How to Make Your Work Really Influence Future Healthcare

Future health systems, besides traditional areas defined and addressed since 1980, face the advent of Proactive, Predictive, Prospective, Preventive, Participative and Personalized health care (HC). Reliable e-health platforms can help us with these challenges. They should be designed and implemented in a way to help ordinary people achieve extraordinary results. Even the best projects addressing HC systems improvement are not automatically qualified for implementation unless adopted by policy makers. The introduction of strategies with a potential for healthcare systems improvement to policy makers is necessary but difficult because of the complexity of the addressed issue. Illustrated on four projects, selected from the 25 the author participated in, from 1993 to 2016, principles, processes and attitudes found beneficial for successful policy implementation in various healthcare environments, are presented, to help with the integration of reliable electronic healthcare platforms into coming healthcare systems.

We Can Trust without Data, But We Are Accountable Only through Measurement

Traditional expectations about healthcare continue to be challenged by the umbrella concerns about accountability and trust. The core of this challenge is two-fold: healthcare providers have seen the absolute trust placed into their intentions and practices erode through the quantification of quality and safety of care, and, the recipients of care have been empowered with timely and specific data to demand accountability rather than unquestionably trust providers. The purpose of this chapter is to review the key dimensions of the operationalization of performance measurement and the translation of its findings to statements about quality and safety of care. The past four decades have seen the continuous discovery and refining of analytical tools to quantify what once was taken for granted: that patients always receive the best care possible. These tools have uncovered the probabilistic nature of medicine and the resulting nature of the relationships outcomes have to processes. Hence the expectations of patients, payers of care and policy makers require being continuously modified to reflect the limitations of medicine and healthcare. The education of various audiences as to what the measures mean not only is a necessary requisite for sound project design but also will determine how the accountability model is shaped in each environment based on the generic measurement tools results, local traditions of care and caring, and expectations about outcomes.

Improving Quality Improvement Collaboratives

For several decades, researchers have studied the comparative effects of face-to-face and electronic communication. Some have claimed that electronic communication is detrimental to outcomes while others have emphasized its advantages. For members of healthcare quality improvement (QI) collaboratives, a mix of both of types of communication is often used, due to geographical dispersion. This chapter examines the outcomes of a specific QI collaborative, the Empira Falls Prevention project in Minnesota, USA. Levels of electronic communication between collaborative members were found to be associated with a positive patient outcome, specifically a reduction in falls. Electronic and face-to-face communication differed in their association with success measures for the collaborative. The findings suggest that the two modes of communication can be leverage to attain maximum benefits from participating in a quality improvement collaborative.

Migrating from ISO/IEC 9126 to SQUARE

When it comes to the evaluation of natural language systems, it is well acknowledged that there is a lack of common evaluation methodologies, making the fair comparison of such systems a difficult task. Many attempts to standardize this process have used a quality model based on the ISO/IEC 9126 standards. The authors have also used these standards for the definition of a weighted quality model for the evaluation of a medical speech translator, showing the relative importance of the system's features depending on the potential user (patient or doctor, developer). More recently, ISO/IEC 9126 has been replaced by a new series of standards, the 25000 or SQuaRE series, indicating that the model should be migrated to the new series in order to maintain compliance adherence to current standards. This chapter demonstrates how to migrate from ISO/IEC 9126 to ISO 25000 by using the authors' previous work as a use case.

Automatic Determination of Pauses in Speech for Classification of Stuttering Disorder

An algorithm to automatically identify segments of silence or speech is presented. The algorithm was developed to measure the silence periods in spontaneous and read speech. These silence periods are one of the parameters used to know the degree of severity of stuttered speech. For this purpose the three longer disfluent events (pauses or other disfluent events) and also the percentage of silence are useful. The algorithm is based on the evaluation of the energy and the zero crossing rate of the signal compared to the threshold values previously determined in silence. One experiment with eight subjects is described using the Stuttering Severity Instrument for Children and Adults – SSI and the percentage of silence in speech. It was concluded that the percentage of silence is good enough to separate stuttered from the normal speech but alone is not capable of measuring the degree of severity of the stuttered speech.

Early Detection of Electroencephalogram Temporal Events in Alzheimer's Disease

Alzheimer's Disease (AD) is considered one of the most debilitating illness in modern societies and the leading cause of dementia. This study is a new approach to detect early AD Electroencephalogram (EEG) temporal events in order to improve early AD diagnosis. For that, Self-Organized Maps (SOM) were used, and it was found that there are sequences of EEG energy variation, characteristic of AD, that appear with high incidence in Mild Cognitive Impairment (MCI) patients. Those AD events are related to the first cognitive changes in patients that interfered with the normal EEG signal pattern. Moreover, there are significant differences concerning the propagation time of those events between the study groups(p=0.0082<0.05), meaning that, as AD progresses the brain dynamics are progressively affected, what is expected because AD causes brain atrophy.

Robotics in Surgical Techniques

Healthcare robotic applications are a growing trend due to rapid demographic changes that affect healthcare systems, professionals and quality of life indicators, for the elderly, the injured and the disabled. Current technological advances in robotic systems offer an exciting field for medical research, as the interdisciplinary approach of robotics in healthcare and specifically in surgery is continuously gaining ground. This chapter features a review of current applications, from external large scale robotic devices to nanoscale swarm robots programmed to interact on a cellular level.

Population Health Management and Cervical Cancer Screening Programs

Population Health Management (PHM) aims to provide better health outcomes for preventing diseases, closing care gaps and providing more personalized care. Since the inception of the Pap test, cervical cancer (CxCa) decreased in countries applying screening programs, involving both prevention and treatment. In this chapter, we map a PHM roadmap to CxCa screening programs, examine the effect of supporting information technology systems, and propose a suitable architecture for implementation. Notwithstanding screening programs have a tight relation to PHM; the mapping reveals numerous interventions involving additional data sources, and timeless reconfiguration. Today, the use of open source platforms allows the implementation of IT systems supporting CxCa screening, when employed in a multitier web-based architecture.

Informed Consent in Healthcare

Informed consents, either for treatment or sensitive information use/disclosure, that protect the privacy of patient/participant information subject to law that in certain circumstances may override patient wishes, are mandatory practice in healthcare. Similarly, for protecting and respecting research participants, informed consents are also prerequisite for human subjects research. Although the healthcare industry has widely adopted Electronic Medical Record (EMR) systems, consents are still obtained and stored primarily on paper or scanned electronic documents. Integrating a consent management system for different purposes into an EMR system involves various implementation challenges. A case study, informed consent for genetic services, is used to show how genetic informed consents placed new challenges on the traditional ethical standards of informed consent, and how appropriate consents can be electronically obtained and automatically enforced using a system that combines medical workflows and hierarchically, ontologically motivated rule enforcement. Finally, this chapter describes an implementation that uses the open-source software-based addition of these components to an open-source EMR system, so that existing systems do not need to be scrapped or otherwise rendered obsolete.

Surface Segmentation

Segmentation is a powerful procedure that could be used to extract relevant information of the images based on advanced techniques (like active contours, region growing, Markov random fields, and medical atlas analysis). For the procedures, the main task is the contour, or volume or surface representation of specific parts of the organs that could be used for the benefit of the patients under doctor evaluation. So, in real cases, the proposed process must be quick, accurate and easy to implement. The segmentation of the organ is another problem that must be considered. More complicated, more demanding the segmentation process. In our case (bronchus segmentation) a quick, effective and easy to implement procedure is proposed based on the combination of boundary tracking and region growing techniques.