Triage of referrals in a child and adolescent mental health service in Qatar: reducing waiting times and promoting needs-based prioritisation.
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ABSTRACT:
SUBMITTER: Khan YS
PROVIDER: S-EPMC8314989 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveWe established a paediatric demand management (PDM) service in our paediatric department in 2017. The aim of this consultant-delivered service is to manage referrals more efficiently by providing active triage of all referrals, daily rapid access clinics and easily accessible advice for primary healthcare professionals. This study presents an evaluation of this service.DesignMixed-methods service evaluation with analysis of data for every contact with the PDM service over a 2-year period. For each patient, the method of contact, reason for contact, presenting complaint and triage outcome were recorded. Feedback from general practitioners (GPs) and patients was gathered.ResultsData were analysed for 7162 patients. More than a quarter (2034; 28%) of all referrals were managed with advice only. Of the 4703 outpatient clinic referrals, 1285 (27%) were managed without a clinic appointment. More than half (54%) of the requests for paediatric assessment unit (PAU) admission were managed alternatively, typically with advice only or a rapid access clinic appointment. This has reversed the increasing trend of PAU admissions from primary care of preceding years. Financial analysis suggested the avoidance of these clinic appointments, and PAU admissions provided a substantial cost saving.ConclusionsOur results indicate that the PDM service has succeeded in reducing unnecessary hospital attendances by managing patients more effectively and strengthening partnerships with primary care. The service has received overwhelmingly positive feedback from GPs. This service could be replicated in other Trusts and developed in the future to facilitate further management of paediatric cases in a primary care setting.
| S-EPMC7903069 | biostudies-literature
Project description:BackgroundPolicies assigning low-priority patients treatment delays for care, in order to make room for patients of higher priority arriving later, are common in secondary healthcare services today. Alternatively, each new patient could be granted the first available appointment. We aimed to investigate whether prioritisation can be part of the reason why waiting times for care are often long, and to describe how departments can improve their waiting situation by changing away from prioritisation.MethodsWe used patient flow data from 2015 at the Department of Otorhinolaryngology, Haukeland University Hospital, Norway. In Dynaplan Smia, Dynaplan AS, dynamic simulations were used to compare how waiting time, size and shape of the waiting list, and capacity utilisation developed with and without prioritisation. Simulations were started from the actual waiting list at the beginning of 2015, and from an empty waiting list (simulating a new department with no initial patient backlog).ResultsFrom an empty waiting list and with capacity equal to demand, waiting times were built 7 times longer when prioritising than when not. Prioritisation also led to poor resource utilisation and short-lived effects of extra capacity. Departments where prioritisation is causing long waits can improve their situation by temporarily bringing capacity above demand and introducing "first come, first served" instead of prioritisation.ConclusionA poor appointment allocation policy can build long waiting times, even when capacity is sufficient to meet demand. By bringing waiting times down and going away from prioritisation, the waiting list size and average waiting times at the studied department could be maintained almost 90% below the current level - without requiring permanent change in the capacity/demand ratio.
| S-EPMC7093047 | biostudies-literature
Project description:BackgroundConcern about long waiting times for elective surgeries is not a recent phenomenon, but it has been heightened by the impact of the COVID-19 pandemic and its associated measures. One way to alleviate the problem might be to use prioritisation methods for patients on the waiting list and a wide range of research is available on such methods. However, significant variations and inconsistencies have been reported in prioritisation protocols from various specialties, institutions, and health systems. To bridge the evidence gap in existing literature, this comprehensive systematic review will synthesise global evidence on policy strategies with a unique insight to patient prioritisation methods to reduce waiting times for elective surgeries. This will provide evidence that might help with the tremendous burden of surgical disease that is now apparent in many countries because of operations that were delayed or cancelled due to the COVID-19 pandemic and inform policy for sustainable healthcare management systems.MethodsWe searched PubMed, EMBASE, SCOPUS, Web of Science, and the Cochrane Library, with our most recent searches in January 2020. Articles published after 2013 on major elective surgery lists of adult patients were eligible, but cancer and cancer-related surgeries were excluded. Both randomised and non-randomised studies were eligible and the quality of studies was assessed with ROBINS-I and CASP tools. We registered the review in PROSPERO (CRD42019158455) and reported it in accordance with the PRISMA statement.ResultsThe electronic search in five bibliographic databases yielded 7543 records (PubMed, EMBASE, SCOPUS, Web of Science, and Cochrane) and 17 eligible articles were identified in the screening. There were four quasi-experimental studies, 11 observational studies and two systematic reviews. These demonstrated moderate to low risk of bias in their research methods. Three studies tested generic approaches using common prioritisation systems for all elective surgeries in common. The other studies assessed specific prioritisation approaches for re-ordering the waiting list for a particular surgical specialty.ConclusionsExplicit prioritisation tools with a standardised scoring system based on clear evidence-based criteria are likely to reduce waiting times and improve equitable access to health care. Multiple attributes need to be considered in defining a fair prioritisation system to overcome limitations with local variations and discriminations. Collating evidence from a diverse body of research provides a single framework to improve the quality and efficiency of elective surgical care provision in a variety of health settings. Universal prioritisation tools with vertical and horizontal equity would help with re-ordering patients on waiting lists for elective surgery and reduce waiting times.
| S-EPMC8404982 | biostudies-literature
Project description:This paper aims to analyse the variation in the delivery of diagnostic imaging services in order to suggest possible solutions for the reduction of waiting times, increase the quality of services and reduce financial costs. This study provides a logic model to manage waiting times in a regional context. Waiting times measured per day were compared on the basis of the variability in the use rates of CT and MRI examinations in Tuscany for the population, as well as on the basis of the capacity offered with respect to the number of radiologists available. The analysis was performed at the local health authority level to support the decision-making process of local managers. Diagnostic imaging services, in particular the CT and MRI examinations. The study involved all the 12 local health authorities that provide services for 3.7 million inhabitants of the Italian Tuscany Region. the study uses regional administrative data on outpatients and survey data on inpatient diagnostic examinations in order to measure productivity. The study uses the volumes per 1000 inhabitants, the days of waiting times and the number of examinations per radiologist. Variability was measured using the traditional SD measures. A significant variation in areas considered homogeneous in terms of age, gender or mortality may indicate that the use of radiological services is not optimal and underuse or overuse occurs and that there is room for improvement in the service organisation. Considering that there is a high level of variability among district use rates and waiting times, this study provides managers with a specific tool to find the cause of the problem, identify a possible solution, assess the financial impact and initiate the eventual reduction of waste.
| S-EPMC3533122 | biostudies-literature
Project description: Not available
| S-EPMC10835204 | biostudies-literature
Project description:In some jurisdictions, routine reporting of the estimated glomerular filtration rate (eGFR) has led to an increase in nephrology referrals and wait times.We describe the use of the Kidney Failure Risk Equation (KFRE) as part of a triage process for new nephrology referrals for patients with chronic kidney disease stages 3 to 5 in a Canadian province.A quasi-experimental study design was used.This study took place in Manitoba, Canada.Demographics, laboratory values, referral numbers, and wait times were compared between periods.In 2012, we adopted a risk-based cutoff of 3% over 5 years using the KFRE as a threshold for triage of new referrals. Referrals who did not meet other prespecified criteria (such as pregnancy, suspected glomerulonephritis, etc) and had a kidney failure risk of <3% over 5 years were returned to primary care with recommendations based on diabetes and hypertension guidelines. The average wait time and number of consults seen between the pretriage (January 1, 2011, to December 31, 2011) and posttriage period (January 1, 2013, to December 31, 2013) were compared using a general linear model.In the pretriage period, the median number of referrals was 68/month (range: 44-76); this increased to 94/month (range: 61-147) in the posttriage period. In the posttriage period, 35% of referrals were booked as urgent, 31% as nonurgent, and 34% of referrals were not booked. The median wait times improved from 230 days (range: 126-355) in the pretriage period to 58 days (range: 48-69) in the posttriage period.We do not have long-term follow-up on patients triaged as low risk. Our study may not be applicable to nephrology teams operating under capacity without wait lists. We did not collect detailed information on all referrals in the pretriage period, so any differences in our pretriage and posttriage patient groups may be unaccounted for.Our risk-based triage scheme is an effective health policy tool that led to improved wait times and access to care for patients at highest risk of progression to kidney failure.
| S-EPMC5555495 | biostudies-other
Project description:PurposeTo examine whether survivorship care planning (receipt of written treatment summary or instructions for follow-up care) is associated with unmet needs among adolescent and young adult (AYA) cancer survivors (aged 15-39 at diagnosis).MethodsWe used data from the 2010 LIVESTRONG Survey for People Affected by Cancer. Outcome variables were survivor reports of unmet needs, including information on late effects of cancer treatment, fertility issues, cancer recurrence, and family cancer risk. We used multivariable logistic regression models to determine whether receipt of either a treatment summary or follow-up care instructions was associated with each unmet needs after controlling for sociodemographic and cancer history factors.ResultsOf the AYA respondents (N = 1395), only 30% reported receipt of a written treatment summary and 86% received instructions for follow-up care. The most commonly reported unmet need was addressing recurrence concerns (80%), followed by information on late effects (78%), family risk of cancer (51%), and fertility information (45%). In multivariable analyses, receipt of a written treatment summary was associated with lower odds of having unmet needs about late effects information (odds ratio; OR = 0.51 [0.37-0.71]) and recurrence concerns (OR = 0.55 [0.39-0.79]). Receipt of follow-up care instructions was associated with lower odds of unmet needs about late effects information (OR = 0.29 [0.15-0.58]) and fertility information (OR = 0.62 [0.42-0.91]).ConclusionsSurvivorship care planning including written treatment summaries and follow-up care instructions may help reduce unmet information and service needs of AYA survivors. This study provides further evidence for the importance of survivorship care planning as a way to improve survivor outcomes.
| S-EPMC5467130 | biostudies-literature
Project description:BackgroundAntenatal care (ANC) provides a range of critical health services during pregnancy that can improve maternal and neonatal health outcomes. In Mozambique, only half of women receive four or more ANC visits, which are provided for free at public health centers by maternal and child health (MCH) nurses. Waiting time has been shown to contribute to negative client experiences, which may be a driver of low maternity care utilization. A recent pilot study of a program to schedule ANC visits demonstrated that scheduling care reduces waiting time and results in higher rates of complete ANC. This study aims to explore client experiences with waiting time for ANC in standard practice and care and after the introduction of appointment scheduling.MethodsThis study uses a series of qualitative interviews to unpack client experiences with ANC waiting time with and without scheduled care, in order to better understand the impact of waiting time on client experiences. Thirty-eight interviews were collected in May to June 2017 at three pilot study clinics in southern Mozambique, with a focus on two paired intervention and comparison facilities sharing similar facility characteristics. Data were analyzed using inductive thematic analysis methods using NVivo software.ResultsClients described strong motivations to seek ANC, pointing to the need to address convenience of care, and highlighted direct and indirect costs of seeking care that were exacerbated by long waiting times. Direct costs include time and transport costs of going to the clinic, while indirect costs include being unable to fulfill household and work obligations. Other barriers to complete ANC utilization of four or more visits include transport costs, negative provider experiences, and delayed ANC initiation, which limit the potential number of clinic contacts.ConclusionsFindings demonstrate that the scheduling intervention improves the client experience of seeking care by allowing women to both seek ANC and fulfill other productive obligations. Innovation in healthcare delivery should consider adapting models that minimize waiting times.
| S-EPMC6670125 | biostudies-literature
Project description:BackgroundGlobally, reduction of patient waiting time has been identified as one of the major characteristics of a functional health system. In South Africa, 83% of the general population visiting primary healthcare (PHC) facilities must contend with long waiting times, overcrowding, staff shortages, poor quality of care, an ineffective appointment booking system, and a lack of medication. These experiences may, in turn, affect how patients view service quality.MethodsThis scoping review was guided by Arksey and O'Malley methodological framework. The primary literature search of peer-reviewed and review articles was achieved through PubMed/MEDLINE, Google Scholar, Science Direct, and World Health Organization (WHO) library databases, using waiting times, outpatient departments, factors, interventions, and primary healthcare facilities as keywords. Two independent reviewers screened abstracts and full articles, using the set inclusion and exclusion criteria. We used NVIVO® version 10 software to facilitate thematic analysis of the results from included studies.ResultsFrom the initial 250 records screened, nine studies were eligible for inclusion in this scoping review. Seven papers identified the factors contributing to waiting time, and five papers mentioned effective interventions implemented to reduce waiting times within PHC facilities. Our analysis produced three (patient factors, staff factors, and administrative systems) and two (manual-based waiting time reduction systems and electronic-based waiting time reduction systems) main themes pertaining to factors contributing to long waiting times and interventions to reduce waiting times, respectively.ConclusionOur results revealed that the patients, staff, and administrative systems all contribute to long waiting times within the PHC facilities. Patient waiting times recorded a wider and more evenly spread patient arrival pattern after the identified interventions in our study were implemented. There is a need to constantly strategize on measures such as implementing the use of an electronic appointment scheduling system and database, improving staff training on efficient patient flow management, and regularly assessing and optimizing administrative processes. By continuously monitoring and adapting these strategies, PHC facility managers can create a more efficient and patient-centered healthcare experience.
| S-EPMC11338458 | biostudies-literature
Project description:BackgroundPrioritisation instruments were developed for patients on waiting list for hip and knee arthroplasties (AI) and cataract surgery (CI). The aim of the study was to assess their convergent and discriminant validity and inter-observer reliability.MethodsMulticentre validation study which included orthopaedic surgeons and ophthalmologists from 10 hospitals. Participating doctors were asked to include all eligible patients placed in the waiting list for the procedures under study during the medical visit. Doctors assessed patients' priority through a visual analogue scale (VAS) and administered the prioritisation instrument. Information on socio-demographic data and health-related quality of life (HRQOL) (HUI3, EQ-5D, WOMAC and VF-14) was obtained through a telephone interview with patients. The correlation coefficients between the prioritisation instrument score and VAS and HRQOL were calculated. For the reliability study a self-administered questionnaire, which included hypothetic patients' scenarios, was sent via postal mail to the doctors. The priority of these scenarios was assessed through the prioritisation instrument. The intraclass correlation coefficient (ICC) between doctors was calculated.ResultsCorrelations with VAS were strong for the AI (0.64, CI95%: 0.59-0.68) and for the CI (0.65, CI95%: 0.62-0.69), and moderate between the WOMAC and the AI (0.39, CI95%: 0.33-0.45) and the VF-14 and the CI (0.38, IC95%: 0.33-0.43). The results of the discriminant analysis were in general as expected. Inter-observer reliability was 0.79 (CI95%: 0.64-0.94) for the AI, and 0.79 (CI95%: 0.63-0.95) for the CI.ConclusionThe results show acceptable validity and reliability of the prioritisation instruments in establishing priority for surgery.
| S-EPMC2373288 | biostudies-literature