Targeted Deprescribing in Patients on Hemodialysis

Study Overview
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Brief Summary
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Hemodialysis (HD) patients take more pills per day on average than any other chronically ill patient population. On average, an HD patient takes 19 medications per day, of which 70% may not be appropriate. The reason the medications may not be appropriate is that HD patients are rarely included in clinical trials for new medications and therefore the efficacy and safety data that exists for the general population may not actually apply to them. Tools to guide the re-assessment and discontinuation (deprescribing) of these specific medications that lack evidence for efficacy and safety in HD patients are needed. These tools will help reduce the amount of medications being taken and the potential negative consequences of taking so many medications (e.g. adverse drug reactions, drug interactions, non-adherence, increased risk of cognitive impairment, impaired balance and falls, and increased risk of morbidity, hospitalization, and mortality). Nine medications that are often inappropriately prescribed to HD patients have been identified by the investigators. These medications are: Alpha-1 Blockers, Anticonvulsants, Benzodiazepines & Z-Drugs, Loop Diuretics, Prokinetic Agents, Proton Pump Inhibitors, Quinine, Urate Lowering Agents, and Statins. The investigators developed and validated tools to help medical teams in outpatient HD units with identifying and stopping these medications in their patients. The next step will be to perform a study where test these tools are tested in practice at multiple HD centers across Canada. This initiative should decrease the average number of medications per patient and inappropriate medication use in the HD units where these tools are used. The overall objective of this study is to improve current clinical practice by optimizing medication use and prescribing patterns in the HD units across Canada.

Detailed Description
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Background: Hemodialysis (HD) patients are rarely included in clinical trials, thus medication efficacy and safety data specific to this population is lacking. Toxicity from medications inadequately removed by dialysis is also a risk for them. HD patients take an average of 19 pills daily, with 70% potentially inappropriate. This polypharmacy increases their risk of adverse events, drug-drug interactions, non-adherence, cognitive impairment, impaired balance and falls, morbidity, hospitalization and mortality. Using provincial databases, the investigators identified 9 medication classes with uncertain indications and/or safety in HD patients: Alpha-1 Blockers, Anticonvulsants, Benzodiazepines & Z-medications, Loop Diuretics, Prokinetic Agents, Proton Pump Inhibitors, Quinine, Urate Lowering Agents and Statins. The investigators developed and validated tools for deprescribing, safety monitoring and patient education for each of these medications. The next step will be to perform an implementation study evaluating these deprescribing tools at multiple HD units across Canada. The investigators hypothesize that implementation of these deprescribing tools will decrease polypharmacy and improve safety and patient satisfaction in these HD units. Specific Aims are to determine: Effectiveness of the deprescribing algorithms for decreasing polypharmacy (i.e. % of successful deprescribing of at least 1 of the medication classes at 6 month post implementation) Safety of the deprescribing algorithms using monitoring tools developed for each medication The impact of the deprescribing tools on patient satisfaction Methods: In this quasi-experimental interventional cohort study, the nephrology healthcare team will assess medications for all patients as per usual practice in their respective HD units, using the deprescribing algorithms to assist in clinical decision making and patient education tools to explain rationale to patients. Participating patients will be followed for 6 months for outcomes. The primary outcome will be proportion of individuals successfully deprescribed at least one of the 9 target medications. Additional outcomes include: Adverse events associated with deprescribing and medication class specific safety outcomes (e.g. for furosemide, the investigators will be tracking blood pressure, potassium, intradialytic weight gain and heart failure admissions) Proportion of identified candidates who began a deprescribing trial Proportion of deprescribing trials declined by medical team and patient, respectively Patient satisfaction (using a patient survey) Average number of medications per patient before/after implementation Average medication cost savings per patient Expected Results/Impact on Health Research: This study will determine the efficacy of the deprescribing algorithms on reducing polypharmacy in HD patients. It will also provide insights on knowledge translation, as investigators aim to educate providers and patients on the harms of polypharmacy and influence prescribing patterns in HD units nationally. This study will encourage other institutions to incorporate similar tools into their practice and encourage comprehensive and team based re-assessment of patient's medications.

Official Title
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Implementation of Deprescribing and Patient Education Tools In Hemodialysis Units To Decrease Polypharmacy

Conditions
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End Stage Renal Disease on Dialysis (Diagnosis)

Intervention / Treatment
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* Other: De-prescribing Trial


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: 18+ years Have been receiving outpatient HD treatment at one of the four study sites for at least the past three months Able to read and understand English and provide consent Exclusion Criteria: - Acute starts to HD

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Hemodialysis Patients<br>There will be approximately 1,200 patients in the outpatient HD units from Toronto (300), Vancouver (200), Winnipeg (400) and Halifax (300). Based on a previous pilot study, it is assumed that 80% of patients have been prescribed at least one of the nine target drugs (i.e., n=960). Of those, it is assumed that 50% will be eligible for the study (i.e., n=480). Of eligible individuals, it is assumed 88% will initiate a De-prescribing Trial (Intervention Group), resulting in an anticipated cohort of n=420. | Other: De-prescribing Trial<br>* Validated de-prescribing algorithms will be applied for any patients identified as taking one of the 9 study drugs in order to determine whether or not physician should consider a deprescribing trial. If they are are identified as candidates for deprescribing and consent to participate in the trial, they will enter the Deprescribing Trial group and begin the deprescribing trial.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Number of patients who began any of the 9 deprescribing trials who have successfully stayed off that medications by the end of the study | Numbers will be given for each of the 9 drug classes and overall | 1 year | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Number of patients who were identified as candidates for a deprescribing trial, after an assessment using one of the nine deprescribing algorithms | Numbers will be given for each of the 9 drug classes and overall | 1 year | 
| Number of patients who were identified as candidates for a deprescribing trial (after an assessment using one of the nine deprescribing algorithms) but who did not begin a deprescribing trial due to refusal by the medical team | Numbers will be given for each of the 9 drug classes and overall | 1 year | 
| Number of patients who were identified as candidates for a deprescribing trial (after an assessment using one of the nine deprescribing algorithms) but who did not begin a deprescribing trial due to refusal by the patient | Numbers will be given for each of the 9 drug classes and overall | 1 year | 
| Average number of medications (including target medications and any other medications) per patient before and after this deprescribing implementation study |  | 1 year | 
| Change in patient satisfaction scores pre-intervention vs. post-intervention, as assessed by patient satisfaction surveys (developed for this study) administered before the study and 6 months after the study start date | The patient satisfaction survey is based on the Consumer Assessment of Healthcare Providers & Systems (CAHPS®) In-Center HD Survey, which rates the medication and dialysis services. Most questions are on a Likert scale ranging from Never (1) to Always (4) or from Strongly Disagree (1) to Strong Agree (5). There are also two No (1) / Yes (2) questions and one 0 (Worst possible) to 10 (Best possible) question. The survey is divided into 3 sections: Dialysis Center Staff, Your Medications, and Deprescribing. The average total score overall for patients before vs. after the study will be compared (higher scores indicate higher satisfaction). The average total score per section for patients before vs. after the study will also be compared. | 1 year | 
| Number of participants with treatment-related adverse events, as assessed by patient monitoring app (developed for this study) | The study app will track at adverse events associated with deprescribing each of the specific medication classes. For example: for loopdiuretics, blood pressure, potassium, intradialytic weight gain and heart failure admissions will be tracked; for proton pump inhibitors, gastroesophageal reflux disease (GERD) symptom severity and frequency of antacid use will be tracked By comparing baseline symptoms to symptoms during and at the completion of deprescribing, safety concerns will be identified. | 1 year | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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deprescribing, hemodialysis, medication optimization, medication prescribing patterns, patient safety, polypharmacy, pill burden, quality improvement activity, chronic kidney disease, end-stage renal disease