COPD Clinical Trial
Official title:
Impact of Telemedicine in the Rate of Readmission for COPD and Cost-effectiveness Analysis (e- Pneumo ) : Project CRONEX 3.0
| NCT number | NCT03505138 |
| Other study ID # | CRONEX3.0 |
| Secondary ID | |
| Status | Completed |
| Phase | N/A |
| First received | |
| Last updated | |
| Start date | May 1, 2018 |
| Est. completion date | February 1, 2019 |
| Verified date | April 2018 |
| Source | Sociedad Española de Neumología y Cirugía Torácica |
| Contact | n/a |
| Is FDA regulated | No |
| Health authority | |
| Study type | Interventional |
The prevalence of COPD is high and suppose one of the first public health problem in the
world. It has a high morbidity and mortality and healthcare costs. The economic aspect is
directly related to hospitalization, accounting for 45-50% of total expenditure of COPD.
Patients with frequent exacerbations generate most of the cost.
In these patients, there are not standardized treatments or monitoring in a medium or long
term, but it seems reasonable that the combination of various interventions (programs
self-care, active role of health professionals in consultations, home programs, group visits,
establishment action plans for patients, use of communication technologies or social
networks) may improve many patient outcomes.
The hypothesis of our work will be to introduce telemedicine platform to establish action
plans for the patient, recognition of symptoms and exacerbations, treatments for the
exacerbations, training material on COPD, smoking and inhalation therapy, establishment of a
fast and fluid communication with pulmonologist, with the purpose of responding to various
health problems that patients with COPD (exacerbator phenotype or ACO phenotype) may have. We
will study the impact of this tool to reduce the rate income or readmission for the patients
with COPD, analyzing it from the perspective of cost-effectiveness.
| Status | Completed |
| Enrollment | 120 |
| Est. completion date | February 1, 2019 |
| Est. primary completion date | December 1, 2018 |
| Accepts healthy volunteers | Accepts Healthy Volunteers |
| Gender | All |
| Age group | 18 Years and older |
| Eligibility |
Inclusion Criteria: 1. COPD, which after evaluation of its clinical history, belonging to exacerbator phenotype (chronic bronchitic / emphysema) or mixed phenotype ("COPD-asthma") readmission (2 or more income in the previous year) and are stable least six weeks before inclusion in the study. 2. Age over 18 years 3. The patient or caregiver should be able to use the tablet type telematic tool for tracking and monitoring. Exclusion Criteria: 1. Patients with severe comorbidity grade IV heart failure, renal failure on hemodialysis or active neoplasia 2. Patients with difficulties phone coverage 3. Patients with lack of adequate social and family support. 4. Patients who do not grant informed consent |
| Country | Name | City | State |
|---|---|---|---|
| Spain | Jaime Corral Peñafiel | Cáceres |
| Lead Sponsor | Collaborator |
|---|---|
| Sociedad Española de Neumología y Cirugía Torácica |
Spain,
Bischoff EW, Hamd DH, Sedeno M, Benedetti A, Schermer TR, Bernard S, Maltais F, Bourbeau J. Effects of written action plan adherence on COPD exacerbation recovery. Thorax. 2011 Jan;66(1):26-31. doi: 10.1136/thx.2009.127621. Epub 2010 Oct 30. — View Citation
Bourbeau J, Julien M, Maltais F, Rouleau M, Beaupré A, Bégin R, Renzi P, Nault D, Borycki E, Schwartzman K, Singh R, Collet JP; Chronic Obstructive Pulmonary Disease axis of the Respiratory Network Fonds de la Recherche en Santé du Québec. Reduction of hospital utilization in patients with chronic obstructive pulmonary disease: a disease-specific self-management intervention. Arch Intern Med. 2003 Mar 10;163(5):585-91. — View Citation
Cosio BG, Agustí A. Update in chronic obstructive pulmonary disease 2009. Am J Respir Crit Care Med. 2010 Apr 1;181(7):655-60. doi: 10.1164/rccm.201001-0111UP. Review. — View Citation
De Vries B, Darling-Fisher C, Thomas AC, Belanger-Shugart EB. Implementation and outcomes of group medical appointments in an outpatient specialty care clinic. J Am Acad Nurse Pract. 2008 Mar;20(3):163-9. doi: 10.1111/j.1745-7599.2007.00300.x. — View Citation
Escarrabill J. Discharge planning and home care for end-stage COPD patients. Eur Respir J. 2009 Aug;34(2):507-12. doi: 10.1183/09031936.00146308. Review. — View Citation
Hurst JR, Fitzgerald-Khan F, Quint JK, Goldring JJ, Mikelsons C, Dilworth JP, Wedzicha JA. Use and utility of a 24-hour Telephone Support Service for 'high risk' patients with COPD. Prim Care Respir J. 2010 Sep;19(3):260-5. doi: 10.4104/pcrj.2010.00035. — View Citation
Jurado Gámez B, Feu Collado N, Jurado García JC, García Gíl F, Muñoz Gomariz E, Jiménez Murillo L, Muñoz Cabrera L. Home intervention and predictor variables for rehospitalization in chronic obstructive pulmonary disease exacerbations. Arch Bronconeumol. 2013 Jan;49(1):10-4. doi: 10.1016/j.arbres.2012.08.003. Epub 2012 Oct 22. English, Spanish. — View Citation
| Type | Measure | Description | Time frame | Safety issue |
|---|---|---|---|---|
| Primary | Assess whether a telematic program intervention can decrease the rate of readmissions in patients with COPD, comparing with conventional management. | outcome measure: the rate of readmissions during the study | one year | |
| Secondary | Conducting a cost-effectiveness study that allows us to estimate the incremental cost-effectiveness ratio (ICER) of this patient group compared with the control group. | outcome measure: incremental cost-effectiveness ratio (ICER) between these two arms | one year | |
| Secondary | Compare the quality of life of COPD patients by measuring CAT in study groups | outcome measure: quality of life measured by CAT questionnaire | one year | |
| Secondary | To study the evolution of lung function in both groups after 1 year of follow up. | outcome measure: lung function by spirometry (FEV1/FVC, FVC, FEV1) | one year | |
| Secondary | Analyze the survival at 12 months follow-up in each group. | outcome measure: number of deaths in each group to see the survival in this study | one year | |
| Secondary | Analyze a biomarker predictor of exacerbation severity. | outcome measure: PCR (mg/L) | one year | |
| Secondary | Analyze the inhaler compliance and adherence of treatment in both groups. | outcome measure: Morisky-Green“s scoring | one year | |
| Secondary | Make satisfaction survey patients and caregivers, comparing both study groups. | outcome measure: satisfaction (very satisfied, satisfied, unsatisfied, very unsatisfied) | one year | |
| Secondary | Compare the quality of life of patients by measuring EQ-5D in study groups | outcome measure: EQ-5D questionnaire | one year | |
| Secondary | Analyze a biomarker predictor of exacerbation severity. | outcome measure: fibrinogen (g/L) | one year | |
| Secondary | Analyze a biomarker predictor of exacerbation severity. | outcome measure: leukocytes (mil/mm3) | one year | |
| Secondary | Analyze a biomarker predictor of exacerbation severity. | outcome measure: eosinophils (mil/mm3) | one year | |
| Secondary | Analyze a biomarker predictor of exacerbation severity. | outcome measure: pro-BNP (pg/ml) | one year | |
| Secondary | Analyze a biomarker predictor of exacerbation severity. | outcome measure: cholesterol (mg/dL) | one year | |
| Secondary | Analyze a biomarker predictor of exacerbation severity. | outcome measure: proteins (mg/dL) | one year |
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