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Booked inpatient admissions and hospital capacity: mathematical modelling study.

ABSTRACT: OBJECTIVES:To investigate the variability of patients' length of stay in intensive care after cardiac surgery. To investigate potential interactions between such variability, booked admissions, and capacity requirements. DESIGN:Mathematical modelling study using routinely collected data. SETTING:A cardiac surgery department. SOURCE OF DATA:Hospital records of 7014 people entering intensive care after cardiac surgery. MAIN OUTCOME MEASURES:Length of stay in intensive care; capacity requirements of an intensive care unit for a hypothetical booked admission system. RESULTS:Although the vast majority of patients (89.5%) had a length of stay in intensive care of < or = 48 hours, there was considerable overall variability and the distribution of stays has a lengthy tail. A mathematical model of the operation of a hypothetical booking system indicates that such variability has a considerable impact on intensive care capacity requirements, indicating that a high degree of reserve capacity is required to avoid high rates of operation cancellation because of unavailability of suitable postoperative care. CONCLUSION:Despite the considerable enthusiasm for booked admissions systems, queuing theory suggests that caution is required when considering such systems for inpatient admissions. Such systems may well result in frequent operational difficulties if there is a high degree of variability in length of stay and where reserve capacity is limited. Both of these are common in the NHS.

SUBMITTER: Gallivan S

PROVIDER: S-EPMC65062 | biostudies-literature | 2002 Feb

REPOSITORIES: biostudies-literature

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Booked inpatient admissions and hospital capacity: mathematical modelling study.

Gallivan Steve S Utley Martin M Treasure Tom T Valencia Oswaldo O

BMJ (Clinical research ed.) 20020201 7332

<h4>Objectives</h4>To investigate the variability of patients' length of stay in intensive care after cardiac surgery. To investigate potential interactions between such variability, booked admissions, and capacity requirements.<h4>Design</h4>Mathematical modelling study using routinely collected data.<h4>Setting</h4>A cardiac surgery department.<h4>Source of data</h4>Hospital records of 7014 people entering intensive care after cardiac surgery.<h4>Main outcome measures</h4>Length of stay in int ...[more]

PMID: 11823362

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Project description:ObjectivesTo 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.DesignOpen-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.SettingSW at a time considered early in the pandemic, where National Health Service authorities required evidence to guide localised planning and support decision-making.ParticipantsPublicly available data on patients with COVID-19.Primary and secondary outcome measuresThe 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.ResultsSW 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).ConclusionsThe 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.

Project description:BackgroundConsequences of reduced acute coronary syndrome (ACS) admissions during COVID-19 pandemic periods were reported by different countries. However, admissions, treatments, and prognosis of ACS during and after COVID-19 pandemic in Beijing, China was unknown.MethodsInformation on ACS admissions and heart failure (HF) admission were identified from database of Beijing Municipal Health Commission Information Center. Study period was defined as December 1, 2019 to June 30, 2020, and control period was defined as December 1, 2018 to June 30, 2019. Numbers of admission for HF during the control period, the study period, and seven months after study period were compared to evaluate the consequence of changed ACS care during the COVID-19 pandemic.FindingsAdmissions for ST-elevation myocardial infarction (STEMI), Non-ST-elevation myocardial infarction (Non-STEMI), and unstable angina (UAP) reduced by 38·0%, 41·0%, and 63·3% (N = 1953, 1991, 7664 between January 24, 2020 to June 30, 2020 vs. N = 3150, 3373, and 20,868 between January 24, 2019 to June 30, 2019) in study period. Percutaneous coronary intervention performed within 24 h were significantly more frequent during study period in patients with STEMI (37·9% vs. 31·7%, P<0·0001), but significantly less frequent in patients with Non-STEMI (7·9% vs. 9·5%, P = 0·049), and in patients with UAP (1·7% vs. 3·5%, P<0·0001). In-hospital mortality rates in patients with ACS were similar during the study period and the control period (3·1% vs 2·5%, P = 0·174 for STEMI; 2·7% vs 2·3%, P = 0·429 for Non-STEMI; 0·2% vs 0·1%, P = 0·222 for UAP). A fall by 23.9% for HF admissions was also observed during the seven months following the study period than equivalent period in 2019.InterpretationDuring COVID-19 pandemic, ACS admissions reduced significantly in Beijing; however, increase of HF admissions was not observed within seven months post-pandemic period, implying the pandemic didn't deteriorate the short-term prognosis for ACS.Fundingthe National Natural Science Foundation of China (82,103,904), the National Key Research and Development Program of China (Grant number: 2020YFC2004803).

Project description:BackgroundPulmonary alveolar proteinosis (PAP) is a rare clinical syndrome involving the accumulation of lipid-rich proteinaceous material in the alveoli. There is a paucity of published studies on this condition. To better characterize the demographics, complication rates, mortality, and healthcare costs of patients hospitalized for PAP in the United States, a secondary analysis on the Hospital Cost and Utilization Project's Nationwide Inpatient Sample (NIS) was performed on patients admitted from 2012 to 2014 with a diagnosis of pulmonary alveolar proteinosis.MethodsUsing the NIS database, a secondary analysis was performed on 500 admissions with the diagnosis "pulmonary alveolar proteinosis." The clinical variables and outcome measures extracted were: patient demographics, hospital costs, length of stay, frequency of admissions, and inpatient mortality rate.ResultsAmong a weighted estimate of 500 hospital admissions from 2012 to 2014, the number of PAP admissions averaged 4.7 per million. The population was predominantly male (55%) with a mean age of 41.45 (CI 38.3-44.5) from all socioeconomic levels. Inpatient mortality was calculated to be 5%, which may result from the fact that the majority of admitted patients had few or no comorbid conditions (CCI 0.72). The most common procedure performed during admission was a bronchoalveolar lavage. Mean length of stay was 6.2 days (CI 3.9-8.5) and average cost of admission was $29,932.20 (CI 13,739-46,124). Of note, 50% of these admissions were considered "elective."ConclusionsDemographics of patients with PAP who have been hospitalized in the United States are similar to previously reported demographics from prior patient cohorts, specifically a male predominance and a mean age in the 40 s. The inpatient mortality rate of 5% we found is consistent with prior studies demonstrating good disease-specific survival rates. Notably, the cost per admission and overall annual cost associated with PAP hospitalization was calculated to be $29932.20 and $5 million respectively. This reflects the high economic cost associated with hospitalization of PAP patients, and provokes thought about ways to make treatment more cost-effective.

Project description:BackgroundA second wave of COVID-19 cases in autumn, 2020, in England led to localised, tiered restrictions (so-called alert levels) and, subsequently, a second national lockdown. We examined the impact of these tiered restrictions, and alternatives for lockdown stringency, timing, and duration, on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and hospital admissions and deaths from COVID-19.MethodsWe fit an age-structured mathematical model of SARS-CoV-2 transmission to data on hospital admissions and hospital bed occupancy (ISARIC4C/COVID-19 Clinical Information Network, National Health Service [NHS] England), seroprevalence (Office for National Statistics, UK Biobank, REACT-2 study), virology (REACT-1 study), and deaths (Public Health England) across the seven NHS England regions from March 1, to Oct 13, 2020. We analysed mobility (Google Community Mobility) and social contact (CoMix study) data to estimate the effect of tiered restrictions implemented in England, and of lockdowns implemented in Northern Ireland and Wales, in October, 2020, and projected epidemiological scenarios for England up to March 31, 2021.FindingsWe estimated a reduction in the effective reproduction number (Rt) of 2% (95% credible interval [CrI] 0-4) for tier 2, 10% (6-14) for tier 3, 35% (30-41) for a Northern Ireland-stringency lockdown with schools closed, and 44% (37-49) for a Wales-stringency lockdown with schools closed. From Oct 1, 2020, to March 31, 2021, a projected COVID-19 epidemic without tiered restrictions or lockdown results in 280 000 (95% projection interval 274 000-287 000) hospital admissions and 58 500 (55 800-61 100) deaths. Tiered restrictions would reduce hospital admissions to 238 000 (231 000-245 000) and deaths to 48 600 (46 400-50 700). From Nov 5, 2020, a 4-week Wales-type lockdown with schools remaining open-similar to the lockdown measures announced in England in November, 2020-was projected to further reduce hospital admissions to 186 000 (179 000-193 000) and deaths to 36 800 (34 900-38 800). Closing schools was projected to further reduce hospital admissions to 157 000 (152 000-163 000) and deaths to 30 300 (29 000-31 900). A projected lockdown of greater than 4 weeks would reduce deaths but would bring diminishing returns in reducing peak pressure on hospital services. An earlier lockdown would have reduced deaths and hospitalisations in the short term, but would lead to a faster resurgence in cases after January, 2021. In a post-hoc analysis, we estimated that the second lockdown in England (Nov 5-Dec 2) reduced Rt by 22% (95% CrI 15-29), rather than the 32% (25-39) reduction estimated for a Wales-stringency lockdown with schools open.InterpretationLockdown measures outperform less stringent restrictions in reducing cumulative deaths. We projected that the lockdown policy announced to commence in England on Nov 5, with a similar stringency to the lockdown adopted in Wales, would reduce pressure on the health service and would be well timed to suppress deaths over the winter period, while allowing schools to remain open. Following completion of the analysis, we analysed new data from November, 2020, and found that despite similarities in policy, the second lockdown in England had a smaller impact on behaviour than did the second lockdown in Wales, resulting in more deaths and hospitalisations than we originally projected when focusing on a Wales-stringency scenario for the lockdown.FundingHorizon 2020, UK Medical Research Council, and the National Institute for Health Research.

Project description:It is important that actual outcomes of care and not surrogate markers, such as process measures, be used to evaluate the quality of inpatient care. Because of the heterogenous composition of patients, risk-adjustment is essential for the objective evaluation of outcomes following inpatient care. Comparative evaluation of risk-adjusted outcomes can be used to identify suboptimal performance and can provide direction for care improvement initiatives.We studied the risk-adjusted outcomes of 6 medical conditions during the inpatient and 90-day post-discharge period to identify the opportunities for care improvement. The Medicare Limited Dataset for 2012 to 2014 was used to identify acute myocardial infarction (AMI), chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), pneumonia (PNEU), cerebrovascular accidents (CVA), and gastrointestinal hemorrhage (GIH). Stepwise logistic predictive models were developed for the adverse outcomes (AOs) of inpatient deaths, 3-sigma prolonged length-of-stay outliers, 90-day post-discharge deaths, and 90-day readmissions after unrelated events were excluded. Observed and predicted AOs were determined for each hospital with ?75 cases for each of the 6 medical conditions. Z-scores and risk-adjusted AO rates for each hospital permitted comparative analysis of outcomes after adjusting for covariance among the medical conditions.There were a total of 1,811,749 patients from 973 acute care hospitals with the 6 medical conditions. A total of 41% of all patients had ?1 AO events. One or more readmissions were identified in 29.8% of patients. A total of 64 hospitals (6.4%) were 2 standard deviations better than the mean for risk-adjusted outcomes, and 72 (7.4%) were 2 standard deviations poorer. The best performing decile of hospitals had mean AO rates of 35.1% (odds ratio?=?0.766; 95% confidence interval (CI) CI: 0.762-0.771) and the poorest performing decile a mean AO rate of 48.5% (odds ratio?=?1.357; 95% CI: 1.346-1.369). Volume of qualifying cases ranged from 670 to 9314; no association was identified for increased volume of patients (P?<?.40).Risk-adjusted AO rates demonstrated nearly a 14% opportunity for care improvement between top and suboptimal performing hospitals. Hospitals must be able to benchmark objective measurement of outcomes to inform quality initiatives.

Project description:IntroductionPlasmodium knowlesi is now recognised as a leading cause of malaria in Malaysia. As humans come into increasing contact with the reservoir host (long-tailed macaques) as a consequence of deforestation, assessing the potential for a shift from zoonotic to sustained P. knowlesi transmission between humans is critical.MethodsA multi-host, multi-site transmission model was developed, taking into account the three areas (forest, farm, and village) where transmission is thought to occur. Latin hypercube sampling of model parameters was used to identify parameter sets consistent with possible prevalence in macaques and humans inferred from observed data. We then explore the consequences of increasing human-macaque contact in the farm, the likely impact of rapid treatment, and the use of long-lasting insecticide-treated nets (LLINs) in preventing wider spread of this emerging infection.ResultsIdentified model parameters were consistent with transmission being sustained by the macaques with spill over infections into the human population and with high overall basic reproduction numbers (up to 2267). The extent to which macaques forage in the farms had a non-linear relationship with human infection prevalence, the highest prevalence occurring when macaques forage in the farms but return frequently to the forest where they experience higher contact with vectors and hence sustain transmission. Only one of 1,046 parameter sets was consistent with sustained human-to-human transmission in the absence of macaques, although with a low human reproduction number (R(0H) = 1.04). Simulations showed LLINs and rapid treatment provide personal protection to humans with maximal estimated reductions in human prevalence of 42% and 95%, respectively.ConclusionThis model simulates conditions where P. knowlesi transmission may occur and the potential impact of control measures. Predictions suggest that conventional control measures are sufficient at reducing the risk of infection in humans, but they must be actively implemented if P. knowlesi is to be controlled.

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Booked inpatient admissions and hospital capacity: mathematical modelling study.

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Booked inpatient admissions and hospital capacity: mathematical modelling study.

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