Evidence map›Paper›PMID 27578751›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2017

Navigating a ship with a broken compass: evaluating standard algorithms to measure patient safety.

Jennifer L Hefner, Timothy R Huerta, Ann Scheck McAlearney, Barbara Barash, Tina Latimer, Susan D Moffatt-Bruce

Open access · bronzeAbstract readValidation Study
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. 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 2 institutions in 1 country.

Jennifer L HefnerDepartment of Family Medicine, College of Medicine, The Ohio State University, Columbus, Ohio, USA.
Timothy R HuertaDepartment of Family Medicine, College of Medicine, The Ohio State University, Columbus, Ohio, USA.
Ann Scheck McAlearneyDepartment of Family Medicine, College of Medicine, The Ohio State University, Columbus, Ohio, USA.
Barbara BarashDepartment of Family Medicine, College of Medicine, The Ohio State University, Columbus, Ohio, USA.
Tina LatimerQuality and Operations, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA.
Susan D Moffatt-BruceQuality and Operations, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA.
The Ohio State University · USThe Ohio State University Wexner Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Agency for Healthcare Research and Quality (AHRQ) software applies standardized algorithms to hospital administrative data to identify patient safety indicators (PSIs). The objective of this study was to assess the validity of PSI flags and report reasons for invalid flagging. Material and Methods: At a 6-hospital academic medical center, a retrospective analysis was conducted of all PSIs flagged in fiscal year 2014. A multidisciplinary PSI Quality Team reviewed each flagged PSI based on quarterly reports. The positive predictive value (PPV, the percent of clinically validated cases) was calculated for 12 PSI categories. The documentation for each reversed case was reviewed to determine the reasons for PSI reversal. Results: Of 657 PSI flags, 185 were reversed. Seven PSI categories had a PPV below 75%. Four broad categories of reasons for reversal were AHRQ algorithm limitations (38%), coding misinterpretations (45%), present upon admission (10%), and documentation insufficiency (7%). AHRQ algorithm limitations included 2 subcategories: an "incident" was inherent to the procedure, or highly likely (eg, vascular tumor bleed), or an "incident" was nonsignificant, easily controlled, and/or no intervention was needed. Discussion: These findings support previous research highlighting administrative data problems. Additionally, AHRQ algorithm limitations was an emergent category not considered in previous research. Herein we present potential solutions to address these issues. Conclusions: If, despite poor validity, US policy continues to rely on PSIs for incentive and penalty programs, improvements are needed in the quality of administrative data and the standardized PSI algorithms. These solutions require national motivation, research attention, and dissemination support.

Indexed as

AlgorithmsPatient SafetyQuality Indicators, Health CareAcademic Medical CentersHumansMedical ErrorsRetrospective StudiesSafety ManagementSoftwareUnited StatesUnited States Agency for Healthcare Research and Qualityadministrative datapatient safety indicatorsquality measurement

Identifiers

PMID27578751
PMCPMC7651941
OpenAlexW2507394908

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.