Evidence map›Paper›PMID 33345949›Full record

ArticleChest2021

Development and Validation of Algorithms to Identify Pulmonary Arterial Hypertension in Administrative Data.

Kari R Gillmeyer, Eduardo R Nunez, Seppo T Rinne, Shirley X Qian, Elizabeth S Klings, Renda Soylemez Wiener

Abstract readValidation Study
In one paragraph

Article in Chest, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Kari R GillmeyerCenter for Healthcare Organization & Implementation Research, Edith Nourse Rogers Veterans Hospital, Bedford, MA; VA Boston Healthcare System, Boston, MA; The Pulmonary Center, Boston University School of Medicine, Boston, MA. Electronic address: krgill@bu.edu.
Eduardo R NunezCenter for Healthcare Organization & Implementation Research, Edith Nourse Rogers Veterans Hospital, Bedford, MA; VA Boston Healthcare System, Boston, MA; The Pulmonary Center, Boston University School of Medicine, Boston, MA.
Seppo T RinneCenter for Healthcare Organization & Implementation Research, Edith Nourse Rogers Veterans Hospital, Bedford, MA; VA Boston Healthcare System, Boston, MA; The Pulmonary Center, Boston University School of Medicine, Boston, MA.
Shirley X QianCenter for Healthcare Organization & Implementation Research, Edith Nourse Rogers Veterans Hospital, Bedford, MA; VA Boston Healthcare System, Boston, MA.
Elizabeth S KlingsThe Pulmonary Center, Boston University School of Medicine, Boston, MA.
Renda Soylemez WienerCenter for Healthcare Organization & Implementation Research, Edith Nourse Rogers Veterans Hospital, Bedford, MA; VA Boston Healthcare System, Boston, MA; The Pulmonary Center, Boston University School of Medicine, Boston, MA.

Funding

Project-005UL1TR001430 · NCATS · BOSTON UNIVERSITY MEDICAL CAMPUS · PI BAIR-MERRITT, MEGAN H, CENTER, DAVID M. · 2015 to 2024
$52.3M
BIOLOGY OF THE LUNG--MULTIDISCIPLINARY PROGRAMT32HL007035 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI Darrell N. Kotton, JOSEPH P MIZGERD · 1985 to 2026
$24.3M
Hematopoietic Stem Cell Transplantation for Young Adults with Sickle Cell Disease - Clinical Coordinating CenterU01HL128566 · NHLBI · YALE UNIVERSITY · PI KRISHNAMURTI, LAKSHMANAN, WALTERS, MARK C · 2015 to 2019
$7.3M
1/2 Sickle Cell Disease and CardiovAscular Risk - Red cell Exchange Trial (SCD-CARRE Trial)UG3HL143192 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI GLADWIN, MARK T, TRIULZI, DARRELL J · 2019 to 2019
$1.5M
Determining disparities in treatment of pulmonary arterial hypertension nationallyF32HL149236 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI GILLMEYER, KARI · 2019 to 2020
$157k
Improving Analysis of Endogenous Multimodal Treatments for Use in Geriatrics Health Outcomes StudiesI01HX002237 · VA · VA BOSTON HEALTH CARE SYSTEM · PI GARRIDO, MELISSA M · 2018 to 2021
–
Factors and Outcomes Associated with Inappropriate Prescribing of Phosphodiesterase-5-Inhibitors for Pulmonary HypertensionI01HX001830 · VA · VA BOSTON HEALTH CARE SYSTEM · PI WIENER, RENDA SOYLEMEZ · 2019 to 2021
–
HSRD VA I01 HX001830HSRD VA SDR 02-237NCATS NIH HHS UL1 TR001430NHLBI NIH HHS F32 HL149236NHLBI NIH HHS L60 HL154266NHLBI NIH HHS T32 HL007035NHLBI NIH HHS U01 HL128566NHLBI NIH HHS UG3 HL143192
6 · The paper itself

Abstract

backgroundPulmonary arterial hypertension (PAH) is a rare disease, and much of our understanding stems from single-center studies, which are limited by sample size and generalizability. Administrative data offer an appealing opportunity to inform clinical, research, and quality improvement efforts for PAH. Yet, currently no standardized, validated method exists to distinguish PAH from other subgroups of pulmonary hypertension (PH) within this data source. RESEARCH QUESTION: Can a collection of algorithms be developed and validated to detect PAH in administrative data in two diverse settings: all Veterans Health Administration (VA) hospitals and Boston Medical Center (BMC), a PAH referral center. STUDY DESIGN AND

methodsIn each setting, we identified all adult patients with incident PH from 2006 through 2017 using International Classification of Diseases PH diagnosis codes. From this baseline cohort of all PH subgroups, we sequentially applied the following criteria: diagnosis codes for PAH-associated conditions, procedure codes for right heart catheterizations (RHCs), and pharmacy claims for PAH-specific therapy. We then validated each algorithm using a gold standard review of primary clinical data and calculated sensitivity, specificity, positive predictive values (PPVs), and negative predictive values.

resultsFrom our baseline cohort, we identified 12,012 PH patients in all VA hospitals and 503 patients in BMC. Sole use of PH diagnosis codes performed poorly in identifying PAH (PPV, 16.0% in VA hospitals and 36.0% in BMC). The addition of PAH-associated conditions to the algorithm modestly improved PPV. The best performing algorithm required ICD diagnosis codes, RHC codes, and PAH-specific therapy (VA hospitals: specificity, 97.1%; PPV, 70.0%; BMC: specificity, 95.0%; PPV, 86.0%).

interpretationThis set of validated algorithms to identify PAH in administrative data can be used by the PAH scientific and clinical community to enhance the reliability and value of research findings, to inform quality improvement initiatives, and ultimately to improve health for PAH patients.

Indexed as

AlgorithmsInformation Storage and RetrievalAcademic Medical CentersAdultHospitals, VeteransHumansInternational Classification of DiseasesPulmonary Arterial Hypertensionadministrative datamedical informaticspulmonary arterial hypertensionpulmonary hypertension

Identifiers

PMID33345949
PMCPMC8129727

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.