Evidence map›Paper›PMID 22963227›Full record

ArticleBMC medical informatics and decision making2012

Why technology matters as much as science in improving healthcare.

Robert J Szczerba, Marco D Huesch

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

  1. Pooled it
  2. Review
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

2 authors.

Robert J SzczerbaLockheed Martin Corporation, Owego, NY 13827, USA.
Marco D Huesch

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMore than half a million new items of biomedical research are generated every year and added to Medline. How successful are we at applying this steady accumulation of scientific knowledge and so improving the practice of medicine in the USA? DISCUSSION: The conventional wisdom is that the US healthcare system is plagued by serious cost, access, safety and quality weaknesses. A comprehensive solution must involve the better translation of an abundance of clinical research into improved clinical practice.Yet the application of knowledge (i.e. technology) remains far less well funded and less visible than the generation, synthesis and accumulation of knowledge (i.e. science), and the two are only weakly integrated. Worse, technology is often seen merely as an adjunct to practice, e.g. electronic health records.Several key changes are in order. A helpful first step lies in better understanding the distinction between science and technology, and their complementary strengths and limitations. The absolute level of funding for technology development must be increased as well as being more integrated with traditional science-based clinical research. In such a mission-oriented federal funding strategy, the ties between basic science research and applied research would be better emphasized and strengthened. SUMMARY: It bears repeating that only by applying the wealth of existing and future scientific knowledge can healthcare delivery and patient care ever show significant improvement.

Indexed as

Biomedical ResearchDiffusion of InnovationTechnology TransferTranslational Research, BiomedicalDelivery of Health CareEvidence-Based MedicineGuidelines as TopicHumansInformation DisseminationOrganizational CultureQuality Assurance, Health CareTechnology Assessment, BiomedicalTime FactorsUnited States

Identifiers

PMID22963227
PMCPMC3468390

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.