Pharmacist Led Intervention to Improve Medication Use in Older In-patients Living With Frailty: the Drug Burden Index

Sedative Adverse Reaction Clinical Trial

Official title: Pharmacist Led Intervention to Improve Medication Use in Older In-patients Living With Frailty: the Drug Burden Index

Status Active, not recruiting

Clinical Trial Summary

Older people in Canada commonly take multiple medicines for their health conditions. Certain medicines, especially when taken together can lead to serious harms, such as falls. As people age and their health changes, medicines that were once helpful may become harmful. Healthcare professionals recognise that better tools and procedures are needed to make sure that people are taking the right medicines at the right time. A tool has been recently created, called the Drug Burden Index (DBI) Calculator©, to be used by hospital pharmacists. It helps them identify which medicines (and combinations of medicines) are harmful to older people. This tool also produces reports for the doctor and for the older person and their family. In this study, hospital pharmacists will use the DBI calculator© during their normal activities. The investigators will measure what effect this has on the medicines used and health outcomes in older adults. The investigators are also interested in what influences use and impact of the calculator. For example, there may be differences in use in older males compared to females or in the benefits seen in people living with frailty compared to those who are not frail. Use of the DBI calculator© may lead to improvements in how medicines are managed in hospital. This would mean less drug costs and drug side effects. Overall, the project may lead to improving the quality of life for older Canadians. Hypothesis: Implementation of a ward-based, pharmacist-led intervention utilizing the DBI Calculator© will lead to optimization of medications, reduced DBI and improved health outcomes in frail and non-frail older adults.

Clinical Trial Description

Polypharmacy and inappropriate medication use in older adults is common and associated with a number of harms including adverse drug reactions, falls, hospitalization, reduced quality of life and mortality. There is particular concern about medications with anticholinergic and sedative effects.Older adults may be sensitive to adverse effects of these agents due to changes in pharmacokinetics (increased exposure to the drug) and pharmacodynamics (increased sensitivity to the effects). Frailty is a condition of cumulative reduction in function of multiple body systems. Frail individuals are vulnerable to external stressors and less able to recover; as such they are at greater risk of medication related harms. Anticholinergic medications are used for a variety of conditions such as allergic rhinitis, urinary incontinence, and nausea/vomiting. Other medications, including some common anti-depressants also have anticholinergic activity, even when not central to their efficacy. Sedatives may be used short term to treat insomnia and anxiety, however, many medications produce sedation as an unintended side effect. While these medications have therapeutic effects, their use in older adults has been linked to multiple adverse effects manifesting as limitations in physical and cognitive function.Furthermore, there may be reduced or limited benefits of these agents. Taken altogether, in older adults with multi-morbidity and polypharmacy there is a picture of reduced benefit and increased risk associated with use of anticholinergic and sedative medications which may be amplified among frail individuals. The Drug Burden Index (DBI) is an evidence-based risk assessment tool developed to measure exposure to anticholinergic and sedative medications to determine the effect on physical and cognitive function. DBI score has been associated in several cross-sectional studies with poorer physical function, reduced quality of life, frailty, falls and hospital readmission. Cognition and mortality have been found to be effected by DBI score in some cross-sectional studies, but not others. Longitudinal studies have found increased DBI is independently associated with lower physical function over 5 years, poorer delayed memory performance, increased physician visits and mortality. These results represent 20 different studies, span multiple countries (Australia, Canada, Finland, the Netherlands, New Zealand, UK and US) and provide a substantial argument to reduce DBI score in individuals where possible. Despite the knowledge of the risks associated with anticholinergic and sedative medications, their use is relatively common with studies showing use of one or more of these agents in approximately 20-80% of older adults. Concerningly, their use may also be more common in frail older adults who are at further risk of harm from medication use. A provincial based point prevalence study conducted within the Nova Scotia Health Authority (NSHA) found an overall prevalence of 35% of benzodiazepine use among patients admitted to acute care. The DBI was proposed as an innovative tool to identify older adults at high risk of medication associated harm, and to highlight medications that may be suitable for deprescribing. The DBI Calculator© was developed and validated to automatically calculate the DBI score and produce a detailed report with suggestions to improve the medication regimen. In a recent evaluation, the DBI Calculator© was considered useful by 80% of pharmacists. Recently, a randomized controlled trial of a pharmacist-led intervention using the tool was conducted in a large teaching hospital in Australia. Preliminary analysis found that more of the older inpatients had a reduction in their DBI score in the intervention versus the usual care group. In addition, improved clinical outcomes were detected with the intervention group experiencing fewer new adverse drug reactions while in hospital. Optimizing medication use and reducing exposure to potentially harmful medications through deprescribing may improve outcomes in frail older adults. Even so, there are numerous barriers to deprescribing such as lack of recognition of potentially harmful medications and limited time of clinicians. Hospitalization provides a unique opportunity to initiate deprescribing as there is access to an interdisciplinary team, which can conduct short term monitoring in a controlled environment. Pharmacists as medication experts on the interdisciplinary hospital team are well poised to assess medication regimens of hospitalized older adults. As such they can lead medication optimization strategies, including deprescribing (supervised withdrawal of inappropriate medications). Within NSHA, review and optimization of medications including recommendations for deprescribing is part of the role of a clinical pharmacist. As many older patients in hospital are prescribed large quantities of medications, tools such as the DBI Calculator©, can assist pharmacists in targeting deprescribing efforts. Further work is required to explore the implementation of the DBI Calculator©, and whether there is a variable effect on frail versus robust older adults and across sexes. Hypothesis and Research Question(s) Hypothesis: Implementation of a ward-based, pharmacist-led intervention utilizing the DBI Calculator© will lead to optimization of medications, reduced DBI and improved health outcomes in frail and non-frail older adults. The research questions are: 1. What is the effect of integration of the DBI Calculator© into pharmacist medication optimization activities on: 1. change in quality of medication use (measured by DBI scores and change in medications) during hospitalization and at 3 months after discharge? 2. clinical outcomes during hospitalization and at 3 months after discharge (including adverse drug reactions, hospital readmission and mortality)? 2. Is there a different effect of the intervention based on individual characteristics (frailty status and sex) and/or the setting of the intervention (i.e. different ward and/or hospital characteristics)? 3. What are the barriers to and enablers of implementation of an electronic tool, the DBI Calculator©, into pharmacist-led medication optimization activities during inpatient admissions? 4. What is the cost-effectiveness of the intervention? Overall Goal and Objectives The goal of this project is to improve health and quality of life outcomes in frail older adults through optimization of medication use during hospitalization. The objectives of this study are to: 1. Adapt the DBI Calculator© to the Canadian context 2. Describe the feasibility of implementation of the DBI Calculator© in hospital practice. 3. Evaluate the outcomes of implementation of the intervention on medication use and clinical outcomes on frail and robust older inpatients. 4. Determine the moderating factors (determinants) which may directly and indirectly influence the outcomes, either through influencing the success of implementation or through biological mechanisms in individuals (illustrated in the logic model. Achievement of these objectives will increase capacity to care for older people living with frailty through medication optimization activities. The end of grant knowledge translation goals includes raising awareness and promoting consideration of wider implementation of this tool across Nova Scotia and Canada. Number of participants Quantitative study: 50 participants/ward Total number of wards: 4 Total number of participants across all sites: 200 Identification of participants Intervention participants New patients admitted to the ward will be screened for eligibility by ward nurse or ward pharmacist. Those who are potentially eligible are asked for their consent to be approached by a member of the research team who will confirm eligibility. Informed consent process: Information about the study will be provided by a member of the research team to the potential participant with time given to consider participation and speak to family/friends/caregivers if they wish to before consenting. The ward pharmacist will determine whether the patient is competent to understand the information provided (prior to a member of the research team seeking consent). If they are competent, then they will be asked to provide written informed consent, without coercion. If they are not competent to consent, then voluntary informed consent will be sought from a substitute decision maker if available. Those who are not competent and do not have a person responsible to provide consent do not satisfy the inclusion criteria and will not be recruited to participate in the study. Research Plan Study type This project is a prospective interventional implementation study with a pre-intervention control cohort; mixed methods will be used to explore the success and moderators of implementation. Specifically, it consists of: - A retrospective study (NB: ethics for this part of the overall study has been sought separately and already approved, file number 1023666). - A before/after intervention - A multiple case study (a sub-study of the before/after intervention) A before/after intervention method was chosen as a pragmatic method to both determine the outcomes of the intervention and explore implementation. Additionally, this method was chosen to minimize contamination bias. Due to the pragmatic nature of the study, participants, researchers and those conducting the intervention will not be blinded to the intervention. Intervention Pharmacist-led medication optimization intervention using an electronic tool (DBI Calculator©). The DBI Calculator is a clinical tool which calculates a score from the medication reconciliation list. A DBI report will be created by the ward pharmacist who will then discuss their recommendations (using the report) with the healthcare team and the participant/family. The DBI report contains: 1. A full list of the participant's medications on admission to hospital (i.e. those prescribed/taken in the community prior to hospital admission - as entered by the pharmacist following taking a Best Possible Medication History conducted as part of usual care) 2. DBI score of the individual with a summary of the potential risk to the patient based on their exposure to sedative and anticholinergic medications 3. Medications contributing to the DBI score (medications with sedative and anticholinergic effects) are highlighted as potentially suitable for deprescribing 4. Space for the pharmacist and healthcare team to make notes about potential changes to medications A copy of the DBI report will be placed in progress notes and the pharmacist will document their recommendations. Changes may be made to participants' medications over the course of their stay from these recommendations and further discussions between the healthcare team and the participant/family. All decisions about changes will be conducted as deemed appropriate by the healthcare team as would occur in regular care. The DBI Calculator© provides a tool for pharmacists to review and identify potentially problematic medications and also acts as a communication and documentation method (i.e. it does not dictate care or treatment but can provide guidance to clinicians wanting to make informed decisions). A second DBI report will be created on discharge to show the changes made during admission, this will be placed in their progress notes. A copy of this report (with reasons for changes included) and additional recommendations will be given to the participant's primary care provider describing potential future changes to their medications and any need for monitoring (based on changes made in hospital). For example, if a participant had the dose of their medication reduced while in hospital with the intention of further dose reduction or cessation (which could not be completed during admission) this will be communicated to their regular primary care physician. Additionally, a consumer version of the report given to the participant/family with verbal education about what changes had been made and self-monitoring (as appropriate). Study sites The intervention is being investigated in four wards, purposely chosen to represent a variety of settings/contexts: 1. Geriatric Assessment Unit, Central Zone, Halifax Infirmary, NSHA: large tertiary care centre, urban setting 2. General surgery ward, Central Zone, Victoria General Hospital, NSHA: large tertiary care centre, urban setting 3. Mixed general medicine & surgery ward, Central Zone, Hants Community Hospital, NSHA: small community hospital, rural setting 4. Mixed general medicine & surgery ward, Central Zone, Dartmouth General Hospital, NSHA: small community hospital, suburban setting 5. Orthopaedic surgery ward, Central Zone, Halifax Infirmary, NSHA: large tertiary care centre, urban setting Data collection Participants will be recruited and baseline data collected during admission at a time suitable to them (and when they are not being seen by members of their healthcare team). It is anticipated that the interview with the participant to collect baseline data will take approximately 20-30 minutes. The time spent interacting with the pharmacist is part of regular clinical care. For the 3-month follow-up, the medical record numbers (MRNs) of participants will be given to health records and an electronic queue created and accessed by the sub-investigator (MD). Clinical Portal and HPF databases will be used to determine emergency department visits and hospital readmission up to 3 months post-discharge. Census data will be used to determine if the participant is deceased. The Drug Information System (DIS) via Health Data NS will be accessed to identify drug identification numbers (DINs), along with doses, which correspond with DBI medication(s) that the participant has filled at any pharmacy in NS (excluding over-the-counter medications unless explicitly recorded by a community pharmacy team member on the profile). This is conducted to determine DBI score 3 months post-discharge and sustainability of intervention. Accuracy of these findings will be validated by a follow-up phone call in a randomly chosen 10% of participants from the intervention group. Sub-study: Multiple case study To explore the success of implementation and identify factors that influenced implementation, a qualitative multiple case study will be conducted.At each site, two participants will be purposely sampled during the final 4 weeks of the intervention period, one who had a reduction in their DBI score and one who did not. These participants will be purposefully identified by the ward pharmacist before their discharge. The assumption of this study is that multiple factors (determinants) will influence the success of implementation such as setting, clinician and patient factors. The data sources for the analysis include, progress notes, medication information, interviews with the participant and/or family (via phone), ward pharmacist and treating physician (or medical team). Participants Participants of this sub-study will involve the following: Participants from the main study (patient participants) As per inclusion/exclusion criteria previously described. All participants in the intervention study will be informed that they may be invited (prior to discharge) to participate in a sub-study which involves a follow-up telephone interview. Potentially suitable participants selected by the ward pharmacist will be approached by a member of the research team to gain informed consent for participation in the sub-study before their discharge. Alternatively, they may be contacted via the phone after discharge to gain consent. (Note: this is separate and not related to the random 10% of participants who will receive a follow-up phone call at the 3-month follow-up to validate the robustness of the follow-up data.) . Informal caregivers/family/friends of patient participants (family participants) Patient participants will be asked at time of consent whether they have a family member/friend who is involved with decisions about medications (which may include attending medical appointments, picking up medications from a pharmacy, or discussing decisions about medications outside of formal HCP appointments). If yes, the patient participant will be instructed to ask this person whether they are willing to be involved in the sub-study, and if agreeing, will provide contact details of the individual to the researcher. The researcher will then phone the individual to gain informed consent. Alternatively, as is common in the hospital setting, family members/friends are often present at the time of discharge and therefore this may be done in person. Pharmacist and other healthcare professionals (HCPs) involved in the care of the patient participant (HCP participants) Prior to beginning the intervention on the ward, the pharmacist and relevant staff members will be provided with information about the project, including the possibility of being asked to participate in this sub-study. The pharmacist delivering the intervention will be asked to provide informed consent for participation in this sub-study. When identifying the potential patient participant, the pharmacist will also be asked to identify which team members they interacted with in relation to the DBI Calculator© for that patient. Members of the medical team will be specifically recruited based their involvement in the participant's care during hospital stay (this may include non-medical staff members such as administrative staff). Each person will be approached by the ward pharmacist to gain their consent to be approached by a member of the research team who will then obtain written informed consent. Participant Interviews For the patient and family participants recruited for the multiple case study (two patient participants per ward), it is anticipated that interviews will take approximately 30-60 minutes and will be conducted via phone at a time suitable to the participants. Interviews with medical team members will be restricted to 15-30 minutes (to avoid undue inconvenience on the staff) and conducted at a time suitable for them (in person or via phone with corresponding consent). For those who were involved with the care of both patient participants from the ward recruited for the multiple case study, they will only be interviewed once. Interviews will be audio recorded and will be semi-structured following the interview guides in the appendix. Participant withdrawals Intervention participants will be able to withdraw their consent from participation at any point during hospital discharge and up until the 3-month follow-up point without any implications for their ongoing care. Information will be requested (but not required) from any participants who do withdraw on the reason for withdrawal. Participants will be informed that after the 3-month follow-up, their information will be de-identified and as such their details cannot be withdrawn from the study. Participants will be withdrawn from the study if they are transferred to a different unit within the same hospital, or if they are transferred to another acute hospital for care. Participants will be informed by the researcher that they have been withdrawn from the study as the pharmacist is not able to complete the intervention and the investigators may not be able to collect the required data for analysis. Analysis of Data Sample size calculation This study has been powered to detect the change in prescribing at each site based on that found in the previous hospital study completed in Australia, and a reduction in new adverse drug reactions across all sites. In the Australian study 68% of intervention participants and 30% of control participants had a reduction of their DBI score by ≥0.5 points (a difference of 0.5 points is associated with clinically significant differences in physical function and falls). To detect this difference, 26 participants are required per group per site (alpha = 0.05, power = 0.8). To detect a difference between adverse drug reactions found in the Australian study (20% versus 34%) a total of 157 participants are required in each group. Therefore, the investigators aim to recruit 40 intervention participants per site: 160 intervention participants across all sites (and collect data for the same number of participants in the pre-intervention groups). To allow for drop outs, those transferred to different units during the study and missing follow-up data the investigators aim to recruit up to 50 participants per ward. Quantitative data - Change in DBI: proportion with a reduction of 0.5 in DBI between admission and discharge compared between groups (chi square), mean DBI on discharge compared between groups (t-test) - Clinical outcomes: compare between baseline and 3 months, additionally clinically outcomes will be compared between intervention participants and data collected from the retrospective study, REB file number file number 1023666 (t-test, chi square) - Feasibility: time taken to complete report and feedback to staff (descriptive) Multiple case study analysis (sub-study) NVivo will be used to manage data during collection and analysis. Analysis will be conducted using explanation building based on our logic model. As described above, two participants at each site will be sampled during the final 4 weeks of the intervention period, one with a reduction in their DBI score and one without. The data collected for this portion includes progress notes within the patient chart, medication information, and interviews with the participant/family (via phone or in person after consent within 2 weeks of discharge), ward pharmacist and other member of the medical team. The purpose of conducting this mixed methods study is to converge information to best understand the research topic (barriers and enablers of implementation of the intervention). Using a triangulation design model, the quantitative (intervention results) and qualitative (multiple case study) data is collected simultaneously and analyzed separately, after which the two sets of results are compared looking for consistency or contrast among the results. Harms This study provides a tool and a process to enhance the activities of ward pharmacists. All changes being made to participants' medications (or any other aspects of their care) will be done by their medical team (with no control or influence by the research team). The researchers will be involved in training for using the tool and data collection and not with any treatment decisions. All adverse events (such as adverse drug reactions and adverse drug withdrawal reactions) will be dealt with through the regular NSHA channels as they would in regular care. The research team is aware that unanticipated issues related to medication withdrawal may arise. The intent of this study as previously described is to limit potentially harmful and inappropriate medications in older adults in conjunction with the medical team providing care and as such may lead to the medical team initiating tapering, dose reduction and/or cessation of medications. The potential harms of medication discontinuation have been recently reviewed and include adverse drug withdrawal reactions, return of medical conditions, reversal of drug-drug interactions and disruption of the doctor-patient relationship. The review concluded that the potential for these harms was low where the discontinuation process was planned in conjunction with the health care professional(s) and patient/family members and monitored. As previously noted, the decision to discontinue (or reduce the dose) of medications will be conducted by the medical team with the patient, as they would normally do as part of regular care. This intervention only provides a tool to highlight medications which may be suitable for discontinuation/dose reduction. As such, any adverse effects of changes to medications will be monitored and documented by the medical team as part of the standard of care. For the sub-study participants, the investigators do not anticipate any harms other than inconvenience for their time. Benefits This project directly investigates the implementation of a tool to improve the care provided to older adults on hospital wards, which have a high prevalence of frailty, at a time when they are at their most vulnerable. There is significant potential for this intervention to be adopted into practice across all hospitals in Nova Scotia; results of this study will directly inform the next steps required to achieve this. Successful implementation of the DBI Calculator© could lead to reduced costs (less medication use and reduced health care utilisation though reduction in adverse drug reactions). This proposal also involves an innovative approach to determining moderators of successful outcomes through a mixed methods analysis. There is strong evidence suggesting that implementation of the DBI Calculator© will improve clinical outcomes for older adults, based on previous studies in other jurisdictions (see Background). While it is not expected that all participants will directly benefit from participation in this study, it is possible that a proportion of them will. Evaluating the intervention and feasibility on four hospital wards in Nova Scotia will ensure efficacy in this jurisdiction is consistent with the literature. Indirectly, the results of this study will improve the care of older Canadians by adding to what little is known about the risks and benefits of medication use in frail older adults. Investigations into medication use in frail older adults in acute care have found both increased and decreased use of inappropriate medications in frail older adults compared to their robust counterparts. Almost no studies were found which looked at altered clinical outcomes (such as prevalence of adverse drug reactions) in hospitalized frail older adults. The data collected in this study will be able to explore this and whether reducing high risk medication use has different outcomes in frail versus non-frail older adults. This will increase evidence for decision making and enable advocating for change in how medications are prescribed and deprescribed to ensure that the needs of this population are met. For the sub-study participants, the investigators do not anticipate any additional benefits above what has been described for the main intervention study. ;

Related Conditions & MeSH terms

• Anticholinergic Adverse Reaction
• Frailty
• Sedative Adverse Reaction

• NCT number: NCT03698487
• Study type: Interventional
• Source: Nova Scotia Health Authority
• Status: Active, not recruiting
• Phase: N/A
• Start date: February 6, 2019
• Completion date: August 2024