Correct Medication List at and After Hospital Discharge

Background

LIMM-studies interventions decreased error rates in the discharge medication lists from 66 to 32% and the risk for clinical negative consequences from 32 to 16%. Patients who manage their own medication and patients with different cultural background have not been studied in the LIMM-model. In a pilot study using the same methods as in this planned RCT 22 problems were identified among 7 patients in the medication list at discharge. All problems were solved and no remained at follow-up 2 weeks later.

Aim The aim of this study is to evaluate the effects of an intervention to reduce errors in the patient medication list when discharged from hospital to home. A further aim is to compare the effects of the intervention in two different patient populations, Swedish- and Arabic speaking, and the potential clinical and economic consequences of the errors.

Methods

Study design

This is a prospective, RCT with two parallel groups. Patients are randomized to standard care (control) or an intervention. The investigators want to secure that patients have the correct medications available for use after discharge and, that the information about current medications is correct in the EHR and the pharmacy dispensing system, and to ensure that the accurate medication list is communicated and agreed with the patient. Patients 60 years and older, handling their own medications, and with at least five continuous medications, Swedish or Arabic speaking, will be recruited from two departments at Skåne University hospital (SUS) in Malmö before discharge, during 4-12 months starting from September 2022. Patients will be given written and verbal information about the trial by a pharmacist (the PhD student), as well as an invitation to take part. Patients unable to discuss their treatment will be excluded Patients will be randomised to standard care (control) or standard care plus research pharmacist activities (intervention). The randomisation will be stratified based on Swedish speaking or Arabic speaking (requiring an interpreter). The randomisation sequence will be computer-generated by a researcher not involved in data collection. The researcher (a PhD student) collects baseline questionnaires and defines the stratum of each patient before assigning the patient to the intervention or control group according to the serial number. As described below 100 patients are planned to be included, 60 Swedish and 40 Arabic speaking. If it proves to be difficult to include 40 Arabic speaking patients, more Swedish speaking patient will be included.

Assessments and interventions in both intervention and control groups

Baseline assessment data for both intervention and control patients, including demographics, civil status, social factors (level of education and employment), comorbidities, are collected from the electronic health care record (EHR) and/or by asking the patient verbally. Two questionnaires "Beliefs about medicines questionnaire" (BMQ-S) and "Medication adherence report scale" (MARS) will also be used. Standard medical care including medication reconciliation and -review according to Swedish constitution will be performed by responsible physician in both groups . At discharge, a ward physician is supposed to prepare a written discharge information for the patient including a medication list.

A follow-up telephone meeting with the patient will be booked 3 weeks after discharge. Changes in the medication list and what the patient really takes are identified.

Intervention group protocol

At discharge, the PhD-student performs activities developed and tested in the described study and further developed in the pilot study. The intervention includes dispensing the correct medications to the patient and to correct errors and missunderstandings based on patient perceptions and usage, pharmacy records, medical notes, and written discharge information. The investigators aim to make the patients fully informed and conscious about which medications to take or not, at home, and that the prescriptions are updated to support this. The discharge information produced by a physician will also be updated to reflect this and will contain a correct medication list. Based on the medication reconciliation and a brief medication review, possible problems will be discussed with the responsible physician and the patient, to finally be corrected. At discharge, the patient will receive a correct medication list and his/her new medications dispensed by the researcher, bedside.

Identification of errors

If there is a written discharge information including a medication list this will be considered the correct medication list at discharge. If not, the final medication list in the EHR on the day at discharge will be considered the correct medication list. These lists are compared to the medication list stated by the patient 3 weeks after discharge and corrected for changes performed and documented after discharge when needed. The patient is the main source on which medications that are really used. The patient´s statement on which medications are being used is to be compared with the medication list at discharge. EHR and pharmacy dispensing records will be used to establish and check the list. If investigators have access to EHR at the primary care system this will be used as a complement to the other systems. In this way, the investigators make sure that the discharge information from the hospital has reached the primary care both in intervention and control groups, and that they have had enough time to take the discharge information and different changes into account and make their own statements.

Errors during the discharge process will be identified. This will be performed simultaneously as the identification of clinical risk as described below.

A checklist, including basic clinical patient information, the correct medication list at discharge and the establishment of a correct medication list 3 weeks after discharge will be used. The establishment of a correct medication list 3 weeks after discharge will be based on the following process: 1/ identify new prescriptions (after discharge) and medication information from pharmacy records and EHR. 2/ let the patient describe their current medication use. 3/ ask questions based on correct medication list at discharge and new information from records as above. 4/ask questions from a specific list used for medication reconciliation.

The definition of medication error proposed by Leape will be applied. With this definition, a medication error is any error in the process of prescribing, dispensing, or administering a drug, whether there are adverse consequences or not. The focus will be on what the patients take. If drugs are added, withdrawn or the dosage had changed without any documentation in charts, medical records, or medication lists, it will be considered an error.

Evaluation of risk of an error

The clinical risk associated with an error, will be evaluated for each patient and for each error, separately by two senior researchers. They will receive allocation blinded basic clinical patient information and documentation on medication lists at and 3 weeks after discharge. Patients' risks will be classified into one of three groups, (1) without clinical risk, (2) with moderate clinical risk and (3) with high clinical risk.

Clinical consequences and health economic evaluation

Patients with at least one error classified as moderate or high risk will be evaluated. All contacts that these patients have with primary care or hospital care within 3 months after discharge will be documented and evaluated. A regional patient register (RSVD) will be used to investigate each contact. For all included patients all information on each contact will be collected and prepared by the PhD student for blind evaluation of errors, risks, and clinical outcomes. The probability that medication errors had caused the clinical outcome or need for administrative corrections will be estimated according to the WHO's criteria as certain, probable, possible, unlikely, and no.

Health economic evaluation will be performed based on time spent in the intervention, costs for healthcare resources during three months and error rates. Incremental costs will be calculated by comparing the mean cost of all healthcare during the study period between the groups. This cost will be compared in an incremental cost-effectiveness ratio using the number of clinically relevant medication errors reaching the patient as the health outcome.

Statistical methods and sample size

All errors for each patient in intervention and control group will be tabulated based on type and clinical risk to allow comparisons. Proportion of patients with no errors in the medication list 3 weeks after discharge, and also no clinical consequences after 3 months will be the primary outcome measure. Also, the mean number of errors for each group, and proportions of patients with at least 1, 2, 3, 5 and 10 errors, as well as clinical risk and consequences will be compared. Also the Swedish and Arabic speaking populations will be compared. Finally, possible relationship between individual patients BMQ-S and MARS scores, and the outcomes will be studied. T-test, chi-square test, multiple regression test, etcetera as appropriate will be used. All tests will be two-sided and a P value of <0.05 will be considered significant.

Based on previous studies it is anticipated an increase in the number of patients with no medication errors at follow up from 20% to at least 80% in the intervention group. With a 5%-significance level and power of 80%, 11 patients in each group is needed. Similarily the number of patients with no clinical consequences is anticipated to increase from 71% to at least 94% in the intervention group and 43 patients in each group is needed.