Data Visualization: New Health Data Value

Old School Data Set, Rebooted, Repurposed and Creating Killer New Value Health Datapalooza, June 2, 2015

Ramon MartinezAdviser in Health Metrics, Pan American Health Organization (PAHO)

martiner@paho.org @HlthAnalysis

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Introduction• In health, sharing data will help save lives by

informing research, policies and decisions to improve prevention of diseases and delivery of healthcare.

• Health data sets should be shared with tools that facilitate data exploration and understanding

• Data Visualization New Value to Health Data

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Data Visualization is a product of

Data Analytic Process

and

Visual Analytic Cycle

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The analytic process

1. The question – public health issue or situation

2. Analytic framework

3. Identification of data sources

4. Analytic plan - methods

5. Analysis & interpretation of results

6. Communication of results and findings

7. Interventions – actions for improving health

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Visual Analytic Cycle

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Data set New value

Prevalence of Diabetes in Adults, 2013

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Objective: Assess the level and trends of the prevalence of diabetes worldwide

Source: International Diabetes Federation (IDF)

Analytics questions:1. How is the diabetes prevalence

distributed geographically? 2. Which countries have the highest

level of prevalence3. Is prevalence of diabetes related to

impaired glucose tolerance (IGT)

Prevalence of hypertension in the USObjective:

Identify areas with highest level of prevalence of high blood pressure

Source: Estimates of high blood pressure in the US. Institute of Health Metrics and Evaluation (IHME)

Analytic questions:1. How is hypertension distributed

across the US?2. Is there any geographic pattern?3. Which States and Counties

should we prioritize for cardiovascular disease program

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Some points to conclude• In health, sharing data will help save lives by informing

research, policies and decisions to improve prevention of diseases and delivery of healthcare.

• Share data sets and information visualizations for impact on a broader audience

• Interactive visualizations can encourage and enable people to explore underlying or contextual data to broaden understanding

• An interactive data visualization can tell a story or enable users to explore and find stories.