ELECTROQUÍMICA Y MEDIO AMBIENTE
11.5.1.2. Reducciones directas
a Pharmaceutical Care Research Group, Pharmaceutical Sciences, University of Basel,
Switzerland
b Institute of Pharmaceutical Medicine (ECPM), University of Basel, Switzerland
c Division of Substance Use Disorders, Psychiatric University Clinics of Basel, Switzerland
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Abstract
Background and Objectives: The number of older patients with opioid-assisted therapy
(OAT) and polypharmacy is rising globally. Alternative supply models to assist these patients with their medication management and support medication adherence are needed. Higher adherence has been associated with reduced overall healthcare costs and reduced
hospitalization risk. However, evidence about cost-effectiveness of adherence-enhancing interventions is sparse. Electronic medication management systems might offer a benefit to older drug users receiving polypharmacy. We aimed to a) perform a cost-of-illness (COI) evaluation of patients receiving OAT and polypharmacy and to b) compare a novel electronic medication supply model to usual care.
Methods: We estimated COI from a societal perspective for eligible patients of an outpatient
addiction service (OAS) during one year. Direct medical costs for each patient were obtained from health insurance records for the year 2014. Direct non-medical and indirect costs were estimated based on a survey of patients’ caregivers. For the cost-comparison model, we calculated the mean costs for the novel supply model, estimated changes in direct medical costs based on available literature, and compared costs to usual care. A sensitivity analysis was performed based on the variability of cost items for the novel supply model.
Results: We included 29 patients (mean age of 47 ± 6.3 years, 6 ± 2 medications, 48.3%
female) and health insurance records were available for 21 patients. None of the patients pursued a paid employment and 86% received disability benefits. Total yearly cost per patient was 109‘611 Swiss Francs (SFr), with direct costs accounting for 30% of the total costs. With the novel supply model, total yearly costs per patient increased by SFr 2’509 for repackaging of medication, leasing of the dispenser, and time spent for travel, refill, and support (+ 2.2% compared to base case). Sensitivity analysis showed that the results were robust and overall costs did not substantially change with various estimations.
Conclusion: Cost-of-illness for older patients with OAT and polypharmacy is high, especially
when considering indirect costs, such as productivity loss due to disability. A novel electronic medication supply model increases overall costs marginally, but might offset the costs of more expensive alternatives, such as nursing homes. Further studies should evaluate the long-term benefits and cost-effectiveness of the novel supply model.
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Introduction
Healthcare costs are rising worldwide. A major driver of this development is the demographic shift to an older multi-morbid population. Globally, mental and substance use disorders were the leading cause of years lived with disability in 2010252. Up to 50% of opioid-dependent
patients suffer from one or more psychiatric comorbidities253. Illicit drug users have higher
rates of emergency medical visits and hospitalization than other high risk groups254,255. In
2002, hospitalization costs of opioid-dependent patients in the United States (US) were US$ 13’393 in a two-year period, 2.5 times higher than those of average patients256. Alongside the
trend in the general population, the age of patients with opioid-assisted therapy (OAT) is also increasing183-185. The concomitant increase in multi-morbidity leads to an even higher
potential for negative health outcomes for patients with OAT. Older drug users are likely to suffer from the accumulated physical and mental health effects of polysubstance use, overdoses and infections257. On the one hand, drug use causes premature ageing of the
body258,259. On the other hand, effective therapies extend lives. Consequently, older drug users
become prone to conditions that normally occur with greater frequency among much older people, such as alcohol- and tobacco-related illnesses, including diabetes, hypertension, osteoporosis, arthritis, cardiovascular conditions, and chronic lung disease. In addition, older drug users may also be affected by progressive conditions that may take decades to cause significant illness or death: A study estimated that in 2010, 2.1% of opioid users were HIV- positive and 43% had chronic hepatitis C virus (HCV) infection260. Pharmacotherapy has
become standard in the therapy of most chronic conditions. Consequently, many older and thus multi-morbid patients with OAT also take multiple chronic medications. In a sample of 154 opioid-substituted patients from an outpatient addiction service (OAS) in Basel,
Switzerland, 58.4% used 3 or more active ingredients in 201393. Although many studies have
shown clinical and economic benefits of pharmacotherapy when used consequently, adherence to medication is generally only around 75% and even lower with psychiatric illnesses38. Opioid-dependent patients are at high risk for non-adherence due to high
prevalence of psychological problems, substance abuse, unemployment, low socioeconomic status, and low social support38,211,215,216,261,262.
Low medication adherence has been associated with increased morbidity, mortality, and costs. The world health organization estimated the annual cost of medication non-adherence at US$ 300 billion world-wide19. Higher adherence has been associated with reduced overall
healthcare costs and reduced hospitalization risk for diabetes, hypertension,
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cost-effectiveness of adherence-enhancing interventions43,263,264. Recently, electronic
medication management aids (MMAs) emerged, reminding patients with acoustic or visual alerts to take their medication, dispensing the right medication at the right time, and tracking each event. A review of telemedicine and telecare for older patients found mostly positive results, especially for behavioral outcomes such as adherence265. Furthermore, the “Safe at
home” project evaluated assistive technology to improve the independence of older patients and reported net savings of over £ 1.5 million during 21 months for 233 service users compared with 173 non-users266.
Rationale
Opioid-dependent patients pose a high burden on health-care expenditures, and the increasing age and complexity of this population will likely lead to additional costs.
Alternative supply models to assist patients with their medication management and support medication adherence are needed for older patients with OAT and polypharmacy. Electronic medication dispensers might offer a benefit to older drug users receiving polypharmacy. First, a remote support assures independence of the patients. Second, real-time monitoring assures high medication adherence without the need of too many visits to a dispensing point. A novel remote electronic medication supply model was feasible to maintain medication supply and assure correct implementation of dosing regimens of more than 90% for such patients. The sustained persistence and consistent implementation accomplished with this model may reduce healthcare costs and the savings might compensate for the additional costs of the novel model.
Aims
Our goal was to analyze the cost aspects of the medication supply for opioid-substituted patients. We aimed to:
Perform a cost-of-illness evaluation of patients receiving OAT and polypharmacy (base case)
establish a cost-comparison model for the novel supply model compared to standard medication supply (base case)
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Methods
Study design and setting
First, we performed a COI study for patients with OAT and polypharmacy from a societal perspective (base case). We considered tangible costs using a prevalence-based approach and estimated direct and indirect costs during one year. Second, we generated a cost-comparison model for the novel supply model versus the base case. The setting was the outpatient addiction service (OAS) of the Psychiatric University Hospital in Basel, Switzerland. The OAS offers treatment to patients with substance use disorders, mental and somatic disorders, and social impairments and problems. Patients are treated by a multidisciplinary team consisting of professionals from the fields of medicine, nursing, social work and psychology. Up to 100 patients per day visit the public dispensing point of the OAS to obtain their medication in the traditional way. Patients take their (substitution) medication on site under supervision at least once per week and receive additional doses and medications for take-home. Medications are either prepared in advance or immediately before dispensing. In some cases, the OAS prepares and delivers medications including OAT for patients living in supervised settings (Figure 36). With the novel supply model, patients receive OAT at the OAS once per week, while all other medications are supplied approximately three-weekly in unit-dose pouches with an automated electronic dispenser located at the patient’s home. The dispenser is an electronic medication management system described elsewhere in detail94. Briefly, it
dispenses pre-packed medication according to a schedule and remotely monitors medication retrievals.
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Figure 36: The three possibilities of the medication process at the OAS
Target population
Patients were included in a two-step process. First, all patients of the OAS were screened in a pseudonymized database for the number of medications. Patients receiving more than 3 medications per day were identified and included based on the following criteria:
reading and writing literacy in German
stable housing situation in canton Basel-Stadt and adjoining municipality polymedication (treatment with more than 3 drugs per day)
insured with a Swiss health insurance provided signed written consent
Measures
Direct medical costs (Swiss Francs, SFr) were obtained for each patient from health insurance records for the year 2014. We differentiated between hospital costs, psychiatric treatments (including OAT and other medications dispensed in the OAS), other medical services,
pharmacy costs, laboratory tests, and home care. Costs for repackaging of medication for the novel supply model were derived from the collective remuneration agreement between the
Patient collects medication at OAS
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Swiss pharmacist association and health insurers (tariff “Wochendosiersystem”, LOA IV). For direct non-medical costs of the traditional medication supply, we measured the time
(minutes) necessary for dispensing medications in the OAS. Time spent between patients advancing to the counter and their departure was measured with a stopwatch during one day for each counter. Dispensing of prepared medication or interruptions, such as alcohol breath tests, were noted for each measurement. Medication preparation time for patients receiving pre-prepared medications was measured during four different days. Direct non-medical costs for the novel supply model were estimated by measuring time spent for travel and refills (two patients), as well as support (four patients) between November 2013 and April 2015. Time-units were converted to monetary costs using hourly wages of health-care
professionals with no management function according to the Swiss federal statistical office for 2012267. Costs of the dispenser were based on an annual fee paid to the supplier
(Innospense BV, The Netherlands).
A questionnaire that was distributed to caregivers captured information about individual patients in order to calculate direct non-medical costs and indirect costs. We questioned the caregivers and not patients to avoid social desirability bias. We contacted patients in case of missing information. Layout, comprehensibility, and completeness of the questionnaire were assessed in a pilot with 4 PhD students of the Pharmaceutical Care Research Group, 2 Master students, and 2 caregivers from the OAS. The final questionnaire included 5 questions and took 5 minutes to answer. Questions 1-4 covered direct non-medical costs (frequency of visits to the OAS per week, preparation of medications in advance, travel time from patient’s home to OAS and means of travel, and support with medication management at home) and question 5 covered indirect costs (profession, employment, working ability, social benefits). Together with the questionnaire, caregivers were asked to provide medication lists and diagnoses for each patient to verify the inclusion criteria.
Indirect costs included productivity losses (human capital method) and disability/social benefits in Swiss Francs. Gross monthly wages were obtained from the Swiss federal statistical office for 2012267,268. Information about disability benefits and extraordinary
benefits were obtained from an information sheet of the service point of the old age, disabled and survivors' social security system in collaboration with the Federal office for social insurance269. Information about social benefits was obtained from the Swiss conference for
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Analysis
Data were analyzed with SPSS® Version 22 (Statistical Package for the Social Sciences, IBM, Armonk, New York - USA). We calculated means and medians, minimum, maximum, and standard deviations for descriptive variables. We applied Mann-Whitney U-Test and chi- square tests for comparisons of two independent groups and Spearman tests for correlations. A p-value < 0.05 was considered significant.
For the cost-comparison model, we calculated the mean costs for the novel supply model and performed a sensitivity analysis by adding and subtracting one standard deviation from individual cost items (i.e., travel, refill, and support). We assumed that costs for some
elements of direct medical costs (i.e., hospital costs, other medical treatments, and laboratory tests) would decrease, while costs for pharmacy-dispensed medications would increase. We excluded psychiatric treatments from this assumption, because these included OAT, which would not change with the novel supply model. A study assessing the association between medication adherence and healthcare costs estimated a gross reduction of medical costs by 20% and an increase of medication costs by 45% for perfect adherence versus various levels of non-adherence223. We therefore calculated our cost-comparison model with these
estimations and assumed that indirect costs remained unchanged with the novel supply model.