1. Introduction
Concerns about the adverse effects of the drugs used in health care are increasing among healthcare professionals [
1,
2,
3]. Trying to prevent them, the World Health Organization (WHO) reported specific measures on the safe usage of drugs, describing the process called Medication Reconciliation [
1]. In 2017, this same organization highlighted that improving the communication at the different healthcare transition points was essential to avoid harm originated by drugs [
4]. Healthcare transitions do generate a risk for patient safety, as medication errors are likely to occur, due to the lack of communication among healthcare professionals, and the potential loss of information [
4,
5,
6].
The reconciliation of medication contrasts the patients’ medication to the medication prescribed after a healthcare transition, to analyze and solve discrepancies and medication errors [
7,
8,
9,
10]. A medication error is a preventable event, related to the prescription and the use of drugs, that can cause harm to patients. It can be related to clinical and procedural issues but, in most cases, it is due to the use of inappropriate drugs [
2,
3,
4,
9]. These errors cost billions of euros and an incalculable human cost [
9]. It is estimated that, in the European Union, up to 12% of patients admitted to hospitals suffer from adverse effects related to drugs [
11]; and 40–60% of the patients’ medications can show discrepancies at hospital discharge [
12]. To identify and correct medication discrepancies, the National Institute for Health and Care Excellence (NICE), the Accreditation Canada, and the Joint Commission propose to perform medication reconciliation in healthcare transitions [
2,
5,
8,
13].
In Spain, 9.4% of patients admitted to hospitals have had adverse effects, and one-third of them could be related to the use of medication. It is estimated that 25.6% of these errors could have been prevented [
14,
15]. For this reason, the Spanish Ministry of Health elaborated the Patient security strategy guide, which included the reconciliation of medication as a step between hospital and primary health care transition [
3]. As poly-medicated and chronic patients are more susceptible to experiencing medication errors, in these specific groups is more relevant to perform the reconciliation of medication at any healthcare transition [
7,
12,
13,
16,
17].
The reconciliation of medication is performed by primary health care physicians, following a structured and systematic method, using a computer program provided by the Andalusian Health Service. This tool has a checklist, which guarantees the adherence to the protocol, that must be fulfilled by the physicians. All the discrepancies must be recorded. The conciliations performed are recorded in a database that is subsequently analyzed. The process of conciliation is based on a three-step methodology, endorsed by various national and international institutions [
12]. In the first step, a full list of the medication is obtained from the digital medical records. This list includes dosages, posology, and dosage form. A personal interview with the patient or its caregiver, can also be performed. The second step compares that medication list with the new prescriptions performed at the hospital discharge, to find and solve potential discrepancies. The medication errors, considered as standard to perform this analysis, are the following: medication omission, contraindicated medication, discrepancies in dosages, drug interactions, and duplicated therapeutics [
17]. In the third step, the physician informs the patients about the modifications performed in their medication [
11,
12,
13]. Involving the patients in the management of their medication increases their safety and their adherence to the treatment [
18].
Nevertheless, few studies have analyzed the process of medication reconciliation in the primary health care context. Therefore, the main aim of this research was to analyze the results of the systematic processing of the reconciliation of medication, performed by the physicians of primary health care, identifying discrepancies and medication errors, generated after hospital discharge, before they could affect the patients. We further sought to analyze some demographic aspects of the patients that could be associated with the occurrence of these errors.
2. Materials and Methods
A cross-sectional study was performed using the database which contains all the records generated by the medication reconciliations performed by the physicians of the Andalusian Public Health Service, in Spain. This research was performed in the Primary Health District of Almería, which attends a population of 301,457 inhabitants, distributed among 18 primary healthcare centers, and a reference hospital.
For this research, every patient discharged from four hospital services (cardiology, internal medicine, digestive and respiratory) during a year (May 2019–February 2020) were analyzed. The data collected was the following: age, gender, if medication reconciliation was performed, medication discrepancies, medication errors (medication omission, contraindicated drugs, duplicated therapeutics, differences in dosages, potential drug interactions), and if the discrepancies were corrected.
Univariate analysis was performed describing the variables collected. For descriptive analysis of the collected variables, central tendency and dispersion measures were used for quantitative variables, absolute frequencies were used for qualitative variables, and 95% confidence intervals (CI) were calculated for means and proportions. The goodness of fit to normality for the variables was calculated using the Kolmogorov–Smirnov test. For the analysis of the medication errors, the patients were grouped into two age strata: those who were younger than 65, and those aged 65 and older. The analysis was also performed considering their gender. To perform bivariate analysis, the nonparametric Mann–Whitney test was used to compare the main quantitative variables. For qualitative variables, the Pearson Chi-squared test and Fisher’s exact test were used. Statistical analyses were performed using SPSS version 26 (IBM Inc., Armonk, NY, USA).
This was a cross-sectional study based on clinical data previously existing in medical records. As no personal information was collected, data was anonymous, and no informed consent was required. All the procedures described in this study were approved by the Research and Ethics Committee of the Province of Almeria (Spain), with protocol code TFG-ACME-2020, and approval number 07/2021 (27 January 2021).
4. Discussion
The main aim of this research was to evaluate the systematic processing of the reconciliation of medication at hospital discharge, in a primary health care context, identifying discrepancies and medication errors. We further sought to analyze some demographic aspects of the patients, like age and gender, that could be associated with the occurrence of these errors.
Our results show that performing medication helps to detect discrepancies and medication errors that can be solved before the patients begin their new treatments. Other studies have stated this, for different levels of healthcare transitions [
5,
13,
18,
19]. Indeed, some national [
3,
14,
15] and international health agencies [
1,
2,
8,
11,
13] have stated that the process of medication conciliation is a useful strategy to reduce medication errors, preventing problems for patients.
Some research [
9,
16,
17,
18] describe that, due to the complexity of the process of conciliation, it is important to follow a structured method to optimize the adequacy of the treatments to the clinical situation of the patients. Thus, potential discrepancies and medication errors that could harm the patients can be detected and evaluated. Our results confirm this, as the physicians of the Andalusian Public Health Service follow a structured method of conciliation based on an online software, which provided the database that was analyzed.
A systematic review performed on twenty interventions [
5] found that most of these conciliations were performed in patients of 65 and over, poly-medicated, and in socio-medical centers and hospitals [
5,
10,
20]. This high mean age, also found in our sample, seems otherwise logical, as older people usually require more hospital treatments. In addition, these patients usually need to take more medications. As a consequence of these two aspects, they are more eligible to perform the medication reconciliation process. As the studies evaluated used different methods, it was not possible to detect which conciliation methods were more effective [
12,
16,
21]. Despite this, the authors concluded that discrepancies were prevalent, that they were generated in healthcare transitions, and thatthey were related to medication adverse effects, medication conciliation being the process to follow to avoid medication errors. Our findings do agree with these affirmations.
In this same research, the authors found that more than 70% of the patients analyzed, after hospital discharge, showed some kind of discrepancies in their treatment, being the mean of medication errors per patient of 2.7. A total of 70.5% of these medication errors were found in patients 65 years and older. Other research stated a total of 42.9% of patients with discrepancies, with a mean of 2.1 medication errors per patient [
7]. Other research, performed in a hospital, detected that a total of 55.1% of the admitted patients had one or more medication errors, with a mean of 3.2 medication errors per patient [
21]. Several studies that performed conciliation in primary health care, after hospital discharge, found discrepancies in 40–60% of the medications of the analyzed patients [
7,
12,
19]. Our figures are in concordance with these previous publications.
Regarding medication errors, omission error was the most frequent error found in our research. This finding agrees with the results of other studies, which found this error in 40–60% of the analyzed patients [
12,
13,
16,
17], although we must consider that they were performed in hospitals. This is also confirmed by the Spanish Institute for Safe Medication, which stated that, in the year 2020, medication omission was the most frequent medication error, and with the most severe consequences [
22].
Regarding the sex and the different age groups of the patients, the prevalence of medication errors found in our research was bigger in women of 65 and older, when compared to men of the same age. Although these differences were statistically significant, we have not found similar research with medication errors categorized by gender and groups of age. In the 20–34 age strata, the percentage of medication errors was higher for women than men, which was different from other age strata. A possible explanation for this finding is that, in that age strata, the number of women was higher than men, and there was thus a higher number of drugs prescribed to women in this age strata. Therefore, the likelihood of finding medication errors was higher among women, in this specific age strata.
Our results show that primary health care plays an essential role in the process of medication conciliation, as it is accessible for patients and caregivers, and offers a comprehensive vision of the patient, and its social and familiar circle [
3,
12,
15]. As a conclusion, it could be useful to implement the conciliation process among all the physicians of primary health care. This way, this process could be integrated into their daily workflow, allowing the detection of numerous potential errors. To accomplish this, the support of all stakeholders and additional resources, such as more time to perform the process, are required. In addition, it could be useful to perform more research about medication conciliation in the primary healthcare environment.
Our research had some limitations. One of the most significant limitations is that our study was performed using the database of the Andalusian Public Health Service, therefore only the medication conciliations performed using this software could be analyzed. The conciliations performed in private practice, or the medications that were used by the patients but not communicated to the physicians, could not be included in this research. We must also consider that the sample was obtained from four hospital services, an aspect that could generate a potential selection bias. Therefore, these potential limitations must be considered when interpreting the external validity of our results. Our research also had some strengths. The most important is that the process of conciliation analyzed was systematic, using an online conciliation tool. This ensures that all primary care physicians followed the same process, reducing the variability of the process and therefore increasing the reliability of the analysis. Another strength of our research is that our sample size was 6115 patients, larger than the sample analyzed in other similar research.