Healthcare market segmentation and data mining: A systematic review

Area of Science:

• Health Marketing Research
• Consumer Behavior Analysis
• Data Mining Applications

Background:

• Healthcare delivery is shifting towards patient-centered models.
• Understanding consumer attitudes and behaviors is crucial for this transition.
• Effective health marketing strategies require deep consumer insights.

Purpose of the Study:

• To systematically review the literature on healthcare market segmentation and data mining.
• To identify gaps and opportunities in current health marketing research.
• To inform future research directions in leveraging patient data.

Main Methods:

• Systematic literature review.
• Analysis of common themes in healthcare market segmentation studies.
• Identification of data mining techniques used in health marketing.

Main Results:

• Current research often relies on survey data and basic clustering methods.
• Limited use of advanced classification modeling post-clustering was observed.
• Demographic analysis of clusters is common, but patient-level data is underutilized.
• Opportunities exist for advanced data mining with patient-level data.

Conclusions:

• There is a need to move beyond traditional survey data in health marketing.
• Advanced data mining techniques offer significant potential for deeper consumer insights.
• Future research should focus on leveraging patient-level data for more sophisticated segmentation and marketing strategies.