Health services research · 2021
Congruence of opioid prescriptions and dispensing using electronic records and claims data.
СтатьяНаблюдательное исследованиеНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Nataraj Nisha, Zhang Kun, Strahan Andrea E, Guy Gery P
Аннотация
OBJECTIVE: To quantify discrepancies between opioid prescribing and dispensing via the percentage of patients with Electronic Medical Record (EMR) prescriptions who subsequently filled the prescription within 90 days, defined as congruence, and compared opioid congruence with related medications.
DATA SOURCES: Deidentified data from the IBM MarketScan Explorys Claims-EMR Dataset.
STUDY DESIGN: In this retrospective, observational study, we examined congruence for commonly prescribed controlled substances-opioids, stimulants, and benzodiazepines. Congruence was stratified by age group and sex.
DATA COLLECTION/EXTRACTION METHODS: Continuously enrolled adults aged 18-64 years with an EMR encounter (excluding inpatient settings) and ≥ 1 prescription for selected classes between 1/1/2016 and 10/2/2017.
PRINCIPAL FINDINGS: During the study period, 1,353,478 adults had ≥1 EMR encounter. Patients with stimulants prescriptions had the highest congruence (83%) corresponding to 7151 claims for 8,635 EMR prescriptions, followed by opioids (66%; 62,766/95,690) and benzodiazepines (64%; 30,181/47,408). Chi-square testing showed congruence differed by age group within opioids (P < .0001) and benzodiazepines (P < .0001) and was higher among females within benzodiazepines (P < .0001).
CONCLUSIONS: These findings demonstrate that relying on claims data alone for opioid prescribing measures might underestimate actual prescribing magnitude by as much as one-third in these data. Combined EMR and claims data can help future research better understand characteristics associated with congruence or incongruence between prescribing and dispensing.
DATA SOURCES: Deidentified data from the IBM MarketScan Explorys Claims-EMR Dataset.
STUDY DESIGN: In this retrospective, observational study, we examined congruence for commonly prescribed controlled substances-opioids, stimulants, and benzodiazepines. Congruence was stratified by age group and sex.
DATA COLLECTION/EXTRACTION METHODS: Continuously enrolled adults aged 18-64 years with an EMR encounter (excluding inpatient settings) and ≥ 1 prescription for selected classes between 1/1/2016 and 10/2/2017.
PRINCIPAL FINDINGS: During the study period, 1,353,478 adults had ≥1 EMR encounter. Patients with stimulants prescriptions had the highest congruence (83%) corresponding to 7151 claims for 8,635 EMR prescriptions, followed by opioids (66%; 62,766/95,690) and benzodiazepines (64%; 30,181/47,408). Chi-square testing showed congruence differed by age group within opioids (P < .0001) and benzodiazepines (P < .0001) and was higher among females within benzodiazepines (P < .0001).
CONCLUSIONS: These findings demonstrate that relying on claims data alone for opioid prescribing measures might underestimate actual prescribing magnitude by as much as one-third in these data. Combined EMR and claims data can help future research better understand characteristics associated with congruence or incongruence between prescribing and dispensing.