Evidence map›Paper›PMID 20131023›Full record

ArticleJournal of general internal medicine2010

Primary medication non-adherence: analysis of 195,930 electronic prescriptions.

Michael A Fischer, Margaret R Stedman, Joyce Lii, Christine Vogeli, William H Shrank, M Alan Brookhart, Joel S Weissman

2 registry-linked trialsAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of general internal medicine, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 259 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
259citing papers in PubMed, 6 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.

NCT07613216 not yet recruitingnot on this mapstarted 2026, after this paper: background citation

A Comparison of a Medication Adherence Platform (FORTISKAP™) vs. Usual Care in Subjects on Oral Medications for the Treatment of Interstitial Lung Disease, Sarcoid and Pulmonary Hypertension

TypeobservationalSponsorCosmos Rx, IncRan2026 to 2027Enrolled100ConditionsIdiopathic Pulmonary Fibrosis (IPF), Sarcoidosis Lung, Pulmonary Hypertension, Usual Interstitial Pneumonia
NCT07712614 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

A Comparison of Cosmos Rx Medication Adherence Platform (FORTISKAP™) vs. Pharmacy Fill Adherence Measures for Subjects Undergoing Treatment for Gastroesophageal Reflux Disease With Proton Pump Inhibitors

TypeinterventionalSponsorCosmos Rx, IncRan2026 to 2027Enrolled50ConditionsGERD (Gastroesophageal Reflux Disease)ArmsFortiskap
3 · Its place in the literature

Who cites it

259 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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199 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Michael A FischerDivision of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital, Boston, MA 02120, USA. mfischer@partners.org
Margaret R Stedman
Joyce Lii
Christine Vogeli
William H Shrank
M Alan Brookhart
Joel S Weissman

Funding

An intervention to improve rational prescribing in cardiovascular diseaseK23HL090505 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SHRANK, WILLIAM · 2007 to 2010
$650k
E-Prescribing Impact on Patient Safety, Use, and CostR01HS015175 · AHRQ · MASSACHUSETTS GENERAL HOSPITAL · PI WEISSMAN, JOEL S. · 2004 to 2006
$163k
AHRQ HHS R01 HS015175AHRQ HHS R01 HS15175NHLBI NIH HHS HL090505NHLBI NIH HHS K23 HL090505NIA NIH HHS AG12084
6 · The paper itself

Abstract

backgroundNon-adherence to essential medications represents an important public health problem. Little is known about the frequency with which patients fail to fill prescriptions when new medications are started ("primary non-adherence") or predictors of failure to fill.

objectiveEvaluate primary non-adherence in community-based practices and identify predictors of non-adherence.

participants75,589 patients treated by 1,217 prescribers in the first year of a community-based e-prescribing initiative.

designWe compiled all e-prescriptions written over a 12-month period and used filled claims to identify filled prescriptions. We calculated primary adherence and non-adherence rates for all e-prescriptions and for new medication starts and compared the rates across patient and medication characteristics. Using multivariable regressions analyses, we examined which characteristics were associated with non-adherence. MAIN MEASURES: Primary medication non-adherence. KEY

resultsOf 195,930 e-prescriptions, 151,837 (78%) were filled. Of 82,245 e-prescriptions for new medications, 58,984 (72%) were filled. Primary adherence rates were higher for prescriptions written by primary care specialists, especially pediatricians (84%). Patients aged 18 and younger filled prescriptions at the highest rate (87%). In multivariate analyses, medication class was the strongest predictor of adherence, and non-adherence was common for newly prescribed medications treating chronic conditions such as hypertension (28.4%), hyperlipidemia (28.2%), and diabetes (31.4%).

conclusionsMany e-prescriptions were not filled. Previous studies of medication non-adherence failed to capture these prescriptions. Efforts to increase primary adherence could dramatically improve the effectiveness of medication therapy. Interventions that target specific medication classes may be most effective.

Indexed as

Drug MonitoringAdolescentAdultAgedChildChild, PreschoolCommunity Pharmacy ServicesConfidence IntervalsDatabases, FactualElectronic PrescribingFemaleHealth Care SurveysHumansInfantInformation SystemsMale

Identifiers

PMID20131023
PMCPMC2842539

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.