Biography
Aneeta Minhas is an MS (Ophthalmology) from India, and worked as a private specialist in Mumbai. In 2003, I joined the prestigious Singapore General Hospital in the Health Information Management Systems department as a clinical coder and subsequently as an auditor. I also worked as a hospital internal auditor for preparation of JCI accreditation. In 2009, I joined the Medical board under Clinical Governance to undertake clinical quality and focused reviews as part of the Clinical Review Program team. My work entails reviewing flagged cases to identify adverse clinical events which are highlighted to the departments and solutions for prevention are implemented and monitored by our team. We also conduct RCA (Root Cause Analysis) of critical clinical incidents and follow-up on the recommendations of the QAC committees. I have been leading departmental projects in creating educational kits for the junior doctors teaching, and have been part of improvement projects for patient safety by our team and am also involved in paper writing. In my free time I like to read biographies and fiction. I love gardening and am in the process of creating an indoor succulent garden in my home. I enjoy acrylics, oils and Chinese brush painting.
Abstract
Background: The objective of this project was to redesign the selection criteria for readmission cases so as to improve pick up rates of adverse events* during the clinical review of inpatient medical records. No similar study has been done in this subject and a new methodology was tried and tested through this project. (*Adverse events (AE) are defined as an unintended injury or complication resulting in an increased length of hospital stay, temporary or permanent disability or death, which is caused by healthcare management rather than by the disease process Level 1 AE’s: these are unpreventable events only for the information of the clinical departments Level 2 AE’s: these are preventable or potentially preventable events that are reported to the Heads of clinical departments to address.) Methods: Selected screening criteria were applied to the readmission cases for review in a series of iterative quality improvement cycles. Further modification was done by using Hospital Inpatient Discharge Summary (HIDS) screening of all the selected cases to further eliminate unnecessary cases for review. A checklist to simplify the screening of cases for review was implemented and a staff satisfaction survey was conducted to see the efficacy of these modifications. Results: It was seen that modifications of the selection criteria increased the total adverse effect pick up rate. Hospital Inpatient Discharge Summary (HIDS) screening was also effective in reducing the number of unnecessary reviews. The checklist for screening cases proved effective as shown by the staff satisfaction survey conducted. It improved knowledge about the review process and selection of cases resulting in better time management. Conclusion: This project was unique as no similar studies have been recorded in literature regarding improving AE pickup rates and significantly decreasing unnecessary reviews. The project resulted in a significant increase in the total AE pickup rate of 94.23% as compared to the baseline of 80%. The level 1 and 2 AE rates also increased to 92.31% and 1.92% from the baseline rates of 75% and 0.2%. There was also noted to be a significant decrease of 80.98% in the man hours required to review the inpatient readmission case-notes. These findings support the fact that an effective screening process for readmission review is beneficial and worth implementing.
Biography
Toshiko Sawaguchi has been acting as originally pediatric forensic pathologist and moved to the epidemiology and public health field since 1st April 2015 as the research managing director.
Abstract
Aim: The aim is to estimate the emergency survival rate after traffic accidents if these rates could analyse the prefecture difference. Materials & methods: As for the totalized Japan, each prefecture in all Japan and 4 prefectures in the Hokuriku area in Japan, the number of traffic accidents, the number of the injured persons, the number of the injured dead persons were extracted from the total statistic book edited by the National Police Agency. The same kinds of data as for cities & towns in Niigata Prefecture were also extracted from the homepage of Niigata Prefecture in 2014,2013 & 2012. Using these data, the emergency survival rate after traffic accidents were calculated using the following formula; The emergency survival rate after traffic accidents = (the number of the injured & dead persons after traffic accidents―the number of the injured persons after traffic accidents)/ the number of the injured & dead persons after traffic accidents) Each rate by each 4 prefecture & by secondary medical area in Niigata was tested using non-parametric one-way ANOVA.SAS Analytic Pro was used for statistical analysis. Results: Significant differences were suggested as the following, between the secondary medical area only using the Cramer-Mises test only as for the number of traffic accidents, the number of dead persons after traffic accidents, the number of injured & dead persons after traffic accidents and the number of injured persons after traffic accidents(CM<1.5).