A comparison between medication reconciliation by a pharmacy technician and the use of an online personal health record by patients for identifying medication discrepancies in patients’ drug lists prior to elective admissions

https://doi.org/10.1016/j.ijmedinf.2020.104370Get rights and content

Highlights

  • Medication reconciliation (MR) is time consuming and its success relies on the quality of different information sources.

  • Online personalized health records (PHRs) increase patient empowerment and may overcome the implementation problems of MR.

  • Patients who used an online PHR can relatively accurately record a list of their medication.

  • PHRs may have the potential to replace MR in detecting medication discrepancies.

Abstract

Aim

Medication discrepancies (MDs), defined as unexplained differences among medication regimens, cause important public health problems with clinical and economic consequences. Medication reconciliation (MR) reduces the risk of MDs, but is time consuming and its success relies on the quality of different information sources. Online personalized health records (PHRs) may overcome these drawbacks. Therefore, the aim of this study is to determine the level of agreement of identified MDs between traditional MR and an online PHR and the correctness of the identified MDs with a PHR.

Methods

A prospective cohort study was conducted at the cardiology, neurology, internal medicine and pulmonary department of the Amphia Hospital, the Netherlands. Two weeks prior to a planned admission all patients received an invitation from a PHR to update their medication file derived from the Nationwide Medication Record System (NMRS). At admission MR was performed with all by a pharmacy technician, who created the best possible medication history (BPMH) based on the NMRS data and an interview. MDs were determined as discrepancies between the available information from the NMRS and the input and alterations patients or pharmacy technician made. The number, correctness of patients’ alterations, type and severity of identified MDs were analysed.

Results

Of 488 patients approached, 155 (31.8 %) patients who both used the PHR and had received MR were included. The mean number of MDs identified with MR and PHR was 6.2 (SD 4.3) and 4.7 (SD 3.7), respectively. 82.1 % of the drug information noted by the patient in the PHR was correct compared to the BPMH and 98.6 % had no clinically relevant differences between the lists.

Conclusion

Patients who used an online PHR can relatively accurately record a list of their medication. Further research is required to explore the level of agreement and the correctness of a PHR in other (larger) hospital(departments).

Introduction

Transitions in healthcare are associated with a high risk of medication errors, mainly caused by poor communication of drug information at transition points [[1], [2], [3], [4], [5]]. To reduce the amount of medication errors, it is important to identify medication discrepancies (MDs), defined as unexplained differences among medication regimens [6]. Around half of the MDs have the potential to harm patients resulting in prolonged hospital stay, emergency room visits and readmissions [2,[7], [8], [9], [10]]. Because all patients admitted to the hospital have at least one MD, it is important to identify harmful MDs [[11], [12], [13]].

Medication reconciliation (MR) has the potential to identify and reduce MDs by 68 % [14,15].The Institute of Healthcare Improvement defined MR as “the process of identifying the most accurate list of patient’s current medicines including the name, dosage, frequency and route — and comparing them to the current list in use, recognizing and documenting any MDs, finally resulting in a complete list of medications” [16]. Although the World Health Organization (WHO) considers MR to be one of the five top strategies for ensuring patient safety, implementation of MR is hampered by the large amount of admitted patients with respect to the given time spent to perform MR (up to 30 min for each MR) [17,18]. Moreover, MR is performed according to different protocols using different resources [14,19].

Besides MR, patient empowerment, the involvement of the patient in their own care with the goal to make competent, well-informed decisions about their health and take action to support those decisions, is also an upcoming essential public health strategy to reduce medication errors [[20], [21], [22], [23]]. A personalized health record (PHR), which gives patients access to personal health information, may have the ability to empower patients to manage their own medication use [24]. Recent studies explored the effect of patient empowerment in the MR process by using a PHR [[25], [26], [27], [28], [29]]. However, only one of these studies directly compared the identified MDs with a PHR to traditional MR. Buning et al. concluded that drug lists compiled by patients using a PHR (n = 17) were sufficiently reliable in terms of their accuracy (mean number of 1.2 deviations in the PHR per patient compared to MR) [29]. However, the level of agreement between the PHR and MR and the severity of deviations in the PHR were not investigated. Therefore, the aim of this study is to determine the level of agreement of identified MDs between traditional MR (executed by a pharmacy technician) and an online PHR (used by patients) and the correctness of the identified MDs with an online PHR.

Section snippets

Study design

A prospective cohort study was conducted at the Amphia Hospital, Breda, the Netherlands. Inclusion criteria were age 18 years, able to read the Dutch language, had an admission at the cardiology, or neurology, or internal medicine, or pulmonary ward in the period of March or April 2019, had verified their drug list in the PHR and had received MR at admission or by telephone (at least three days before admission). Patients were excluded if no information from the Nationwide Medication Record

Study sample

Among 488 patients initially invited, 217 patients responded of which 155 met the inclusion criteria. Almost half of the non-responders (48 %) had an explanation why they did not use the PHR (Fig. 1).

Table 1 shows the characteristics of the study sample. Patients who used the PHR (mean age 63.8 +/- 13.1 years, 69.0 % male), used a median number of 7.0 (IQR: 3.0–10.0) drugs and were home living (98.7 %). MR was mostly performed by telephone (96.1 %) and most patients (90.3 %) were admitted at

Discussion

We examined the level of agreement of identified MDs between MR by a pharmacy technician and the use of an online PHR by the patient and assessed the correctness of the identification of MDs with an online PHR as compared to MR. Results from this study showed that although MR resulted in significantly more identified (CR)MD, more than 80 % of all drug information entered by the patient was correct, and in the case of incorrectness up to 99 % of the discrepancies between the MR and online PHR

Conclusions

Based on the results of this study, we conclude that patients who used an online PHR can relatively accurately record a list of their medication. Especially the identification of MDs with a PHR shows a high level of agreement with MR performed by pharmacy technicians. PHRs may have the potential to replace MR in detecting MDs, but further research is required to determine the level of agreement and the correctness of the PHR in different (larger) settings. Besides that, PHRs have to be further

Authors’ contributions

All authors contributed to all of the following: (1) the conception and design of the research, (2) drafting the article or revising it critically for important intellectual content, (3) final approval of the version to be submitted. The acquisition, analysis and interpretation of data were performed by DN, MT and HO.

Author’s statement

All authors (DN, MT, VH, BB and OH) contributed to all of the following: (1) the conception and design of the research, (2) drafting the article or revising it critically for important intellectual content, (3) final approval of the version to be submitted. The acquisition, analysis and interpretation of data were performed by DN, MT and OH.

Funding sources

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Declaration of Competing Interest

The authors had no competing interest.

Acknowledgements

None.

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