Automated Outreach to Increase Primary Adherence to Cholesterol-Lowering Medications

Derose, Stephen F.; Green, Kelley; Marrett, Elizabeth; Tunceli, Kaan; Cheetham, T. Craig; Chiu, Vicki; Harrison, Teresa N.; Reynolds, Kristi; Vansomphone, Southida S.; Scott, Ronald D.

doi:10.1001/2013.jamainternmed.717

Cited by 103 publications

(96 citation statements)

References 20 publications

(20 reference statements)

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“…The study most similar to this was recently performed in the Kaiser system by DeRose et al (2013) and did find a reduction in PMN with use of an automated telephone call and followup letter, although without the initial calls that preceded our intervention. 19 Of note, the PMN rate in the DeRose study was much higher than the rate observed in this study, which left potential for improvement that may not have been present for our intervention given the very low baseline PMN.…”

Section: Tablecontrasting

confidence: 53%

“…18 Studies in integrated health care systems have found lower rates of PMN (15%-17% for antihypertensives and antidiabetic medications), but the scope of the problem is substantial even in these settings. [19][20][21][22][23][24] • Primary medication nonadherence (PMN) occurs for 15%-30% of prescriptions, so that many patients never start taking medications prescribed to treat chronic diseases.…”

mentioning

confidence: 99%

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A Randomized Telephone Intervention Trial to Reduce Primary Medication Nonadherence

Fischer¹,

Jones²,

Wright³

et al. 2015

JMCP

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Section: Tablecontrasting

confidence: 53%

mentioning

confidence: 99%

A Randomized Telephone Intervention Trial to Reduce Primary Medication Nonadherence

Fischer¹,

Jones²,

Wright³

et al. 2015

JMCP

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“…13,14 Studies in closed health care systems have found slightly lower rates of PMN (15%-26%), although the problem is still substantial. [15][16][17] Once PMN can be identified and measured, the challenge is to identify interventions specifically targeting PMN. Systematic reviews of the adherence literature indicate that community pharmacists can play an important role.…”

Section: Resultsmentioning

confidence: 99%

Pharmacy-based Interventions to Reduce Primary Medication Nonadherence to Cardiovascular Medications

et al. 2014

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BACKGROUND: Primary medication nonadherence (PMN) occurs when patients do not fill new prescriptions. Interventions to reduce PMN have not been well described. OBJECTIVES: To determine whether 2 pharmacy-based interventions could decrease PMN. DESIGN: Two sequential interventions with a control group were evaluated after completion. The automated intervention began in 2007 and consisted of phone calls to patients on the third and seventh days after a prescription was processed but remained unpurchased. The live intervention began in 2009 and used calls from a pharmacist or technician to patients who still had not picked up their prescriptions after 8 days. SUBJECTS: Patients with newly prescribed cardiovascular medications received at CVS community pharmacies. Patients with randomly selected birthdays served as the control population. MEASURES: Patient abandonment of new prescription, defined as not picking up medications within 30 days of initial processing at the pharmacy. RESULTS: The automated intervention included 852,612 patients and 1.2 million prescriptions, with a control group of 9282 patients and 13,178 prescriptions. The live intervention included 121,155 patients and 139,502 prescriptions with a control group of 2976 patients and 3407 prescriptions. The groups were balanced by age, sex, and patterns of prior prescription use. For the automated intervention, 4.2% of prescriptions were abandoned in the intervention group and 4.5% in the control group (P>0.1), with no significant differences for any individual classes of medications. The live intervention was used in a group that had not purchased prescriptions after 8 days and thus had much higher PMN. In this setting 36.9% of prescriptions were abandoned in the intervention group and 41.7% in the control group, a difference of 4.8% (P<0.0001). The difference in abandoned prescriptions for antihypertensives was 6.9% (P<0.0001) but for antihyperlipidemics was only 1.4% (P>0.1). CONCLUSIONS: Automated reminder calls had no effect on PMN. Live calls from pharmacists decreased antihypertensive PMN significantly, although many patients still abandoned their prescriptions.

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“…57 Along with EMR, there may be other tools providers could use in efforts to improve patient adherence, including interactive voice recognition and automated personalized calls. 58 However, research has not yet demonstrated the relative effectiveness or cost-effectiveness of individualized, technology-based interventions compared with increased patient-provider communication.…”

Section: ■■ Discussion and Conclusionmentioning

confidence: 99%

Understanding and Overcoming Barriers to Medication Adherence: A Review of Research Priorities

Seabury

Gupta²,

Philipson³

et al. 2014

JMCP

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Automated Outreach to Increase Primary Adherence to Cholesterol-Lowering Medications

Cited by 103 publications

References 20 publications

A Randomized Telephone Intervention Trial to Reduce Primary Medication Nonadherence

A Randomized Telephone Intervention Trial to Reduce Primary Medication Nonadherence

Pharmacy-based Interventions to Reduce Primary Medication Nonadherence to Cardiovascular Medications

Understanding and Overcoming Barriers to Medication Adherence: A Review of Research Priorities

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