Business intelligence: assimilation and outcome measures for the health sector

Date

2017-12-18

Authors

Loewen, Elizabeth (Liz)

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Abstract

Increased adoption of health information systems in clinical practice has set a foundation for use of this data for Business Intelligence (BI). BI is the use of specialized tools to collect, analyze, and present organizational data to operational leaders in user-friendly formats to support organizational objectives. This is a routine component of management practice in sectors such as finance and manufacturing but has not yet reached its full potential in the health sector where limited availability of BI systems and factors such as data quality, complexity, and access to data have been identified as barriers. Correspondingly, there are no established conceptual models for measuring successful adoption of BI in the health sector. This dissertation study proposes a Business Intelligence Benefits Model for Health derived from frameworks used in other sectors and establishes health sector measures for two foundational constructs, BI Assimilation and Health System Organizational Performance. Through an online Delphi consensus process involving 25 Canadian health leadership panelists from four provinces, the study establishes a total of 30 concept measures for these constructs. Only seven (23.3%) of the concepts identified by the panelists in the study are reflected in an established non-health sector framework, the Business Value of BI Model, validating the need for sector specific measures. The study also compares priorities between leadership groups: top management team versus operational managers; and, leaders with a nursing related portfolio versus those without. The comparisons demonstrate variations among these groups but consistency in requirements overall. Establishing these BI constructs for healthcare is a precursor to measuring BI success and informs priorities and approaches for BI implementation as well as further instrument development.

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Keywords

health care, business intelligence, nursing, performance outcomes, framework

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