Bed Utilization Research Articles

Constructing operating theatre schedules using partitioned graph colouring techniques

ABSTRACT In hospitals, scheduled operations can often be cancelled in large numbers due to the unavailability of beds for post-operation recovery. Operating theatre scheduling is known to be an -hard optimisation problem. Previous studies have shown that the correct scheduling of surgical procedures can have a positive impact on the availability of beds in hospital wards, thereby allowing a reduction in number of elective operation cancellations. This study proposes an exact technique based on the partitioned graph colouring problem for constructing optimal master surgery schedules, with the goal of minimising the number of cancellations. The resultant schedules are then simulated in order to measure how well they cope with the stochastic nature of patient arrivals. Our results show that the utilisation of post-operative beds can be increased, whilst the number of cancellations can be decreased, which may ultimately lead to greater patient throughput and reduced waiting times. A scenario-based model has also been employed to integrate the stochastic-nature associated with the bed requirements into the optimisation process. The results indicate that the proposed model can lead to more robust solutions.

Hospitalized Morbidity & Utilization of Beds in a Rural Health Training Centre

Background: Morbidity consumes a substantial portion of health care resources in a hospital. The overload in hospital ward remains a major source of concern in many countries, including India, for policy makers. The availability of beds is perhaps the single most important factor in determination of the hospital utilization in a country. Objective: To determine the pattern of hospitalized morbidity, hospital bed utilization by different morbidity and length of stay in the Rural Health Training Centre (RHTC). Observation: A total of 528 patients were admitted in RHTC of which max, 53% were females with mean age of male and female patients were 48.15yrs (SD=19.22) and 40.39yrs (SD=16.64) respectively. Max, 22.9% patients were in age group 26-35 years. Max. 38.6% hospitalized morbidity was mainly due to viral fever followed by gastroenteritis, 21.5% and among the total anaemic admissions, higher proportion, 70% was belonged to females. Length of stay due to hospitalised morbidity range from one to four days of which max length of stay was seen in age 46 to 55 yrs and mainly due to enteric fever. Overall bed occupancy rate due to hospitalized morbid condition during study period was 54.92%. Bed occupancy rate was high, 17.91% due to viral fever followed by gastroenteritis, 15.05%, and enteric fever (10.38%) respectively. However, maximum length of hospital stay ,4 days was mainly due to enteric fever and variation within disease about the length of stay in hospital is found significant. Conclusion: Hospitalized utilization in rural area is mainly due to infectious diseases and need efforts to sensitize the poor and neglected sector of rural community to access the health care services for positive health.

Tactical scheduling of surgeries to level bed utilization in the intensive care unit

The intensive care unit is a highly specialized and expensive hospital resource serving both emergency and scheduled patients. The vast majority of scheduled patients arrive from the operating theater. Therefore, the operating theater schedule has a strong impact on intensive care unit occupancy levels. Prior research focuses on the creation of a new master surgery schedule to optimize the patient flow in downstream units. In practice, however, the master surgery schedule affects a multitude of related processes, and changing it causes significant disruptions within the hospital. Hence, our approach emphasizes a centralized reallocation of scheduled surgeries while maintaining the existing master surgery schedule. We propose a mixed-integer quadratic model that optimizes the tactical surgery schedule to balance the expected day-to-day occupancy of scheduled patients in the surgical intensive care unit. Supported by two years of data from a German university hospital, we analyze three planning strategies and their impact on bed utilization in the intensive care unit. Our approach yields an improvement of 17.5% in intensive care bed utilization variability compared to a decentral approach, which is similar to current hospital practice. Additionally, we show that our approach can realize the majority of the improvement potential without the disruptions that derive from an entirely new master surgery schedule.

Mercury emission and adsorption characteristics of fly ash in PC and CFB boilers

The mercury emission was obtained by measuring the mercury contents in flue gas and solid samples in pulverized coal (PC) and circulating fluidized bed (CFB) utility boilers. The relationship was obtained between the mercury emission and adsorption characteristics of fly ash. The parameters included unburned carbon content, particle size, and pore structure of fly ash. The results showed that the majority of mercury released to the atmosphere with the flue gas in PC boiler, while the mercury was enriched in fly ash and captured by the precipitator in CFB boiler. The coal factor was proposed to characterize the impact of coal property on mercury emissions in this paper. As the coal factor increased, the mercury emission to the atmosphere decreased. It was also found that the mercury content of fly ash in the CFB boiler was ten times higher than that in the PC boiler. As the unburned carbon content increased, the mercury adsorbed increased. The capacity of adsorbing mercury by fly ash was directly related to the particle size. The particle size corresponding to the highest content of mercury, which was about 560 ng/g, appeared in the range from 77.5 to 106 µm. The content of mesoporous (4–6 nm) of the fly ash in the particle size of 77.5–106 µm was the highest, which was beneficial to adsorbing the mercury. The specific surface area played a more significant role than specific pore volume in the mercury adsorption process.

Clinical Characteristics and Outcomes of Patients Admitted with Brief Resolved Unexplained Events to a Tertiary Care Pediatric Intensive Care Unit.

The aim of this study was to determine outcomes of patients admitted to a tertiary care pediatric intensive care unit (PICU) with brief, resolved, unexplained event (BRUE), and to review the diagnostic and treatment options utilized for such patients. A retrospective data analysis was conducted for infants and children who were admitted to the PICU at a tertiary hospital with a diagnosis of BRUE over a period of three years (2015-2017). The study included 30 infants, 15 males, and 15 females. All patients survived to hospital discharge. The most frequent presenting symptoms and signs were apnea (73.3%), cyanosis (60.0%), and cough (20.0%). The most frequent reported affected systems were respiratory (33.3%), gastrointestinal (20%), and infection-related illness (20.0%). We conclude that the careful history taking, complete physical examination, and the appropriate workup for patients with BRUE play an integral role in optimum health service and utilization of critical care beds. Survival to hospital discharge with no serious in-hospital events warrants the adaptation of evidence-based medicine guidelines to stratify such patients based on the risk of recurrence or a serious underlying condition. Prospective multicenter studies are recommended to explore the effectiveness of such guidelines implementation on outcomes and diagnostic testing in such patients to optimize the utilization of the limited critical care beds.

Utilization of deceased donors during a pandemic: argument against using SARS-CoV-2-positive donors.

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has rapidly become an unprecedented pandemic that has impacted society, disrupted hospital functions, strained health care resources, and impacted the lives of transplant professionals. Despite this, organ failure and the need for transplant continues throughout the United States. Considering the perpetual scarcity of deceased donor organs, Kates et al present a viewpoint that advocates for the utilization of coronavirus disease 2019 (COVID‐19)–positive donors in selected cases. We present a review of the current literature that details the potential negative consequences of COVID‐19–positive donors. The factors we consider include (1) the risk of blood transmission of SARS‐CoV‐2, (2) involvement of donor organs, (3) lack of effective therapies, (4) exposure of health care and recovery teams, (5) disease transmission and propagation, and (6) hospital resource utilization. While we acknowledge that transplant fulfills the mission of saving lives, it is imperative to consider the consequences not only to our recipients but also to the community and to health care workers, particularly in the absence of effective preventative or curative therapies. For these reasons, we believe the evidence and risks show that COVID‐19 infection should continue to remain a contraindication for donation, as has been the initial response of donation and transplant societies.

A Safe Transitions Pathway for post-craniotomy neurological surgery patients: high-value care that bypasses the intensive care unit.

High-value medical care is described as care that leads to excellent patient outcomes, high patient satisfaction, and efficient costs. Neurosurgical care in particular can be expensive for the hospital, as substantial costs are accrued during the operation and throughout the postoperative stay. The authors developed a "Safe Transitions Pathway" (STP) model in which select patients went to the postanesthesia care unit (PACU) and then the neuro-transitional care unit (NTCU) rather than being directly admitted to the neurosciences intensive care unit (ICU) following a craniotomy. They sought to evaluate the clinical and financial outcomes as well as the impact on the patient experience for patients who participated in the STP and bypassed the ICU level of care. Patients were enrolled during the 2018 fiscal year (FY18; July 1, 2017, through June 30, 2018). The electronic medical record was reviewed for clinical information and the hospital cost accounting record was reviewed for financial information. Nurses and patients were given a satisfaction survey to assess their respective impressions of the hospital stay and of the recovery pathway. No patients who proceeded to the NTCU postoperatively were upgraded to the ICU level of care postoperatively. There were no deaths in the STP group, and no patients required a return to the operating room during their hospitalization (95% CI 0%-3.9%). There was a trend toward fewer 30-day readmissions in the STP patients than in the standard pathway patients (1.2% [95% CI 0.0%-6.8%] vs 5.1% [95% CI 2.5%-9.1%], p = 0.058). The mean number of ICU days saved per case was 1.20. The average postprocedure length of stay was reduced by 0.25 days for STP patients. Actual FY18 direct cost savings from 94 patients who went through the STP was $422,128. Length of stay, direct cost per case, and ICU days were significantly less after the adoption of the STP, and ICU bed utilization was freed for acute admissions and transfers. There were no substantial complications or adverse patient outcomes in the STP group.

Quality assessment of weekend discharge: a systematic review and meta-analysis

Hospital bed utility and length of stay affect the healthcare budget and quality of patient care. Prior studies already show admission and operation on weekends have higher mortality rates compared with weekdays, which has been identified as the 'weekend effect.' However, discharges on weekends are also linked with quality of care, and have been evaluated in the recent decade with different dimensions. This meta-analysis aims to discuss weekend discharges associated with 30-day readmission, 30-day mortality, 30-day emergency department visits and 14-day follow-up visits compared with weekday discharges. PubMed, EMBASE, Cochrane Library and ClinicalTrials.gov were searched from January 2000 to November 2019. Preferred reporting items for systematic reviews and meta-analyses guidelines were followed. Only studies published in English were reviewed. The random-effects model was applied to assess the effects of heterogeneity among the selected studies. Year of publication, country, sample size, number of weekday/weekend discharges, 30-day readmission, 30-day mortality, 30-day ED visits and 14-day appointment follow-up rate. There are 20 studies from seven countries, including 13 articles from America, in the present meta-analysis. There was no significant difference in odds ratio (OR) in 30-day readmission, 30-day mortality, 30-day ED visit, and 14-day follow-up between weekday and weekend. However, the OR for 30-day readmission was significantly higher among patients in the USA, including studies with high heterogeneity. In the USA, the 30-day readmission rate was higher in patients who had been discharged on the weekend compared with the weekday. However, interpretation should be cautious because of data limitation and high heterogeneity. Further intervention should be conducted to eliminate any healthcare inequality within the healthcare system and to improve the quality of patient care.

The Crucible of War: Innovation in a Pandemic.

The Crucible of War: Innovation in a Pandemic.

Fixed bed utilization for the isolation of xylene vapor: Kinetics and optimization using response surface methodology and artificial neural network

This paper discusses the isolation of xylene vapor through adsorption using granular activated carbon as an adsorbent. The operating parameters investigated were bed height, inlet xylene concentration and flow rate, their influence on the percentage utilization of the adsorbent bed up to the breakthrough was found out. Mathematical modeling of experimental data was then performed by employing a response surface methodology (RSM) technique to obtain a set of optimum operating conditions to achieve maximum percentage utilization of bed till breakthrough. A fairly high value of R2 (0.993) asserted the proposed polynomial equation’s validity. ANOVA results indicated the model to be highly significant with respect to operating parameters studied. A maximum of 76.1% utilization of adsorbent bed was found out at a bed height of 0.025 m, inlet xylene concentration of 6,200 ppm and a gas flow rate of 25 mL.min-1. Furthermore, the artificial neural network (ANN) was also employed to compute the percentage utilization of the adsorbent bed. A comparison between RSM and ANN divulged the performance of the latter (R2 = 0.99907) to be slightly better. Out of various kinetic models studied, the Yoon-Nelson model established its appropriateness in anticipating the breakthrough curves.

Housing Orientations and Needs of Above-Average Length of Stay Hospitalized Psychiatric Patients.

A small number of severely and persistently mentally ill in-patients awaiting residential or long-stay facilities represent an obstacle to the efficient utilization of acute care beds. These facilities are costly and currently reputed to be contrary to recovery principles. In 2013, all acute psychiatric care wards in Montreal identified 194 in-patients who could be discharged to residential or long-term nursing care facilities. Program clinical professionals of regional residential facilities sent adapted standardized questionnaires to ward staff. Evaluators also collected the residential preferences of both staff and patients, and then made their own assessments. The 194 in-patients were mostly middle-aged single men. Over 80% had a psychosis diagnosis and half had judicial constraints. The staff evaluated that 71.1% could be discharged from hospital within 24 h. Of these, 55% could be referred to group resources with continuous 24 h, 7 days a week staff presence, 32% could be transferred to apartments with 7-day continuous or non-continuous staff presence, 12% could be transferred to institutional care and only 2% could be moved to an apartment of their own. Evaluator and ward staff residential preferences were highly similar, but differed with patient preferences, half of whom prefer their own apartment. Discrepancy between staff evaluations and patient preferences were higher for longer stay patients with more severe symptoms and comorbidity of personality disorders.

Interfacility Neonatal Transport for Convalescent Care: Improving Regionalized Care.

Transfer of infants who no longer need intensive or specialized care from tertiary to community hospitals or clinics contributes to efficient bed utilization in neonatal intensive care units (NICUs). We retrospectively analyzed the records of all 1,503 infants admitted to our NICU during the 6-year period from April 2013 through March 2019 to evaluate the impact of interfacility neonatal transport for convalescent care. During the study period, our NICU accepted 33 infants from other tertiary NICUs and transferred 103 infants to other hospitals or clinics before their home discharge for convalescent care. Our NICU covered 39% of the total hospital days of infants accepted from other NICUs. Among infants transferred to other facilities, 81% born at our hospital were born to mothers transported to our obstetrics department as imminent high-risk deliveries; 94% of infants born at other hospitals were moved back to the referring facility. Interfacility neonatal transport for accepting and transferring infants for convalescent care is now an integral part of NICU practice, to bridge gaps between higher-level care facilities and homes. Establishment of well-defined transfer criteria and appropriate allocation of medical and staff resources among relevant facilities are desirable.

Same Game New Rules: What is the Impact of the 2018 UNOS Heart Allocation Change?

The 2018 UNOS heart allocation policy shifted priority from patients supported with durable devices to those with temporary mechanical support. We sought to quantify the implications of this change including impact on wait times, hospital bed utilization and use of mechanical circulatory support devices. This study was a retrospective review of 32 consecutive patients who underwent heart transplantation at a single center between October 2017 and May 2019. Patient charts were reviewed for information regarding preoperative characteristics, operative data, and perioperative characteristics. Univariate analysis compared demographics and outcomes before and after the October 2018 policy change. There were 16 patients each in the pre and post policy-change groups. Patients did not differ significantly in their demographic profiles. Significant differences were noted, however, in the time on transplant list with median days of 166 before vs. 18.5 after policy change (p= .017), and in the presence of preoperative temporary support (12.5% vs. 68.75%, p= .011). Prior to the allocation change most heart transplant patients were admitted from home on the day of transplant (9/16 vs. 6/16), while afterwards the average preoperative length of stay was 14.7 days with the majority of these days as ICU status (11.06). Operative times were shorter (593 vs. 685 median minute, p= .0026) in the post allocation change group. There was no difference in operating room blood transfusions, postoperative outcomes, or postoperative length of stay between the groups. This study suggests that following the 2018 policy change, patients who received heart transplants experienced shorter waitlist times, longer preoperative hospital stays, and had an increased use of temporary mechanical assist devices. This shift to a resource intensive inpatient management strategy has implications that will require further evaluation.

Review of the first comprehensive outpatient parenteral antimicrobial therapy program in a tertiary care hospital in Japan

ObjectivesThe infectious diseases team at Kameda Medical Center, Japan, implemented a new outpatient parenteral antimicrobial therapy (OPAT) program in July 2012 and expanded the program with the support of home care services. This study reviews the OPAT program after 5.5 years of operation. MethodsWe prospectively collected data about the age, sex, diagnoses, causative organisms, types of OPAT, modes of administration, selected antibiotics, treatment durations, bed days saved, outcomes, readmissions, and estimated cost reductions of all patients who were treated in the OPAT program from July 2012 to December 2017. ResultsOf the 66 patients treated under the OPAT program, 45 (68.2%) were treated using clinic OPAT, and 21 (31.8%) were treated using homecare OPAT. The most commonly targeted organism was methicillin-susceptible Staphylococcus aureus. Continuous infusion with elastomeric pumps was employed in 55 patients (83.3%). Cefazolin was the most frequently used antibiotic (39.4%), followed by penicillin G (24.2%). The median OPAT duration was 13 days (range, 3–51), and the total bed days saved was 923. The estimated medical cost reduction was approximately 87,000 US dollars. ConclusionsOur experience shows that OPAT is a safe and feasible practice not only for efficient bed utilization and medical cost savings but also for better antimicrobial stewardship.

Adsorption of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) from water using leaf biomass (Vitis vinifera) in a fixed-bed column study.

Adsorption of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) onto modified activated carbons (AC-H3PO4) produced from leaf biomass of Vitis vinifera leaf litter in a fixed bed column experiment was investigated in this study. The column bed was packed with the produced activated carbons in a uniform particle size of ˃ 64μm. Experimental parameters including the initial concentration of the solution, column bed height, the mass of adsorbent and flow rate were optimized to establish the best adsorption efficiency parameters for the system. Breakthrough and saturated time were estimated from the column fixed bed experimental data and analysed using the Adam-Bohart, Thomas model, and Yoon-Nelson models. Maximum sorption capacities of produced activated carbon ACH3PO4 based on Thomas model were 159.61 and 208.64mg/g for PFOA and PFOS, respectively. The results indicated the breakthrough and saturated time of the system increased concurrently with the increase in bed height and initial concentrations, while an increase in flow rate enhanced fractional bed utilization (FBU) efficiency of the column. Thomas and Yoon-Nelson model best describe the prediction of breakthrough data and sorption behaviour of PFOA and PFOS indicating suitability of AC-H3PO4 column design. Findings suggest that agro based adsorbent is a good alternative to non-ago based adsorbent. The surface characteristics of the phosphoric acid modified activated carbons AC-H3PO4 affirmed the removal of PFOA and PFOS from the contaminated water.

Data analytics for the sustainable use of resources in hospitals: Predicting the length of stay for patients with chronic diseases

Various factors are behind the forces that drive hospitals toward more sustainable operations. Hospitals contracting with Medicare, for instance, are reimbursed for the procedures performed, regardless of the number of days that patients stay in the hospital. This reimbursement structure has incentivized hospitals to use their resources (such as their beds) more efficiently to maximize revenues. One way hospitals can improve bed utilization is by predicting patients’ length of stay (LOS) at the time of admission, the benefits of which extend to employees, communities, and the patients themselves. In this paper, we employ a data analytics approach to develop and test a deep learning neural network to predict LOS for patients with chronic obstructive pulmonary disease (COPD) and pneumonia. The theoretical contribution of our effort is that it identifies variables related to patients’ prior admissions as important factors in the prediction of LOS in hospitals, thereby revising the current paradigm in which patients’ medical histories are rarely considered for the prediction of LOS. The methodological contributions of our work include the development of a data engineering methodology to augment the data sets, prediction of LOS as a numerical (rather than a binary) variable, temporal evaluation of the training and validation data sets, and a significant improvement in the accuracy of predicting LOS for COPD and pneumonia inpatients. Our evaluations show that variables related to patients’ previous admissions are the main driver of the deep network’s superior performance in predicting the LOS as a numerical variable. Using the assessment criteria introduced in prior studies (i.e., ±2 days and ±3 days tolerance), our models are able to predict the length of hospital stay with 86 % and 91 % accuracy for the COPD data set, and with 74 % and 85 % accuracy for the pneumonia data set. Hence, our effort could help hospitals serve a larger number of patients with a fixed amount of resources, thereby reducing their environmental footprint while increasing their revenue, as well as their patients’ satisfaction.

Abstract WP461: Stop in the Name of Falls

Background and Purpose: One of OhioHealth’s strategic priorities includes improving patient safety by eliminating preventable patient harm. The Integrated Stroke Unit (ISU) at Riverside Methodist Hospital worked to achieve this goal by reducing falls by 20%. The ISU consistently experienced a higher fall rate compared to like units across the nation. The ISU averaged over 7 falls per month with injury falls steadily increasing. The ISU experienced inconsistencies related to fall risk assessment and fall prevention interventions. As a result, a Fall Risk Scorecard was created to streamline interdisciplinary team work, increase patient safety, and improve safe patient handling and mobility. Methods: A multidisciplinary approach was used to improve patient safety and determine the root cause for patient falls. A team of nurses, rehab therapist, and patient support assistants was established. Inconsistencies were identified related to recognition of patients at risk for falls, types of fall interventions in place, and bed alarm knowledge and utilization. A need for visual management to standardize practice was seen. A Fall Risk Scorecard was created to help identify fall risk patients, standardize fall prevention interventions, and provide knowledge to staff regarding the patient’s activity level. The PDSA cycle was used to create standard work for the care team. Educational materials were developed and one-on-one training was provided to staff. The multidisciplinary approach helped to create a standardized process for each therapist coming to the ISU. The Fall Risk Scorecard was piloted for 3 months. Results: During the pilot, the unit saw a 57% reduction in falls. Current state, the ISU has continued to utilize the Fall Risk Scorecards and has sustained a 57% reduction in falls. With the utilization of lean methodology, members of the care team were able to ensure the right patient received the right intervention at the right time. With these results, the pilot has been selected for a system-wide roll-out over 11 different care sites. Conclusion: By taking a collaborative approach, utilizing lean methodology, and real-time problem solving, the ISU has successfully reached their goal to increase patient safety and improve safe patient handling and mobility.

Abstract TP349: Improving Utilization of ICU Care: Change in Intracerebral Hemorrhage Admission Protocol at a Comprehensive Stroke Center

Objectives: Non traumatic intracerebral hemorrhage (ICH) is responsible for 10-20% of acute stroke events and carries significant mortality concern. The protocol at our comprehensive stroke centers (CSC) is to admit all ICH patients to Neurosciences Intensive Care Unit (NSICU). We also have a stroke Intermediate Care Unit (IMCU) at our hospital which is a dedicated stroke unit where patients can be closely monitored and maintained on IV nicardipine. Optimal bed utilization is essential at our busy referral center. We aimed to develop criteria to identify ICH patients at low risk for clinical deterioration who could be admitted directly to our IMCU rather than the NSICU thereby improving overall utilization of monitored beds. Methods: Retrospective chart review for patients admitted between July 2018-Dec 2018 was performed. Age, sex, race, presenting Glasgow coma scale (GCS), ICH score, ICH volume, presence of IVH and location of the hemorrhage was documented. Patients who did not need any neurosurgical procedures (external ventricular drain, craniectomy or hematoma evacuation) and were not documented to have acute respiratory failure during their admission were considered appropriate for IMCU admission and were further assessed for hematoma expansion to determine stability throughout their hospital course. Results: 118 patients with ICH were included in the analysis, out of which 61 patients were suitable for IMCU admission. On univariable analysis, patients that had lower ICH scores (0.6±0.7 vs 2.5±0.9) and higher GCS score (14.1±1.4 vs 7.8±3.7) did not need any acute intervention. In this group of patients, only 9 (14.7%) patients had hematoma expansion documented out of which 6 (67%) patients had coagulation abnormalities on admission either due to medications or low platelet count. Conclusions: We conclude that the patients who had admission ICH score < 2, GCS ≥ 12 and no coagulation abnormalities on admission could have safely been admitted to our IMCU instead of the NSICU for further care and management. This would have led to a decrease in ICU admission rate. Application of such separate protocols for stroke IMCU admission vs ICU admission would lead to better utilization of resources at comprehensive stroke centers throughout the country.

Diagnose, indicate, and treat severe mental illness (DITSMI) as appropriate care: A three-year follow-up study in long-term residential psychiatric patients on the effects of re-diagnosis on medication prescription, patient functioning, and hospital bed utilization.

While polypharmacy is common in long-term residential psychiatric patients, prescription combinations may, from an evidence-based perspective, be irrational. Potentially, many psychiatric patients are treated on the basis of a poor diagnosis. We therefore evaluated the DITSMI model (i.e., Diagnose, Indicate, and Treat Severe Mental Illness), an intervention that involves diagnosis (or re-diagnosis) and appropriate treatment for severely mentally ill long-term residential psychiatric patients. Our main objective was to determine whether DITSMI affected changes over time regarding diagnoses, pharmacological treatment, psychosocial functioning, and bed utilization. DITSMI was implemented in a consecutive patient sample of 94 long-term residential psychiatric patients during a longitudinal cohort study without a control group. The cohort was followed for three calendar years. Data were extracted from electronic medical charts. As well as diagnoses, medication use and current mental status, we assessed psychosocial functioning using the Health of the Nations Outcome Scale (HoNOS). Bed utilization was assessed according to length of stay (LOS). Change was analyzed by comparing proportions of these data and testing them with chi-square calculations. We compared the numbers of diagnoses and medication changes, the proportions of HoNOS scores below cut-off, and the proportions of LOS before and after provision of the protocol. Implementation of the DITSMI model was followed by different diagnoses in 49% of patients, different medication in 67%, some improvement in psychosocial functioning, and a 40% decrease in bed utilization. Our results suggest that DITSMI can be recommended as an appropriate care for all long-term residential psychiatric patients.

Simulation modeling for predicting hospital admissions and bed utilisation

Demographic research of world population shows that societies are ageing. The ongoing changes in the population structure will require appropriate quantitative and qualitative adjustments in health services to meet the needs of society. Simulation methods turn out to be helpful in these kinds of analyses. In this paper, the authors present a case study on using discrete event simulation (DES) to support decision-making in the field of hospital bed management in the light of demographic changes. The case study was elaborated for one of the Polish district hospitals. A discrete simulation model was built to simulate admissions to two hospital wards: pediatric and geriatric. A series of experiments was carried out as based on real data extracted from the hospital database and forecasted demographic trends elaborated by The Central Statistical Office (CSO). The influence of demographic changes on hospital admissions in the chosen age-gender cohorts was explored, examining different variants of hospital bed availability. The results of the experiments show that demographic trends significantly influence healthcare admission and bed utilisation. The reduction in the number of admissions to the pediatric ward by about 6% results in a change in average bed utilisation from 57.90% to 54.06%. With about 12% more admissions to the geriatric ward, the change is from 68.88% to 75.59%.