Patient referral is one of the strategies recommended for enhancing access to healthcare as stipulated by the Sustainable Development Goals Target 3 of the United Nations. However, the success of patient referral is directly dependent upon knowledge of the availability of requisite resources in the referral facility. Whereas several models based on heuristic search algorithms have been developed for healthcare system resource allocation, none seem to have been targeted at paediatric patients. This paper presents an intelligent distributed system resource allocation model based on Honey Bee Foraging theory for improving healthcare system provision to paediatric patients. The model was proved to be effective in enhancing healthcare service delivery due to informed decision making before a referral process was completed. More models should be designed which are capable of integrating patients and specialist data across county boundaries to facilitate wider referral options.
Objectives: Many factors affect adoption of health information systems, user involvement and satisfaction are some of the main factors of user adoption of health information systems. Despite the benefits due to social, cultural, organizational and technological factors some of the benefits become complex and difficult to achieve in practice. Both users and development team lack time due to busy schedules, sometimes disagreements between the users and the project team to reach concurrence, user at time might lack the necessary skills and knowledge to effectively participate in the design process. This study will investigate the user involvements and satisfaction levels of health information systems during the design and development phase. Methods: Cross sectional survey was utilized. Several existing tools were modified and used for the study namely Patient Satisfaction Questionnaire, Usefulness, Satisfaction, and Ease of use (USE) Questionnaire and Purdue Usability Testing Questionnaire. Structured equation models (SEM) analysis was used in the analysis. Ordinal regression statistics was used. Results: User involvement and satisfaction measure as the dependent variable and the user participation during the design and development of the health information systems as the independent variables. For every one unit increase in independent variable there is a predicted increase (of a certain amount) in the log odds falling at a higher level of the dependent variable. Generally showing that as scores increase on the independent variables, there is an increase probability falling at a higher level on the dependent variable.Conclusions: User involvement and participation has positive impact on the satisfaction levels of users during the design and development of the health information system.
The current health information systems have many challenges such as lack of standard user interfaces, data security and privacy issues, inability to uniquely identify patients across multiple hospital information systems, probable misuse of patient data, high technological costs, resistance to technology deployments in hospital management, lack of data gathering, processing and analysis standardization. All these challenges, among others hamper either the acceptance of the health information systems, operational efficiency or expose patient information to cyber attacks. In this paper, an enhanced information systems success model for patient information assurance is developed using an amalgamation of Technology Acceptance Model (TAM) and Information Systems Success Model (ISS). This involved the usage of Linear Structured Relationship (LISREL) software to model a combination of ISS and Intention to Use (ITU), TAM and ITU, ISS and user satisfaction (US), and finally TAM and US. The sample size of 110 respondents was obtained based on the total population of 221 using the Conhrans formula. Thereafter, simple random sampling was employed to select members within each category of employees to take part in the study. The questionnaire as a research tool was checked for reliability via Cronbach’s Alpha. The results obtained showed that for ISS and ITU modeling, only perceived ease of use, system features, response time, flexibility, timeliness, accuracy, responsiveness and user training positively influenced the intention to use. However, for the TAM and ITU modeling, only TAM’s measures such as timely information, efficiency, increased transparency, and proper patient identification had a positive effect on intension to use. The ISS and US modeling revealed that perceived ease of use had the greatest impact on user satisfaction while response time had the least effect on user satisfaction. On its part, the TAM and US modeling showed that timely information, effectiveness, consistency, enhanced communication, and proper patients identification had a positive influence on user satisfaction.
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