Understanding Patient Safety Reports via Multi-label Text Classification and Semantic Representation

Medical errors are the results of problems in health care delivery. One of the key steps to eliminate errors and improve patient safety is through patient safety event reporting. A patient safety report may record a number of critical factors that are involved in the health care when incidents, near misses, and unsafe conditions occur. Therefore, clinicians and risk management can generate actionable knowledge by harnessing useful information from reports. To date, efforts have been made to establish a nationwide reporting and error analysis mechanism. The increasing volume of reports has been driving improvement in quantity measures of patient safety. For example, statistical distributions of errors across types of error and health care settings have been well documented. Nevertheless, a shift to quality measure is highly demanded. In a health care system, errors are likely to occur if one or more components (e.g., procedures, equipment, etc.) that are intrinsically associated go wrong. However, our understanding of what and how these components are connected is limited for at least two reasons. Firstly, the patient safety reports present difficulties in aggregate analysis since they are large in volume and complicated in semantic representation. Secondly, an efficient and clinically valuable mechanism to identify and categorize these components is absent. I strive to make my contribution by investigating the multi-labeled nature of patient safety reports. To facilitate clinical implementation, I propose that machine learning and semantic information of reports, e.g., semantic similarity between terms, can be used to jointly perform automated multi-label classification. My work is divided into three specific aims. In the first aim, I developed a patient safety ontology to enhance semantic representation of patient safety reports. The ontology supports a number of applications including automated text classification. In the second aim, I evaluated multilabel text classification algorithms on patient safety reports. The results demonstrated a list of productive algorithms with balanced predictive power and efficiency. In the third aim, to improve the performance of text classification, I developed a framework for incorporating semantic similarity and kernel-based multi-label text classification. Semantic similarity values produced by different semantic representation models are evaluated in the classification tasks. Both ontology-based and distributional semantic similarity exerted positive influence on classification performance but the latter one shown significant efficiency in terms of the measure of semantic similarity. Our work provides insights into the nature of patient safety reports, that is a report can be labeled by multiple components (e.g., different procedures, settings, error types, and contributing factors) it contains. Multi-labeled reports hold promise to disclose system vulnerabilities since they provide the insight of the intrinsically correlated components of health care systems. I demonstrated the effectiveness and efficiency of the use of automated multi-label text classification embedded with semantic similarity information on patient safety reports. The proposed solution holds potential to incorporate with existing reporting systems, significantly reducing the workload of aggregate report analysis

Annotated Bibliography: Understanding Ambulatory Care Practices in the Context of Patient Safety and Quality Improvement.

The ambulatory care setting is an increasingly important component of the patient safety conversation. Inpatient safety is the primary focus of the vast majority of safety research and interventions, but the ambulatory setting is actually where most medical care is administered. Recent attention has shifted toward examining ambulatory care in order to implement better health care quality and safety practices. This annotated bibliography was created to analyze and augment the current literature on ambulatory care practices with regard to patient safety and quality improvement. By providing a thorough examination of current practices, potential improvement strategies in ambulatory care health care settings can be suggested. A better understanding of the myriad factors that influence delivery of patient care will catalyze future health care system development and implementation in the ambulatory setting

Keeping the Commitment: A Progress Report on Four Early Leaders in Patient Safety Improvement

Examines four healthcare systems' expansion of patient safety interventions over five years through the development of practical training methods, effective tools for minimizing errors, an emphasis on goal setting and accountability, and other approaches

Committed to Safety: Ten Case Studies on Reducing Harm to Patients

Presents case studies of healthcare organizations, clinical teams, and learning collaborations to illustrate successful innovations for improving patient safety nationwide. Includes actions taken, results achieved, lessons learned, and recommendations

Patient safety in Europe: medication errors and hospital-acquired infections

The Report was commissioned by the European Federation of Nurses Associations (EFN) in November 2007 in order to support its policy statements on Patient Safety (June 2004). In that statement the EFN declares its belief that European Union health services should operate within a culture of safety that is based on working towards an open culture and the immediate reporting of mistakes; exchanging best practice and research; and lobbying for the systematic collection of information and dissemination of research findings. This Report adressess specifically the culture of highly reliable organisations using the work of James Reason (2000). Medication errors and hospital-acquired infections are examined in line with the Reprt´s parameters and a range of European studies are used as evidence. An extensive reference list is provided that allows EFN to explore work in greater detail as required

Advancing Patient Safety in the U.S. Department of Veterans Affairs

As part of a systemwide transformation, the VA formed its National Center for Patient Safety to foster an organizational culture of safety within its nationwide network of hospitals and outpatient clinics. A recent medical team training program designed to improve communication among operating room staff was associated with a reduction in surgical mortality and improvements in quality of care, on-time surgery starts, and staff morale. The program is now being expanded to other clinical units, along with a patient engagement program that prevents errors by facilitating communication relating to patients' daily care plans. A recognition program stimulated facilities to conduct timelier and higher-quality root-cause analyses of reported safety events to identify stronger actions for preventing their recurrence. Other initiatives have reduced rates of health care -- associated infections, patient mortality, and post-operative complications. Success factors include leadership accountability for performance and organizational support for testing, expanding, and adopting improvements