Understanding Temporal Patterns in Hypertensive Drug Therapy 1 - - PowerPoint PPT Presentation

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Understanding Temporal Patterns in Hypertensive Drug Therapy 1 - - PowerPoint PPT Presentation

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Understanding Temporal Patterns in Hypertensive Drug Therapy 1 Margret Bjarnadottir, 2 Sana Malik , 2 Catherine Plaisant, 3 Eberechukwu Onukwugha 1 Smith School of Business, University of Maryland, College Park 2 Department of Computer Science,

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SLIDE 1

Understanding Temporal Patterns


in Hypertensive Drug Therapy

1Margret Bjarnadottir, 2Sana Malik, 2Catherine Plaisant, 3Eberechukwu Onukwugha

1Smith School of Business, University of Maryland, College Park 2Department of Computer Science, University of Maryland, College Park 3School of Pharmacy, University of Maryland, Baltimore

May 28, 2015 — HCIL 32nd Annual Symposium

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2

๏ Worsened conditions ๏ Adverse outcomes ๏ Increased risk of death

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Hospitalization costs due to medication non-adherence are estimated as high as $13 billion annually.

3

Sullivan et al., “Noncompliance with medication regimens and subsequent hospitalizations: a literature analysis and cost of hospitalization estimate,” Journal of Research in Pharmaceutical Economics, Vol. 2, No.

  • 2. (1990), pp. 19-33.
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SLIDE 4

Medication Possession Ratio (MPR)

4

period n

  • bservatio
  • f

length supplied days

∑

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Medication Possession Ratio (MPR)

4

period n

  • bservatio
  • f

length supplied days

∑

time Study ¡start Study ¡end

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SLIDE 6

Medication Possession Ratio (MPR)

4

period n

  • bservatio
  • f

length supplied days

∑

time Study ¡start Study ¡end

= ¡100%

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SLIDE 7

Medication Possession Ratio (MPR)

4

period n

  • bservatio
  • f

length supplied days

∑

time Study ¡start Study ¡end

= ¡83%

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SLIDE 8

Medication Possession Ratio (MPR)

5

period n

  • bservatio
  • f

length supplied days

∑

= ¡75%

time Study ¡start Study ¡end

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SLIDE 9

Hypertensive Drug Therapy

Angiotension-Converting Enzyme-Inhibitors Angiotension II Receptor Blockers Calcium Channel Blockers Beta Blockers Diuretics

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ACE ARB CCB Beta Diur

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SLIDE 10

time

Hypertensive Drug Therapy

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SLIDE 11

time

Hypertensive Drug Therapy

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SLIDE 12

time

Hypertensive Drug Therapy

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SLIDE 13

time

Hypertensive Drug Therapy

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SLIDE 14

time

Hypertensive Drug Therapy

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SLIDE 15

time

Hypertensive Drug Therapy

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SLIDE 16

time

Hypertensive Drug Therapy

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SLIDE 17

time

Hypertensive Drug Therapy

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SLIDE 18

time

Hypertensive Drug Therapy

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SLIDE 19

time

Hypertensive Drug Therapy

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SLIDE 20

time

Hypertensive Drug Therapy

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SLIDE 21

time

Hypertensive Drug Therapy

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SLIDE 22

time

Hypertensive Drug Therapy

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SLIDE 23

time

Hypertensive Drug Therapy

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SLIDE 24

time

Hypertensive Drug Therapy

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SLIDE 25

time

Hypertensive Drug Therapy

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SLIDE 26

time

Hypertensive Drug Therapy

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SLIDE 27

time

Hypertensive Drug Therapy

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SLIDE 28

time

Hypertensive Drug Therapy

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SLIDE 29

time

Hypertensive Drug Therapy

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SLIDE 30

time

Hypertensive Drug Therapy

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SLIDE 31

time

Hypertensive Drug Therapy

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SLIDE 32

time

Hypertensive Drug Therapy

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SLIDE 33

time

Hypertensive Drug Therapy

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Can we use visualization tools to more accurately understand adherence patterns in hypertensive drug therapy?

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11

๏ Can we identify good vs. bad patterns? ๏ Can we understand patient behavior?

Research Questions

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Data

๏ Commercial prescription claims ๏ 900,000 individuals (16 million claims) ๏ 5 Drug Classes

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Angiotension-Converting Enzyme-Inhibitors Angiotension II Receptor Blockers Calcium Channel Blockers Beta Blockers Diuretics

ACE ARB CCB Beta Diur

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Data Simplification

๏ Partitioning ๏ Temporal Windowing ๏ Interval Merging

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Data Simplification

๏ Partitioning ๏ Temporal Windowing ๏ Interval Merging

Dataset

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Data Simplification

๏ Partitioning ๏ Temporal Windowing ๏ Interval Merging

— Single

}

2 Drugs

}

3 Drugs

}

4 Drugs — All 5

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Data Simplification

๏ Partitioning ๏ Temporal Windowing ๏ Interval Merging

time Start ¡of ¡record

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Data Simplification

๏ Partitioning ๏ Temporal Windowing ๏ Interval Merging

time 2 ¡years Start ¡of ¡record

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Data Simplification

๏ Partitioning ๏ Temporal Windowing ๏ Interval Merging

time

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Data Simplification

๏ Partitioning ๏ Temporal Windowing ๏ Interval Merging

time

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How do allowable gap and overlap assumptions affect adherence analysis?

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Sensitivity Analysis: Allowable Gap

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0 days 7 days 15 days 30 days

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Sensitivity Analysis: Allowable Gap

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0 days 7 days 15 days 30 days

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Sensitivity Analysis: Allowable Gap

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0 days 7 days 15 days 30 days

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SLIDE 48

Sensitivity Analysis: Allowable Gap

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0 days 7 days 15 days 30 days

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0 days 7 days 15 days 30 days

Sensitivity Analysis: Allowable Overlap

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SLIDE 50

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0 days 7 days 15 days 30 days

Sensitivity Analysis: Allowable Overlap

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SLIDE 51

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0 days 7 days 15 days 30 days

Sensitivity Analysis: Allowable Overlap

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0 days 7 days 15 days 30 days

Sensitivity Analysis: Allowable Overlap

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SLIDE 53

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Single Drugs

ACE ARB CCB Beta Diur

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Single Drugs

ACE ARB CCB Beta Diur

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2 Drugs

ACE Beta Both

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2 Drugs

ACE Beta Both

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2 Drugs

false overlap

ACE Beta Both

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2 Drugs

ACE Beta Both

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2 Drugs

ACE Beta Both

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All 5 Drugs

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2,200 patients

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2,200 patients

All 5 Drugs

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2,200 patients

All 5 Drugs

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2,200 patients

All 5 Drugs

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2,200 patients

All 5 Drugs

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All 5 Drugs

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2,200 patients

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All 5 Drugs

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2,200 patients

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Starting on Diuretic

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ACE ARB CCB Beta Diur

150,000 patients

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Starting on Diuretic

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ACE ARB CCB Beta Diur

150,000 patients

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Starting on Diuretic

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ACE ARB CCB Beta Diur

150,000 patients

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Summary

๏ Visualization facilitated rapid

understanding of complex patient behavior

๏ Interactions allow systematic analysis

  • f episode modeling

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Understanding Temporal Patterns


in Hypertensive Drug Therapy

Sana Malik maliks@cs.umd.edu www.cs.umd.edu/hcil/eventflow

Thanks to Sophia Wu. Support from the University of Maryland Center for Health-related Informatics and Bioimaging (CHIB).