Evidence map›Paper›PMID 30135608›Full record

ArticleThe Engineering economist2017

Evaluating the Cost-Effectiveness of an Early Detection of Parkinson's Disease through Innovative Technology.

David A Munoz, Mehmet Serdar Kilinc, Harriet B Nembhard, Conrad Tucker, Xuemei Huang

Open access · greenAbstract read
In one paragraph

Article in The Engineering economist, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.2field-weighted citation impact, top 46% of its field
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

8 citing papers in PubMed, 15 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

David A MunozDepartment of Industrial and Manufacturing Engineering, The Pennsylvania State University.
Mehmet Serdar KilincDepartment of Industrial and Manufacturing Engineering, The Pennsylvania State University.
Harriet B NembhardDepartment of Industrial and Manufacturing Engineering, The Pennsylvania State University.
Conrad TuckerDepartment of Industrial and Manufacturing Engineering, The Pennsylvania State University.
Xuemei HuangCollege of Medicine, The Pennsylvania State University.
Pennsylvania State University · US

Funding

Penn State Clinical and Translational Science InstituteUL1TR002014 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI KRASCHNEWSKI, JENNIFER L. · 2016 to 2025
$33.7M
Penn State Clinical and Translational Science InstituteUL1TR000127 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI SINOWAY, LAWRENCE I · 2012 to 2015
$17.1M
NCATS NIH HHS UL1 TR000127NCATS NIH HHS UL1 TR002014
6 · The paper itself

Abstract

Early detection of Parkinson's Disease (PD) is critically important as it can increase patient quality of life and save treatment cost. An innovative approach for early detection of PD is to use non-wearable sensors that are capable of capturing skeletal joint data. This paper evaluates the cost-effectiveness of this sensor-based intervention considering the quality-adjusted life years (QALYs) and the associated costs. The results indicate that the intervention would be cost-effective if devices were deployed for community health screening in public places such as health fairs and pharmacies.

Indexed as

Cost-effectiveness analysishealthcare interventionParkinson’s Diseasequality-adjusted life years

Identifiers

PMID30135608
PMCPMC6101669
OpenAlexW2590239694

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.