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Cost savings from medication reviews in community pharmacies for nursing home residents in Estonia: a case study

BMC Health Services Research volume 24, Article number: 1119 (2024) Cite this article

Abstract

Background

The aim of this study is to assess the cost savings from medication reviews conducted for individuals living in nursing homes in Estonia. Medication reviews performed as part of the automated dose dispensing (ADD) service by community pharmacies might help identify suboptimal medicine regimens.

Methods

We use a case study approach to identify suboptimal use of medication in treatment plans and estimate the potential cost saving from medication reviews. To achieve this, we assess 101 treatment plans submitted for medication review by nursing homes in Estonia between 2021 and 2023. Additionally, we run OLS regressions to identify the most important determinants of medication cost savings.

Results

We estimate an average direct cost saving of €43.62 per patient per year, which corresponds to 8.27% of the average annual medication costs. If medication reviews were conducted for all elderly individuals over 75 years old who use six or more prescription medicines, nearly 2% of Estonia’s pharmaceutical budget could be saved. Regression analysis indicates that the most significant contributors to these cost savings are suboptimal use of generics, incorrect dosages (too high), and the elimination of incorrect medications.

Conclusions

Our study suggests that annual medication reviews conducted as part of the ADD service might help reduce medication expenditure when offered to a wider public.

Peer Review reports

Background

Introduction

Individuals over 65 years old are at high risk of adverse drug events with age, comorbidities, polypharmacy, anticoagulants and cognitive problems being major risk factors of adverse drug events [1]. The risk of adverse drug events increases sharply with the prescription of more than nine medications [2]. Nursing home residents often have more than nine medications and have several active medical diagnoses [2, 3]. Hence, drug-related problems are particularly prevalent in nursing homes, specifically due to the prescription of potentially inappropriate medication [4], which has been shown to be associated with adverse drug events, hospitalizations and higher total medication costs [5,6,7,8].

Optimizing the prescribing practice for elderly, including the nursing home residents, is of major importance. Medication review is a tool to assure optimal medication use, a pharmacist-led multidisciplinary activity which might improve patient outcomes and reduce healthcare costs. The latest guiding principles by the European Directorate for the Quality of Medicines & HealthCare emphasize the role of pharmacists in providing medication reviews as a vital component of pharmaceutical care [9].

In Northern-Europe, medication reviews are often conducted for patients using the automated dose dispensing (ADD) service offered by community pharmacies [10, 11]. This service is typically offered for specific patient groups such as nursing home residents over 75 years old who use six or more prescription medicines suitable for automated dispensing [11]. For example, in Finland, medication reviews for the above patient group are conducted before initiating the ADD service and then once per year; a practice encouraged by authorities to ensure optimal medication use and supported by financial incentives [11].

In Estonia, as of 31 July 2023, Apotheka is the only community pharmacy in Estonia which conducts medication reviews as part of its ADD service. The ADD pharmacy at Apotheka conducts advanced medication reviews as defined by the Pharmaceutical Care Network Europe [12] — an approach adopted as part of a professional non-binding standard in Estonia. During the review process, the pharmacist assesses each treatment plan for possible interactions, side effects, and suboptimal use, including suboptimal generic use. A thorough medication review is conducted for each new patient (first-time service recipient); during 90% of these reviews the pharmacist consults the patient’s physician or nurse as well.

Until now, the economic impact of medication reviews conducted as part of the ADD service for nursing home residents in Estonia has not yet been assessed—a service that nursing homes can independently choose to adopt [8, 11, 13]. The purpose of this study is to measure and evaluate the economic impact of medication reviews performed by pharmacists as part of the ADD service in Estonia. In particular, we aim at assessing whether medication reviews, performed in community pharmacies as a part of the ADD service, is associated with lower medication costs among patients living in nursing homes in Estonia. Moreover, we aim at identifying which type of suboptimal medication use results in the largest cost savings.

Benefits of medication reviews

Extensive evidence in the literature supports the positive impact of medication reviews across diverse settings (hospital vs. community pharmacy), formats (prescription review vs. clinical medication review), and quality levels (basic, structured, comprehensive). Pharmacist-led medication reviews resulted in lower blood pressure and low-density lipoprotein levels, reduced the probability of potentially inappropriate medication, decreased the probability of all-cause mortality and falls, and was associated with significant cost savings in the majority of the studies [6,7,8, 14, 15]. Nevertheless, the evidence on the effectiveness of medication reviews is not fully convincing. Some systematic reviews found no significant effect on all-cause emergency hospital admissions, mortality, health-related quality of life and healthcare costs [14, 16, 17]. All in all, empirical evidence, even if less robust, generally suggests that medication reviews conducted for elderly, including the nursing home residents, deliver benefits in terms of patient outcomes and healthcare cost. This conclusion is consistent with a narrative review, which also finds that that clinical medication reviews for older people are probably of value and may be cost effective [18].

When looking at nursing home residents only, empirical evidence consistently shows that medication reviews conducted by pharmacists result in significant cost savings [8, 19, 20]. For example, in a systematic review, the authors found that pharmacist-led medication reviews consistently led to reduced medication or treatment costs per resident across various studies [8]. Recently, the positive impact of multidisciplinary medication review on medication costs for nursing home residents was also documented in France [20]. The authors estimated a mean medication cost saving of 45.85% (€226) per patient per six months from the nursing home perspective.

Long-term care expenditures in Estonia

By 2050, it is estimated that one third of Estonians will be aged over 65. Currently, up to 40,000 Estonians live with severe activity limitations requiring 24-hour general care, and the proportion of these people increases as the population ages [21].

Long-term care expenditures were 1.5% of the GDP on average in the 32 OECD countries in 2020, while it is only 0.7% in Estonia [22]. Public sector coverage of long-term care costs in Estonia is 60%, lower than the 80% average in other EU countries [22]. To address the funding gap in long-term care, a reform was introduced as of July 1, 2023. The care home fee is now split between the local authority and the individual providing better access to care home [21].

In 2021, around 15% of the total healthcare costs paid by the Estonian Health Insurance Fund were allocated to medicines [23]. Given the size of healthcare budget spent on medicines, medication optimization is vital both at micro and macro level.

Methods

Research design

We use a single-case design, a widely used evaluation method that rigorously assesses the outcome of an intervention, even with a relatively small sample size [24]. In particular, we assess the impact of medication reviews offered as part of the ADD service on medication costs of patients living in nursing homes in Estonia. We aim to determine if the medication review conducted as part of the ADD service leads to reduced medication costs, and if so, identify which type of suboptimal use is associated with the greatest cost savings. Figure 1 presents an overview of our research methodology.

Fig. 1
figure 1

Research design for assessing the impact of medication reviews

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We expect that if the prescriptions are taken to a pharmacy offering medication reviews, then the cost of the treatment plan would have been lower for two main reasons:

  1. 1)

    In Estonia, the pharmacy offering medication reviews as part of the ADD service has the highest percentage of medicines sold under the reference price. The ADD pharmacy selects the cheapest medication possible for each active substance [25, 26].

  2. 2)

    Empirical evidence shows that medication reviews conducted for nursing home residents lead to significant costs savings in several countries across the globe [6, 8, 19, 20]. In Europe, a medication cost saving in a range of 6.87-45.85% has been documented [20, 27, 28].

Data

Sampling

The sample consists of individuals who used the ADD service within the period of January 2021 and February 2023 for the first time. Hundred and one nursing home residents were included in the sample from five nursing homes from the ADD database of Apotheka. The nursing homes were selected by the first author and the pharmacist being responsible for the ADD service. The selection criteria were developed through a consensus-based approach. The selection criteria included geographic coverage, type of the service offered by the nursing homes, and the date when the nursing home used the ADD service for the first time. Each nursing home in the sample was general care service provider with several locations in Estonia, and provided onsite nursing care services.

All patients from the selected nursing homes were included in the sample. Afterwards, the time of the first medication review was identified for each patient in order to compare the treatment plans before and immediately after the review. Pharmacists review the treatment plan only when the ADD service is requested from Apotheka. The treatment plan immediately following the delivery of the first ADD service reflects the revisions made by a clinical pharmacist. These revised treatment plans are then validated and dispensed as part of the ADD service.

Classifying suboptimal medication use

As a next step, two pharmacists manually coded the reasons for the changes in the treatment plans by indicating the type of suboptimal medication use. Suboptimal use of medication refers to a situation in which a medication is used in a way that is not optimal for the patient, either because the medication is not the best choice for the patient’s condition or because the dose, frequency, or duration of use is inappropriate. Suboptimal medication use is a common phenomenon among older adults [29, 30]. Suboptimal use of medication can lead to poor health outcomes, increased risk of adverse effects, and increased healthcare costs [31, 32].

The coding was performed by the pharmacists independently; in case of inconsistencies a consensus was reached. Edited treatment plan data was retrieved from the pharmacy software NOOM into an Excel worksheet. The treatment plans were anonymous; they did not include any personal identification details. The anonymous data records included only two patient attributes: age and gender. All patient-related information was treated in accordance with national and international regulations as specified in the ’Principles of customer data processing in Apotheka pharmacies’ [33]; principles which have been developed in accordance with the rules of personal data protection and regulate the conditions for data processing of customers of Apotheka, including Apotheka e-pharmacy.

The type of suboptimal medication use has been identified and coded as reported in Table 1. This classification system relies extensively on the classification of drug-related problems developed and regularly reviewed by the Pharmaceutical Care Network Europe (PCNE) [34]. We have thoroughly assessed the PCNE classification and adjusted it to meet our needs. Note that the classification shown in Table 1 is very similar to the validated DOCUMENT classification system developed for identifying potential drug-related problems as well [35, 36]. For identifying potentially inappropriate medications and drug-drug interactions, we used a variety of databases, including Inxbase, drugs.com, systems developed internally by Apotheka, as well as information (e.g., SPCs) from the Ravimiregister, the Register of Medicinal Products in Estonia.

Table 1 Classifying suboptimal medication use
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Medication cost

In order to evaluate the medication cost before the medication review, assumptions were made. First, we estimated the cost saving per patient per year by assuming that the patient would have continued with the same suboptimal treatment plan without any adjustment throughout the year. Second, we had to make assumptions due to the unknown brand name of the medication the patient would have taken if they had visited a pharmacy that does not offer medication reviews. In particular, prescription medicines are prescribed by the active substance, so patients can choose from a variety of brands according to their preferences and the medication in stock. To estimate which brand the patient would have bought from a pharmacy, the average price per tablet was calculated for each active substance in the patients’ treatment plans before the medication review. For a particular active substance all brands were considered, and the weighted average price per tablet was calculated using sales data from 83 pharmacies around Estonia, excluding the ADD pharmacy at Apotheka. A 3-month period was selected as the reference period in order to exclude the effect of price differences and supply chain disruptions.

Finally, when extrapolating the medication cost savings documented for the 101 nursing home residents to all nursing home residents in Estonia, we assumed these cost savings are representative of the entire nursing home population.

Regressions

To identify the most important determinants of medication cost savings, we run OLS regressions. The dependent variable is the cost saving, that is, the change in the treatment cost. When calculating the treatment cost, we consider the retail price of the medications at the pharmacy counter including margins and value-added taxes. The independent variables include the manually coded reasons for the change in the treatment plans—the types of the suboptimal medication use. Control variables include the age and gender of the patient. The regression equation can be written as follows:

$$\eqalign{ Cost{\mkern 1mu} savin{g_i}{\mkern 1mu} = & {\beta _0} + {\beta _1}{\rm{*}}Supplydisruptio{n_i} + \cr & {\beta _2}{\rm{*}}Polypharmac{y_i} + \cr & {\beta _3}*Suboptimal\_generic\_us{e_i} + \cr & {\beta _4}{\rm{*}}Wrong\_dose\_hig{h_i} + \cr & {\beta _5}*Wrong\_dose\_insufficien{t_i} + \cr & {\beta _6}{\rm{*}}Medicine\_missin{g_i} + \cr & {\beta _7}{\rm{*}}Number\_med\_adde{d_i} + \cr & {\beta _8}{\rm{*}}Wrong{\mkern 1mu} medicatio{n_i} + \cr & {\beta _9}{\rm{*}}Number\_med\_eliminate{d_i} + \cr & {\beta _{10}}*Prescription\_missin{g_i} + \cr & {\beta _{11}}{\rm{*}}Wrong\_intake\_tim{e_i} + \cr & {\beta _{12}}*{\rm{Wrong}}\_{\rm{intake}}\_{\rm{metho}}{{\rm{d}}_i}{\rm{ + }} \cr & {\beta _{13}}{\rm{*}}Othe{r_i} + {\beta _{14}}{\rm{*}}Ag{e_i} + {\beta _{15}}{\rm{*}}Gende{r_i} + \varepsilon \cr}$$
(1)

In Eq. 1 Cost saving is the change in the treatment costs resulting from the medication review; β0 is a constant; β1,β2,β3,…., βn are the regression coefficients of the independent and control variables, while ε is the error term. The independent variables are defined and explained in Table 1. All but two independent variables are dummy variables, taking the value of 1 if yes, and 0 otherwise. Two variables (number of medications added and number of medications eliminated) are categorical variables. The control variables include two key demographic characteristics of the patients (age and gender). The gender is a binary variable (male/female), while age is a categorical variable.

In the main regression, we exclude the two maximum outliers. We run three robustness checks. First, we run the OLS regression after removing one additional outlier, the minimum value. Second, we exclude the four maximum outliers (instead of two as in the main model). Finally, we run the regression using data of 50 randomly selected patients.

Results

Descriptive statistics

The nursing homes in the sample were located all around Estonia. The sample of nursing homes can be considered as representative in terms of geographical coverage and type of service provided. The sample population represents around 1% of those receiving nursing home care in Estonia [40]. The demographic characteristics of the sample population are as follows: 74% female and 26% male with an average age 83. In the sample, females are slightly overrepresented, while males are slightly underrepresented; 66% of the patients living in nursing homes in Estonia are female, while 34% are male [40]. The mean age of the sample population is slightly higher than the mean age of the population living in nursing homes (83 vs. 80 years) [40].

The box plot of the dependent variable (cost saving) is shown in Fig. 2A. For the 101 patients in the sample, the mean value of the cost saving is €52.44 per annum by assuming that the patient would have continued with the same suboptimal treatment plan throughout the year. The maximum cost saving achieved is €515.46, while the maximum cost incurred is €137.1. In the former case the treatment cost after the medication review was by €515.46 lower, while in the latter case by €137.1 higher. The standard deviation of the annual cost saving is €91.14. As shown in the box plot, there are a few outliers. If two outliers from the upper end are excluded (cost savings of €515.46 and €462.42), the distribution of the cost saving is shown in Fig. 2B. In this case, the mean value of the cost saving is €43.62 per annum.

After excluding the two maximum outliers the mean and median annual medication costs are €527.34 and €432.84, respectively. Therefore, the estimated annual cost saving of €43.62 corresponds to 8.27% of the average annual medication costs and 10.08% of the median medication costs, respectively.

Fig. 2
figure 2

A Box plot of the cost saving. The boundaries of the box plot are the first quantile (Q1=€10.14) and the third quantile (Q3=€75.90), with the horizontal line drawn in the middle being the median cost saving (€31.86). The interquartile range (Q3-Q1) is €65.76 The highest point of the upper whisker represents the maximum (Q3 + 1.5* Interquartile range = €174.54), while the lowest point of the lower whisker represents the minimum (Q1–1.5* Interquartile range = €-88.5), after excluding the outliers. In the figure, outliers (black dots) are plotted beyond the whiskers. B Distribution of the cost saving. Histogram of 99 patients after excluding the two maximum outliers (cost saving of €515.46 and €462.427) from the upper end

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Table 2 shows the reasons for changes in the treatment plans and their frequency. The most common reasons for the change include suboptimal use of generics, incorrect intake times, excessively high doses, and the need to discontinue a medication.

Table 2 Reasons for changes in the treatment plans and their frequency (N = 101 patients)
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Tetrachoric correlation was used to calculate the correlation between the binary categorical independent variables [41]. The tetrachoric correlation matrix showed that all but one correlation coefficients are below 0.6, and hence the variables can be added to the regressions at the same time. The correlation was strong between the variables of ‘Other, please specify’ and ‘Supply disruption’ with the correlation coefficient being 0.78. From these two highly correlating variables the former was excluded from the regressions.

Regression results

The regression results from the main regression are shown in Table 3. In this regression specification, the two maximum outliers are excluded. At a 5% significance level, three types of suboptimal medication use are significantly associated with the cost saving resulting from the medication review conducted by Apotheka: the presence of suboptimal generic use; if there was a medication which was prescribed in a too high dose; and the number of medications being inappropriate for the patient, and hence excluded from the treatment plan. If the patient did not have the generic brand in the treatment plan although there was a lower-cost generic medication available with the same active substance, then the medication cost for two months was by €9.32 higher compared to the case when the patient had the particular generic brand in the treatment plan. When the patient had a medication where the dose was too high in the treatment plan, then the treatment cost for two months was by €5.33 higher compared to the situation in which the dose was set as optimal. When the treatment plan included medications being inappropriate for the patient, then one unit increase in the number of medications eliminated (e.g., from 0 to 1) resulted in €4.77 higher medication cost in the next two months compared to the base case.

Table 3 Regression results
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Table 3 also includes the regression results from the three robustness checks. All in all, our results are robust. The robustness checks confirm that suboptimal generic use and overdosing are significantly associated with higher medication costs before the medication review. These two variables are significant (albeit only at 6.1% level) even when half of the patients are removed. The number of medicines eliminated is significant in two out of four model specifications. Medicines might be eliminated for a number of reasons: harmful interaction related to polypharmacy, medication being inappropriate for the patient’s condition or duplicate prescription. Incorrect medication is one of the major drivers which is reflected in the high Pearson’s product-moment correlation coefficient between Number_med_eliminated and Wrong_medication (ƍ=0.59).

Discussion

Changes in the treatment plan

In this study, we documented that 62% of the patients had suboptimal generic use; patients could have used the lower-cost generic medication with the same active substance. This aligns with findings from Finland, where generic substitution accounted for 57% of treatment plan changes during medication reviews [42]. Suboptimal generic use can arise due to several factors including prescriber preferences (prescribing brand-name medications due to familiarity or perceived efficacy) and patient preferences (requesting brand-name medications due to brand loyalty, perceived quality differences, or lack of awareness about the availability and equivalence of generics).

Treatment related changes affected 74 patients, 73.27% of the sample population. Drug-drug interactions were prevalent in 3% of the sample population; patients were exposed to harmful interactions which had to be addressed immediately. Duplicate therapy (medication eliminated) affected 26% of the patients, while too high dose was present for 27% of the sample population.

In this research, we document that the number of medications used decreased after conducting the medication review. In our sample, nursing home patients used six medications on average before the medication review. After the medication review, the number of medications used was five. This finding is in line with the empirical evidence reported in the literature [10, 15, 16].

Cost saving at population level

In this study, for the first time in the literature, we find that medication reviews conducted as part of the ADD service by a community pharmacy result in lower medication costs. We document an average annual cost saving of €43.62 per patient, equating to 8.27% of the average and 10.08% of the median annual medication costs. This finding is in line with previous European research documenting medication cost savings in the UK, Switzerland, and France, where the authors reported savings of 6.87%, 16.4%, and 45.85%, respectively. [20, 27, 28].

Based on the representative sample of 99 patients, we extrapolate the annual medication cost saving at patient level to the level of the elderly population. In our calculations, we consider elderly over 75 years using six or more reimbursable prescription medicines, in line with the Finnish regulation [13]. According to the Estonian Health Insurance Fund, in 2022, there were 45,098 such elderly with a total medication cost of €45,721,120. Assuming an average annual medication cost saving of 8.27% and a conservative one-year remaining life expectancy [43], we estimate the total potential direct cost saving from medication reviews offered as part of the ADD service to be €3,781,137 per annum. This amount corresponds to 1.99% of the pharmaceutical budget of Estonia in 2022 [23].

Nursing home residents are the current beneficiaries of the medication reviews offered as part of the ADD service in Estonia. With the population getting older, the cost savings will be even higher in the future than the one estimated in this research. It is worth noting that the cost savings could be even more substantial if elderly using less than six prescription medications and/or less than 75 years of age could also enrol and benefit from regular medication reviews.

Determinants of lower medication costs

The regression analysis revealed three significant determinants being associated with lower medication costs. First, medication costs can be significantly reduced by encouraging generic drug use. The use of generic medications has proven to be one of the main drivers of medication cost reduction [44, 45]. In Estonia, the use of generic medication is below the OECD average; the share of generics in the total pharmaceutical market is 17% in value and 38% in volume in Estonia, while the corresponding figures are 24% and 53% for the 26 OECD countries in the sample [46]. Generic medicine is less expensive and hence more accessible to patients which can help improve medication adherence and ultimately lead to better health outcomes.

Although pharmacists in Estonia are required to offer patients the cheapest alternative containing the same active substance as the prescribed medication, substantial cost savings are observed when the use of generic medications is optimized. There are two potential explanations for this phenomenon. First, the cheapest generic medication may not be available in retail pharmacies. Second, patients may opt for the higher-priced generic medication or the patented original brand over the cheaper generic option because they tend to choose medicines they have previously used or insist on the brand prescribed by their family physician. At the same time, in Estonia, the pharmacy offering the ADD service is authorized to select the cheapest medication for each active substance without consulting the patient.

We have also documented that lowering the prescribed dose when deemed necessary lowers the medication costs significantly. At the same time, lowering the dose to optimal level contributes to additional savings to the healthcare system. In our sample, for example, there was a case when the patient was advised to take apixabanum (an anticoagulant) at twice necessary dosage (10 mg instead of 5 mg), which could have led to fatal consequences. If a patient is given a wrong dose of medicine, they may experience adverse drug reactions, which can result in hospitalization or longer stay in hospital, additional tests and treatments, all of which can be costly [5, 47, 48].

Finally, eliminating unnecessary or redundant medicines can lead to significant cost savings for patients and healthcare systems. For example, if a patient is taking multiple medications with the same therapeutic effects, eliminating one or more of those medications reduces the cost of the treatment without negatively affecting the health outcomes. In addition, potential negative impact on patient health outcomes and hence additional healthcare costs can be avoided.

Additional costs and benefits of the medication review offered as part of the ADD service

Medication reviews are associated with an increased workload for pharmacists, which should also be considered from a healthcare system perspective. In France, the average intervention time required by the pharmacist was 45 ± 7 min per patient when leading a multidisciplinary medication review for nursing home residents [20]. In Finland, community pharmacists reported that they spent on average 38 min per patient in reconciling the medication list and reviewing the medication [42]. In Estonia, assuming an hour spent on each medication review and an hourly gross salary of €15 for pharmacists, this additional workload translates to a cost of €20 per patient borne by the pharmacy after considering social security contributions levied on the employer.

The workload of general practitioners may also increase due to interactions with pharmacists during medication reviews. However, we might speculate that this additional time could be significantly lower than the time general practitioners would have needed to address medical complications arising from drug-related problems or drug overdose. Consequently, it seems reasonable to assume that there is no net increase in the workload of general practitioners related to medication reviews.

It is of crucial importance to recognize that the medication review offered as part of the ADD service delivers several long-term benefits to the patients and the society. First, pharmacist-lead medication reviews enhance knowledge and adherence among older adults by simplifying the medication regimens and correcting wrong intake time or method [15, 16]. During the dose dispensing phase medications are repackaged into unit-dose bags for each administration based on the time of intake which increases medication adherence as well [39, 49]. Second, chronic disease management can be improved by more precisely following the medication regimens as a result of the dose dispensing service [10, 49]. Third, medication-related complications can be avoided, preventing adverse drug reactions, drug interactions, or treatment failure [5, 20]. Better medication adherence, improved chronic disease management, and avoiding medication related complications can reduce healthcare utilization by preventing disease progression and the need for more intensive and costly treatment options, as observed among nursing home residents in Australia, Singapore, the UK and the US [8]. At the same time, improvement in the treatment plan, higher medication adherence, and better disease management are associated with improved health outcomes, longer life expectancy, and higher quality of life [8, 50].

Moreover, medication reviews might ease the burden on caregivers and healthcare workers by reducing the time spent on addressing errors and managing adverse events. With an optimal treatment plan, patients are less likely to experience side effects or complications, leading to cost savings in time and resources for both caregivers and healthcare workers. Finally, medication reviews contribute to sustainability by reducing the overall use of medications and decreasing medication waste [51].

Policy implications

The medication review offered as part of the ADD service by community pharmacies may result in significant economic and social benefits for the society, including lower medication expenses, lower healthcare utilization and improved medication adherence. Given the reduction in healthcare expenses, both short term and long term, the government might consider encouraging and financially supporting pharmacies to offer this valuable service. One feasible way to introduce medication reviews as part of the ADD service at a wider scale is to follow the Swedish or Finish example. In both countries, the service shall be prescribed by a physician, most often following the recommendation by a nurse. The ADD service is fully reimbursed for patients receiving home care in Sweden, as well as for nursing home residents over the age of 75 in Finland who are using six or more reimbursable prescription medicines suitable for automated dispensing [13]. The medication review, as a component of the ADD service, is recommended to be conducted regularly, at least once a year [11].

In Estonia, to make the medication reviews offered as part of the ADD service more accessible to patients, regulatory barriers should be removed. First and foremost, the ADD service shall be made accessible to all patients, not just the ones living in nursing homes [52]. Second, the range of medicines that can be dispensed shall be expanded; as of now not all medicines can be offered for automatic dose dispension [53]. Third, currently it is prohibited to deliver narcotics and psychotropic substances to the nursing homes which restricts patients’ access to the ADD service [52]. Regulatory bodies should consider exempting patients being enrolled in the ADD service from this restriction. Fourth, pharmacies offering the ADD service should be allowed to purchase bulk packages, including packages without marketing authorisation in Estonia, to enable further cost savings. Finally, regulation might allow community pharmacies to purchase ADD services from another pharmacies [52].

Limitations and future research

This research has a number of limitations. First, the sample size is small, 101 patients from five nursing homes, which may not allow to draw valid conclusions for the entire sector. Although patients in the sample did not exhibit any particular characteristics compared to those benefiting from Apotheka’s ADD service, we cannot rule out the possibility that nursing homes using the ADD service may have patients with certain diseases that are either underrepresented or overrepresented. Moreover, as long-term care expenditure and its public sector coverage is lower in Estonia than in the OECD countries [22], access to long-term care may heavily depend on clients’ ability to pay out-of-pocket which might lead to socio-economic biases in the sample.

Second, although suboptimal medication use in the treatment plans was identified and coded by two independent pharmacists and in case of inconsistencies a consensus was reached, manual coding might include subjectivity bias.

Third, we have only assessed the short-term benefits of medication reviews offered as part of the ADD service. Evaluating the long-term benefits to patients and society was beyond the scope of this study. We did not estimate the reduction in healthcare utilization, including costs associated with medical complications due to drug-related problems (e.g., medication-related hospital admissions), nor the improvement in health outcomes and quality of life. Future research might aim at measuring such long-term benefits.

Finally, performing a carefully designed cost-benefit analysis was beyond the scope of this study. Our results suggest significant cost savings for the society; 1.99% of the pharmaceutical budget of Estonia when considering medication cost savings at the level of elderly population over 75 years using six or more prescription medicines. This cost saving is associated with an increased workload for pharmacists (borne by the pharmacy), with speculative implications of no net increase in workload for general practitioners. Nevertheless, decision makers must perform a carefully designed and executed cost-benefit analysis to understand fully the impact of stimulating and supporting medication reviews at a wider scale; medication reviews which are offered as part of the ADD service by community pharmacies. In particular, the change in the workload of the physicians, the investment in the dispensing machine, and the wide-reaching long-term impacts shall be assessed to the best possible extent.

Conclusions

Purpose and key findings

The aim of this study was to assess the medication cost savings from medication reviews offered as part of the ADD service by community pharmacies for nursing home residents in Estonia. The regression analysis revealed that the most significant contributors to lower medication costs are suboptimal generic use, medications that are inappropriate, and too high dose. We estimated that the direct cost saving from the medication review offered as part of the ADD service is €43.62 on average per treatment plan per year. For elderly over 75 years using six or more reimbursable prescription medicines, we estimated a total cost savings of nearly 2% of the pharmaceutical budget in Estonia.

Policy implications

Medication reviews offered as part of the ADD service promote generic substitution and reduce suboptimal medication use, leading to significant cost savings for Estonia’s healthcare system. Therefore, the government shall consider introducing medication reviews, a key component of the ADD service provided by community pharmacies, to a broader population.

Data availability

The datasets used and analysed during the current study are available from the first author (jyrgen.janese@apotheker.ee) on reasonable request.

Abbreviations

ADD:

Automated dose dispensing

EU:

European Union

GDP:

Gross domestic product

OECD:

Organization for economic cooperation and development

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Acknowledgements

The authors acknowledge the excellent research assistance from Jekaterina Tsirkunov (MSc in Pharmacy, clinical pharmacy candidate) in manually coding the reasons for the changes in the treatment plans after the medication reviews. The authors thank ADD pharmacy manager Ave Vainoja for providing access to the data, Aljona Golubeva for helping with the data analysis, and colleagues at Apotheka for offering guidance and support throughout the research.

Funding

This research did not receive any specific funding. This research is a continuation of the Executive MBA thesis of Jürgen Jänese and Lauris Žēpers, supervised by Ágnes Lublóy. The two-year Executive MBA studies of Jürgen Jänese were financed by Apotheka Mustamäe Apteek.

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Authors and Affiliations

  1. Apotheka Mustamäe Apteek OÜ, Laagri Ärimaja, Vae 16, Laagri, Harjumaa, 76401, Estonia

    Jürgen Jänese

  2. Stockholm School of Economics in Riga, Strēlnieku iela 4a, Rīga, LV-1010, Latvia

    Jürgen Jänese, Lauris Žēpers & Ágnes Lublóy

Authors
  1. Jürgen Jänese
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Contributions

J.J. conceived and designed the study, acquired the data, developed the methodology, analysed the data, interpreted the results, prepared the figures, and drafted the manuscript. L.Z designed the study, analysed the data, and interpreted the results. Á.L. designed the study, reviewed the literature, developed the methodology, interpreted the results, and wrote the final manuscript.

Corresponding author

Correspondence to Ágnes Lublóy.

Ethics declarations

Ethics approval and consent to participate

The ethical aspects of this study were approved by the Ethics Committee of the Stockholm School of Economics in Riga consisting of experts of various nationalities. Requirement for written informed consent from study participants was waived by the same committee. This study used anonymized patient data (treatment plans before and after medication reviews, patient’s age and gender) provided by Apotheka Mustamäe Apteek. All patient-related information was treated in accordance with national and international regulations, as specified in the ‘Principles of customer data processing in Apotheka pharmacies’ (https://www.apotheka.ee/kliendiandmete-tootlemise-pohimotted); principles which have been developed in accordance with the rules of personal data protection and regulate the conditions for data processing of customers of Apotheka, including Apotheka e-pharmacy.

Consent for publication

Not applicable.

Competing interests

Jürgen Jänese is the owner and the board member of Apotheka Mustamäe Apteek OÜ, Estonia, a company being responsible for the online pharmacy operations and the automated dose dispensing (ADD) service. As the first author, Jürgen Jänese played a role in the design of the study, collection, analysis and interpretation of data, and writing the manuscript. All other authors declare no competing interests.

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Jänese, J., Žēpers, L. & Lublóy, Á. Cost savings from medication reviews in community pharmacies for nursing home residents in Estonia: a case study. BMC Health Serv Res 24, 1119 (2024). https://doi.org/10.1186/s12913-024-11504-z

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