Rationing Out-Patients: A Defence of the Waiting List

SummaryNew psychiatric out-patients were offered immediate or delayed appointments (average delay 12 weeks) in random order. The two groups thus formed, comprising 234 patients, were shown to be comparable in some important respects. Immediate appointments were taken up significantly more frequently than delayed appointments, and 12 per cent of immediate and 22 per cent of delayed patients did not receive any psychiatric service. No evidence was found that delay increased other medical services supplied. Non-attenders were presumed to suffer from ‘neurosis’ and ‘personality problem’. Initial attenders used more services than those who failed to keep their first appointment but came later. A waiting list is proposed as a screening device to limit out-patient referrals.

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The orthopaedic waiting list crisis

Bone & Joint Open ◽

10.1302/2633-1462.27.bjo-2021-0044.r1 ◽

2021 ◽

Vol 2 (7) ◽

pp. 530-534

Author(s):

Matthew Hampton ◽

Ella Riley ◽

Naren Garneti ◽

Alexander Anderson ◽

Kevin Wembridge

Keyword(s):

Primary Care ◽

Secondary Care ◽

Waiting Lists ◽

Waiting List ◽

Retrospective Data ◽

Day Case ◽

Number Of Patients ◽

Robust Planning ◽

Therapy Services ◽

Patient Referrals

Aims Due to widespread cancellations in elective orthopaedic procedures, the number of patients on waiting list for surgery is rising. We aim to determine and quantify if disparities exist between inpatient and day-case orthopaedic waiting list numbers; we also aim to determine if there is a ‘hidden burden’ that already exists due to reductions in elective secondary care referrals. Methods Retrospective data were collected between 1 April 2020 and 31 December 2020 and compared with the same nine-month period the previous year. Data collected included surgeries performed (day-case vs inpatient), number of patients currently on the orthopaedic waiting list (day-case vs inpatient), and number of new patient referrals from primary care and therapy services. Results There was a 52.8% reduction in our elective surgical workload in 2020. The majority of surgeries performed in 2020 were day case surgeries (739; 86.6%) with 47.2% of these performed in the independent sector on a ‘lift and shift’ service. The total number of patients on our waiting lists has risen by 30.1% in just 12 months. As we have been restricted in performing inpatient surgery, the inpatient waiting lists have risen by 73.2%, compared to a 1.6% rise in our day-case waiting list. New patient referral from primary care and therapy services have reduced from 3,357 in 2019 to 1,722 in 2020 (49.7% reduction). Conclusion This study further exposes the increasing number of patients on orthopaedic waiting lists. We observed disparities between inpatient and day-case waiting lists, with dramatic increases in the number of inpatients on the waiting lists. The number of new patient referrals has decreased, and we predict an influx of referrals as the pandemic eases, further adding to the pressure on inpatient waiting lists. Robust planning and allocation of adequate resources is essential to deal with this backlog. Cite this article: Bone Jt Open 2021;2(7):530–534.

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Invite Your Friend and You’ll Move Up in Line: Optimal Design of Referral Priority Programs

Manufacturing & Service Operations Management ◽

10.1287/msom.2020.0868 ◽

2020 ◽

Author(s):

Luyi Yang

Keyword(s):

Optimal Design ◽

Queuing Theory ◽

Problem Definition ◽

Waiting List ◽

System Throughput ◽

Market Size ◽

Customer Acquisition ◽

Average Delay ◽

Managerial Implications ◽

First In First Out

Problem definition: This paper studies the optimal design of referral priority programs, in which customers on a waiting list can jump the line by inviting their friends to also join the waiting list. Academic/practical relevance: Recent years have witnessed a growing presence of referral priority programs as a novel customer-acquisition strategy for firms that maintain a waiting list. Different variations of this scheme are seen in practice, raising the question of what should be the optimal referral priority mechanism. Methodology: I build an analytical model that integrates queuing theory into a mechanism design framework in which the objective of the firm is to maximize the system throughput, that is, accelerate customer acquisition as much as possible. Results: My analysis shows that the optimal mechanism has one of the following structures: full priority; partial priority; first in, first out (FIFO); and strategic delay. A full-priority (partial-priority) scheme enables referring customers to get ahead of all (only some) nonreferring ones. A FIFO scheme does not provide any priority-based referral incentive. A strategic-delay scheme grants full priority to referring customers but artificially inflates the delay of nonreferring ones. I show that FIFO is optimal if either the base-market size or the referral cost is large. Otherwise, partial priority is optimal if the base-market size is above a certain threshold; full priority is optimal at the threshold base-market size; strategic delay is optimal if the base-market size is below the threshold. I also find that referrals motivate the firm to maintain a larger capacity and therefore can surprisingly shorten the average delay, even though more customers sign up and strategic delay is sometimes inserted. Managerial implications: My paper provides prescriptive guidance for launching an optimal referral priority program and rationalizes common referral schemes seen in practice.

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Psychiatric In-Patients and Out-Patients

The British Journal of Psychiatry ◽

10.1192/bjp.120.557.474-c ◽

1972 ◽

Vol 120 (557) ◽

pp. 474-475

Author(s):

A. G. Mezey

Keyword(s):

General Hospital ◽

Hospital Admissions ◽

Psychiatric Service ◽

Admission Rate ◽

District General Hospital ◽

The Elderly ◽

Referral Rate ◽

Official Statistics ◽

Cent Increase ◽

Patient Referrals

The reply of Morgan and Compton in this issue of the Journal (pp. 433–6), is based on a misunderstanding of our results and of the problem investigated. This leads them into a refutation of ‘claims' never made and they buttress it with a statistical exercise of great naivety. Our findings were:(a) ‘… in certain important respects in-patients and out-patients are derived from different though overlapping populations.’ The most marked differences (dismissed by Morgan and Compton as 'slight’) were found among the elderly. ‘The admission rate for the over 65s of both sexes was 4 · 90 per 1,000. In contrast, increasing age was associated with a gradual fall of out-patient referral rate to 1 · 60 for the over 65s.’ We did not claim to have demonstrated the cause of these differences, but mentioned possible reasons for them.(b) In a district general hospital-centied psychiatric service we observed a 34 per cent increase of new out-patient referrals while hospital admissions remained static; this occurred over a period of three years, when nationally hospital admissions were still rising. We quoted in illustration some extreme figures from official statistics and the figures for the Sheffield and the Liverpool regions were extreme whether one refers to Tables 3, 11 or 13 (1). This prompted the hypothesis that an increase in new out-patient referrals can prevent admission or prove an alternative to it. No ‘claim’ was made, and we advisedly used the term 'suggestion’ to emphasize that these are ‘no more than tentative and incomplete incursions into this difficult and relatively unexplored field’ (2).

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Psychiatric Clinics in Different Settings

The British Journal of Psychiatry ◽

10.1192/bjp.153.2.243 ◽

1988 ◽

Vol 153 (2) ◽

pp. 243-245 ◽

Cited By ~ 9

Author(s):

C. Bruce Low ◽

Ian Pullen

Keyword(s):

Primary Care ◽

Psychiatric Service ◽

Case Register ◽

Primary Care Clinics ◽

Psychiatric Case Register ◽

Psychiatric Case ◽

Patient Referrals

Out-patient referrals to the Edinburgh adult psychiatric service between 1981 and 1985 were studied using the Edinburgh Psychiatric Case Register. The hypotheses that primary-care clinics have more patients with less severe illnesses and fewer patients with psychotic illnesses were confirmed.

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Pathway to Service and Duration of Untreated Attention Deficit, Hyperactivity Disorder among Children Presented to a Governmental, Mental Health Hospital in Egypt

QJM ◽

10.1093/qjmed/hcab102.005 ◽

2021 ◽

Vol 114 (Supplement_1) ◽

Author(s):

Hisham Ahmed Ramy ◽

Reem Elsayed Hashem ◽

Marwa Esameldin Khamis ◽

Aya Alaa Said Abdelaziz

Keyword(s):

Mental Health ◽

Help Seeking ◽

Psychiatric Service ◽

Cross Sectional Study ◽

Average Delay ◽

Cross Sectional ◽

Hyperactivity Disorder ◽

Stigma Of Mental Illness ◽

Mental Health Hospital ◽

Health Hospital

Abstract Background ADHD is one of the most common neurodevelopmental disorders. Despite the presence of evidence based approved diagnosing and treatment tools for ADHD, there still is an underdiagnoses and underutilization of these services. Untreated ADHD, unlike what some families may believe, doesn’t go away on its own, in fact, the condition may get worse with age, affecting more domains of the child’s life as an adolescent and later on as an adult. In addition, untreated ADHD impacts not only the patient, but also the family and the society as a whole. Objective to investigate different routes that parents take before reaching the child and adolescence psychiatric services. And to further explore various reasons for any delay in seeking psychiatric help. In addition we aimed to estimate the duration of untreated ADHD before patients receive proper psychiatric service and treatment. Patients and Methods A total of 350 cases were recruited in a cross sectional study that took place at the Child and Adolescence outpatient clinic at Abbassia mental health hospital in Cairo, Egypt. Results Results showed that the average delay in seeking Child and Adolescence psychiatric service and the duration of untreated ADHD was 3±2 years. The majority of parents, 27.1%, first consulted pediatricians as regards to their child’s symptoms. The most commonly reported source of referral was school teachers in 23.1%. The most distressing symptom stated by 28.1% of parents was impulsivity. Stigma of mental illness was the most frequently reported reason for delay in reaching out for psychiatric service. Conclusion we concluded that parents tend to take other routes through different professions before reaching Child and Adolescence Mental Health Services, this causes subsequent delay in receiving diagnosis and treatment for ADHD. In Addition, it was concluded that sociocultural beliefs affected parent’s pattern of help seeking.

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Socio-economic deprivation and psychiatric referral and admission rates – an ecological study in one London borough

Psychiatric Bulletin ◽

10.1192/pb.26.5.175 ◽

2002 ◽

Vol 26 (5) ◽

pp. 175-178 ◽

Cited By ~ 4

Author(s):

G. Mustafa Soomro ◽

Tom Burns ◽

Azeem Majeed

Keyword(s):

Service Provision ◽

Ecological Study ◽

Practice Nurse ◽

Psychiatric Service ◽

Referral Rates ◽

Admission Rates ◽

Patient Admissions ◽

Or Practice ◽

Patient Referrals ◽

Relevant Factors

AIMS AND METHODWe retrospectively investigated the association between the Jarman and Townsend indices of deprivation and referral rates to community mental health teams (CMHTs) and in-patient admissions rates, including the contribution of general practice factors to these rates. The samples consisted of all community/out-patient referrals and admissions to four CMHTs over 1 year.RESULTSLow positive correlation was found between community/out-patient referral rates for all diagnoses and psychosis with the Jarman index, and between both the indices and admission rates for all diagnoses and non-psychosis. Referrals from general practitioners (GPs) varied nearly 40-fold and were not related to either indices, fundholding status or having practice manager or practice nurse.CLINICAL IMPLICATIONSOverall, the Jarman index appears to be a more useful index for planning psychiatric service provision. However, because of the small correlation with referral and admission rates, deprivation indices in themselves would be of limited value, as there may be other relevant factors that require investigating. GP characteristics investigated did not predict referral rates.

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