Sarah J. Billups, PharmD

The purpose of this study was to identify and describe patient rationales for filling prescriptions at an out-of-plan pharmacy (OOPP).

A cross-sectional survey conducted in February 2013 among a random sample of 1000 patients.

Adult Kaiser Permanente Colorado (KPCO) patients who had a prescription electronically issued to an OOPP in November 2012 were surveyed. The study questionnaire was developed using items obtained from the literature and prepared de novo, as needed. The questionnaire included items regarding whether the electronic prescription issued to an OOPP was filled; if filled, which OOPP was used; factors that may have influenced the use of an OOPP; and the patient’s ability to afford medications. Responses to the survey were tabulated and reported as percentages.

The survey response rate was 38%. Respondents (N = 382) had a mean age of 61 years, 35% were males, and anti-hypertensives were their most common OOPP prescription. Overall, 330 (86%) respondents reported that they had their prescription filled at an OOPP. The most commonly reported OOPPs utilized were supermarket pharmacies (42%). Factors that influenced the decision to use an OOPP included the prescription being less expensive (58%), the OOPP had a discount generic prescription program (57%), and the OOPP’s location was convenient (44%). Thirty-nine percent of respondents reported that using an OOPP helped them afford their prescriptions.

Prescription cost and pharmacy convenience were identified as the most significant drivers of OOPP use. Future research should be conducted to assess the health-related consequences of OOPP use.

		The rate of prescriptions electronically issued to out-of-plan pharmacies (OOPPs) has risen considerably, but factors driving OOPP use are largely unknown.

		A random sample of patients who had a prescription electronically issued to an OOPP were surveyed.

		The most common factors reported that influenced the decision to use an OOPP included that the prescription was less expensive at the OOPP (58%), the OOPP had a discount generic prescription program (57%), and the OOPP’s location was convenient (44%).

		Out-of-plan pharmacy use may result in less expensive medications and increased convenience for patients; however, the risks to patients of using an OOPP are unclear.

Health plans, whether they are managed care organizations, accountable care organizations, or other types of care networks, often require their members to utilize in-plan pharmacies to receive subsidized prescription medications. Filling all prescriptions at the same pharmacy has been shown to decrease the risk for potentially harmful drug combinations.

 Plan members may also fill prescriptions at unsubsidized prices at out-of-plan pharmacies (OOPP).

 However, seeking prescription medications from multiple pharmacies, sometimes called “pharmacy shopping,” may contribute to medication-related problems, such as an increased risk for adverse drug interactions.

 The term “pharmacy shopping” suggests that this behavior is motivated by the goal of identifying the lowest medication cost. While actual patient-reported reasons for this OOPP use have not been well studied,

 some evidence does support medication cost as a factor. Discount generic prescription programs (DGPs) were introduced at several large chain pharmacies in 2006 and offer very lowcost generic prescription medications.

 Accordingly, the rate of prescriptions electronically issued to OOPPs has risen considerably since the introduction of DGPs.

 The influence of other factors driving OOPP use (eg, convenience, customer service, pharmacy loyalty) are largely unknown.

Information regarding the rationale for OOPP use is necessary in order to identify opportunities to improve patient safety, healthcare quality, and potentially member satisfaction. The objectives of this study were to describe if and where prescriptions electronically issued to an OOPP were filled, and the rationales for OOPP use among patients of an integrated health system with in-plan pharmacies.

This was a cross-sectional survey conducted in February 2013 among a random sample of 1000 patients from Kaiser Permanente Colorado (KPCO) who had a prescription electronically issued to an OOPP in November 2012. Kaiser Permanente Colorado is a group model, not-forprofit, integrated health system with more than 500,000 members in the Denver/Boulder metropolitan area that uses an electronic medical record (EMR) (Epic Clarity, Madison, WI) with e-prescribing capabilities. The e-prescribing system allows for the identification of whether a prescription was electronically issued for an in-plan pharmacy or OOPP. Data for this study were obtained from queries of the KPCO integrated, electronic administrative databases; the EMR; and a 12-item questionnaire mailed to the random sample of patients. This study was sponsored by the KPCO Pharmacy Department and all aspects were reviewed and approved by the KPCO Institutional Review Board prior to data collection.

Patients were eligible for inclusion in the survey if: (1) they were 18 years or older as of November 1, 2012; (2) they had a prescription electronically issued to an OOPP between November 1, 2012, and November 30, 2012; (3) their prescription was not for an over-the-counter, injectable, or infused medication or medical supply; (4) they had continuous KPCO membership for the 180 days prior to the prescription being electronically issued; (5) they were not residing in a skilled nursing facility at the time of the prescription; and (6) they were alive as of January 20, 2013.

A total of 12,827 prescriptions for 7841 patients were electronically issued for an OOPP in November 2012. Of these, 7531 (58.7%) prescriptions for 4177 (53.3%) patients were eligible for the survey. A random sample of 1000 eligible patients and their first eligible prescription electronically issued to an OOPP in the study month (heretofore termed the index prescription) was generated for the survey mailing.

The primary outcome was the group of patient-reported factors that influenced the use of an OOPP. Secondary outcomes included an assessment of patient-reported information on the OOPP used, patients’ ability to afford medications, and pharmacy services use behaviors. In addition, a comparison of the characteristics of responders and nonresponders was performed.

The study questionnaire was developed at KPCO using items obtained from the literature

 as needed to assess patient rationales for OOPP use. The questionnaire included information on the patient’s index prescription along with the name of the prescriber, whether the index prescription was filled or not, which OOPP was used, factors that may have influenced the use of an OOPP, ability to afford medications, and general health perceptions. The questionnaire items were assessed for interpretability (ie, reading level, jargon, etc), content validity, face validity, and reliability among a sample of KPCO pharmacy department staff. No outstanding issues were identified among the items.

The questionnaire and a cover letter explaining the purpose of the survey, along with a return envelope, were mailed via the US Postal Service to the random sample during the third week of January 2013. A reminder postcard was mailed approximately 2 weeks after the initial questionnaire. HealthCare Research, Inc (Denver, Colorado) conducted the survey and collected information from the returned questionnaires. Each questionnaire included a unique identifier to allow for the linking of the survey results with patient characteristics.

Patients’ demographic and health characteristics were identified using KPCO electronic administrative databases, including ambulatory visit, pharmacy use, membership databases, and the EMR. Administrative data collected included patient date of birth, KPCO membership status, sex, index prescription information (eg, index prescription drug class, in-plan medication purchases), socioeconomic demographics, and health plan information (eg, Medicare status).

As this was a descriptive study, no a priori sample size calculation was performed. The types of OOPP reported as used to purchase the index prescription were categorized as: (1) big box (eg, Walmart, Kmart); (2) discounter (eg, Sam’s Club, Costco); (3) chain (eg, CVS, Walgreens); (4) supermarket (eg, Krogers, Safeway); and (5) other (eg, independent pharmacy, Veterans Administration). Medicare status was categorized as Medicare beneficiary with a coverage gap, Medicare beneficiary without a coverage gap, or non-Medicare. Health plan type was categorized as traditional HMO or other (eg, preferred provider option, high deductible). Medications were classified into therapeutic drug classes based on their National Drug Code. A chronic disease score (CDS), a validated measure ranging from 0 to 35 with a higher score representing an increased burden of chronic disease,

was calculated from medication purchases during the 180 days prior to November 1, 2012. The count of in-plan prescription medication purchases during this time period was calculated. Patient race was categorized as white, other, or unknown/unreported.

Responses to the survey were tabulated and reported as percentages. Patient characteristics were reported as means/medians and percentages, as appropriate. Differences between respondents and nonrespondents were examined using c2 tests of association/Fisher’s exact test and t tests, as appropriate. A 2-sided alpha was set at 0.05.

A total of 4177 patients with a prescription electronically issued to an OOPP in November 2012 were eligible for this study. A random sample of 1000 of these patients were surveyed; 382 returned the questionnaire with usable data, for a survey response rate of 38.2%. Patients were stratified by survey response status into survey respondents and nonrespondents.

Survey respondents and nonrespondents were similar on sex distributions, count of previous prescription purchases at KPCO pharmacies, and socioeconomic indicators (all 

). However, respondents were more likely to be older and Medicare members and to have maintained plan membership during the 2 months following their index prescription order date (all 

 <.001). In addition, respondents were more likely to be white and less likely to be Hispanic than nonrespondents, and there were differences between groups across index prescription medication categories (all 

 <.05). The majority of respondents (n = 194, 51.5%) reported that they perceived their general health to be very good/excellent; this information was unobtainable for nonrespondents.

Overall, 330 (86.4%) respondents reported that they had purchased their index prescription at an OOPP (

). Their prescription being less expensive at the OOPP (n = 190, 57.6%), the OOPP having a discount generic prescription program (n = 188, 57%), and the OOPP’s convenient location (n = 145, 43.9%) were reported most frequently as factors influencing respondents’ decisions to choose their OOPP. In addition, 61 respondents (18.5%) reported that receiving extra incentives, such as fuel discounts, was a factor. The most commonly utilized OOPPs were supermarket (n = 140, 42.4%) and big box (n = 86, 26.1%) (

Almost one-fourth of respondents (n = 91) reported that they had used 2 or more OOPPs within the past year (Table 2). Less than 30% of respondents reported that they informed their Kaiser pharmacist (n = 95, 29.8%) or non-Kaiser OOPP pharmacist (n = 72, 22.6%) about their prescriptions filled at other pharmacies. Among respondents who reported using 2 or more OOPPs in the past year plus a Kaiser pharmacy (n = 77), 39% (30/77) reported informing their Kaiser pharmacist about their OOPP use.

While nearly a quarter (n = 87, 23.1%) of respondents reported that it was somewhat or very difficult for them to afford their prescriptions in 2012 (Table 2), 123 (39.4%) respondents indicated that using an OOPP helped them afford prescriptions they otherwise would not have been able to afford. Also among respondents who reported that it was somewhat or very difficult for them to afford their prescriptions in 2012 (n = 87), 69 (79.3%) reported that using their OOPP helped them afford their prescription(s). Among respondents who reported that their prescription, being less expensive at an OOPP, was a factor for using an OOPP (n = 190), 42.1% (80) reported that using their OOPP helped them afford their prescription(s).

In this survey of patients who had a prescription electronically issued to an OOPP in November 2012, we found that the most salient patient-reported factors given for using an OOPP were lower cost and convenience. These findings suggest that even patients with a defined pharmacy prescription drug benefit view prescription drugs as a commodity. Thus, “pharmacy shopping” may be a viable strategy for them to obtain prescription medications at a lowest cost. Most patients in our survey reported utilizing supermarket and big box retail pharmacies, reinforcing cost and convenience as drivers of OOPP use. Little information exists in the literature about why patients use an OOPP, and which one.

 Nevertheless, our findings do support previous research that identified convenience and inexpensive medications as factors that patients value.

Prescription cost makes sense as a commonly reported determinant of OOPP use, as this reinforces the theory that patients are concerned with prescription affordability.

Nevertheless, patients in our study reported that other factors, such as relationship(s) with a pharmacy’s staff and a pharmacy’s customer service also contribute to OOPP use. It is interesting to note that lower cost may not necessarily be equivalent to prescription affordability; while 57.6% of our respondents reported that their prescription was less expensive at an OOPP, approximately one-third of our respondents indicated that utilizing an OOPP helped them to afford prescriptions that they otherwise would not have been able to afford. This suggests that OOPP use among some patients is equivalent to buyers searching for the best bargain (ie, pharmacy shopping),

 not an inability to pay for medications.

Additionally, our study found that convenience is an important factor influencing OOPP use. Respondents reported that they most commonly utilized supermarket pharmacies for medications electronically issued to an OOPP. As convenience is typically advertised as one of the benefits of utilizing a supermarket, this finding is not surprising and is consistent with previously published data that indicate supermarket pharmacies are the most common choice for prescriptions transferred to an OOPP.

 Our findings suggest that convenience is crucial for health systems with in-plan pharmacies to consider if their current prescription delivery model is to stay competitive in the changing healthcare landscape. Future research should be undertaken to assess whether more prescriptions would be filled at in-plan pharmacies if more in-plan pharmacy locations and/or longer pharmacy operating hours were available.

Our study found that approximately 14% of patients reported that they did not fill their prescription electronically issued to an OOPP. This proportion is numerically lower than but similar to that reported by Fischer and  colleagues in their study of 3 Massachusetts health plans with e-prescribing capabilities who identified that 22% of electronically issued prescriptions were not filled.

These findings suggest another potential medication-related problem: failure to fill a prescription electronically issued to an OOPP. It is unclear if patients do not fill their prescription because they perceive medication costs as too expensive, or because they are not interested in obtaining the medication, or for some other reason(s).

Other results from our survey are disconcerting as well: approximately one-fifth of respondents reported that they inform their OOPP pharmacists about medications they receive at other pharmacies. This is troubling because in-plan EMRs and OOPP pharmacy dispensing systems generally do not share patient-specific information unless a health plan contracts with a pharmacy benefit manager (PBM) to perform this service.

Thus, the burden of ensuring communication across pharmacies about a patient’s other medication use can rest largely with the patient. The potential for adverse medication outcomes with this behavior is substantial (eg, drug-drug interactions).

It is unclear whether in-plan prescribers should discuss this gap in patient care when providing prescriptions electronically issued to an OOPP, ensure that their health plan has adequate drug utilization management coverage across pharmacies, or place the onus on patients to ensure that all of a patient’s medication information is communicated to each of the patient’s pharmacists. One low-tech option would be for prescribers to provide patients with a list of their current medications to share with their OOPP pharmacist.

Coupled with our current findings and previous work that revealed that approximately 5% of prescriptions are electronically issued to an OOPP,

 OOPP use appears to be an entrenched activity among a minority of patients. A retrospective analysis conducted in the Netherlands identified that approximately 11% of 45,805 patients from one insurance company were identified as OOPP users.

 Additionally, Gatwood and colleagues reported from their survey of 414 patients in a university-affiliated general medicine clinic that approximately 32% of respondents engaged in OOPP use.

 Therefore, it appears that different health systems have different rates of OOPP use, but that such use is ingrained.

Our study had several limitations. First, there was a moderate survey response rate. We attempted to encourage as many responses as possible by delaying survey administration until after the holiday season and utilizing a reminder postcard for nonrespondents. However, since we asked patients questions pertaining to their health-related behaviors that could be uncomfortable to answer and/or construed as their health plan checking up on them, it is unsurprising that a majority refused to participate. Second, patients may have felt compelled to respond in the affirmative (whatever they perceived the affirmative to have been), since it was a survey from their health plan. We attempted to mitigate the potential to answer in the affirmative by wording our items to be as nonjudgmental as possible. Third, this survey was conducted in a health plan with its own pharmacies. Patients from health plans that utilize a network of pharmacies may have different rationales for use of an OOPP. In addition, our study did not examine medication-related outcomes for patients utilizing an OOPP. Future research is essential to determine the impact of OOPP use on medication-related outcomes. If such research shows harm from OOPP use, strategies to recapture OOPP-using patients into in-plan pharmacies will need to be developed.

In this survey of patients who had a prescription electronically issued to an OOPP, we identified cost and convenience as the most significant drivers of OOPP use. While factors such as lost revenue, impact on healthcare quality, and the inability to track appropriate medication use would appear to be harmful from the health plan’s perspective, the risks to patients for using an OOPP are not clear. Future research should be conducted to assess the health-related consequences of OOPP use.

 From Kaiser Permanente Colorado, Pharmacy Department, Aurora, CO (TD, SJB), Greeley, CO (APB), and Englewood, CO (DK)

 This study was funded in its entirety by the Kaiser Permanente Colorado Pharmacy Department. Preliminary findings from this study were presented at the 2013 Western States Conference in San Diego, CA, as part of Alexander Block’s PGY2 pharmacy residency requirements.

 The authors report no conflicts of interest.

Concept and design (TD, APB, DK, SJB); acquisition of data (TD); analysis and interpretation of data (TD, APB, DK, SJB); drafting of the manuscript (TD, APB, DK); critical revision of the manuscript for important intellectual content (TD, APB, DK, SJB); statistical analysis (TD); provision of study materials or patients (TD, DK); obtaining funding (TD); administrative, technical, or logistic support (DK); and supervision (TD).

 Thomas Delate, PhD, 16601 E Centretech Pkwy, Aurora, CO 80011. E-mail: 

1. Tamblyn RM, McLeod PJ, Abrahamowicz M, Laprise R. Do too many cooks spoil the broth? multiple physician involvement in medical management of elderly patients and potentially inappropriate drug combinations. 

2. Gatwood J, Tungol A, Truong C, Kucukarslan SN, Erickson SR. Prevalence and predictors of utilization of community pharmacy generic drug discount programs. 

3. Buurma H, Bouvy ML, De Smet PA, Floor-Schreudering A, Leufkens HG, Egberts AC. Prevalence and determinants of pharmacy shopping behavior. 

4. Varallo FR, Capucho HC, Planeta CS, Mastroianni Pde C. Safety assessment of potentially inappropriate medications (PIM) use in older people and the factors associated with hospital admission. 

5. Delate T, Albrecht G, Olson K. Out-of-plan pharmacy utilization by members of a managed care organization. 

Articles

Prescription cost and pharmacy convenience were identified as the most significant drivers of out-of-plan pharmacy use.

Out-of-Plan Pharmacy Use: Insights Into Patient Behavior

To evaluate the health system cost of a home blood pressure monitoring (HBPM) program versus usual care in an integrated healthcare system.

This cost-effectiveness analysis was based upon a previously completed randomized controlled trial of 348 hypertensive patients, in which mean systolic blood pressure (BP) was lowered 21 versus 8 mm Hg in the HBPM and usual care groups, respectively, and BP control was achieved in 54% versus 35% of patients (

This analysis compared direct costs from the health plan perspective, including clinic visits, e-mail and telephone encounters, laboratory tests, medications, hospitalizations, and emergency department visits between the 2 groups. Primary outcomes were the incremental hypertension care-related cost of HBPM per mm Hg lowering of systolic BP per patient, per additional BP controlled, and per life-year gained.

Median hypertension-related cost per patient over 6 months was $455 in the HBPM group and $179 for usual care (P <.001). This increase was attributable to additional e-mail and telephone encounters, greater antihypertensive medication use, additional laboratory monitoring, and the BP monitor. Median total cost per patient was $1530 and $1283 for the HBPM and usual care groups, respectively (

 = .034). The HBPM program increased hypertension-related expenditures by $20.50 per mm Hg lowering of systolic BP, $1331 per additional patient achieving BP control at 6 months, and $3330 per life-year gained.

The HBPM program requires investment in outpatient encounters, medications, and laboratory monitoring, but produces significantly improved BP control.

This study highlights the cost-effective manner in which home-monitoring technology plus clinical pharmacy specialist involvement improves blood pressure (BP) control.

		Patients in the Home Blood Pressure Monitoring (HBPM) program had more overall telephone and email encounters with a pharmacist, but the same number of office visits with a pharmacist, and utilized more antihypertensive medications and laboratory monitoring compared with patients managed through usual care.

		The incremental 6-month cost of this intervention was $20.50 per mm Hg of systolic BP lowered, $1331 per additional BP controlled, and $3330 per life-year gained compared with usual care.

		The incremental costs of this intervention compare favorably with other interventions, largely because the HBPM program was more effective than usual care.

Nearly $51 billion in direct and indirect costs related to hypertension were spent in the United States in 2009, with much of it attributable to the healthrelated consequences of hypertension.

 One in 3 adults in the United States has hypertension, and about half of those have uncontrolled blood pressure (BP), putting them at increased risk for acute myocardial infarction, stroke, renal disease, and congestive heart failure.

 Lowering BP has been shown to reduce the occurrence of these events.

Despite effective therapeutic interventions to control BP, at least a quarter of patients with uncontrolled hypertension receive no pharmacologic treatment. Novel care delivery models using home BP monitoring have demonstrated improved BP control.

 Demonstrating the benefits, costs, and cost effectiveness of such programs will help clinicians and policy makers to decide whether to invest in these programs.

Investigators at Kaiser Permanente Colorado (KPCO) conducted a randomized, controlled trial to evaluate the effectiveness of a home BP monitoring (HBPM) intervention that used the American Heart Association Heart360 Web interface (

) to send home BP readings to a clinical pharmacy specialist who managed the patient’s medication therapy via phone or e-mail communication. The purpose of this study was to determine the cost-effectiveness of the HBPM program compared with usual care.

The study was conducted at KPCO, a group-model, closed-panel, nonprofit managed care organization that cares for more than 500,000 members in the Denver-Boulder metropolitan area. Outpatient medical services are provided at 18 primary care clinics spread geographically across the metropolitan area, 10 of which participated in the present study. Each clinic is staffed with 1 or more clinical pharmacy specialists who assist primary care providers with drug therapy management. With regard to hypertension management, clinical pharmacy specialists work under preapproved collaborative drug therapy management protocols that permit them to initiate or change antihypertensive medications, adjust medication doses, and order laboratory tests related to medication monitoring. KPCO clinicians use a commercially available EpicCare electronic health record (EHR) as part of routine care delivery. The KPCO EHR has a feature called My Chart which allows patients and their providers to communicate electronically through a password-protected website.

The study was approved by the KPCO Institutional Review Board.

The HBPM study has been described in detail elsewhere. 8 This was a randomized, controlled study of 348 patients with uncontrolled hypertension randomly assigned to the HBPM program or usual care. Patients in the HBPM group were provided with and trained to use a home BP monitor (Omron HEM-790IT monitor), and they were guided in establishing a Heart360 account and in how to automatically upload BP measurements from their monitor to their Heart360 account. Patients in the HBPM group also met with a clinical pharmacy specialist, who reviewed their current BP medication regimen, provided counseling on lifestyle changes, and adjusted or changed antihypertensive medications, as needed. Patients in the usual care group were instructed to follow up with their primary care physician for BP care. Patients in both groups returned at 6 months for an in-clinic BP measurement. Blood pressure goal was <140/90 mm Hg for all patients, except for those with diabetes mellitus or chronic kidney disease for whom the goal was <130/80 mm Hg. At 6 months, 54% of patients in the HBPM group attained their BP goal, compared with 35% in the usual-care group (

 <.001). The HBPM group lowered their systolic blood pressure (SBP) by an average of 21 mm Hg compared with 8 mm Hg in the usual care group (

The economic analysis was conducted from the health plan perspective over the 6-month study period. Cost inputs included costs of the blood pressure cuff, clinic visits, e-mail and telephone encounters, laboratory tests, medications, hospitalizations, and emergency department (ED) visits. Indirect costs (eg, the administrative costs necessary for day-to-day operations) were not included as they were not expected to differ between the groups.

Healthcare utilization data were collected for 6 months prior to and after study enrollment using administrative databases maintained by KPCO. Data included all outpatient encounters (office visits, telephone contacts, e-mails), laboratory and radiology tests, prescriptions, ambulatory surgery, ED visits, and hospital admissions both within the KPCO system as well as claims for care that occurred outside KPCO. Costs were classified as hypertension-related if the primary 

International Classification of Diseases, Ninth Revision, Clinical Modification

 code associated with each expenditure was hypertension (401.9); hospitalizations, clinic encounters, and ED visits were reviewed manually to verify accurate categorization. Current procedural terminology codes were used to assign costs according to a fee schedule derived from the 2009 national Medicare fee schedule.

Costs for professional claims were based on billed amounts. Prescriptions billed through insurance were collected during the same time frame, and costs were determined using discounted average wholesale price to approximate Medicare pricing, with the addition of an $8 dispensing fee.

Costs for the initial clinic visit, telephone encounters with a clinical pharmacy specialist, and all e-mail encounters were estimated by multiplying the time spent by each provider type by the hourly wage. Provider compensation rates were taken from the United States Census Bureau wages and compensation 2009 data plus 29.2% to account for benefits.

The following hourly rates were used: pharmacist, $74.14; medical assistant, $19.39; registered nurse, $44.09; and physician, $99.72. The initial clinic visits differed in that the HBPM group required an additional 20 minutes of medical assistant time for training on the home BP monitor, setting up a Heart360 account, and downloading BP readings to the website, plus 20 minutes with a clinical pharmacy specialist to review antihypertensive medications and make any necessary dose adjustments. Based on a survey of the clinical pharmacy specialists participating in the study, pharmacist time was estimated at 10 minutes for each telephone follow-up encounter. E-mails from any provider were estimated at 6 minutes per e-mail encounter. All costs have been adjusted to reflect 2013 dollars using the Consumer Price Index rates for medical costs.16 The selected home BP monitor or a similar model can be purchased for approximately $60.

Direct costs were grouped into the following categories: outpatient encounters (including in-person clinic visits, telephone calls, and e-mail exchanges); outpatient laboratory; pharmacy outpatient; and all other costs (ambulatory surgery, ED, hospitalizations, and outpatient radiology). Total healthcare costs for 6 months prior to enrollment were compared between groups to assess for baseline differences in costs and to adjust for such differences (if present) during the study period. Total and hypertension-related costs during the 6-month study period were calculated to demonstrate the relationship between hypertension-related and total healthcare costs and to capture any unintended increases in healthcare utilization (eg, due to adverse events) related to the study. Three incremental cost-effectiveness ratios (ICERs) were calculated: cost per mm Hg lowering of SBP per patient, cost per controlled BP achieved, and cost per life-year gained. To determine the cost of an additional 1 mm Hg lowering of SBP in a patient, the mean difference in 6-month costs for hypertension care was divided by the mean SBP change in each group. To determine the cost of 1 patient achieving BP control, the mean difference in 6-month hypertension-related costs was divided by the difference in the number of patients achieving control in each group.

Cost per life-year gained was determined by first calculating the discounted life expectancy (DLE) for each patient at baseline and after the intervention using the formula:

=1.5% is the discount rate for life years,

is the current age of the patient in years, and 

 denotes the probability of surviving until age 

 denotes the 1-year risk of death for a patient of age s with the same gender and BP control level as the patient. (The symbol Π denotes the product operator; for example 

 ). The mortality rates were estimated from life expectancy data based on age, gender, and BP control level.18 The mortality rate for a patient of age s years was calculated by the formula:

 is the life expectancy of a patient of age s of the same gender and BP control level; this was determined by linear interpolation or extrapolation from Tables 3, 

 The mortality rate formula was derived by assuming that deaths occur at the end of each year so that:

We calculated the incremental hypertension care costs of the intervention for year 1 of the program plus subsequent years of follow-up. Total hypertension care cost in each group for year 1 was calculated by first estimating the increased cost of antihypertensive medications for the entire year for each patient. To account for expected follow-up needs in the second 6-month period, the costs for non—study-related outpatient encounters in the first 6 months was doubled and an additional e-mail encounter was added for intervention patients. Additional laboratory costs were not added for the second 6-month period because most antihypertensive medications require annual monitoring. To determine the incremental hypertension care cost for each intervention patient in year 1, the mean cost of a usual-care patient was subtracted from the actual cost for each intervention patient. Incremental cost for subsequent years was calculated as the average difference in costs for antihypertensive medication plus laboratory monitoring between groups plus the cost of 3 e-mail encounters in the intervention group.

The discounted cost of intervention for each patient in the intervention group was calculated by the formula:

where rc = 3% is the discount rate for costs,

 is the incremental hypertension care cost for intervention patients in year 1 as described above, and 

 is the incremental cost for each subsequent year. Subset analyses were performed on the group of patients with diabetes mellitus to calculate the incremental cost-effectiveness ratios for this high-risk group.

Cost comparisons between each group were reported as median and interquartile range values as cost data were not normally distributed. Wilcoxon rank sum was used to determine the significance of the between-group differences in cost. Level of significance was set at an α of 0.05. All statistical analyses were performed using SAS version 9.2 (SAS Institute, Carey, North Carolina).

The average age of the 348 study participants was 60 years; about 60% were male (

). Almost half of the participants had either diabetes mellitus or chronic kidney disease (Table 1).

Compared with patients in the usual care group, patients in the HBPM group had significantly more e-mail (median 5 vs 1, 

 <.001) encounters during the 6-month study period. There were no statistically significant differences between the 2 groups in the number of office visits, ED visits, or hospitalizations over the 6-month study period (

There were no statistically significant differences in total costs for the intervention and usual care groups in the 6-month pre-enrollment period (

 = .828 for total costs). Median total healthcare costs per patient during the 6-month study period were higher in the HBPM group ($1590) than in the usual care group ($1283; 

). This difference was largely driven by higher outpatient encounter costs ($481 vs $381, 

 = .006) and higher medication costs ($622 vs $475, 

 = .034) for HBPM and usual care groups, respectively.

When only considering hypertension-related costs, all major cost categories were higher in the HBPM group (median hypertension-related care cost of $455 per patient) compared with usual care (median cost $179; 

 <.001, Table 3). The incremental hypertension-related cost per additional mm Hg reduction in SBP was $20.50. The incremental hypertension-related cost per patient who achieved BP control was $1331 (

A technology-based, pharmacist-run home blood pressure monitoring program improves health outcomes by investing $20.50 per mm Hg systolic blood pressure lowered and $3300 per life-year gained.

Sarah J. Billups, PharmD

Articles

Out-of-Plan Pharmacy Use: Insights Into Patient Behavior

Cost-effectiveness Evaluation of a Home Blood Pressure Monitoring Program