Authors (including presenting author) :
Wong LMK(1), Chan GBK(1), Mak HKC(2), KU PS(1), Pang JYW(1), Cheung NT(1), Ng PSB(1), Yiu CWC(1), Hui HL(1), Poon CM(1), Leung CMY(1), Yeung WCS(1), Ho KHW(1)
Affiliation :
(1)Information Technology and Health Informatics Division, Hospital Authority Head Office (2) Project Management Office, Queen Elizabeth Hospital
Introduction :
Vital signs (VS) documentation is a crucial component of patient care which allows monitoring of patient’s health condition, tracking effectiveness of treatments as well as identifying potential complications. The accuracy and timeliness of VS documentation are significantly important to help healthcare providers (HCP) to make informed decisions about patient’s treatment plan. Currently, measured VS values in out-patient clinics (OPC) is manually recorded in a paper record by nurses or healthcare assistants (HCA) before medical consultation. During the consultation, doctors are then required to manually key in those data into the Clinical Management System (CMS). Both the above processes are time-consuming, error-prone and labour-intensive. Automation of VS documentation aims to tackle all these weaknesses. A pilot was carried out in a few OPCs by implementing a system using Internet of Things (IoT) VS devices to capture VS data and send the data back to HA automatically, the identified patient’s VS data was then integrated with various functions in CMS for clinical review by HCP.
Objectives :
1. To improve patient’s experience in OPC visits 2. To improve clinical documentation and data quality 3. To streamline clinical workflow and reduce manual data entry error
Methodology :
Self-service VS measurement stations were set up in selected OPC, which included the use of IoT devices, secured cloud technology, HA external Wi-Fi, mobile network SIM, barcode scanner and mobile tablet. Patients who visited OPC would register their attendance in the counter or via HA GO, a receipt with barcode containing their OP case number would then be given to patients or displayed in their HA GO. By scanning that barcode in the VS measurement station, patient’s identity would be verified followed by auto log in to the system where measurement could begin. Patients would be guided throughout the process by visual and audio instructions shown in the tablet. The VS measurement stations allowed capturing of 7 VS data including blood pressure, pulse, temperature, oxygen saturation, body weight, body height and calculated BMI. The captured data would then be sent to HA's database and the identified patient’s CMS through cloud technology. Patients could get a printout (similar size as supermarket receipt) of their consolidated VS values if needed. During the consultation, doctors could retrieve and document the VS values in just 1-2 clicks in CMS (integration with Consultation Note (CN) and Family Medicine Clinical note (FMCN)). The automation also made VS auto charting possible, the trend of patients’ VS would be displayed under the same OP case number in Vital Sign Chart Enquiry for record and comparison purposes.
Result & Outcome :
The pilot took place in 13 OPC including 9 SOPCs and 4 GOPCs across 5 clusters (HKEC, KCC, KEC, NTEC, NTWC) from April to December 2021. 9199 and 22809 VS data were successfully uploaded to CN and FMCN respectively. An evaluation had been conducted with 34 responses received from doctors, nurses and HCA of the pilot sites. Over 82% respondents reported as frequent users of the solutions. The feedback was positive in general, all pilot doctors welcome the smooth integration of VS data into CN and FMCN as it streamlined the workflow during consultation, the VS data were accurately displayed in CMS in no time. As many as 76.5% of the respondents agreed that the solution had improved the clinical workflow. The satisfaction was revealed as majority of them (88.2%) support further rollout of the solution in their hospitals. Users also suggested to integrate the solution into more clinical systems like Antenatal Record System and Metabolic Risk Follow Up form so to enjoy the benefits of the solution brought. The pilot successfully proved a significant improvement for patients, staff and data itself.
