Development of an algorithm to link electronic health record prescriptions with pharmacy dispense claims

Megan Hoopes, Heather Angier, Lewis A. Raynor, Andrew Suchocki, John Muench, Miguel Marino, Pedro Rivera, Nathalie Huguet

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Objective Medication adherence is an important aspect of chronic disease management. Electronic health record (EHR) data are often not linked to dispensing data, limiting clinicians' understanding of which of their patients fill their medications, and how to tailor care appropriately. We aimed to develop an algorithm to link EHR prescribing to claims-based dispensing data and use the results to quantify how often patients with diabetes filled prescribed chronic disease medications. Materials and Methods We developed an algorithm linking EHR prescribing data (RxNorm terminology) to claims-based dispensing data (NDC terminology), within sample of adult (19-64) community health center (CHC) patients with diabetes from a network of CHCs across 12 states. We demonstrate an application of the method by calculating dispense rates for a set of commonly prescribed diabetes and cardio-protective medications. To further inform clinical care, we computed adjusted odds ratios of dispense by patient-, encounter-, and clinic-level characteristics. Results Seventy-six percent of cardio-protective medication prescriptions and 74% of diabetes medications were linked to a dispensing record. Age, income, ethnicity, insurance, assigned primary care provider, comorbidity, time on EHR, and clinic size were significantly associated with odds of dispensing. Discussion EHR prescriptions and pharmacy dispense data can be linked at the record level across different terminologies. Dispensing rates in this low-income population with diabetes were similar to other populations. Conclusion Record linkage resulted in the finding that CHC patients with diabetes largely had their chronic disease medications dispensed. Understanding factors associated with dispensing rates highlight barriers and opportunities for optimal disease management.

Original languageEnglish (US)
Pages (from-to)1322-1330
Number of pages9
JournalJournal of the American Medical Informatics Association
Volume25
Issue number10
DOIs
StatePublished - Oct 1 2018

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Electronic Health Records
Prescriptions
Terminology
Community Health Centers
Chronic Disease
Disease Management
RxNorm
Medication Adherence
Poverty
Insurance
Comorbidity
Primary Health Care
Odds Ratio
Population

Keywords

  • diabetes
  • electronic health records
  • linkage algorithm
  • medication adherence
  • pharmacy claims

ASJC Scopus subject areas

  • Health Informatics

Cite this

Development of an algorithm to link electronic health record prescriptions with pharmacy dispense claims. / Hoopes, Megan; Angier, Heather; Raynor, Lewis A.; Suchocki, Andrew; Muench, John; Marino, Miguel; Rivera, Pedro; Huguet, Nathalie.

In: Journal of the American Medical Informatics Association, Vol. 25, No. 10, 01.10.2018, p. 1322-1330.

Research output: Contribution to journalArticle

Hoopes, Megan ; Angier, Heather ; Raynor, Lewis A. ; Suchocki, Andrew ; Muench, John ; Marino, Miguel ; Rivera, Pedro ; Huguet, Nathalie. / Development of an algorithm to link electronic health record prescriptions with pharmacy dispense claims. In: Journal of the American Medical Informatics Association. 2018 ; Vol. 25, No. 10. pp. 1322-1330.
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abstract = "Objective Medication adherence is an important aspect of chronic disease management. Electronic health record (EHR) data are often not linked to dispensing data, limiting clinicians' understanding of which of their patients fill their medications, and how to tailor care appropriately. We aimed to develop an algorithm to link EHR prescribing to claims-based dispensing data and use the results to quantify how often patients with diabetes filled prescribed chronic disease medications. Materials and Methods We developed an algorithm linking EHR prescribing data (RxNorm terminology) to claims-based dispensing data (NDC terminology), within sample of adult (19-64) community health center (CHC) patients with diabetes from a network of CHCs across 12 states. We demonstrate an application of the method by calculating dispense rates for a set of commonly prescribed diabetes and cardio-protective medications. To further inform clinical care, we computed adjusted odds ratios of dispense by patient-, encounter-, and clinic-level characteristics. Results Seventy-six percent of cardio-protective medication prescriptions and 74{\%} of diabetes medications were linked to a dispensing record. Age, income, ethnicity, insurance, assigned primary care provider, comorbidity, time on EHR, and clinic size were significantly associated with odds of dispensing. Discussion EHR prescriptions and pharmacy dispense data can be linked at the record level across different terminologies. Dispensing rates in this low-income population with diabetes were similar to other populations. Conclusion Record linkage resulted in the finding that CHC patients with diabetes largely had their chronic disease medications dispensed. Understanding factors associated with dispensing rates highlight barriers and opportunities for optimal disease management.",
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