1
|
Sánchez-Viñas A, Corral-Partearroyo C, Gil-Girbau M, Peñarrubia-María MT, Gallardo-González C, Olmos-Palenzuela MDC, Aznar-Lou I, Serrano-Blanco A, Rubio-Valera M. Effectiveness and cost-effectiveness of an intervention to improve Initial Medication Adherence to treatments for cardiovascular diseases and diabetes in primary care: study protocol for a pragmatic cluster randomised controlled trial and economic model (the IMA-cRCT study). BMC PRIMARY CARE 2022; 23:170. [PMID: 35790915 PMCID: PMC9255541 DOI: 10.1186/s12875-022-01727-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 05/04/2022] [Indexed: 02/06/2023]
Abstract
Background Between 2 and 43% of patients who receive a new prescription in PC do not initiate their treatments. Non-initiation is associated with poorer clinical outcomes, more sick leave and higher costs to the healthcare system. Existing evidence suggests that shared decision-making positively impacts medication initiation. The IMA-cRCT assesses the effectiveness of the IMA intervention in improving adherence and clinical parameters compared to usual care in patients with a new treatment for cardiovascular disease and diabetes prescribed in PC, and its cost-effectiveness, through a cRCT and economic modelling. Methods The IMA intervention is a shared decision-making intervention based on the Theoretical Model of Non-initiation. A cRCT will be conducted in 24 PC teams in Catalonia (Spain), randomly assigned to the intervention group (1:1), and community pharmacies in the catchment areas of the intervention PC teams. Healthcare professionals in the intervention group will apply the intervention to all patients who receive a new prescription for cardiovascular disease or diabetes treatment (no other prescription from the same pharmacological group in the previous 6 months). All the study variables will be collected from real-world databases for the 12 months before and after receiving a new prescription. Effectiveness analyses will assess impact on initiation, secondary adherence, cardiovascular risk, clinical parameters and cardiovascular events. Cost-effectiveness analyses will be conducted as part of the cRCT from a healthcare and societal perspective in terms of extra cost per cardiovascular risk reduction and improved adherence; all analyses will be clustered. Economic models will be built to assess the long-term cost-effectiveness of the IMA intervention, in terms of extra cost for gains in QALY and life expectancy, using clinical trial data and data from previous studies. Discussion The IMA-cRCT represents an innovative approach to the design and evaluation of behavioural interventions that use the principles of complex interventions, pragmatic trials and implementation research. This study will provide evidence on the IMA intervention and on a new methodology for developing and evaluating complex interventions. The results of the study will be disseminated among stakeholders to facilitate its transferability to clinical practice. Trial registration ClinicalTrials.gov, NCT05026775. Registered 30th August 2021. Supplementary Information The online version contains supplementary material available at 10.1186/s12875-022-01727-6.
Collapse
|
2
|
Achkasov E, Bondarev S, Smirnov V, Waśkiewicz Z, Rosemann T, Nikolaidis PT, Knechtle B. Atrial Fibrillation in Athletes-Features of Development, Current Approaches to the Treatment, and Prevention of Complications. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:E4890. [PMID: 31817190 PMCID: PMC6950061 DOI: 10.3390/ijerph16244890] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 11/04/2019] [Accepted: 11/25/2019] [Indexed: 12/31/2022]
Abstract
Atrial fibrillation (AF) is one of the most common types of cardiac arrhythmias. This review article highlights the problem of the development of atrial fibrillation in individuals engaged in physical activity and sports. Predisposing factors, causes, and development mechanisms of atrial fibrillation in athletes from the perspective of the authors are described. Methods of treatment, as well as prevention of thromboembolic complications, are discussed. Directions for further studies of this problem and prevention of complications are proposed.
Collapse
Affiliation(s)
- Evgeny Achkasov
- Department of Sports Medicine and Medical Rehabilitation, Sechenov First Moscow State Medical University (Sechenov University), Moscow 119991, Russia; (E.A.); (S.B.); (Z.W.)
| | - Sergey Bondarev
- Department of Sports Medicine and Medical Rehabilitation, Sechenov First Moscow State Medical University (Sechenov University), Moscow 119991, Russia; (E.A.); (S.B.); (Z.W.)
| | - Victor Smirnov
- Department of Hospital Therapy, Saint-Petersburg State Pediatric Medical University Ministry of Health of Russia, Saint Petersburg 194100, Russia;
| | - Zbigniew Waśkiewicz
- Department of Sports Medicine and Medical Rehabilitation, Sechenov First Moscow State Medical University (Sechenov University), Moscow 119991, Russia; (E.A.); (S.B.); (Z.W.)
- Institute of Sport Science, Jerzy Kukuczka Academy of Physical Education, 40-065 Katowice, Poland
| | - Thomas Rosemann
- Institute of Primary Care, University of Zurich, 8091 Zurich, Switzerland;
| | | | - Beat Knechtle
- Exercise Physiology Laboratory, 18450 Nikaia, Greece;
- Medbase St. Gallen Am Vadianplatz, 9001 St. Gallen, Switzerland
| |
Collapse
|
3
|
Pandya A, Sy S, Cho S, Alam S, Weinstein MC, Gaziano TA. Validation of a Cardiovascular Disease Policy Microsimulation Model Using Both Survival and Receiver Operating Characteristic Curves. Med Decis Making 2017; 37:802-814. [PMID: 28490271 DOI: 10.1177/0272989x17706081] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
BACKGROUND Despite some advances, cardiovascular disease (CVD) remains the leading cause of death and healthcare costs in the United States. We therefore developed a comprehensive CVD policy simulation model that identifies cost-effective approaches for reducing CVD burden. This paper aims to: 1) describe our model in detail; and 2) perform model validation analyses. METHODS The model simulates 1,000,000 adults (ages 35 to 80 years) using a variety of CVD-related epidemiological data, including previously calibrated Framingham-based risk scores for coronary heart disease and stroke. We validated our microsimulation model using recent National Health and Nutrition Examination Survey (NHANES) data, with baseline values collected in 1999-2000 and cause-specific mortality follow-up through 2011. Model-based (simulated) results were compared to observed all-cause and CVD-specific mortality data (from NHANES) for the same starting population using survival curves and, in a method not typically used for disease model validation, receiver operating characteristic (ROC) curves. RESULTS Observed 10-year all-cause mortality in NHANES v. the simulation model was 11.2% (95% CI, 10.3% to 12.2%) v. 10.9%; corresponding results for CVD mortality were 2.2% (1.8% to 2.7%) v. 2.6%. Areas under the ROC curves for model-predicted 10-year all-cause and CVD mortality risks were 0.83 (0.81 to 0.85) and 0.84 (0.81 to 0.88), respectively; corresponding results for 5-year risks were 0.80 (0.77 to 0.83) and 0.81 (0.75 to 0.87), respectively. LIMITATIONS The model is limited by the uncertainties in the data used to estimate its input parameters. Additionally, our validation analyses did not include non-fatal CVD outcomes due to NHANES data limitations. CONCLUSIONS The simulation model performed well in matching to observed nationally representative longitudinal mortality data. ROC curve analysis, which has been traditionally used for risk prediction models, can also be used to assess discrimination for disease simulation models.
Collapse
Affiliation(s)
- Ankur Pandya
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA (AP, SS, SA, MCW, TAG)
| | - Stephen Sy
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA (AP, SS, SA, MCW, TAG)
| | - Sylvia Cho
- Department of Biomedical Informatics, Columbia University, New York, NY, USA (SC)
| | - Sartaj Alam
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA (AP, SS, SA, MCW, TAG)
| | - Milton C Weinstein
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA (AP, SS, SA, MCW, TAG)
| | - Thomas A Gaziano
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA (AP, SS, SA, MCW, TAG).,Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, MA, USA (TAG)
| |
Collapse
|
4
|
|
5
|
Clinical management and burden of prostate cancer: a Markov Monte Carlo model. PLoS One 2014; 9:e113432. [PMID: 25474006 PMCID: PMC4256380 DOI: 10.1371/journal.pone.0113432] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2014] [Accepted: 10/27/2014] [Indexed: 11/24/2022] Open
Abstract
Background Prostate cancer (PCa) is the most common non-skin cancer among men in developed countries. Several novel treatments have been adopted by healthcare systems to manage PCa. Most of the observational studies and randomized trials on PCa have concurrently evaluated fewer treatments over short follow-up. Further, preceding decision analytic models on PCa management have not evaluated various contemporary management options. Therefore, a contemporary decision analytic model was necessary to address limitations to the literature by synthesizing the evidence on novel treatments thereby forecasting short and long-term clinical outcomes. Objectives To develop and validate a Markov Monte Carlo model for the contemporary clinical management of PCa, and to assess the clinical burden of the disease from diagnosis to end-of-life. Methods A Markov Monte Carlo model was developed to simulate the management of PCa in men 65 years and older from diagnosis to end-of-life. Health states modeled were: risk at diagnosis, active surveillance, active treatment, PCa recurrence, PCa recurrence free, metastatic castrate resistant prostate cancer, overall and PCa death. Treatment trajectories were based on state transition probabilities derived from the literature. Validation and sensitivity analyses assessed the accuracy and robustness of model predicted outcomes. Results Validation indicated model predicted rates were comparable to observed rates in the published literature. The simulated distribution of clinical outcomes for the base case was consistent with sensitivity analyses. Predicted rate of clinical outcomes and mortality varied across risk groups. Life expectancy and health adjusted life expectancy predicted for the simulated cohort was 20.9 years (95%CI 20.5–21.3) and 18.2 years (95% CI 17.9–18.5), respectively. Conclusion Study findings indicated contemporary management strategies improved survival and quality of life in patients with PCa. This model could be used to compare long-term outcomes and life expectancy conferred of PCa management paradigms.
Collapse
|
6
|
Lewsey JD, Lawson KD, Ford I, Fox KAA, Ritchie LD, Tunstall-Pedoe H, Watt GCM, Woodward M, Kent S, Neilson M, Briggs AH. A cardiovascular disease policy model that predicts life expectancy taking into account socioeconomic deprivation. Heart 2014; 101:201-8. [PMID: 25324535 PMCID: PMC4316925 DOI: 10.1136/heartjnl-2014-305637] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Objectives A policy model is a model that can evaluate the effectiveness and cost-effectiveness of interventions and inform policy decisions. In this study, we introduce a cardiovascular disease (CVD) policy model which can be used to model remaining life expectancy including a measure of socioeconomic deprivation as an independent risk factor for CVD. Design A state transition model was developed using the Scottish Heart Health Extended Cohort (SHHEC) linked to Scottish morbidity and death records. Individuals start in a CVD-free state and can transit to three CVD event states plus a non-CVD death state. Individuals who have a non-fatal first event are then followed up until death. Taking a competing risk approach, the cause-specific hazards of a first event are modelled using parametric survival analysis. Survival following a first non-fatal event is also modelled parametrically. We assessed discrimination, validation and calibration of our model. Results Our model achieved a good level of discrimination in each component (c-statistics for men (women)—non-fatal coronary heart disease (CHD): 0.70 (0.74), non-fatal cerebrovascular disease (CBVD): 0.73 (0.76), fatal CVD: 0.77 (0.80), fatal non-CVD: 0.74 (0.72), survival after non-fatal CHD: 0.68 (0.67) and survival after non-fatal CBVD: 0.65 (0.66)). In general, our model predictions were comparable with observed event rates for a Scottish randomised statin trial population which has an overlapping follow-up period with SHHEC. After applying a calibration factor, our predictions of life expectancy closely match those published in recent national life tables. Conclusions Our model can be used to estimate the impact of primary prevention interventions on life expectancy and can assess the impact of interventions on inequalities.
Collapse
Affiliation(s)
- J D Lewsey
- Health Economics and Health Technology Assessment, Institute of Health & Wellbeing, University of Glasgow, Glasgow, UK
| | - K D Lawson
- Health Economics and Health Technology Assessment, Institute of Health & Wellbeing, University of Glasgow, Glasgow, UK
| | - I Ford
- Robertson Centre for Biostatistics, Institute of Health & Wellbeing, University of Glasgow, Glasgow, UK
| | - K A A Fox
- BHF Centre for Research Excellence, University of Edinburgh, Edinburgh, UK
| | - L D Ritchie
- Centre of Academic Primary Care, University of Aberdeen, University of Aberdeen, Aberdeen, UK
| | - H Tunstall-Pedoe
- Institute of Cardiovascular Research, University of Dundee, Ninewells Hospital, Dundee, UK
| | - G C M Watt
- General Practice & Primary Care, Institute of Health & Wellbeing, University of Glasgow, Glasgow, UK
| | - M Woodward
- The George Institute for Global Health, The University of Sydney, Sydney, New South Wales, Australia
| | - S Kent
- Health Economics and Health Technology Assessment, Institute of Health & Wellbeing, University of Glasgow, Glasgow, UK
| | - M Neilson
- Health Economics and Health Technology Assessment, Institute of Health & Wellbeing, University of Glasgow, Glasgow, UK
| | - A H Briggs
- Health Economics and Health Technology Assessment, Institute of Health & Wellbeing, University of Glasgow, Glasgow, UK
| |
Collapse
|
7
|
Jaime Caro J, Eddy DM, Kan H, Kaltz C, Patel B, Eldessouki R, Briggs AH. Questionnaire to assess relevance and credibility of modeling studies for informing health care decision making: an ISPOR-AMCP-NPC Good Practice Task Force report. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2014; 17:174-82. [PMID: 24636375 DOI: 10.1016/j.jval.2014.01.003] [Citation(s) in RCA: 128] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2014] [Accepted: 01/13/2014] [Indexed: 05/05/2023]
Abstract
The evaluation of the cost and health implications of agreeing to cover a new health technology is best accomplished using a model that mathematically combines inputs from various sources, together with assumptions about how these fit together and what might happen in reality. This need to make assumptions, the complexity of the resulting framework, the technical knowledge required, as well as funding by interested parties have led many decision makers to distrust the results of models. To assist stakeholders reviewing a model's report, questions pertaining to the credibility of a model were developed. Because credibility is insufficient, questions regarding relevance of the model results were also created. The questions are formulated such that they are readily answered and they are supplemented by helper questions that provide additional detail. Some responses indicate strongly that a model should not be used for decision making: these trigger a "fatal flaw" indicator. It is hoped that the use of this questionnaire, along with the three others in the series, will help disseminate what to look for in comparative effectiveness evidence, improve practices by researchers supplying these data, and ultimately facilitate their use by health care decision makers.
Collapse
Affiliation(s)
- J Jaime Caro
- Faculty of Medicine, McGill University, Montreal, Canada; Evidera, Lexington, MA, USA.
| | | | - Hong Kan
- Glaxo Smith Kline, Research Triangle Park, NC, USA
| | - Cheryl Kaltz
- Prescription Drug Plan, University of Michigan, Northville, MI, USA
| | - Bimal Patel
- Outcomes and PE Clinical Research Department, MedImpact Healthcare Systems, Inc., San Diego, CA, USA
| | - Randa Eldessouki
- Scientific & Health Policy Initiatives, ISPOR, Lawrenceville, NJ, USA
| | - Andrew H Briggs
- William R. Lindsay Chair of Health Economics, Health Economics & Health Technology Assessment, Institute of Health & Wellbeing, University of Glasgow, Glasgow, UK
| |
Collapse
|