In this paper we present the development and evaluation of a parent decision support tool for a neonatal intensive care unit (NICU), known as PPADS or Physician and Parent Decision Support. The NICU interprofessional (IP) team uses advanced technology to care for the sickest infants in the hospital, some at the edge of viability. Many difficult care decisions are made daily for this vulnerable population. The PPADS tool, a computerized decision support system, aims to augment current NICU decision-making by helping parents make more informed decisions, improving physician-parent communication, increasing parent decision-making satisfaction, decreasing conflict, and increasing decision efficiency when faced with ethically challenging situations. The development and evaluation of the PPADS tool followed a five step methodology: assessing the clinical environment, establishing the design criteria, developing the system design, implementing the system, and performing usability testing. Usability testing of the PPADS tool with parents of neonates who have graduated (survived) from a tertiary level NICU demonstrates the usefulness and ease of use of the tool.
"In extending the tool to data acquired in real-time, we created new mortality models for the best estimations to be integrated into the PPADS tool, allowing physicians to quickly assess the current status of their patients. Fig. 2. Summary of patients for the clinician module   II. METHODOLOGY "
[Show abstract][Hide abstract] ABSTRACT: Our previous research led to the development of mortality risk estimations for infants in the neonatal intensive care unit (NICU) using quality archived databases. A decision support system was created with a clinician module containing relevant patient information and a variety of outcome estimations; the PPADS (Physician-Parent Decision Support) tool also contains a module for parents with the aim to help them make joint decisions with physicians on the direction of care for their infant. New work developed the ANN-Builder which uses an open-source artificial neural network library that would enable handling real-time data streaming and automate the process of providing risk estimations of mortality. Additionally, the patient data and risk estimations were successfully integrated into the PPADS tool. The mortality estimations surpass the clinical expectations. The next and final step will be to replace missing values in the data and add alarms for major changes in the risk estimations provided by the system.
"The CDS database stores the information entered by the physician and parents and the outcome predictions obtained from the data in the CDR, and on the usage log. The fourth step was implementation, with several rounds of feedback from clinical neonatal experts . "
[Show abstract][Hide abstract] ABSTRACT: Family-centered care is becoming the new standard for Neonatal Intensive Care Unit (NICU) patients. In support of this, we developed the Physician PArent Decision Support System (PPADS), which provides clinical updates and predictions of clinical outcomes for infants in the NICU to the neonatologists, and provides an aid to parents for making difficult decisions on the direction of care of their infant with the health care team. The tool may lead to earlier intervention, better allocation of resources, and reduction of the negative outcomes. The tool underwent a usability study with 8 parents whose infant survived the NICU stay and 5 neonatologists. Both parents and physicians thought the tool was easy to use, useful, and would help improve team communication. The next usability study will be with parents whose infant died while in the NICU, and then conduct a randomized prospective study with parents who have a sick infant admitted to the NICU.
Studies in health technology and informatics 08/2013; 192:23-7. DOI:10.3233/978-1-61499-289-9-23
[Show abstract][Hide abstract] ABSTRACT: The perceived usefulness of a Clinical Data Repository (CDR) prototype in a hospital setting was assessed by clinicians to determine whether they would find it helpful for their clinical and research work. The CDR automatically collects and stores clinical data in real time from patient monitoring devices, clinical information systems, laboratory systems, and the Health Records Department in a de-identified, easily extractable format for secondary uses. A secure online survey was distributed to physicians, research institute investigators, and research institute coordinators at the Children's Hospital of Eastern Ontario (CHEO) through email. According to the survey responses, participants felt the CDR was a useful tool, showed interest in it, and thought it would be important to have for future work. To illustrate how the CDR could be used in a clinical setting we have provided a sample clinical application; a tool for engaging physicians and parents in discussion about the clinical progress and prognosis of infants in the Neonatal Intensive Care Unit (NICU).
Medical Measurements and Applications Proceedings (MeMeA), 2013 IEEE International Symposium on; 01/2013
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