Dr. Shogo Kato

Dr. Shogo Kato is a lecturer at School of Engineering, the University of Tokyo. His research interests are system analysis engineering in both healthcare and industrial fields, as represented by patient safety, trouble prevention, and so on. He was awarded the Nikkei QC Literature Prize in 2009.

He has made a presentation titled as “A Model for Discharge Coordination in a Hospital” at ASQ World Conference on Quality and Improvement 2006, Milwaukee, titled as “Model for Designing Rehabilitation Training Program” at ASQ World Conference on Quality and Improvement 2010, St. Louis, titled as “A Model for Designing a Long-term Care Program” at 54th EOQ Congress 2010, Izmir, titled as “Methodology for the Establishment of "Standards" as Sociotechnology” at 55th EOQ Congress 2011, Budapest, and titled as “Collaboration with Patients for Prevention of Medical Accidents Caused by Patient Action” at 58th EOQ Congress 2014, Gothenburg.

Abstract

Development of the Assessment System for Preventing Patient Falls based on Multivariate Analysis

Recently, more and more attention is focused on quality and safety in healthcare. Medical accidents are classified into 2 types. One type is accidents caused by medical staff while providing services, such as medication errors, misidentification of patients, and so on, and another type is accidents caused by patient’s actions, such as those caused by falls, evulsion of tubes, continuous infusion needles, and so on.

To prevent the former type of accidents, process approaches, such as standardization of operation processes, error proofing and so on, are considered to be effective. However, it is still difficult to prevent the later type of accidents in these approaches, because such accidents would occur when patients took high-risk actions without following the instructions form medical staff.

Among the latter type of accidents, falls remain a significant problem, accounting for large number, and they often have significant consequences, such as fractures and so on. Assessment score sheets as tools for evaluating risk of patient falls are usually used in hospitals in order to prevent and reduce the number of patient falls. Although, satisfactory results has not been achieved yet. We argue that the primary reason is the impossibility in identification of dangerous situations using these sheets. Therefore, it is difficult to take appropriate countermeasures to prevent patient falls based on the output of these sheets.

In the previous study, we proposed the assessment system, which enable to determine concrete countermeasures for each patient, by including knowledgebase on the relationships between risk factor, dangerous situation, and countermeasures. The knowledgebase was developed based on 26 risk factors used in Iizuka Hospital, which is an acute stage hospital, located in Fukuoka Prefecture. However, the number of risk factors is too large to practicably use in the daily work of nurses in acute hospitals.

In this study, we aim to propose a practicable assessment system, which enable to determine concrete countermeasures by smaller number of risk factors, through multivariate analysis using big size case data accumulated in Iizuka Hospital between these 4 years. Current 26 risk factors and risk score for each risk factor are identified based on logistic regression analysis. We apply some regression analysis using logistic model, cox proportional hazard model, and some models for recurrent events analysis such as AG model, PWP model, to find both the best statistical model for patient falls, important risk factors, and risk score for each risk factor. As the results, we finally found 12 risk factors and their risk scores, which has higher prediction capability than the current set of 26 risk factors, and also has enough information to determine appropriate countermeasures.

We believe that our new assessment system will contribute to reduce patient falls both by predicting patient falls precisely and by accounting the concrete countermeasures for each patient, with less work by nurses than current situation. In the future, we will implement the series of development process into other hospitals, and aim to establish the standard methodology to prevent patient falls to improve the quality in healthcare.

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