understanding temporal patterns · understanding temporal patterns in hypertensive drug therapy...

Understanding Temporal Patternsin 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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๏ Worsened conditions

๏ Adverse outcomes

๏ Increased risk of death

Hospitalization costs due to medication non-adherence are estimated as high as

$13 billion annually.

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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.

Medication Possession Ratio (MPR)

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period nobservatio of lengthsupplied days∑


4


time

Study start Study end


4


time


= 100%


4


time


= 83%


5

period nobservatio of lengthsupplied days∑ = 75%

time


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

time

Hypertensive Drug Therapy

Can we use visualization tools to more accurately understand adherence

patterns in hypertensive drug therapy?

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๏ Can we identify good vs. bad patterns?

๏ Can we understand patient behavior?

Research Questions

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

Data Simplification

๏ Partitioning

๏ Temporal Windowing

๏ Interval Merging

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Data Simplification

๏ Partitioning


๏ Interval Merging Dataset

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Data Simplification

๏ Partitioning



— Single

} 2 Drugs

} 3 Drugs

} 4 Drugs

— All 5

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Data Simplification

๏ Partitioning



timeStart of record

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Data Simplification

๏ Partitioning



time2 yearsStart of record

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Data Simplification

๏ Partitioning



time

How do allowable gap and overlap assumptions affect adherence

analysis?

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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Single DrugsACE

ARB

CCB

Beta

Diur

21

2 DrugsACE

Beta

Both

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2 Drugs

false overlap

ACE

Beta

Both

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2 DrugsACE

Beta

Both

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2 DrugsACE

Beta

Both

All 5 Drugs

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2,200 patients

2,200 patientsAll 5 Drugs

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All 5 Drugs

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2,200 patients

Starting on Diuretic

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ACE

ARB

CCB

Beta

Diur150,000 patients

Summary

๏ Visualization facilitated rapid understanding of complex patient behavior

๏ Interactions allow systematic analysis of episode modeling

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Understanding Temporal Patternsin Hypertensive Drug Therapy

Sana [email protected]/hcil/eventflow

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

mailto:[email protected]

http://www.cs.umd.edu/hcil/eventflow

understanding temporal patterns · understanding temporal patterns in hypertensive drug therapy...

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