Enhancing the effectiveness of data management to improve data quality for evidence-based decision-making : a case study of Pelonomi Tertiary Hospital

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dc.contributor.advisorAjam, Taniaen_ZA
dc.contributor.authorMalahleha, Mafumane Aliceen_ZA
dc.contributor.otherStellenbosch University. Faculty of Economic and Management Sciences. School of Public Leadership.en_ZA
dc.date.accessioned2024-03-04T19:12:36Z
dc.date.accessioned2024-04-26T18:57:47Z
dc.date.available2024-03-04T19:12:36Z
dc.date.available2024-04-26T18:57:47Z
dc.date.issued2024-03
dc.descriptionThesis (MPA)--Stellenbosch University, 2024. en_ZA
dc.description.abstractENGLISH SUMMARY: We are currently living in an era where effective data management has become a critical process for improving data quality and informing rational management decision-making across organisations. New technologies show promising results globally for managing data. The healthcare sector produces heterogenous data daily and big data solutions are used internationally to manage voluminous data as traditional data management systems cannot keep up. In the healthcare sector, the need for effective decision-making is high and the consequences of ill-informed decisions could lead to loss of life; this compels the decision-makers to have real-time data, sound data management policies and other essential resources to manage and improve the quality of data produced and used to inform such decisions. Good data management practices can assist in minimising potential errors by establishing efficient processes and policies for usage and building confidence in the data being used to make rational decisions about patient care and health outcomes across healthcare institutions. The study aims to enhance the effectiveness of data management practices at Pelonomi Tertiary Hospital to improve data quality for evidence-based decision-making. A qualitative case study approach is utilised. Self-administered questionnaires and semi-structured interviews have been deployed as data collection methods, purposeful sampling was done and an appropriate sample size was selected. The findings of the study revealed that gradual adoption of new technologies can assist in overcoming the system fragmentation and harmonise data management practices for improved data quality that can be used confidently for evidence-based decision-making. Management support is key to achieving data of high quality and there is a need to comply with data management human resource requirements as stipulated in the District Health Information Management Systems policy. The placement of data management personnel on the organogram needs urgent management attention if the hospital is to maintain high data quality and enhance data management practices. This will also assist in role clarification in data management activities and improve levels of accountability and ownership of data produced.en_ZA
dc.description.abstractAFRIKAANSE OPSOMMING: Ons leef tans in 'n era waar effektiewe databestuur 'n kritieke proses geword het om datakwaliteit en inligting oor rasionele bestuursbesluitneming oor organisasies heen te verbeter. Nuwe tegnologiee lewer wereldwyd belowende resultate vir die bestuur van data. Die gesondheidsorgsektor produseer daagliks heterogene data en grootdata-oplossings word internasionaal gebruik om lywige data te bestuur aangesien tradisionele databestuurstelsels nie kan byhou nie. Daar is 'n groot behoefte aan doeltreffende besluitneming in die gesondheidsorgsektor en die gevolge van oningeligte besluite kan tot lewensverlies lei; dit dwing die besluitnemers om intydse data, gesonde databestuursbeleide en ander noodsaaklike hulpbronne te he om die kwaliteit van data wat geproduseer en gebruik word om sulke besluite te beinvloed, te bestuur en te verbeter. Goeie databestuurspraktyke kan help om potensiele foute te minimaliseer deur doeltreffende prosesse en beleide vir gebruik daar te stel en vertroue te bou in die data wat gebruik word om rasionele besluite oor pasientsorg en gesondheidsuitkomste oor gesondheidsorginstellings heen te neem. Die studie het ten doel om die doeltreffendheid van databestuurspraktyke by Pelonomi Tersiere Hospitaal (PTH) te verbeter om datakwaliteit vir bewysgebaseerde besluitneming te verbeter. 'n Kwalitatiewe gevallestudiebenadering word gebruik. Self-geadministreerde vraelyste en semi-gestruktureerde onderhoude is ontplooi as data-insamelingsmetodes en doelgerigte steekproefneming is gedoen en ‘n toepaslike steekproefgrootte is gekies. Die bevindinge van die studie het aan die lig gebring dat geleidelike aanvaarding van nuwe tegnologiee kan help om die stelselfragmentasie te oorkom en databestuurspraktyke te harmoniseer vir verbeterde datakwaliteit wat met selfvertroue gebruik kan word vir bewysgebaseerde besluitneming. Bestuursondersteuning is die sleutel tot die verkryging van data van hoe gehalte en daar is 'n behoefte om te voldoen aan databestuur menslike hulpbronvereistes soos uiteengesit in die Distriksgesondheid Bestuursinligtingstelsel beleid. Die plasing van databestuurspersoneel op die organogram verg dringende bestuursaandag as die hospitaal hoe datakwaliteit sou handhaaf en databestuurspraktyke sou verbeter. Dit sal ook help met rolverduidleliking in databestuuraktiwiteite, en vlakke van aanspreeklikheid en eienaarskap van data wat geproduseer word, verbeter.af_ZA
dc.description.versionMasters
dc.format.extentxiii, 148 pages : illustrations, includes annexures
dc.identifier.urihttps://scholar.sun.ac.za/handle/10019.1/130475
dc.language.isoen_ZAen_ZA
dc.publisherStellenbosch : Stellenbosch University
dc.rights.holderStellenbosch University
dc.subject.lcshHealth services administration -- Data processingen_ZA
dc.subject.lcshInformation storage and retrieval systems -- Health services administrationen_ZA
dc.subject.lcshPublic health administrationen_ZA
dc.subject.lcshClinical medicine -- Decision makingen_ZA
dc.subject.nameUCTD
dc.titleEnhancing the effectiveness of data management to improve data quality for evidence-based decision-making : a case study of Pelonomi Tertiary Hospitalen_ZA
dc.typeThesisen_ZA
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