Within and across country variations in treatment of patients with heart failure and diabetes.
Or, Z
Shatrov, K
Penneau, A
Wodchis, W
Abiona, O
Blankart, CR
Bowden, N
Bernal-Delgado, E
Knight, H
Lorenzoni, L
Marino, A
Papanicolas, I
Riley, K
Pellet, L
Estupiñán-Romero, F
van Gool, K
Figueroa, JF
- Publisher:
- WILEY
- Publication Type:
- Journal Article
- Citation:
- Health services research, 2021, 56 Suppl 3, (S3), pp. 1358-1369
- Issue Date:
- 2021-12
Closed Access
Filename | Description | Size | |||
---|---|---|---|---|---|
1-s2.0-S0191886921003299-main.pdf | Published version | 870.65 kB | Adobe PDF |
Copyright Clearance Process
- Recently Added
- In Progress
- Closed Access
This item is closed access and not available.
Full metadata record
Field | Value | Language |
---|---|---|
dc.contributor.author | Or, Z | |
dc.contributor.author | Shatrov, K | |
dc.contributor.author | Penneau, A | |
dc.contributor.author | Wodchis, W | |
dc.contributor.author |
Abiona, O https://orcid.org/0000-0002-1696-4475 |
|
dc.contributor.author | Blankart, CR | |
dc.contributor.author | Bowden, N | |
dc.contributor.author | Bernal-Delgado, E | |
dc.contributor.author | Knight, H | |
dc.contributor.author | Lorenzoni, L | |
dc.contributor.author | Marino, A | |
dc.contributor.author | Papanicolas, I | |
dc.contributor.author | Riley, K | |
dc.contributor.author | Pellet, L | |
dc.contributor.author | Estupiñán-Romero, F | |
dc.contributor.author | van Gool, K | |
dc.contributor.author | Figueroa, JF | |
dc.date.accessioned | 2021-12-27T06:30:18Z | |
dc.date.available | 2021-07-20 | |
dc.date.available | 2021-12-27T06:30:18Z | |
dc.date.issued | 2021-12 | |
dc.identifier.citation | Health services research, 2021, 56 Suppl 3, (S3), pp. 1358-1369 | |
dc.identifier.issn | 0017-9124 | |
dc.identifier.issn | 1475-6773 | |
dc.identifier.uri | http://hdl.handle.net/10453/152523 | |
dc.description.abstract | <h4>Objective</h4>To compare within-country variation of health care utilization and spending of patients with chronic heart failure (CHF) and diabetes across countries.<h4>Data sources</h4>Patient-level linked data sources compiled by the International Collaborative on Costs, Outcomes, and Needs in Care across nine countries: Australia, Canada, England, France, Germany, New Zealand, Spain, Switzerland, and the United States.<h4>Data collection methods</h4>Patients were identified in routine hospital data with a primary diagnosis of CHF and a secondary diagnosis of diabetes in 2015/2016.<h4>Study design</h4>We calculated the care consumption of patients after a hospital admission over a year across the care pathway-ranging from primary care to home health nursing care. To compare the distribution of care consumption in each country, we use Gini coefficients, Lorenz curves, and female-male ratios for eight utilization and spending measures.<h4>Principal findings</h4>In all countries, rehabilitation and home nursing care were highly concentrated in the top decile of patients, while the number of drug prescriptions were more uniformly distributed. On average, the Gini coefficient for drug consumption is about 0.30 (95% confidence interval (CI): 0.27-0.36), while it is, 0.50 (0.45-0.56) for primary care visits, and more than 0.75 (0.81-0.92) for rehabilitation use and nurse visits at home (0.78; 0.62-0.9). Variations in spending were more pronounced than in utilization. Compared to men, women spend more days at initial hospital admission (+5%, 1.01-1.06), have a higher number of prescriptions (+7%, 1.05-1.09), and substantially more rehabilitation and home care (+20% to 35%, 0.79-1.6, 0.99-1.64), but have fewer visits to specialists (-10%; 0.84-0.97).<h4>Conclusions</h4>Distribution of health care consumption in different settings varies within countries, but there are also some common treatment patterns across all countries. Clinicians and policy makers need to look into these differences in care utilization by sex and care setting to determine whether they are justified or indicate suboptimal care. | |
dc.format | Print-Electronic | |
dc.language | eng | |
dc.publisher | WILEY | |
dc.relation.ispartof | Health services research | |
dc.relation.isbasedon | 10.1111/1475-6773.13854 | |
dc.rights | info:eu-repo/semantics/closedAccess | |
dc.subject | 1117 Public Health and Health Services, 1605 Policy and Administration | |
dc.subject.classification | Health Policy & Services | |
dc.subject.mesh | Aged | |
dc.subject.mesh | Australia | |
dc.subject.mesh | Chronic Disease | |
dc.subject.mesh | Critical Pathways | |
dc.subject.mesh | Cross-Cultural Comparison | |
dc.subject.mesh | Developed Countries | |
dc.subject.mesh | Diabetes Mellitus | |
dc.subject.mesh | Europe | |
dc.subject.mesh | Female | |
dc.subject.mesh | Heart Failure | |
dc.subject.mesh | Home Care Services | |
dc.subject.mesh | Hospitalization | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Male | |
dc.subject.mesh | North America | |
dc.subject.mesh | Primary Health Care | |
dc.subject.mesh | Rehabilitation Centers | |
dc.title | Within and across country variations in treatment of patients with heart failure and diabetes. | |
dc.type | Journal Article | |
utslib.citation.volume | 56 Suppl 3 | |
utslib.location.activity | United States | |
utslib.for | 1117 Public Health and Health Services | |
utslib.for | 1605 Policy and Administration | |
pubs.organisational-group | /University of Technology Sydney | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Health | |
pubs.organisational-group | /University of Technology Sydney/Strength - CHERE - Centre for Health Economics Research and Evaluation | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Health/Centre for Health Economics Research and Evaluation | |
utslib.copyright.status | closed_access | * |
dc.date.updated | 2021-12-27T06:30:17Z | |
pubs.issue | S3 | |
pubs.publication-status | Published | |
pubs.volume | 56 Suppl 3 | |
utslib.citation.issue | S3 |
Abstract:
Objective
To compare within-country variation of health care utilization and spending of patients with chronic heart failure (CHF) and diabetes across countries.Data sources
Patient-level linked data sources compiled by the International Collaborative on Costs, Outcomes, and Needs in Care across nine countries: Australia, Canada, England, France, Germany, New Zealand, Spain, Switzerland, and the United States.Data collection methods
Patients were identified in routine hospital data with a primary diagnosis of CHF and a secondary diagnosis of diabetes in 2015/2016.Study design
We calculated the care consumption of patients after a hospital admission over a year across the care pathway-ranging from primary care to home health nursing care. To compare the distribution of care consumption in each country, we use Gini coefficients, Lorenz curves, and female-male ratios for eight utilization and spending measures.Principal findings
In all countries, rehabilitation and home nursing care were highly concentrated in the top decile of patients, while the number of drug prescriptions were more uniformly distributed. On average, the Gini coefficient for drug consumption is about 0.30 (95% confidence interval (CI): 0.27-0.36), while it is, 0.50 (0.45-0.56) for primary care visits, and more than 0.75 (0.81-0.92) for rehabilitation use and nurse visits at home (0.78; 0.62-0.9). Variations in spending were more pronounced than in utilization. Compared to men, women spend more days at initial hospital admission (+5%, 1.01-1.06), have a higher number of prescriptions (+7%, 1.05-1.09), and substantially more rehabilitation and home care (+20% to 35%, 0.79-1.6, 0.99-1.64), but have fewer visits to specialists (-10%; 0.84-0.97).Conclusions
Distribution of health care consumption in different settings varies within countries, but there are also some common treatment patterns across all countries. Clinicians and policy makers need to look into these differences in care utilization by sex and care setting to determine whether they are justified or indicate suboptimal care.Please use this identifier to cite or link to this item:
Download statistics for the last 12 months
Not enough data to produce graph