SaaS-platform for mobile health applications

Berndt, R.-D.; Takenga, M. C.; Kuehn, Sebastian; Preik, Petra; Sommer, Georg; Berndt, Sara

doi:10.1109/ssd.2012.6198120

Cited by 26 publications

(18 citation statements)

References 3 publications

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“…Some of the supported standards include HL7, CDA, WSDL and XML. This platform was also presented in [ 34 ].…”

Section: Methodsmentioning

confidence: 99%

Impact of Information Technology on the Therapy of Type-1 Diabetes: A Case Study of Children and Adolescents in Germany

Berndt¹,

Takenga²,

Preik³

et al. 2014

JPM

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Being able to manage and adjust insulin doses is a key part of managing type-1 diabetes. Children and adolescents with type-1 diabetes mellitus often have serious difficulties with this dosage adjustment. Therefore, this paper aims to investigate the impact of using novel mobile, web and communication technologies in assisting their therapy and treatment. A trial was conducted in the north-eastern part of Germany to evaluate the impact of the “Mobil Diab”, a mobile diabetes management system, on the clinical outcome. 68 subjects aged between 8 and 18 years, divided randomly into control and intervention groups, were included into the study. Metrics such as changes in the quality of metabolic control, changes in psychological parameters, usability and acceptance of the technology were used for evaluation purpose. Metabolic control was mainly assessed by the mean HbAlc. Analysis showed a good acceptance of the proposed system. An overall improvement in mean levels of HbA1c was observed, however further studies will be conducted to prove evidence of the weight and BMI improvements. Moreover, initial indications of positive impact on the improvement in psychological parameters were presumed based on the result of the conducted study. The system appeared to be an efficient and time saving tool in diabetes management.

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“…Some of the supported standards include HL7, CDA, WSDL and XML. This platform was also presented in [ 34 ].…”

Section: Methodsmentioning

confidence: 99%

Impact of Information Technology on the Therapy of Type-1 Diabetes: A Case Study of Children and Adolescents in Germany

Berndt¹,

Takenga²,

Preik³

et al. 2014

JPM

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show abstract

“…With this understanding, the term cloud based health system refers to all computing mechanisms such as infrastructure, software and hardware used by healthcare service providers to deliver healthcare services like Software as a Service (SaaS), Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) [ 13 ]. The factors mentioned above has been considered in the design of cloud based computing systems for the care of elderly and patients with anxiety disorders [ 14 ], patients with chronic diseases [ 15 ] and monitoring of patients with artificial hearts [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Assessing factors militating against the acceptance and successful implementation of a cloud based health center from the healthcare professionals’ perspective: a survey of hospitals in Benue state, northcentral Nigeria

Idoga

Toycan

Nadiri

et al. 2019

BMC Med Inform Decis Mak

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Background Cloud based health platforms (CBHP) have tremendous capacity to meet patient’s health needs. The benefits inherent in CBHP position it to be relevant for efficient healthcare delivery. Nonetheless, studies have shown that the adoption of new technologies is sometimes a challenge especially in developing nations. This study, therefore, aim to examine, identify and evaluate the factors affecting healthcare professionals’ intention to accept the cloud-based health center (CBHC) in developing countries. The research study focuses on hospitals in North-central of Nigeria. Methods Using questionnaire adopted from related studies, a cross-sectional study was carried out of 300 healthcare professionals selected from medical health institutions in Benue State Nigeria. The study adopted the Unified Theory of Acceptance and use of Technology Extended (UTAUT2). Data analysis was carried out using SPSS (V20.0) and LISREL (V9.30) generally employed in Structural Equation Modeling to examine components and path model. The Socio technical design method was used to develop the CBHC. Results Findings portrays performance expectancy, cloud based health knowledge, IT infrastructure and social influence to have significant effects on the intentions of healthcare professionals to accept and use the CBHC. These findings, agrees with prior related studies. Conclusions Our findings impacts the body of knowledge in that it identifies important areas the studies can be useful, especially, to managers and healthcare policy makers in the planning/implementation of health cloud. Research findings from the theoretical acceptance model identifies the factors and barriers towards sustainable cloud based health center solutions to meet the healthcare needs of people in remote communities.

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“…(i) infrastructure level [14,17,32,[36][37][38][39]: endpoint device (vital sign sensor, POC detector), data transmission (Bluetooth, Zegbee, Wi-Fi, 3G+, Internet), middleware (Gateway, data exchange, HL7, LOINC, etc. ), care system (call center, e-healthcare IS, HIS, etc.…”

Section: Application On E-healthcarementioning

confidence: 99%

Adaptive Failure Identification for Healthcare Risk Analysis and Its Application on E-Healthcare

Chu

Hung

2014

Journal of Applied Mathematics

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To satisfy the requirement for diverse risk preferences, we propose a generic risk priority number (GRPN) function that assigns a risk weight to each parameter such that they represent individual organization/department/process preferences for the parameters. This research applies GRPN function-based model to differentiate the types of risk, and primary data are generated through simulation. We also conduct sensitivity analysis on correlation and regression to compare it with the traditional RPN (TRPN). The proposed model outperforms the TRPN model and provides a practical, effective, and adaptive method for risk evaluation. In particular, the defined GRPN function offers a new method to prioritize failure modes in failure mode and effect analysis (FMEA). The different risk preferences considered in the healthcare example show that the modified FMEA model can take into account the various risk factors and prioritize failure modes more accurately. In addition, the model also can apply to a generic e-healthcare service environment with a hierarchical architecture.

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SaaS-platform for mobile health applications

Cited by 26 publications

References 3 publications

Impact of Information Technology on the Therapy of Type-1 Diabetes: A Case Study of Children and Adolescents in Germany

Impact of Information Technology on the Therapy of Type-1 Diabetes: A Case Study of Children and Adolescents in Germany

Assessing factors militating against the acceptance and successful implementation of a cloud based health center from the healthcare professionals’ perspective: a survey of hospitals in Benue state, northcentral Nigeria

Adaptive Failure Identification for Healthcare Risk Analysis and Its Application on E-Healthcare

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