Innovation management using logical framework in hospital-based healthcare units

Innovation is part and parcel of any service in today's environment, so as to remain competitive. Quality improvement in healthcare services is a complex, multi-dimensional task. This study proposes innovation management in healthcare services using a logical framework. A problem tree and an objective tree are developed to identify and mitigate issues and concerns. A logical framework is formulated to develop a plan for implementation and monitoring strategies, potentially creating an environment for continuous quality improvement in a specific unit. We recommend logical framework as a valuable model for innovation management in healthcare services. Copyright © 2006 Inderscience Enterprises Ltd.

Managing healthcare quality using logical framework analysis

Purpose - The purpose of this paper is to develop an integrated quality management model that identifies problems, suggests solutions, develops a framework for implementation and helps to evaluate dynamically healthcare service performance. Design/methodology/approach - This study used the logical framework analysis (LFA) to improve the performance of healthcare service processes. LFA has three major steps - problems identification, solution derivation, and formation of a planning matrix for implementation. LFA has been applied in a case-study environment to three acute healthcare services (Operating Room utilisation, Accident and Emergency, and Intensive Care) in order to demonstrate its effectiveness. Findings - The paper finds that LFA is an effective method of quality management of hospital-based healthcare services. Research limitations/implications - This study shows LFA application in three service processes in one hospital. This very limited population sample needs to be extended. Practical implications - The proposed model can be implemented in hospital-based healthcare services in order to improve performance. It may also be applied to other services. Originality/value - Quality improvement in healthcare services is a complex and multi-dimensional task. Although various quality management tools are routinely deployed for identifying quality issues in healthcare delivery, they are not without flaws. There is an absence of an integrated approach, which can identify and analyse issues, provide solutions to resolve those issues, develop a project management framework to implement those solutions. This study introduces an integrated and uniform quality management tool for healthcare services. © Emerald Group Publishing Limited.

A stepwise fuzzy linear programming model with possibility and necessity relations

Linear programming (LP) is the most widely used optimization technique for solving real-life problems because of its simplicity and efficiency. Although conventional LP models require precise data, managers and decision makers dealing with real-world optimization problems often do not have access to exact values. Fuzzy sets have been used in the fuzzy LP (FLP) problems to deal with the imprecise data in the decision variables, objective function and/or the constraints. The imprecisions in the FLP problems could be related to (1) the decision variables; (2) the coefficients of the decision variables in the objective function; (3) the coefficients of the decision variables in the constraints; (4) the right-hand-side of the constraints; or (5) all of these parameters. In this paper, we develop a new stepwise FLP model where fuzzy numbers are considered for the coefficients of the decision variables in the objective function, the coefficients of the decision variables in the constraints and the right-hand-side of the constraints. In the first step, we use the possibility and necessity relations for fuzzy constraints without considering the fuzzy objective function. In the subsequent step, we extend our method to the fuzzy objective function. We use two numerical examples from the FLP literature for comparison purposes and to demonstrate the applicability of the proposed method and the computational efficiency of the procedures and algorithms. © 2013-IOS Press and the authors. All rights reserved.

Trademarks with a reputation:bridging the 'logical lapse'

The article focuses on the Trade Marks Regulations 2004, which came into force on May 5, 2004. Regulation 7 repeals s 5(3)(b) and amends s 10(3) of the Trade Marks Act 1994, implementing the decision of the European Court of Justice in Davidoff & Cie SA and Zino Davidoff SA v Gofkid Ltd., which was then confirmed in Adidas-Salomon AG and Adidas Benelux BV v Fitnessworld Trading Ltd. The orthodox definition of the primary and proper function of a trademark is that it is to identify the origin or ownership of the goods to which the mark is affixed. As society has changed so too have the functions of the trademark. Due to increased affluence and the growth of the consumer society, some trademarks may now have achieved the status of being a symbol of desire in their own right.

Combined quality function deployment and logical framework analysis to improve quality of emergency care in Malta

Purpose – The purpose of this paper is to develop an integrated patient-focused analytical framework to improve quality of care in accident and emergency (A&E) unit of a Maltese hospital. Design/methodology/approach – The study adopts a case study approach. First, a thorough literature review has been undertaken to study the various methods of healthcare quality management. Second, a healthcare quality management framework is developed using combined quality function deployment (QFD) and logical framework approach (LFA). Third, the proposed framework is applied to a Maltese hospital to demonstrate its effectiveness. The proposed framework has six steps, commencing with identifying patients’ requirements and concluding with implementing improvement projects. All the steps have been undertaken with the involvement of the concerned stakeholders in the A&E unit of the hospital. Findings – The major and related problems being faced by the hospital under study were overcrowding at A&E and shortage of beds, respectively. The combined framework ensures better A&E services and patient flow. QFD identifies and analyses the issues and challenges of A&E and LFA helps develop project plans for healthcare quality improvement. The important outcomes of implementing the proposed quality improvement programme are fewer hospital admissions, faster patient flow, expert triage and shorter waiting times at the A&E unit. Increased emergency consultant cover and faster first significant medical encounter were required to start addressing the problems effectively. Overall, the combined QFD and LFA method is effective to address quality of care in A&E unit. Practical/implications – The proposed framework can be easily integrated within any healthcare unit, as well as within entire healthcare systems, due to its flexible and user-friendly approach. It could be part of Six Sigma and other quality initiatives. Originality/value – Although QFD has been extensively deployed in healthcare setup to improve quality of care, very little has been researched on combining QFD and LFA in order to identify issues, prioritise them, derive improvement measures and implement improvement projects. Additionally, there is no research on QFD application in A&E. This paper bridges these gaps. Moreover, very little has been written on the Maltese health care system. Therefore, this study contributes demonstration of quality of emergency care in Malta.

Continuous quality improvement in a Maltese hospital using logical framework analysis

Purpose: The purpose of this paper is to present the application of logical framework analysis (LFA) for implementing continuous quality improvement (CQI) across multiple settings in a tertiary care hospital. Design/methodology/approach: This study adopts a multiple case study approach. LFA is implemented within three diverse settings, namely, intensive care unit, surgical ward, and acute in-patient psychiatric ward. First, problem trees are developed in order to determine the root causes of quality issues, specific to the three settings. Second, objective trees are formed suggesting solutions to the quality issues. Third, project plan template using logical framework (LOGFRAME) is created for each setting. Findings: This study shows substantial improvement in quality across the three settings. LFA proved to be effective to analyse quality issues and suggest improvement measures objectively. Research limitations/implications: This paper applies LFA in specific, albeit, diverse settings in one hospital. For validation purposes, it would be ideal to analyse in other settings within the same hospital, as well as in several hospitals. It also adopts a bottom-up approach when this can be triangulated with other sources of data. Practical implications: LFA enables top management to obtain an integrated view of performance. It also provides a basis for further quantitative research on quality management through the identification of key performance indicators and facilitates the development of a business case for improvement. Originality/value: LFA is a novel approach for the implementation of CQI programs. Although LFA has been used extensively for project development to source funds from development banks, its application in quality improvement within healthcare projects is scant.