Optimizing PharmacoTherapy In the Multimorbid Elderly in Primary CAre: the OPTICA Trial
NCT ID: NCT03724539
Last Updated: 2021-02-18
Study Results
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Basic Information
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COMPLETED
NA
323 participants
INTERVENTIONAL
2019-01-07
2021-02-15
Brief Summary
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Detailed Description
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Policy makers face many challenges, when they plan health care systems to meet the needs of the fast growing elderly population. More than 60% of the elderly suffer from multiple chronic conditions (multimorbidity - commonly defined as ≥3 chronic diseases) and get multiple drugs (polypharmacy - commonly defined as ≥5 regular medications). Multimorbid patients are often excluded from randomized controlled trials (RCT) and consequently most prescribing guidelines address diseases in isolation. Consequently, there is inappropriate prescribing, which results in diminished health states and lower quality of life of the patients.
Older patients usually rely on their general practitioners (GPs) to manage their medications. However, GPs often have limited time to adapt polypharmacy. Reviewing medications and understanding their interactions based on a list of diagnoses and drugs is complex and time consuming. Furthermore, due to the increase of patients with multimorbidity and polypharmacy, medication review especially in patients with many drugs is often neglected. Pilot data from the Netherlands showed that a software-assisted method, called STRIPA, was effective for optimizing pharmacotherapy in primary care. Through the OPTICA trial this tool will now be tested in the Swiss primary care context.
Study design:
The OPTICA trial is a single-site cluster randomized controlled trial (RCT), which will be conducted at the Institute for Primary Health Care of the University of Bern (BIHAM). All study-related tasks will be performed centrally at the BIHAM except for patient recruitment and use of the STRIPA, as these two tasks will be performed in participating GP offices.
The GPs in the intervention group use the STRIP assistant, whereas the GPs in the control group conduct a sham intervention: usual medication review and shared-decision making with patient. STRIPA is designed to optimize drug therapy and to advise on safe and appropriate therapy using STOPP/START criteria (STOPP = 'screening tool of older people's prescriptions'; START = 'screening tool to alert to right treatment'). Patients will be followed for 1 year with follow-up phone calls after 6 and 12 months.
Study objectives:
The primary objective of this study is to assess the effect of pharmacotherapy optimization through STRIPA on the medication appropriateness, which is measured by the medication appropriateness index (MAI) for drug overuse and by the assessment of underutilization (AOU) for drug underuse.
The secondary objective of the OPTICA study is to assess the impact of pharmacotherapy optimization by STRIPA on the parameters listed below (1- 4) as well as to examine the use of the STRIP assistant by GPs (5) and to examine patients' willingness to deprescribe (6):
1. Degree of polypharmacy
2. Degree of over- and underprescribing
3. Number of falls and fractures
4. Quality of life, including pain/discomfort
5. Health economic parameters, including direct costs of the intervention and incremental cost-effectiveness
6. Enablers and barriers faced by GPs when using the STRIP assistant
7. Patients' willingness to deprescribe
Statistical considerations:
40 clusters with a cluster size of 8-10 patients will be included. The primary analysis will be an intention-to-treat (ITT) analysis, whereby all randomised patients will be included in the group they were allocated to.
There will be two co-primary outcomes, the improvement in the MAI score at 12 months, defined as decrease of the score of at least one point, and improvement in the AOU index at 12 months, defined as a reduction of at least one prescribing omission. Both outcomes will be tested separately and success claimed if either test is significant. Adjustment for multiple testing will be performed.
In the primary analysis, the investigators will assess outcomes at the patient level, accounting for the correlated nature of data among GPs by using multilevel mixed-effects models. For the co-primary outcomes, the investigators will present and compare the proportion of patients with improvement of the MAI score and AOU index in the control and intervention groups. The relative difference between groups will be assessed using a mixed-effects logistic model with a random intercept at the GP level in order to account for clustering.
Secondary binary outcomes will be evaluated like the primary outcomes. Secondary continuous outcomes will be analyzed using random-effects linear regression with a random intercept at the GP level. Models will additionally be adjusted for the baseline value as a covariate. Secondary count outcomes will be analyzed using random-effects Poisson regression with a random intercept at the GP level.
Health economic analyses will comprise the assessment i) of resource use and cost differences between the trial arms, ii) the assessment of differences in quality-adjusted lifetime between the trial arms (expressed as quality-adjusted life years \[QALYs\]), and iii) the assessment of the cost-effectiveness of the intervention in comparison with the comparator, i.e. medication review in accordance with standard care.
Conditions
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Study Design
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RANDOMIZED
PARALLEL
The patients assigned to a cluster (i.e. GP) which was allocated to the intervention arm will undergo a systematic pharmacotherapy optimization by their GP using the STRIP assistant and shared decision making. Patients assigned to a cluster that was assigned to the control arm will receive a sham intervention, which consists of a usual medication review by the GP in accordance with usual care and shared decision making.
This RCT randomizes GPs instead of patients to prevent contamination, which would occur if the same GPs treated patients in the intervention and the control arm simultaneously.
HEALTH_SERVICES_RESEARCH
TRIPLE
* Due to the nature of the study intervention participating GPs (care providers) cannot be blinded.
* Patients remain blinded. They will not be informed to which treatment arm their GP is allocated to, in order to minimize performance and other reporting biases. Despite this, they receive a "high-level description" of the study question and the study procedures.
* Data collection for primary and secondary outcome analyses will be conducted by blinded study team members.
* Outcome adjudication (MAI and AOU assessment) will be performed by blinded study team members.
Study Groups
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STRIPA intervention
GPs in the intervention group will perform a STRIPA analysis for each of their 8-10 patients after the recruitment of the patient into the OPTICA trial, so that the results can be discussed in the next consultation and a shared decision-making can be performed.
STRIPA is a structured method to perform pharmacotherapy optimization. The STRIPA intervention in the OPTICA trial consists of 4 steps:
1. recording medication and diagnoses in STRIPA (upload from data from the 'Family medicine ICPC Research using Electronic medical records' (FIRE) database)
2. structured drug review through the GP based on the STRIPA with the integrated STOPP/START criteria
3. shared decision-making between GP and patient with possible adaptation of the recommendation
4. follow-up through study team
STRIPA intervention
STRIPA is a Dutch software-based tool for the support of the pharmaceutical analysis by 1) taking into account the predictable adverse medication effects, 2) advising safe and appropriate therapy using established STOPP/START criteria, 3) interaction monitoring, and 4) appropriate dosing in accordance with renal function. It represents a highly efficient and user-friendly software engine, which is capable of individually screening the clinical status and pharmacological therapy of older patients with multimorbidity, which can define optimal drug therapy, and which can highlight the adverse drug reaction risk. A summary of these outputs will be used as STRIPA recommendations, which will, if applicable, be implemented by GPs and patients.
Prior to the STRIPA medication review, the necessary patient information will be loaded from the FIRE database that contains data from more than 300 Swiss GP practices.
Sham intervention
Patients in the control group will receive a sham intervention, which consists of a usual medication review by their GP as well as a shared decision making of the latter.
Sham intervention
Patients being assigned to the control arm will be treated in accordance with standard care. They will receive a sham intervention, which consists of a usual medication review by their GP and a shared decision making between patient and GP.
Interventions
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STRIPA intervention
STRIPA is a Dutch software-based tool for the support of the pharmaceutical analysis by 1) taking into account the predictable adverse medication effects, 2) advising safe and appropriate therapy using established STOPP/START criteria, 3) interaction monitoring, and 4) appropriate dosing in accordance with renal function. It represents a highly efficient and user-friendly software engine, which is capable of individually screening the clinical status and pharmacological therapy of older patients with multimorbidity, which can define optimal drug therapy, and which can highlight the adverse drug reaction risk. A summary of these outputs will be used as STRIPA recommendations, which will, if applicable, be implemented by GPs and patients.
Prior to the STRIPA medication review, the necessary patient information will be loaded from the FIRE database that contains data from more than 300 Swiss GP practices.
Sham intervention
Patients being assigned to the control arm will be treated in accordance with standard care. They will receive a sham intervention, which consists of a usual medication review by their GP and a shared decision making between patient and GP.
Eligibility Criteria
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Inclusion Criteria
* Age: 65 years of age or older
* Multimorbidity: 3 or more coexistent chronic conditions defined by 3 distinct International Classification in Primary Care -2 (ICPC-2) codes defined as chronic (O'Halloran et al., 2004) with an estimated duration of 6 months or more, or based on a clinical decision supported by Pharmacost Groups (PCG) for chronic conditions in an algorithm from FIRE
* Polypharmacy: Use of five or more different regular drugs (defined as authorized medications with registration numbers) for more than 30 days before signing the informed consent form
Exclusion Criteria
* If the patient is already participating in the a different interventional study
65 Years
ALL
No
Sponsors
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Utrecht University
OTHER
University of Basel
OTHER
University of Zurich
OTHER
Swiss National Science Foundation
OTHER
University of Bern
OTHER
Responsible Party
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Principal Investigators
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Sven Streit, Prof., MD, PhD
Role: PRINCIPAL_INVESTIGATOR
University of Bern
Locations
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Berner Institut für Hausarztmedizin, BIHAM
Bern, , Switzerland
Countries
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References
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Barry PJ, Gallagher P, Ryan C, O'mahony D. START (screening tool to alert doctors to the right treatment)--an evidence-based screening tool to detect prescribing omissions in elderly patients. Age Ageing. 2007 Nov;36(6):632-8. doi: 10.1093/ageing/afm118. Epub 2007 Sep 19.
Chmiel C, Bhend H, Senn O, Zoller M, Rosemann T; FIRE study-group. The FIRE project: a milestone for research in primary care in Switzerland. Swiss Med Wkly. 2011 Jan 28;140:w13142. doi: 10.4414/smw.2011.13142. eCollection 2011.
Gallagher P, O'Mahony D. STOPP (Screening Tool of Older Persons' potentially inappropriate Prescriptions): application to acutely ill elderly patients and comparison with Beers' criteria. Age Ageing. 2008 Nov;37(6):673-9. doi: 10.1093/ageing/afn197. Epub 2008 Oct 1.
Gallagher PF, O'Connor MN, O'Mahony D. Prevention of potentially inappropriate prescribing for elderly patients: a randomized controlled trial using STOPP/START criteria. Clin Pharmacol Ther. 2011 Jun;89(6):845-54. doi: 10.1038/clpt.2011.44. Epub 2011 Apr 20.
Jadad AR, To MJ, Emara M, Jones J. Consideration of multiple chronic diseases in randomized controlled trials. JAMA. 2011 Dec 28;306(24):2670-2. doi: 10.1001/jama.2011.1886. No abstract available.
Meulendijk M, Spruit M, Drenth-van Maanen C, Numans M, Brinkkemper S, Jansen P. General practitioners' attitudes towards decision-supported prescribing: an analysis of the Dutch primary care sector. Health Informatics J. 2013 Dec;19(4):247-63. doi: 10.1177/1460458212472333.
Meulendijk MC, Spruit MR, Willeboordse F, Numans ME, Brinkkemper S, Knol W, Jansen PA, Askari M. Efficiency of Clinical Decision Support Systems Improves with Experience. J Med Syst. 2016 Apr;40(4):76. doi: 10.1007/s10916-015-0423-z. Epub 2016 Jan 20.
Samsa GP, Hanlon JT, Schmader KE, Weinberger M, Clipp EC, Uttech KM, Lewis IK, Landsman PB, Cohen HJ. A summated score for the medication appropriateness index: development and assessment of clinimetric properties including content validity. J Clin Epidemiol. 1994 Aug;47(8):891-6. doi: 10.1016/0895-4356(94)90192-9.
Somers A, Mallet L, van der Cammen T, Robays H, Petrovic M. Applicability of an adapted medication appropriateness index for detection of drug-related problems in geriatric inpatients. Am J Geriatr Pharmacother. 2012 Apr;10(2):101-9. doi: 10.1016/j.amjopharm.2012.01.003. Epub 2012 Feb 1.
O'Mahony D, O'Sullivan D, Byrne S, O'Connor MN, Ryan C, Gallagher P. STOPP/START criteria for potentially inappropriate prescribing in older people: version 2. Age Ageing. 2015 Mar;44(2):213-8. doi: 10.1093/ageing/afu145. Epub 2014 Oct 16.
Jeffry S, Ruby C, Twersky J, Hanlon JT. Effect of an interdisciplinary team on suboptimal prescribing in a long-term care facility. The Consultant Pharmacist 14(12):1386-91, 1994.
Jungo KT, Deml MJ, Schalbetter F, Moor J, Feller M, Luthold RV, Huibers CJA, Sallevelt BTGM, Meulendijk MC, Spruit M, Schwenkglenks M, Rodondi N, Streit S. A mixed methods analysis of the medication review intervention centered around the use of the 'Systematic Tool to Reduce Inappropriate Prescribing' Assistant (STRIPA) in Swiss primary care practices. BMC Health Serv Res. 2024 Mar 18;24(1):350. doi: 10.1186/s12913-024-10773-y.
Jungo KT, Weir KR, Cateau D, Streit S. Older adults' attitudes towards deprescribing and medication changes: a longitudinal sub-study of a cluster randomised controlled trial. BMJ Open. 2024 Jan 10;14(1):e075325. doi: 10.1136/bmjopen-2023-075325.
Jungo KT, Ansorg AK, Floriani C, Rozsnyai Z, Schwab N, Meier R, Valeri F, Stalder O, Limacher A, Schneider C, Bagattini M, Trelle S, Spruit M, Schwenkglenks M, Rodondi N, Streit S. Optimising prescribing in older adults with multimorbidity and polypharmacy in primary care (OPTICA): cluster randomised clinical trial. BMJ. 2023 May 24;381:e074054. doi: 10.1136/bmj-2022-074054.
Jungo KT, Meier R, Valeri F, Schwab N, Schneider C, Reeve E, Spruit M, Schwenkglenks M, Rodondi N, Streit S. Baseline characteristics and comparability of older multimorbid patients with polypharmacy and general practitioners participating in a randomized controlled primary care trial. BMC Fam Pract. 2021 Jun 22;22(1):123. doi: 10.1186/s12875-021-01488-8.
Jungo KT, Rozsnyai Z, Mantelli S, Floriani C, Lowe AL, Lindemann F, Schwab N, Meier R, Elloumi L, Huibers CJA, Sallevelt BTGM, Meulendijk MC, Reeve E, Feller M, Schneider C, Bhend H, Burki PM, Trelle S, Spruit M, Schwenkglenks M, Rodondi N, Streit S. 'Optimising PharmacoTherapy In the multimorbid elderly in primary CAre' (OPTICA) to improve medication appropriateness: study protocol of a cluster randomised controlled trial. BMJ Open. 2019 Sep 3;9(9):e031080. doi: 10.1136/bmjopen-2019-031080.
Related Links
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Project description by National Research Programme 74 "Smarter Healthcare" (NRP74) / Swiss National Science Foundation (SNSF)
Other Identifiers
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U1111-1181-9400
Identifier Type: -
Identifier Source: org_study_id
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