Validation of EHR medication fill data obtained through electronic linkage with pharmacies

Blecker, Saul; Adhikari, Samrachana; Zhang, Hanchao; Dodson, John A.; Desai, Sunita; Anzisi, Lisa; Pazand, Lily; Schoenthaler, Antoinette; Mann, Devin

doi:10.18553/jmcp.2021.27.10.1482

Cited by 16 publications

(26 citation statements)

References 19 publications

(22 reference statements)

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“… 4 Pharmacy fill data, particularly PDC, are considered to be the most practical and inexpensive technique and are suitable for use in large population studies. 19 However, PDC may not be readily available for the general practitioner, whereas CAT is used increasingly in clinical practice. Pharmacy fill records may not reflect adherence adequately if prescription data are not captured from all potential sources or patients do not take the dispensed medications.…”

Section: Discussionmentioning

confidence: 99%

“…Accordingly, a recent analysis showed that pharmacy fill data available in the electronic heath record overestimated adherence when compared with insurance claims data. 19 CAT is another technique increasingly used in the United States and many other countries to assess medication adherence as it is easy to obtain and highly sensitive. 10 , 11 However, white coat adherence (taking the pills only when tested) may occur if patients are aware of the tests, which limits accuracy of biochemical adherence testing as the gold standard test.…”

Section: Discussionmentioning

confidence: 99%

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Comparison of Pharmacy Refill Data With Chemical Adherence Testing in Assessing Medication Nonadherence in a Safety Net Hospital Setting

Osula

Schesing

et al. 2022

JAHA

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Background Pharmacy fill data are a practical tool for assessing medication nonadherence. However, previous studies have not compared the accuracy of pharmacy fill data to measurement of plasma drug levels, or chemical adherence testing (CAT). Methods and Results We performed a cross‐sectional study in patients with uncontrolled hypertension in outpatient clinics in a safety net health system. Plasma samples were obtained for measurement of common cardiovascular drugs, including calcium channel blockers, thiazide diuretics, beta blockers, angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers, and statins, using liquid chromatography mass spectrometry. Proportion of days covered (PDC), a method for tracking pharmacy fill data, was calculated via linkages with Surescripts, and its diagnostic test characteristics were compared with CAT. Among 77 patients with uncontrolled hypertension, 13 (17%) were nonadherent to at least 1 antihypertensive drug and 23 (37%) were nonadherent to statins by CAT. PDC was significantly lower in the nonadherent versus the adherent group by CAT only among patients prescribed an angiotensin‐converting enzyme inhibitor/angiotensin receptor blocker or statin (all P <0.05) but not in patients prescribed other drug classes. The sensitivity and specificity of PDC in detecting nonadherence to angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers and statin drugs by CAT were 75% to 82% and 56% to 79%, respectively. The positive predictive value of PDC in detecting nonadherence was only 11% to 27% for antihypertensive drugs and 45% for statins. Conclusions PDC is useful in detecting nonadherence to angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers and statins but has limited usefulness in detecting nonadherence to calcium channel blockers, beta blockers, or thiazide diuretics and has a low positive predictive value for all drug classes.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Comparison of Pharmacy Refill Data With Chemical Adherence Testing in Assessing Medication Nonadherence in a Safety Net Hospital Setting

Osula

Schesing

et al. 2022

JAHA

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“…The health system’s EHR provided demographic information, laboratory test results, weight, blood pressure, and health care use. Prescription drug orders were recorded, and whether they were dispensed at major pharmacy chains was observed using Surescripts . For patients enrolled in the health system’s insurance plan, paid claims were available.…”

Section: Methodsmentioning

confidence: 99%

“…Prescription drug orders were recorded, and whether they were dispensed at major pharmacy chains was observed using Surescripts. 33 For patients enrolled in the health system's insurance plan, paid claims were available.…”

Section: Datamentioning

confidence: 99%

Effect of an Intensive Food-as-Medicine Program on Health and Health Care Use

Doyle,

Alsan,

Skelley

et al. 2024

JAMA Intern Med

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ImportanceFood-as-medicine programs are becoming increasingly common, and rigorous evidence is needed regarding their effects on health.ObjectiveTo test whether an intensive food-as-medicine program for patients with diabetes and food insecurity improves glycemic control and affects health care use.Design, Setting, and ParticipantsThis stratified randomized clinical trial using a wait list design was conducted from April 19, 2019, to September 16, 2022, with patients followed up for 1 year. Patients were randomly assigned to either participate in the program immediately (treatment group) or 6 months later (control group). The trial took place at 2 sites, 1 rural and 1 urban, of a large, integrated health system in the mid-Atlantic region of the US. Eligibility required a diagnosis of type 2 diabetes, a hemoglobin A1c (HbA1c) level of 8% or higher, food insecurity, and residence within the service area of the participating clinics.InterventionThe comprehensive program provided healthy groceries for 10 meals per week for an entire household, plus dietitian consultations, nurse evaluations, health coaching, and diabetes education. The program duration was typically 1 year.Main Outcomes and MeasuresThe primary outcome was HbA1c level at 6 months. Secondary outcomes included other biometric measures, health care use, and self-reported diet and healthy behaviors, at both 6 months and 12 months.ResultsOf 3712 patients assessed for eligibility, 3168 were contacted, 1064 were deemed eligible, 500 consented to participate and were randomized, and 465 (mean [SD] age, 54.6 [11.8] years; 255 [54.8%] female) completed the study. Of those patients, 349 (mean [SD] age, 55.4 [11.2] years; 187 [53.6%] female) had laboratory test results at 6 months after enrollment. Both the treatment (n = 170) and control (n = 179) groups experienced a substantial decline in HbA1c levels at 6 months, resulting in a nonsignificant, between-group adjusted mean difference in HbA1c levels of −0.10 (95% CI, −0.46 to 0.25; P = .57). Access to the program increased preventive health care, including more mean (SD) dietitian visits (2.7 [1.8] vs 0.6 [1.3] visits in the treatment and control groups, respectively), patients with active prescription drug orders for metformin (134 [58.26] vs 119 [50.64]) and glucagon-like peptide 1 medications (114 [49.56] vs 83 [35.32]), and participants reporting an improved diet from 1 year earlier (153 of 164 [93.3%] vs 132 of 171 [77.2%]).Conclusions and RelevanceIn this randomized clinical trial, an intensive food-as-medicine program increased engagement with preventive health care but did not improve glycemic control compared with usual care among adult participants. Programs targeted to individuals with elevated biomarkers require a control group to demonstrate effectiveness to account for improvements that occur without the intervention. Additional research is needed to design food-as-medicine programs that improve health.Trial RegistrationClinicalTrials.gov Identifier: NCT03718832

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“…Two data sources were used to compute PDC: (1) pharmacy fill information (Surescripts) and (2) prescription information (EHR). As previously described by our group, this EHR-linked data set was comprehensive and contained more prescription fill information than insurance claims data. PDC was measured over 6 months from time of prescription order and averaged across GDMT categories if more than 1 GDMT was prescribed, as previously described .…”

Section: Methodsmentioning

confidence: 99%

Neighborhood-Level Socioeconomic Status and Prescription Fill Patterns Among Patients With Heart Failure

Mukhopadhyay,

Blecker,

et al. 2023

JAMA Netw Open

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ImportanceMedication nonadherence is common among patients with heart failure with reduced ejection fraction (HFrEF) and can lead to increased hospitalization and mortality. Patients living in socioeconomically disadvantaged areas may be at greater risk for medication nonadherence due to barriers such as lower access to transportation or pharmacies.ObjectiveTo examine the association between neighborhood-level socioeconomic status (nSES) and medication nonadherence among patients with HFrEF and to assess the mediating roles of access to transportation, walkability, and pharmacy density.Design, Setting, and ParticipantsThis retrospective cohort study was conducted between June 30, 2020, and December 31, 2021, at a large health system based primarily in New York City and surrounding areas. Adult patients with a diagnosis of HF, reduced EF on echocardiogram, and a prescription of at least 1 guideline-directed medical therapy (GDMT) for HFrEF were included.ExposurePatient addresses were geocoded, and nSES was calculated using the Agency for Healthcare Research and Quality SES index, which combines census-tract level measures of poverty, rent burden, unemployment, crowding, home value, and education, with higher values indicating higher nSES.Main Outcomes and MeasuresMedication nonadherence was obtained through linkage of health record prescription data with pharmacy fill data and was defined as proportion of days covered (PDC) of less than 80% over 6 months, averaged across GDMT medications.ResultsAmong 6247 patients, the mean (SD) age was 73 (14) years, and majority were male (4340 [69.5%]). There were 1011 (16.2%) Black participants, 735 (11.8%) Hispanic/Latinx participants, and 3929 (62.9%) White participants. Patients in lower nSES areas had higher rates of nonadherence, ranging from 51.7% in the lowest quartile (731 of 1086 participants) to 40.0% in the highest quartile (563 of 1086 participants) (P &lt; .001). In adjusted analysis, patients living in the lower 2 nSES quartiles had significantly higher odds of nonadherence when compared with patients living in the highest nSES quartile (quartile 1: odds ratio [OR], 1.57 [95% CI, 1.35-1.83]; quartile 2: OR, 1.35 [95% CI, 1.16-1.56]). No mediation by access to transportation and pharmacy density was found, but a small amount of mediation by neighborhood walkability was observed.Conclusions and RelevanceIn this retrospective cohort study of patients with HFrEF, living in a lower nSES area was associated with higher rates of GDMT nonadherence. These findings highlight the importance of considering neighborhood-level disparities when developing approaches to improve medication adherence.

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Validation of EHR medication fill data obtained through electronic linkage with pharmacies

Abstract: BACKGROUND: Recent linkages between electronic health records (EHRs) and pharmacy data hold opportunity for up-to-date assessment of medication adherence at the point of care.

Cited by 16 publications

References 19 publications

Comparison of Pharmacy Refill Data With Chemical Adherence Testing in Assessing Medication Nonadherence in a Safety Net Hospital Setting

Comparison of Pharmacy Refill Data With Chemical Adherence Testing in Assessing Medication Nonadherence in a Safety Net Hospital Setting

Effect of an Intensive Food-as-Medicine Program on Health and Health Care Use

Neighborhood-Level Socioeconomic Status and Prescription Fill Patterns Among Patients With Heart Failure

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