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The American Journal of Managed Care December 2013
Implementing Effective Care Management in the Patient-Centered Medical Home
Catherine A. Taliani, BS; Patricia L. Bricker, MBA; Alan M. Adelman, MD, MS; Peter F. Cronholm, MD, MSCE, FAAFP; and Robert A. Gabbay, MD, PhD
Cost Utility of Hub-and-Spoke Telestroke Networks From Societal Perspective
Bart M. Demaerschalk, MD, MSc; Jeffrey A. Switzer, DO; Jipan Xie, MD, PhD; Liangyi Fan, BA; Kathleen F. Villa, MS; and Eric Q. Wu, PhD
Generic Initiation and Antidepressant Therapy Adherence Under Medicare Part D
Yuhua Bao, PhD; Andrew M. Ryan, PhD; Huibo Shao, MS; Harold Alan Pincus, MD; and Julie M. Donohue, PhD
Economics of Genomic Testing for Women With Breast Cancer
Robert D. Lieberthal, PhD
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Impact of Electronic Prescribing on Medication Use in Ambulatory Care
Ashley R. Bergeron, MPH; Jennifer R. Webb, MA; Marina Serper, MD; Alex D. Federman, MD, MPH; William H. Shrank, MD, MSHS; Allison L. Russell, BA; and Michael S. Wolf, PhD, MPH
Characteristics of Low-Severity Emergency Department Use Among CHIP Enrollees
Justin Blackburn, PhD; David J. Becker, PhD; Bisakha Sen, PhD; Michael A. Morrisey, PhD; Cathy Caldwell, MPH; and Nir Menachemi, PhD, MPH
Collection of Data on Race/Ethnicity and Language Proficiency of Providers
David R. Nerenz, PhD; Rita Carreón, BS; and German Veselovskiy, MS
Dietary Diversity Predicts Type of Medical Expenditure in Elders
Yuan-Ting Lo, PhD; Mark L. Wahlqvist, MD; Yu-Hung Chang, PhD; Senyeong Kao, PhD; and Meei-Shyuan Lee, DPH

Impact of Electronic Prescribing on Medication Use in Ambulatory Care

Ashley R. Bergeron, MPH; Jennifer R. Webb, MA; Marina Serper, MD; Alex D. Federman, MD, MPH; William H. Shrank, MD, MSHS; Allison L. Russell, BA; and Michael S. Wolf, PhD, MPH
Both potential benefits and unexpected consequences were found as a result of the rollout of electronic prescribing.
Objectives: To investigate differences before and after rollout of electronic prescribing (e-prescribing) in (1) patients’ primary adherence to newly prescribed medications, (2) patients' understanding of how to use their medications, and (3) multiple pharmacy use.

Study Design: Postvisit interviews and follow-up phone calls were done with 344 patients at an academic general internal medicine clinic.

Methods: Patient interviews and follow-up phone calls were done (1) before e-prescribing, (2) 1 to 6 months after e-prescribing, and (3) 12 to 18 months after e-prescribing.

Results: Overall, rates of abandoned prescriptions were 6.9% before e-prescribing, 10.6% 1 to 6 months after e-prescribing, and 2.5% 12 to 18 months after e-prescribing (P = .07). There was a reduction in awareness of the indication for a newly prescribed medicine among patients after e-prescribing (95.4%, 97.9%, and 89.8%, respectively; P = .03). There was a decrease in patients’ ability to demonstrate proper use of their new medicine after e-prescribing (69.0% before e-prescribing, 67.1% 1-6 months after e-prescribing, 51.9% 12 -18 months after e-prescribing; P = .02). There was an increasing trend in the percentage of patients using multiple pharmacies after e-prescribing was implemented.

Conclusions: We found both potential benefits and unexpected consequences as a result of the rollout of electronic prescribing. Adaptation to  e-prescribing might be improved with outreachand education, including explicitly informing patients of the change during the first months of rollout. Tangible prescription information for reminder purposes only may also be beneficial.

Am J Manag Care. 2013;19(12):1012-1017
Postvisit interviews and follow-up phone calls among 344 patients (recruited from an academic general internal medicine clinic) were conducted to determine if and when patients picked up their new prescription and their understanding of it.
  • Initially, rates of abandoned prescriptions increased after e-prescribing, but they later resolved to rates below baseline.

  • There were decreases in patients’ ability to demonstrate both proper use of and knowledge about their medication.

  • There was an increasing trend of multiple pharmacy use after implementation of eprescribing.

  • These results suggest the need for improved outreach and education during e-prescribing rollout.
Between 2009 and 2011, there was a 72% increase in electronic prescribing (e-prescribing), from 191 million to 326 million e-prescribed orders.1 From a quality and safety perspective, e-prescribing has been thought to have the potential to improve patient care by improving clinic efficiency, preventing medication errors, and even improving regimen adherence.2-8 Yet to date there is  limited evidence on the impact of e-prescribing on the patient experience in primary care, including adherence-related concerns.9-11

Despite the promise of e-prescribing to improve healthcare quality, a possible consequence could be primary nonadherence (ie,  e-prescriptions would actually negatively impact the timely retrieval and purchase of a new prescription). The hypothesis follows that despite the expedited order from prescriber to pharmacy, e-prescribing removes the known tangible reminder to fill a prescription by eliminating the paper prescription. Additionally, it is plausible that the nature of physicianpatient communication during a medical encounter on a newly prescribed medicine could change with greater efficiency, which may impact essential patient understanding of what a prescribed medicine is for (indication) and proper daily dosing. Beyond adherence concerns, the process of e-prescribing could lead to issues with medication reconciliation, as it requires patients to identify the pharmacy that they would like the order to be directed to; multiple pharmacies can be entered per patient (eg, pharmacy near work vs pharmacy closer to home). Multiple pharmacy use has been associated with lower compliance, higher risk of potentially dangerous or inappropriate drug combinations, and higher costs of pharmaceutical services.12-14

In 2009, our team was conducting baseline interviews as part of a clinical trial evaluating an electronic health record strategy to  promote safe, appropriate medication use. Six months later, the clinic implemented e-prescribing for the first time, allowing for a  natural experiment to take place. While it was not the original intention of the study, we identified a unique opportunity to leverage extensive data collection to explore several critical research questions. We were able to investigate differences before and up to 18 months after e-prescribing was implemented in the clinic in the following outcomes: (1) patients’ primary adherence to newly  prescribed medications as determined by rate of prescription abandonment (unfilled prescriptions) and delays in filling a prescription; (2) medication understanding  as determined by patient understanding of a new prescription medication’s indication and demonstrated proper use (number of pills per dose, times taken per day, total number of pills to be taken daily); and (3) multiple pharmacy use.


We conducted a cross-sectional evaluation examining the impact of e-prescribing implementation within 1 primary care clinic, with 3 waves of patient interviews. Specifically, 1 baseline assessment was conducted during the 6 months prior to the implementation of e-prescribing (before e-prescribing), and 2 posttest assessments were performed, the first during the 6 months after implementation of e-prescribing (e-prescribing interval 1) and the second 12 to 18 months after implementation of eprescribing (e-prescribing interval 2). 


Adult patients (N = 344) receiving care at 1 academic general internal medicine ambulatory care clinic were recruited between September 2009 and March 2011. Three cohorts of patients were recruited: 144 patients before e-prescribing, 127 patients during the first 6 months after e-prescribing, and 73 patients 12 to 18 months after e-prescribing implementation. Individuals were eligible if they (1) were 18 years  or older, (2) were established patients at the clinic, (3) had an appointment with their physician on the day of recruitment, and (4) received a new order for a prescription medication during their visit. Patients receiving only orders for refills (ie, no orders for a new prescription medication) were not eligible to participate, nor was anyone with a moderate to severe visual, hearing, or cognitive impairment as determined by clinical staff or the interviewer at the time of recruitment. If patients received both an order for a refill and an order for a new prescription, they were eligible to participate. Patients were also ineligible if they had participated in an earlier interview wave for this study. The Northwestern University Institutional Review Board approved the study prior to its initiation.


Trained research interviewers working with clinic physicians and staff identified eligible patients upon their medical encounter at discharge. Specifically, clerical staff provided patients at check-in and discharge with a flyer that described the study in some detail as well as eligibility requirements. Staff directed interested patients to the available research staff who were waiting on site. Those who consented to participate then completed a brief, interviewer-assisted survey that included a literacy assessment. Interviewers notified patients they would receive  a follow-up phone call with additional questions about their prescription, such as if and when they filled the medication and how they were taking it.


Patients provided information regarding age, sex, marital status, race, education, income, type of insurance, number of medications currently prescribed, and number of comorbid conditions. Each patient also completed the Rapid Estimate of Adult Literacy in Medicine to assess literacy. The encounter discharge summary was reviewed to obtain the name, dose, and frequency information for the newly prescribed medication. Follow-up phone interviews occurred from as early as 6 days to as long as 2 weeks after the initial interview. During these follow-up phone interviews, appropriate medication knowledge (indication, side effects) and proper use (number of pills, number of times per day, time of day) were assessed. Additionally, patients were asked if they had filled their prescription, and if not, the reason for not obtaining the medication and the number of pharmacies used.

Statistical Analyses

Data were analyzed using SAS version 9.2 (SAS Institute Inc, Cary, North Carolina). Descriptive statistics were calculated for each variable. Chi-square tests were used to evaluate the association between sociodemographic characteristics and e-prescribing period according to the time point that patients were recruited into the study (before e-prescribing [n = 144], e-prescribing interval 1 [n = 123], or e-prescribing interval 2 [n = 73]). Differences in primary adherence and multiple pharmacy use were also examined using the x2 test, with significance set at P <.05. Differences in medication knowledge (indication and proper use) by eprescribing period were examined as an additional exploratory outcome.


Table 1 presents the sociodemographic characteristics of subjects stratified by e-prescribing period. A total of 428 new medications were prescribed among the 344 patients. Specifiimplemented (29.9% in e-prescribing interval 1 and 26.0% in e-prescribing interval 2 vs 13.2% before e-prescribing; P = .003). Patients recruited after implementation of e-prescribing were more likely to have limited literacy (P = .05). While not statistically significant, more patients in e-prescribing interval 2 had 3 or more chronic conditions compared with the 2 other time frames (37.0% e-prescribing interval 2, 33.9% e-prescribing interval 1, and 24.3% before   e-prescribing; P = .12). More patients recruited before e-prescribing had private health insurance (76.4% before e-prescribing, 62.2% during e-prescribing interval 1, 66.7% during e-prescribing interval 2; P = . 09) and lower numbers of total prescription  medications compared with patients recruited after the implementation of e-prescribing (P = .41).

Overall rates of primary nonadherence varied between recruitment periods (Table 2). Nonadherence rates as measured by abandoned prescriptions were 6.9% before e-prescribing, 10.6% during e-prescribing interval 1, and 2.5% during eprescribing interval 2 (P = . 07). Patient-reported reasons for primary nonadherence included the medication being too expensive or a lack of prescription insurance coverage (20.7%), opting for an over-the-counter medication instead (17.3%), stating that they wanted to wait to see if they felt better (24.2%), and concerns about side effects (3.4%), as well as miscellaneous other concerns (34.4%) such as not liking samples given to them or not wanting to be on too many medications. Nonsignificant trends in delays in filling a prescription were also noted between periods, with 12.3% of patients delaying their time to fill a prescription before e-prescribingcompared with 8.5% during e-prescribing interval 1 and 6.4% during e-prescribing interval 2 (P = .28).

Medications were classified into 5 categories: cardiovascular medications (20.1%), antibiotics (16.8%), analgesics/sedative hypnotics (14.5%), over-the-counter medications such as those for colds/allergies (12.2%), and “other” medications (36.4%). The other category included prescriptions that had too small a number to be included in a separate category (<5% of prescriptions). This category included antidepressants, hormones, anticonvulsants, and muscularskeletal, antimalarial, gastrointestinal, diabetic, respiratory, triptan, eye and ear, and dermatology medications. There were minor differences in medication category by e-prescribing period, as there were slightly fewer over-thecounter medications prescribed and slightly more analgesic/sedative hypnotics in e-prescribing interval 2. Prescriptions were also classified as acute or chronic medications. There were no differences in acute versus chronic medications by e-prescribing period (36.4% were chronic medications before e-prescribing, 30.0% during e-prescribing interval 1, and 41.3% during e-prescribing interval 2; P = .19). No differences in adherence rates were found by medication type or by chronic versus acute.

An increasing but nonsignificant trend was noted in the percentage of patients using multiple pharmacies after e-prescribing was implemented (20.0% before e-prescribing, 26.5% during e-prescribing interval 1, and 30.1% during e-prescribing interval 2; P = . 23). Interestingly, among patients with adequate literacy skills, rates of prescription abandonment did not change from before e-prescribing to e-prescribing interval 1, but decreased approximately 50% by e-prescribing interval  2 (8.7% vs 8.9% vs 3.1%). Among patients with limited literacy skills, 0% of prescriptions were abandoned before eprescribing, but 14.6% of prescriptions were abandoned during e-prescribing interval 1. The prescription abandonment rate returned to 0% during e-prescribing interval 2. No other trends were found by literacy or age group.

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