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Patient-centred medicine
Original research
Enhancing patient participation in discharge medication communication: a feasibility pilot trial
  1. Georgia Tobiano1,2,
  2. Elizabeth Manias3,
  3. Wendy Chaboyer1,4,
  4. Sharon L Latimer1,4,
  5. Trudy Teasdale2,
  6. Kellie Wren2,
  7. Kim Jenkinson2,
  8. Andrea P Marshall2,4
  1. 1NHMRC CRE in Wiser Wounds Care, Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia
  2. 2Gold Coast University Hospital, Southport, Queensland, Australia
  3. 3School of Nursing and Midwifery, Monash University, Clayton, Victoria, Australia
  4. 4School of Nursing and Midwifery, Griffith University, Gold Coast, Queensland, Australia
  1. Correspondence to Ms Georgia Tobiano; g.tobiano{at}griffith.edu.au

Abstract

Objectives To pilot test a co-designed intervention that enhances patient participation in hospital discharge medication communication.

Design Pilot randomised controlled trial.

Setting One tertiary hospital.

Participants Patients who were ≥45 years of age; ≥1 chronic illness and ≥1 regularly prescribed medication that they manage at home were recruited between October 2022 and May 2023. Healthcare professionals on participating units completed surveys.

Intervention The co-designed intervention included three websites: a medication search engine, a medication question builder and tools to facilitate medication management at home. Inpatient posters contained QR codes to provide access to these websites.

Primary and secondary outcome measures The primary outcomes were the feasibility of study processes and intervention acceptability. Feasibility of study processes was measured in terms of recruitment, fidelity, retention, missing data and contamination. Patients in the intervention group and healthcare professionals on the wards self-reported intervention acceptability. Secondary outcomes were medication understanding, use, self-efficacy and healthcare utilisation.

Results 60 patients were recruited and randomised; half in each study group. The intervention was largely delivered as intended, and 99.7% of data collected was complete. In total, 16/59 (27.1%) patients were lost to follow-up 28 days after hospital discharge, and 3 patients in the usual care group reported that they saw the intervention poster prior to hospital discharge. 21 of 24 intervention group patients (87.5%) deemed the intervention acceptable, while half of the healthcare professionals (n=5, 50%) thought it was acceptable.

Conclusions We demonstrated that in a future definitive trial, intervention fidelity would be high with little missing data, and patients would likely find the intervention acceptable. Thus, a larger trial may be warranted, as the intervention is implementable and approved by patients. However, additional strategies to increase recruitment and retention of eligible participants are needed. Healthcare professionals may require more preparation for the intervention to enhance their perceptions of intervention acceptability.

Trial registration number ACTRN12622001028796.

  • Inpatients
  • Patient Participation
  • Hospital to Home Transition
  • Patient-Centered Care
  • Hospitals
  • Medication Adherence

Data availability statement

No data are available. Participants of this study did not agree for their data to be shared publicly, so supporting data are not available. Upon reasonable request, our research team could approach the approving ethics committee to seek opportunities for data sharing.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi-org.ezproxy.u-pec.fr/10.1136/bmjopen-2023-083462

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    STRENGTH AND LIMITATIONS OF THIS STUDY

    • Consumer and healthcare professional engagement in intervention development and the research process was comprehensive.

    • Outcome assessors, analysts and participants were not blinded to group allocation.

    • Self-report data were collected, which are at risk of social desirability bias.

    • Only pharmacist and nurse perceptions of intervention acceptability were measured; future studies should include physicians as well.

    • Patients’ digital literacy was not measured, which may influence intervention use and acceptability.

    Introduction

    When medical and surgical patients are discharged from the hospital, medications form an important part of ongoing treatment, which can pose an enduring risk to patient safety. Root problems can include patients receiving insufficient information about their medication regimen at hospital discharge, or patients who are not adhering to prescribed medication once at home.1 The impacts of medication-related problems are significant for patients and healthcare services. For example, in a 2020 systematic review of 54 studies, nearly one-third of adult patients experienced an adverse drug event (ADE) after discharge from the hospital; ADEs were defined as injuries resulting from medical intervention related to a medication.2 Not only are patients harmed, but recent studies show that 16%–40% of patients have a medication-related readmission to hospital within 30 days of hospital discharge.3 4 Medication-related hospital admissions cost about GBP £368 million per annum in the UK and AUD $1.4 billion per annum in Australia.5 Attention must be paid to improving patient safety and reducing the burden of medication-related problems that arise after hospital discharge.

    One strategy to enhance medication safety after hospital discharge is optimal medication communication between patients and healthcare professionals.1 Manias6 identified that effective medication communication is patient-centred and incorporates active patient participation in two-way communication based on patient needs, priorities and preferences. When patients participate in medication communication, patient safety can improve by patients providing current and individualised information about their medications, voicing medication concerns and learning to identify safety issues with their medications.7 8 However, patient participation in medication communication may be a solution that is yet to be fully realised. For example, in an observational study of 173 patients aged ≥65 years and older, patients were largely passive during hospital discharge medication communication.9 Further, medication communication was overwhelmingly initiated by the healthcare professional with one-way information provided to the patient.9 There are several factors that impede patient participation in discharge medication communication including the patient’s preference, health literacy and the complexity of the medication regimen.10 These findings collectively imply that efforts to improve patient participation in medication communication should target patients prior to hospital discharge.

    Interventional research has been successful in increasing patient participation in medication communication.10 In a 2019 systematic review of 15 studies, providing patients with clear and accessible medication information, respecting patients’ preferences and providing patients with health literate tools led to more active participation in medication communication in hospital.10 However, none of the interventions were created with patients, and thus may not be acceptable or relevant to patient needs.10 Therefore, we co-designed an intervention with patients, healthcare professionals and organisational leaders to improve patient participation in hospital discharge medication communication.11 The intervention comprised three websites accessed by scanning QR codes on a poster. The websites included a medication search engine, a medication question builder and tools to facilitate medication management at home. The intervention was reviewed by a small group of hospital inpatients, who determined it was usable and acceptable. Following intervention development, effectiveness should be assessed, but this requires the feasibility of the study processes and implementation processes to be first assessed in a pilot study.12 This step allows the research team to make necessary adjustments to the study protocol and intervention prior to a larger effectiveness trial.12 Thus, the overall aim of this study was to pilot test an intervention that enhances patient participation in hospital discharge medication communication. The specific objectives included:

    • To assess the feasibility of study processes, as per pre-specified criteria, to inform a future effectiveness trial.

    • To assess patients’ and healthcare professionals’ perceptions and experiences of intervention acceptability.

    Methods

    Design

    This pilot randomised controlled trial was reported as per the ‘Consolidated standards of reporting trials: extension to randomised pilot and feasibility trials checklist’.13 The trial was registered on the Australian New Zealand Clinical Trials Registry.

    Patient and public involvement

    During intervention development, three consumers who had lived experience of hospital discharge—aged ≥45 years, with ≥1 chronic illness and ≥1 regularly prescribed medication that they managed at home—were recruited through ‘Health Consumers Queensland’, as well as three nurses, three doctors and three pharmacists who worked at the study hospital and had direct experience undertaking discharge medication communication with patients, attended co-design meetings and developed the intervention.11 During both intervention development and pilot-testing (the focus of the current paper), a team of four opinion leaders, who were influential within the participating hospital, was engaged in the research process. This team consisted of the Chair of the Consumer Advisory Group, the Medical Executive Director, a Nursing Safety and Quality Coordinator and the Pharmacy Assistant Director. They were involved in all phases of the programme of research, including start-up phase (eg, reviewed study protocol and grant application, developed the intervention, reviewed study materials for patients), active phase (facilitated recruitment of units for the study, advised on issues during data collection) and close-out phase (reviewed the final manuscript, if desired). Regular meetings were held with the opinion leaders, separate from the academic researchers, to allow opinion leaders to share their views freely.

    Setting and participants

    Two units, one cardiology unit and one vascular unit, were study sites. These units provided medical and surgical services in a large Australian metropolitan tertiary hospital. We aimed to recruit 60 patient participants, consistent with median sample sizes for pilot studies,14 and deemed sufficient to provide practical information about the feasibility of study processes.15 Inclusion criteria were consenting adult patients ≥45 years of age; ≥1 chronic illness and ≥1 regularly prescribed medication that they manage at home. Additionally, patients required a smart device (ie, tablet or phone) to access the intervention. The inclusion criteria were selected based on state-level data that demonstrated patients meeting these criteria had complex medication regimens and/or chronic health management needs, putting them at high risk of not adhering to medications in the community.16 Exclusion criteria were patients receiving end-of-life care, planned discharge to an aged care facility, any form of cognitive impairments or inability to communicate in English.

    Two nurse researchers, who had clinical expertise in assessing eligibility criteria, were trained to recruit patients. Patients were recruited at any time prior to hospital discharge but we aimed to avoid recruiting on the day of discharge, given that patients may not have sufficient time to interact with the intervention. The nurse researchers screened all patients on the unit each recruitment day, and then consecutively approached all potentially eligible patients undertaking the informed consent process. Participants were given verbal explanations of the project and a participant information form prior to consenting. Potential participants had the opportunity to ask questions prior to consenting to the project and could determine how long they wanted to consider participation prior to consenting. Written consent was obtained. Recruitment occurred from October 2022–January 2023 to February–May 2023, with a 1 month pause during January–February 2023 due to staffing issues. Final follow-up data collection was completed by July 2023.

    In addition, our aim was to recruit 10 healthcare professionals (pharmacists and registered nurses) working on the participating units to explore their perceptions of intervention acceptability.

    Randomisation

    Using the centralised, web-based randomisation service, eligible patients who were recruited were randomly allocated to the intervention plus usual care or usual care alone. Randomisation was not stratified by units at the study site. Groups were allocated using simple random sampling in a 1:1 ratio in varying blocks of 4 and 6. Group allocation was revealed to patients after baseline data were collected. Patients and healthcare professionals could not be blinded to group allocation, due to the nature of the intervention. It was also impossible to blind the nurse researchers collecting data after hospital discharge as participants in the intervention group were asked additional questions about intervention acceptability.

    Intervention

    A detailed description of the co-designed intervention and its development is described elsewhere.11 The intervention comprised a poster with three QR codes linked to three websites; some websites were owned by the Australian Government and others were created by the research team. Details of each website are listed below:

    1. ‘Learn more’ QR code: a medication information search engine that allows patients to search for consumer-friendly information about their medications.

    2. ‘Ask questions’ QR code: a question builder website, where patients select questions that are important to them, and receive these questions as a text or email that prompts them to remember to ask these questions when in the presence of a healthcare professional.

    3. ‘Manage medicines’ QR code: a website with a range of resources to assist with medication management at home, including community contacts and tools such as mobile applications to help track medications.

    During education sessions, patients in the intervention group were shown the poster (figure 1) and three websites by the research nurses and were instructed that they could access these websites at any time, when needed. An A3 size poster was hung on the wall in the patient room. In addition, patients were provided with an A4 poster to take home.

    Figure 1
    Figure 1

    Intervention poster.

    Regardless of group allocation, all patients received usual care which included:

    • Discharge medication conversations during routine tasks (eg, bedside handover and ward rounds), dependent on patient and healthcare professional communication skills and preferences.

    • Pharmacist consultation on hospital admission and discharge; not all patients will receive this depending on pharmacist workload and timing of patient admission/discharge.

    Primary outcomes

    The primary outcomes were feasibility of study processes (which included various measures) and intervention acceptability. Pre-defined criteria for progression to an effectiveness trial were based on previous pilot trials.17–19

    Feasibility of study processes

    • Recruitment: >75% of eligible patients approached consent to participate.

    • Fidelity: >80% of intervention group patients receive the intervention as intended.

    • Retention: >80% of recruited patients provide complete outcome data at 28 days post-discharge.

    • Missing data: >80% of data collected is complete.

    • Contamination: >95% of the usual care group did not get the intervention.

    Intervention acceptability

    • Intervention acceptability: >80% of patients and healthcare professionals view the intervention as acceptable.

    Researcher logs were used to collect feasibility of study process outcomes, and patients in the control group were asked ‘Did you see a poster hung in your room with a title ‘Take control of your medicines, now’, that had three QR codes that linked you to websites, such as a question builder and search engine for leaning about your medicines?’, to assess contamination. Contamination was defined as patients in the control group seeing posters that had been hung for intervention group patients.

    For intervention acceptability, the 8-item Theoretical Framework of Acceptability (TFA) questionnaire,20 with established content validity20 was used for patients. The Likert scale responses measure the extent to which people receiving a healthcare intervention consider it appropriate, based on anticipated or experienced cognitive and emotional responses to the intervention.20 Healthcare professionals received a survey developed for this study, which asked them to comment on whether they thought the intervention was appropriate in general (open-ended question). They were also asked questions not related to pre-defined acceptability criterion such as facilitators and barriers to patients using the intervention (open-ended responses), suggested intervention changes, and whether they thought the intervention was feasible in real practice (responses: yes/no/unsure).

    Secondary outcomes

    Secondary outcome measures were those anticipated for use in a future effectiveness trial, including: (1) Medication Understanding Questionnaire (MUQ); (2) Medication Understanding and Use Self-Efficacy Scale (MUSE) and (3) Healthcare utilisation (see online supplemental file 1) for further details about these measures.

    Data collection

    At baseline, sociodemographic information was collected from all patients via surveys delivered by research nurses and from their electronic medical record. Additionally, the MUSE and MUQ were administered in-person by the nurse researcher. All patients, regardless of group allocation, were followed up at two time points; 7 and 28 days after hospital discharge. The risk of medication-related harm is highest 7–10 days after hospital discharge21; thus, consistent with other Australian pharmacy outreach services, we collected follow-up data approximately 7 days post hospital discharge.22 The nurse researcher phoned all patients at day 7 and re-administered the MUSE and MUQ. Additionally, intervention group patients were administered the TFA questionnaire20 and asked questions about using the intervention. Control group patients were asked about intervention contamination. At 28 days post hospital discharge, patients were phoned and asked about their healthcare utilisation. We used this time point, because the usual timing for a definition of readmission is within 28 days of an index admission.23 For all follow-up phone calls, the nurse researcher sent a text to remind patients of the upcoming call, and attempted to call the patient three times before the patient was deemed lost to follow-up. Attempting follow-up three times is a common approach used at our hospital that is acceptable to our ethics committee.

    Once patient recruitment had ceased, the healthcare professional questionnaire about intervention acceptability was administered at a convenient time to them.

    Data analysis

    Frequencies and percentages were used to report all categorical sociodemographic data, log data and responses to the questionnaires. For the TFA questionnaire, the first question is a global rating scale for overall intervention acceptability. All patients who responded ‘acceptable’ or ‘completely acceptable’ were calculated. For healthcare professionals, responses to the question about whether they thought the intervention was appropriate were categorised as ‘yes’, ‘unsure’ and ‘no’. The suggested intervention changes were then summarised. Medians and IQRs were reported for continuous social-demographic data and secondary outcome measures, as data were not normally distributed. For primary outcomes, all percentages were assessed against pre-specified criteria. All data were analysed using IBM SPSS Statistics for Windows (V.27) (IBM Corp: Armonk, New York, USA).

    Results

    In total, 318 patients were screened for study eligibility (figure 2), with 107 (33.6%) deemed eligible and 60 (56.1%) recruited, as intended. Of those eligible patients who refused participation (n=37, 34.5%), 19 patients (51.4%) did not provide a reason; the remaining reasons for declining consent were already being happy and confident managing medications (n=6, 16.2%), not being confident using their smart phone or not liking using their smart phone (n=5, 13.5%), being too focused on health issues or too unwell (n=4, 10.8%) or being frustrated with the hospital or healthcare professionals (n=3, 8.1%). 30 patients were randomly allocated to each study group. An overview of patient characteristics is in table 1.

    Figure 2
    Figure 2

    CONSORT 2010 flow diagram for study.

    View this table:
    Table 1

    Patient characteristics and baseline self-report survey responses

    Table 2 reports the results for how each primary outcome performed against pre-specified criteria, showing that intervention fidelity and missing data criteria were met. Additional data collected that is not related to pre-defined criteria, and a summary of secondary outcome results, are reported in online supplemental files 3 and 4.

    View this table:
    Table 2

    Primary outcome results

    Discussion

    The various measures of feasibility of study outcomes had mixed results. We had adequate intervention fidelity and low missing data. However, recruitment rates and 28 days follow-up after hospital discharge retention rates were problematic. The intervention was acceptable to patients, yet healthcare professionals were more unsure about the intervention acceptability.

    Recruitment

    In this study, we did not meet pre-specified criteria for recruitment; a common reason for participation refusal was patients considered that they were confident in managing their medications. These patients may have been more ‘activated’, which is conceptualised as patients having the knowledge, skills and confidence to manage their healthcare.24 Increasingly, researchers are using the Patient Activation Measure (PAM) prior to intervention delivery, and providing interventions that are tailored to patients’ level of activation.25 For example, in a study for patients with inflammatory bowel disease, patients with lower levels of activation received an intervention that provided information about the disease prognosis and the importance of being active in disease management, while those at higher levels received an intervention that encouraged them to remain partners in managing their health.26 Thus, we suggest that researchers could use screening tools such as the PAM to identify patients who may benefit most from the intervention or tailor their level of engagement in the intervention, to reap the well-known benefits linked to being engaged in care, such as reduced emergency department and hospital use.25

    Other reasons that participants refused participation included low confidence using or dislike for smart phones, health issues and frustration with hospital processes or healthcare professionals. Health issues are a common reason for patients to refuse participation in studies.27 Additionally, studies relating to hospital discharge, often evoke feelings of frustration for patients, which can result in refusal to participate in studies.28 Perceptions related to smart phones may be a reason for refusal that is more specific to the intervention tested in our study. The median age of study participants was 63.5 years; stereotypes are present that older adults use smart technology less.29 However, research conducted with 3125 older people across six countries has shown that their mobile phone practices are dynamic and can increase, similar to other age groups.29 In fact, people aged 60 years and older have considerably varying levels of technophobia.30 Importantly, older people have expressed willingness to learn to use technology, but may require training to feel comfortable to engage with smart phones, which can ultimately reduce the digital divide that may leave some older adults feeling excluded from society.31 Overall, we cannot assume that older people will refuse participation in studies that use smart phone interventions; but additional training may need to be provided during intervention delivery to boost recruitment rates.

    Retention

    In our study, retention rates did not meet pre-specified criteria. Yet, our completion rates at 28 days after hospital discharge resonate with other interventional research where loss to follow-up was 27% for phone surveys.32 Even though retention rates are generally expected to be 80% or higher,33 using a study with similar mode of survey delivery and duration for follow-up, such as Kang et al,32 may have more adequately guided our pre-specified criteria. In encouraging adequate retention rates, it is important to be open to innovative and flexible ways of retaining patients through to 28 days after hospital discharge. Mixed modes of data collection, where patients are offered the choice of phone, paper or electronic surveys, are gaining popularity, due to their ability to overcome the limitations of each individual mode of data collection.34 Bull et al35 recently used this mixed approach for data collection and demonstrated high survey completion rates and a truly patient-centred approach to data collection that valued patient preferences.35 Overall, for researchers attempting to collect data long after hospital discharge, we suggest nuancing the accepted retention rate to the duration of follow-up and/or using more novel approaches to data collection.

    Of note, in our study, only n=8 (13.6%) of patients were lost to follow-up at 7 days after hospital discharge. This low rate of loss to follow-up resonates with another study where over >80% of patients completed phone surveys 1 week after surgery.36 These authors used similar techniques to us, such as text message reminders prior to phone calls, nurses meeting the patient face-to-face prior to phoning patients and using caller ID, which may have all attributed to the completion of surveys at 7 days.36 We recommend that other researchers use similar strategies to enhance follow-up, and stricter pre-specified criteria for retention rates could be set for researchers collecting data 7 days after hospital discharge.

    Intervention acceptability

    Although the intervention was acceptable to patients, some patients refused to participate in the study because they were not confident with or did not like using their smart phone. In response to the COVID-19 pandemic, there has been wide implementation of QR code scanning on smart phones for planning and contact tracing.37 As a result, researchers have increasingly replaced paper-based patient information materials with QR codes linked to websites. In one study with orthodontic patients in the UK, 94% found QR code education easy to use, however, 18% of patients did require some assistance, especially those who had not used QR codes previously.38 Yet, in another study using QR codes in gynaecology waiting rooms for patient information, previous use of a QR code did not influence patient ability to use a QR code.39 Additionally, researchers using QR codes for surgical patient information leaflets showed that being 70 years or older was associated with lower acceptance of QR codes.40 However, there is variability in the literature on the relationship between age and QR codes use.39 Overall, the literature on using QR codes for health research is still emerging. We recommend that researchers ensure their QR codes interventions incorporate clear instructions for how to use QR codes, and provide opportunities to support patient learning, if required.

    Healthcare professionals in our study had mixed views on intervention acceptability; a common view for interventions that encourage more active patient participation in care.41 Healthcare professionals are often sceptical about these types of interventions because they fear releasing control and increased workload from active patient participation.42 Yet, a systematic review of 32 studies showed that patient communication skills training interventions increased patients’ participation in active communication, without increasing the duration of conversations with healthcare professionals.43 Thus, informing healthcare professionals of time-costs may be an important implementation strategy when testing patient participation interventions. However, these types of interventions may work regardless of healthcare professional attitudes. A systematic review on patient-mediated interventions showed that interventions comprising question-builders increased patient communication in hospital, which in turn increased healthcare professionals’ adherence to recommended clinical practice, regardless of healthcare professionals’ views on intervention acceptability. For future researchers, we suggest careful planning for how to disseminate information to healthcare professionals about interventions that encourage patient participation, to ensure healthcare professionals are receptive. For example, Leeman et al44 suggest that materials should be formatted into a way that the intended audience can use, and could be distributed through multiple channels (ie, in-person presentations, emails and interpersonal connections), for effective dissemination.

    Limitations

    This pilot study contained limitations. First, blinding of researchers collecting secondary outcome data and conducting analysis was not possible due to this being a small pilot study, with limited funds. In a future larger funded trial, outcome assessors and data analysts could be blinded. Additionally, it was impossible to blind patients due to the nature of the intervention; patients would know whether they received a poster or not. Second, many primary and secondary outcome measures were self-reported, which could result in social desirability bias. In future intervention testing, the person delivering the intervention could differ from the person collecting outcome data, to reduce social desirability bias. Third, three patients in the usual care group thought they saw the intervention poster. Thus, in future trials, it is important to ensure that patients in different groups are spatially or temporally separate, and if posters are being used for the intervention, nurse researchers must actively remove them when a patient reaches study endpoints. Fourth, we only assessed nurse and pharmacist perceptions of intervention acceptability; patients desire more medication conversations with physicians in hospital,28 thus, physician acceptability should be assessed in future studies. Finally, we did not measure the digital literacy of patients which may have affected how they used the intervention and their perceived acceptability towards the intervention. In future research, we recommend that researchers use available tools to measure digital literacy.45

    Conclusions

    In this study, the feasibility of study processes and intervention acceptability were tested. Some study processes were feasible, such as data collection and intervention delivery fidelity. However, the recruitment rate for eligible patients was lower than expected, with some patients already feeling confident with their medication management, and there was high loss to follow-up 28 days after discharge using telephone interviews for data collection. A future definitive trial may require changes to study processes including the mode of follow-up for data collection and strategies to screen patients who will benefit most from an intervention that encourage active patient participation. For intervention acceptability, patients viewed the intervention as acceptable, while healthcare professionals were more sceptical about the intervention. While this finding is not uncommon, future iterations of the intervention must ensure there are appropriate disseminations strategies in place to fully inform healthcare professionals about the intervention benefits.

    Data availability statement

    No data are available. Participants of this study did not agree for their data to be shared publicly, so supporting data are not available. Upon reasonable request, our research team could approach the approving ethics committee to seek opportunities for data sharing.

    Ethics statements

    Patient consent for publication

    Ethics approval

    This study involves human participants and was approved. The project had ethics approval from appropriate hospitals (HREC/2021/QGC/74585) and universities (GU: 2021/436, DU: 2021-216). Participants gave informed consent to participate in the study before taking part.

    Acknowledgments

    The authors would like to thank Liz Fountain and Tarah Fantis for their contributions to data collection. Thank you to Margaret Shapiro, Chair of the Consumer Advisory Group and opinion leader, who contributed to all phases of the study but preferred not to engage in the manuscript writing phase. Thank you to the patients and healthcare professionals who so willingly supported this study.

    References

    1. ↵
      1. Uitvlugt EB,
      2. Janssen MJA,
      3. Siegert CEH, et al
      . Medication-related hospital readmissions within 30 days of discharge: prevalence, preventability, type of medication errors and risk factors. Front Pharmacol 2021;12:567424. doi:10.3389/fphar.2021.567424
    2. ↵
      1. Alqenae FA,
      2. Steinke D,
      3. Keers RN
      . Prevalence and nature of medication errors and medication-related harm following discharge from hospital to community settings: a systematic review. Drug Saf 2020;43:517–37. doi:10.1007/s40264-020-00918-3
      OpenUrlCrossRefPubMed
    3. ↵
      1. Glans M,
      2. Kragh Ekstam A,
      3. Jakobsson U, et al
      . Medication-related hospital readmissions within 30 days of discharge - a retrospective study of risk factors in older adults. PLoS ONE 2021;16:e0253024. doi:10.1371/journal.pone.0253024
    4. ↵
      1. Lim R,
      2. Ellett LMK,
      3. Semple S, et al
      . The extent of medication-related hospital admissions in Australia: a review from 1988 to 2021. Drug Saf 2022;45:249–57. doi:10.1007/s40264-021-01144-1
      OpenUrl
    5. ↵
      1. Parekh N,
      2. Ali K,
      3. Stevenson JM, et al
      . Incidence and cost of medication harm in older adults following hospital discharge: a multicentre prospective study in the UK. Br J Clin Pharmacol 2018;84:1789–97. doi:10.1111/bcp.13613
      OpenUrlCrossRefPubMed
    6. ↵
      1. Manias E
      . Medication communication: a concept analysis. J Adv Nurs 2010;66:933–43. doi:10.1111/j.1365-2648.2009.05225.x
      OpenUrlCrossRefPubMed
    7. ↵
      1. Flink M,
      2. Öhlén G,
      3. Hansagi H, et al
      . Beliefs and experiences can influence patient participation in handover between primary and secondary care--a qualitative study of patient perspectives. BMJ Qual Saf 2012;21:76–83. doi:10.1136/bmjqs-2012-001179
      OpenUrl
    8. ↵
      1. Giles SJ,
      2. Lewis PJ,
      3. Phipps DL, et al
      . Capturing patients’ perspectives on medication safety: the development of a patient-centered medication safety framework. J Patient Saf 2020;16:324–39. doi:10.1097/PTS.0000000000000583
      OpenUrl
    9. ↵
      1. Tobiano G,
      2. Manias E,
      3. Thalib L, et al
      . Older patient participation in discharge medication communication: an observational study. BMJ Open 2023;13:e064750. doi:10.1136/bmjopen-2022-064750
    10. ↵
      1. Tobiano G,
      2. Chaboyer W,
      3. Teasdale T, et al
      . Patient engagement in admission and discharge medication communication: a systematic mixed studies review. Int J Nurs Stud 2019;95:87–102. doi:10.1016/j.ijnurstu.2019.04.009
      OpenUrl
    11. ↵
      1. Tobiano G,
      2. Latimer S,
      3. Manias E, et al
      . Co-design of an intervention to improve patient participation in discharge medication communication. Int J Qual Health Care 2024;36:e1–10. doi:10.1093/intqhc/mzae013
      OpenUrl
    12. ↵
      1. Skivington K,
      2. Matthews L,
      3. Simpson SA, et al
      . A new framework for developing and evaluating complex interventions: update of medical research council guidance. BMJ 2021;374:2061. doi:10.1136/bmj.n2061
      OpenUrlCrossRef
    13. ↵
      1. Eldridge SM,
      2. Chan CL,
      3. Campbell MJ, et al
      . CONSORT 2010 statement: extension to randomised pilot and feasibility trials. BMJ 2016;355:5239. doi:10.1136/bmj.i5239
    14. ↵
      1. Billingham SAM,
      2. Whitehead AL,
      3. Julious SA
      . An audit of sample sizes for pilot and feasibility trials being undertaken in the United Kingdom registered in the United Kingdom clinical research network database. BMC Med Res Methodol 2013;13:104. doi:10.1186/1471-2288-13-104
    15. ↵
      1. Thabane L,
      2. Ma J,
      3. Chu R, et al
      . A tutorial on pilot studies: the what, why and how. BMC Med Res Methodol 2010;10:1. doi:10.1186/1471-2288-10-1
      OpenUrlCrossRefPubMed
    16. ↵
      1. State of Queensland
      . The health of queenslanders 2018. 2018. Available: https://www.health.qld.gov.au/__data/assets/pdf_file/0032/732794/cho-report-2018-full.pdf
    17. ↵
      1. Purcell A,
      2. Buckley T,
      3. King J, et al
      . Eutectic mixture of local anaesthetics (EMLA®) as a primary dressing on painful chronic leg ulcers: a pilot randomised controlled trial. Pilot Feasibility Stud 2018;4:123. doi:10.1186/s40814-018-0312-6
    18. ↵
      1. Roberts S,
      2. Desbrow B,
      3. Chaboyer W
      . Feasibility of a patient-centred nutrition intervention to improve oral intakes of patients at risk of pressure ulcer: a pilot randomised control trial. Scand J Caring Sci 2016;30:271–80. doi:10.1111/scs.12239
      OpenUrl
    19. ↵
      1. Molassiotis A,
      2. Roberts S,
      3. Cheng HL, et al
      . Partnering with families to promote nutrition in cancer care: feasibility and acceptability of the PIcNIC intervention. BMC Palliat Care 2018;17:50. doi:10.1186/s12904-018-0306-4
    20. ↵
      1. Sekhon M,
      2. Cartwright M,
      3. Francis JJ
      . Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework. BMC Health Serv Res 2017;17:88–101. doi:10.1186/s12913-017-2031-8
      OpenUrlCrossRefPubMed
    21. ↵
      1. Nguyen A,
      2. Yu K,
      3. Shakib S, et al
      . Classification of findings in the home medicines reviews of post‐discharge patients at risk of medication misadventure. Pharm Pract Res 2007;37:111–4. doi:10.1002/j.2055-2335.2007.tb00030.x
      OpenUrl
    22. ↵
      1. Hanna M,
      2. Larmour I,
      3. Wilson S, et al
      . The impact of a hospital outreach medication review service on hospital readmission and emergency department attendances. Pharm Pract Res 2016;46:112–21. doi:10.1002/jppr.1173
      OpenUrl
    23. ↵
      1. Clarke A
      . Readmission to hospital: a measure of quality or outcome? Qual Saf Health Care 2004;13:10–1. doi:10.1136/qshc.2003.008789
      OpenUrlFREE Full Text
    24. ↵
      1. Greene J,
      2. Hibbard JH
      . Why does patient activation matter? An examination of the relationships between patient activation and health-related outcomes. J Gen Intern Med 2012;27:520–6. doi:10.1007/s11606-011-1931-2
      OpenUrlCrossRefPubMed
    25. ↵
      1. Janamian T,
      2. Greco M,
      3. Cosgriff D, et al
      . Activating people to partner in health and self-care: use of the patient activation measure. Med J Aust 2022;216:S5–8. doi:10.5694/mja2.51535
      OpenUrl
    26. ↵
      1. Kanu C,
      2. Brown C,
      3. Barner J, et al
      . The effect of a tailored patient activation intervention in inflammatory bowel disease patients. J Contemp Pharm Pract 2019;66:11–21. doi:10.37901/jcphp18-00009
      OpenUrl
    27. ↵
      1. Strayer TE,
      2. Hollingsworth EK,
      3. Shah AS, et al
      . Why do older adults decline participation in research? Results from two deprescribing clinical trials. Trials 2023;24:456. doi:10.1186/s13063-023-07506-7
    28. ↵
      1. Tobiano G,
      2. Chaboyer W,
      3. Teasdale T, et al
      . Older patient and family discharge medication communication: a mixed-methods study. J Eval Clin Pract 2021;27:898–906. doi:10.1111/jep.13494
      OpenUrl
    29. ↵
      1. Fernández-Ardèvol M,
      2. Rosales A,
      3. Morey Cortès F
      . Set in stone? Mobile practices evolution in later life. MC 2023;11:40–6. doi:10.17645/mac.v11i3.6701
      OpenUrl
    30. ↵
      1. Nimrod G
      . Technophobia among older internet users. Educ Gerontol 2018;44:148–62. doi:10.1080/03601277.2018.1428145
      OpenUrl
    31. ↵
      1. Guner H,
      2. Acarturk C
      . The use and acceptance of ICT by senior citizens: a comparison of technology acceptance model (TAM) for elderly and young adults. Univ Access Inf Soc 2020;19:311–30. doi:10.1007/s10209-018-0642-4
      OpenUrl
    32. ↵
      1. Kang E,
      2. Chaboyer W,
      3. Tobiano G, et al
      . Evaluating the feasibility of a web-based discharge education programme to improve general surgical patients’ postdischarge recovery: a pilot randomised controlled trial. BMJ Open 2022;12:e054038. doi:10.1136/bmjopen-2021-054038
    33. ↵
      1. Fincham JE
      . Response rates and responsiveness for surveys, standards, and the journal. Am J Pharm Educ 2008;72:43. doi:10.5688/aj720243
    34. ↵
      1. EDd L
      . To mix or not to mix data collection modes in surveys. J Off Stat 2005;21:233–55. Available: https://bebr.ufl.edu/sites/default/files/To%20Mix%20or%20Not%20to%20Mix%20Data%20Collection%20Modes%20in%20Surveys.pdf
      OpenUrl
    35. ↵
      1. Bull C,
      2. Crilly J,
      3. Latimer S, et al
      . The initial psychometric evaluation of a new emergency department patient-reported experience measure (ED PREM). Pat Exp J 2023;10:59–74. doi:10.35680/2372-0247.1744
      OpenUrl
    36. ↵
      1. Peters LE,
      2. Zhao J,
      3. Gelzinnis S, et al
      . Use of caller ID and text messaging from cell phones to increase response rates in patient surveys. Res Methods Med Health Sci 2023;4:150–5. doi:10.1177/26320843231167496
      OpenUrl
    37. ↵
      1. Whitelaw S,
      2. Mamas MA,
      3. Topol E, et al
      . Applications of digital technology in COVID-19 pandemic planning and response. Lancet Digit Health 2020;2:e435–40. doi:10.1016/S2589-7500(20)30142-4
      OpenUrl
    38. ↵
      1. Sharara S,
      2. Radia S
      . Quick Response (QR) codes for patient information delivery: a digital innovation during the coronavirus pandemic. J Orthod 2022;49:89–97. doi:10.1177/14653125211031568
      OpenUrl
    39. ↵
      1. Fischer-Suárez N,
      2. Lozano-Paniagua D,
      3. García-Duarte S, et al
      . Using QR codes as a form of ehealth to promote health among women in a pandemic: cross-sectional study. JMIR Hum Factors 2022;9:e41143. doi:10.2196/41143
    40. ↵
      1. Azad A,
      2. Laidlaw DAH,
      3. Orlans HO
      . Using QR smartphone technology to improve patient communication and information distribution. Eye (Lond) 2022;36:1321–2. doi:10.1038/s41433-021-01757-x
      OpenUrl
    41. ↵
      1. Tobiano G,
      2. Roberts S,
      3. Muir R, et al
      . Patient-mediated interventions in hospital: a systematic review. J Adv Nurs 2023;79:418–41. doi:10.1111/jan.15500
      OpenUrl
    42. ↵
      1. Chegini Z,
      2. Arab-Zozani M,
      3. Shariful Islam SM, et al
      . Barriers and facilitators to patient engagement in patient safety from patients and healthcare professionals’ perspectives: a systematic review and meta-synthesis. Nurs Forum 2021;56:938–49. doi:10.1111/nuf.12635
      OpenUrl
    43. ↵
      1. D’Agostino TA,
      2. Atkinson TM,
      3. Latella LE, et al
      . Promoting patient participation in healthcare interactions through communication skills training: a systematic review. Pat Educ Couns 2017;100:1247–57. doi:10.1016/j.pec.2017.02.016
      OpenUrl
    44. ↵
      1. Leeman J,
      2. Birken SA,
      3. Powell BJ, et al
      . Beyond 'implementation strategies': classifying the full range of strategies used in implementation science and practice. Impl Sci 2017;12:125. doi:10.1186/s13012-017-0657-x
    45. ↵
      1. Oh SS,
      2. Kim KA,
      3. Kim M, et al
      . Measurement of digital literacy among older adults: systematic review. J Med Internet Res 2021;23:e26145. doi:10.2196/26145

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    Footnotes

    • X @georgia_tobiano, @emanias1

    • Contributors We declare that all the authors meet the criteria for authorship, have approved the final article version submitted and are listed as authors. In terms of the criteria for authorship, authors contributed in the following ways: (1) GT, EM, WC, SLL, TT, KW, KJ and APM contributed to the conception and design of the study, GT and APM contributed to the acquisition of data or GT, EM, WC, SLL, TT, KW, KJ and APM contributed to the analysis and interpretation of data; (2) GT, EM, WC, SLL, TT, KW, KJ and APM contributed to the drafting of the article or revising it critically for important intellectual content; (3) GT, EM, WC, SLL, TT, KW, KJ and APM contributed to the final approval of the version to be submitted. GT is the guarantor.

    • Funding This research was supported by the Gold Coast Health and Gold Coast Foundation Collaborative Research Grant Scheme (RGS2020-038). Two researcher’s salaries were funded by the NHMRC Centre of Research Excellence in Wiser Wound Care.

    • Competing interests None declared.

    • Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.