Saide Jorge Calil

Health Failure Mode and Effect Analysis for Clinical Engineering: Application on Cardiac Defibrillators

Attempting to guarantee the quality of cardiac defibrillators, a study was performed at a Brazilian public hospital applying the Health Care Failure Mode and Effect Analysis. Although this technique was developed for applications within the healthcare process, it can be adapted for usage by the clinical engineering to identify the failure modes of medical equipment and to assess the involved risks. Through this study, problems that interfere with the performance of cardiac defibrillators were identified and, subsequently, some actions were proposed to help reduce the risks of these potential problems. These actions certify the safe functioning of this device within the standards of safety and quality.

Findings of the Worldwide Clinical Engineering Survey conducted by the Clinical Engineering Division of the International Federation for Medicine and Biological Engineering

Despite the clinical engineering profession already exists in most parts of the world, one cannot say that its activities and profile are the same in each country. However, just a number of few countries have already conducted a survey to identify the characteristics of its clinical engineers. This survey, developed by the International Federation for Medicine and Biological Engineering, is the first attempt to identify the clinical engineer, the clinical engineering activities and the kind of employer worldwide. The results have shown significant differences according to the analyzed region.

Risk Classification of Medical Equipment in Alert States

Safety is todays one of the major issues within the health area all over the world. Among the factors that affect safety are the hazards originated by the utilization of medical equipment. Aiming at the reduction of the risks from such equipment, the clinical engineering groups have been developing programs for preventive maintenance and routines for safety inspections. Allied to these actions, the risk management techniques contribute to increase the efficiency of the risk control for medical equipment utilization. In this sense, a proposal of risk classification is presented here.

Clinical engineering in Brazil: current status.

It is estimated that 20-40% of all existing healthcare equipment in Brazil is not working because of a lack of service, parts, or supplies, or because it has not been installed. Traditionally, equipment goes completely unattended until a complete failure occurs. Then, it sits idle, paralyzing those services provided by it, until its owner gathers enough money to afford the extravagant repairs provided by manufacturers and their representatives, with little continuing assurance of quality and efficacy. During the last 10 years, a few medical institutions have started to establish their own clinical engineering (CE) teams. Besides providing significant savings, these pioneers are contributing to the improvement of the process of managing the introduction of technology into healthcare. Now, about 10% of all hospitals with more than 150 beds have their own CE departments. Three years ago, the Brazilian Association of Hospital Engineering and Maintenance was created to promote the recognition of CE as a new profession. The main difficulties that inhibit the faster and wider adoption of the self-reliant approach are analyzed and some possible solutions are discussed.

The Importance of a Safety Culture in Healthcare Facilities for the Development of an Incident Investigation System

Different industry sectors have developed numerous tools for risk management, from simple risk assessments to more complex tools like FMEA and incident investigation methodologies. Although the healthcare sector deals with a highly risky environment, little has been done if compared to other Industry sectors and service providers with the same level of inherent risk. To overcome these deficiencies, some methodologies have been created to fill the existing gaps in healthcare facilities, being one of these the incident investigation system. Although this methodology is very effective as one of the risk management tools, to obtain better results it requires the implementation of an adequate safety culture before its development. This article will discuss the importance of a safety culture inside a healthcare institution for the adequate development of an incident investigation system. The limitations and barriers due to the lack of a safety culture towards the incident investigation will be discussed over the different phases of an incident investigation system. The consequences and the difficulties faced by the implementers will be presented, as well as the solutions and benefits that will blossom from the implementation of a safety culture allied to an incident investigation system.

Allocation of Medical Equipment Costs to Medical Procedures

Despite the little amount of information about the contribution of hardware and software to the cost of providing health care, much of the raise in the sector’s expenditures in the last decades has been pointed out as result of the increasing use of medical equipment. This study presents a method to analyze the way medical equipment consumes resources during medical procedures and to estimate the costs of these resources. Focusing on the medical procedure, the method combines Time-Driven Activity-Based Costing (TDABC) and Total Cost of Ownership (TCO) to evaluate the role of medical equipment in the process of delivering health care. The method is composed of two phases: (1) mapping of the resource consumption structure, from medical procedure activities to resources and (2) identification and allocation of costs, from resources to activities. The method does not consider human resources’ costs but only the ones directly related to the equipment (such as accessories, disposables and maintenance). The results showed that the cost contribution of equipment in a medical procedure depends on the way it is used in each procedure and on the hospital’s specific practices.

Connectionist Model to Help the Evaluation of Medical Equipment Purchasing Proposals

There is in the developing world a great number of idle medical equipment, due to the absence of experienced professionals to conduct an effective purchasing plan in its several phases, including vendors proposals evaluation. As artificial neural networks are typically applied for pattern recognition and function approximation, it was developed a decision-making computational model, based on artificial neural networks, which entries were grades given to physical risk, cost and strategic importance to a chosen medical equipment. The outputs were also grades attributed by clinical engineers according to the importance of five factors (clinical, financial, quality, safety and technical) during the equipment evaluation. The use of the model’s outcome allows any clinical engineer to identify the proposal that best attend the health unit requirements. To validate this model, a national inquiry (32 clinical engineers) was conducted using an electronic chart that permitted to: (a) establish a major professional profile of the inquired engineers; (b) determine which were the most important criteria considered during a medical equipment procurement process and (c) generate 95 examples that were used to train, and to test, diverse types of artificial neural networks. Hence, to represent the knowledge of clinical engineers (for the evaluation process of purchasing proposals) who worked at public hospitals, with three to ten years of experience, the best results were encountered for an ensemble of 100 two-hidden-layers perceptrons trained with the Backpropagation algorithm. The neural networks responses presented average reliability superior than 85% in all cases studied. Therefore, a connectionist computational model can be useful during a decision making process to help hospital managers to choose an appropriate medical equipment.

A Method to Create Resource Consumption Profiles for Biomedical Equipment

Much of the raise in the healthcare sector’s expenditures in the last few decades has been pointed out as result of the increasing use of medical equipment, but little is actually known about the contribution of hardware and soft-ware to the cost of providing health care. This study presents a method to create resource consumption profiles within medical procedures. Based on Time-Driven Activity-Based Costing (TDABC), the method focuses on the medical procedure to evaluate the way medical equipment consumes resources in the process of delivering health care. The mapping of the resource consumption structure is gradually done, from medical procedure activities to resources. Because the focus is on the bio-medical equipment (BME), the method ignores human re-sources and considers only the ones directly related to the equipment (such as maintenance, accessories and disposables). The results showed that the resource consumption of equipment in a medical procedure depends on each specific procedure and on the hospital’s specific practices.

Incident Investigation in the Healthcare System: a Comparative Analysis Derived from the Chemical Industries

Incidents and near misses are found in any kind of industry or service provider. Owing to the high impact of certain incidents, some industries like chemical, automotive and airline have developed methodologies to manage risks and avoid occurrences by studying previous incident. These methodologies have been widely developed and a complete incident investigation system has been built, suited for incidents occurring within each particular industry. In the healthcare system, only nowadays it is possible to see some action to reduce existing risks. Unfortunately, the safety programs found in healthcare facilities usually focus in biohazards reduction, leaving behind several safety issues that, if considered, could avoid the majority of occurrences. Considering the large amount of existing methodologies and the characteristics of the incidents, they can be specifically adapted according to the needs of incident investigation in the healthcare system. An analysis of reported incidents and characteristics of the chemical industries and the healthcare facilities is developed to consider the differences between each environment. Then a detailed assessment of existing methodologies and its characteristics is developed considering three categories: evidence gathering, witness interviews and equipment analysis. Analyzing the reported incidents, each of the categories above is adapted from an already available set of methodologies. In the first category, despite the different characteristics of the evidences, it is possible to adapt the procedures used for chemical industries, due to minor scope of evidence gathering in healthcare system’s incidents. The interview process available for chemical industries is not adequate to use within the healthcare system’s incidents, which imposed the use of a different methodology. The combination of methodologies from different sources is more adequate for the equipment analysis category, due to already developed methodologies specific for equipment incidents. Changes in the culture of the healthcare system and behavior after an incident are discussed in this study to achieve a better and safer system. Much has to be done to attain a complete guide for incident investigation within the healthcare system, but the existing groundwork from other industries allows the adaptation and merging of the existing data into one methodology appropriate to the healthcare system.

Computerized blood-flow evaluation in vascular surgeries with a CW Doppler

The main difficulty found in vascular surgery is reliable evaluation of intraoperatory performance of vascular prosthesis in patients with vascular diseases. A system is proposed which uses CW Doppler ultrasonic equipment. The ultrasonic transducer is fixed on arteries and/or prosthesis using a special device, developed by the authors for on-site blood flow evaluation. A 16-bit microcomputer connected to the ultrasonic system digitalizes, stores in a circular memory, and processes a series of 12 signals chosen on screen by the keyboard, using functions also developed here. The signals are summed, using the peak of the QRS complex as trigger, to obtain the average result. Special software was developed to detect the QRS peak and calculate some parameters. All the results, including the averaged curve, are shown on the screen.<<ETX>>