Impact of cognitive decline on medical outcomes and nursing workload: A retrospective cohort study.

Few reports have quantitatively investigated the effect of dementia on medical outcomes and nurse workload. Therefore, we aimed to investigate whether cognitive decline can be identified from a nurse assessment and determined its effect on medical outcomes and nurse workload. This retrospective cohort study used electronic medical record data to investigate whether patients judged by nurses to have cognitive decline were as affected as those with a dementia diagnosis. Further, a model formula was created and validated to predict the probability of needing physical restraint, the nursing care workload, and the record volume. The subjects were 43,330 patients aged ≥40 years who were hospitalized at the study hospital during the four-year study period. Data were analyzed using the chi-square test, Welch's t-test, logistic regression analysis and linear regression analysis. The implementation of physical restraint and a discharge support conference was significantly higher in patients deemed by nurses to have cognitive decline. Nurse-deemed patients with cognitive decline were affected by the outcome and workload as much as those with dementia. The false discovery rate for the Probability model formula of physical restraint and discharge support conference were 0.198 and 0.266. The correlation coefficient of the model formula for predicting nursing care and recording volume was 0.5-0.6. Combining nurse assessment and patient attribute information in a model was useful for predicting nurse workload. These findings may serve as a foundational component for the Clinical Decision Support System, aiding in the evaluation of intervention methods from the early stages of hospital admission and improving care delivery.

Verification of the relationship between the sequential organ failure assessment score and the length of intensive care unit and hospital stay in terms of medical resources input.

This study aimed to clarify the relationship between the sequential organ failure assessment (SOFA) score and the length of intensive care unit (ICU) and hospital stays and verify whether the SOFA score can indicate the optimal length of ICU stay. Medical resource input was evaluated as the medical treatment score, converted by volume, within 2 days after ICU admission. After classifying emergency patients into surgical and nonsurgical categories, the relationship between medical resources, SOFA score, and ICU and hospital stay lengths was analyzed. Medical resource input was high when the SOFA score was high after ICU admission. A positive correlation was confirmed between the SOFA score and length of ICU stay in surgical and nonsurgical patients. Nonsurgical patients are more likely to be discharged within the diagnosis procedure combination hospital stages I and II if medical resources are high in the initial stages of ICU admission. The SOFA score affects medical resource input and the length of ICU stay. The early input of medical resources after ICU admission reduces the length of hospital stay in the diagnosis procedure combination, suggesting that the SOFA score is a valuable indicator of the optimal length of ICU stay.

Supporting the Early Detection of Disease Onset and Change Using Document Vector Analysis of Nursing Observation Records.

Nursing records are an account of patient condition and treatment during their hospital stay. In this study, we developed a system that can automatically analyze nursing records to predict the occurrence of diseases and incidents (e.g., falls). Text vectorization was performed for nursing records and compared with past case data on aspiration pneumonia, to develop an onset prediction system. Nursing records for a patient group that developed aspiration pneumonia during hospitalization and a non-onset control group were randomly assigned to definitive diagnostic (for learning), preliminary survey, and test datasets. Data from the preliminary survey were used to adjust parameters and influencing factors. The final verification used the test data and revealed the highest compatibility to predict the onset of aspiration pneumonia (sensitivity = 90.9%, specificity = 60.3%) with the parameter values of size = 80 (number of dimensions of the sentence vector), window = 13 (number of words before and after the learned word), and min_count = 2 (threshold of wordcount for word to be included). This method represents the foundation for a discovery/warning system using machine-based automated monitoring to predict the onset of diseases and prevent adverse incidents such as falls.

Secondary use of hospital information system data for safe bedside radiography in terms of patient factors.

OBJECTIVE:: The purpose of this study was to use patient data gathered by a hospital information system (HIS) to improve the safe performance of bedside radiography. METHOD:: Hierarchical cluster analysis was used to investigate the factors of hospitalised patients who had undergone radiography in the X-ray room or at the bedside. Logistic regression analysis was then performed to quantify patient factors and calculate the probability of undergoing general radiography or bedside radiography. RESULTS:: Patients were grouped into six clusters by hierarchical cluster analysis on the basis of their factors. We found a remarkable difference between clusters for the ratio of bedside radiography. Results indicated that "types of transportation" and "level of mobility" related to the ratio of bedside radiography. Logistic regression analysis of the associations between the probability of undergoing bedside radiography and patient factors indicated that type of transportation and level of mobility were highly correlated with bedside radiography or general radiography. CONCLUSION:: Our results suggested that the secondary use of HIS data for the quantitative evaluation of patient factors and implementation of those quantitative values in medical records may be useful for the safe performance of bedside radiography as well as providing a method of decision support for doctors to order bedside radiography.

Development of an electronic instruction system to promote multidisciplinary teams.

While the provision of medical care incorporating safety measures, etc. that can earn the trust of the people, patients in particular, is required, the content of instruction is diverse, complex and rapidly increasing in volume along with the sophistication and specialization of medical care. However, until now, the development of electronic instruction systems has lagged behind in the development of HIS. All instructions must be linked to orders and the input of the implementation of instructions in the electronic instruction system incorporated into medical accounting. The system must aim at integrating physician and nursing records and be of a specification that can ensure reliability and efficiency. We report on the efforts at Kagoshima University Hospital to systematize instruction in order to promote multidisciplinary teams.

Development of the electronic patient record system based on problem oriented system.

In Japan, POS (problem oriented system) is recommended in the clinical guideline. Therefore, the records are mainly made by SOAP. We developed a system mainly with a function which enabled our staff members of all kinds of professions including doctors to enter the patients' clinical information as an identical record, regardless if they were outpatients or inpatients, and to observe the contents chronologically. This electric patient record system is called "e-kanja recording system". On this system, all staff members in the medical team can now share the same information. Moreover, the contents can be reviewed by colleagues; the quality of records has been improved as it is evaluated by the others.