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      Optimizing Therapy to Prevent Avoidable Hospital Admissions in Multimorbid Older Adults (OPERAM): cluster randomised controlled trial

      research-article
      1 , 2 , 3 , 4 , 5 , 6 , 1 , 2 , 1 , 2 , 1 , 7 , 2 , 1 , 2 , 1 , 1 , 2 , 1 , 2 , 8 , 9 , 3 , 4 , 10 , 11 , 11 , 12 , 13 , 10 , 14 , 15 , 6 , 1 , 16 , 11 , 10 , 15 , 12 , 13 , 17 , 1 , 2 , 1 , 2 , 1 , 2 , 4 , 5 , 10 , 1 , 18 , 10 , 3 , 19 , 15 , 20 , 4 , 21 , 11 , 7 , 1 , 2 ,
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          Abstract

          Objective

          To examine the effect of optimising drug treatment on drug related hospital admissions in older adults with multimorbidity and polypharmacy admitted to hospital.

          Design

          Cluster randomised controlled trial.

          Setting

          110 clusters of inpatient wards within university based hospitals in four European countries (Switzerland, Netherlands, Belgium, and Republic of Ireland) defined by attending hospital doctors.

          Participants

          2008 older adults (≥70 years) with multimorbidity (≥3 chronic conditions) and polypharmacy (≥5 drugs used long term).

          Intervention

          Clinical staff clusters were randomised to usual care or a structured pharmacotherapy optimisation intervention performed at the individual level jointly by a doctor and a pharmacist, with the support of a clinical decision software system deploying the screening tool of older person’s prescriptions and screening tool to alert to the right treatment (STOPP/START) criteria to identify potentially inappropriate prescribing.

          Main outcome measure

          Primary outcome was first drug related hospital admission within 12 months.

          Results

          2008 older adults (median nine drugs) were randomised and enrolled in 54 intervention clusters (963 participants) and 56 control clusters (1045 participants) receiving usual care. In the intervention arm, 86.1% of participants (n=789) had inappropriate prescribing, with a mean of 2.75 (SD 2.24) STOPP/START recommendations for each participant. 62.2% (n=491) had ≥1 recommendation successfully implemented at two months, predominantly discontinuation of potentially inappropriate drugs. In the intervention group, 211 participants (21.9%) experienced a first drug related hospital admission compared with 234 (22.4%) in the control group. In the intention-to-treat analysis censored for death as competing event (n=375, 18.7%), the hazard ratio for first drug related hospital admission was 0.95 (95% confidence interval 0.77 to 1.17). In the per protocol analysis, the hazard ratio for a drug related hospital admission was 0.91 (0.69 to 1.19). The hazard ratio for first fall was 0.96 (0.79 to 1.15; 237 v 263 first falls) and for death was 0.90 (0.71 to 1.13; 172 v 203 deaths).

          Conclusions

          Inappropriate prescribing was common in older adults with multimorbidity and polypharmacy admitted to hospital and was reduced through an intervention to optimise pharmacotherapy, but without effect on drug related hospital admissions. Additional efforts are needed to identify pharmacotherapy optimisation interventions that reduce inappropriate prescribing and improve patient outcomes.

          Trial registration

          ClinicalTrials.gov NCT02986425.

          Related collections

          Most cited references66

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          STOPP/START criteria for potentially inappropriate prescribing in older people: version 2

          Purpose: screening tool of older people's prescriptions (STOPP) and screening tool to alert to right treatment (START) criteria were first published in 2008. Due to an expanding therapeutics evidence base, updating of the criteria was required. Methods: we reviewed the 2008 STOPP/START criteria to add new evidence-based criteria and remove any obsolete criteria. A thorough literature review was performed to reassess the evidence base of the 2008 criteria and the proposed new criteria. Nineteen experts from 13 European countries reviewed a new draft of STOPP & START criteria including proposed new criteria. These experts were also asked to propose additional criteria they considered important to include in the revised STOPP & START criteria and to highlight any criteria from the 2008 list they considered less important or lacking an evidence base. The revised list of criteria was then validated using the Delphi consensus methodology. Results: the expert panel agreed a final list of 114 criteria after two Delphi validation rounds, i.e. 80 STOPP criteria and 34 START criteria. This represents an overall 31% increase in STOPP/START criteria compared with version 1. Several new STOPP categories were created in version 2, namely antiplatelet/anticoagulant drugs, drugs affecting, or affected by, renal function and drugs that increase anticholinergic burden; new START categories include urogenital system drugs, analgesics and vaccines. Conclusion: STOPP/START version 2 criteria have been expanded and updated for the purpose of minimizing inappropriate prescribing in older people. These criteria are based on an up-to-date literature review and consensus validation among a European panel of experts.
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            Proportional hazards tests and diagnostics based on weighted residuals

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              Modeling valuations for EuroQol health states.

              Paul Dolan (1997)
              It has become increasingly common for preference-based measures of health-related quality of life to be used in the evaluation of different health-care interventions. For one such measure, The EuroQol, designed to be used for these purposes, it was necessary to derive a single index value for each of the 243 health states it generates. The problem was that it was virtually impossible to generate direct valuations for all of these states, and thus it was necessary to find a procedure that allows the valuations of all EuroQol states to be interpolated from direct valuations on a subset of these. In a recent study, direct valuations were elicited for 42 EuroQol health states (using the time trade-off method) from a representative sample of the UK population. This article reports on the methodology that was adopted to build up a "tariff" of EuroQol values from this data. A parsimonious model that fits the data well was defined as one in which valuations were explained in terms of the level of severity associated with each dimension, an intercept associated with any move away from full health, and a term that picked up whether any dimension in the state was at its most severe level. The model presented in this article appears to predict the values of the states for which there are direct observations and, thus, can be used to interpolate values for the states for which no direct observations exist.
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                Author and article information

                Contributors
                Role: internist
                Role: research fellow
                Role: professor
                Role: professor
                Role: internist
                Role: internist
                Role: internist
                Role: statistician
                Role: research fellow
                Role: research coordinator
                Role: research fellow
                Role: research fellow
                Role: internist
                Role: clinical pharmacist
                Role: research fellow
                Role: lecturer
                Role: research fellow
                Role: geriatrician
                Role: professor
                Role: lecturer
                Role: pharmacist
                Role: data scientist
                Role: research fellow
                Role: research fellow
                Role: research fellow
                Role: research fellow
                Role: computer scientist
                Role: internist
                Role: internist
                Role: research fellow
                Role: research fellow
                Role: research fellow
                Role: pharmacist
                Role: pharmacist
                Role: research fellow
                Role: professor
                Role: professor
                Role: professor
                Role: geriatrician
                Role: professor
                Role: professor
                Role: professor
                Role: associate professor
                Role: senior clinical trial expert
                Role: professor
                Journal
                BMJ
                BMJ
                BMJ-UK
                bmj
                The BMJ
                BMJ Publishing Group Ltd.
                0959-8138
                1756-1833
                2021
                13 July 2021
                : 374
                : n1585
                Affiliations
                [1 ]Department of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
                [2 ]Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
                [3 ]Clinical Pharmacy, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
                [4 ]Clinical Pharmacy Research Group, Louvain Drug Research Institute, Université catholique de Louvain, Belgium
                [5 ]Department of Pharmacy, CHU UCL Namur, Yvoir, Belgium
                [6 ]School of Medicine, University College Cork, Cork, Republic of Ireland
                [7 ]CTU Bern, University of Bern, Bern, Switzerland
                [8 ]Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI, USA
                [9 ]Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA
                [10 ]Pharmaceutical Care Research Group, School of Pharmacy, University College Cork, Cork, Republic of Ireland
                [11 ]Department of Geriatric Medicine and Expertise Centre Pharmacotherapy in Old Persons, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
                [12 ]Geriatric Medicine Division, Cliniques Universitaires Saint-Luc, Brussels, Belgium
                [13 ]Institute of Health and Society, Université Catholique de Louvain, Belgium
                [14 ]Institute of Hospital Pharmacy, Bern University Hospital, University of Bern, Bern, Switzerland
                [15 ]Department of Information and Computing Sciences, Utrecht University, Utrecht, Netherlands
                [16 ]Division of Angiology, Swiss Cardiovascular Center, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
                [17 ]Department of Internal Medicine and Intensive Care Unit, St Antonius Hospital, Nieuwegein and Utrecht, Netherlands
                [18 ]Department of Primary School Education, University of Ioannina, Greece
                [19 ]Institute of Pharmaceutical Medicine, University of Basel, Basel, Switzerland
                [20 ]Public Health and Primary Care, Leiden University Medical Center, Leiden, Netherlands
                [21 ]Pharmacy, Cliniques Universitaires Saint-Luc, Brussels, Belgium
                Author notes
                Correspondence to: N Rodondi nicolas.rodondi@ 123456insel.ch (or @nicolasrodondi on Twitter)
                Author information
                https://orcid.org/0000-0001-9083-6896
                Article
                blum065222
                10.1136/bmj.n1585
                8276068
                34257088
                47c92b36-71fa-4fa5-ab4e-76511cc7b136
                © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                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 and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 17 June 2021
                Categories
                Research

                Medicine
                Medicine

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