Measuring supply chain performance among public hospital laboratories

Performance assessment of medical diagnostic laboratories: A network DEA approach

RATIONALE, AIMS, AND OBJECTIVES

The main purpose of this paper is to measure the efficiency and ranking of medical diagnostic laboratories by applying a network data envelopment analysis (NDEA).

METHODS

In this study, each medical diagnostic laboratory is considered as a decision-making unit (DMU), and an NDEA model is utilized to calculate the efficiency of each medical diagnostic laboratory. Therefore, we design a series of four-stage system composed of three main laboratory processes (the pretest process, the test process, and the posttest process). We also consider sustainability criteria in order to cover social, economic, and environmental problems of health care organizations.

RESULTS

The results show that three of the 22 considered laboratories are efficient. Therefore, the NDEA approach can lead to performance scores and ultimately real ranking. Also, the average efficiency scores show that the decrease of the reception unit's efficiency results in a decrease of the efficiency of each laboratory. Therefore, the laboratories can increase the number of patients. Along with the intermediate values of the reception unit and the sampling unit, the efficiency of the reception unit increases, which results in an increase for the overall efficiency of each laboratory.

CONCLUSION

The proposed model can appropriately help the administrators and managers to identify inefficient units in their laboratory and ultimately improve the laboratory performance.

Sustainable efficiency assessment of private diagnostic laboratories under uncertainty

Purpose

Assessing the performance of medical laboratories plays an important role in the quality of health services. However, because of imprecise data, reliable results from laboratory performance cannot be obtained easily. The purpose of this paper is to illustrate the use of interval network data envelopment analysis (INDEA) based on sustainable development indicators under uncertainty.

Design/methodology/approach

In this study, each medical diagnostic laboratory is considered as a decision-making unit (DMU) and an INDEA model is used for calculating the efficiency of each medical diagnostic laboratory under imprecise inputs and outputs. The proposed model helps provide managers with effective performance scores for deficiencies and business improvements. The proposed model with realistic efficiency scores can help administrators manage their deficiencies and ultimately improve their business.

Findings

The results indicate that uncertainty can lead to changes in performance scores, rankings and performance classifications. Therefore, the use of DEA models under certainty can be potentially misleading.

Originality/value

The contribution of this study provides useful insights into the use of INDEA as a modeling tool to aid managerial decision-making in assessing efficiency of medical diagnostic laboratories based on sustainable development indicators under uncertainty.

Adaptation of the balanced scorecard model to measure performance of the departments at Dr Zainoel Abidin Regional General Hospital, Banda Aceh

Purpose

This paper aims to determine the performance of the departments at Dr Zainoel Abidin Regional General Hospital, Banda Aceh, Indonesia, in 2016, based on the targets and realization of their work programs using balanced scorecard.

Design/methodology/approach

This study adopted qualitative and quantitative approaches.

Findings

The overall results of the performance appraisal using the balanced scorecard approach seen from the financial, internal business, customer and training and learning perspectives are good. Dr Zainoel Abidin Regional General Hospital has provided good services, and performance of its departments have generated the expected outcome, realized by the Hospital.

Originality/value

The novelty of the present study lies in its research model, where human resources (transformational leadership, organizational commitment and resource uniqueness) and financial management (business plans, budget and performance).

Moderated influence of return frequency and resource commitment on information systems and reverse logistics strategic performance

Purpose

Reverse logistics (RL) is a strategic instrument across industries. The rapid evolution of online marketplaces has led to frequent product returns with variations across diversified businesses. These marketplaces have caused potential losses due to fraudulent returns, hence requiring a commitment of resources to RL. With information systems (IS) playing a role in improved supply chain performance, the purpose of this paper is to analyse the impact of a conceptualized IS framework on achieving RL strategic outcomes, under the individual moderating influence of resource commitment (RC) and return frequency.

Design/methodology/approach

Data have been collected through a questionnaire from top to middle management executives managing the supply chain, logistics and IS. Moderated regression analysis was conducted on the collected sample using Hayes’ (2013) process modeling.

Findings

The study depicts that IS capability, IS for logistics, IS partnership quality and IS for value addition lead to RL strategic benefits. Also, return frequency and RC act as relatively strong moderators with a negative impact. When analyzed for the individual IS constructs, RC has a stronger moderating impact than return frequency.

Practical implications

The IS usage framework can be used effectively by practitioners for enhancing strategic RL performances depending on variations in committed resources and return frequency for individual industries.

Originality/value

The study proposes an IS usage framework for achieving enhanced RL strategic outcomes and emphasizes on the moderating role played by RC and return frequency for producing the results.