Evidence map›Paper›PMID 30054889›Full record

ArticleJournal of general internal medicine2018

Time to Filling of New Prescriptions for Chronic Disease Medications Among a Cohort of Elderly Patients in the USA.

Jessica M Franklin, Mufaddal Mahesri, Alexis A Krumme, Julie Barberio, Michael A Fischer, Gregory Brill, Caroline McKay, Heather Black, Niteesh K Choudhry

Abstract readMulticenter Study
In one paragraph

Article in Journal of general internal medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 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.

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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Not obtaining a medication the first time it is prescribed: primary non-adherence to cardiovascular pharmacotherapy.Clinical research in cardiology : official journal of the German Cardiac Society · 2024
    Review
  5. Article
  6. Observational
  7. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Jessica M FranklinDivision of Pharmacoepidemiology & Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. jmfranklin@bwh.harvard.edu.
Mufaddal MahesriDivision of Pharmacoepidemiology & Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Alexis A KrummeDivision of Pharmacoepidemiology & Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Julie BarberioDivision of Pharmacoepidemiology & Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Michael A FischerDivision of Pharmacoepidemiology & Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Gregory BrillDivision of Pharmacoepidemiology & Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Caroline McKayMerck & Co., Inc., Kenilworth, NJ, USA.
Heather BlackMerck & Co., Inc., Kenilworth, NJ, USA.
Niteesh K ChoudhryDivision of Pharmacoepidemiology & Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundData on primary nonadherence remains sparse, due to a lack of data resources that combine information on medication prescribing and dispensing. In addition, previous work on primary nonadherence has used follow-up periods ranging from 30 days up to 18 months, making results difficult to compare.

objectiveTo evaluate the prevalence and predictors of primary nonadherence by measuring time until filling in a cohort of elderly patients.

designRetrospective cohort study of new prescription episodes. PATIENTS: Data comes from a linked database of electronic health records and claims for patients aged ≥ 65 years enrolled in Medicare Parts A, B, and D during 2007-2014. We identified patients receiving a new prescription for a chronic disease medication with continuous Medicare enrollment for 180 days prior to the index prescription order and no fills or orders for the medication during this period. MAIN MEASURES: Time until filling of the index prescription for up to 1 year. KEY

resultsIn 32,586 new medication orders, the majority (75%; 95% confidence interval [CI] 74-75%) of new prescriptions were filled within 7 days, 81% (81-82%) were filled within 30 days, and 91% (91-92%) were filled within 1 year. The rate and timing of dispensing were similar across therapeutic areas. Timing of initial filling within 7 days or within 30 days could be predicted with moderate accuracy (C-statistics = 0.70-0.74). Patients with > 5 current medications on hand at the time of the index prescription and average out-of-pocket medication costs < $5 filled 89% of prescriptions within 7 days. Patients with no current medications and out-of-pocket costs > $50 filled only 25% of prescriptions within 7 days.

conclusionsNearly 20% of patients do not fill a new chronic disease prescription within 30 days. Patients with fewer recent fills and higher out-of-pocket costs are at higher risk of primary nonadherence.

Indexed as

Medication AdherenceAgedAged, 80 and overChronic DiseaseCohort StudiesDrug PrescriptionsFemaleFollow-Up StudiesHealth ExpendituresHumansMaleRetrospective StudiesTime FactorsUnited Stateselectronic health recordshealth insurance claimslassopredictionprimary nonadherence

Identifiers

PMID30054889
PMCPMC6206334

What OpenQuestion holds

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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.