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Quality of life in chronic conditions using patient-reported measures and biomarkers : a DEA analysis in type 1 diabetes

Borg, Sixten LU ; Gerdtham, Ulf-G LU ; Eeg-Olofsson, Katarina ; Palaszewski, Bo and Gudbjörnsdottir, Soffia (2019) In Health Economics Review 9(1). p.1-17
Abstract

BACKGROUND: A chronic disease impacts a patient's daily life, with the burden of symptoms and managing the condition, and concerns of progression and disease complications. Such aspects are captured by Patient-Reported Outcomes Measures (PROM), assessments of e.g. wellbeing. Patient-Reported Experience Measures (PREM) assess patients' experiences of healthcare and address patient preferences. Biomarkers are useful for monitoring disease activity and treatment effect and determining risks of progression and complications, and they provide information on current and future health. Individuals may differ in which among these aspects they consider important. We aimed to develop a measure of quality of life using biomarkers, PROM and PREM,... (More)

BACKGROUND: A chronic disease impacts a patient's daily life, with the burden of symptoms and managing the condition, and concerns of progression and disease complications. Such aspects are captured by Patient-Reported Outcomes Measures (PROM), assessments of e.g. wellbeing. Patient-Reported Experience Measures (PREM) assess patients' experiences of healthcare and address patient preferences. Biomarkers are useful for monitoring disease activity and treatment effect and determining risks of progression and complications, and they provide information on current and future health. Individuals may differ in which among these aspects they consider important. We aimed to develop a measure of quality of life using biomarkers, PROM and PREM, that would provide an unambiguous ranking of individuals, without presuming any specific set of importance weights. We anticipated it would be useful for studying needs and room for improvement, estimating the effects of interventions and comparing alternatives, and for developing healthcare with a broad focus on the individual. We wished to examine if efficiency analysis could be used for this purpose, in an application to individuals with type 1 diabetes.

RESULTS: We used PROM and PREM data linked to registry data on risk factors, in a large sample selected from the National Diabetes Registry in Sweden. Efficiency analysis appears useful for evaluating the situation of individuals with type 1 diabetes. Quality of life was estimated as efficiency, which differed by age. The contribution of different components to quality of life was heterogeneous, and differed by gender, age and duration of diabetes. Observed quality of life shortfall was mainly due to inefficiency, and to some extent due to the level of available inputs.

CONCLUSIONS: The efficiency analysis approach can use patient-reported outcomes measures, patient-reported experience measures and comorbidity risk factors to estimate quality of life with a broad focus on the individual, in individuals with type 1 diabetes. The approach enables ranking and comparisons using all these aspects in parallel, and allows each individual to express their own view of which aspects are important to them. The approach can be used for policy regarding interventions on inefficiency as well as healthcare resource allocation, although currently limited to type 1 diabetes.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Benefit-of-the-doubt, Biomarkers, Data envelopment analysis, Diabetes, Efficiency analysis, Patient-reported experience measures (PREM), Patient-reported outcomes measures (PROM), Quality of life
in
Health Economics Review
volume
9
issue
1
article number
31
pages
1 - 17
publisher
Springer Open
external identifiers
  • scopus:85074734601
  • pmid:31696324
ISSN
2191-1991
DOI
10.1186/s13561-019-0248-4https://doi.org/10.1186/s13561-019-0248-4
language
English
LU publication?
yes
id
8dd4fb7b-6a9c-4e3a-b248-3b45cd29e706
date added to LUP
2019-11-13 12:50:04
date last changed
2020-02-13 03:00:19
@article{8dd4fb7b-6a9c-4e3a-b248-3b45cd29e706,
  abstract     = {<p>BACKGROUND: A chronic disease impacts a patient's daily life, with the burden of symptoms and managing the condition, and concerns of progression and disease complications. Such aspects are captured by Patient-Reported Outcomes Measures (PROM), assessments of e.g. wellbeing. Patient-Reported Experience Measures (PREM) assess patients' experiences of healthcare and address patient preferences. Biomarkers are useful for monitoring disease activity and treatment effect and determining risks of progression and complications, and they provide information on current and future health. Individuals may differ in which among these aspects they consider important. We aimed to develop a measure of quality of life using biomarkers, PROM and PREM, that would provide an unambiguous ranking of individuals, without presuming any specific set of importance weights. We anticipated it would be useful for studying needs and room for improvement, estimating the effects of interventions and comparing alternatives, and for developing healthcare with a broad focus on the individual. We wished to examine if efficiency analysis could be used for this purpose, in an application to individuals with type 1 diabetes.</p><p>RESULTS: We used PROM and PREM data linked to registry data on risk factors, in a large sample selected from the National Diabetes Registry in Sweden. Efficiency analysis appears useful for evaluating the situation of individuals with type 1 diabetes. Quality of life was estimated as efficiency, which differed by age. The contribution of different components to quality of life was heterogeneous, and differed by gender, age and duration of diabetes. Observed quality of life shortfall was mainly due to inefficiency, and to some extent due to the level of available inputs.</p><p>CONCLUSIONS: The efficiency analysis approach can use patient-reported outcomes measures, patient-reported experience measures and comorbidity risk factors to estimate quality of life with a broad focus on the individual, in individuals with type 1 diabetes. The approach enables ranking and comparisons using all these aspects in parallel, and allows each individual to express their own view of which aspects are important to them. The approach can be used for policy regarding interventions on inefficiency as well as healthcare resource allocation, although currently limited to type 1 diabetes.</p>},
  author       = {Borg, Sixten and Gerdtham, Ulf-G and Eeg-Olofsson, Katarina and Palaszewski, Bo and Gudbjörnsdottir, Soffia},
  issn         = {2191-1991},
  language     = {eng},
  month        = {11},
  number       = {1},
  pages        = {1--17},
  publisher    = {Springer Open},
  series       = {Health Economics Review},
  title        = {Quality of life in chronic conditions using patient-reported measures and biomarkers : a DEA analysis in type 1 diabetes},
  url          = {http://dx.doi.org/10.1186/s13561-019-0248-4https://doi.org/10.1186/s13561-019-0248-4},
  doi          = {10.1186/s13561-019-0248-4https://doi.org/10.1186/s13561-019-0248-4},
  volume       = {9},
  year         = {2019},
}