User Evaluation Indicates High Quality of the Surveillance Outbreak Response Management and Analysis System (SORMAS) After Field Deployment in Nigeria in 2015 and 2018

Tom-Aba, Daniel; Toikkanen, Salla E.; Glöckner, Stephan; Adeoye, Olawunmi; Mall, Sabine; Fähnrich, Cindy; Denecke, Kerstin; Benzler, Justus; Kirchner, Göran; Schwarz, Norbert; Poggensee, Gabriele; Silenou, Bernard C.; Ameh, Celestine A.; Nguku, Patrick; Olubunmi, Ojo; Ihekweazu, Chikwe; Krause, Gérard (2018). User Evaluation Indicates High Quality of the Surveillance Outbreak Response Management and Analysis System (SORMAS) After Field Deployment in Nigeria in 2015 and 2018 Studies in Health Technology and Informatics, 253, pp. 233-237. IOS Press 10.3233/978-1-61499-896-9-233

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During the West African Ebola virus disease outbreak in 2014-15, health agencies had severe challenges with case notification and contact tracing. To overcome these, we developed the Surveillance, Outbreak Response Management and Analysis System (SORMAS). The objective of this study was to measure perceived quality of SORMAS and its change over time. We ran a 4-week-pilot and 8-week-implementation of SORMAS among hospital informants in Kano state, Nigeria in 2015 and 2018 respectively. We carried out surveys after the pilot and implementation asking about usefulness and acceptability. We calculated the proportions of users per answer together with their 95% confidence intervals (CI) and compared whether the 2015 response distributions differed from those from 2018. Total of 31 and 74 hospital informants participated in the survey in 2015 and 2018, respectively. In 2018, 94% (CI: 89-100%) of users indicated that the tool was useful, 92% (CI: 86-98%) would recommend SORMAS to colleagues and 18% (CI: 10-28%) had login difficulties. In 2015, the proportions were 74% (CI: 59-90%), 90% (CI: 80-100%), and 87% (CI: 75-99%) respectively. Results indicate high usefulness and acceptability of SORMAS. We recommend mHealth tools to be evaluated to allow repeated measurements and comparisons between different versions and users.

Item Type:

Journal Article (Original Article)

Division/Institute:

School of Engineering and Computer Science > Institute for Patient-centered Digital Health
School of Engineering and Computer Science

Name:

Tom-Aba, Daniel;
Toikkanen, Salla E.;
Glöckner, Stephan;
Adeoye, Olawunmi;
Mall, Sabine;
Fähnrich, Cindy;
Denecke, Kerstin0000-0001-6691-396X;
Benzler, Justus;
Kirchner, Göran;
Schwarz, Norbert;
Poggensee, Gabriele;
Silenou, Bernard C.;
Ameh, Celestine A.;
Nguku, Patrick;
Olubunmi, Ojo;
Ihekweazu, Chikwe and
Krause, Gérard

ISSN:

1879-8365

Publisher:

IOS Press

Language:

English

Submitter:

Kerstin Denecke

Date Deposited:

12 Feb 2020 09:01

Last Modified:

15 Jan 2024 15:15

Publisher DOI:

10.3233/978-1-61499-896-9-233

PubMed ID:

30147081

Uncontrolled Keywords:

Africa disease surveillance eHealth infectious disease mHealth medical and health informatics open source outbreak response systematic evaluation

ARBOR DOI:

10.24451/arbor.9187

URI:

https://arbor.bfh.ch/id/eprint/9187

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