[Patient dissatisfaction following prolonged stay in the post-anesthesia care unit due to unavailable ward bed in a tertiary hospital]

OBJECTIVES

The present study aimed to evaluate subjective reactions of post-surgery and anesthesia patients who stay in post-anesthesia care units (PACU) longer than necessary medically, due to administrative causes.

METHODS

We interviewed consenting postoperative patients during an 18-month period. All patients who remained in the PACU twice our obligatory PACU length of stay (> 4 hours) due to lack of an available bed in the appropriate hospital ward, were interviewed at the time of discharge. The study group consisted of those who remained > 4 hours after surgery and a control group of patients who were discharged within 4 hours. The questions were chosen from different sources, including generic and condition-specific questionnaires.

RESULTS

A total of 67 patients stayed > 4 hours and 63 < 4 hours. The overall mean PACU length of stay for the former was 14.23 +/- 5.77 hours (range 1.5-30 hours). No significant differences were found between the groups in terms of age, gender, surgical time or postoperative pain visual analogue scale. Irritability due to lack of independence were statistically higher, and satisfaction rates were lower in patients who stayed > 12 hours compared to those who were discharged after 4-12 hours (P < 0.05).

CONCLUSIONS

Overcrowded wards may lead to significant delays in discharge from the PACU. Prolonged stay in the PACU requires attention, both from the administrative and the medical standpoints, because it may irritate the patient. Patients' irate behavior may distract the medical staff from effectively performing their duties and interferes with optimal medical care in the PACU.

A dismantling study of assertive outreach services: comparing activity and outcomes following replacement with the FACT model

PURPOSE

Financial constraints and some disappointing research evaluations have seen English assertive outreach (AO) teams subject to remodelling, decommissioning and integration into standard care. We tested a specific alternative model of integrating the AO function from two AO teams into six standard community mental health teams (CMHT). The Flexible Assertive Community Treatment model (FACT) was adopted from the Netherlands (Van Veldhuizen, Commun Mental Health J 43(4):421-433, 2007; Bond and Drake, Commun Mental Health J 43(4):435-438, 2007). We aimed to demonstrate non-inferiority in clinical effectiveness and thereby show cost efficiencies associated with FACT.

METHODS

Outcomes were compared in a mirror-image study of the 12 months periods pre- and post-service change with eligible individuals from the AO teams' caseloads (n = 112) acting as their own controls. We also conducted a cost-consequence analysis of the changes. Outcome data regarding admissions, use of crisis and home treatment, frequency of contact and DNA rate were extracted from the electronic patient record.

RESULTS

The results show AO patients (n = 112) transferred to standard CMHTs with FACT had significantly fewer admissions and a halving of bed use (21 fewer admission and 2,394 fewer occupied bed days) whilst being in receipt of a less intensive service (2,979 fewer contacts). This was offset by significantly poorer engagement but not by increased use of crisis and home treatment services.

CONCLUSIONS

Enhancing multi-disciplinary CMHTs with FACT provides a clinically effective alternative to AO teams. FACT offers a cost-effective model compared to AO.

Successful introduction of ring-fenced inpatient surgical beds in a general hospital setting

This study aimed to assess the impact of ring-fenced inpatient general surgical beds on day of surgery (DOS) admission, duration of elective inpatient stay (DEIS), and cancellation rates over a 6 month period. In June 2010 17 of 60 surgical inpatient beds were decommissioned. The remainder (43) were ring-fenced for general surgery patients only. Comparative analysis examining admission rates, cancellation rates, and theatre activity was performed between a reference period (January-June 2010) and the study period (July-December 2010). Complexity of all operations was graded according to an index schedule of procedures. There was no difference between the reference and study periods in volumes of elective admissions (472 [53.03%] vs. 418 [4797%]) and emergency admissions (928 [50.03%] vs. 927 [49.97%]). DOS admissions increased 5-fold during the study period (38 [8.1%] vs. 190 [45.5%], P < 0.001). Average duration of elective inpatient stay reduced from 4.3 days to 3.06 days in the study period (P < 0.001). No difference was observed in volume of operations performed at all levels of complexity. There were 78 (58.2%) cancellations during the reference period and 56 (41.8%) during the study period with patient non-attendance the most common cause for cancellation in both periods. Ring-fenced surgical beds facilitated higher DOS admission rates and shorter duration of elective inpatient stay, leading to more efficient use of hospital resources.

Interest of a simple on-line screening registry for measuring ICU burden related to an influenza pandemic

INTRODUCTION

The specific burden imposed on Intensive Care Units (ICUs) during the A/H1N1 influenza 2009 pandemic has been poorly explored. An on-line screening registry allowed a daily report of ICU beds occupancy rate by flu infected patients (Flu-OR) admitted in French ICUs.

METHODS

We conducted a prospective inception cohort study with results of an on-line screening registry designed for daily assessment of ICU burden.

RESULTS

Among the 108 centers participating to the French H1N1 research network on mechanical ventilation (REVA) - French Society of Intensive Care (SRLF) registry, 69 ICUs belonging to seven large geographical areas voluntarily participated in a website screening-registry. The aim was to daily assess the ICU beds occupancy rate by influenza-infected and non-infected patients for at least three weeks. Three hundred ninety-one critically ill infected patients were enrolled in the cohort, representing a subset of 35% of the whole French 2009 pandemic cohort; 73% were mechanically ventilated, 13% required extra corporal membrane oxygenation (ECMO) and 22% died. The global Flu-OR in these ICUs was only 7.6%, but it exceeded a predefined 15% critical threshold in 32 ICUs for a total of 103 weeks. Flu-ORs were significantly higher in University than in non-University hospitals. The peak ICU burden was poorly predicted by observations obtained at the level of large geographical areas.

CONCLUSIONS

The peak Flu-OR during the pandemic significantly exceeded a 15% critical threshold in almost half of the ICUs, with an uneven distribution with time, geographical areas and between University and non-University hospitals. An on-line assessment of Flu-OR via a simple dedicated registry may contribute to better match resources and needs.

Evaluation of utilization and efficacy of general hospitals in Serbia: is there a shift forward?

INTRODUCTION

In the Republic of Serbia the activity of general hospitals has not been sufficiently evaluated.

OBJECTIVE

The aim of this study was to evaluate, by analyzing the basic indicators of general hospitals condition and functioning, the network, utilization and efficacy of general hospitals for further improvement of their organization and work.

METHODS

The paper is a part of a retrospective-prospective analysis of hospital healthcare services which we performed in 2011. The research involved all 40 general hospitals in Serbia evaluated as a general hospitals system. We selected seven basic indicators of hospitals condition and functioning that we followed-up in the period 2000-2009. As the data source we used the Reports of the Office for Hospital Stationary Treatment of general hospitals and the Report of the Republican Institution for Statistics entitled Vital Events in the Republic of Serbia. Numerical data were analyzed using the methods of descriptive statistics and the program Microsoft Office Excel 2007 and SPSS for Windows. Statistical significance indicators of differences were determined by Student's t-test.

RESULTS

In general hospitals during the studied years, the number of beds decreased by 16.5% (p(t)=0.057). The number of discharged patients was increased by 11.8% (p(t)=0.035). The number of hospitalization days was reduced by 11.2% (p(t)=0.038).The average length of treatment was reduced by 1.9 days (p(t)=0.074). The average daily bed occupancy was increased by 4% (p(t)=0.020). The utilization of beds was increased by 4.5% (p(t)=0.019). Throughput capacity of beds increased by 8.5 patients per bed or by 27.8% (p(t)=0.091).

CONCLUSION

The most significant indicators of the utilization and efficacy of general hospitals were improved. Nevertheless, European and domestic guidelines were achieved only in the average length of treatment.

Improving hospital bed utilisation through simulation and optimisation: with application to a 40% increase in patient volume in a Norwegian General Hospital

PURPOSE

This paper analyses the problem of allocating beds among hospital wards in order to minimise crowding.

METHOD

We present a generic discrete event simulation model of patient flow through the wards of a hospital. In the generic model, each ward can have separate probability distributions for arrival times and length of stay, which may be time dependent. Output of the model is a matrix, with statistics on the utilisation of different hypothetical numbers of beds for each ward. This matrix is fed into an allocation algorithm, which distributes the available beds among the wards in an optimal way. We define bed utilisation either in terms of how often it is in use (prevalence), or in terms of how often a newly arriving patient is placed in it (incidence). For these classes of utilisation measures we develop efficient allocation algorithms, which we prove to be optimal.

APPLICATION

The model was applied to Akershus University Hospital in Norway. In 2011, some of the wards of this hospital experienced a high occupancy rate, while others had a lower utilisation. Our model was applied in order to reallocate the hospital beds among the wards. For each ward, acute arrivals were modelled with Poisson-distributions with time-varying intensity, while elective arrivals were programmed to arrive in specific numbers at specific times. The arrival rates were based on empirical data for 2010, scaled up by an expected increase of 40% due to a restructuring of the hospital districts in Oslo and the greater metropolitan area in 2011. Length of stay was modelled as beta-distributions, using a combination of subject matter experts' evaluations and empirical data from 2010. The model has been verified and validated.

RESULTS

Intuitively, both prevalence (average number of crowding beds in use) and incidence (number of patients placed in crowding beds) might seem like relevant optimisation criteria. However, our experiments show that prevalence optimisation gives more sensible solutions than incidence optimisation, as the latter tends to sacrifice entire wards where length of stay is long and patient turnover is slow. Prevalence optimisation was therefore used. The main results show that when the bed distribution is optimised, the share of crowding patient nights is reduced from 6.5% to 4.2%.

CONCLUSION

This model provides a powerful tool for optimising hospital bed utilisation, and the application showed an important reduction in crowding bed usage. The generic model is flexible, as the level of detail in the modelling of arrivals and length of stay can vary according to the data available and accuracy required.

[Present situation of neonatal subspecialty in the mainland of China: a survey based on 109 hospitals]

OBJECTIVE

To investigate the present situation of neonatal subspecialty in the mainland of China, and provide reference data for further development and standardization of neonatal discipline in China.

METHODS

Data of neonatal subspecialty of 109 hospitals in the mainland of China acquired by questionnaire were collected and analyzed.

RESULTS

Of the 109 hospitals that located in 22 provinces, municipalities and autonomous regions, 68 (62.4%) had independent neonatology departments, and 41 (37.6%) had neonatal subspecialty groups affiliated to pediatric departments. The average number of neonatal beds was 35.95 (range from 6 to 300, median 30) per unit, compared with a number of 45.21 per unit in grade III-A general hospitals (range from 6 to 300, median 30). In all the 109 hospitals, the general beds to physicians ratio and beds to nurses ratio were 1:3.24 and 1:1.42, respectively. Each unit was in average equipped with 4.50 infant radiant warmers, 23.83 neonatal incubators, 3 normal frequency ventilators and 2.55 CPAP ventilators. All 22 clinical technologies, including ECMO, had been carried out, but only the new resuscitation technique has been carried out in each of these hospitals, and there were still eight technologies that were carried out in less than 50% hospitals. Totally 139 084 infants were treated in 109 hospitals in 2008, with the average number of 1276 patients per unit (range from 32 to 5500, median 1160). The average survival rate and mortality rate during hospitalization were 95.31% and 1.43%, respectively, while the survival rate of very low birth weight premature infants and extremely low birth weight premature infants were 82.43% and 41.30%, respectively. Transport service was provided in 62 (56.9%) hospitals, with the average transport number of 330 infants per hospital, accounting for 20.28% of the total admission.

CONCLUSION

The survey shows that neonatal subspecialty in the mainland of China already has a considerable size, however, the development is not balanced. The system of classification of neonatal units and standards of ward construction suitable for China should be set up as soon as possible.

Direct observation of bed utilization in the pediatric intensive care unit

BACKGROUND

The pediatric intensive care unit (PICU), with limited number of beds and resource-intensive services, is a key component of patient flow. Because the PICU is a crossroads for many patients, transfer or discharge delays can negatively impact a patient's clinical status and efficiency.

OBJECTIVE

The objective of this study was to describe, using direct observation, PICU bed utilization.

METHODS

We conducted a real-time, prospective observational study in a convenience sample of days in the PICU of an urban, tertiary-care children's hospital.

RESULTS

Among 824 observed hours, 19,887 bed-hours were recorded, with 82% being for critical care services and 18% for non-critical care services. Fourteen activities accounted for 95% of bed-hours. Among 200 hours when the PICU was at full capacity, 75% of the time included at least 1 bed that was used for non-critical care services; 37% of the time at least 2 beds. The mean waiting time for a floor bed assignment was 9 hours (median, 5.5 hours) and accounted for 4.62% of all bed-hours observed.

CONCLUSIONS

The PICU delivered critical care services most of the time, but periods of non-critical care services represented a significant amount of time. In particular, periods with no bed available for new patients were associated with at least 1 or more PICU beds being used for non-critical care activities. The method should be reproducible in other settings to learn more about the structure and processes of care and patient flow and to make improvements.

Review of acute cancer beds

A review of admissions to cancer services at University Hospital Galway (UHG) was undertaken to assess the appropriateness of hospital usage. All cancer specialty patients admitted from 26-28 May 2009 were reviewed (n = 82). Chi square tests, Exact tests, and One-way ANOVA were utilised to analyse key issues emerging from the data. Fifty (61%) were classified as emergencies. Twenty three (67%) occupied a designated cancer bed with 24 (30%) in outlying non-oncology wards. The mean length of stay was 29.3 days. Possible alternatives to admission were identified for 15 (19%) patients. There was no evidence of discharge planning for 50 (60%) admissions. There is considerable potential to make more appropriate utilisation of UHG for cancer patients, particularly in terms of reducing bed days and length of stay and the proportion of emergency cancer admissions, and further developing integrated systems of discharge planning.

Mortality scoring in ITU

Chronic shortage of ITU beds makes decisions on admission difficult and responsible. The use of computer-based mortality scoring should help in decision-making and for this purpose, a number of different scoring systems have been created; in principle, they should be easy to use, adaptable to all populations of patients and suitable for predicting the risk of mortality during both ITU and hospital stay. Most of existing scales and scoring systems were included in this review. They are frequently used in ITUs and become a necessary tool to describe ITU populations and to explain differences in mortality. As there are several pitfalls related to the interpretation of the numbers supplied by the systems, they should be used with the knowledge on the severity scoring science. Moreover, the cost and significant workload limit the use of scoring systems; in many cases an extra person has to be employed for collection and analysis of data only.

Emergency department overcrowding and inpatient boarding: a statewide glimpse in time

OBJECTIVES

This was a point-prevalence study designed to quantify the magnitude of emergency department (ED) overcrowding and inpatient boarding. Every ED in Michigan was surveyed at a single point in time on a Monday evening. Given the high patient volumes on Monday evenings, the effect on inpatient boarding the next morning was also reviewed.

METHODS

All 134 EDs within the state of Michigan were contacted and surveyed on Monday evening, March 16, 2009, over a single hour and again the following morning. Questions included data on annual census, bed number, number of admitted patients within the ED, ambulance diversion, and ED length of stay.

RESULTS

Data were obtained from 109 of the 134 (81%) hospitals on Monday evening and 99 (74%) on Tuesday morning. There was no difference in annual visits or ED size between participating and nonparticipating EDs. Forty-seven percent of EDs were boarding inpatients on Monday evening, compared with 30% on Tuesday morning. The mean estimated boarding times were 3.7 hours (Monday evening) and 7.2 hours (Tuesday morning). Twenty-four percent of respondents met the definition of overcrowded during sampling times. There was a significant relationship between inpatient boarding and ED overcrowding (p < 0.001). Only three EDs were actively diverting ambulances.

CONCLUSIONS

In this study on a single Monday evening, 47% of EDs in Michigan were actively boarding inpatients, while 24% were operating beyond capacity. On the following morning (Tuesday), EDs had fewer boarded inpatients than on Monday evening. However, these boarded inpatients remained in the ED for a significantly longer duration.

Addressing inpatient crowding by smoothing occupancy at children's hospitals

OBJECTIVE

To quantify the difference in weekday versus weekend occupancy, and the opportunity to smooth inpatient occupancy to reduce crowding at children's hospitals.

METHODS

Daily inpatient census data for 39 freestanding, tertiary-care children's hospitals were used to calculate occupancy and to model the impact of reducing variation in occupancy and the change in the number of patients, patient-days, and hospitals exposed to high occupancy pre- and post-smoothing. We also calculated the proportion of weekly admissions that would require different scheduling to achieve within-week smoothing.

RESULTS

Overall, hospitals' mean occupancy ranged from 70.9% to 108.1% on weekdays, and 65.7% to 94.9% on weekends. Weekday occupancy exceeded weekend occupancy with a median difference of 8.2% points. The mean post-smoothing reduction in weekly maximum occupancy across all hospitals was 6.6% points. Through smoothing, 39,607 patients from the 39 hospitals were removed from exposure to occupancy levels >95%. To achieve within-week smoothing, a median 2.6% of admissions would have to be scheduled on a different day of the week; this equates to a median of 7.4 patients per week (range: 2.3-14.4).

CONCLUSION

Hospitals do have substantial unused capacity, and smoothing occupancy over the course of a week could be a useful strategy that hospitals can use to reduce crowding and protect patients from crowded conditions.

Diabetes inpatients: a case of lose, lose, lose. Is it time to use a 'diabetes-attributable hospitalization cost' to assess the impact of diabetes?

AIMS

The UK National Health Service in England pays for inpatients using a formula ('tariff'). The appropriateness of the tariff for people with diabetes is unknown. We have compared the tariff paid and costs for inpatients with/without diabetes and tested the concept of a 'diabetes-attributable hospitalization cost'.

METHODS

This was a cross-sectional, retrospective 12-month audit in a single teaching hospital assessing mortality, bed days per annum and 'diabetes-attributable hospitalization cost' (i.e. the proportion of costs for all patients with diabetes in excess of that paid for comparable patients without diabetes).

RESULTS

There were 64 829 inpatient admissions, with 4864 of those coded as having diabetes; 12.9% was estimated to be the number of patients having diabetes but not coded. People with diabetes occupied 13.9% of all bed days and were 18.1% (1.3-37.8%) more likely to die (age adjusted). The mean bed days per annum were greatest among those with (vs. without) diabetes (men 10.9 ± 17.0 vs. 6.3 ± 12.8; women 11.4 ± 19.4 vs. 5.9 ± 11.6; P < 0.001). The greatest excess admission rates were among those aged 25-64 years. The annual mean tariff was greater for those with diabetes (5380 ± 8740) than those without diabetes (3706 ± 6221) (P < 0.001). The overall cost was even higher among those with diabetes: 5835 ± 11 246 vs. 3567 ± 7238 (P < 0.001). The diabetes-attributable hospitalization cost was 46.5% (9 125 085). An HbA(1c) > 10.0% (> 86 mmol/mol) was associated with excess hospitalization.

CONCLUSIONS

Those with diabetes cost more and are more likely to die when inpatients. The tariff paid for diabetes is high, but in this centre less than the actual costs. Approaches known to reduce hospitalization are urgently required.

Association between provision of mental illness beds and rate of involuntary admissions in the NHS in England 1988-2008: ecological study

OBJECTIVE

To examine the rise in the rate of involuntary admissions for mental illness in England that has occurred as community alternatives to hospital admission have been introduced.

DESIGN

Ecological analysis.

SETTING

England, 1988-2008.

DATA SOURCE

Publicly available data on provision of beds for people with mental illness in the National Health Service from Hospital Activity Statistics and involuntary admission rates from the NHS Information Centre.

MAIN OUTCOME MEASURES

Association between annual changes in provision of mental illness beds in the NHS and involuntary admission rates, using cross correlation. Partial correlation coefficients were calculated and regression analysis carried out for the time lag (interval) over which the largest association between these variables was identified.

RESULTS

The rate of involuntary admissions per annum in the NHS increased by more than 60%, whereas the provision of mental illness beds decreased by more than 60% over the same period; these changes seemed to be synchronous. The strongest association between these variables was observed when a time lag of one year was introduced, with bed reductions preceding increases in involuntary admissions (cross correlation -0.60, 95% confidence interval -1.06 to -0.15). This association increased in magnitude when analyses were restricted to civil (non-forensic) involuntary admissions and non-secure mental illness beds.

CONCLUSION

The annual reduction in provision of mental illness beds was associated with the rate of involuntary admissions over the short to medium term, with the closure of two mental illness beds leading to one additional involuntary admission in the subsequent year. This study provides a method for predicting rates of involuntary admissions and what may happen in the future if bed closures continue.