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

doi:10.1093/jamia/ocy095

Cited by 12 publications

(6 citation statements)

References 32 publications

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“…Furthermore, not all countries have a unique patient identifier, resulting in the use of demographic data such as gender, year of birth, and postcode, to identify entries belonging to the same person [ 46 ]. Regardless, we find other studies have reported similar levels of inconsistency between features in matched records, such as brand name, dose strength, and time between prescribing and dispensing [ 44 , 47 ]. We also observed the substantial increase in matches when variables were cleaned, and recoded, and our probabilistic methodology was used in the place of a simple pseudo-deterministic matching.…”

Section: Discussionsupporting

confidence: 45%

“…In Appendix D , we see that 3% of matches had distinct and non-missing medication brand names. This highlights that potentially brand substitutions occurring at the pharmacy need to be accounted for in the matching [ 44 ]. The variable with the biggest change in distribution between the candidate links and the final matches was whether the medication was dispensed within one month of prescribing – 33% of candidates and 99% of matches (see Fig.…”

Section: Discussionmentioning

confidence: 99%

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Linkage of primary care prescribing records and pharmacy dispensing Records in the Salford Lung Study: application in asthma

Tibble

Lay-Flurrie

Sheikh

et al. 2020

BMC Med Res Methodol

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Background Records of medication prescriptions can be used in conjunction with pharmacy dispensing records to investigate the incidence of adherence, which is defined as observing the treatment plans agreed between a patient and their clinician. Using prescribing records alone fails to identify primary non-adherence; medications not being collected from the dispensary. Using dispensing records alone means that cases of conditions that resolve and/or treatments that are discontinued will be unaccounted for. While using a linked prescribing and dispensing dataset to measure medication non-adherence is optimal, this linkage is not routinely conducted. Furthermore, without a unique common event identifier, linkage between these two datasets is not straightforward. Methods We undertook a secondary analysis of the Salford Lung Study dataset. A novel probabilistic record linkage methodology was developed matching asthma medication pharmacy dispensing records and primary care prescribing records, using semantic (meaning) and syntactic (structure) harmonization, domain knowledge integration, and natural language feature extraction. Cox survival analysis was conducted to assess factors associated with the time to medication dispensing after the prescription was written. Finally, we used a simplified record linkage algorithm in which only identical records were matched, for a naïve benchmarking to compare against the results of our proposed methodology. Results We matched 83% of pharmacy dispensing records to primary care prescribing records. Missing data were prevalent in the dispensing records which were not matched – approximately 60% for both medication strength and quantity. A naïve benchmarking approach, requiring perfect matching, identified one-quarter as many matching prescribing records as our methodology. Factors associated with delay (or failure) to collect the prescribed medication from a pharmacy included season, quantity of medication prescribed, previous dispensing history and class of medication. Our findings indicate that over 30% of prescriptions issued were not collected from a dispensary (primary non-adherence). Conclusions We have developed a probabilistic record linkage methodology matching a large percentage of pharmacy dispensing records with primary care prescribing records for asthma medications. This will allow researchers to link datasets in order to extract information about asthma medication non-adherence.

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Section: Discussionsupporting

confidence: 45%

Section: Discussionmentioning

confidence: 99%

Linkage of primary care prescribing records and pharmacy dispensing Records in the Salford Lung Study: application in asthma

Tibble

Lay-Flurrie

Sheikh

et al. 2020

BMC Med Res Methodol

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“…While on the School of Dentistry EHR roadmap, electronic prescribing did not exist at the time of this study. Another approach could be the use by both entities of a drug vocabulary supported by RxNorm (Hoopes et al 2018). A further improvement would be the implementation of data exchange standards to facilitate the rapid and consistent transfer of clinical information electronically, such as HL7 FHIR (Health Level 7 Fast Healthcare Interoperability Resources) Release 4, which has seen significant adoption in recent years (Evans 2016).…”

Section: Discussionmentioning

confidence: 99%

Agreement in Medications Reported in Medical and Dental Electronic Health Records

Tenuta

Canady

Eber

et al. 2021

JDR Clinical & Translational Research

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Introduction: The historical separation between medicine and dentistry has resulted in the creation of separate health records, which have the potential to negatively impact patient care and safety. Of particular importance, errors or omissions in medication lists in separate electronic health records (EHRs) may lead to medical errors and serious adverse outcomes. Objective: This study aimed to compare medication lists reported in the EHRs of active patients treated by both the University of Michigan School of Dentistry and Michigan Medicine to determine if differences exist. Methods: In this cohort study, EHRs of a population of 159,733 patients that the University of Michigan medical and dental clinics share in common were investigated for agreement in the reporting of 16 medications. After exclusion of minors and patients not seen in the last 5 y, records of 27,277 patients were examined. Results: The maximum percentage of agreement in medications reported in both records was 52% for levothyroxine, and the minimum was 7% for sildenafil. The medical record had a significantly higher number of unique medications than the dental record, suggesting higher underreporting in the dental setting. Conclusion: The lack of agreement in the report of medications with serious dental and medical implications argues in favor of unification of records and use of available technology to increase accurate medication reporting. Knowledge Transfer Statement: The results demonstrate a lack of agreement between medications reported in medical and dental records, which can have serious implications to patients’ health. A unified health record, employing available technology to increase accurate medication reporting, would mitigate this problem.

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“…We then used the prescriber's unique identifier to subset the sample to new patient opioid use episodes that could be linked to a corresponding medical claim (considered to be the prescribing visit) in the 14 days prior to filling the prescription (Hoopes et al 2018). The prescribing appointment must have taken place in the primary care office setting, which we identified using the Centers for Medicare and Medicaid Services (CMS) service location code and the prescriber's specialty as reported in NPPES.…”

Section: Sample Selectionmentioning

confidence: 99%

Curbing the Opioid Epidemic at Its Root: The Effect of Provider Discordance After Opioid Initiation

et al. 2022

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Although medical research has addressed the clinical management of chronic opioid users, little is known about how operational interventions shortly after opioid initiation can impact a patient’s likelihood of long-term opioid use. Using a nationwide U.S. database of medical and pharmaceutical claims, we investigate the care delivery process at the most common entry point to opioid use: the primary care setting. For patients who return to primary care for a follow-up appointment within 30 days of opioid initiation, we ask who should revisit and potentially revise the opioid-based treatment plan: the initial prescriber (provider concordance) or an alternate clinician (provider discordance)? First, using a fully controlled logistic model, we find that provider discordance reduces the likelihood of long-term opioid use 12 months after opioid initiation by 31% (95% Confidence Interval: [18%, 43%]). Both the instrumental variable analysis technique and propensity-score matching (utilizing the minimum-bias estimator approach) account for omitted variable bias and indicate that this is a conservative estimate of the true causal effect. Second, looking at patient activities immediately after the follow-up appointment, we find that this long-term reduction is at least partially explained by an immediate reduction in opioids prescribed after the follow-up appointment. Third, the data suggest that the benefit associated with provider discordance remains significant regardless of whether the patient’s initial prescriber was their regular primary care provider or another clinician. Overall, our analysis indicates that systematic, operational changes in the early stages of managing new opioid patients may offer a promising, and hitherto overlooked, opportunity to curb the opioid epidemic. This paper was accepted by David Simchi-Levi, healthcare management.

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

Abstract: 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.

Cited by 12 publications

References 32 publications

Linkage of primary care prescribing records and pharmacy dispensing Records in the Salford Lung Study: application in asthma

Linkage of primary care prescribing records and pharmacy dispensing Records in the Salford Lung Study: application in asthma

Agreement in Medications Reported in Medical and Dental Electronic Health Records

Curbing the Opioid Epidemic at Its Root: The Effect of Provider Discordance After Opioid Initiation

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