The False Economy of Seeking to Eliminate Delayed Transfers of Care: Some Lessons from Queueing Theory.

BACKGROUND: It is a stated ambition of many healthcare systems to eliminate delayed transfers of care (DTOCs) between acute and step-down community services. OBJECTIVE: This study aims to demonstrate how, counter to intuition, pursual of such a policy is likely to be uneconomical, as it would require large amounts of community capacity to accommodate even the rarest of demand peaks, leaving much capacity unused for much of the time. METHODS: Some standard results from queueing theory-a mathematical discipline for considering the dynamics of queues and queueing systems-are used to provide a model of patient flow from the acute to community setting. While queueing models have a track record of application in healthcare, they have not before been used to address this question. RESULTS: Results show that 'eliminating' DTOCs is a false economy: the additional community costs required are greater than the possible acute cost saving. While a substantial proportion of DTOCs can be attributed to inefficient use of resources, the remainder can be considered economically essential to ensuring cost-efficient service operation. For England's National Health Service (NHS), our modelling estimates annual cost savings of £117m if DTOCs are reduced to the 12% of current levels that can be regarded as economically essential. CONCLUSION: This study discourages the use of 'zero DTOC' targets and instead supports an assessment based on the specific characteristics of the healthcare system considered.

Supporting COVID-19 elective recovery through scalable wait list modelling: Specialty-level application to all hospitals in England.

The recovery of elective waiting lists represents a major challenge and priority for the health services of many countries. In England's National Health Service (NHS), the waiting list has increased by 45% in the two years since the COVID-19 pandemic was declared in March 2020. Long waits associate with worse patient outcomes and can deepen inequalities and lead to additional demands on healthcare resources. Modelling the waiting list can be valuable for both estimating future trajectories and considering alternative capacity allocation strategies. However, there is a deficit within the current literature of scalable solutions that can provide managers and clinicians with hospital and specialty level projections on a routine basis. In this paper, a model representing the key dynamics of the waiting list problem is presented alongside its differential equation based solution. Versatility of the model is demonstrated through its calibration to routine publicly available NHS data. The model has since been used to produce regular monthly projections of the waiting list for every hospital trust and specialty in England.

Improvement in bladder function in children with functional constipation after a bowel management program.

PURPOSE: We sought to determine if children with functional constipation (FC) would have an improvement in bladder function with treatment of constipation with a bowel management program (BMP). METHODS: A single-institution review was performed in children aged 3-18 with FC who underwent a BMP from 2014 to 2020. Clinical characteristics, bowel management details, and the Vancouver Symptom Score for Dysfunctional Elimination Syndrome (VSS), Baylor Continence Scale (BCS), and Cleveland Clinic Constipation Score (CCCS) were collected. Data were analyzed using linear mixed effect modeling with random intercept. RESULTS: 241 patients were included with a median age of 9 years. Most were White 81 and 47% were female. Univariate tests showed improvement in VSS (- 3.6, P < 0.0001), BCS (- 11.96, P < 0.0001), and CCCS (- 1.9, P < 0.0001) among patients having undergone one BMP. Improvement was noted in VSS and CCCS among those with more than one BMP (VSS: - 1.66, P = 0.023; CCCS: - 2.69, P < 0.0001). Multivariate tests indicated undergoing a BMP does result in significant improvement in VSS, BCS, and CCCS (P < 0.0001). CONCLUSIONS: There is significant improvement in bladder function in children with FC who undergo a BMP. For patients with bowel and bladder dysfunction and FC, a BMP is a reasonable treatment strategy for lower urinary tract symptoms.

Modeling the Recovery of Elective Waiting Lists Following COVID-19: Scenario Projections for England.

OBJECTIVES: A significant indirect impact of COVID-19 has been the increasing elective waiting times observed in many countries. In England's National Health Service, the waiting list has grown from 4.4 million in February 2020 to 5.7 million by August 2021. The objective of this study was to estimate the trajectory of future waiting list size and waiting times up to December 2025. METHODS: A scenario analysis was performed using computer simulation and publicly available data as of November 2021. Future demand assumed a phased return of various proportions (0%, 25%, 50%, and 75%) of the estimated 7.1 million referrals "missed" during the pandemic. Future capacity assumed 90%, 100%, and 110% of that provided in the 12 months immediately before the pandemic. RESULTS: As a worst-case scenario, the waiting list would reach 13.6 million (95% confidence interval 12.4-15.6 million) by Autumn 2022, if 75% of missed referrals returned and only 90% of prepandemic capacity could be achieved. The proportion of patients waiting under 18 weeks would reduce from 67.6% in August 2021 to 42.2% (37.4%-46.2%) with the number waiting over 52 weeks reaching 1.6 million (0.8-3.1 million) by Summer 2023. At this time, 29.0% (21.3%-36.8%) of patients would be leaving the waiting list before treatment. Waiting lists would remain pressured under even the most optimistic of scenarios considered, with 18-week performance struggling to maintain 60%. CONCLUSIONS: This study reveals the long-term challenge for the National Health Service in recovering elective waiting lists and potential implications for patient outcomes and experience.

Pilot study of an adult bowel management program for fecal incontinence.

OBJECTIVE: Bowel management programs are efficacious in pediatric patients with fecal incontinence or intractable constipation unresponsive to standard treatment. No studies have been done examining outcomes in adults. The objective of this study was to assess continence and quality of life outcomes in adults who have underwent bowel management program. METHODS: A retrospective review of patients 16 or older at the time they underwent a bowel management program for fecal incontinence or constipation was performed. Data collected included intake and follow-up stool and urinary continence, patient-reported outcomes measures (Cleveland Clinic Constipation Score, Baylor Continence Scale, Vancouver Symptom Score for Dysfunctional Elimination), and an age-adjusted health-related quality of life measure. RESULTS: The cohort included 38 patients with a median age of 19 years (range: 16-55) when they underwent our program. 50% of patients were female and the majority (33, 87%) were White. The most common diagnosis was anorectal malformation (16, 42%) followed by functional constipation (10, 27%). Stool continence rates improved after undergoing the program (52.7% prior to 87.6% at follow-up, p<0.01). There was significant improvement in the Baylor Continence Scale, Cleveland Clinic Constipation Score, and PedsQL (p<0.05). CONCLUSIONS: Adult patients who underwent a bowel management program for severe fecal incontinence or constipation show significant improvement in stool continence rates, patient-reported outcomes measures, and quality of life. A bowel management program (in-person or via telemedicine) is a feasible treatment strategy for adult patients who fail standard management of fecal incontinence or constipation and should be offered when appropriate. LEVEL OF EVIDENCE: III.

Both sides of the screen: Provider and patient perspective on telemedicine in pediatric surgery.

BACKGROUND: There has been increased telemedicine use secondary to the COVID-19 pandemic. The objective of this study was to assess patient/parent satisfaction with their telemedicine experience, gauge provider perspective on telemedicine for the management of pediatric colorectal disease and evaluate the quality of telemedicine care being provided. METHODS: A cross sectional study was performed at a single institution from March 2020-February 2021. Patients who completed a patient/parent telemedicine survey after a telemedicine appointment and nurse practitioners/surgeons who completed a provider telemedicine survey were included. Patient and provider characteristics and responses were analyzed using descriptive statistics. Differences between the levels of provider confidence to provide telemedicine care were analyzed using Pearson's chi-square test. RESULTS: 118 patients/parents completed the survey. The median age of patients was 7 years. Most patients were male (59%) and White (73%). The most common diagnosis was anorectal malformation (49%). 71% of parents felt the telemedicine visit was as effective or better than an in-person visit and over 70% said they prefer a telemedicine visit to an in-person visit. Ten surgeons and 8 nurse practitioners completed the provider survey. 28% had previous telemedicine experience and 94% planned to continue offering telemedicine appointments. Providers felt significantly more confident performing clinical duties via video telemedicine compared to telephone telemedicine. CONCLUSIONS: Telemedicine is a useful adjunct or alternative in pediatric surgery for complex patients who require multidisciplinary care. Providers show confidence with the use of video telemedicine and parents show high satisfaction, with the majority preferring telemedicine visits over in-person visits. LEVEL OF EVIDENCE: IV.

Food Insecurity during COVID-Is Associated with Worse Outcomes among People with Type 2 Diabetes

Background: Low food security is associated with increased barriers to diabetes management, and COVID-has exacerbated food insecurity in the United States. This study assessed correlation between food insecurity and health outcomes among people with type 2 diabetes (T2D) during the first year of the COVID-pandemic from March 2020 to March 2021. Methods: In March 2021, 3,235 adults with T2D completed an online questionnaire which included the validated 2-item Hunger Vital Sign screening tool to assess risk of household food insecurity in the last 12 months. Health and demographic information were collected. Results: Twenty percent of the sample were at risk of food insecurity within the last 12 months. Those at risk of food insecurity were more likely to report adverse physical health outcomes and poor mental well-being. Disparities in outcomes between those at risk and those not at risk were present across household income brackets. Among those at risk of food insecurity, 35% reported spending less on food to be able to pay for diabetes medications or supplies in the last 12 months, whereas only 4% of those not at risk reported the same.

Optimising the balance of acute and intermediate care capacity for the complex discharge pathway: Computer modelling study during COVID-19 recovery in England.

OBJECTIVES: While there has been significant research on the pressures facing acute hospitals during the COVID-19 pandemic, there has been less interest in downstream community services which have also been challenged in meeting demand. This study aimed to estimate the theoretical cost-optimal capacity requirement for 'step down' intermediate care services within a major healthcare system in England, at a time when considerable uncertainty remained regarding vaccination uptake and the easing of societal restrictions. METHODS: Demand for intermediate care was projected using an epidemiological model (for COVID-19 demand) and regressing upon public mobility (for non-COVID-19 demand). These were inputted to a computer simulation model of patient flow from acute discharge readiness to bedded and home-based Discharge to Assess (D2A) intermediate care services. Cost-optimal capacity was defined as that which yielded the lowest total cost of intermediate care provision and corresponding acute discharge delays. RESULTS: Increased intermediate care capacity is likely to bring about lower system-level costs, with the additional D2A investment more than offset by substantial reductions in costly acute discharge delays (leading also to improved patient outcome and experience). Results suggest that completely eliminating acute 'bed blocking' is unlikely economical (requiring large amounts of downstream capacity), and that health systems should instead target an appropriate tolerance based upon the specific characteristics of the pathway. CONCLUSIONS: Computer modelling can be a valuable asset for determining optimal capacity allocation along the complex care pathway. With results supporting a Business Case for increased downstream capacity, this study demonstrates how modelling can be applied in practice and provides a blueprint for use alongside the freely-available model code.

Use of linked patient data to assess the effect of Long-COVID on system-wide healthcare utilisation.

Background: Within the relatively early stages of the COVID-19 pandemic, there had been an awareness of the potential longer-term effects of infection (so called Long-COVID) but little was known of the ongoing demands such patients may place on healthcare services. Objective: To investigate whether COVID-19 illness is associated with increased post-acute healthcare utilisation. Method: Using linked data from primary care, secondary care, mental health and community services, activity volumes were compared across the 3 months preceding and proceeding COVID-19 diagnoses for 7,791 individuals, with a distinction made between whether or not patients were hospitalised for treatment. Differences were assessed against those of a control group containing individuals who had not received a COVID-19 diagnosis. All data were sourced from the authors' healthcare system in South West England. Results: For hospitalised COVID-19 cases, a statistically significant increase in non-elective admissions was identified for males and females <65 years. For non-hospitalised cases, statistically significant increases were identified in GP Doctor and Nurse attendances and GP prescriptions (males and females, all ages); Emergency Department attendances (females <65 years); Mental Health contacts (males and females ≥65 years); and Outpatient consultations (males ≥65 years). Conclusion: There is evidence of an association between positive COVID-19 diagnosis and increased post-acute activity within particular healthcare settings. Linked patient-level data provides information that can be useful to understand ongoing healthcare needs resulting from Long-COVID, and support the configuration of Long-COVID pathways of care.

Modelling the effect of COVID-19 mass vaccination on acute hospital admissions.

BACKGROUND: Managing high levels of acute COVID-19 bed occupancy can affect the quality of care provided to both affected patients and those requiring other hospital services. Mass vaccination has offered a route to reduce societal restrictions while protecting hospitals from being overwhelmed. Yet, early in the mass vaccination effort, the possible impact on future bed pressures remained subject to considerable uncertainty. OBJECTIVE: The aim of this study was to model the effect of vaccination on projections of acute and intensive care bed demand within a 1 million resident healthcare system located in South West England. METHODS: An age-structured epidemiological model of the susceptible-exposed-infectious-recovered type was fitted to local data up to the time of the study, in early March 2021. Model parameters and vaccination scenarios were calibrated through a system-wide multidisciplinary working group, comprising public health intelligence specialists, healthcare planners, epidemiologists and academics. Scenarios assumed incremental relaxations to societal restrictions according to the envisaged UK Government timeline, with all restrictions to be removed by 21 June 2021. RESULTS: Achieving 95% vaccine uptake in adults by 31 July 2021 would not avert the third wave in autumn 2021 but would produce a median peak bed requirement ∼6% (IQR: 1-24%) of that experienced during the second wave (January 2021). A 2-month delay in vaccine rollout would lead to significantly higher peak bed occupancy, at 66% (11-146%) of that of the second wave. If only 75% uptake was achieved (the amount typically associated with vaccination campaigns), then the second wave peak for acute and intensive care beds would be exceeded by 4% and 19%, respectively, an amount which would seriously pressure hospital capacity. CONCLUSION: Modelling influenced decision-making among senior managers in setting COVID-19 bed capacity levels, as well as highlighting the importance of public health in promoting high vaccine uptake among the population. Forecast accuracy has since been supported by actual data collected following the analysis, with observed peak bed occupancy falling comfortably within the inter-quartile range of modelled projections.

Outcomes of a telemedicine bowel management program during COVID-19.

PURPOSE: Due to the COVID-19 pandemic, we transitioned from an in-person bowel management program (BMP) to a telemedicine BMP. The telemedicine BMP consisted of video and/or phone call visits (remote) or a single initial in-person visit followed by remote visits (hybrid). We hypothesized that patient/family satisfaction of a telemedicine BMP would be comparable to an in-person BMP and that there would be improvement in quality of life and functional outcomes after the telemedicine BMP. METHODS: After IRB approval, demographic and outcomes data were obtained for patients who underwent the telemedicine BMP from May-October 2020. Outcomes included a parent/patient satisfaction survey, Pediatric Quality of Life Inventory (PedsQL), and parent/patient-reported outcome measures (Vancouver, Baylor, and Cleveland scores) at baseline, 1 and 3 month follow-up. Variables were compared using Chi-square or Wilcoxon-Mann-Whitney tests and a generalized mixed model was used to evaluate outcomes scores at follow-up compared to baseline. RESULTS: Sixty-seven patients were included in our analysis with an average age of 8.6 years (SD: 3.9). Patients had the following diagnoses anorectal malformation (52.2%), Hirschsprung's disease (20.9%), functional constipation (19.4%), myelomeningocele (6.0%), and spinal injury (1.5%). Forty-eight patients (72%) underwent the remote BMP and 19 (28%) underwent the hybrid BMP. Sixty-two percent of parents completed the satisfaction survey, with a median score of 5 (very satisfied) for all questions. Over 75% of parents said they would prefer a telemedicine program over an in-person program. There was significant improvement in the Baylor and Vancouver scores after the BMP (p < 0.01), but no difference in the PedsQL or Cleveland scores (p > 0.05). There was a significant improvement in stool continence after the BMP (p < 0.01). CONCLUSION: A telemedicine BMP can be an acceptable alternative to a traditional in-person program. There was high parental/patient satisfaction and significant improvement in outcomes. Further research is needed to assess long-term outcomes. LEVEL OF EVIDENCE: III.

Projecting the effect of easing societal restrictions on non-COVID-19 emergency demand in the UK: Statistical inference using public mobility data.

While it is well established that societal restrictions have been effective in reducing COVID-19 emergency demand, evidence also suggests an impact upon emergency demand not directly related to COVID-19 infection. Hospital planning may benefit from a greater understanding of this association and the ability to reliably forecast future levels of non-COVID-19 demand. Activity data for Accident and Emergency (A&E) attendances and emergency admissions were sourced for all hospitals within the Bristol, North Somerset and South Gloucestershire healthcare system. These were regressed upon publicly available mobility data obtained from Google's Community Mobility Reports for the local area. Seasonal trends were controlled for using time series decomposition. The models were used to predict non-COVID-19 emergency demand under the UK Government's plan to sequentially lift all restrictions by 21 June 2021, in addition to three alternative hypothetical relaxation strategies. Rates of public mobility within the local area were shown to account for 77% and 65% of the variance in non-COVID-19 related A&E attendances and emergency admissions respectively. Modelling supports an increase in emergency demand in line with the level and timing of societal restrictions, with significant increases to be expected upon the ending of all legal limits. This study finds that non-COVID-19 emergency demand associates with the level of societal restrictions, with rates of public mobility representing a key determinant. Through predictive modelling, healthcare systems can improve their demand forecasting in effectively managing hospital capacity.

The impact of increased outpatient telehealth during COVID-19: Retrospective analysis of patient survey and routine activity data from a major healthcare system in England.

In response to societal restrictions due to the COVID-19 pandemic, a significant proportion of physical outpatient consultations were replaced with virtual appointments within the Bristol, North Somerset and South Gloucestershire healthcare system. The objective of this study was to assess the impact of this change in informing the potential viability of a longer-term shift to telehealth in the outpatient setting. A retrospective analysis was performed using data from the first COVID-19 wave, comprising 2998 telehealth patient surveys and 143,321 distinct outpatient contacts through both the physical and virtual medium. Four in five specialities showed no significant change in the overall number of consultations per patient during the first wave of the pandemic when telehealth services were widely implemented. Of those surveyed following virtual consultation, more respondents 'preferred' virtual (36.4%) than physical appointments (26.9%) with seven times as many finding them 'less stressful' than 'more stressful'. In combining both patient survey and routine activity data, this study demonstrates the importance of using data from multiple sources to derive useful insight. The results support the potential for telehealth to be rapidly employed across a range of outpatient specialities without negatively affecting patient experience.

Nowcasting for improved management of COVID-19 acute bed capacity

As the second wave of COVID-19 continues to push healthcare services to their limits, rapid and strategic planning has never been more important. Richard M Wood explains how statistical 'nowcasting' can be used to predict bed occupancy rates and help leaders to better manage acute capacity during this ongoing crisis.

The Value of Triage during Periods of Intense COVID-19 Demand: Simulation Modeling Study.

BACKGROUND: During the COVID-19 pandemic, many intensive care units have been overwhelmed by unprecedented levels of demand. Notwithstanding ethical considerations, the prioritization of patients with better prognoses may support a more effective use of available capacity in maximizing aggregate outcomes. This has prompted various proposed triage criteria, although in none of these has an objective assessment been made in terms of impact on number of lives and life-years saved. DESIGN: An open-source computer simulation model was constructed for approximating the intensive care admission and discharge dynamics under triage. The model was calibrated from observational data for 9505 patient admissions to UK intensive care units. To explore triage efficacy under various conditions, scenario analysis was performed using a range of demand trajectories corresponding to differing nonpharmaceutical interventions. RESULTS: Triaging patients at the point of expressed demand had negligible effect on deaths but reduces life-years lost by up to 8.4% (95% confidence interval: 2.6% to 18.7%). Greater value may be possible through "reverse triage", that is, promptly discharging any patient not meeting the criteria if admission cannot otherwise be guaranteed for one who does. Under such policy, life-years lost can be reduced by 11.7% (2.8% to 25.8%), which represents 23.0% (5.4% to 50.1%) of what is operationally feasible with no limit on capacity and in the absence of improved clinical treatments. CONCLUSIONS: The effect of simple triage is limited by a tradeoff between reduced deaths within intensive care (due to improved outcomes) and increased deaths resulting from declined admission (due to lower throughput given the longer lengths of stay of survivors). Improvements can be found through reverse triage, at the expense of potentially complex ethical considerations.

Estimating the COVID-19 epidemic trajectory and hospital capacity requirements in South West England: a mathematical modelling framework.

OBJECTIVES: To develop a regional model of COVID-19 dynamics for use in estimating the number of infections, deaths and required acute and intensive care (IC) beds using the South West England (SW) as an example case. DESIGN: Open-source age-structured variant of a susceptible-exposed-infectious-recovered compartmental mathematical model. Latin hypercube sampling and maximum likelihood estimation were used to calibrate to cumulative cases and cumulative deaths. SETTING: SW at a time considered early in the pandemic, where National Health Service authorities required evidence to guide localised planning and support decision-making. PARTICIPANTS: Publicly available data on patients with COVID-19. PRIMARY AND SECONDARY OUTCOME MEASURES: The expected numbers of infected cases, deaths due to COVID-19 infection, patient occupancy of acute and IC beds and the reproduction ('R') number over time. RESULTS: SW model projections indicate that, as of 11 May 2020 (when 'lockdown' measures were eased), 5793 (95% credible interval (CrI) 2003 to 12 051) individuals were still infectious (0.10% of the total SW population, 95% CrI 0.04% to 0.22%), and a total of 189 048 (95% CrI 141 580 to 277 955) had been infected with the virus (either asymptomatically or symptomatically), but recovered, which is 3.4% (95% CrI 2.5% to 5.0%) of the SW population. The total number of patients in acute and IC beds in the SW on 11 May 2020 was predicted to be 701 (95% CrI 169 to 1543) and 110 (95% CrI 8 to 464), respectively. The R value in SW was predicted to be 2.6 (95% CrI 2.0 to 3.2) prior to any interventions, with social distancing reducing this to 2.3 (95% CrI 1.8 to 2.9) and lockdown/school closures further reducing the R value to 0.6 (95% CrI 0.5 to 0.7). CONCLUSIONS: The developed model has proved a valuable asset for regional healthcare services. The model will be used further in the SW as the pandemic evolves, and-as open-source software-is portable to healthcare systems in other geographies.

The mixing of airborne contaminants by the repeated passage of people along a corridor

We report a series of experiments in which a cylinder, with a vertical axis, is moved back and forth along a long narrow channel containing fresh water at Reynolds numbers \(Re=3220\text {--}13\,102\). We examine the mixing of a cloud of dye along the channel by the oscillatory motion of the cylinder. Using light attenuation techniques to measure the time evolution of the concentration of dye along the channel, we find that at early times the concentration profile collapses to a Gaussian profile with dispersivity, \(D=(2.4\pm 0.5) fdW\), where \(f\) is the frequency of the cylinder oscillation, \(d\) is the diameter of the cylinder and \(W\) is the width of the channel, respectively. For times much longer than \(L

Population Health Management to identify and characterise ongoing health need for high-risk individuals shielded from COVID-19: a cross-sectional cohort study.

OBJECTIVES: To use Population Health Management (PHM) methods to identify and characterise individuals at high-risk of severe COVID-19 for which shielding is required, for the purposes of managing ongoing health needs and mitigating potential shielding-induced harm. DESIGN: Individuals at 'high risk' of COVID-19 were identified using the published national 'Shielded Patient List' criteria. Individual-level information, including current chronic conditions, historical healthcare utilisation and demographic and socioeconomic status, was used for descriptive analyses of this group using PHM methods. Segmentation used k-prototypes cluster analysis. SETTING: A major healthcare system in the South West of England, for which linked primary, secondary, community and mental health data are available in a system-wide dataset. The study was performed at a time considered to be relatively early in the COVID-19 pandemic in the UK. PARTICIPANTS: 1 013 940 individuals from 78 contributing general practices. RESULTS: Compared with the groups considered at 'low' and 'moderate' risk (ie, eligible for the annual influenza vaccination), individuals at high risk were older (median age: 68 years (IQR: 55-77 years), cf 30 years (18-44 years) and 63 years (38-73 years), respectively), with more primary care/community contacts in the previous year (median contacts: 5 (2-10), cf 0 (0-2) and 2 (0-5)) and had a higher burden of comorbidity (median Charlson Score: 4 (3-6), cf 0 (0-0) and 2 (1-4)). Geospatial analyses revealed that 3.3% of rural and semi-rural residents were in the high-risk group compared with 2.91% of urban and inner-city residents (p<0.001). Segmentation uncovered six distinct clusters comprising the high-risk population, with key differentiation based on age and the presence of cancer, respiratory, and mental health conditions. CONCLUSIONS: PHM methods are useful in characterising the needs of individuals requiring shielding. Segmentation of the high-risk population identified groups with distinct characteristics that may benefit from a more tailored response from health and care providers and policy-makers.