Analysis of Business Intelligence Applications in Healthcare Organizations

In today’s healthcare (HC) market there are lots of pressures on HC organizations (Os). Besides, many challenges including; demographic changes and the need to manage vastly increasing data volumes in HC, have motivated these organizations to adopt business intelligence (BI) solutions. Through a systematic review of the literature, this study establishes the patterns of BI adoption in the HC domain by examining the nature of BI solutions in use, expected outcomes from BI use, specific types of BI capabilities deployed, and aspects of HCOs directly impacted. Findings from our study provide a foundation for future research agenda on BI in Healthcare. We conclude by highlighting the shortcomings of current BI practice in the HC domain in the context of the emerging value-based (VB) HC delivery model and the need for research in this direction

Investigating Analytics Dashboards’ Support for the Value-based Healthcare Delivery Model

Improving the value of care is one of the essential aspects of Value-Based Healthcare (VBHC) model today. VBHC is a new HC delivery model which is centered on patient health outcomes and improvements. There is anecdotal evidence that the use of decision aid tools like dashboards can play a significant role in the successful implementation of VBHC models. However, there has been little or no systematic studies and reviews to establish the extent to which analytics dashboards are used to support patient care in a VBHC delivery context. This paper bridges this knowledge gap through a systematic review of the existing literature on dashboards in the HC domain. Our study reveals dashboard capabilities as an enabling tool for value improvements and provides insight into the design of dashboards. This study concludes by highlighting a few gaps, question, and need for research in the future

Towards a theoretical model of dashboard acceptance and use in healthcare domain

The objective of this paper is to investigate existing factors related to the decision to adopt and use of dashboards in the healthcare domain using a systematic literature review approach. The study is part of a larger initiative on how analytics dashboards can support decisions in value-based prostate cancer treatment and care. Although many studies have been undertaken to evaluate the implementation of health information technologies in the healthcare sector, as far as we know, none of these studies provides a framework for dashboards use in the healthcare context. We believe that the resulting model from our study provides the necessary first step in developing empirical evidence for the acceptance and use of the dashboards in the healthcare domain

A term extraction approach to survey analysis in health care

The voice of the customer has for a long time been a key focus of businesses in all domains. It has received a lot of attention from the research community in Natural Language Processing (NLP) resulting in many approaches to analysing customers feedback ((aspect-based) sentiment analysis, topic modeling, etc.). In the health domain, public and private bodies are increasingly prioritising patient engagement for assessing the quality of the service given at each stage of the care. Patient and customer satisfaction analysis relate in many ways. In the domain of health particularly, a more precise and insightful analysis is needed to help practitioners locate potential issues and plan actions accordingly. We introduce here an approach to patient experience with the analysis of free text questions from the 2017 Irish National Inpatient Survey campaign using term extraction as a means to highlight important and insightful subject matters raised by patients. We evaluate the results by mapping them to a manually constructed framework following the Activity, Resource, Context (ARC) methodology (Ordenes et al., 2014) and specific to the health care environment, and compare our results against manual annotations done on the full 2017 dataset based on those categories

Investigating Analytics Dashboards' Support for the Value-based Healthcare Delivery Model

Improving the value of care is one of the essential aspects of Value-Based Healthcare (VBHC) model today. VBHC is a new HC delivery model which is centered on patient health outcomes and improvements. There is anecdotal evidence that the use of decision aid tools like dashboards can play a significant role in the successful implementation of VBHC models. However, there has been little or no systematic studies and reviews to establish the extent to which analytics dashboards are used to support patient care in a VBHC delivery context. This paper bridges this knowledge gap through a systematic review of the existing literature on dashboards in the HC domain. Our study reveals dashboard capabilities as an enabling tool for value improvements and provides insight into the design of dashboards. This study concludes by highlighting a few gaps, question, and need for research in the future

A term extraction approach to survey analysis in health care

The voice of the customer has for a long time been a key focus of businesses in all domains. It has received a lot of attention from the research community in Natural Language Processing (NLP) resulting in many approaches to analyzing customers feedback ((aspect-based) sentiment analysis, topic modeling, etc.). In the health domain, public and private bodies are increasingly prioritizing patient engagement for assessing the quality of the service given at each stage of the care. Patient and customer satisfaction analysis relate in many ways. In the domain of health particularly, a more precise and insightful analysis is needed to help practitioners locate potential issues and plan actions accordingly. We introduce here an approach to patient experience with the analysis of free text questions from the 2017 Irish National Inpatient Survey campaign using term extraction as a means to highlight important and insightful subject matters raised by patients. We evaluate the results by mapping them to a manually constructed framework following the Activity, Resource, Context (ARC) methodology (Ordenes, 2014) and specific to the health care environment, and compare our results against manual annotations done on the full 2017 dataset based on those categories.This work presented in this paper was partially supported by the Patient Centred Service Improvement (PaCSI Project) and by Science Foundation Ireland grant 12/RC/2289 2 (Insight)

A term extraction approach to survey analysis in health care

The voice of the customer has for a long time been a key focus of businesses in all domains. It has received a lot of attention from the research community in Natural Language Processing (NLP) resulting in many approaches to analysing customers feedback ((aspect-based) sentiment analysis, topic modeling, etc.). In the health domain, public and private bodies are increasingly prioritising patient engagement for assessing the quality of the service given at each stage of the care. Patient and customer satisfaction analysis relate in many ways. In the domain of health particularly, a more precise and insightful analysis is needed to help practitioners locate potential issues and plan actions accordingly. We introduce here an approach to patient experience with the analysis of free text questions from the 2017 Irish National Inpatient Survey campaign using term extraction as a means to highlight important and insightful subject matters raised by patients. We evaluate the results by mapping them to a manually constructed framework following the Activity, Resource, Context (ARC) methodology (Ordenes et al., 2014) and specific to the health care environment, and compare our results against manual annotations done on the full 2017 dataset based on those categories

A term extraction approach to survey analysis in health care

The voice of the customer has for a long time been a key focus of businesses in all domains. It has received a lot of attention from the research community in Natural Language Processing (NLP) resulting in many approaches to analysing customers feedback ((aspect-based) sentiment analysis, topic modeling, etc.). In the health domain, public and private bodies are increasingly prioritising patient engagement for assessing the quality of the service given at each stage of the care. Patient and customer satisfaction analysis relate in many ways. In the domain of health particularly, a more precise and insightful analysis is needed to help practitioners locate potential issues and plan actions accordingly. We introduce here an approach to patient experience with the analysis of free text questions from the 2017 Irish National Inpatient Survey campaign using term extraction as a means to highlight important and insightful subject matters raised by patients. We evaluate the results by mapping them to a manually constructed framework following the Activity, Resource, Context (ARC) methodology (Ordenes et al., 2014) and specific to the health care environment, and compare our results against manual annotations done on the full 2017 dataset based on those categories