In the present study, we conducted a cost-effectiveness analysis of the implementation of a multidisciplinary healthcare programme for the secondary prevention of DRPs in patients attending an ED from a Catalan healthcare payer perspective. Specifically, the programme developed a set of interventions at different levels of healthcare (collectively referred to as ‘Medication Code’) with the objective of reducing the 30-day revisits of patients attended in the ED for DRPs caused by medicines from the Anatomical Therapeutic Chemical (ATC) categories A (Alimentary tract and metabolism), B (Blood and blood forming organs) or C (Cardiovascular system). These interventions included actions aimed at improving the patient's chronic prescriptions (interview with the patient and a review of their chronic medication treatment), therapeutic adherence (including the delivery of written information on the medication treatment plan and a telephone consultation 48 h after discharge), and coordination between different levels of healthcare (including sending an email to the next healthcare provider explaining the reason for the consultation any changes in the medication treatment). Patients in the control group received the standard care in ED, consisting of medication review and prescriptions validation.
For this purpose, an economic model was developed to determine the effects on the short-term (time horizon: 30 days) implementation of the programme in a 644-bed public tertiary university hospital that attends 140,000 emergencies per year. The development of the model was based on the results of the ‘Medicine Code’ Clinical Trial (Clinical Trials.gov: NCT03607097) [8]. According to the results of this clinical trial, the population that consults the hospital emergency services for DRPs is mainly aged (average age: 80.3 (12.4) years), polymedicated (median: 9 (IQR:6–12)), being antithrombotic drugs the majority involved in these episodes. The model considered the context of the National Health System and included only direct medical costs (Table 1). The costs assumed for the implementation of the programme included the salaries of two full-time clinical pharmacist specialised in the management of patients with DRPs.
Table 1
Costs and variables considered in the model.
| Intervention Group | DRP Code | References |
ED assistance fee | 185 | 185 | [18] |
Hospital admission fee | 3000 | 3000 | [19] |
Annual healthcare specialist salary (€) | 0 | 59,284 | [19] |
Annual cost per all DRP code personnel (€) | 0 | 118,568 | |
ED Revisit | 14.9% | 18.1% | [8] |
Hospital readmission | 10.4% | 7.3% | [8] |
Mortality | 4.7% | 4.7% | [8] |
Hospital-days | | | |
Annual ED Visits | 144000 | 144000 | [20] |
% DRP as cause of ED visit | 21.0% | 21.0% | [9] |
% DRP caused by ATC groups A, B or C | 36.4% | 36.4% | [9] |
% Patients lost | 30.0% | 30.0% | |
Life of years Gained | | | |
Mean age | 80.1 | 80.1 | [8] |
Life expectancy (years) | 83.6 | 83.6 | [10] |
DRP: Drug-related problems; ED: Emergency department; ATC: Anatomical therapeutic classification |
According to the results published in the literature, the frequency of ED visits owing to DRPs is 21%, of which 36.4% are caused by medicines from therapeutic groups A, B, or C [9]. According to the results of the clinical trial, the implementation of a health programme for patients with DRPs reduces the frequency of 30-day ED revisits by 17.6% (14.9% vs. 18.1%) and 30-day readmissions by 29.8% (7.3% vs. 10.4%)8. For the present analysis, a patient identification loss rate of 30% was assumed.
A decision tree was developed to simulate the clinical progression of patients attended in the ED (Fig. 1), according to which patients attended for DRPs for medicines in groups A, B, or C could be either treated or not by the ‘Medication Code’ programme. To simplify the model, the DRPs were considered mutually exclusive. As the study determined the effect of the intervention programme after hospital discharge, the possible reduction in the patient's length of hospital stay after the initial intervention programme was not considered in the model.
An incremental cost-effectiveness ratio (ICER) analysis was performed on the ability of the programme to reduce ED attendance. The ICER was calculated based on the costs assumed for the implementation of the programme in relation to the ED revisit cases with and without the implementation of the programme. The cost per life year gained (LYG) was calculated based on the prevention of death after a revisit due to DRPs, considering a mortality attributable to the admission for DRPs of 4.7% and a mean age of ED attendance of 80.3 years according to the results of the clinical trial7, being the life expectancy of 83.8 years in Spain [10].
The final model was calculated using Microsoft Excel v.14.5.9. A univariate sensitivity analysis (tornado diagram) was performed to establish the short-term robustness of the model to variables with uncertainty, including the risk of revisit and readmission (50%), costs associated with revisits (20%), number of annual ED visits (5%), patient identification loss rate (50%), as well as the percentage of visits caused by DRPs in A, B, or C groups (20%).
In addition, a probabilistic sensitivity analysis was performed to analyse the cost per prevented DRPs and per LYG. The variables included in the analysis were the risk of revisit and readmission (50%), the costs associated with these (20%), the number of annual ED visits (5%), the patient identification loss rate (50%), as well as the percentage of visits caused by DRPs in groups A, B, or C (20%). The variation in mortality related to DRPs was considered to be 20%. The analysis was performed using a Monte-Carlo simulation on the included uncertainty variables, simulating a cohort of 1,000 patients admitted to the ED unit, either after the implementation of the program or without it. Each point estimate contains random values within the considered range. All variable distributions were considered to represent beta distributions. The considered distribution values are presented in Table 2.
Table 2
Probability values and fixed applied during probabilistic sensitivity analysis.
Name | Data distribution | Point estimate of probability | Initial value considered | Range |
Hospital readmission reduction | beta | 29.8% | 50,0% | 14.9–44.7% |
Revisit reduction | beta | 17.6% | 50,0% | 8.8–26.4% |
Annual visits to ED | beta | 144,000 | 5,0% | 136.800-151.200 |
Annual visits to ED caused by DRP | beta | 21,0% | 20,0% | 16.8–25.2% |
DRPs caused by drugs from ATC groups A, B or C | beta | 36.4% | 20,0% | 29.1–43.6% |
DRPs mortality | beta | 4.7% | 20,0% | 3.8–5.6% |
Patients Lost | beta | 30,0% | 50,0% | 15.0–45.0% |
Annual Cost of DRP-Code implementation | uniform | 89,000 € | * | 89.000 € |
Cost per ED visit | uniform | 185 € | * | 185 € |
Cost per hospitalization | uniform | 3,000 € | * | 3,000 € |
1DRP: Drug-related problem; EDD: Emergency Department |