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. 2018 Jul 10;6(3):78.
doi: 10.3390/healthcare6030078.

Developing a Case-Based Blended Learning Ecosystem to Optimize Precision Medicine: Reducing Overdiagnosis and Overtreatment

Affiliations

Developing a Case-Based Blended Learning Ecosystem to Optimize Precision Medicine: Reducing Overdiagnosis and Overtreatment

Vivek Podder et al. Healthcare (Basel). .

Abstract

Introduction: Precision medicine aims to focus on meeting patient requirements accurately, optimizing patient outcomes, and reducing under-/overdiagnosis and therapy. We aim to offer a fresh perspective on accuracy driven “age-old precision medicine” and illustrate how newer case-based blended learning ecosystems (CBBLE) can strengthen the bridge between age-old precision approaches with modern technology and omics-driven approaches.

Methodology: We present a series of cases and examine the role of precision medicine within a “case-based blended learning ecosystem” (CBBLE) as a practicable tool to reduce overdiagnosis and overtreatment. We illustrated the workflow of our CBBLE through case-based narratives from global students of CBBLE in high and low resource settings as is reflected in global health.

Results: Four micro-narratives based on collective past experiences were generated to explain concepts of age-old patient-centered scientific accuracy and precision and four macro-narratives were collected from individual learners in our CBBLE. Insights gathered from a critical appraisal and thematic analysis of the narratives were discussed.

Discussion and conclusion: Case-based narratives from the individual learners in our CBBLE amply illustrate their journeys beginning with “age-old precision thinking” in low-resource settings and progressing to “omics-driven” high-resource precision medicine setups to demonstrate how the approaches, used judiciously, might reduce the current pandemic of over-/underdiagnosis and over-/undertreatment.

Keywords: CBBLE (case-based-based blended learning ecosystem); case studies; high resource setting; low resource setting; omics driven; overdiagnosis; overtreatment; precision medicine.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Mapping ‘Precision’ and ‘Accuracy’ in Medicine (Accuracy—achieving patients’ requirement of best outcome, and Precision—the narrowest path to achieve it).
Figure 2
Figure 2
Illustrates the analogy of healthcare ecosystem functioning in the form of a cricket match.
Figure 3
Figure 3
Illustrating the patient data shared online into our CBBLE online network.
Figure 4
Figure 4
Illustrating the patient data shared online into our CBBLE online network.
Figure 5
Figure 5
Illustrates the graphical representation of her illness during her stay in the hospital.
Figure 6
Figure 6
Illustrates the feedback and the queries posted from the CBBLE online network.

References

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