Evidence map›Paper›PMID 34316631›Full record

ArticleClinical parkinsonism & related disorders2020

Use of a medication-based algorithm to identify advanced Parkinson's disease in administrative claims data: Associations with claims-based indicators of disease severity.

Nabila Dahodwala, Amy R Pettit, Jordan Jahnke, Pengxiang Li, Vrushabh P Ladage, Prasanna L Kandukuri, Jorge Zamudio, Yash J Jalundhwala, Jalpa A Doshi

Abstract read
In one paragraph

Article in Clinical parkinsonism & related disorders, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Nabila DahodwalaDepartment of Neurology, Perelman School of Medicine, University of Pennsylvania, 330 South 9th Street, 2nd Floor, Philadelphia, PA 19107, USA.
Amy R PettitCenter for Public Health Initiatives, University of Pennsylvania, Philadelphia, PA, USA.
Jordan JahnkeDepartment of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, 1223 Blockley Hall, Philadelphia, PA 19104, USA.
Pengxiang LiLeonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.
Vrushabh P LadageDepartment of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, 1223 Blockley Hall, Philadelphia, PA 19104, USA.
Prasanna L KandukuriAbbVie Inc., 1 N Waukegan Road, North Chicago, IL 60064, USA.
Jorge ZamudioAbbVie Inc., 1 N Waukegan Road, North Chicago, IL 60064, USA.
Yash J JalundhwalaAbbVie Inc., 1 N Waukegan Road, North Chicago, IL 60064, USA.
Jalpa A DoshiLeonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionLack of a gold standard definition for advanced Parkinson's Disease (APD), coupled with absence of disease severity information in diagnostic codes, hinders use of large administrative databases for conducting population health and comparative effectiveness studies.

methodsUsing pharmacy claims data, we created an algorithm to identify APD: any 30-day average levodopa equivalent dose (LED) >1000 mg/day. Using 2013 100% U.S. Medicare claims, we applied this algorithm and used multivariate logistic regression to examine associations between assigned APD status and claims-based indicators of PD severity (any deep brain stimulation, fall, hallucinations, walker, wheelchair, specialty bed, dementia diagnosis, skilled nursing facility, hospice), adjusting for sociodemographic, clinical, and treatment characteristics. Levodopa >1000 mg/day, levodopa >800 mg/day and LED >800 mg/day were used in sensitivity analysis.

resultsIn our sample (

conclusionsMedicare patients classified as having APD via a pharmacy claims-based algorithm had higher odds of having claims-based clinical markers of APD, compared with patients categorized as having mild-moderate PD. This proxy strategy could facilitate future claims-based studies and warrants further refinement and validation using medical records or other clinical sources.

Indexed as

Claims dataClinical indicatorsDisease stagingMedicareParkinson's disease

Identifiers

PMID34316631
PMCPMC8298763

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.