Modular structures and the delivery of inpatient care in hospitals: a Network Science perspective on healthcare function and dysfunction.

BACKGROUND: Reinforced by the COVID-19 pandemic, the capacity of health systems to cope with increasing healthcare demands has been an abiding concern of both governments and the public. Health systems are made up from non-identical human and physical components interacting in diverse ways in varying locations. It is challenging to represent the function and dysfunction of such systems in a scientific manner. We describe a Network Science approach to that dilemma. General hospitals with large emergency caseloads are the resource intensive components of health systems. We propose that the care-delivery services in such entities are modular, and that their structure and function can be usefully analysed by contemporary Network Science. We explore that possibility in a study of Australian hospitals during 2019 and 2020. METHODS: We accessed monthly snapshots of whole of hospital administrative patient level data in two general hospitals during 2019 and 2020. We represented the organisations inpatient services as network graphs and explored their graph structural characteristics using the Louvain algorithm and other methods. We related graph topological features to aspects of observable function and dysfunction in the delivery of care. RESULTS: We constructed a series of whole of institution bipartite hospital graphs with clinical unit and labelled wards as nodes, and patients treated by units in particular wards as edges. Examples of the graphs are provided. Algorithmic identification of community structures confirmed the modular structure of the graphs. Their functional implications were readily identified by domain experts. Topological graph features could be related to functional and dysfunctional issues such as COVID-19 related service changes and levels of hospital congestion. DISCUSSION AND CONCLUSIONS: Contemporary Network Science is one of the fastest growing areas of current scientific and technical advance. Network Science confirms the modular nature of healthcare service structures. It holds considerable promise for understanding function and dysfunction in healthcare systems, and for reconceptualising issues such as hospital capacity in new and interesting ways.

Effective Response to Hospital Congestion Scenarios: Simulation-Based Evaluation of Decongestion Interventions.

Hospital overcrowding is becoming a major concern in the modern era due to the increasing demand for hospital services. This study seeks to identify effective and efficient ways to resolve the serious problem of congestion in hospitals by testing a range of decongestion strategies with simulated scenarios. In order to determine more efficient solutions, interventions with smaller changes were consistently tested at the beginning through a simulation platform. In addition, the implementation patterns were investigated, which are important to hospital managers with respect to the decisions made to control hospital congestion. The results indicated that diverting a small number of ambulances seems to be more effective and efficient in congestion reduction compared to other approaches. Furthermore, instead of implementing an isolated approach continuously, combining one approach with other strategies is recommended as a method for dealing with hospital overcrowding.

A virtual evaluation of options for managing risk of hospital congestion with minimum intervention.

Hospital congestion is a common problem for the healthcare sector. However, existing approaches including hospital resource optimization and process improvement might lead to huge cost of human and physical structure changes. This study evaluated less disruptive interventions based on a hospital simulation model and offer objective reasoning to support hospital management decisions. This study tested a congestion prevention method that estimates hospital congestion risk level (R), and activates minimum intervention when R is above certain threshold, using a virtual hospital created by simulation modelling. The results indicated that applying a less disruptive intervention is often enough, and more cost effective, to reduce the risk level of hospital congestion. Moreover, the virtual implementation approach enabled testing of the method at a more detailed level, thereby revealed interesting findings difficult to achieve theoretically, such as discharging extra two medical inpatients, rather than surgical inpatients, a day earlier on days when R is above the threshold, would bring more benefits in terms of congestion reduction for the hospital.

Case report: Streptococcus pneumoniae pneumonia characterized by diffuse centrilobular nodules in both lungs.

Background: Streptococcus pneumoniae (S. pneumoniae) is the most common pathogen in community-acquired pneumonia (CAP) and takes the form of lobar pneumonia as typical computed tomography (CT) findings. Various patterns of radiological manifestation have also been reported in patients with S. pneumoniae pneumonia; however, the appearance of diffuse centrilobular nodules in both lungs is rarely reported. Case presentation: We report the case of a patient with a history of chronic lymphocytic leukemia (CLL) for 9 years who presented with new-onset fever, cough, excess sputum, and shortness of breath for 1 week. He was given intravenous antibacterial (cephalosporin) treatment for 4 days, but his condition did not improve and dyspnea became more serious. The chest CT indicated diffuse centrilobular nodules in both lungs at admission. Patient's bronchoalveolar (BAL) fluid was sent for metagenomic next-generation sequencing, which only supported a diagnosis of S. pneumoniae infection. His condition improved gradually after antimicrobial treatment (moxifloxacin) and a follow-up CT showed that the diffuse centrilobular nodules in both lungs were absorbed completely. Conclusion: This case highlights a rare CT presentation of S. pneumoniae pneumonia that should alert clinicians, so as to avoid taking unnecessary treatment measures.

Hospital's instability wedges.

In this study, we define a hospital congestion episode as a situation where the number of new patients needing admission is greater than the number of available beds in the hospital, and investigate the likelihood that the current day's midnight occupancy will exceed any specified threshold level. We demonstrate that this measure of risk exhibits a characteristic sensitivity phenomenon that we have named as hospital's instability wedge. In particular, it is seen that frequently even small changes in the numbers of patients admitted or discharged can dramatically change the risk of exceeding the threshold, thereby changing the risk of subsequent congestion episodes. While this finding captures a salient difficulty of operating a modern public hospital, it also opens up an opportunity for monitoring and alleviating the above defined risk with only small changes in admission, discharge, and cancellation rates. A case study with recent patient journey data from Flinders Medical Centre in South Australia is presented.

Hospital occupancy and discharge strategies: a simulation-based study.

BACKGROUND: Increasing demand for hospital services has resulted in more arrivals to emergency department (ED), increased admissions, and, quite often, access block and ED congestion, along with patients' dissatisfaction. Cost constraints limit an increase in the number of hospital beds, so alternative solutions need to be explored. AIMS: To propose and test different discharge strategies, which, potentially, could reduce occupancy rates in the hospital, thereby improving patient flow and minimising frequency and duration of congestion episodes. METHODS: We used a simulation approach using HESMAD (Hospital Event Simulation Model: Arrivals to Discharge) - a sophisticated simulation model capturing patient flow through a large Australian hospital from arrival at ED to discharge. A set of simulation experiments with a range of proposed discharge strategies was carried out. The results were tabulated, analysed and compared using common hospital occupancy indicators. RESULTS: Simulation results demonstrated that it is possible to reduce significantly the number of days when a hospital runs above its base bed capacity. In our case study, this reduction was from 281.5 to 22.8 days in the best scenario, and reductions within the above range under other scenarios considered. CONCLUSION: Some relatively simple strategies, such as 24-h discharge or discharge/relocation of long-staying patients, can significantly reduce overcrowding and improve hospital occupancy rates. Shortening administrative and/or some treatment processes have a smaller effect, although the latter could be easier to implement.

Cord blood-derived cytokine-induced killer cells biotherapy combined with second-line chemotherapy in the treatment of advanced solid malignancies.

This study investigated the efficacy of cord blood-derived cytokine-induced killer (CB-CIK) biotherapy combined with second-line chemotherapy in treating advanced solid malignancies after first-line chemotherapy failure. Forty patients with advanced solid malignancies after first-line chemotherapy failure were divided into two groups: CB-CIK cells transfusion plus second-line chemotherapy (CB-CIK+Chemotherapy) group and second-line chemotherapy alone (Chemotherapy) group. The ORR and DCR were 30% and 80% in CB-CIK + Chemotherapy group compared with 15% and 70% in Chemotherapy group (P = 0.451 for ORR and P = 0.716 for DCR) respectively. The time to progression and the median survival time were 3.45 months (95% CI 2.30-4.60 months) and 11.17 months (95% CI 9.05-13.28 months) in CB-CIK+Chemotherapy group compared with 2.03 months (95% CI 1.23-2.82 months) and 7.52 months (95% CI 5.97-9.06 months) in Chemotherapy group respectively. Compared with patients in Chemotherapy group, the patients in CB-CIK+Chemotherapy group had significantly longer PFS (P = 0.031) and overall survival (P = 0.048). In vitro studies further revealed that CB-CIK cells could overcome drug resistance in cisplatin-resistant lung adenocarcinoma cell line A549/CDDP through downregulating ABCG-2 and P-gp and induce cytotoxicity through the high level expression of CD3, CD56, FasL, and CD69. This could explain why CB-CIK could have synergistic effects with second-line chemotherapy shown in this clinical study. We concluded CB-CIK cells combined with second-line chemotherapy can significantly improve PFS and median survival compared with second-line chemotherapy alone in patients with advanced solid malignancies after first-line chemotherapy failure.