Data Sheet 1_Evaluation of the epidemiological and economic impact of the ADLIFE intervention on medium- to long-term in patients with advanced chronic disease.pdf
Introduction<p>Patients with advanced chronic disease (ACD) experience transitions in their clinical stability, leading to increased healthcare resource use and costs. EU-funded ADLIFE digital intervention aimed to ensure their quality of life through individualised care plans, clinical decisi...
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| _version_ | 1849927623217512448 |
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| author | Igor Larrañaga (5434382) |
| author2 | Javier Mar (85334) Ania Gorostiza (8833430) Borja García-Lorenzo (10196950) Beñat Zubeltzu (22687214) Remedios Vega (22687217) Rachelle Kaye (6829220) Gil Levy (4002569) Olga Vishnevetsky (22687220) Rikke Lyngholm Christensen (22687223) Anne Dichmann Sorknæs (18935599) Natassia Garton (22687226) Anne Swoboda (22687229) Fritz Arndt (17711075) Lisa McCann (6167027) Roma Maguire (6167015) Morven Miller (22687232) Gokce B. Laleci Erturkmen (18617965) Mustafa Yuksel (4269145) Theodoros N. Arvanitis (2178638) Chao Tong (389167) Jose I. Aznar-Baranda (22687235) Jessica Caballero (22687238) Nerea González (5464928) Juan de la Torre (22687241) Dolores Verdoy (9085276) Esteban de Manuel Keenoy (9085279) Ane Fullaondo (452170) ADLIFE Consortium (22687244) |
| author2_role | author author author author author author author author author author author author author author author author author author author author author author author author author author author author |
| author_facet | Igor Larrañaga (5434382) Javier Mar (85334) Ania Gorostiza (8833430) Borja García-Lorenzo (10196950) Beñat Zubeltzu (22687214) Remedios Vega (22687217) Rachelle Kaye (6829220) Gil Levy (4002569) Olga Vishnevetsky (22687220) Rikke Lyngholm Christensen (22687223) Anne Dichmann Sorknæs (18935599) Natassia Garton (22687226) Anne Swoboda (22687229) Fritz Arndt (17711075) Lisa McCann (6167027) Roma Maguire (6167015) Morven Miller (22687232) Gokce B. Laleci Erturkmen (18617965) Mustafa Yuksel (4269145) Theodoros N. Arvanitis (2178638) Chao Tong (389167) Jose I. Aznar-Baranda (22687235) Jessica Caballero (22687238) Nerea González (5464928) Juan de la Torre (22687241) Dolores Verdoy (9085276) Esteban de Manuel Keenoy (9085279) Ane Fullaondo (452170) ADLIFE Consortium (22687244) |
| author_role | author |
| dc.creator.none.fl_str_mv | Igor Larrañaga (5434382) Javier Mar (85334) Ania Gorostiza (8833430) Borja García-Lorenzo (10196950) Beñat Zubeltzu (22687214) Remedios Vega (22687217) Rachelle Kaye (6829220) Gil Levy (4002569) Olga Vishnevetsky (22687220) Rikke Lyngholm Christensen (22687223) Anne Dichmann Sorknæs (18935599) Natassia Garton (22687226) Anne Swoboda (22687229) Fritz Arndt (17711075) Lisa McCann (6167027) Roma Maguire (6167015) Morven Miller (22687232) Gokce B. Laleci Erturkmen (18617965) Mustafa Yuksel (4269145) Theodoros N. Arvanitis (2178638) Chao Tong (389167) Jose I. Aznar-Baranda (22687235) Jessica Caballero (22687238) Nerea González (5464928) Juan de la Torre (22687241) Dolores Verdoy (9085276) Esteban de Manuel Keenoy (9085279) Ane Fullaondo (452170) ADLIFE Consortium (22687244) |
| dc.date.none.fl_str_mv | 2025-11-26T06:31:33Z |
| dc.identifier.none.fl_str_mv | 10.3389/fpubh.2025.1682492.s001 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Data_Sheet_1_Evaluation_of_the_epidemiological_and_economic_impact_of_the_ADLIFE_intervention_on_medium-_to_long-term_in_patients_with_advanced_chronic_disease_pdf/30718556 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Public Health and Health Services not elsewhere classified advanced chronic disease digital health integrated care personalised care plan simulation model discrete event simulation economic evaluation budget impact analysis |
| dc.title.none.fl_str_mv | Data Sheet 1_Evaluation of the epidemiological and economic impact of the ADLIFE intervention on medium- to long-term in patients with advanced chronic disease.pdf |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | Introduction<p>Patients with advanced chronic disease (ACD) experience transitions in their clinical stability, leading to increased healthcare resource use and costs. EU-funded ADLIFE digital intervention aimed to ensure their quality of life through individualised care plans, clinical decision-making support, and patient empowerment. This study assessed the impact and sustainability of ADLIFE.</p>Materials and methods<p>Target population included patients aged ≥55 years with heart failure (HF) and/or chronic obstructive pulmonary disease (COPD). First, a discrete event simulation (DES) model was developed using data from Osakidetza-Basque Health Service to represent the natural history of the disease. Second, ADLIFE intervention was implemented in four pilot sites: Spain, England, Israel and Denmark. Intervention effect was quantified by comparing resource use between control and intervention groups. Finally, a budget impact analysis (BIA) was conducted by extrapolating the burden of the disease to 2030 under two scenarios: conventional and ADLIFE.</p>Results<p>ADFLIFE intervention involved 370 patients (185 intervention, 185 control). Emergency visits and consultations with primary care professionals decreased significantly, while specialist consultations increased. Depending on the pilot site, projections estimated that ACD prevalence will increase by 37–50% by 2030, increasing associated costs. Under the ADLIFE scenario, the burden of the disease could be reduced by 1–2%, resulting in cumulative savings of €4–58 million.</p>Discussion<p>Projections indicated a major challenge ahead due to a rise in ACD prevalence, highlighting the need for timely and effective healthcare responses. ADLIFE improved patient care and resource management, and its adoption could help reduce the disease burden and generate sustained long-term savings.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_69967bb97616e949f8b0c9ddbffa7a58 |
| identifier_str_mv | 10.3389/fpubh.2025.1682492.s001 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30718556 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
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| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Data Sheet 1_Evaluation of the epidemiological and economic impact of the ADLIFE intervention on medium- to long-term in patients with advanced chronic disease.pdfIgor Larrañaga (5434382)Javier Mar (85334)Ania Gorostiza (8833430)Borja García-Lorenzo (10196950)Beñat Zubeltzu (22687214)Remedios Vega (22687217)Rachelle Kaye (6829220)Gil Levy (4002569)Olga Vishnevetsky (22687220)Rikke Lyngholm Christensen (22687223)Anne Dichmann Sorknæs (18935599)Natassia Garton (22687226)Anne Swoboda (22687229)Fritz Arndt (17711075)Lisa McCann (6167027)Roma Maguire (6167015)Morven Miller (22687232)Gokce B. Laleci Erturkmen (18617965)Mustafa Yuksel (4269145)Theodoros N. Arvanitis (2178638)Chao Tong (389167)Jose I. Aznar-Baranda (22687235)Jessica Caballero (22687238)Nerea González (5464928)Juan de la Torre (22687241)Dolores Verdoy (9085276)Esteban de Manuel Keenoy (9085279)Ane Fullaondo (452170)ADLIFE Consortium (22687244)Public Health and Health Services not elsewhere classifiedadvanced chronic diseasedigital healthintegrated carepersonalised care plansimulation modeldiscrete event simulationeconomic evaluationbudget impact analysisIntroduction<p>Patients with advanced chronic disease (ACD) experience transitions in their clinical stability, leading to increased healthcare resource use and costs. EU-funded ADLIFE digital intervention aimed to ensure their quality of life through individualised care plans, clinical decision-making support, and patient empowerment. This study assessed the impact and sustainability of ADLIFE.</p>Materials and methods<p>Target population included patients aged ≥55 years with heart failure (HF) and/or chronic obstructive pulmonary disease (COPD). First, a discrete event simulation (DES) model was developed using data from Osakidetza-Basque Health Service to represent the natural history of the disease. Second, ADLIFE intervention was implemented in four pilot sites: Spain, England, Israel and Denmark. Intervention effect was quantified by comparing resource use between control and intervention groups. Finally, a budget impact analysis (BIA) was conducted by extrapolating the burden of the disease to 2030 under two scenarios: conventional and ADLIFE.</p>Results<p>ADFLIFE intervention involved 370 patients (185 intervention, 185 control). Emergency visits and consultations with primary care professionals decreased significantly, while specialist consultations increased. Depending on the pilot site, projections estimated that ACD prevalence will increase by 37–50% by 2030, increasing associated costs. Under the ADLIFE scenario, the burden of the disease could be reduced by 1–2%, resulting in cumulative savings of €4–58 million.</p>Discussion<p>Projections indicated a major challenge ahead due to a rise in ACD prevalence, highlighting the need for timely and effective healthcare responses. ADLIFE improved patient care and resource management, and its adoption could help reduce the disease burden and generate sustained long-term savings.</p>2025-11-26T06:31:33ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.3389/fpubh.2025.1682492.s001https://figshare.com/articles/dataset/Data_Sheet_1_Evaluation_of_the_epidemiological_and_economic_impact_of_the_ADLIFE_intervention_on_medium-_to_long-term_in_patients_with_advanced_chronic_disease_pdf/30718556CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/307185562025-11-26T06:31:33Z |
| spellingShingle | Data Sheet 1_Evaluation of the epidemiological and economic impact of the ADLIFE intervention on medium- to long-term in patients with advanced chronic disease.pdf Igor Larrañaga (5434382) Public Health and Health Services not elsewhere classified advanced chronic disease digital health integrated care personalised care plan simulation model discrete event simulation economic evaluation budget impact analysis |
| status_str | publishedVersion |
| title | Data Sheet 1_Evaluation of the epidemiological and economic impact of the ADLIFE intervention on medium- to long-term in patients with advanced chronic disease.pdf |
| title_full | Data Sheet 1_Evaluation of the epidemiological and economic impact of the ADLIFE intervention on medium- to long-term in patients with advanced chronic disease.pdf |
| title_fullStr | Data Sheet 1_Evaluation of the epidemiological and economic impact of the ADLIFE intervention on medium- to long-term in patients with advanced chronic disease.pdf |
| title_full_unstemmed | Data Sheet 1_Evaluation of the epidemiological and economic impact of the ADLIFE intervention on medium- to long-term in patients with advanced chronic disease.pdf |
| title_short | Data Sheet 1_Evaluation of the epidemiological and economic impact of the ADLIFE intervention on medium- to long-term in patients with advanced chronic disease.pdf |
| title_sort | Data Sheet 1_Evaluation of the epidemiological and economic impact of the ADLIFE intervention on medium- to long-term in patients with advanced chronic disease.pdf |
| topic | Public Health and Health Services not elsewhere classified advanced chronic disease digital health integrated care personalised care plan simulation model discrete event simulation economic evaluation budget impact analysis |