Does a multimethod approach improve identification of medication nonadherence in adolescents with chronic kidney disease?

Cozumel S Pruette, Shayna S. Coburn, Cyd K. Eaton, Tammy McLoughlin Brady, Shamir Tuchman, Susan Mendley, Barbara A Fivush, Michelle Eakin, Kristin Riekert

Research output: Contribution to journalArticle

Abstract

Background: Medical provider assessment of nonadherence is known to be inaccurate. Researchers have suggested using a multimethod assessment approach; however, no study has demonstrated how to integrate different measures to improve accuracy. This study aimed to determine if using additional measures improves the accurate identification of nonadherence beyond provider assessment alone. Methods: Eighty-seven adolescents and young adults (AYAs), age 11–19 years, with chronic kidney disease (CKD) [stage 1–5/end-stage renal disease (ESRD)] and prescribed antihypertensive medication, their caregivers, and 17 medical providers participated in the multisite study. Five adherence measures were obtained: provider report, AYA report, caregiver report, electronic medication monitoring (MEMS), and pharmacy refill data [medication possession ratio (MPR)]. Concordance was calculated using kappa statistic. Sensitivity, specificity, positive predictive power, and negative predictive power were calculated using MEMS as the criterion for measuring adherence. Results: There was poor to fair concordance (kappas = 0.12–0.54), with 35–61% of AYAs classified as nonadherent depending on the measure. While both providers and MEMS classified 35% of the AYAs as nonadherent, sensitivity (0.57) and specificity (0.77) demonstrated poor agreement between the two measures on identifying which AYAs were nonadherent. Combining provider report of nonadherence and MPR < 75% resulted in the highest sensitivity for identifying nonadherence (0.90) and negative predictive power (0.88). Conclusions: Nonadherence is prevalent in AYAs with CKD. Providers inaccurately identify nonadherence, leading to missed opportunities to intervene. Our study demonstrates the benefit to utilizing a multimethod approach to identify nonadherence in patients with chronic disease, an essential first step to reduce nonadherence.

Original languageEnglish (US)
JournalPediatric Nephrology
DOIs
StateAccepted/In press - Jan 1 2018

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Medication Adherence
Chronic Renal Insufficiency
Young Adult
Micro-Electrical-Mechanical Systems
Caregivers
Sensitivity and Specificity
Patient Compliance
Antihypertensive Agents
Chronic Kidney Failure
Chronic Disease
Research Personnel

Keywords

  • Adherence
  • Antihypertensive
  • Concordance
  • Measures
  • Pediatric
  • Provider perception

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health
  • Nephrology

Cite this

@article{2e6e8736ea6d4635a5929a831c884671,
title = "Does a multimethod approach improve identification of medication nonadherence in adolescents with chronic kidney disease?",
abstract = "Background: Medical provider assessment of nonadherence is known to be inaccurate. Researchers have suggested using a multimethod assessment approach; however, no study has demonstrated how to integrate different measures to improve accuracy. This study aimed to determine if using additional measures improves the accurate identification of nonadherence beyond provider assessment alone. Methods: Eighty-seven adolescents and young adults (AYAs), age 11–19 years, with chronic kidney disease (CKD) [stage 1–5/end-stage renal disease (ESRD)] and prescribed antihypertensive medication, their caregivers, and 17 medical providers participated in the multisite study. Five adherence measures were obtained: provider report, AYA report, caregiver report, electronic medication monitoring (MEMS), and pharmacy refill data [medication possession ratio (MPR)]. Concordance was calculated using kappa statistic. Sensitivity, specificity, positive predictive power, and negative predictive power were calculated using MEMS as the criterion for measuring adherence. Results: There was poor to fair concordance (kappas = 0.12–0.54), with 35–61{\%} of AYAs classified as nonadherent depending on the measure. While both providers and MEMS classified 35{\%} of the AYAs as nonadherent, sensitivity (0.57) and specificity (0.77) demonstrated poor agreement between the two measures on identifying which AYAs were nonadherent. Combining provider report of nonadherence and MPR < 75{\%} resulted in the highest sensitivity for identifying nonadherence (0.90) and negative predictive power (0.88). Conclusions: Nonadherence is prevalent in AYAs with CKD. Providers inaccurately identify nonadherence, leading to missed opportunities to intervene. Our study demonstrates the benefit to utilizing a multimethod approach to identify nonadherence in patients with chronic disease, an essential first step to reduce nonadherence.",
keywords = "Adherence, Antihypertensive, Concordance, Measures, Pediatric, Provider perception",
author = "Pruette, {Cozumel S} and Coburn, {Shayna S.} and Eaton, {Cyd K.} and Brady, {Tammy McLoughlin} and Shamir Tuchman and Susan Mendley and Fivush, {Barbara A} and Michelle Eakin and Kristin Riekert",
year = "2018",
month = "1",
day = "1",
doi = "10.1007/s00467-018-4044-x",
language = "English (US)",
journal = "Pediatric Nephrology",
issn = "0931-041X",
publisher = "Springer Verlag",

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TY - JOUR

T1 - Does a multimethod approach improve identification of medication nonadherence in adolescents with chronic kidney disease?

AU - Pruette, Cozumel S

AU - Coburn, Shayna S.

AU - Eaton, Cyd K.

AU - Brady, Tammy McLoughlin

AU - Tuchman, Shamir

AU - Mendley, Susan

AU - Fivush, Barbara A

AU - Eakin, Michelle

AU - Riekert, Kristin

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Background: Medical provider assessment of nonadherence is known to be inaccurate. Researchers have suggested using a multimethod assessment approach; however, no study has demonstrated how to integrate different measures to improve accuracy. This study aimed to determine if using additional measures improves the accurate identification of nonadherence beyond provider assessment alone. Methods: Eighty-seven adolescents and young adults (AYAs), age 11–19 years, with chronic kidney disease (CKD) [stage 1–5/end-stage renal disease (ESRD)] and prescribed antihypertensive medication, their caregivers, and 17 medical providers participated in the multisite study. Five adherence measures were obtained: provider report, AYA report, caregiver report, electronic medication monitoring (MEMS), and pharmacy refill data [medication possession ratio (MPR)]. Concordance was calculated using kappa statistic. Sensitivity, specificity, positive predictive power, and negative predictive power were calculated using MEMS as the criterion for measuring adherence. Results: There was poor to fair concordance (kappas = 0.12–0.54), with 35–61% of AYAs classified as nonadherent depending on the measure. While both providers and MEMS classified 35% of the AYAs as nonadherent, sensitivity (0.57) and specificity (0.77) demonstrated poor agreement between the two measures on identifying which AYAs were nonadherent. Combining provider report of nonadherence and MPR < 75% resulted in the highest sensitivity for identifying nonadherence (0.90) and negative predictive power (0.88). Conclusions: Nonadherence is prevalent in AYAs with CKD. Providers inaccurately identify nonadherence, leading to missed opportunities to intervene. Our study demonstrates the benefit to utilizing a multimethod approach to identify nonadherence in patients with chronic disease, an essential first step to reduce nonadherence.

AB - Background: Medical provider assessment of nonadherence is known to be inaccurate. Researchers have suggested using a multimethod assessment approach; however, no study has demonstrated how to integrate different measures to improve accuracy. This study aimed to determine if using additional measures improves the accurate identification of nonadherence beyond provider assessment alone. Methods: Eighty-seven adolescents and young adults (AYAs), age 11–19 years, with chronic kidney disease (CKD) [stage 1–5/end-stage renal disease (ESRD)] and prescribed antihypertensive medication, their caregivers, and 17 medical providers participated in the multisite study. Five adherence measures were obtained: provider report, AYA report, caregiver report, electronic medication monitoring (MEMS), and pharmacy refill data [medication possession ratio (MPR)]. Concordance was calculated using kappa statistic. Sensitivity, specificity, positive predictive power, and negative predictive power were calculated using MEMS as the criterion for measuring adherence. Results: There was poor to fair concordance (kappas = 0.12–0.54), with 35–61% of AYAs classified as nonadherent depending on the measure. While both providers and MEMS classified 35% of the AYAs as nonadherent, sensitivity (0.57) and specificity (0.77) demonstrated poor agreement between the two measures on identifying which AYAs were nonadherent. Combining provider report of nonadherence and MPR < 75% resulted in the highest sensitivity for identifying nonadherence (0.90) and negative predictive power (0.88). Conclusions: Nonadherence is prevalent in AYAs with CKD. Providers inaccurately identify nonadherence, leading to missed opportunities to intervene. Our study demonstrates the benefit to utilizing a multimethod approach to identify nonadherence in patients with chronic disease, an essential first step to reduce nonadherence.

KW - Adherence

KW - Antihypertensive

KW - Concordance

KW - Measures

KW - Pediatric

KW - Provider perception

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