Dataset Information

Evaluation of Biomedical Laboratory Performance Optimisation using the DEA Method.

ABSTRACT: Introduction:The Slovenian Resolution on the National Healthcare Plan notes that the country's medical laboratory activities are fragmented, which may result in cost-inefficiency and a reduction in the quality of the services provided. Defining the efficiency of laboratory service providers can therefore help us to pursue the objectives of the Resolution, i.e. to consolidate and integrate laboratory activities. Methods:Using the DEA method, we conducted an analysis of the efficiency of 20 biomedical laboratories in Slovenia, and made a comparison with a "virtual" laboratory, i.e. a merger of laboratories within a selected organisational unit. By testing different DEA models, we sought to determine whether the use of different input variables caused significant differences in the laboratories' efficiency scores. Results:The research results show that inefficiency resulting from the size of the units is 1.5 times greater than process inefficiency. Using a non-parametric Wilcoxon Signed Rank test, we determined, at a risk level of 0.05, that there was no difference between the efficiency results when using two different technical efficiency DEA models. When evaluating the virtually merged laboratory, we determined that, under all three models, the virtual laboratory achieved 100% VRS efficiency. However, when the CRS methodology was used, the laboratory showed a certain degree of scale inefficiency. Conclusions:When evaluating merger of medical laboratories we note that the DEA method is methodologically suitable for evaluating the effects of health policy implementation, and is an appropriate tool for identifying where the field of laboratory medicine might be further developed and improved.

SUBMITTER: Lamovsek N

PROVIDER: S-EPMC7478087 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Evaluation of Biomedical Laboratory Performance Optimisation using the DEA Method.

Lamovšek Nejc N Klun Maja M

Zdravstveno varstvo 20200625 3

<h4>Introduction</h4>The Slovenian Resolution on the National Healthcare Plan notes that the country's medical laboratory activities are fragmented, which may result in cost-inefficiency and a reduction in the quality of the services provided. Defining the efficiency of laboratory service providers can therefore help us to pursue the objectives of the Resolution, i.e. to consolidate and integrate laboratory activities.<h4>Methods</h4>Using the DEA method, we conducted an analysis of the efficien ...[more]

PMID: 32952718

Similar Datasets

Project description:IntroductionElectronic audit and feedback (e-A&F) systems are used worldwide for care quality improvement. They measure health professionals' performance against clinical guidelines, and some systems suggest improvement actions. However, little is known about optimal interface designs for e-A&F, in particular how to present suggested actions for improvement. We developed a novel theory-informed system for primary care (the Performance Improvement plaN GeneratoR; PINGR) that covers the four principal interface components: clinical performance summaries; patient lists; detailed patient-level information; and suggested actions. As far as we are aware, this is the first report of an e-A&F system with all four interface components.Objectives(1) Use a combination of quantitative and qualitative methods to evaluate the usability of PINGR with target end-users; (2) refine existing design recommendations for e-A&F systems; (3) determine the implications of these recommendations for patient safety.MethodsWe recruited seven primary care physicians to perform seven tasks with PINGR, during which we measured on-screen behaviour and eye movements. Participants subsequently completed usability questionnaires, and were interviewed in-depth. Data were integrated to: gain a more complete understanding of usability issues; enhance and explain each other's findings; and triangulate results to increase validity.ResultsParticipants committed a median of 10 errors (range 8-21) when using PINGR's interface, and completed a median of five out of seven tasks (range 4-7). Errors violated six usability heuristics: clear response options; perceptual grouping and data relationships; representational formats; unambiguous description; visually distinct screens for confusable items; and workflow integration. Eye movement analysis revealed the integration of components largely supported effective user workflow, although the modular design of clinical performance summaries unnecessarily increased cognitive load. Interviews and questionnaires revealed PINGR is user-friendly, and that improved information prioritisation could further promote useful user action.ConclusionsComparing our results with the wider usability literature we refine a previously published set of interface design recommendations for e-A&F. The implications for patient safety are significant regarding: user engagement; actionability; and information prioritisation. Our results also support adopting multi-method approaches in usability studies to maximise issue discovery and the credibility of findings.

Project description:BackgroundUndergraduate biomedical engineering (BME) students interested in pursuing a career in research and development of medical or physiological monitoring devices require a strong foundation in biosignal analysis as well as physiological theory. Applied learning approaches are reported to be effective for reinforcing physiological coursework; therefore, we propose a new laboratory protocol for BME undergraduate physiology courses that integrates both neural engineering and physiological concepts to explore involuntary skeletal muscle reflexes. The protocol consists of two sections: the first focuses on recruiting soleus motor units through transcutaneous electrical nerve stimulation (TENS), while the second focuses on exploring the natural stretch reflex with and without the Jendrassik maneuver. In this case study, third-year biomedical engineering students collected electromyographic (EMG) activity of skeletal muscle contractions in response to peripheral nerve stimulation using a BioRadio Wireless Physiology Monitor system and analyzed the corresponding signal parameters (latency and amplitude) using the MATLAB platform.Results/protocol validationElectrical tibial nerve stimulation successfully recruited M-waves in all 8 student participants and F-waves in three student participants. The students used this data to learn about orthodromic and antidromic motor fiber activation as well as estimate the neural response latency and amplitude. With the stretch reflex, students were able to collect distinct signals corresponding to the tendon strike and motor response. From this, they were able to estimate the sensorimotor conduction velocity. Additionally, a significant increase in the stretch reflex EMG amplitude response was observed when using the Jendrassik maneuver during the knee-jerk response. A student exit survey on the laboratory experience reported that the class found the module engaging and helpful for reinforcing physiological course concepts.ConclusionThis newly developed protocol not only allows BME students to explore physiological responses using natural and electrically-induced involuntary reflexes, but demonstrates that budget-friendly commercially available devices are capable of eliciting and measuring involuntary reflexes in an engaging manner. Despite some limitations caused by the equipment and students' lack of signal processing experience, this new laboratory protocol provides a robust framework for integrating engineering and physiology in an applied approach for BME students to learn about involuntary reflexes, neurophysiology, and neural engineering.

Dataset Information

Evaluation of Biomedical Laboratory Performance Optimisation using the DEA Method.

Publications

Evaluation of Biomedical Laboratory Performance Optimisation using the DEA Method.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets