Evidence map›Paper›PMID 25298814›Full record

ArticleApplied clinical informatics2014

Reducing risk with clinical decision support: a study of closed malpractice claims.

G Zuccotti, F L Maloney, J Feblowitz, L Samal, L Sato, A Wright

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Applied clinical informatics, 2014. 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
4.0field-weighted citation impact, top 7% 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, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Using statistical anomaly detection models to find clinical decision support malfunctions.Journal of the American Medical Informatics Association : JAMIA · 2018
    Article
  6. Review
  7. Knowledge Translation and Barriers to Imaging Optimization in the Emergency Department: A Research Agenda.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2015
    Article
  8. 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

6 authors at 1 institution in 1 country.

G ZuccottiBrigham and Women's Hospital and Harvard Medical School , Boston, MA, USA ; Partners HealthCare , Boston, MA, USA ; CRICO/Risk Management Foundation , Cambridge, MA, USA.
F L MaloneyPartners HealthCare , Boston, MA, USA.
J FeblowitzBrigham and Women's Hospital and Harvard Medical School , Boston, MA, USA.
L SamalBrigham and Women's Hospital and Harvard Medical School , Boston, MA, USA.
L SatoCRICO/Risk Management Foundation , Cambridge, MA, USA.
A WrightBrigham and Women's Hospital and Harvard Medical School , Boston, MA, USA ; Partners HealthCare , Boston, MA, USA.
Brigham and Women's Hospital · US

Funding

Health Information Technology for Chronic Kidney Disease ManagementK23DK097187 · NIDDK · BRIGHAM AND WOMEN'S HOSPITAL · PI SAMAL, LIPIKA · 2013 to 2017
$920k
NIDDK NIH HHS K23 DK097187
6 · The paper itself

Abstract

objectiveIdentify clinical opportunities to intervene to prevent a malpractice event and determine the proportion of malpractice claims potentially preventable by clinical decision support (CDS). MATERIALS AND

methodsCross-sectional review of closed malpractice claims over seven years from one malpractice insurance company and seven hospitals in the Boston area. For each event, clinical opportunities to intervene to avert the malpractice event and the presence or absence of CDS that might have a role in preventing the event, were assigned by a panel of expert raters. Compensation paid out to resolve a claim (indemnity), was associated with each CDS type.

resultsOf the 477 closed malpractice cases, 359 (75.3%) were categorized as substantiated and 195 (54%) had at least one opportunity to intervene. Common opportunities to intervene related to performance of procedure, diagnosis, and fall prevention. We identified at least one CDS type for 63% of substantiated claims. The 41 CDS types identified included clinically significant test result alerting, diagnostic decision support and electronic tracking of instruments. Cases with at least one associated intervention accounted for $40.3 million (58.9%) of indemnity. DISCUSSION: CDS systems and other forms of health information technology (HIT) are expected to improve quality of care, but their potential to mitigate risk had not previously been quantified. Our results suggest that, in addition to their known benefits for quality and safety, CDS systems within HIT have a potential role in decreasing malpractice payments.

conclusionMore than half of malpractice events and over $40 million of indemnity were potentially preventable with CDS.

Indexed as

Compensation and RedressInsurance Claim ReviewBostonDecision Support Systems, ClinicalInsurance, LiabilityLiability, LegalMalpracticeMedical ErrorsRisk Reduction Behaviorclinical decision support systemselectronic health recordshealth information technologyMalpracticeprofessional liability

Identifiers

PMID25298814
PMCPMC4187091
OpenAlexW1850222847

What OpenQuestion holds

Textmetadata
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.