Identifying logistical parameters in hospitals: Does literature reflect integration in hospitals? A scoping study

Impact of Life Cycle Costing in Procurement of Robotic Track-Based Central Laboratory at Apex Medical Institute in India

Introduction  Life cycle costing is an important management tool that takes into account the implications of planning, acquiring, operating, maintaining, and disposing of an asset during its complete life cycle. A major hindrance to the procurement of expensive equipment in developing countries is the lack of a reliable framework combining and integrating all the equipment life cycle aspects into procurement process. Methods  The study was conducted from the data collected from the bids that were received for procurement of two robotic track-based central laboratories which were installed at All India Institute of Medical Sciences (AIIMS), New Delhi. The procurement was done as per the guidelines laid down under General Finance Rules (GFR) 2017 following the two bid systems: technical bid and price/commercial bid. Results  A complete financial analysis of the robotic laboratory was done that involved gathering of all the pertinent financial information into one place and then using that data to analyze the feasibility of the bid. The life cycle costs of both the labs were calculated by assuming the life of equipment as 10 years and by factoring in cost of equipment including 5-year warranty, comprehensive maintenance from years 6 to 10, indicative cost of all reagents for 10 years, and indicative cost of all other consumables for 10 years. Conclusion  Results showed that the cost of equipment alone should not be the sole predictor of making purchase decisions of equipment. Further research may additionally explore differences between processes being followed in government versus private organizations, as well as national guidelines and subnational practices.

How to Use Lean Thinking for the Optimization of Clinical Pathways: A Systematic Review and a Proposed Framework to Analyze Pathways on a System Level

Lean Thinking and clinical pathways are commonly used concepts to improve healthcare. However, little is known on how to use Lean Thinking for the optimization of pathways or the quantification of both concepts. This study aims to create a framework to analyze pathways with Lean Thinking on a system level, by quantifying the seven wastes, flow and pull. A systematic literature review was performed. Inclusion criteria were the focus of the article on a well-defined group of patients and studied a pathway optimization with Lean Thinking. Data were extracted on measured outcomes, type of intervention and type of researched pathway. Thirty-six articles were included. No articles described the implementation of the Lean Thinking philosophy or studied the development of their people and partners ("4 P" model). Most articles used process optimization tools or problem-solving tools. The majority of the studies focused on process measures. The measures found in the review were used as input for our suggested framework to identify and quantify wastes, flow, and pull in a clinical pathway. The proposed framework can be used to create an overview of the improvement potential of a pathway or to analyze the level of improvement after an enhancement is introduced to a pathway. Further research is needed to study the use of the suggested quantifications.

Purchasing high-cost medical devices and equipment in hospitals: a systematic review

OBJECTIVES

To systematically review academic literature for studies on any processes, procedures, methods or approaches to purchasing high-cost medical devices and equipment within hospitals in high-income countries.

METHODS

On 13 August 2020, we searched the following from inception: Cost-Effectiveness Analysis Registry, EconLit and ProQuest Dissertations & Theses A&I via ProQuest, Embase, MEDLINE, and MEDLINE in Process via Ovid SP, Google and Google Scholar, Health Management and Policy Database via Ovid SP, IEEE Xplore Digital Library, International HTA Database, NHS EED via CRD Web, Science Citation Index-Expanded, Conference Proceedings Citation Index-Science, and Emerging Sources Citation Index via Web of Science, Scopus, and Zetoc conference search. Studies were included if they described the approach to purchasing (also known as procurement or acquisition) of high-cost medical devices and/or equipment conducted within hospitals in high-income countries between 2000 and 2020. Studies were screened, data extracted and results summarised in tables under themes identified.

RESULTS

Of 9437 records, 24 were included, based in 12 different countries and covering equipment types including surgical robots, medical imaging equipment, defibrillators and orthopaedic implants. We found heterogeneity in methods and approaches; including descriptions of processes taking place within or across hospitals (n=14), out of which three reported cost savings; empirical studies in which hospital records or participant data were analysed (n=8), and evaluations or pilots of proposed purchasing processes (n=2). Studies emphasise the importance of balancing technical, financial, safety and clinical requirements for device selection through multidisciplinary involvement (especially clinical engineers and clinicians) in decision-making, and the potential of increasing evidence-based purchasing decisions using approaches such as hospital-based health technology assessments, ergonomics and device 'user trials'.

CONCLUSIONS

We highlight the need for more empirical work that evaluates purchasing approaches or interventions, and greater specificity in study reporting (eg, equipment type, evaluation outcomes) to build the evidence base required to influence policy and practice for medical equipment purchasing.

PROTOCOL REGISTRATION

This review was registered in Open Science Framework: Shokraneh F, Hinrichs-Krapels S, Chalkidou A et al. Purchasing high-cost medical equipment in hospitals in OECD countries: A systematic review. Open Science Framework 2021; doi:10.17605/OSF.IO/GTXN8. Available at: https://osf.io/gtxn8/ (accessed 12 February 2022).

Explaining integration and differentiation by identifying the rules and coordination mechanisms in a hospital's logistical system

PURPOSE

Integration, that is, the coordination and alignment of tasks, is widely promoted as a means to improve hospital performance. A previous study examined integration and differentiation, that is, the extent to which tasks are segmented into subsystems, in a hospital's social network. The current study carries this research further, aiming to explain integration and differentiation by studying the rules and coordination mechanisms that agents in a hospital network use.

DESIGN/METHODOLOGY/APPROACH

The current case study deepens the analysis of the social network in a hospital. All planning tasks and tasks for surgery performance were studied, using a naturalistic inquiry approach and a mixed method.

FINDINGS

Of the 314 rules found, 85% predominantly exist in people's minds, 31% are in documents and 7% are in the information system. In the early planning stages for a surgery procedure, mutual adjustment based on hospital-wide rules is dominant. Closer to the day of surgery, local rules are used and open loops are closed through mutual adjustment, thus achieving integration. On the day of surgery, there is mainly standardization of work and output, based on hospital-wide rules. The authors propose topics for future research, focusing on increasing the hospital's robustness and stability.

ORIGINALITY/VALUE

This exploratory case study provides an overview of the rules and coordination mechanisms that are used for organizing hospital-wide logistics for surgery patients. The findings are important for future research on how integration and differentiation are effectively achieved in hospitals.

Identifying integration and differentiation in a Hospital's logistical system: a social network analysis of a case study

Background

Integration, the coordination and alignment of tasks, has been promoted widely in order to improve the performance of hospitals. Both organization theory and social network analysis offer perspectives on integration. This exploratory study research aims to understand how a hospital’s logistical system works, and in particular to what extent there is integration and differentiation. More specifically, it first describes how a hospital organizes logistical processes; second, it identifies the agents and the interactions for organizing logistical processes, and, third, it establishes the extent to which tasks are segmented into subsystems, which is referred to as differentiation, and whether these tasks are coordinated and aligned, thus achieving integration.

Methods

The study is based on case study research carried out in a hospital in the Netherlands. All logistical tasks that are executed for surgery patients were studied. Using a mixed method, data were collected from the Hospital Information System (HIS), documentation, observations and interviews. These data were used to perform a social network analysis and calculate the network metrics of the hospital network.

Results

This paper shows that 23 tasks are executed by 635 different agents who interact through 31,499 interaction links. The social network of the hospital demonstrates both integration and differentiation. The network appears to function differently from what is assumed in literature, as the network does not reflect the formal organizational structure of the hospital, and tasks are mainly executed across functional silos. Nurses and physicians perform integrative tasks and two agents who mainly coordinate the tasks in the network, have no hierarchical position towards other agents. The HIS does not seem to fulfill the interactional needs of agents.

Conclusions

This exploratory study reveals the network structure of a hospital. The cross-functional collaboration, the integration found, and position of managers, coordinators, nurses and doctors suggests a possible gap between organizational perspectives on hospitals and reality. This research sets a basis for further research that should focus on the relation between network structure and performance, on how integration is achieved and in what way organization theory concepts and social network analysis could be used in conjunction with one another.

An intelligent real-time scheduler for out-patient clinics: A multi-agent system model

Scheduling of resources and patients are crucial in outpatient clinics, particularly when the patient demand is high and patient arrivals are random. Generally, outpatient clinic systems are push systems where scheduling is based on average demand prediction and is considered for long term (monthly or bimonthly). Often, planning and actual scenario vary due to uncertainty and variability in demand and this mismatch results in prolonged waiting times and under-utilization of resources. In this article, we model an outpatient clinics as a multi-agent system and propose an intelligent real-time scheduler that schedules patients and resources based on the actual status of departments. Two algorithms are implemented: one for resource scheduling that is based on predictive demand and the other is patient scheduling which performs path optimization depending on the actual status of departments. In order to match resources with stochastic demand, a coordination mechanism is developed that reschedules the resources in the outpatient clinics in real time through auction-bidding procedures. First, a simulation study of intelligent real-time scheduler is carried out followed by implementation of the same in an outpatient clinic of Aravind Eye Hospital, Madurai, India. This hospital has huge patient demand and the patient arrivals are random. The results show that the intelligent real-time scheduler improved the performance measures like waiting time, cycle time, and utilization significantly compared to scheduling of resources and patients in isolation. By scheduling resources and patients, based on system status and demand, the outpatient clinic system becomes a pull system. This scheduler transforms outpatient clinics from open loop system to closed-loop system.