The Effects of Cost Sharing on Adherence to Medications Prescribed for Concurrent Use: Do Definitions Matter?

Sacks, Naomi; Burgess, James; Cabral, Howard; McDonnell, Marie E.; Pizer, Steven D.

doi:10.18553/jmcp.2015.21.8.678

Cited by 6 publications

(8 citation statements)

References 38 publications

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“… 45 – 48 Particularly, we believe that PDC is more appropriate in the SMI context than alternative measures such as medical possession ratio as it captures discontinuation as non-adherence. While typically used in the literature for serious mental illnesses and other conditions, 46 – 51 to our best knowledge, this threshold is arbitrary and lacks validation for patients with serious mental illness. Moreover, as any claims-based measure, PDC may overestimate adherence as patients may fill prescriptions they do not actually ingest.…”

Section: Discussionmentioning

confidence: 99%

Does knowledge of patient non-compliance change prescribing behavior in the real world? A claims-based analysis of patients with serious mental illness

Shafrin¹,

Bognar²,

Everson³

et al. 2018

CEOR

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BackgroundNew digital technologies offer providers the promise of more accurately tracking patients’ medication adherence. It is unclear, however, whether access to such information will affect provider treatment decisions in the real world.MethodsUsing prescriber-reported information on patient non-compliance from health insurance claims data between 2008 and 2014, we examined whether prescribers’ knowledge of non-compliance was associated with different prescribing patterns for patients with serious mental illness (SMI). We examined patients who initiated an oral atypical antipsychotic, but were later objectively non-adherent to this treatment, defined as proportion of days covered (PDC) <0.8. We examined how a physician’s awareness of patient non-compliance (ICD-9 diagnosis code: V15.81) was correlated with the physician’s real-world treatment decisions for that patient. Treatment decisions studied included the share of patients who increased antipsychotic dose, augmented treatment, switched their antipsychotic, or used a long-acting injectable (LAI).ResultsAmong the 286,249 patients with SMI who initiated an antipsychotic and had PDC <0.8, 4,033 (1.4%) had documented non-compliance. When prescribers documented non-compliance, patients were more likely to be switched to another antipsychotic (32.8% vs 24.7%, P<0.001), have their dose increased (24.4% vs 22.1%, P=0.004), or receive an LAI (0.09% vs 0.04%, P=0.008), but were less likely to have augmented therapy with another antipsychotic (1.1% vs 1.3%, P=0.035) than patients without documented non-compliance.ConclusionAmong SMI patients with documented non-compliance, the frequency of dose, medication switches, and LAI use were higher and augmentation was lower compared to patients without documented non-compliance. Access to adherence information may help prescribers more rapidly switch ineffective medications as well as avoid unnecessary medication augmentation.

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Section: Discussionmentioning

confidence: 99%

Does knowledge of patient non-compliance change prescribing behavior in the real world? A claims-based analysis of patients with serious mental illness

Shafrin¹,

Bognar²,

Everson³

et al. 2018

CEOR

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“…A few studies have examined specific proximal factors associated with NAA discontinuance, such as medication experience, 4 type of NAA prescribed, 14 presence of hypoglycemic events, [14][15] refill gaps, 5,6 hemoglobin A1c measures, 16 distribution channel, 17 and medication cost. 5,6,18 But to date, no comprehensive study has assessed how dynamic factors combine to explain NAA discontinuance, particularly for long-term discontinuers. As a result, clinicians are ill equipped to diagnose triggers for discontinuance and thus miss potentially important intervention opportunities.…”

Section: Methodsmentioning

confidence: 99%

Proximal Predictors of Long-Term Discontinuance with Noninsulin Antihyperglycemic Agents

Stuart

Shen

Quinn

et al. 2016

JMCP

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This study was funded by Merck & Co. Huang and Raipathak are employees of Merck & Co. Brandt reports consultancy and speaker fees from Catapult, Omnicare, RAND, HRSA, CMS, and AGS Beers Criteria. Loh is currently employed at Touro College of Pharmacy. All other authors have no relevant potential conflicts of interest to disclose. Study concept and design were primarily contributed by Stuart, Quinn, and Brandt, along with Shen, Roberto, Hendrick, Huang, and Rajpathak. Shen, Loh, Hendrick, and Kim collected the data, and data interpretation was performed primarily by Stuart, Shen, and Roberto, assisted by Quinn, Brandt, Hendrick, Huang, and Rajpathak. The manuscript was written primarily by Stuart, with assistance from the other authors, and revised by Huang, Rajpathak, and Stuart, with assistance from the other authors.

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“…Half of the studies (n 5 18) used the interval-based approach [6,10,14,17e19,21,23, 24,27,28,30e36], whereas 16 studies used the prescription-based approach [11e13, 16,20,22,25,26,29, 37e43] and two studies used both the interval-and prescription-based approach [7,15]. Of the 18 studies using the interval-based approach, only six studies took medication switching into account [6,10,14,18,33,36].…”

Section: Multiple Medications Adherence Measuresmentioning

confidence: 99%

“…First, measuring adherence to ''all medications'': Four studies assessed adherence to each medication separately and defined patients as being adherent when they had collected at least 80% of each, that is, ''all medications'' [6,7,14,22]. All four studies assessed adherence to medication at class level, considering individual drugs within the same medication class as interchangeable, and then calculated adherence to multiple classes at therapeutic level, either for oral glucose-lowering [6,7,14] or blood pressure-lowering medication [22].…”

Section: Multiple Medications Adherence Measuresmentioning

confidence: 99%

“…Third, measuring adherence to ''any medication'': Twelve studies assessed adherence from number of days with at least one medication available and defined patients as being adherent when they had collected at least 80% of one, that is, ''any medication'' [6,7,14,15,18,22e24, 28,33,35,38]. Also the studies using this measure first assessed adherence for medication at class level and then calculated adherence to multiple medication classes at therapeutic level for glucose-lowering [6,7,14,18,33,38], blood pressure-lowering [15,18,22e24,28,35], or lipid-lowering medication [18,28]. Two of these studies validated the proposed measure by assessing its association with clinical outcomes.…”

Section: Multiple Medications Adherence Measuresmentioning

confidence: 99%

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A systematic review finds inconsistency in the measures used to estimate adherence and persistence to multiple cardiometabolic medications

Alfian

Pradipta

Denig

2019

Journal of Clinical Epidemiology

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Objectives: We reviewed measures used to estimate adherence and persistence to multiple cardiometabolic medications from prescription data, particularly for blood pressure-lowering, lipid-lowering, and/or glucose-lowering medication, and give guidance on which measures to choose. Study Design and Setting: A literature search of Medline, Embase, and PsycINFO databases was conducted to identify studies assessing medication adherence and/or persistence for patients using multiple cardiometabolic medications. Two reviewers performed the study selection process independently. Results: From the 54 studies assessing adherence, only 36 (67%) clearly described the measures used. Five measures for adherence were identified, including adherence to ''all,'' to ''any,'' to ''both'' medication, ''average adherence,'' and ''highest/lowest adherence". From the 22 studies assessing persistence, only six (27%) clearly described the measures used. Three measures for persistence were identified, including persistence with ''all,'' with ''both,'' and with ''any'' medication. Less than half of the studies explicitly considered medication switches when relevant. Conclusion: From the identified measures, the ''any medication'' measure is most suitable for identifying patients in need of an intervention, whereas the ''all medication'' measure is useful for assessing the effect of interventions. More attention is needed for adequate measurement definitions when reporting on and interpreting adherence or persistence estimates to multiple medications.

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The Effects of Cost Sharing on Adherence to Medications Prescribed for Concurrent Use: Do Definitions Matter?

Cited by 6 publications

References 38 publications

Does knowledge of patient non-compliance change prescribing behavior in the real world? A claims-based analysis of patients with serious mental illness

Does knowledge of patient non-compliance change prescribing behavior in the real world? A claims-based analysis of patients with serious mental illness

Proximal Predictors of Long-Term Discontinuance with Noninsulin Antihyperglycemic Agents

A systematic review finds inconsistency in the measures used to estimate adherence and persistence to multiple cardiometabolic medications

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