Table 3.

Primary Studies on the Use of Narrative Electronic Prescribing Instructions (NEPIs) to Assess Drug Exposure

Author (Year)	Data Source and Setting	Objective	Major Findings: Application of NEPI
Goud (2019)	EHR, Cedars-Sinai Medical Center in Los Angeles California, US	To demonstrate the feasibility of using prescription instructions to determine units/day for calculating Sig-morphine milligram equivalent daily dose	NLP was used determine the maximum units per day
Marcum (2019)	EHR, Sutter Health of Northern California, US	To compare adherence and changes in LDL among statin users prescribed evening versus daily dosing	Manual coding of statin dosing as evening or daily
Sullivan (2020)	EHR, Kaiser Permanente Washington, US	To determine if opioid taper plans are associated with opioid dose reductions	NLP was used to identify opioid taper plans
Wolf (2020)	Pharmacy dispensing data, Walgreens pharmacies nationwide, US	To examine use of Universal Medication Schedule (UMS) prescribing and determine whether it was associated with higher rates of medication adherence	Manual coding of prescriptions as UMS or non-UMS
Wong (2017)	Electronic prescribing data from primary care practices, Quebec, Canada,	To examine the prevalence of off-label indications for antidepressants	Manual coding of prescriptions as on-label or off-label

EHR, Electronic Health Records; LDL, low-density lipoprotein cholesterol; NLP, natural language processing; Sig, signatura; SQL, structured query language; US, United States,