Evidence map›Paper›PMID 35052233›Full record

ArticleHealthcare (Basel, Switzerland)2021

Persistent Cardiometabolic Health Gaps: Can Therapeutic Care Gaps Be Precisely Identified from Electronic Health Records.

Xiaowei Yan, Walter F Stewart, Hannah Husby, Jake Delatorre-Reimer, Satish Mudiganti, Farah Refai, Andrew Hudnut, Kevin Knobel, Karen MacDonald, Frangiscos Sifakis and 1 more

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Xiaowei YanSutter Center for Health System Research, 2121 N. California Blvd, Suite 310, Walnut Creek, CA 94596, USA.
Walter F StewartMedcurio, Inc., Oakland, CA 94618, USA.
Hannah HusbySutter Center for Health System Research, 2121 N. California Blvd, Suite 310, Walnut Creek, CA 94596, USA.ORCID 0000-0001-8809-5582
Jake Delatorre-ReimerFormerly Sutter Health Research, 2121 N. California Blvd, Suite 310, Walnut Creek, CA 94596, USA.
Satish MudigantiSutter Center for Health System Research, 2121 N. California Blvd, Suite 310, Walnut Creek, CA 94596, USA.
Farah RefaiFormerly Sutter Health Research, 2121 N. California Blvd, Suite 310, Walnut Creek, CA 94596, USA.
Andrew HudnutSutter Medical Group, Sacramento, CA 95833, USA.
Kevin KnobelSutter Gould Medical Foundation, Modesto, CA 95355, USA.
Karen MacDonaldFormerly AstraZeneca, Wilmington, DE 19897, USA.
Frangiscos SifakisFormerly AstraZeneca, Wilmington, DE 19897, USA.
James B JonesSutter Center for Health System Research, 2121 N. California Blvd, Suite 310, Walnut Creek, CA 94596, USA.

Funding

AstraZeneca N/A
6 · The paper itself

Abstract

The objective of this study was to determine the strengths and limitations of using structured electronic health records (EHR) to identify and manage cardiometabolic (CM) health gaps. We used medication adherence measures derived from dispense data to attribute related therapeutic care gaps (i.e., no action to close health gaps) to patient- (i.e., failure to retrieve medication or low adherence) or clinician-related (i.e., failure to initiate/titrate medication) behavior. We illustrated how such data can be used to manage health and care gaps for blood pressure (BP), low-density lipoprotein cholesterol (LDL-C), and HbA1c for 240,582 Sutter Health primary care patients. Prevalence of health gaps was 44% for patients with hypertension, 33% with hyperlipidemia, and 57% with diabetes. Failure to retrieve medication was common; this patient-related care gap was highly associated with health gaps (odds ratios (OR): 1.23-1.76). Clinician-related therapeutic care gaps were common (16% for hypertension, and 40% and 27% for hyperlipidemia and diabetes, respectively), and strongly related to health gaps for hyperlipidemia (OR = 5.8; 95% CI: 5.6-6.0) and diabetes (OR = 5.7; 95% CI: 5.4-6.0). Additionally, a substantial minority of care gaps (9% to 21%) were uncertain, meaning we lacked evidence to attribute the gap to either patients or clinicians, hindering efforts to close the gaps.

Indexed as

cardiometabolic conditionscare gapselectronic health record (EHR)health gapsmedication adherence

Identifiers

PMID35052233
PMCPMC8775887

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Registered trials

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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.