Influence of prolonged hospitalization on overall bed occupancy: a five-year single-centre study

Background: Effective bed use is crucial to an efficient NHS. Current targets suggest a decrease in mean occupancy as the most appropriate method of improving overall efficiency. The elderly and those suffering from complex medical problems are thought to account for a high proportion of overall bed occupancy.

Aim: To assess the effect of prolonged hospital stay (>100 days) on overall bed occupancy in a modern teaching hospital.

Design: Retrospective analysis.

Methods: Analysis of all admission episodes (n = 117 178) over a five-year period in a large teaching hospital in a single UK region, serving a population of approximately 200 000. A logistic regression multi-factorial model was used to assess the effect of demographic and diagnostic variables on duration of stay.

Results: A prolonged stay (>100 days) was seen in 648 admission episodes (0.6%). These accounted for 11% of the overall bed occupancy over the 5-year period. Excluding all prolonged admission episodes from our analysis made no difference to the overall median length of stay.

Discussion: Prolonged hospitalizations have a significant impact on bed occupancy. Targeting these very long (>100 days) hospital stays may better improve overall efficiency, compared to targeting mean or median length of stay.

The Impact of Admissions for the Management of End-stage renal disease on hospital bed occupancy

BACKGROUND:

End-stage renal disease (ESRD) is increasingly prevalent but the inpatient costs associated with this condition are poorly defined due to limitations with data extraction and failure to differentiate between hospitalisation for renal and non-renal disease reasons. The impact of admissions primarily for the management of ESRD on hospital bed utilisation was assessed over a 5-year period in a large teaching hospital.

METHODS:

All admission episodes were reviewed and the ESRD group was identified by a primary International Classification of Diseases code for ESRD or a non-specific primary renal failure code with a secondary code for ESRD. The frequency and duration of hospitalisation and contribution to bed day occupancy of this group with ESRD was determined.

RESULTS:

There were 70,808 patients responsible for a total of 116,915 admissions and 919,212 bed days over the study period. Of these, 988 (1.4%) patients were admitted for the management of ESRD, accounting for 2,387 (2.0%) of admissions and utilisation of 23,011 (2.5%) bed days. After adjustment for age and gender, those admitted for ESRD management were significantly more likely to have a prolonged admission exceeding 30 days (odds ratio 1.46, 95% confidence interval 1.23-1.72, p < 0.001). When the admission was an emergency rather than an elective event, the patient was 4.6 times more likely to be hospitalised for over 30 days.

CONCLUSIONS:

Persons admitted for ESRD management are hospitalised more frequently and for longer than the overall inpatient population, occupying a substantial number of bed days.

Assessment of the benefits of Discrete Conditional Survival Models in modelling ambulance response times

Many of the challenges faced in health care delivery can be informed through building models. In particular, Discrete Conditional Survival (DCS) models, recently under development, can provide policymakers with a flexible tool to assess time-to-event data. The DCS model is capable of modelling the survival curve based on various underlying distribution types and is capable of clustering or grouping observations (based on other covariate information) external to the distribution fits. The flexibility of the model comes through the choice of data mining techniques that are available in ascertaining the different subsets and also in the choice of distribution types available in modelling these informed subsets. This paper presents an illustrated example of the Discrete Conditional Survival model being deployed to represent ambulance response-times by a fully parameterised model. This model is contrasted against use of a parametric accelerated failure-time model, illustrating the strength and usefulness of Discrete Conditional Survival models.

A Bayesian Network Hybrid Model for Representing Accident and Emergency Waiting Times

The paper introduces a new modeling approach that represents the waiting times in an Accident and Emergency (A&E) Department in a UK based National Health Service (NHS) hospital. The technique uses Bayesian networks to capture the heterogeneity of arriving patients by representing how patient covariates interact to influence their waiting times in the department. Such waiting times have been reviewed by the NHS as a means of investigating the efficiency of A&E departments (Emergency Rooms) and how they operate. As a result activity targets are now established based on the patient total waiting times with much emphasis on trolley waits.

Discrete Conditional Phase-type models utilising classification trees: Application to modelling health service capacities

Discrete Conditional Phase-type (DC-Ph) models consist of a process component (survival distribution) preceded by a set of related conditional discrete variables. This paper introduces a DC-Ph model where the conditional component is a classification tree. The approach is utilised for modelling health service capacities by better predicting service times, as captured by Coxian Phase-type distributions, interfaced with results from a classification tree algorithm. To illustrate the approach, a case-study within the healthcare delivery domain is given, namely that of maternity services. The classification analysis is shown to give good predictors for complications during childbirth. Based on the classification tree predictions, the duration of childbirth on the labour ward is then modelled as either a two or three-phase Coxian distribution. The resulting DC-Ph model is used to calculate the number of patients and associated bed occupancies, patient turnover, and to model the consequences of changes to risk status.

Patterns of hospitalisation before and following initiation of haemodialysis: a 5 year single centre study

Background: The utilisation of healthcare resources by prevalent haemodialysis patients has been robustly evaluated with regard to the provision of outpatient haemodialysis; however, the impact of hospitalisation among such patients is poorly defined. Minimal information is available in the UK to estimate the health and economic burden associated with the inpatient management of prevalent haemodialysis patients. The aim of this study was to assess the pattern of hospitalisation among a cohort of haemodialysis patients, before and following their initiation of haemodialysis. In addition the study sought to assess the impact of their admissions on bed occupancy in a large tertiary referral hospital in a single region in the UK.

Methods: All admission episodes were reviewed and those receiving dialysis with the Belfast City Hospital Programme were identified over a 5 year period from January 2001 to December 2005. This tertiary referral centre provides dialysis services for a population of approximately 700?000 and additional specialist renal services for the remainder of Northern Ireland. The frequency and duration of hospitalisation, and contribution to bed day occupancy of haemodialysis patients, was determined and compared to other common conditions which are known to be associated with high bed occupancy. In addition, the pattern and timing of admissions in dialysis patients in relation to their dialysis initiation date was assessed.

Results: Over the 5 year study period, 798 haemodialysis patients were admitted a total of 2882 times. These accounted for 2.5% of all admissions episodes; the median number of admissions for these patients was 3 (2–5) which compared with 1 (1–2) for non-dialysis patients. The majority of first hospitalisations (54%) were within 100 days before or after commencement of maintenance dialysis therapy. In all clinical specialties the median length of stay for haemodialysis patients was significantly longer than for patients not on haemodialysis (p=0.004). In multivariate analysis with adjustment for age, gender, and other clinically relevant diagnostic codes, maintenance haemodialysis patients stayed on average 3.75 times longer than other patient groups (ratio of geometric means 3.75, IQR 3.46–4.06).

Conclusions: Maintenance haemodialysis therapy is an important risk factor for prolonged hospitalisation regardless of the primary reason for admission. Such patients require admission more frequently than the general hospital population, particularly within 100 days before and after initiation of their first dialysis treatment.

An Introduction to the Special issue - Housing in Hard Times: Marginality, Inequality and Class, with Kim McKee

‘Housing in Hard Times’ was the theme of the Housing Studies Association annual conference in April 2011. The papers featured in this special issue are drawn from that conference. They examine the uneven impact of economic change on housing policy and related areas, with reference to conceptual ideas pertaining to urban marginality, inequality and class. Whilst the empirical focus of the papers is the UK, their intellectual contribution represents an attempt to ‘bring class back in’ to the housing studies literature and encourage more critical, theoretically informed scholarship.

The application of the ecological footprint in two Irish urban areas: Limerick and Belfast

The ecological footprint is now a widely accepted indicator of sustainable
development. Footprinting translates resource consumption into the land area
required to sustain it, and allows for an average per capita footprint for a region
or nation to be compared with the global average. This paper reports on a project
in which footprints were calculated for two Irish cities, namely Belfast in
Northern Ireland and Limerick in the Republic of Ireland for the year 2001. As
is frequently the case at sub-national scale, data quality and availability were
often problematic, and in general data gaps were filled by means of population
proxies or national averages. A range of methods was applied to convert
resource flows to land areas. Both footprints suggest that the lifestyles of citizens
of the cities use several times more land than their global share, as has been
found for other cities.

Rapid design of application specific FFT cores

Methods are presented for developing synthesizable FFT cores. These are based on a modular approach in which parameterized commutator and processor blocks are cascaded to implement the computations required in many important FFT signal flow graphs. In addition, it is shown how the use of a digital serial data organization can be used to produce systems that offer 100% processor utilization along with reductions in storage requirements. The approach has been used to create generators for the automated synthesis of FFT cores that are portable across a broad range of silicon technologies. Resulting chip designs are competitive with ones created using manual methods but with significant reductions in design times.

Bedside application of the Neonatal Facial Coding System in pain assessment of premature neonates

Assessment of infant pain is a pressing concern, especially within the context of neonatal intensive care where infants may be exposed to prolonged and repeated pain during lengthy hospitalization. In the present study the feasibility of carrying out the complete Neonatal Facial Coding System (NFCS) in real time at bedside, specifically reliability, construct and concurrent validity, was evaluated in a tertiary level Neonatal Intensive Care Unit (NICU). Heel lance was used as a model of procedural pain, and observed with n = 40 infants at 32 weeks gestational age. Infant sleep/wake state, NFCS facial activity and specific hand movements were coded during baseline, unwrap, swab, heel lance, squeezing and recovery events. Heart rate was recorded continuously and digitally sampled using a custom designed computer system. Repeated measures analysis of variance (ANOVA) showed statistically significant differences across events for facial activity (P <0.0001) and heart rate (P <0.0001). Planned comparisons showed facial activity unchanged during baseline, swab and unwrap, then increased significantly during heel lance (P <0.0001), increased further during squeezing (P <0.003), then decreased during recovery (P <0.0001). Systematic shifts in sleep/wake state were apparent. Rise in facial activity was consistent with increased heart rate, except that facial activity more closely paralleled initiation of the invasive event. Thus facial display was more specific to tissue damage compared with heart rate. Inter-observer reliability was high. Construct validity of the NFCS at bedside was demonstrated as invasive procedures were distinguished from tactile. While bedside coding of behavior does not permit raters to be blind to events, mechanical recording of heart rate allowed for an independent source of concurrent validation for bedside application of the NFCS scale.

Explaining Prolonged Silences in Transitional Justice: The Disappeared in Cyprus and Spain

The article examines why some postconflict societies defer the recovery of those who forcibly disappeared as a result of political violence, even after a fully fledged democratic regime is consolidated. The prolonged silences in Cyprus and Spain contradict the experience of other countries such as Bosnia, Guatemala, and South Africa, where truth recovery for disappeared or missing persons was a central element of the transition to peace and democracy. Exhumations of mass graves containing the victims from the two periods of violence in Cyprus (1963–1974) and the Spanish Civil War (1936–1939) was delayed up until the early 2000s. Cyprus and Spain are well suited to explain both prolonged silences in transitional justice and the puzzling decision to become belated truth seekers. The article shows that in negotiated transitions, a subtle elite agreement links the non-instrumental use of the past with the imminent needs for political stability and nascent democratization. As time passes, selective silence becomes an entrenched feature of the political discourse and democratic institutions, acquiring a hegemonic status and prolonging the silencing of violence.

Investigation of the M2/G2/1/ ∞, N Queue with Restricted Admission of Priority Customers and its Application to HSDPA Mobile Systems

This paper investigates a queuing system for QoS optimization of multimedia traffic consisting of aggregated streams with diverse QoS requirements transmitted to a mobile terminal over a common downlink shared channel. The queuing system, proposed for buffer management of aggregated single-user traffic in the base station of High-Speed Downlink Packet Access (HSDPA), allows for optimum loss/delay/jitter performance for end-user multimedia traffic with delay-tolerant non-real-time streams and partially loss tolerant real-time streams. In the queuing system, the real-time stream has non-preemptive priority in service but the number of the packets in the system is restricted by a constant. The non-real-time stream has no service priority but is allowed unlimited access to the system. Both types of packets arrive in the stationary Poisson flow. Service times follow general distribution depending on the packet type. Stability condition for the model is derived. Queue length distribution for both types of customers is calculated at arbitrary epochs and service completion epochs. Loss probability for priority packets is computed. Waiting time distribution in terms of Laplace-Stieltjes transform is obtained for both types of packets. Mean waiting time and jitter are computed. Numerical examples presented demonstrate the effectiveness of the queuing system for QoS optimization of buffered end-user multimedia traffic with aggregated real-time and non-real-time streams.