we conceptualize administrative burdens as those burdens patients and caregivers experience due to cancer-related, resource-consuming bureaucratic and logistical tasks. Finally, financial hardship can be conceptualized as problems patients experience related to the cost of medical care. These burdens do not exist in isolation; time, administrative, and financial burdens intersect with and compound each other. Currently, we have limited evidence-based measures on the objective (e.g., scheduling time, transportation, wait time) and subjective (e.g., mental, emotional and physical stress) measures of time and administrative burden. We have even more limited evidence of the risk factors for and outcomes from increased time and administrative burdens, and how they differentially impact populations across social and demographic groups. In this commentary, we present a research agenda to map, measure, evaluate, and mitigate the time, administrative, and financial burdens of cancer and its care.

First Contact Physiotherapy: A 4-Year Service Evaluation of UK Primary Care Data.

The First Contact Physiotherapist (FCP) role offers patients direct access to musculoskeletal (MSK) specialists in primary care settings and is designed to reduce GP workload while providing high-quality care. Despite positive early evaluations of FCP services, there remains a need for up-to-date assessments of their impact. To evaluate the FCP model of care implemented in an NHS Primary Care Network (PCN) against pre-defined service objectives. A service evaluation was conducted using data from April 2020 to March 2024. Key performance indicators were based on national FCP evaluation criteria. Data included appointment utilisation, wait times, referral patterns, patient and staff satisfaction surveys, and audit results from clinical data. Over 4years, 12,185 patients were seen. Of these, 69% of patients were seen as true first contacts. The majority of patients (86.4%) were managed within primary care, with a referral rate of 8.5% to outpatient physiotherapy and 5.1% to orthopaedics. Patient satisfaction was high, with 82% rating their FCP experience as excellent or outstanding. The FCP service successfully met its objectives by reducing GP workload and providing effective care. However, there was an increase in outpatient physiotherapy referrals over the 4-year period. Staff satisfaction was generally positive, though some highlighted concerns about appointment duration and workload. This evaluation demonstrates that FCP services provide a viable solution for managing MSK conditions in primary care. Future research should explore the most effective MSK service delivery models and incorporate digital solutions for comprehensive outcome and experience measures.

SIMULTANEOUS VERSUS STAGED TOTAL HIP ARTHROPLASTY FOLLOWING ACETABULAR FRACTURE FIXATION: A COMPARISON OF OUTCOMES

Acetabular fractures present a challenge. Anatomical reduction can be achieved by open reduction and internal fixation (ORIF). However, in elderly patients with complex fracture patterns and osteoporotic bone stock, “fix and replace” has become an option in the management of these injuries. This involves ORIF of the acetabulum to enable insertion of a press fit cup and subsequent cemented femoral stem at the index surgery.A Retrospective analysis of all operatively managed acetabular fractures by a regional Pelvic and Acetabular Trauma service (01/01/2018-30/05/2023) STATA used for analysis. 34 patients undergoing “fix and replace” surgery. Of the 133 patients managed with ORIF, 21 subsequently required Total Hip Arthroplasty (THA). Mean follow up was 2.7 years versus 5.1. There was no statistical significance between the two groups with regards to BMI or sex. Mean age in the “fix and replace” group was 68 compared to 48 in the ORIF and subsequent THA group. This reached statistical significance between the two groups (p=0.001).ASA and Charlson Comorbidity Index (3 and 3 in “fix and replace” and 2 and 1.2 in ORIF to THA group) and Charlson Comorbidity Index both were statistically significantly different (p=0.006 and p=0.027, respectively). High energy mechanism of injury accounted for 56% of the “fix and replace” group compared to 48% in the ORIF to THA. 74% of “fix and replace” were associated fractures compared to 53% of ORIF to THA. Wait to surgery was 3 days for “fix and replace” while 186 days was the mean wait time from listing to THA for the ORIF to THA group. Complication rate was 41% versus 43% in the two groups. 14% in the ORIF to THA group developed PJI versus 6% in “fix and replace”.Fix and replace allows early mobilisation in frailer, elderly patients. Our results show fewer returns to theatre and less PJI in patients having arthroplasty as part of “fix and replace” than subsequent to Open reduction internal fixation.

Hospital to community in Wales: What is the value of optometrists playing a greater role in managing neovascular AMD and glaucoma in primary care?

To evaluate the value of enhanced optometric services for managing neovascular age-related macular degeneration (nAMD) and glaucoma in primary care optometry services, instead of hospital eye services (HES). Seven enhanced optometric service pathways in primary care in Wales were assessed with a mixed-methods approach: three for nAMD and four for glaucoma. The methods were a patient-related experience measure (PREM), a Realist Review and Evaluation involving both patients and staff, a discrete event simulation model estimating the economic impact of the pathways and a workforce survey of optometrists to gauge capability and capacity. Patient-related experience measure responses (802) indicated that primary care experience was comparable to that of HES. Utilising enhanced optometric services in primary care resulted in reduced wait times compared with HES, with suspected nAMD shortened to 4-5 days and glaucoma monitoring to 5 days. Waiting lists were dramatically reduced with primary care-based services to just three people waiting for nAMD and five for glaucoma, compared with 216 and 5691 people, respectively, in HES. Consultant ophthalmologist time was reduced from 57% to 15%-16% for nAMD services and from 48% to 22%-23% for glaucoma services. Integrating enhanced optometric services into primary care incurred a similar cost. The workforce survey confirms that optometrists possess the skills and qualifications and are willing to deliver these enhanced optometric services. The Realist Review and Evaluation revealed that clear patient communication, effective coordination and strong interprofessional communication between optometrists and ophthalmologists along with a shared electronic record are crucial to the success of this change. Providing enhanced optometric services in primary care for nAMD and glaucoma brings substantial benefits for the UK National Health Service and patients, including reduced waiting times, waiting lists and released HES capacity. The success of this transition hinges on clear patient communication, administrative co-ordination and effective interprofessional communication.

Churning the tides of care: when nurse turnover makes waves in patient access to primary care

BackgroundTeam-based primary care (PC) enhances the quality of and access to health care. The Veterans Health Administration (VHA) implements team-based care through Patient Aligned Care Teams (PACTs), consisting of four core members: a primary care provider, registered nurse (RN) care manager, licensed vocational nurse, and scheduling clerk. RNs play a central role: they coordinate patient care, manage operational needs, and serve as a patient point of contact. Currently, it is not known how varying levels of RN staffing on primary care teams impact patient outcomes.ObjectiveThis study aims to empirically assess how the stability of RN staffing within team-based primary care affects patient access to care.MethodsA retrospective database review using clinical and administrative data from the VHA over 24 months. Participants included 5,897 PC PACTs across 152 VHA healthcare facilities in the United States and its territories. The stability of personnel in the RN role was categorized as: RN continuous churn, RN staffing instability and RN vacancy. All 3 categories were compared to teams with RN stability (i.e., same person in the role for the entire 24-month period). Access measures included: average third-next-available appointment, established patient average wait time in days, urgent care utilization, emergency room utilization, and total inbound-to-outbound PC secure messages ratio.ResultsRN continuous churn within PACTs had a significant impact on third-next-available appointment (b = 3.70, p < 0.01). However, RN staffing instability and vacancy had no significant relationship with any of the access measures. Several risk adjustment variables, including team full-time equivalency, team stability, relative team size, and average team size, were significantly associated with access to health care.ConclusionsTeams are impacted by churn on the team. Adequate staffing and team stability significantly predict patient access primary care services. Healthcare organizations should focus on personnel retention and strategies to mitigate the impact(s) of continuous RN turnover. Future research should examine the relative impact of turnover and stability of other roles (e.g., clerks) and how team members adapt to personnel changes.

Utilisation of maternal healthcare services and influencing factors in public health facilities in Addis Ababa, Ethiopia.

Ethiopian maternal mortality remains high, despite the implementation of extensive health programmes. This indicates that the full potential of maternal health services is not being effectively utilised. This study aimed to evaluate the utilisation and factors influencing maternal healthcare services in public health facilities in Addis Ababa. This study was conducted in five public hospitals and 10 public health centres of Addis Ababa city administration from 31st August 2023 to 13th October 2023. The study's design utilised a cross-sectional quantitative technique, which involved interviewing 354 women from each group who received visits throughout their pregnancy, delivery and postpartum period. The data were analysed using SPSS version 26. This study analysed maternal health service utilisation indicators, revealing a 70.8% overall utilisation of services, with antenatal care (ANC) at 85.5%, delivery at 71.58% and family planning services (PNC) at 55.4%. The study found that the length of time spent travelling to public health facilities significantly impacts the use of maternal health services. Pregnant women who travelled less than 30 min used services 2.29 times more than those over 2 h. The average client wait time also influenced service usage. Pregnant women with four or more prenatal care visits were more likely to use services. The study conducted in Addis Ababa's capital city revealed that the utilisation of maternity health care services is not optimal, despite the concentrated resources. The findings of the study could be beneficial for the Addis Ababa Health Bureau, Ministry of Health, legislators, and other stakeholders. It can help in the development of affordable intervention programmes, filling knowledge gaps and updating scientific understanding.

Day case laparoscopic cholecystectomy: a review of patient selection factors and identification of potential barriers to same-day discharge.

Day-case laparoscopic cholecystectomy (DCLC) is a useful tool for minimizing hospital admissions and prolonged presurgical wait times in suitable patient cohorts. There have been many international studies to support this finding and an increasing interest has grown in implementation in Australia. This review aims to provide clarity how to best implement this tool in gallbladder disease patient demographic. This literature review evaluates studies on day-case cholecystectomy procedures, focusing on patient factors, procedural aspects, surgical morbidity, and systemic implications. It explores inclusion and exclusion criteria for day-case suitability, factors influencing same-day discharge, reasons for hospital admission, pain management, patient quality of life, patient satisfaction, and cost implications. DCLC, when selected judiciously, is a safe alternative to overnight stay procedures for cholecystectomy with comparable surgical outcomes and patient satisfaction, affirming its viability. Strict patient selection criteria can aid in optimizing the successful implementation procedure, reducing unexpected admissions and readmissions and we have demonstrated useful criteria for guidance in establishing day-case laparoscopic cholecystectomy protocol at a hospital.

Current Capacity for Diagnosing Alzheimer's Disease in Germany and Implications for Wait Times.

Amyloid-targeting therapies for Alzheimer's disease (AD) might become available in Germany soon. The combination of a large pool of prevalent cases and a complex diagnostic process to determine eligibility for these treatments is likely to challenge health systems' capacity. To analyze Germany's healthcare system capacity to identify treatment-eligible patients in a timely and equitable manner. We modeled patients' diagnostic journey and projects wait times due to capacity constraints for AD specialist visits and PET scans from 2024 to 2043. Model parameters were derived from published data and expert input. Wait times would be ∼50 months over the model horizon, if patients were referred to specialists based on a brief cognitive assessment in primary care. Wait times for patients with social health insurance are projected to be 1.9 times those of patients with private insurance, with peak wait times of around 76 and 40 months, respectively. Adding a blood test for the AD pathology as additional triage step would reduce wait times to below 24 months. In spite of having a well-resourced health system, Germany is projected to be unable to cope with the demand for biomarker-based AD diagnosis, if a disease-modifying AD treatment were introduced. As these treatments might become available by the end of 2024, decisive action, in particular dissemination of high-performing AD blood tests for triage in primary care, will be needed to prevent delays in access and potentially avoidable and inequitable disease progression.

Experiences of abortion care in Australia: a qualitative study examining multiple dimensions of access

BackgroundThe United Nations’ Sustainable Development Goals identify universal access to sexual and reproductive health services as a global priority. Yet barriers to abortion access remain, including legal restrictions, cost, stigma, and limited services and information. The aim was to identify barriers to and facilitators of abortion care access experienced in Australia.MethodsThis qualitative phenomenological study examined abortion access in Australia, where abortion is decriminalised, from March 2020 to December 2022. We used social media and flyers in clinics to recruit adults who had sought abortion care, then interviewed them in-depth. We mapped participant experiences to five dimensions of access identified by Levesque et al.’s patient-centred access to healthcare framework: approachability, acceptability, availability and accommodation, affordability, and appropriateness.ResultsThe 24 participants lived across Australia and sought abortion during the COVID-19 pandemic. Approachability: Before seeking abortion, most did not know where to access information about the service and where to obtain it. Acceptability: Many were uncomfortable disclosing their abortion to family or friends; they reported that healthcare providers demonstrated varying levels of support. Availability and accommodation: Regional participants travelled far and faced long wait-times, exacerbated by pandemic restrictions. Affordability: Participants described financial stress paying for the service, travel, and related expenses. Appropriateness: Most participants expected judgemental care. Experiences varied widely: many participants experienced unempathetic, rushed, or judgemental interactions with healthcare staff, and many also reported at least one non-judgmental and supportive interaction on the same pathway to care.DiscussionAbortion seekers experienced varying obstacles when seeking care. The findings illustrate the need for population- and system-level initiatives such as: providing accurate information about and normalising abortion; implementing system-level strategies to reduce wait times, travel, and costs, especially for rural populations; and developing regulatory and quality improvement initiatives to increase the workforce and its readiness to provide high-quality, non-judgemental abortion care. Challenges seeking care during pandemic restrictions illustrate the importance of social support during care and choice between abortion modalities and service types. Consumer voices can help understand the diverse pathways to abortion care and inform solutions to overcome the multidimensional barriers to access.