Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Purpose: The aim of this study was to assess the quality of life, number of diseases and burden of morbidity of multimorbid primary care users and whether a simple disease count or a multimorbidity burden score is more predictive of quality of life. Patients and methods: Primary care patients with at least 1 of 11 specified chronic conditions were invited to participate in a postal survey. Participants completed the Disease Burden Impact Scale (DBIS) questionnaire, the five dimension-five level Euro-Qol (EQ-5D-5L) and standard demographics questions. The DBIS asks participants to self-report chronic conditions and to rate the impact of each condition. Descriptive statistics and analysis of variance were used to determine quality of life, count of diseases and burden of morbidity. Multiple linear regression analyses determined whether disease count or the DBIS, adjusted for demographics, was more predictive of the EQ-5D-5L scores. Results: Thirty-one percent (n=917) responded, from which 69 were excluded as they reported no or only one condition, leaving 848 (92%) in the analysis. Slightly more women (50.9%) participated; the mean age was 67.0 (SD 13.9) and the mean number of conditions was 6.5 (SD 3.49). The mean scores were: DBIS 15.5 (SD 12.00; score range 0-140, with higher scores indicating higher multimorbidity burden), EQ-5D-5L score 0.69 (SD 0.28; score range -0.28 [a state worse than death] to 1 [best possible health state]) and EQ-5D Visual Analog Scale (EQ-VAS) 65.44 (SD 23.66; score range 0-100 with higher scores meaning better health). The model using the DBIS score was more predictive of the EQ-5D-5L score and EQ-VAS than the model using the disease count (R2adj=0.53 using DBIS and R2adj=0.42 using disease count for EQ-5D-5L score, and R2adj=0.44 using DBIS versus R2adj=0.34 using disease count for EQ-VAS). All models were statistically significant (p<0.001). Conclusion: The DBIS is a useful measure for assessing multimorbidity from the perspective of primary care users in particular, as it is more predictive of health outcomes than a simple count of conditions.

Original publication

DOI

10.2147/PROM.S148358

Type

Journal article

Journal

Patient Relat Outcome Meas

Publication Date

2018

Volume

9

Pages

103 - 113

Keywords

chronic disease, disease burden, multimorbidity, patient-reported outcomes, quality of life