Adoption and Use of Stand-Alone Electronic Prescribing in a Health Plan–Sponsored Initiative

Published Online: March 09, 2010
Joshua M. Pevnick, MD, MSHS; Steven M. Asch, MD, MPH; John L. Adams, PhD; Soeren Mattke, MD, DSc; Mihir H. Patel, PharmD; Susan L. Ettner, PhD; and Douglas S. Bell, MD, PhD

Objectives: To quantify rates of stand-alone e-prescribing (SEP) adoption and use among primary care physicians (PCPs) participating in a SEP initiative and to determine which physician and patient characteristics were associated with higher rates of each.


Study Design: Using records from an insurer-led SEP initiative, we compared the characteristics of 297 PCPs who adopted SEP through the initiative with the characteristics of 1892 eligible PCPs who did not. Among 297 adopters, we studied the extent of SEP use.


Methods: Dependent variables included each physician’s adoption of SEP and his or her e-prescribing use ratio (the ratio of electronic prescriptions to pharmacy claims in the same period). Independent variables included characteristics of PCPs (specialty, practice size, and prescribing volume) and their patients (patient age, sex, race/ethnicity, and household income).


Results: Solo practitioners, pediatricians, and physicians with more patients from predominantly African American zip codes were underrepresented among SEP adopters. The mean (SD) e-prescribing use ratio among adopters was 0.23 (0.28). Twenty percent of physicians maintained e-prescribing use ratios above 0.50. Available physician characteristics explained little of the variance in use, but physicians in smaller practices had greater use (P = .02).


Conclusions: Certain categories of physicians may need more tailored incentives to adopt SEP. On average, adopters used the SEP system for only about one-quarter of their prescriptions. Some adopters achieved high levels of SEP use, and further research is needed to elucidate the factors that enabled this.


(Am J Manag Care. 2010;16(3):182-189)

e-Prescribing is seen as a critical technology for improving medication use.


  • In a health plan–sponsored e-prescribing initiative, the mean e-prescribing rate of participating primary care physicians (PCPs) was 1 prescription per 4 pharmacy claims, but some PCPs achieved high use.
  • Given this low use, future initiatives may need to consider more resources to increase e-prescribing use.
  • Efforts should be made to ensure that all patient demographics benefit from e-prescribing.
  • Higher e-prescribing use among physicians in smaller practices suggests that e-prescribing may be an appropriate manner of extending health information technology to these physicians, who traditionally are reluctant users of such technology.
There is evidence that in some settings health information technology (HIT) can improve patient outcomes and reduce healthcare costs.1 Most of this evidence comes from 4 healthcare organizations at which academic physicians and employees are usually required to use homegrown electronic medical records (EMRs).2-5 However, few physicians practice in these types of environments. More than 75% of physicians practice in groups of 5 or fewer.6 Unfortunately, the structure of these small community private practices is not conducive to providing the financial and time investment necessary for EMR adoption.7,8 As a result, only 9% to 14% of these practices have adopted EMRs compared with 23% to 50% of larger practices.9

Stand-alone e-prescribing (SEP) has been proposed as a possible method of transitioning community physicians toward EMR functionality without the initial investments required for a full EMR system.10,11 Indeed, recent legislation promises to increase Medicare reimbursement for e-prescribing physicians in the short term and to decrease Medicare reimbursement for paper prescribers in the long term.12

We are aware of only 1 prior study that evaluates adoption and use of commercial SEP systems by community physicians. Fischer et al13 examined use and adoption of the PocketScript system, which was offered without cost to high-volume outpatient prescribers in Massachusetts. A striking finding of their analysis was the low use of e-prescribing, which (although increasing throughout the period studied) was less than 30% of all eligible prescriptions 1 year after adoption. The authors cite anecdotal evidence of increased e-prescribing since that period but present data only through early 2005.

To further characterize experiences with SEP from other states using another e-prescribing system and in a more recent period, we quantified the rates of e-prescribing adoption and use that occurred when Horizon Blue Cross Blue Shield of New Jersey (Horizon BCBSNJ) offered SEP to community physicians participating in their health maintenance organization (HMO) and preferred provider organization network. Our primary study objectives were to quantify rates of SEP adoption and use and to determine which physician and patient characteristics were associated with higher rates of each.


Setting and Intervention

Horizon BCBSNJ, New Jersey’s largest health insurer, provides coverage for 3.2 million members. In late 2004, Horizon BCBSNJ launched an initiative offering its physicians Caremark’s iScribe SEP software (Caremark is Horizon BCBSNJ’s pharmacy benefits manager). The program installed SEP systems for individual physicians rather than for practices as a whole. All features of the program, including the target population, recruitment, and incentives provided, were determined by Horizon BCBSNJ for purposes of improving care delivery. Our analysis of physicians’ SEP adoption and use was subsequently designed to use secondary data from the program and from other sources.

Of approximately 14,250 physicians in the Horizon BCBSNJ provider network, about 5890 were eligible for the program based on prescribing activity that resulted in at least 500 Horizon BCBSNJ pharmacy claims annually (this cutoff was determined by Horizon BCBSNJ for purposes of program feasibility). Eighty-seven percent of these eligible physicians were in practices containing 5 or fewer physicians. An initial wave of recruitment focused on the highest-volume prescribers (>2500 filled prescriptions per year), and subsequent phases targeted incrementally lower-volume prescribers. By the time the allocated resources were expended, 4457 physicians had received the e-prescribing offer (Figure 1).

Study Population and Dependent Variable for Physician Adoption Analysis

We retrospectively constructed 2 cohorts, one of physicians who adopted the offered SEP system and another of physicians who did not. Physician adoption was then used as the dependent variable in our adoption analysis. Physicians were also characterized based on their specialty, practice size, prior Horizon BCBSNJ pharmacy claims volume, and assigned primary care patient panel. Horizon BCBSNJ ensured that all patients in their HMO and point-of-service insurance plans had an assigned primary care physician (PCP), whereas all patients with other Horizon BCBSNJ insurance plans did not. To focus our analysis on PCPs, physicians without any assigned Horizon BCBSNJ primary care patients were excluded from the analysis. However, physicians with few Horizon BCBSNJ–assigned primary care patients were included in the analysis, with the expectation that they probably also provided primary care to many non–managed care patients insured by Horizon BCBSNJ.

Dependent Variable for e-Prescribing Use Analysis

The second major goal of our project was to study physician use of SEP among adopters. We calculated an “e-prescribing use ratio” (range, 0-1) by dividing the number of SEP prescriptions the physician wrote for Horizon BCBSNJ patients by the number of Horizon BCBSNJ pharmacy claims attributable to the physician during the same quarter. Each physician’s ratio was calculated for each quarter of the e-prescribing use evaluation period (January 1, 2006, to June 30, 2006). Because pharmacy claims may be generated for prescriptions written before a given quarter, it was possible for a PCP’s ratio to exceed 1; this occurred in particular when total prescription denominators were low. Therefore, all eprescribing use ratios were capped at 1 for the analysis. The ratio numerator included all prescriptions generated through the SEP system whether printed or electronically transmitted. Because we wanted to understand physician behavior rather than patient behavior, electronic renewals (physician behavior) were counted in the ratio numerator, and renewal claims were counted in the ratio denominator. Refills (patient behavior) of existing prescriptions were excluded from the ratio numerator and denominator.

After all PCPs were assigned e-prescribing use ratios, some physicians were also classified as “never having used” the system if records did not show any electronic prescriptions after the day of activation (when test prescriptions were often transmitted). Other PCPs were classified as having “quit e-prescribing” if they had initially used the system but later stopped synchronizing their personal digital assistant and sending any electronic prescriptions by the last quarter of the use evaluation period.

Independent Variables for PCP Characteristics and Patient Panel Data

Caremark provided physician specialty and practice size information, which was available only in previously determined groupings (1, 2-5, 6-10, and >10 physicians). Each physician’s total pharmacy claims volume was provided by Horizon BCBSNJ for 2003 (the calendar year before the start of program recruitment) in categories (0-250, 251-500, etc), which we aggregated into approximate “high,” “medium,” and “low” tercile categories. Physicians were categorized as low-volume prescribers (<1750 Horizon BCBSNJ pharmacy claims in 2003, which represented the 35th percentile), mid-volume prescribers, and high-volume prescribers (>3500 Horizon BCBSNJ pharmacy claims in 2003, which represented the 71st percentile).

We used zip codes to estimate the racial/ethnic makeup of the neighborhoods from which the PCPs’ patients were drawn. First, patients living in zip codes with more than 50% African American residents (per 2000 US Census data) were categorized as living in majority African American neighborhoods; those from zip codes with more than 40% Hispanic residents were categorized as living in Hispanic plurality neighborhoods. An analysis of the studied zip codes showed that these predominantly African American and Hispanic neighborhood categorizations were mutually exclusive more than 99% of the time. The PCPs were then categorized based on having at least 10% of their patients living in majority African American and Hispanic plurality neighborhoods (which represented the 80th and 87th percentiles, respectively).

Statistical Analysis

Our analysis consisted of 2 components. In the first component (SEP adoption analysis), we compared the physician characteristics of adopting PCPs versus control PCPs using t test, χ2 test, and multivariate logistic regression. The second component measured use among adopting PCPs via a 2-part model. The first part was a logistic regression model in which the dependent variable was “never having used” or “quit e-prescribing” (as already described) versus having some evidence of e-prescribing use into the last quarter of the observation period. The objective was to identify factors that predispose physicians to stop e-prescribing. The second part was a multivariate linear regression model that examined the association between physician characteristics and extent of SEP use among the subsample of physicians who had started e-prescribing and did not quit. We excluded “never having used” and “quit eprescribing” physicians to examine ongoing use barriers among those physicians who continued to try to use SEP.

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