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Understanding quality improvement in care: The case of public care procurement and process mining

Sara Dahlin (Institutionen för teknikens ekonomi och organisation, Service Management and Logistics)
Gothenburg : Chalmers University of Technology, 2017.
[Licentiatavhandling]

Healthcare is facing challenges of increased cost and complexity originating from factors such as new technology and diversified treatments, increased life expectancy, an ageing population, and multi-comorbidity, making the need for Quality Improvement (QI) in care highly relevant. This is, however, easier said than done, considering that healthcare is complex, dynamic, ad-hoc, and multidisciplinary. Additionally, despite efforts taken, improvement initiatives sometimes fail or could potentially be improved further.

QI in care has been defined as ´...the combined and unceasing efforts of everyone - healthcare professionals, patients and their families, researchers, payers, planners and educators - to make changes that will lead to better patient outcomes (health), better system performance (care) and better professional development (learning)...´. To understand care and find new ways of further improving care, inspiration is sometimes taken from other research fields and subjects. This thesis continues that journey by identifying an existing context and methodology that may support and drive QI efforts. The purpose of this thesis is to explore how QI in care can be understood by expanding QI application into a new context and through the support of a new methodology.

Although a significant amount of care is handled through public procurement, there is little understanding of this system's potential for QI. To explore how QI applications can be expanded into the context of public care procurement, one study in the thesis analyzes procurement documents and performs interviews with municipalities. Identified QI criteria were statistically analyzed for correlation to procurement-specific statistics. Although legal requirements sometimes work against QI, such as through advocating static requirements rather than the flexibility necessary to QI, this thesis identified potential ways to support and drive QI through public care procurement.

One way to achieve QI is through a focus on process and a use of planned to-be care pathways. However, since as-is care pathways, based on documented patient data, are often highly variable, they are seldom possible to recognize through mainstream pathway analysis, e.g. process mapping. Therefore, care variation may need to be better understood to attain the desired improvement. Process mining is a recently developed methodology in which knowledge is extracted from event logs based on individual patient data to produce process maps including all pathway variation. Despite this method's aim of discovering, monitoring, and improving processes and its application in healthcare settings, improvement efforts are lacking, and few papers address the combination of QI and process mining. This thesis explores how QI may be understood by expanding QI applications into the methodology of process mining both theoretically and empirically.

This thesis further elaborates upon the effects public care procurement and process mining have on the theoretical knowledge domains of QI and the practice of QI in care.

Nyckelord: elderly care, cancer care, Quality improvement, process mining, care pathways, public care procurement, methodology, context



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Denna post skapades 2017-07-03. Senast ändrad 2017-07-04.
CPL Pubid: 250364

 

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Institutioner (Chalmers)

Institutionen för teknikens ekonomi och organisation, Service Management and Logistics

Ämnesområden

Livsvetenskaper
Övrig annan teknik
Hälso- och sjukvårdsorganisation, hälsopolitik och hälsoekonomi

Chalmers infrastruktur

Examination

Datum: 2017-08-28
Tid: 13:15
Lokal: Room Korsvägen (2456), Vera Sandbergs allé 8
Opponent: Ann-Christine Andersson, Jönköping University

Ingår i serie

Licentiate thesis, report - Department of Technology of Management and Economics, Chalmers University of Technology L2017:092