Search results

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.

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.

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.

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.

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.

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.

Length of stay (LOS) in hospital after surgery varies for each patient depending on surgeon’s decision that considers criticality of the surgery, patient’s conditions before and after surgery, expected time to recovery and experience of the surgeon involved. Decision on patients’ LOS at hospital post-surgery affects overall healthcare performance as it affects both cost and quality of care. The purpose of this paper is to develop a model for deriving the most appropriate LOS after surgical interventions.

The study adopts an action research involving multiple stakeholders (surgeon, patients/patients’ relatives, hospital management and other medics). First, a conceptual model is developed using literature and experts’ opinion. Second, the model is applied in three surgical interventions in a public hospital in Malta to demonstrate the effectiveness of the model. Third, the policy alternatives developed are compared to a selection of current international standards for each surgical intervention. The proposed model analyses three LOS threshold policies for three procedures using efficiency and responsiveness criteria. The entire analysis is carried out using 325 randomly selected patient files along with structured interactions with more than 50 stakeholders (surgeon, patients/patients’ relatives, hospital management and other medics). A multiple criteria decision-making method is deployed for model building and data analysis. The method involves combining the analytic hierarchy process (AHP) for verbal subjective judgements on prioritizing the four predictors of surgical LOS—medical, financial, social and risk, with pairwise comparisons of the sub-criteria under each criterion in line with the concerned interventions—the objective data of which are obtained from the patients’ files.

The proposed model was successfully applied to decide on the best policy alternative for LOS for the three interventions. The best policy alternatives compared well to current international benchmarks.

The proposed method needs to be tested for other interventions across various healthcare settings.

Multi-criteria decision-making tools enable resource optimization and overall improvement of patient care through the application of a scientific management technique that involves all relevant stakeholders while utilizing both subjective judgements as well as objective data.

Traditionally, the duration of post-surgery LOS is mainly based on the surgeons’ clinical but also arbitrary decisions, with, as a result, having insufficiently explicable variations in LOS amongst peers for similar interventions. According to the authors’ knowledge, this is the first attempt to derive post-surgery LOS using the AHP, a multiple criteria decision-making method.

Point-of-care testing (POCT) at the Emergency Department (ED) attains better objectives in patient care while aiming to achieve early diagnosis for faster medical decision-making. This study assesses and compares the benefits of POCT in the ED in Germany and Malta, while considering differences in their health systems.

This chapter utilizes multiple case study approach using Six Sigma. The German case study assesses the use of POCT in acute coronary syndrome patients, compared to the central lab setting. The Maltese case study is a pilot study of the use of medical ultrasonography as a POCT to detect abdominal free fluid in post-blunt trauma.

This study provides clear examples of the effectiveness of POCT in life-threatening conditions, as compared to the use of traditional central lab or the medical imaging department. Therapeutic quality in the ED and patient outcomes directly depend upon turnaround time, particularly for life-threatening conditions. Faster turnaround time not only saves lives but reduces morbidity, which in the long-term is a critical cost driver for hospitals.

The application of Six Sigma and the international comparison of POCT as best practice for life-threatening conditions in the ED.