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Lapa ME, Swabe GM, Magnani JW. Association of Depression and Adherence to Oral Anticoagulation in Patients With Atrial Fibrillation. J Am Heart Assoc 2023; 12:e031281. [PMID: 37982265 PMCID: PMC10727299 DOI: 10.1161/jaha.123.031281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 10/25/2023] [Indexed: 11/21/2023]
Abstract
BACKGROUND Adherence to oral anticoagulation is essential for stroke prevention in atrial fibrillation (AF). Depression has been associated with decreased adherence to medications in multiple disease states and in AF is further associated with increased risk of stroke. We hypothesized that individuals with depression and AF have decreased adherence to anticoagulation than those without depression. METHODS AND RESULTS We used administrative claims data to identify individuals with AF initiating anticoagulation with direct-acting oral anticoagulants (DOACs) or warfarin between 2013 and 2019. We quantified adherence using proportion of days covered, categorized as limited (proportion of days covered, <80%), adequate (proportion of days covered, ≥80% to <90%), or optimal (proportion of days covered, ≥90%). We related depression to 12-month adherence to anticoagulation in logistic regression models, adjusting for demographics, medical and psychiatric comorbidities, household income, educational attainment, and insurance type. As a secondary analysis, we determined the association of depression to adherence for each DOAC agent. We identified 101 041 individuals (aged 74.5±8.9 years; 50.6% women; 29.5% race or ethnicity other than White, including Asian or Black race and Hispanic ethnicity) who initiated either DOACs or warfarin. The odds of adequate adherence to DOACs was 11% (95% CI, 0.85-0.93), and the odds of optimal adherence was 12% (95% CI, 0.83-0.91) less in individuals with depression than those without. Depression was not associated with adherence to warfarin. CONCLUSIONS We identified an association between depression and decreased adherence to DOACs but not warfarin in individuals with AF. Recognizing depression in AF may guide interventions to improve anticoagulation adherence and reduce stroke risk.
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Affiliation(s)
| | | | - Jared W. Magnani
- Department of MedicineUniversity of PittsburghPittsburghPA
- Center for Research on Health Care, Department of MedicineUniversity of PittsburghPittsburghUSA
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Lapa ME, Swabe GM, Rollman BL, Muldoon MF, Thurston RC, Magnani JW. Assessment of Depression and Adherence to Guideline-Directed Medical Therapies Following Percutaneous Coronary Intervention. JAMA Netw Open 2022; 5:e2246317. [PMID: 36508214 PMCID: PMC9856464 DOI: 10.1001/jamanetworkopen.2022.46317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
IMPORTANCE Depression is associated with increased risk of primary and secondary cardiovascular events. Medication adherence may play an essential role. OBJECTIVE To evaluate the association of depression and 12-month adherence to guideline-directed medical therapies (eg, antiplatelet agents, β-blockers, renin-angiotensin-aldosterone system inhibitors [ie, angiotensin-converting enzyme inhibitors and angiotensin receptor blockers], and statins) following percutaneous coronary intervention. DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study included individuals who underwent percutaneous coronary intervention from January 1, 2014, to December 31, 2019. Data were collected from a large US health claims database and analyzed between February and August 2022. MAIN OUTCOMES AND MEASURES Proportion of days covered (PDC) for classes of guideline-directed medical therapies, with 12-month adherence categorized as adequate (PDC ≥80% to <90%) or optimal (PDC ≥90%). Multivariable-adjusted regression models were used to evaluate the association of depression with adherence; models incorporated demographic characteristics, comorbid medical and psychiatric conditions, depression treatment, and guideline-directed medical therapy treatment adjustment. The hypothesis was that those with depression would have lower odds of either adequate or optimal adherence to agents essential for guideline-directed medical therapy. RESULTS Of 124 443 individuals (mean [SD] age, 69.3 [10.6] years; 41 430 [33.3%] female sex; 3694 [3.0%] Asian, 12 611 [10.1%] Black, and 12 337 [9.9%] Hispanic individuals) who received percutaneous coronary interventions, 20 711 (16.6%) had a diagnosis of depression. Those with depression were significantly less likely to obtain adequate 12-month adherence to antiplatelets (odds ratio [OR], 0.80; 95% CI, 0.77-0.85), β-blockers (OR, 0.84; 95% CI, 0.80-0.88), and statins (OR, 0.88; 95% CI, 0.85-0.93) than those without depression; there was no association between depression and adherence to renin-angiotensin-aldosterone system inhibitors (OR, 0.93; 95% CI, 0.85-1.00). Those with depression had similarly decreased likelihood of optimal 12-month adherence to antiplatelets, β-blockers, and statins as well as renin-angiotensin-aldosterone system inhibitors (OR, 0.87; 95% CI, 0.82-0.94). CONCLUSIONS AND RELEVANCE In this cohort study, patients with depression were less likely to achieve adequate or optimal adherence to medications essential to guideline-directed medical therapies following percutaneous coronary intervention compared with those without depression. Recognition of depression may facilitate targeted interventions to address medication adherence and thereby improve secondary cardiovascular disease prevention.
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Affiliation(s)
- Matthew E. Lapa
- University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Gretchen M. Swabe
- University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Bruce L. Rollman
- Center for Behavioral Health and Smart Technology, Division of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | | | - Rebecca C. Thurston
- University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
- Department of Epidemiology, Graduate School of Public Health University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jared W. Magnani
- University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
- Center for Research on Health Care, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
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Dalli LL, Kilkenny MF, Arnet I, Sanfilippo FM, Cummings DM, Kapral MK, Kim J, Cameron J, Yap KY, Greenland M, Cadilhac DA. Towards better reporting of the Proportion of Days Covered method in cardiovascular medication adherence: A scoping review and new tool TEN-SPIDERS. Br J Clin Pharmacol 2022; 88:4427-4442. [PMID: 35524398 PMCID: PMC9546055 DOI: 10.1111/bcp.15391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 04/29/2022] [Accepted: 05/03/2022] [Indexed: 11/27/2022] Open
Abstract
Although medication adherence is commonly measured in electronic datasets using the proportion of days covered (PDC), no standardized approach is used to calculate and report this measure. We conducted a scoping review to understand the approaches taken to calculate and report the PDC for cardiovascular medicines to develop improved guidance for researchers using this measure. After prespecifying methods in a registered protocol, we searched Ovid Medline, Embase, Scopus, CINAHL Plus and grey literature (1 July 2012 to 14 December 2020) for articles containing the terms “proportion of days covered” and “cardiovascular medicine”, or synonyms and subject headings. Of the 523 articles identified, 316 were reviewed in full and 76 were included (93% observational studies; 47% from the USA; 2 grey literature articles). In 45 articles (59%), the PDC was measured from the first dispensing/claim date. Good adherence was defined as 80% PDC in 61 articles, 56% of which contained a rationale for selecting this threshold. The following parameters, important for deriving the PDC, were often not reported/unclear: switching (53%), early refills (45%), in‐hospital supplies (45%), presupply (28%) and survival (7%). Of the 46 articles where dosing information was unavailable, 59% reported how doses were imputed. To improve the transparent and systematic reporting of the PDC, we propose the TEN‐SPIDERS tool, covering the following PDC parameters: Threshold, Eligibility criteria, Numerator and denominator, Survival, Presupply, In‐hospital supplies, Dosing, Early Refills, and Switching. Use of this tool will standardize reporting of the PDC to facilitate reliable comparisons of medication adherence estimates between studies.
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Affiliation(s)
- Lachlan L Dalli
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Victoria, Australia
| | - Monique F Kilkenny
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Victoria, Australia.,Stroke Division, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Victoria, Australia
| | - Isabelle Arnet
- Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland
| | - Frank M Sanfilippo
- School of Population and Global Health, The University of Western Australia, Western Australia, Australia
| | - Doyle M Cummings
- Department of Family Medicine, Brody School of Medicine, East Carolina University, Greenville, North Carolina, USA.,Centre for Health Disparities, East Carolina University, Greenville, North Carolina, USA
| | - Moira K Kapral
- ICES, Toronto, Canada.,Division of General Internal Medicine, Department of Medicine, University of Toronto, Canada.,Institute of Health Policy, Management, and Evaluation, University of Toronto, Canada
| | - Joosup Kim
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Victoria, Australia.,Stroke Division, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Victoria, Australia
| | - Jan Cameron
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Victoria, Australia.,School of Nursing and Midwifery, Monash University, Victoria, Australia.,Australian Centre for Heart Health, Victoria, Australia
| | - Kevin Y Yap
- Department of Pharmacy, Singapore General Hospital, Singapore.,School of Psychology and Public Health, La Trobe University, Victoria, Australia
| | - Melanie Greenland
- Oxford Vaccine Group, Department of Paediatrics, Centre for Clinical Vaccinology and Tropical Medicine, Churchill Hospital, Oxford, UK.,Nuffield Department of Population Health, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Dominique A Cadilhac
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Victoria, Australia.,Stroke Division, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Victoria, Australia
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Arnet I, Greenland M, Knuiman MW, Rankin JM, Hung J, Nedkoff L, Briffa TG, Sanfilippo FM. Operationalization and validation of a novel method to calculate adherence to polypharmacy with refill data from the Australian pharmaceutical benefits scheme (PBS) database. Clin Epidemiol 2018; 10:1181-1194. [PMID: 30233252 PMCID: PMC6132235 DOI: 10.2147/clep.s153496] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Background Electronic health care data contain rich information on medicine use from which adherence can be estimated. Various measures developed with medication claims data called for transparency of the equations used, predominantly because they may overestimate adherence, and even more when used with multiple medications. We aimed to operationalize a novel calculation of adherence with polypharmacy, the daily polypharmacy possession ratio (DPPR), and validate it against the common measure of adherence, the medication possession ratio (MPR) and a modified version (MPRm). Methods We used linked health data from the Australian Pharmaceutical Benefits Scheme and Western Australian hospital morbidity dataset and mortality register. We identified a strict study cohort from 16,185 patients aged ≥65 years hospitalized for myocardial infarction in 2003–2008 in Western Australia as an illustrative example. We applied iterative exclusion criteria to standardize the dispensing histories according to previous literature. A SAS program was developed to calculate the adherence measures accounting for various drug parameters. Results The study cohort was 348 incident patients (mean age 74.6±6.8 years; 69% male) with an admission for myocardial infarction who had cardiovascular medications over a median of 727 days (range 74 to 3,798 days) prior to readmission. There were statins (96.8%), angiotensin converting enzyme inhibitors (88.8%), beta-blockers (85.6%), and angiotensin receptor blockers (13.2%) dispensed. As expected, observed adherence values were higher with mean MPR (median 89.2%; Q1: 73.3%; Q3: 104.6%) than mean MPRm (median 82.8%; Q1: 68.5%; Q3: 95.9%). DPPR values were the most narrow (median 83.8%; Q1: 70.9%; Q3: 96.4%). Mean MPR and DPPR yielded very close possession values for 37.9% of the patients. Values were similar in patients with longer observation windows. When the traditional threshold of 80% was applied to mean MPR and DPPR values to signify the threshold for good adherence, 11.6% of patients were classified as good adherers with the mean MPR relative to the DPPR. Conclusion In the absence of transparent and standardized equations to calculate adherence to polypharmacy from refill databases, the novel DPPR algorithm represents a valid and robust method to estimate medication possession for multi-medication regimens.
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Affiliation(s)
- Isabelle Arnet
- Department of Pharmaceutical Sciences, Pharmaceutical Care Research Group, University of Basel, Basel, Switzerland
| | - Melanie Greenland
- School of Population and Global Health, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, WA, Australia,
| | - Matthew W Knuiman
- School of Population and Global Health, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, WA, Australia,
| | - Jamie M Rankin
- Cardiology Department, Fiona Stanley Hospital Murdoch, WA, Australia
| | - Joe Hung
- School of Medicine, Sir Charles Gairdner Hospital Unit, The University of Western Australia, Perth, WA, Australia
| | - Lee Nedkoff
- School of Population and Global Health, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, WA, Australia,
| | - Tom G Briffa
- School of Population and Global Health, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, WA, Australia,
| | - Frank M Sanfilippo
- School of Population and Global Health, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, WA, Australia,
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