Assessment of a Novel Algorithm System for Polypharmacy Patient Medication Safety and Consultation
Condition: Polypharmacy Patients
Study type: Observational

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.
    

Detailed description: 
      This is an observational, retrospective study performed on deidentified electronic health
      records (EHRs). The study includes two stages: A pilot study for training and verification of
      a novel system; and a clinical validation study for evaluating the MDI system performance in
      comparison to the clinical pharmacist.

      The main aim of the study is to determine the noninferiority of a novel system performance in
      comparison to the clinical pharmacist, for the creation of insights based on the analysis of
      multidrug patients' EHRs. The quality and accuracy of the analysis and insights is
      adjudicated by an external judging committee (the gold standard), comprised of two (2) senior
      academic clinical pharmacists (Pharm.D, Ph.D).

      The clinical site's Information systems division scanned for EHRs of multidrug patients
      according to extraction criteria. The raw data of the patients' records were reviewed by the
      principal investigator (PI). Medical coding definitions of the extraction criteria were
      modified according to discrepancies found by the PI. The patients' deidentified EHRs were
      randomized to a training cohort for the training phase and to the clinical validation cohort.

      Stage 1 of the trial was for training the MDI system on real-life patient EHRs. Deidentified
      EHRs of the training cohort were uploaded to the MDI System platform, which calculates each
      patient's risk for drug induced problems 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 MDI System output report is reviewed by the clinical team. The algorithms
      are modified based on the system-wide conclusions and the risk calculation model.

      Stage 2 of the trial was for the clinical validation of the MDI system. The MDI system and
      clinical pharmacists independently evaluated the clinical cohort EHRs and reported insights
      on conclusion sheets according to the 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.

      Agreement is defined as an identical conclusion between the MDI system/clinical pharmacist's
      conclusion on any of the categories / problems documented on the patient's conclusion sheet
      and the judging committee conclusion (the gold standard). The judges were also instructed to
      add any finding that was missing in their professional opinion from the documented patient
      conclusion sheets. Agreement of a conclusion with the judging committee's conclusion is
      marked as true positive. Nonagreement of a conclusion and the judging committee's conclusion
      is marked as false positive. A conclusion variable found missing by the judging committee is
      marked as false negative. True negatives are defined as agreement between a conclusion
      regarding a missing finding in one of the categories.

      The sample size for the clinical validation of the MDI System was based on the primary
      endpoint of non-inferiority of the diagnostic total agreement of the MDI System compared to
      the diagnostic total agreement of the Clinical Pharmacists for the total of the Combined
      Categories. The gold standard 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.

      Confidence intervals of 95% (95%CI) were calculated according to the T distribution under the
      non-inferiority assumption that the total agreement of the MDI algorithm system will not be
      inferior than the agreement accuracy of the clinical pharmacist. If the 95% CI limit of the
      percentage differences did not exceed 5% in favor of the clinical pharmacist, the
      non-inferiority hypothesis was confirmed. The calculation was performed for the primary
      endpoint (total of the five categories) and the secondary endpoints for each individual
      category.

      The discrete variables assessed in the categories: duplication of therapy, age-related issues
      and incorrect dose were medications. The discrete variables assessed in the categories:
      current side effects and future side effects were the individual side effects. Diagnostic
      accuracy of the MDI System and the Clinical Pharmacists were assessed by the Judging
      Committee (the "gold standard").

      For each subject, total agreement, PPV, NPV, sensitivity and specificity were calculated for
      all the combined categories together and for each separate category. The diagnostic accuracy
      of the total subjects is presented as mean, 95%CI of the mean, standard deviation (Std),
      median, minimum and maximum.

      In addition, overall by-line (regardless of subject) validity parameters (overall agreement,
      PPV, NPV, Sensitivity and Specificity) were analyzed using frequency, percentages and 95% CI.
    

Intervention name(s): Multi-drug analysis of polypharmacy treatment
Intervention type(s): Other
Intervention description(s): Multi-drug analysis to assess and provide insights for lowering the risk of ADRs and increasing the benefit of polypharmacy treatment
Observational model: Other
Time perspective: Retrospective
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.
      
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