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Patchwork of contrasting medication cultures across the USA.

ABSTRACT: Health in the United States is markedly heterogeneous, with large disparities in disease incidence, treatment choices and health spending. Drug prescription is one major component of health care-reflecting the accuracy of diagnosis, the adherence to evidence-based guidelines, susceptibility to drug marketing and regulatory factors. Using medical claims data covering nearly half of the USA population, we have developed and validated a framework to compare prescription rates of 600 popular drugs in 2334 counties. Our approach uncovers geographically separated sub-Americas, where patients receive treatment for different diseases, and where physicians choose different drugs for the same disease. The geographical variation suggests influences of racial composition, state-level health care laws and wealth. Some regions consistently prefer more expensive drugs, even when they have not been proven more efficacious than cheaper alternatives. Our study underlines the benefit of aggregating massive information on medical practice into a summarized and actionable form.

SUBMITTER: Melamed RD

PROVIDER: S-EPMC6177425 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Patchwork of contrasting medication cultures across the USA.

Melamed Rachel D RD Rzhetsky Andrey A

Nature communications 20181009 1

Health in the United States is markedly heterogeneous, with large disparities in disease incidence, treatment choices and health spending. Drug prescription is one major component of health care-reflecting the accuracy of diagnosis, the adherence to evidence-based guidelines, susceptibility to drug marketing and regulatory factors. Using medical claims data covering nearly half of the USA population, we have developed and validated a framework to compare prescription rates of 600 popular drugs i ...[more]

PMID: 30301884

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Project description:IntroductionMedication organizations across the USA have adopted electronic health records, and one of the most anticipated benefits of these was improved medication safety, but alert fatigue has been a major issue.ObjectiveWe compared the appropriateness of medication-related clinical decision support alerts triggered by two commercial applications: EPIC and Seegnal's platform.MethodsThis was a retrospective comparison of two commercial applications. We provided Seegnal with deidentified inpatient, outpatient, and inpatient genetic electronic medical record (EMR)-extracted datasets for 657, 2731, and 413 patients, respectively. Seegnal then provided the alerts that would have triggered, which we compared with those triggered by EPIC in clinical care. A random sample of the alerts triggered were reviewed for appropriateness, and the positive predictive value (PPV) and negative predictive value (NPV) were calculated. We also reviewed all the inpatient and outpatient charts for patients within our cohort who were receiving ten or more concomitant medications with alerts we found to be appropriate to assess whether any adverse events had occurred and whether Seegnal's platform could have prevented them.ResultsResults from EPIC and the Seegnal platform were compared based on alert load, PPV, NPV, and potential adverse events. Overall, compared with EPIC, the Seegnal platform triggered fewer alerts in the inpatient (1697 vs. 27,540), outpatient (2341 vs. 35,134), and inpatient genetic (1493 vs. 20,975) cohorts. The Seegnal platform had higher specificity in the inpatient (99 vs. 0.3%; p < 0.0001), outpatient (99 vs. 0.3%; p < 0.0001), and inpatient genetic (97.9 vs. 1.2%; p < 0.0001) groups and higher sensitivity in the inpatient (100 vs. 68.8%; p < 0.0001) and outpatient (88.6 vs.78.3%; p < 0.0001) groups but not in the inpatient genetic cohort (81 vs. 78.5%; p = 0.11). We identified 16 adverse events that occurred in the inpatient setting, 11 (69%) of which potentially could have been prevented with the Seegnal platform.ConclusionsOverall, the Seegnal platform triggered 94% fewer alerts than EPIC in the inpatient setting and 93% fewer in the outpatient setting, with much higher sensitivity and specificity. This application could substantially reduce alert fatigue and improve medication safety at the same time.

Project description:This cross-sectional study aimed to describe the association between medication experiences and beliefs and self-reported medication adherence in patients with chronic diseases in two different samples from two different societies: the USA and the Sultanate of Oman. The Morisky Medication Adherence Score (MMAS-8) questionnaire was used to measure medication adherence. Three items (statements) were used for measuring medication experiences and beliefs variable on a four-point Likert scale adapted from the 2015 National Consumer Survey of the Medication Experience and Pharmacists' Role (NCSME&PR). In the U.S., quantitative secondary data analysis of 13,731 participants was conducted using the 2015 NCSME&PR, a self-administered online survey coordinated by Qualtrics Panels between 28 April 2015 and 22 June 2015. The same variables were translated into Arabic, with studies conducted at the Royal Court Medical Center in Oman, and data from 714 participants were collected between 16 June 2019 and 16 August 2019. Data were analyzed using IMB/SPSS version 24.0 software. Chi-square analysis and descriptive statistics were used. The results showed that the low adherence rates for medication (MMAS-8 < 6) were 56% and 52% in Omani and U.S. groups, respectively. Approximately 90% of the U.S. and Omani participants believed that "medicines are a life-saver"; however, medication adherence was higher in Oman (30%) than in the United States (9%) for these participants. In total, 60% of the U.S. and 29% of Omani participants believed that "medicines are a burden"; however, about 60-65% of participants in both countries were in the low medication adherence group. Additionally, 63% of the U.S. and 83% of the Omani participants disagreed that "medicines do more harm than good"; however, medication adherence in the U.S. (15%) was higher than in Oman (8%). In conclusion, a decrease in low medication adherence was observed with positive medication experiences and beliefs. However, the impacts of medication experiences and beliefs on low medication adherence rates were different from one population to another. The "medication burden" statement resulted in the highest percentage of difference in terms of low medication adherence rates between those who agree and those who disagree in the U.S. group (20%), whereas the "medicines are a life-saver" statement resulted in a greater difference in the Omani group (30%). Proper communication between patients and healthcare providers based on the patient's medication experiences and beliefs will substantially improve medication adherence.

Dataset Information

Patchwork of contrasting medication cultures across the USA.

Publications

Patchwork of contrasting medication cultures across the USA.

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