Authors (including presenting author) :
Kwok PF 1, Lam WS 1, Wong SW Arale 1, Chung YY 1, Cheng Elaine 2, Sha KY Edmund 2
Affiliation :
1 Continence Nurse Clinic 2 Department of Geri-medical Department, United Christian Hospital, KEC, HA
Introduction :
What comes to your mind when utilizing Smart QR code in clinical area? Specialty nurses spend much of the time entering patient’s information onto CMS during nursing consultation, due to overwhelmed information with massive caseload, accurate and rapid documentation were crucial required. Despite typing skill and statement structure were different from varies nurses, therefore, to make the nursing documentation unified and minimize human error on data entry, a sequent of smart QR codes were designed and created in helping Continence Nurses to sustain a quality documentation and related care.
Objectives :
* To ease nurse’s workload on patient’s information entry by using QR codes as a digital tool * To save time and enhance administrative productivity * To standardize the needed patient’s data and assessment content which facilitate information collection for data analysis instantly * To bring up precise and efficient nursing documentation and eliminate human typographic error
Methodology :
An improvement program on utilizing the Smart QR code on daily practice was conducted in United Christian Hospital Continence Nurse Clinic in the middle of November 2022. The nursing assessment statements were turned into the QR codes for all ranks of continence nurses, the nurses were invited to participate an evaluation test using both manual typing versus using the Smart QR codes for data entry. Time and information accuracy were measured and evaluated.
Result & Outcome :
Eight Continence Nurses had joined the challenging test. The average time of manual typing in data entry was 103.3 seconds whereas the average time of scanning the QR codes was 8.1 sec which nearly 13 times faster in nursing documentation was demonstrated. Total 14 typo errors were found in manual typing which zero typo error was noted using QR codes with 100% accuracy of documentation was achieved.
