Clinical trial NCT03108092: Health Economic Evaluation Alongside the OPERAM Trial
Official title: Health Economic Evaluation Alongside the OPERAM Trial (OPtimising thERapy to Prevent Avoidable Hospital Admissions in the Multimorbid Older People: a Cluster Randomised Controlled Trial).
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: 3 or More Chronic Conditions for 6 Months or Longer
5 or More Regular Drugs
Keywords: Drug Utilization Review
Older people
Health economics
Lead sponsor: Insel Gruppe AG, University Hospital Bern
Sponsor class: OTHER
Collaborators: name: Cliniques universitaires Saint-Luc- Université Catholique de Louvain
name: Cork University Hospital
name: UMC Utrecht
name: University of Basel
name: Université Catholique de Louvain
name: Utrecht University
name: University of Bern
name: State Secretariat for Education Research and Innovation, Switzerland
name: European Commission
First posted: 2017-04-11
Enrollment: 2009
Sex: ALL
Minimum age (years): 70
Standard ages: OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: TREATMENT

Brief summary: The objective of the health economic evaluation is to perform a state-of-the-art economic analysis of the STRIP intervention, alongside the OPERAM Randomised Controlled Trial (RCT).

Detailed description: Background:

Drug-related morbidity and mortality is an increasing problem in European healthcare systems. Multimorbidity, polypharmacy and old age are important risk factors for drug-related hospital admissions (DRAs). The reported incidence of DRAs in the elderly may be as high as 30% of all acute cases, and about half of DRAs are likely to be preventable. They are mainly related to prescribing problems and non-compliance with drug regimens, and are very costly. Public funds spent on prescription medicines are steadily increasing in many European countries. Under strained budget conditions, healthcare services need to show that they provide value for money, and thus detailed health economic evaluations have become essential for health budget planning. Some studies assessing the impact of medication optimising interventions have assessed the cost-effectiveness of such interventions. A recent Cochrane review looking at interventions to optimise prescribing for the older people in care homes found an unclear effect of interventions on drug costs (Alldred DP 2013). Further assessment of healthcare costs related to inappropriate medication and the cost-effectiveness of pharmacotherapy optimising solutions is essential for a better control of rapidly increasing health care costs.

Design:

European multi-centre, cluster randomised, controlled trial of people aged 70 years or older, with multimorbidity and polypharmacy, being on an ambulatory visit or on a hospital stay in one of the four participating centres in Ireland, Belgium, Switzerland and the Netherlands. A cluster is defined around a treating physician, i.e. the treating physician is randomised and defines the allocation of his patients. Clusters of patients will be randomised to the intervention arm receiving STRIP for optimising therapy or to the control arm undergoing usual clinical care. The patients of physicians who are allocated to the intervention group will undergo a systematic drug review and pharmacotherapy optimisation by a physician and a pharmacist using STRIP, including the STRIPA software. That provides the research team with a recommendation of changes in the patient's medication. Based on STRIPA recommendation and agreement on changes to the patients' pharmacotherapy between the team of the research physician and pharmacist and the prescribing physician, will the patient receive structured counselling about his/her medication; general practitioners will receive a report. Health economic data (covering medical resource use, the provision of informal care and health-related quality of life using the EQ-5D instrument) will be collected from enrolled patients at baseline and during the follow-up phone calls after 2, 6 and 12 months. Patients will be asked to complete a booklet serving as a memory aid. Where relevant, information can also be provided by proxy respondents (e.g. family members, primary care physicians). Additionally, staff time spent on the intervention and comparable activities in the comparator arm will be collected from site staff.

Objectives:

The objectives of the health-economic evaluation are to assess the impact of pharmacotherapy optimisation by the STRIP intervention on economic parameters, health care utilisation and preference-based quality of life.

Statistical considerations:

Over all sites, 80 clusters with a cluster size ranging from 12 to 38 participants will be included. Therefore, 2000 patients, 1000 patients in each arm, will be recruited over 18 months. Health economic analyses will comprise the assessment of cost differences between the trial arms, of differences in quality-adjusted lifetime between the trial arms (expressed as quality-adjusted life years), and of the incremental cost-effectiveness of the intervention in comparison with the comparator, i.e. standard care.

Cost will be calculated by combining the healthcare resource utilisation observed in the trial with national unit costs from sources external to the trial. Health economic analyses involving costs are necessarily country-specific. It is planned to perform these analyses for at least two countries contributing patients to the OPERAM trial, which remain to be specified. This will involve the use of all or a subset of trial data (depending on the degree of heterogeneity observed between participating countries) in combination with a set of national unit costs and a national valuation algorithm for the EQ-5D. Perspectives of cost assessment remain to be decided. Typical perspectives are those of the healthcare system or a nationally relevant third party payer.

All health economic analyses will be subjected to extensive sensitivity analyses to understand the robustness of the results given stochastic uncertainty inherent in the trial data and parameter uncertainty expected for the external unit cost data.

Additionally, performance characteristics of the 5-level version (used in all patients) and the 3-level version (additionally administered in a subsample of 300 patients of the EQ-5D will be compared, e.g. in terms of discriminatory power, responsiveness to change over time and effect size.

Eligibility criteria: Inclusion Criteria:

* People 70 years of age or older
* Multimorbidity: 3 or more coexistent chronic conditions defined by 3 distinct International Classification of Diseases (ICD-10) codes with an estimated duration of 6 months or more or based on a clinical decision
* Polypharmacy i.e. five or more different regular drugs (defined as authorised medications with registration numbers) for more than 30 days.
* Estimated minimal length of stay within the cluster is sufficient to apply the intervention
* If outpatient: prescribing physician has GP function and has a planned appointment to conduct intervention

Exclusion Criteria:

* Inability to provide informed consent or to obtain informed consent from a proxy for patients with cognitive impairment
* Direct admission to palliative care (\< 24h after admission)
* Has passed or will pass a systematic structured drug review during this hospitalisation or within the last two months

Primary outcomes:
measure: The cost-effectiveness of the STRIP intervention
timeFrame: 12 months
Secondary outcomes:
measure: Healthcare utilisation
timeFrame: 12 months
measure: Informal care received
timeFrame: 12 months
measure: Healthcare costs
timeFrame: 12 months
measure: Quality of life EQ-5D
timeFrame: 2, 6, and 12 months
measure: Direct costs of the STRIP intervention
timeFrame: during the index hospitalisation at baseline
Other outcomes:
measure: Exploratory outcome measures
timeFrame: 12 months
Locations:
city: Bruxelles
country: Belgium
facility: Cliniques universitaires Saint-Luc
city: Cork
country: Ireland
facility: Dept. of Medicine (Geriatrics), University College Cork
city: Utrecht
country: Netherlands
facility: Universitair Medisch Centrum Utrecht
city: Bern
country: Switzerland
facility: University of Bern and University Hospital Bern (Inselspital)
Study officials:
affiliation: Head of Ambulatory Care Department of General Internal Medicine Inselspital, Bern University Hospital, University of Bern, Switzerland
name: Nicolas Rodondi, Prof.
role: STUDY_CHAIR
References:
citation: Laws MB. Adverse drug reactions as cause of admission to hospital: definition of adverse drug reactions needs to include overdose. BMJ. 2004 Aug 21;329(7463):459-60; author reply 460. doi: 10.1136/bmj.329.7463.459-b. No abstract available.
citation: Leendertse AJ, Egberts AC, Stoker LJ, van den Bemt PM; HARM Study Group. Frequency of and risk factors for preventable medication-related hospital admissions in the Netherlands. Arch Intern Med. 2008 Sep 22;168(17):1890-6. doi: 10.1001/archinternmed.2008.3.
citation: Gillespie U, Alassaad A, Henrohn D, Garmo H, Hammarlund-Udenaes M, Toss H, Kettis-Lindblad A, Melhus H, Morlin C. A comprehensive pharmacist intervention to reduce morbidity in patients 80 years or older: a randomized controlled trial. Arch Intern Med. 2009 May 11;169(9):894-900. doi: 10.1001/archinternmed.2009.71.
citation: Howard RL, Avery AJ, Slavenburg S, Royal S, Pipe G, Lucassen P, Pirmohamed M. Which drugs cause preventable admissions to hospital? A systematic review. Br J Clin Pharmacol. 2007 Feb;63(2):136-47. doi: 10.1111/j.1365-2125.2006.02698.x. Epub 2006 Jun 26.
citation: Alldred DP, Raynor DK, Hughes C, Barber N, Chen TF, Spoor P. Interventions to optimise prescribing for older people in care homes. Cochrane Database Syst Rev. 2013 Feb 28;(2):CD009095. doi: 10.1002/14651858.CD009095.pub2.