Impact of teaching intensity and academic status on medical resource utilization by teaching hospitals in Japan

Merging of two level-1 trauma centers in Amsterdam: premerger demand in integrated acute trauma care

PURPOSE

Availability of adequate and appropriate trauma care is essential. A merger of two Dutch academic level-1 trauma centers is upcoming. However, in the literature, volume effects after a merger are inconclusive. This study aimed to examine the premerger demand for level-1 trauma care on integrated acute trauma care and evaluate the expected demand on the system.

METHODS

A retrospective observational study was conducted between 1-1-2018 and 1-1-2019 in two level-1 trauma centers in the Amsterdam region using data derived from the local trauma registries and electronic patient records. All trauma patients presented at both centers' Emergency Departments (ED) were included. Patient- and injury characteristics and data concerning all prehospital and in-hospital-delivered trauma care were collected and compared. Pragmatically, the demand for trauma care in the post-merger setting was considered a sum of care demand for both centers.

RESULTS

In total, 8277 trauma patients were presented at both EDs, 4996 (60.4%) at location A and 3281 (39.6%) at location B. Overall, 462 patients were considered severely injured patients (Injury Severity Score ≥ 16). In total, 702 emergency surgeries (< 24 h) were performed, and 442 patients were admitted to the ICU. The sum care demand of both centers resulted in a 167.4% increase in trauma patients and a 151.1% increase in severely injured patients. Moreover, on 96 occasions annually, two or more patients within the same hour would require advanced trauma resuscitation by a specialized team or emergency surgery.

CONCLUSION

A merger of two Dutch level-1 trauma centers would, in this scenario, result in a more than 150% increase in the post-merger setting's demand for integrated acute trauma care.

The Three-Step Workflow: A Pragmatic Approach to Allocating Academic Hospitals’ Affiliations for Bibliometric Purposes

Purpose

A key question when ranking universities is whether or not to allocate the publication output of affiliated hospitals to universities. This paper presents a method for classifying the varying degrees of interdependency between academic hospitals and universities in the context of the Leiden Ranking.

Design/methodology/approach

Hospital nomenclatures vary worldwide to denote some form of collaboration with a university, however they do not correspond to universally standard definitions. Thus, rather than seeking a normative definition of academic hospitals, we propose a three-step workflow that aligns the university-hospital relationship with one of three general models: full integration of the hospital and the medical faculty into a single organization; health science centres in which hospitals and medical faculty remain separate entities albeit within the same governance structure; and structures in which universities and hospitals are separate entities which collaborate with one another. This classification system provides a standard through which publications which mention affiliations with academic hospitals can be better allocated.

Findings

In the paper we illustrate how the three-step workflow effectively translates the three above-mentioned models into two types of instrumental relationships for the assignation of publications: “associate” and “component”. When a hospital and a medical faculty are fully integrated or when a hospital is part of a health science centre, the relationship is classified as component. When a hospital follows the model of collaboration and support, the relationship is classified as associate. The compilation of data following these standards allows for a more uniform comparison between worldwide educational and research systems.

Research limitations

The workflow is resource intensive, depends heavily on the information provided by universities and hospitals, and is more challenging for languages that use non-Latin characters. Further, the application of the workflow demands a careful evaluation of different types of input which can result in ambiguity and makes it difficult to automatize.

Practical implications

Determining the type of affiliation an academic hospital has with a university can have a substantial impact on the publication counts for universities. This workflow can also aid in analysing collaborations among the two types of organizations.

Originality/value

The three-step workflow is a unique way to establish the type of relationship an academic hospital has with a university accounting for national and regional differences on nomenclature.

Models and methods for determining the optimal number of beds in hospitals and regions: a systematic scoping review

BACKGROUND

Determining the optimal number of hospital beds is a complex and challenging endeavor and requires models and techniques which are sensitive to the multi-level, uncertain, and dynamic variables involved. This study identifies and characterizes extant models and methods that can be used to determine the required number of beds at hospital and regional levels, comparing their advantages and challenges.

METHODS

A systematic search was conducted using Web of Science, Scopus, Embase and PubMed databases, with the search terms hospital bed capacity, hospital bed need, hospital, bed size, model, and method.

RESULTS

Twenty-three studies met the criteria to be included in the review. Of these studies, a total of 11 models and 5 methods were identified, mainly designed to determine hospital bed capacity at the regional level. Common determinants of the required number of hospital beds in these models included demographic changes, average length of stay, admission rates, and bed occupancy rates.

CONCLUSIONS

There are no specific norms for the required number of beds at hospital and regional levels, but some of the identified models and methods may be used to estimate this number in different contexts. Moreover, it is important to consider alternative approaches to planning hospital capacity like care pathways to fix the limitations of "bed numbers".

Assessing the relationships between hospital resources and activities: a systematic review

Face the challenge of minimizing their resource utilization without reducing the quality of healthcare. Achieving this aim requires precise analysis and optimization of various inputs and outputs. This paper presents a systematic review of the relationships between hospital resources (considered productivity inputs) and financial and activity outcomes (considered productivity outputs). Several electronic bibliographic databases and the Internet were searched for articles published between January 1990 and December 2013 that examined the relationships between hospital resources and financial and activity outcomes. We assessed the quality of the study design, the nature of the sample, input and output indicators, and the statistical methods used for each selected study. Thirty-eight original papers were selected. Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) were the most statistical methods used. Based on our analysis, we retained 18 input and 19 output indicators that could constitute the basis for hospital productivity benchmarking. Selecting a small set of shared economic and activity indicators is relevant for assessing the productivity of a hospital, measuring trends and performing national or international benchmarking. Such indicators should be combined with quality measures for a comprehensive evaluation approach.