Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.694235
Title: Digitisation of healthcare : Barthel Index Assessment, Kardex Management and ECG analysis
Author: Martin, Sarah Elizabeth
ISNI:       0000 0004 5990 4194
Awarding Body: Ulster University
Current Institution: Ulster University
Date of Award: 2016
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Abstract:
We are now living in a world where the adoption of mobile computing technologies within healthcare is becoming more prevalent. Digitisation within hospitals and clinical settings have increased due to smaller, powerful and cost effective devices. The National Health Service has a target to be "completely paperless by 2018" and this Thesis presents work highlighting issues involving the lack of paperless across three key areas: (1) occupational therapists: assessment of occupants' general health and wellbeing, (2) nurses: documentation of patient's status, (3) physicians: interpretation of diagnostic tools. A study assessing the digitisation of a social care assessment chart has been undertaken. An online tool was created in an effort to reduce the amount of miscalculations when compared to the paper assessment chart. As a result, there were no miscalculations when using the online tool, compared to 40% when using the traditional paper-based assessment. In a subsequent study, an evaluation of paperless observations recordings in the form of a digital drug chart displayed on a tablet device are explored. The study established that although the digital drug chart took slightly longer for participants to use, it was the method of assessment that the user correctly noticed the patient's drug allergy to penicillin. The penultimate study involved the design, development and evaluation of an online ECG visualisation tool. Along with the traditional 12-Lead ECG, alternative formats (BSPM and ST-Vector Map) were included to allow comparisons between the most effective method of diagnosis. Work within this study showed that the BSPM was proven to be just as useful as the 12-Lead ECG in identifying myocardial infarctions. The final study aimed to evaluate whether an accurate ECG diagnosis could be made using a smartphone. A clinician was sent 15 ECGs as picture messages before providing a diagnosis for each image. Findings illustrate that all 15 ECGs were diagnosed correctly with the clinician stating that there was no key disadvantage in comparison to paper based ECGs. These studies represent each of the three key areas of healthcare discussed previously, and endeavour to bridge the gap in relation to providing sustainable digital healthcare.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.694235  DOI: Not available
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