DIABETICMedicine DOI: 10.1111/dme.12692
Research: Health Economics Cost-effectiveness analysis of adding pharmacists to primary care teams to reduce cardiovascular risk in patients with Type 2 diabetes: results from a randomized controlled trial S. H. Simpson1, D. A. Lier2, S. R. Majumdar1,2,3, R. T. Tsuyuki3, R. Z. Lewanczuk3, R. Spooner3 and J. A. Johnson2,4 1 Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, 2Institute of Health Economics, Edmonton, 3Department of Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton and 4School of Public Health, University of Alberta, Edmonton, Canada
Accepted 12 January 2015
Abstract Adding pharmacists to primary care teams significantly improved blood pressure control and reduced predicted 10–year cardiovascular risk in patients with Type 2 diabetes. This pre-specified sub-study evaluated the economic implications of this cardiovascular risk reduction strategy.
Background
Methods One-year outcomes and healthcare utilization data from the trial were used to determine cost-effectiveness from the public payer perspective. Costs were expressed in 2014 Canadian dollars and effectiveness was based on annualized risk of cardiovascular events derived from the UKPDS Risk Engine. Results The 123 evaluable trial patients included in this analysis had a mean age of 62 ( 11) years, 38% were men, and mean diabetes duration was 6 ( 7) years. Pharmacists provided 3.0 ( 1.9) hours of additional service to each intervention patient, which cost $226 ( $1143) per patient. The overall one-year per-patient costs for healthcare utilization were $190 lower in the intervention group compared with usual care [95% confidence interval (CI): -$1040, $668). Intervention patients had a significant 0.3% greater reduction in the annualized risk of a cardiovascular event (95% CI: 0.08%, 0.6%) compared with usual care. In the cost-effectiveness analysis, the intervention dominated usual care in 66% of 10 000 bootstrap replications. At a societal willingness-to-pay of $4000 per 1% reduction in annual cardiovascular risk, the probability that the intervention was cost-effective compared with usual care reached 95%. A sensitivity analysis using multiple imputation to replace missing data produced similar results. Conclusions Within a randomized trial, adding pharmacists to primary care teams was a cost-effective strategy for reducing cardiovascular risk in patients with Type 2 diabetes. In most circumstances, this intervention may also be cost saving.
Diabet. Med. 32, 899–906 (2015)
Introduction Cardiovascular disease is a leading cause of morbidity and mortality in the general population, with the risk approximately twofold higher among those living with diabetes [1]. This elevated risk in people with diabetes is attributable to a clustering of cardiovascular risk factors, such as elevated blood pressure, dyslipidaemia and obesity [2,3]. Indeed, hypertension is one of the most common and poorly managed co-morbidities in patients with Type 2 diabetes Correspondence to: Scot H. Simpson. E-mail: [email protected]
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[4], and continues to be a complex treatment challenge for clinicians [5]. Coordinated, goal-oriented, multidisciplinary interventions can lead to significant improvements in blood glucose, blood pressure and other physiological measures in people with diabetes [6,7], and when maintained over time, these improvements lower the risk of cardiovascular events [8]. Our group and others have demonstrated in randomized controlled trials that the addition of pharmacists to primary and specialist care teams can improve management of these patients [7,9,10]. However, the economic implications of this strategy have not been fully characterized.
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Cost-effectiveness analysis of pharmacist intervention in cardiovascular risk S. H. Simpson et al.
What’s new?
outcome analyses were conducted according to the intention-to-treat principle.
• Economic implications of changes to the primary care team have not been fully characterized.
Cost-effectiveness analysis
• This study examines the cost-effectiveness of adding pharmacists to the primary care team. Before adopting a new intervention or programme, such as adding another healthcare professional to a collaborative care team, decision-makers must evaluate the costs and consequences of their choices. We therefore conducted a formal economic analysis using cost and outcome data collected during a previously reported one-year randomized controlled trial [9–11]. We took a public payer perspective to determine whether adding pharmacists to the primary care team would be cost-effective with respect to healthcare utilization and cardiovascular risk reduction.
Methods Description of the randomized controlled trial
The protocol for the main trial was registered (ISRCTN97121854) prior to enrolment of the first patient and results from the main trial and projected long-term effects have been reported previously [9,10]. Briefly, the study was conducted in five primary care clinics affiliated with the Edmonton Southside Primary Care Network in Edmonton, Canada. A total of 260 patients with Type 2 diabetes were enrolled and randomly allocated to either pharmacist intervention or control. Patients in the control group received usual care without any contributions from a pharmacist. Patients allocated to the intervention group met with a pharmacist, who conducted a medication history and limited physical examination, which included blood pressure measurement. After evaluating the patient’s medication regimen and medical history, pharmacists made recommendations to the prescribing physician, based on current clinical practice guidelines [12–14]. During the follow-up period, intervention patients were contacted by study pharmacists to address any issues with medication management. The nature and frequency of these intervention follow-up visits were at the discretion of the study pharmacist, patient and prescribing physician. At the end of one year, all control and intervention patients were seen in-person to determine the achievement of study outcomes. The primary outcome for the main trial was a ≥ 10% decrease in systolic blood pressure at one year, which is widely considered a clinically important improvement [15]. Secondary outcomes included changes in predicted 10–year risk of cardiovascular disease using the UK Prospective Diabetes (UKPDS) Risk Engine, initiation of guideline-concordant antiplatelet therapy, and changes in medication management of hypertension [10,11,16]. All
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Overview
We hypothesized that adding pharmacists to a primary care team would be cost-effective compared with usual care. Our trial provided data on healthcare utilization, changes in prescription drug use, and changes in blood glucose, blood pressure and lipid levels over one year. We took the perspective of a public payer to conduct a cost-effectiveness analysis because all trial patients had universal healthcare coverage for physician visits, emergency department visits, hospitalizations and other healthcare services. Health outcomes
We previously estimated the long-term effects of our intervention using the UKPDS Risk Engine [10]. Data collected at enrolment and at the end of follow-up were used to calculate baseline and one-year UKPDS risk scores for each patient. Intervention group patients had a significantly greater reduction in predicted 10–year risk of a cardiovascular event compared with controls [10]. For this cost-effectiveness study, the between-group difference in predicted 10–year risk was annualized with the use of a previously published nonlinear econometric formula [17]. We assumed that the annualized cardiovascular risk would be consistent with the rate of cardiovascular events experienced by patients during the first year of a pharmacist intervention. Annualizing the difference in predicted cardiovascular risk aligned the analytical horizons for health outcomes and costs. Utilization and cost estimates
Patient-specific costs were estimated for the pharmacist intervention, prescription medications, healthcare services provided by physician specialists and other healthcare professionals, emergency department visits and hospitalizations. All resources used by study patients were valued by applying the corresponding unit costs shown in Table 1. The analytic horizon was one year; therefore, we did not apply any discounting. However, all costs were adjusted to 2014 Canadian prices because patient recruitment and follow-up spanned three years. During the trial, pharmacists recorded their time spent on various activities related to the intervention on a timesheet for each patient and the cost of the intervention for each patient was estimated as the product of pharmacist time and unit cost. Unit cost was estimated by the mid-point in the relevant salary grid, with adjustments for vacation pay (14%), employee benefits (18%) and facility overheads (15%). Patient-specific drug utilization data, relating to all medications except insulin, were obtained directly from community pharmacy dispensation records. The cost of prescription
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Table 1 Unit costs used in the analysis Resource item
Unit
Intervention – pharmacist activity
Hour
Unit cost*
Source
75.09†
Local collective agreement Medication Various Drug -specific [18] Specialist Visit [19] Female, 15–24 years 105.54 Male, 15–24 years 104.50 Female, 25–44 years 106.90 Male, 25–44 years 108.35 Female, 45–64 years 111.87 Male, 45–64 years 117.57 Female, 65–74 years 116.77 Male, 65–74 years 120.90 Female, 74 + years 119.52 Male, 74 + years 117.35 Dietician Visit‡ 30.16† Local collective agreement Nurse Visit‡ 26.72† Local collective agreement Optometrist Visit§ [19] 19–64 years 49.82 65 + years 68.22 Podiatrist 32.26¶ [19] Emergency Visit [20,21] department 18–59 years 395.94 60 + years 431.53 Inpatient stay [22] 18–59 years 5,550 60–79 years 7,891 80 + years 8,728 *2014 Canadian dollars. †Includes vacation pay (14%), employee benefits (18%) and facility overhead (15%). ‡Visit assumed to equal 0.5 h. §Assumed one procedure per visit. ¶Maximum of $250 per year.
medications obtained, excluding co-payments and dispensing fees, was estimated using prices from the benefit list common to all public drug plans in Alberta [18]. Although the provincial drug plan does not cover the entire adult Alberta population, we assumed that all study patients would be eligible for drug coverage because at least 60% of study patients would qualify for provincial drug plan coverage based on age, spousal coverage, disability or social assistance eligibility, and the remaining patients would qualify for private coverage through their employer. We used a patient survey administered at the end of the trial to identify utilization of healthcare providers and healthcare facilities. Healthcare providers included four specific physician specialties (cardiologists, endocrinologists, nephrologists and ophthalmologists, but not family physicians) and other healthcare professionals (dieticians, nurses, optometrists and podiatrists). The patient-specific cost related to each healthcare provider was estimated as the product of the number visits and unit cost. For physician specialists, the unit cost was ª 2015 The Authors. Diabetic Medicine ª 2015 Diabetes UK
estimated as the average cost per visit for ‘major assessment’ according to the published physician fee schedule for Alberta [19]. Published average cost data were available by patient age group and gender, but only for all specialists combined [19]. For dieticians and nurses, each visit was assumed to last 0.5 hours and the unit cost was estimated by the mid-point in the relevant salary grids, with adjustment for vacation pay (14%), employee benefits (18%) and facility overheads (15%). An optometrist visit was assumed to be equivalent to one service and the unit cost was estimated by the published average cost per service by patient age group [19]. The unit cost for podiatrists was estimated by the published average cost per visit up to a yearly maximum [19]. The patient survey also provided data relating to emergency department visits and hospitalizations. The patientspecific cost was estimated as the product of the service count per patient and the unit cost of each service. The unit cost of an emergency department visit was estimated by multiplying the average of the published relative cost for six patient groups (related to stroke, heart and diabetes conditions) by the standard cost per weighted case for Alberta [20,21]. The emergency department visit unit cost includes the cost of chest X–rays and relates specifically to non-anaesthetic cases. The unit cost for a hospitalization was estimated as the average Alberta inpatient cost per discharge for the diabetes patient group [22]. Cost effectiveness analysis
Our main cost-effectiveness analysis included all patients with complete information on healthcare utilization. As a sensitivity analysis, we used multiple imputation to replace missing data for utilization of drugs, healthcare providers and facilities [23]. Ten imputed data sets were generated because the proportion of the missing data was 35%. All statistical analyses were performed using R v. 3.0.1 (R Foundation for Statistical Computing, Vienna, Austria). Data management was conducted with Filemaker Pro Advanced v. 11.4 (Filemaker Inc., Santa Clara, CA, USA). We estimated incremental cost and effectiveness on a per patient basis. Incremental cost was defined as the difference in overall average one-year cost per patient between study arms. The health effect was measured in terms of change from baseline in the annual risk of a cardiovascular event, so that incremental effectiveness is the difference in risk per patient, adjusted for baseline difference in risk [24]. In general, an intervention would be considered cost-effective in relation to the comparator if: (1) it cost less (the incremental cost is negative) and is more effective (the incremental health effect is positive) (i.e. it is dominant); or (2) it costs more and is more effective than the comparator, but society is willing to pay for the additional cost [25]. Stochastic analysis of uncertainty
To account for uncertainty due to sampling variation, we used a non-parametric bootstrapping analysis to generate a
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scatter plot of incremental cost and outcome on the costeffectiveness plane [25]. Based on that generated distribution, a cost-effectiveness acceptability curve (CEAC) was derived, indicating the probability of the intervention being costeffective at various levels of society’s willingness to pay per annual 1% change in cardiovascular risk. We generated 10 000 replications for the main analysis and 5000 replications for each of the ten imputed datasets, for a total of 50 000 replications in the sensitivity analysis. We estimated a cost-effectiveness threshold for the intervention in order to meaningfully interpret the CEAC. In a sense, this threshold represents the opportunity cost, relating to the health outcome foregone, by the reallocation of resources required to implement the intervention [26]. Following a recently published method, we estimated the threshold as the ratio of average cost to average health effect using the sample data of the control arm [27]. We assumed that the existing programme of usual care, represented by the control arm, is as efficient as the least efficient existing programme from which resources would be reallocated. This approach also allowed us to express the denominator of the threshold in terms of how the health outcome was measured in this trial [27].
Results We excluded 137 of 260 trial patients from the main economic analysis because they either did not return a survey containing information on healthcare service utilization or we were unable to obtain pharmacy refill data. The 123 evaluable patients included in the economic analysis were older than the remaining trial patients [mean ( SD): age 61.5 ( 10.9) years versus 56.9 ( 11.8) years, P = 0.0013]; however, there were no significant differences in sex, baseline UKPDS risk score or diabetes duration. Baseline patient characteristics were similar between the 65 intervention patients and 58 controls included in this analysis, suggesting that integrity of the original randomization was preserved (Table 2). There were 47 (38%) men, mean diabetes duration 5.6 ( 7.0) years, and UKPDS risk score 14.4% ( 10.0%). The predicted 10–year risk of a cardiovascular event decreased from a mean of 14.6% ( 10.1%) to 12.0% ( 7.6%) in the intervention group and from 14.2% ( 10.0%) to 13.4% ( 11.1%) in controls (P = 0.035 for the difference of differences). The annualized reduction in risk of a cardiovascular event observed after the one-year study was 0.33% ( 0.67%) in the intervention group and 0.06% ( 0.68%) in controls (between-group difference 0.26%; 95% CI 0.08%, 0.63%). Healthcare service utilization is reported in Table 3. On average, study pharmacists took 1.0 ( 0.3) hour to complete the baseline assessment and spent 2.0 ( 1.8) hours in follow-up visits with each intervention group patient (Table 3). During the one-year follow-up period, pharmacists contacted each intervention patient an average of
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Table 2 Baseline characteristics
Male, n (%) Age, years Duration of diabetes, years No CVD at enrollment, n (%) UKPDS risk score, 10-year % UKPDS risk score, annualized %
Intervention (n = 65)
Control (n = 58)
24 62.0 4.5 49 14.6 1.63
23 60.9 6.8 48 14.2 1.59
(37) (10.2) (3.9) (75) (10.1) (1.3)
(40) (11.6) (9.1) (83) (10.0) (1.3)
Data are reported as mean (SD) unless otherwise specified. All between-group comparisons are not statistically significant
Table 3 Health service utilization Resource item
Intervention
Intervention – pharmacist contact time Baseline assessment (h) 1.0 Follow-up visits (h) 2.0 Total time (h) 3.0 Specialist – cardiologist visits 0.12 Specialist – endocrinologist visits 0.20 Specialist – nephrologist visits 0.08 Specialist – ophthalmologist 0.65 visits* Sub-total specialist visits 1.18 Dietician visits 0.20 Nurse visits† 0.65 Optometrist visits 0.57 Podiatrist visits 0.48 Sub-total other healthcare 1.98 professional visits Emergency department visits 0.34 Inpatient stays 0.05
Control
(0.3) (1.8) (1.9) (0.48) (0.75) (0.37) (0.99)
– – – 0.24 0.28 0.03 0.83
(0.98) (0.79) (0.26) (0.80)
(1.66) (0.62) (1.39) (0.75) (1.85) (2.69)
1.55 0.28 0.93 0.47 0.12 1.81
(2.11) (0.62) (1.35) (0.57) (0.38) (1.76)
(1.33) (0.21)
0.24 (0.57) 0.10 (0.31)
All data are reported as mean (SD) per patient. *P = 0.040; †P = 0.036; all other between-group comparisons are not statistically significant.
6 ( 3) times by telephone and met with them in-person 2 ( 2) times. Intervention patients had fewer visits to ophthalmologists (0.65 0.99 visits per patient) and nurses (0.65 1.39 visits per patient) compared with controls (0.83 0.80, P = 0.040 and 0.93 1.35, P = 0.036, visits per patient, respectively). Although intervention patients had more visits to an emergency department (0.34 1.33 visits per patient) compared with controls (0.25 0.58 visits per patient), the difference was not statistically significant (P = 0.65). The mean annual cost for the pharmacist intervention was estimated to be $226 ( $143) per patient (Table 4). This cost was more than offset by savings in other variables, including medication costs, specialist costs and inpatient costs. Although there was an overall cost saving of $190 for the intervention group, the difference between groups was not statistically significant (95% CI –$1040, $668). Results of the cost–effectiveness analysis (Table 5) indicate the intervention was dominant compared to usual care
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because it cost less (–$190) and was more effective (0.26% greater reduction in annualized cardiovascular risk). Figure 1 presents a scatter plot for the joint distribution of incremental cost and incremental health effect from 10 000 bootstrap replications. The majority (66%) of these replications fell in quadrant IV, supporting the dominance of the intervention compared with usual care. The cost-effectiveness acceptability curve (Fig. 2) shows that, as society’s willingness to pay increases, the probability that the intervention is considered cost-effective reaches 95% at a relatively low level of about $4000 per 1% reduction in annualized cardiovascular risk. The cost-effectiveness threshold (society’s willingness to pay for a reduction of 1% in cardiovascular risk) was estimated to be $33 215 ($1993/ 0.06, control arm data from Table 5) and is shown as point A in Fig. 2. The probability that the intervention would be Table 4 Cost of resources used
Cost per patient* Intervention Intervention 226 Medications 896 Specialists 137 74 Other healthcare professional 142 Emergency department cost Inpatient 328 cost Total cost 1803
(143) (608) (193) (88)
Control – 914 (690) 179 (241) 63 (57)
Difference [95% CI]† (Intervention – Control) 226 –18 –42 11
– [–251, 215] [–119, 36] [–16, 38]
(568)
101 (244)
41 [–119, 200]
(1522)
735 (2213) –407 [–1080, 265]
(2232) 1993 (2620) –190 [–1040, 668]
*Costs are reported as mean (SD) per patient in 2014 Canadian dollars. †95% CI for between group differences are shown within brackets. The 95% CI for total cost was based on 10 000 bootstrap replications. All between-group comparisons are not statistically significant.
dominant or have an incremental cost-effectiveness ratio below this threshold is 99%. We conducted a sensitivity analysis using data from 258 of the 260 main trial patients. One control patient was excluded because they died during the main trial and one intervention patient was excluded because they returned a survey with health service utilization rates that were so high that we suspected errors in reporting. Multiple imputation was used to replace missing data and we observed similar results to our main analysis (Fig. 2 and Table 5).
Discussion We evaluated the economic implications of adding pharmacists to primary care teams using outcomes and healthcare utilization data from patients with Type 2 diabetes enrolled in a randomized controlled trial. Although the cost of the pharmacist intervention was offset by savings in other healthcare services, the cost difference between intervention and control groups was small and not statistically significant. Patients in the intervention group had a small but significantly greater reduction in their annualized risk of a cardiovascular event compared with controls. In the costeffectiveness analysis, the intervention dominated usual care in 66% of 10 000 bootstrap replications. When a societal cost-effectiveness threshold of $31 500 was considered, the probability that the intervention would be cost-effective was 99%. Our observation that adding pharmacists to primary care teams is a cost-effective strategy for managing patients with Type 2 diabetes and poorly controlled hypertension is consistent with other groups. For example, Lowey and colleagues demonstrated in an uncontrolled before–after study that, although a pharmacist-led outpatient clinic would cost over € 1900 (US$2574, C$2867) per person, participating in the clinic could reduce the patient’s predicted 10– year risk of cardiovascular disease by 3.6% and lead to a savings of approximately € 54 000 (US$73 160, C$81 486)
Table 5 Cost-effectiveness analysis
Main analysis (n = 123) Cost† Reduction in CV risk (%)‡ Cost per 1% improvement in risk Multiple imputation (n = 258) Cost† Reduction in CV risk (%)‡ Cost per 1% improvement in risk
Intervention
Control
Difference [95% CI]*
1709 (2117) 0.33 (0.67)
1889 (2483) 0.06 (0.68)
–180 [–987 to 634] 0.26 [0.083 to 0.63]§ na¶
2636 (2116) 0.34 (0.90)
2780 (2290) 0.11 (0.97)
–143 [–739 to 452] 0.21 [0.02 to 0.41]§ na¶
*95% confidence intervals for the incremental cost and incremental health outcome were based on 10 000 bootstrap replications for the main analysis and 50 000 replications for the multiple imputation analysis (10 imputed data sets and 5000 for each imputed data set). †Cost is reported as mean (SD) per patient in 2014 Canadian dollars. ‡Incremental health outcome reported as mean reduction in annualized UKPDS risk sore (SD) per patient. §Adjusted for baseline difference in CV risk between study arms. ¶Not applicable because the intervention is dominant.
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0
1000
QI
—1000 —2000
Incremental Cost †
2000
QII
QIII
—0.5
QIV
0.0
0.5
1.0
Incremental CV Risk (Health Effect) (%)† FIGURE 1 Bootstrap results on the cost-effectiveness plane based on 10 000 bootstrap replications. †Intervention minus control.
60
70
80
90
A
10
20
30
40
50
Main Analysis MI Analysis
0
Probability of Intervention Being Cost-Effective (%)
100
per event avoided [28]. In a retrospective matched-cohort study, Yu and colleagues observed that adding pharmacists to the diabetes management team dominated the control group because predicted 10–year costs were lower and intervention group patients had more quality adjusted life
years compared with controls [29]. These investigators used Markov models to extrapolate data collected during a oneyear observation period and found that the probability of the pharmacist intervention being cost-effective increased as the time horizon for the analysis was extended. In contrast to these studies, we used data collected during a randomized controlled trial and limited our observations to the one-year time horizon of the main study. There are several limitations to consider when interpreting our results. First, we used the UKPDS risk score and estimated an annualized reduction in risk for our effectiveness measure. The UKPDS risk equation was originally developed to predict 10–year risk of cardiovascular disease based on the patient’s current status and assuming a natural course of cardiovascular disease if left untreated [16]. Nevertheless, several other groups have also used changes in UKPDS risk score as a summary estimate for economic evaluations [28,29]. Second, our observations are limited to a one-year time horizon; therefore the long-term cost-effectiveness of adding pharmacists to primary care teams remains unclear. We believe, however, that the one-year improvement in UKPDS risk score may be a conservative estimate. In practice, it is likely that patients receiving pharmacist intervention would have ongoing assessments and improvements in cardiovascular risk factors. By contrast, prior studies have shown that, in the absence of ongoing care and interdisciplinary support, cardiovascular risk factors tend to
0
5000
10000
15000
20000
25000
30000
35000
40000
Willingness to Pay for a One % Reduction in CV Risk($) FIGURE 2 Cost-effectiveness acceptability curve. The main analysis was based on 10 000 bootstrap replications and the multiple imputation analysis was based on 5000 replications of the 10 imputed datasets, for a total of 50 000.
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remain suboptimal or continue to deteriorate over time in most patients with Type 2 diabetes [4,30]. Third, we based our main economic analysis on 123 patients with a complete set of information, only about half of our total trial enrolment. We believe this was a reasonable decision because this is a secondary analysis of a positive trial and a sensitivity analysis using multiple imputation to replace missing data produced results that were similar to our main analysis. Fourth, health utilization information was collected from patient self-report, which may affect accuracy of these estimates. However, we do not believe that there would be important differences in recall between groups and the data were collected and analysed without knowledge of allocation status. Last, these are within-trial economic analyses drawn from a single healthcare setting where all patients have universal healthcare coverage, and there might be some concerns about the wider generalizability of our findings. For example, the number of patients in one setting may not be sufficient to justify a full-time pharmacist and thus require consideration of the additional costs required to travel to multiple locations. In conclusion, this economic analysis suggests that adding pharmacists to primary care teams is a cost-effective strategy for reducing cardiovascular risk in patients with Type 2 diabetes – at the least, when considering a short, one-year time horizon. In most circumstances, and possibly over a longer follow-up period, this additional effort may also be cost-saving from a public payer perspective.
Funding sources
Operating grant funding was provided by the Canadian Diabetes Association, Institute of Health Economics, and Alberta Heritage Foundation for Medical Research (AHFMR). Dr Simpson was supported as a New Investigator by the Canadian Institutes of Health Research (CIHR) during the conduct of this study. Dr Majumdar is supported as a Health Scholar by the Alberta Innovates – Health Solutions (AIHS) and holds the Endowed Chair in Patient Health Management of the Faculties of Medicine and Dentistry and Pharmacy and Pharmaceutical Sciences, University of Alberta. Dr Johnson holds a Health Senior Scholar through the AIHS, and is Chair of the CIHR funded Alliance for Canadian Health Outcomes Research in Diabetes (ACHORD) (reference #: OTG-88588).
Competing interests
None declared.
Acknowledgements
The authors are especially grateful for the contributions of the two study pharmacists, Denise Nitschke, BSc(Pharm), CDE, and Shelley Tuchsherer, BSc(Pharm), CDE. We thank
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the staff at the Epidemiology Coordinating and Research (EPICORE) Centre for their support. We also thank the clinicians and staff at the 5 family medicine clinics in the Edmonton Southside Primary Care Network for working with us during the study.
References 1 Emerging Risk Factors Collaboration. Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med 2011; 364: 829–841. 2 Nathan DM, Meigs J, Singer DE. The epidemiology of cardiovascular disease in type 2 diabetes mellitus: how sweet it is . . . or is it? Lancet 1997; 350(Suppl 1): SI4–SI9. 3 Tan MH, MacLean DR. Epidemiology of diabetes mellitus in Canada. Clin Invest Med 1995; 18: 240–246. 4 Harris SB, Ekoe JM, Zdanowicz Y, Webster-Boagert S. Glycemic control and morbidity in the Canadian primary care setting (results of the diabetes in Canada evaluation study). Diabet Res Clin Pract 2005; 70: 90–97. 5 Leiter LA, Berard L, Bowering CK, Cheng AY, Dawson KG, Ekoe JM et al. Type 2 diabetes mellitus management in Canada: is it improving? Can J Diabetes 2013; 37: 82–89. 6 Gaede P, Vedel P, Larsen N, Jensen GV, Parving HH, Pedersen O. Multifactorial intervention and cardiovascular disease in patients with type 2 diabetes. N Engl J Med 2003; 348: 383– 393. 7 Rothman RL, Malone R, Bryant B, Shintani AK, Crigler B, Dewalt DA et al. A randomized trial of a primary care-based disease management program to improve cardiovascular risk factors and glycated hemoglobin levels in patients with diabetes. Am J Med 2005; 118: 276–284. 8 Gaede P, Lund-Andersen H, Parving HH, Pedersen O. Effect of a multifactorial intervention on mortality in type 2 diabetes. New Engl J Med 2008; 358: 580–591. 9 Simpson SH, Majumdar SR, Tsuyuki RT, Lewanczuk RZ, Spooner R, Johnson JA. Effect of adding pharmacists to primary care teams on blood pressure control in patients with type 2 diabetes: a randomized controlled trial. Diabetes Care 2011; 34: 20–26. 10 Ladhani NN, Majumdar SR, Johnson JA, Tsuyuki RT, Lewanczuk RZ, Spooner R et al. Adding pharmacists to primary care teams reduces predicted long-term risk of cardiovascular events in type 2 diabetic patients without established cardiovascular disease: results from a randomized trial. Diabet Med 2012; 29: 1433–1439. 11 Gilani F, Majumdar SR, Johnson JA, Tsuyuki RT, Lewanczuk RZ, Spooner R et al. Adding pharmacists to primary care teams increases guideline-concordant antiplatelet use in patients with type 2 diabetes: results from a randomized trial. Ann Pharmacother 2013; 47: 43–48. 12 Canadian Diabetes Association Clinical Practice Guidelines Expert Committee. Pharmacologic management of type 2 diabetes. Can J Diabetes 2008; 32(Suppl 1): S53–S61. 13 Canadian Diabetes Association Clinical Practice Guidelines Expert Committee. Vascular protection in people with diabetes. Can J Diabetes 2008; 32(Suppl 1): S102–S106. 14 Culleton B, Drouin D, Larochelle P, Leiter LA, McFarlane P, Tobe S. Treatment of hypertension. Can J Diabetes 2008; 32(Suppl 1): S115–S118. 15 Majumdar SR, Johnson JA, Bowker SL, Booth GL, Dolovich L, Ghali W et al. A Canadian consensus for the standardized evaluation of quality improvement interventions in type 2 diabetes. Can J Diabetes 2005; 29: 220–229.
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16 Stevens RJ, Kothari V, Adler AI, Stratton IM. The UKPDS risk engine: a model for the risk of coronary heart disease in Type II diabetes (UKPDS 56). Clin Sci 2001; 101: 671–679. 17 Briggs A, Sculpher M. An introduction to Markov modelling for economic evaluation. Pharmacoeconomics 1998; 13: 397– 409. 18 Alberta Health. Drug Benefits List 2010. Available from: http:// www.health.alberta.ca/AHCIP/drug-benefit-list.html. Last accessed 11 March 2011. 19 Alberta Health. Care Insurance Plan Statistical Supplement: 20102011. Available from: http://www.health.alberta.ca/newsroom/ publications.html. Last accessed 25 January 2013. 20 Canadian Institute for Health Information. Comprehensive Ambulatory Care Client Tables 2011. Available from: http://www.cihi.ca. Last accessed 11 March 2012. 21 Canadian Institute for Health Information. Hospital Financial Performance (HFP) Indicators. Available from: http://www.cihi.ca. Last accessed 12 December 2012. 22 Canadian Institute for Health Information. Patient Cost Esimator: estimated average costs by CMG and age group, Alberta, 2008–09. Available from: http://apps.cihi.ca/MicroStrategy/asp/Main.aspx. Last accessed 15 March 2013. 23 Rubin DB Multiple Imputation for Nonresponse in Surveys. Wiley Classics Library. Hoboken, NJ: Wiley-Interscience, 2004.
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24 Vickers AJ, Altman DG. Statistics notes: Analysing controlled trials with baseline and follow up measurements. British Medical Journal 2001; 323: 1123–1124. 25 Drummond MF, Sculper MJ, Torrance GW, O’Brien BJ, Stoddart GL. Methods for the Economic Evaluation of Health Care Programmes, 3rd ed. Oxford: Oxford University Press, 2005. 26 Claxton KP, Martin SO, Soares M, Rice N, Spackman E, Hine S et al. Methods for the Estimation of the NICE Cost Effectiveness Threshold. York: Centre for Health Economics, University of York, 2013. 27 Hyewon HL, Levine M. Determing the threshold of acceptability of an ICER when natural health units are used. J Popul Ther Pharmacol 2012; 19: e234–238. 28 Lowey A, Moore S, Norris C, Wright D, Silcock J, Hammond P. The cost-effectiveness of pharmacist-led treatment of cardiac risk in patients with type 2 diabetes. Pharm World Sci 2007; 29: 541–545. 29 Yu J, Shah BM, Ip EJ, Chan J. A Markov model of the costeffectiveness of pharmacist care for diabetes in prevention of cardiovascular diseases: evidence from Kaiser Permanente Northern California. J Manag Care Pharm 2013; 19: 102–114. 30 Johnson JA, Eurich DT, Toth EL, Lewanczuk RZ, Lee TK, Majumdar SR. Generalizability and persistence of a multifaceted intervention for improving quality of care for rural patients with type 2 diabetes. Diabetes Care 2005; 28: 783–788.
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Research: Health Economics Cost-effectiveness analysis of adding pharmacists to primary care teams to reduce cardiovascular risk in patients with Type 2 diabetes: results from a randomized controlled trial S. H. Simpson1, D. A. Lier2, S. R. Majumdar1,2,3, R. T. Tsuyuki3, R. Z. Lewanczuk3, R. Spooner3 and J. A. Johnson2,4 1 Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, 2Institute of Health Economics, Edmonton, 3Department of Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton and 4School of Public Health, University of Alberta, Edmonton, Canada
Accepted 12 January 2015
Abstract Adding pharmacists to primary care teams significantly improved blood pressure control and reduced predicted 10–year cardiovascular risk in patients with Type 2 diabetes. This pre-specified sub-study evaluated the economic implications of this cardiovascular risk reduction strategy.
Background
Methods One-year outcomes and healthcare utilization data from the trial were used to determine cost-effectiveness from the public payer perspective. Costs were expressed in 2014 Canadian dollars and effectiveness was based on annualized risk of cardiovascular events derived from the UKPDS Risk Engine. Results The 123 evaluable trial patients included in this analysis had a mean age of 62 ( 11) years, 38% were men, and mean diabetes duration was 6 ( 7) years. Pharmacists provided 3.0 ( 1.9) hours of additional service to each intervention patient, which cost $226 ( $1143) per patient. The overall one-year per-patient costs for healthcare utilization were $190 lower in the intervention group compared with usual care [95% confidence interval (CI): -$1040, $668). Intervention patients had a significant 0.3% greater reduction in the annualized risk of a cardiovascular event (95% CI: 0.08%, 0.6%) compared with usual care. In the cost-effectiveness analysis, the intervention dominated usual care in 66% of 10 000 bootstrap replications. At a societal willingness-to-pay of $4000 per 1% reduction in annual cardiovascular risk, the probability that the intervention was cost-effective compared with usual care reached 95%. A sensitivity analysis using multiple imputation to replace missing data produced similar results. Conclusions Within a randomized trial, adding pharmacists to primary care teams was a cost-effective strategy for reducing cardiovascular risk in patients with Type 2 diabetes. In most circumstances, this intervention may also be cost saving.
Diabet. Med. 32, 899–906 (2015)
Introduction Cardiovascular disease is a leading cause of morbidity and mortality in the general population, with the risk approximately twofold higher among those living with diabetes [1]. This elevated risk in people with diabetes is attributable to a clustering of cardiovascular risk factors, such as elevated blood pressure, dyslipidaemia and obesity [2,3]. Indeed, hypertension is one of the most common and poorly managed co-morbidities in patients with Type 2 diabetes Correspondence to: Scot H. Simpson. E-mail: [email protected]
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[4], and continues to be a complex treatment challenge for clinicians [5]. Coordinated, goal-oriented, multidisciplinary interventions can lead to significant improvements in blood glucose, blood pressure and other physiological measures in people with diabetes [6,7], and when maintained over time, these improvements lower the risk of cardiovascular events [8]. Our group and others have demonstrated in randomized controlled trials that the addition of pharmacists to primary and specialist care teams can improve management of these patients [7,9,10]. However, the economic implications of this strategy have not been fully characterized.
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What’s new?
outcome analyses were conducted according to the intention-to-treat principle.
• Economic implications of changes to the primary care team have not been fully characterized.
Cost-effectiveness analysis
• This study examines the cost-effectiveness of adding pharmacists to the primary care team. Before adopting a new intervention or programme, such as adding another healthcare professional to a collaborative care team, decision-makers must evaluate the costs and consequences of their choices. We therefore conducted a formal economic analysis using cost and outcome data collected during a previously reported one-year randomized controlled trial [9–11]. We took a public payer perspective to determine whether adding pharmacists to the primary care team would be cost-effective with respect to healthcare utilization and cardiovascular risk reduction.
Methods Description of the randomized controlled trial
The protocol for the main trial was registered (ISRCTN97121854) prior to enrolment of the first patient and results from the main trial and projected long-term effects have been reported previously [9,10]. Briefly, the study was conducted in five primary care clinics affiliated with the Edmonton Southside Primary Care Network in Edmonton, Canada. A total of 260 patients with Type 2 diabetes were enrolled and randomly allocated to either pharmacist intervention or control. Patients in the control group received usual care without any contributions from a pharmacist. Patients allocated to the intervention group met with a pharmacist, who conducted a medication history and limited physical examination, which included blood pressure measurement. After evaluating the patient’s medication regimen and medical history, pharmacists made recommendations to the prescribing physician, based on current clinical practice guidelines [12–14]. During the follow-up period, intervention patients were contacted by study pharmacists to address any issues with medication management. The nature and frequency of these intervention follow-up visits were at the discretion of the study pharmacist, patient and prescribing physician. At the end of one year, all control and intervention patients were seen in-person to determine the achievement of study outcomes. The primary outcome for the main trial was a ≥ 10% decrease in systolic blood pressure at one year, which is widely considered a clinically important improvement [15]. Secondary outcomes included changes in predicted 10–year risk of cardiovascular disease using the UK Prospective Diabetes (UKPDS) Risk Engine, initiation of guideline-concordant antiplatelet therapy, and changes in medication management of hypertension [10,11,16]. All
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Overview
We hypothesized that adding pharmacists to a primary care team would be cost-effective compared with usual care. Our trial provided data on healthcare utilization, changes in prescription drug use, and changes in blood glucose, blood pressure and lipid levels over one year. We took the perspective of a public payer to conduct a cost-effectiveness analysis because all trial patients had universal healthcare coverage for physician visits, emergency department visits, hospitalizations and other healthcare services. Health outcomes
We previously estimated the long-term effects of our intervention using the UKPDS Risk Engine [10]. Data collected at enrolment and at the end of follow-up were used to calculate baseline and one-year UKPDS risk scores for each patient. Intervention group patients had a significantly greater reduction in predicted 10–year risk of a cardiovascular event compared with controls [10]. For this cost-effectiveness study, the between-group difference in predicted 10–year risk was annualized with the use of a previously published nonlinear econometric formula [17]. We assumed that the annualized cardiovascular risk would be consistent with the rate of cardiovascular events experienced by patients during the first year of a pharmacist intervention. Annualizing the difference in predicted cardiovascular risk aligned the analytical horizons for health outcomes and costs. Utilization and cost estimates
Patient-specific costs were estimated for the pharmacist intervention, prescription medications, healthcare services provided by physician specialists and other healthcare professionals, emergency department visits and hospitalizations. All resources used by study patients were valued by applying the corresponding unit costs shown in Table 1. The analytic horizon was one year; therefore, we did not apply any discounting. However, all costs were adjusted to 2014 Canadian prices because patient recruitment and follow-up spanned three years. During the trial, pharmacists recorded their time spent on various activities related to the intervention on a timesheet for each patient and the cost of the intervention for each patient was estimated as the product of pharmacist time and unit cost. Unit cost was estimated by the mid-point in the relevant salary grid, with adjustments for vacation pay (14%), employee benefits (18%) and facility overheads (15%). Patient-specific drug utilization data, relating to all medications except insulin, were obtained directly from community pharmacy dispensation records. The cost of prescription
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Table 1 Unit costs used in the analysis Resource item
Unit
Intervention – pharmacist activity
Hour
Unit cost*
Source
75.09†
Local collective agreement Medication Various Drug -specific [18] Specialist Visit [19] Female, 15–24 years 105.54 Male, 15–24 years 104.50 Female, 25–44 years 106.90 Male, 25–44 years 108.35 Female, 45–64 years 111.87 Male, 45–64 years 117.57 Female, 65–74 years 116.77 Male, 65–74 years 120.90 Female, 74 + years 119.52 Male, 74 + years 117.35 Dietician Visit‡ 30.16† Local collective agreement Nurse Visit‡ 26.72† Local collective agreement Optometrist Visit§ [19] 19–64 years 49.82 65 + years 68.22 Podiatrist 32.26¶ [19] Emergency Visit [20,21] department 18–59 years 395.94 60 + years 431.53 Inpatient stay [22] 18–59 years 5,550 60–79 years 7,891 80 + years 8,728 *2014 Canadian dollars. †Includes vacation pay (14%), employee benefits (18%) and facility overhead (15%). ‡Visit assumed to equal 0.5 h. §Assumed one procedure per visit. ¶Maximum of $250 per year.
medications obtained, excluding co-payments and dispensing fees, was estimated using prices from the benefit list common to all public drug plans in Alberta [18]. Although the provincial drug plan does not cover the entire adult Alberta population, we assumed that all study patients would be eligible for drug coverage because at least 60% of study patients would qualify for provincial drug plan coverage based on age, spousal coverage, disability or social assistance eligibility, and the remaining patients would qualify for private coverage through their employer. We used a patient survey administered at the end of the trial to identify utilization of healthcare providers and healthcare facilities. Healthcare providers included four specific physician specialties (cardiologists, endocrinologists, nephrologists and ophthalmologists, but not family physicians) and other healthcare professionals (dieticians, nurses, optometrists and podiatrists). The patient-specific cost related to each healthcare provider was estimated as the product of the number visits and unit cost. For physician specialists, the unit cost was ª 2015 The Authors. Diabetic Medicine ª 2015 Diabetes UK
estimated as the average cost per visit for ‘major assessment’ according to the published physician fee schedule for Alberta [19]. Published average cost data were available by patient age group and gender, but only for all specialists combined [19]. For dieticians and nurses, each visit was assumed to last 0.5 hours and the unit cost was estimated by the mid-point in the relevant salary grids, with adjustment for vacation pay (14%), employee benefits (18%) and facility overheads (15%). An optometrist visit was assumed to be equivalent to one service and the unit cost was estimated by the published average cost per service by patient age group [19]. The unit cost for podiatrists was estimated by the published average cost per visit up to a yearly maximum [19]. The patient survey also provided data relating to emergency department visits and hospitalizations. The patientspecific cost was estimated as the product of the service count per patient and the unit cost of each service. The unit cost of an emergency department visit was estimated by multiplying the average of the published relative cost for six patient groups (related to stroke, heart and diabetes conditions) by the standard cost per weighted case for Alberta [20,21]. The emergency department visit unit cost includes the cost of chest X–rays and relates specifically to non-anaesthetic cases. The unit cost for a hospitalization was estimated as the average Alberta inpatient cost per discharge for the diabetes patient group [22]. Cost effectiveness analysis
Our main cost-effectiveness analysis included all patients with complete information on healthcare utilization. As a sensitivity analysis, we used multiple imputation to replace missing data for utilization of drugs, healthcare providers and facilities [23]. Ten imputed data sets were generated because the proportion of the missing data was 35%. All statistical analyses were performed using R v. 3.0.1 (R Foundation for Statistical Computing, Vienna, Austria). Data management was conducted with Filemaker Pro Advanced v. 11.4 (Filemaker Inc., Santa Clara, CA, USA). We estimated incremental cost and effectiveness on a per patient basis. Incremental cost was defined as the difference in overall average one-year cost per patient between study arms. The health effect was measured in terms of change from baseline in the annual risk of a cardiovascular event, so that incremental effectiveness is the difference in risk per patient, adjusted for baseline difference in risk [24]. In general, an intervention would be considered cost-effective in relation to the comparator if: (1) it cost less (the incremental cost is negative) and is more effective (the incremental health effect is positive) (i.e. it is dominant); or (2) it costs more and is more effective than the comparator, but society is willing to pay for the additional cost [25]. Stochastic analysis of uncertainty
To account for uncertainty due to sampling variation, we used a non-parametric bootstrapping analysis to generate a
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Cost-effectiveness analysis of pharmacist intervention in cardiovascular risk S. H. Simpson et al.
scatter plot of incremental cost and outcome on the costeffectiveness plane [25]. Based on that generated distribution, a cost-effectiveness acceptability curve (CEAC) was derived, indicating the probability of the intervention being costeffective at various levels of society’s willingness to pay per annual 1% change in cardiovascular risk. We generated 10 000 replications for the main analysis and 5000 replications for each of the ten imputed datasets, for a total of 50 000 replications in the sensitivity analysis. We estimated a cost-effectiveness threshold for the intervention in order to meaningfully interpret the CEAC. In a sense, this threshold represents the opportunity cost, relating to the health outcome foregone, by the reallocation of resources required to implement the intervention [26]. Following a recently published method, we estimated the threshold as the ratio of average cost to average health effect using the sample data of the control arm [27]. We assumed that the existing programme of usual care, represented by the control arm, is as efficient as the least efficient existing programme from which resources would be reallocated. This approach also allowed us to express the denominator of the threshold in terms of how the health outcome was measured in this trial [27].
Results We excluded 137 of 260 trial patients from the main economic analysis because they either did not return a survey containing information on healthcare service utilization or we were unable to obtain pharmacy refill data. The 123 evaluable patients included in the economic analysis were older than the remaining trial patients [mean ( SD): age 61.5 ( 10.9) years versus 56.9 ( 11.8) years, P = 0.0013]; however, there were no significant differences in sex, baseline UKPDS risk score or diabetes duration. Baseline patient characteristics were similar between the 65 intervention patients and 58 controls included in this analysis, suggesting that integrity of the original randomization was preserved (Table 2). There were 47 (38%) men, mean diabetes duration 5.6 ( 7.0) years, and UKPDS risk score 14.4% ( 10.0%). The predicted 10–year risk of a cardiovascular event decreased from a mean of 14.6% ( 10.1%) to 12.0% ( 7.6%) in the intervention group and from 14.2% ( 10.0%) to 13.4% ( 11.1%) in controls (P = 0.035 for the difference of differences). The annualized reduction in risk of a cardiovascular event observed after the one-year study was 0.33% ( 0.67%) in the intervention group and 0.06% ( 0.68%) in controls (between-group difference 0.26%; 95% CI 0.08%, 0.63%). Healthcare service utilization is reported in Table 3. On average, study pharmacists took 1.0 ( 0.3) hour to complete the baseline assessment and spent 2.0 ( 1.8) hours in follow-up visits with each intervention group patient (Table 3). During the one-year follow-up period, pharmacists contacted each intervention patient an average of
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Table 2 Baseline characteristics
Male, n (%) Age, years Duration of diabetes, years No CVD at enrollment, n (%) UKPDS risk score, 10-year % UKPDS risk score, annualized %
Intervention (n = 65)
Control (n = 58)
24 62.0 4.5 49 14.6 1.63
23 60.9 6.8 48 14.2 1.59
(37) (10.2) (3.9) (75) (10.1) (1.3)
(40) (11.6) (9.1) (83) (10.0) (1.3)
Data are reported as mean (SD) unless otherwise specified. All between-group comparisons are not statistically significant
Table 3 Health service utilization Resource item
Intervention
Intervention – pharmacist contact time Baseline assessment (h) 1.0 Follow-up visits (h) 2.0 Total time (h) 3.0 Specialist – cardiologist visits 0.12 Specialist – endocrinologist visits 0.20 Specialist – nephrologist visits 0.08 Specialist – ophthalmologist 0.65 visits* Sub-total specialist visits 1.18 Dietician visits 0.20 Nurse visits† 0.65 Optometrist visits 0.57 Podiatrist visits 0.48 Sub-total other healthcare 1.98 professional visits Emergency department visits 0.34 Inpatient stays 0.05
Control
(0.3) (1.8) (1.9) (0.48) (0.75) (0.37) (0.99)
– – – 0.24 0.28 0.03 0.83
(0.98) (0.79) (0.26) (0.80)
(1.66) (0.62) (1.39) (0.75) (1.85) (2.69)
1.55 0.28 0.93 0.47 0.12 1.81
(2.11) (0.62) (1.35) (0.57) (0.38) (1.76)
(1.33) (0.21)
0.24 (0.57) 0.10 (0.31)
All data are reported as mean (SD) per patient. *P = 0.040; †P = 0.036; all other between-group comparisons are not statistically significant.
6 ( 3) times by telephone and met with them in-person 2 ( 2) times. Intervention patients had fewer visits to ophthalmologists (0.65 0.99 visits per patient) and nurses (0.65 1.39 visits per patient) compared with controls (0.83 0.80, P = 0.040 and 0.93 1.35, P = 0.036, visits per patient, respectively). Although intervention patients had more visits to an emergency department (0.34 1.33 visits per patient) compared with controls (0.25 0.58 visits per patient), the difference was not statistically significant (P = 0.65). The mean annual cost for the pharmacist intervention was estimated to be $226 ( $143) per patient (Table 4). This cost was more than offset by savings in other variables, including medication costs, specialist costs and inpatient costs. Although there was an overall cost saving of $190 for the intervention group, the difference between groups was not statistically significant (95% CI –$1040, $668). Results of the cost–effectiveness analysis (Table 5) indicate the intervention was dominant compared to usual care
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because it cost less (–$190) and was more effective (0.26% greater reduction in annualized cardiovascular risk). Figure 1 presents a scatter plot for the joint distribution of incremental cost and incremental health effect from 10 000 bootstrap replications. The majority (66%) of these replications fell in quadrant IV, supporting the dominance of the intervention compared with usual care. The cost-effectiveness acceptability curve (Fig. 2) shows that, as society’s willingness to pay increases, the probability that the intervention is considered cost-effective reaches 95% at a relatively low level of about $4000 per 1% reduction in annualized cardiovascular risk. The cost-effectiveness threshold (society’s willingness to pay for a reduction of 1% in cardiovascular risk) was estimated to be $33 215 ($1993/ 0.06, control arm data from Table 5) and is shown as point A in Fig. 2. The probability that the intervention would be Table 4 Cost of resources used
Cost per patient* Intervention Intervention 226 Medications 896 Specialists 137 74 Other healthcare professional 142 Emergency department cost Inpatient 328 cost Total cost 1803
(143) (608) (193) (88)
Control – 914 (690) 179 (241) 63 (57)
Difference [95% CI]† (Intervention – Control) 226 –18 –42 11
– [–251, 215] [–119, 36] [–16, 38]
(568)
101 (244)
41 [–119, 200]
(1522)
735 (2213) –407 [–1080, 265]
(2232) 1993 (2620) –190 [–1040, 668]
*Costs are reported as mean (SD) per patient in 2014 Canadian dollars. †95% CI for between group differences are shown within brackets. The 95% CI for total cost was based on 10 000 bootstrap replications. All between-group comparisons are not statistically significant.
dominant or have an incremental cost-effectiveness ratio below this threshold is 99%. We conducted a sensitivity analysis using data from 258 of the 260 main trial patients. One control patient was excluded because they died during the main trial and one intervention patient was excluded because they returned a survey with health service utilization rates that were so high that we suspected errors in reporting. Multiple imputation was used to replace missing data and we observed similar results to our main analysis (Fig. 2 and Table 5).
Discussion We evaluated the economic implications of adding pharmacists to primary care teams using outcomes and healthcare utilization data from patients with Type 2 diabetes enrolled in a randomized controlled trial. Although the cost of the pharmacist intervention was offset by savings in other healthcare services, the cost difference between intervention and control groups was small and not statistically significant. Patients in the intervention group had a small but significantly greater reduction in their annualized risk of a cardiovascular event compared with controls. In the costeffectiveness analysis, the intervention dominated usual care in 66% of 10 000 bootstrap replications. When a societal cost-effectiveness threshold of $31 500 was considered, the probability that the intervention would be cost-effective was 99%. Our observation that adding pharmacists to primary care teams is a cost-effective strategy for managing patients with Type 2 diabetes and poorly controlled hypertension is consistent with other groups. For example, Lowey and colleagues demonstrated in an uncontrolled before–after study that, although a pharmacist-led outpatient clinic would cost over € 1900 (US$2574, C$2867) per person, participating in the clinic could reduce the patient’s predicted 10– year risk of cardiovascular disease by 3.6% and lead to a savings of approximately € 54 000 (US$73 160, C$81 486)
Table 5 Cost-effectiveness analysis
Main analysis (n = 123) Cost† Reduction in CV risk (%)‡ Cost per 1% improvement in risk Multiple imputation (n = 258) Cost† Reduction in CV risk (%)‡ Cost per 1% improvement in risk
Intervention
Control
Difference [95% CI]*
1709 (2117) 0.33 (0.67)
1889 (2483) 0.06 (0.68)
–180 [–987 to 634] 0.26 [0.083 to 0.63]§ na¶
2636 (2116) 0.34 (0.90)
2780 (2290) 0.11 (0.97)
–143 [–739 to 452] 0.21 [0.02 to 0.41]§ na¶
*95% confidence intervals for the incremental cost and incremental health outcome were based on 10 000 bootstrap replications for the main analysis and 50 000 replications for the multiple imputation analysis (10 imputed data sets and 5000 for each imputed data set). †Cost is reported as mean (SD) per patient in 2014 Canadian dollars. ‡Incremental health outcome reported as mean reduction in annualized UKPDS risk sore (SD) per patient. §Adjusted for baseline difference in CV risk between study arms. ¶Not applicable because the intervention is dominant.
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0
1000
QI
—1000 —2000
Incremental Cost †
2000
QII
QIII
—0.5
QIV
0.0
0.5
1.0
Incremental CV Risk (Health Effect) (%)† FIGURE 1 Bootstrap results on the cost-effectiveness plane based on 10 000 bootstrap replications. †Intervention minus control.
60
70
80
90
A
10
20
30
40
50
Main Analysis MI Analysis
0
Probability of Intervention Being Cost-Effective (%)
100
per event avoided [28]. In a retrospective matched-cohort study, Yu and colleagues observed that adding pharmacists to the diabetes management team dominated the control group because predicted 10–year costs were lower and intervention group patients had more quality adjusted life
years compared with controls [29]. These investigators used Markov models to extrapolate data collected during a oneyear observation period and found that the probability of the pharmacist intervention being cost-effective increased as the time horizon for the analysis was extended. In contrast to these studies, we used data collected during a randomized controlled trial and limited our observations to the one-year time horizon of the main study. There are several limitations to consider when interpreting our results. First, we used the UKPDS risk score and estimated an annualized reduction in risk for our effectiveness measure. The UKPDS risk equation was originally developed to predict 10–year risk of cardiovascular disease based on the patient’s current status and assuming a natural course of cardiovascular disease if left untreated [16]. Nevertheless, several other groups have also used changes in UKPDS risk score as a summary estimate for economic evaluations [28,29]. Second, our observations are limited to a one-year time horizon; therefore the long-term cost-effectiveness of adding pharmacists to primary care teams remains unclear. We believe, however, that the one-year improvement in UKPDS risk score may be a conservative estimate. In practice, it is likely that patients receiving pharmacist intervention would have ongoing assessments and improvements in cardiovascular risk factors. By contrast, prior studies have shown that, in the absence of ongoing care and interdisciplinary support, cardiovascular risk factors tend to
0
5000
10000
15000
20000
25000
30000
35000
40000
Willingness to Pay for a One % Reduction in CV Risk($) FIGURE 2 Cost-effectiveness acceptability curve. The main analysis was based on 10 000 bootstrap replications and the multiple imputation analysis was based on 5000 replications of the 10 imputed datasets, for a total of 50 000.
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remain suboptimal or continue to deteriorate over time in most patients with Type 2 diabetes [4,30]. Third, we based our main economic analysis on 123 patients with a complete set of information, only about half of our total trial enrolment. We believe this was a reasonable decision because this is a secondary analysis of a positive trial and a sensitivity analysis using multiple imputation to replace missing data produced results that were similar to our main analysis. Fourth, health utilization information was collected from patient self-report, which may affect accuracy of these estimates. However, we do not believe that there would be important differences in recall between groups and the data were collected and analysed without knowledge of allocation status. Last, these are within-trial economic analyses drawn from a single healthcare setting where all patients have universal healthcare coverage, and there might be some concerns about the wider generalizability of our findings. For example, the number of patients in one setting may not be sufficient to justify a full-time pharmacist and thus require consideration of the additional costs required to travel to multiple locations. In conclusion, this economic analysis suggests that adding pharmacists to primary care teams is a cost-effective strategy for reducing cardiovascular risk in patients with Type 2 diabetes – at the least, when considering a short, one-year time horizon. In most circumstances, and possibly over a longer follow-up period, this additional effort may also be cost-saving from a public payer perspective.
Funding sources
Operating grant funding was provided by the Canadian Diabetes Association, Institute of Health Economics, and Alberta Heritage Foundation for Medical Research (AHFMR). Dr Simpson was supported as a New Investigator by the Canadian Institutes of Health Research (CIHR) during the conduct of this study. Dr Majumdar is supported as a Health Scholar by the Alberta Innovates – Health Solutions (AIHS) and holds the Endowed Chair in Patient Health Management of the Faculties of Medicine and Dentistry and Pharmacy and Pharmaceutical Sciences, University of Alberta. Dr Johnson holds a Health Senior Scholar through the AIHS, and is Chair of the CIHR funded Alliance for Canadian Health Outcomes Research in Diabetes (ACHORD) (reference #: OTG-88588).
Competing interests
None declared.
Acknowledgements
The authors are especially grateful for the contributions of the two study pharmacists, Denise Nitschke, BSc(Pharm), CDE, and Shelley Tuchsherer, BSc(Pharm), CDE. We thank
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the staff at the Epidemiology Coordinating and Research (EPICORE) Centre for their support. We also thank the clinicians and staff at the 5 family medicine clinics in the Edmonton Southside Primary Care Network for working with us during the study.
References 1 Emerging Risk Factors Collaboration. Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med 2011; 364: 829–841. 2 Nathan DM, Meigs J, Singer DE. The epidemiology of cardiovascular disease in type 2 diabetes mellitus: how sweet it is . . . or is it? Lancet 1997; 350(Suppl 1): SI4–SI9. 3 Tan MH, MacLean DR. Epidemiology of diabetes mellitus in Canada. Clin Invest Med 1995; 18: 240–246. 4 Harris SB, Ekoe JM, Zdanowicz Y, Webster-Boagert S. Glycemic control and morbidity in the Canadian primary care setting (results of the diabetes in Canada evaluation study). Diabet Res Clin Pract 2005; 70: 90–97. 5 Leiter LA, Berard L, Bowering CK, Cheng AY, Dawson KG, Ekoe JM et al. Type 2 diabetes mellitus management in Canada: is it improving? Can J Diabetes 2013; 37: 82–89. 6 Gaede P, Vedel P, Larsen N, Jensen GV, Parving HH, Pedersen O. Multifactorial intervention and cardiovascular disease in patients with type 2 diabetes. N Engl J Med 2003; 348: 383– 393. 7 Rothman RL, Malone R, Bryant B, Shintani AK, Crigler B, Dewalt DA et al. A randomized trial of a primary care-based disease management program to improve cardiovascular risk factors and glycated hemoglobin levels in patients with diabetes. Am J Med 2005; 118: 276–284. 8 Gaede P, Lund-Andersen H, Parving HH, Pedersen O. Effect of a multifactorial intervention on mortality in type 2 diabetes. New Engl J Med 2008; 358: 580–591. 9 Simpson SH, Majumdar SR, Tsuyuki RT, Lewanczuk RZ, Spooner R, Johnson JA. Effect of adding pharmacists to primary care teams on blood pressure control in patients with type 2 diabetes: a randomized controlled trial. Diabetes Care 2011; 34: 20–26. 10 Ladhani NN, Majumdar SR, Johnson JA, Tsuyuki RT, Lewanczuk RZ, Spooner R et al. Adding pharmacists to primary care teams reduces predicted long-term risk of cardiovascular events in type 2 diabetic patients without established cardiovascular disease: results from a randomized trial. Diabet Med 2012; 29: 1433–1439. 11 Gilani F, Majumdar SR, Johnson JA, Tsuyuki RT, Lewanczuk RZ, Spooner R et al. Adding pharmacists to primary care teams increases guideline-concordant antiplatelet use in patients with type 2 diabetes: results from a randomized trial. Ann Pharmacother 2013; 47: 43–48. 12 Canadian Diabetes Association Clinical Practice Guidelines Expert Committee. Pharmacologic management of type 2 diabetes. Can J Diabetes 2008; 32(Suppl 1): S53–S61. 13 Canadian Diabetes Association Clinical Practice Guidelines Expert Committee. Vascular protection in people with diabetes. Can J Diabetes 2008; 32(Suppl 1): S102–S106. 14 Culleton B, Drouin D, Larochelle P, Leiter LA, McFarlane P, Tobe S. Treatment of hypertension. Can J Diabetes 2008; 32(Suppl 1): S115–S118. 15 Majumdar SR, Johnson JA, Bowker SL, Booth GL, Dolovich L, Ghali W et al. A Canadian consensus for the standardized evaluation of quality improvement interventions in type 2 diabetes. Can J Diabetes 2005; 29: 220–229.
905
DIABETICMedicine
Cost-effectiveness analysis of pharmacist intervention in cardiovascular risk S. H. Simpson et al.
16 Stevens RJ, Kothari V, Adler AI, Stratton IM. The UKPDS risk engine: a model for the risk of coronary heart disease in Type II diabetes (UKPDS 56). Clin Sci 2001; 101: 671–679. 17 Briggs A, Sculpher M. An introduction to Markov modelling for economic evaluation. Pharmacoeconomics 1998; 13: 397– 409. 18 Alberta Health. Drug Benefits List 2010. Available from: http:// www.health.alberta.ca/AHCIP/drug-benefit-list.html. Last accessed 11 March 2011. 19 Alberta Health. Care Insurance Plan Statistical Supplement: 20102011. Available from: http://www.health.alberta.ca/newsroom/ publications.html. Last accessed 25 January 2013. 20 Canadian Institute for Health Information. Comprehensive Ambulatory Care Client Tables 2011. Available from: http://www.cihi.ca. Last accessed 11 March 2012. 21 Canadian Institute for Health Information. Hospital Financial Performance (HFP) Indicators. Available from: http://www.cihi.ca. Last accessed 12 December 2012. 22 Canadian Institute for Health Information. Patient Cost Esimator: estimated average costs by CMG and age group, Alberta, 2008–09. Available from: http://apps.cihi.ca/MicroStrategy/asp/Main.aspx. Last accessed 15 March 2013. 23 Rubin DB Multiple Imputation for Nonresponse in Surveys. Wiley Classics Library. Hoboken, NJ: Wiley-Interscience, 2004.
906
24 Vickers AJ, Altman DG. Statistics notes: Analysing controlled trials with baseline and follow up measurements. British Medical Journal 2001; 323: 1123–1124. 25 Drummond MF, Sculper MJ, Torrance GW, O’Brien BJ, Stoddart GL. Methods for the Economic Evaluation of Health Care Programmes, 3rd ed. Oxford: Oxford University Press, 2005. 26 Claxton KP, Martin SO, Soares M, Rice N, Spackman E, Hine S et al. Methods for the Estimation of the NICE Cost Effectiveness Threshold. York: Centre for Health Economics, University of York, 2013. 27 Hyewon HL, Levine M. Determing the threshold of acceptability of an ICER when natural health units are used. J Popul Ther Pharmacol 2012; 19: e234–238. 28 Lowey A, Moore S, Norris C, Wright D, Silcock J, Hammond P. The cost-effectiveness of pharmacist-led treatment of cardiac risk in patients with type 2 diabetes. Pharm World Sci 2007; 29: 541–545. 29 Yu J, Shah BM, Ip EJ, Chan J. A Markov model of the costeffectiveness of pharmacist care for diabetes in prevention of cardiovascular diseases: evidence from Kaiser Permanente Northern California. J Manag Care Pharm 2013; 19: 102–114. 30 Johnson JA, Eurich DT, Toth EL, Lewanczuk RZ, Lee TK, Majumdar SR. Generalizability and persistence of a multifaceted intervention for improving quality of care for rural patients with type 2 diabetes. Diabetes Care 2005; 28: 783–788.
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