Assessment of a Novel Algorithm System for Polypharmacy Patient Medication Safety and Consultation

NCT05589870 | Completed

• 1 other identifier: HMO-0353-19
• Study Type: observational
• Target: 91
• Locations: 1 country
• Sites: 1

Brief Summary

The aim of this study is to determine if insights based on the analysis of historical data of multidrug patients' electronic health records, by a novel system and algorithm, is noninferior to a clinical pharmacist analysis and insights. Multidrug patients, also known as polypharmacy patients often suffer from adverse drug reactions (ADRs). In routine practice the clinical pharmacist helps prevent ADRs by comprehensive medication review, identifying drug related risks and problems and providing recommendations. The analysis of multidrug patients is highly complex and time consuming due to the large amount of multifactorial data of chronic multidrug patients' medications, symptoms, comorbidities and age-related issues. The MDI system is a tool for analyzing and providing insights on polypharmacy data \[including electronic health records (EHRs) and claims data\] to help clinicians evaluate complex medical records and ensure optimal and personal treatment recommendations. After initial training of the MDI system on historical real-life patient EHRs, the MDI system and the clinical pharmacist reviewed patient EHR data from another patient cohort according to five categories: 1) duplication of therapy, 2) age-related issues, 3) incorrect dose, 4) current side effects and 5) future side effects risks. The insights of this assessment were recorded on patient conclusion sheets and adjudicated by an external judging committee, comprised of two senior academic clinical pharmacists. The judging committee were blinded to the source of the conclusion sheets. Diagnostic accuracy parameters: agreement, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the MDI system and the clinical pharmacist were assessed. The gold standard of the diagnostic accuracy analysis was the judging committee. Assuming that the total agreement is 5% higher for the MDI System, with a non-inferiority margin of 5%, α level of 5%, statistical power of 90%, and an expected standard deviation of 15%, the minimum sample size is about 20 cases. The achieved recruitment level was more than twice as much in the actual clinical trial.

Conditions

Polypharmacy Patients

Keywords

Polypharmacy; Adverse Drug Reaction; Drug related problems; Drug induced disease; Multi-morbidity; Multi-drug treatments; Drug safety; Comprehensive medication reviews; Drug interactions; Side effects; Clinical pharmacists; Drug effects; Drug related risks

Outcome Measures

Primary Outcomes (1)

• Primary Outcome Measure: Noninferiority of agreement for combined categories

  The overall mean percentage of agreement between the MDI system/clinical pharmacists and the judging committee (gold standard) for the combined categories

  90 days

Secondary Outcomes (3)

• Secondary Outcome: Noninferiority of agreement for separate categories

  90 days

• Secondary Outcome: Noninferiority of PPV, NPV, sensitivity and specificity for the combined categories

  90 days

• Secondary Outcome: Noninferiority of PPV, NPV, sensitivity and specificity for the separate categories

  90 days

Study Arms (2)

Clinical pharmacists group

A group of patient files that were evaluated by the clinical pharmacists, Insights Insights were categorized according to five categories: 1) duplication of therapy, 2) age-related issues, 3) incorrect dose, 4) current side effects and 5) future side effects risks. An external judging committee comprised of two (2) senior clinical pharmacy doctors, who were blinded to the source of the conclusion sheets, adjudicated the MDI system and clinical pharmacist insights.

Other: Multi-drug analysis of polypharmacy treatment

MDI system group

A group of patient files that were evaluated by the MDI system. Insights were categorized according to five categories: 1) duplication of therapy, 2) age-related issues, 3) incorrect dose, 4) current side effects and 5) future side effects risks. An external judging committee comprised of two (2) senior clinical pharmacy doctors, who were blinded to the source of the conclusion sheets, adjudicated the MDI system and clinical pharmacist insights.

Other: Multi-drug analysis of polypharmacy treatment

Interventions

Multi-drug analysis of polypharmacy treatment OTHER

Multi-drug analysis to assess and provide insights for lowering the risk of ADRs and increasing the benefit of polypharmacy treatment

Clinical pharmacists group; MDI system group

Eligibility Criteria

• Age: 45 Years - 100 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients aged ≥45 years, that were prescribed at least six (6) medications on hospital admission for one of the following medical conditions: type 2 diabetes mellitus, hypertension, hyperlipidemia, ischemic heart disease, s/p cerebrovascular accident (CVA), depression, dementia, neuropathy, and related symptoms and disease states \[sleep disorder, pain, diabetic neuropathy, gastrointestinal (GI) discomfort\]. Patients were excluded from the study if they had one of the following disease states: oncologic disease, dialysis / end-stage renal disease (ESRD), epilepsy, ventilated and sedated, hyperparathyroidism or were breastfeeding or pregnant.

You may qualify if:

• Men or women aged 45 and over (inclusive) at the time of admission to hospital. Hospitalized at Hadassah Hospital from 2010 to 2017 in one of the following departments: Internal Medicine, Cardiology, Orthopedics, Neurology, Rehabilitation.
• Patients who have available hospitalization summary information available that contains the content required to complete the indicated fields (according to the fields listed in Appendix 1 - Patient Sheet).
• The patient's chronic medications at admission to hospital are from the following pharmacological families / medications: angiotensin converting enzyme inhibitors (ACEI), angiotensin II receptor blockers (ARB), Beta Blockers, calcium channel blockers (CCB), Alpha blockers, Potassium-sparing diuretics, diuretics loop, diuretics thiazide, Anti platelets agents anticoagulants, Metformin Insulin, sulfonylurea (SU) / repaglinide glucagon like peptide 1 (GLP1) analogues, dipeptidyl peptidase IV (DPP-4) inhibitors, sodium-glucose transport protein 2 (SGLT2) inhibitor, statin Fibrates, benzodiazapines / Z-drugs, Mirtazapine, selective serotonin reuptake inhibitors (SSRIs) / norepinephrine reuptake inhibitors (SNRIs), tricyclic antidepressants (TCA), Antispasmodic / Anticholinergic, Antiepileplic agents) Gabapentin, Pregabalin, Primidone) , Opioids, proton-pump inhibitors (PPIs), histamine 2 (H2) blockers.
• Take at least six (6) chronic medications from the above list at the time of admission to the hospital (the list may also include medications that have been discontinued on admission to the hospital).

You may not qualify if:

• Oncology patients
• Dialysis patients
• Epileptic patients
• Respiratory and anesthetized
• Breastfeeding patients
• Pregnant patients
• Patients with hyperparathyroidism

Sponsors & Collaborators

• MDI Health: lead
• Hadassah Medical Organization: collaborator

Study Sites (1)

Hadassah Ein Kerem

Jerusalem, 9112001, Israel

Location

Related Publications (5)

• Masnoon N, Shakib S, Kalisch-Ellett L, Caughey GE. What is polypharmacy? A systematic review of definitions. BMC Geriatr. 2017 Oct 10;17(1):230. doi: 10.1186/s12877-017-0621-2.

  PMID: 29017448 BACKGROUND

• Parameswaran Nair N, Chalmers L, Peterson GM, Bereznicki BJ, Castelino RL, Bereznicki LR. Hospitalization in older patients due to adverse drug reactions -the need for a prediction tool. Clin Interv Aging. 2016 May 2;11:497-505. doi: 10.2147/CIA.S99097. eCollection 2016.

  PMID: 27194906 BACKGROUND

• Fabbri E, Zoli M, Gonzalez-Freire M, Salive ME, Studenski SA, Ferrucci L. Aging and Multimorbidity: New Tasks, Priorities, and Frontiers for Integrated Gerontological and Clinical Research. J Am Med Dir Assoc. 2015 Aug 1;16(8):640-7. doi: 10.1016/j.jamda.2015.03.013. Epub 2015 May 7.

  PMID: 25958334 BACKGROUND

• Johnell K, Klarin I. The relationship between number of drugs and potential drug-drug interactions in the elderly: a study of over 600,000 elderly patients from the Swedish Prescribed Drug Register. Drug Saf. 2007;30(10):911-8. doi: 10.2165/00002018-200730100-00009.

  PMID: 17867728 BACKGROUND

• Syrowatka A, Song W, Amato MG, Foer D, Edrees H, Co Z, Kuznetsova M, Dulgarian S, Seger DL, Simona A, Bain PA, Purcell Jackson G, Rhee K, Bates DW. Key use cases for artificial intelligence to reduce the frequency of adverse drug events: a scoping review. Lancet Digit Health. 2022 Feb;4(2):e137-e148. doi: 10.1016/S2589-7500(21)00229-6. Epub 2021 Nov 23.

  PMID: 34836823 BACKGROUND

MeSH Terms

Conditions

Drug-Related Side Effects and Adverse Reactions

Condition Hierarchy (Ancestors)

Chemically-Induced Disorders

Study Officials

• Sigal Shafran, Dr.

  Hadassah Medical Organization

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: RETROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: October 18, 2022
• First Posted: October 21, 2022
• Study Start: February 13, 2021
• Primary Completion: July 7, 2021
• Study Completion: July 7, 2021
• Last Updated: October 23, 2023

Record last verified: 2023-10

Data Sharing

• IPD Sharing: Will not share

Locations

IL (1)