Evidence map›Paper›PMID 21552512›Full record

ArticleResearch Evaluation2010

Integrating utilization-focused evaluation with business process modeling for clinical research improvement.

Jonathan M Kagan, Scott Rosas, William M K Trochim

Abstract read
In one paragraph

Article in Research Evaluation, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. IRB Process Improvements: A Machine Learning Analysis.Journal of clinical and translational science · 2017
    Article
  2. Article
  3. Article
  4. Article
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

3 authors.

Jonathan M KaganDivision of Clinical Research, NIAID/NIH, 6700 B Rockledge Drive, Room 1102, MSC 7609, Bethesda, MD 20892-7609, USA.
Scott Rosas
William M K Trochim

Funding

CTSA INFRASTRUCTURE FOR PEDIATRIC RESEARCHUL1RR024996 · NCRR · WEILL MEDICAL COLL OF CORNELL UNIV · PI IMPERATO-MCGINLEY, JULIANNE L · 2007 to 2011
$49.6M
STRUCTURE AND FUNCTION OF THE T GONDII VACUOLE MEMBRANER01AI030060 · NIAID · YALE UNIVERSITY · PI JOINER, KEITH ALAN · 1990 to 2006
$2.7M
NCRR NIH HHS UL1 RR024996NIAID NIH HHS N01 AI030020NIAID NIH HHS N01 AI030060NIAID NIH HHS N01 AI050022
6 · The paper itself

Abstract

New discoveries in basic science are creating extraordinary opportunities to design novel biomedical preventions and therapeutics for human disease. But the clinical evaluation of these new interventions is, in many instances, being hindered by a variety of legal, regulatory, policy and operational factors, few of which enhance research quality, the safety of study participants or research ethics. With the goal of helping increase the efficiency and effectiveness of clinical research, we have examined how the integration of utilization-focused evaluation with elements of business process modeling can reveal opportunities for systematic improvements in clinical research. Using data from the NIH global HIV/AIDS clinical trials networks, we analyzed the absolute and relative times required to traverse defined phases associated with specific activities within the clinical protocol lifecycle. Using simple median duration and Kaplan-Meyer survival analysis, we show how such time-based analyses can provide a rationale for the prioritization of research process analysis and re-engineering, as well as a means for statistically assessing the impact of policy modifications, resource utilization, re-engineered processes and best practices. Successfully applied, this approach can help researchers be more efficient in capitalizing on new science to speed the development of improved interventions for human disease.

Identifiers

PMID21552512
PMCPMC3087184

What OpenQuestion holds

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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.