A novel client service quality measuring model and an eHealthcare mitigating approach

Objectives Facing population ageing in Hong Kong, the demand of long-term elderly health care services is increasing. The challenge is to support a good quality service under the constraints faced by recent shortage of nursing and care services professionals without redesigning the work flow operated in the existing elderly health care industries. the existing elderly health care industries. 1) Developing a model for measuring Total Quality of Services,2) Using the Total Quality of Services measure to assess staffing conditions, i.e. shortage or surplus, and to measure the effectives of catering new services,3) Incorporating Information and Communication Technologies (ICT) to mitigate the staff shortage problems and to enhance efficiency of care,4) Utilizing the Total Quality of Services measure to quantify the improvement and providing an indicator for services assessment in future.Methods 1. Model Development We use Finite Capacity Queuing Model to develop a model for Total Quality of Services and use the balk rate of the model to set up an efficiency rate. We then assume multiple independent queues existed in the model and calculate the accumulated efficiency rates to give The Total Quality of Services measure.2. Model Simulation We conduct simulation on the model and check for its validity.3. ICT Solutions To keep up a desired quality service, we developed a “Residents Clinical Service Monitoring and Quality Control System” to test the appropriateness of the model. We designed the system to (i) make sure that clinical nursing care staff will run the nursing care protocol; (ii) cut substantially manual operation cost and possible human errors; (iii) give exception alerts for caring rules; (iv) promote efficient communication between staff and cost saving.4. Field Trials We carried out field trials for over 2 years and enhanced the system periodically.Results The Total QoS measure based on Finite Capacity Queuing Model is a reliable method and an effective measurement for Quality of services. The value is good for measuring the staffing level and offers a measurement for efficiency enhancement when incorporate new technologies like ICT. The implemented system has improved the Quality of Service by more than 14% and the extra released manpower resource will allow clinical care provider to offer further value added services without actually increasing head count. Conclusions We have developed a novel Quality of Service measurement for Clinical Care services based on multi-queue using finite capacity queue model M/M/c/K/n and the measurement is useful for estimating the shortage of staff resource in a caring institution. It is essential for future integration with the existing widely used assessment model to develop reliable measuring limits which allow an effective measurement of public fund used in health care industries.