Private health insurance and quality of life: perspectives of older Australians with multiple chronic conditions

2012 ◽  
Vol 18 (3) ◽  
pp. 212 ◽  
Author(s):  
Yun-Hee Jeon ◽  
Annie Black ◽  
Janelle Govett ◽  
Laurann Yen ◽  
Ian McRae

A qualitative study was conducted to explore in-depth issues relating to the health costs of chronic illness as identified in a previous study. A key theme that emerged from interviews carried out was the benefits and challenges of private health insurance (PHI) membership, and choices older Australians with multimorbidity make in accessing health services, with and without PHI. This is the focus of this paper. Semistructured interviews were conducted with 40 older people with multiple chronic conditions. Data were analysed using content analysis. Key motivators for maintaining PHI included: fear of an inability to access timely health care; the opportunity to exercise choice in service provider; a belief of being ‘better off’ both medically and financially, which was often ill-founded; and the core values of self reliance and independence. Most described financial pressure caused by rising PHI premiums as well as other out-of-pocket health related expenses. Many older people who can ill afford PHI still struggle to maintain it, potentially at the cost of their quality of life, based on beliefs about costs of health care that they have never properly assessed. The findings highlight the degree to which people whose resources are constrained are prepared to go to maintain access to private hospital care. Attention should be given to assisting older people to make informed and valid choices of health insurance derived from the facts, rather than being based on fear and assumptions.

10.2196/25175 ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. e25175
Author(s):  
David H Gustafson Sr ◽  
Marie-Louise Mares ◽  
Darcie C Johnston ◽  
Jane E Mahoney ◽  
Randall T Brown ◽  
...  

Background Multiple chronic conditions (MCCs) are common among older adults and expensive to manage. Two-thirds of Medicare beneficiaries have multiple conditions (eg, diabetes and osteoarthritis) and account for more than 90% of Medicare spending. Patients with MCCs also experience lower quality of life and worse medical and psychiatric outcomes than patients without MCCs. In primary care settings, where MCCs are generally treated, care often focuses on laboratory results and medication management, and not quality of life, due in part to time constraints. eHealth systems, which have been shown to improve multiple outcomes, may be able to fill the gap, supplementing primary care and improving these patients’ lives. Objective This study aims to assess the effects of ElderTree (ET), an eHealth intervention for older adults with MCCs, on quality of life and related measures. Methods In this unblinded study, 346 adults aged 65 years and older with at least 3 of 5 targeted high-risk chronic conditions (hypertension, hyperlipidemia, diabetes, osteoarthritis, and BMI ≥30 kg/m2) were recruited from primary care clinics and randomized in a ratio of 1:1 to one of 2 conditions: usual care (UC) plus laptop computer, internet service, and ET or a control consisting of UC plus laptop and internet but no ET. Patients with ET have access for 12 months and will be followed up for an additional 6 months, for a total of 18 months. The primary outcomes of this study are the differences between the 2 groups with regard to measures of quality of life, psychological well-being, and loneliness. The secondary outcomes are between-group differences in laboratory scores, falls, symptom distress, medication adherence, and crisis and long-term health care use. We will also examine the mediators and moderators of the effects of ET. At baseline and months 6, 12, and 18, patients complete written surveys comprising validated scales selected for good psychometric properties with similar populations; laboratory data are collected from eHealth records; health care use and chronic conditions are collected from health records and patient surveys; and ET use data are collected continuously in system logs. We will use general linear models and linear mixed models to evaluate primary and secondary outcomes over time, with treatment condition as a between-subjects factor. Separate analyses will be conducted for outcomes that are noncontinuous or not correlated with other outcomes. Results Recruitment was conducted from January 2018 to December 2019, and 346 participants were recruited. The intervention period will end in June 2021. Conclusions With self-management and motivational strategies, health tracking, educational tools, and peer community and support, ET may help improve outcomes for patients coping with ongoing, complex MCCs. In addition, it may relieve some stress on the primary care system, with potential cost implications. Trial Registration ClinicalTrials.gov NCT03387735; https://www.clinicaltrials.gov/ct2/show/NCT03387735. International Registered Report Identifier (IRRID) DERR1-10.2196/25175


2019 ◽  
Vol 25 (1) ◽  
pp. 90 ◽  
Author(s):  
Michael R. Le Grande ◽  
Graeme Tucker ◽  
Stephen Bunker ◽  
Alun C. Jackson

Despite the large number of Australians with private health insurance (PHI), normative quality-of-life data are not available for this population. The Short Form (SF)-12 has been used to characterise the health-related quality of life of Australians in the general population, but there is debate concerning the appropriate algorithm that should be used to calculate its physical and mental component summary scores. The standard (orthogonal method) approach assumes that the mental and physical components are unrelated, whereas an alternate approach (the correlated method) assumes that the two components are related. A consecutive sample of 24957 PHI members with four major initial disease conditions were administered the SF-12 via phone and 4330 participants were followed up at a mean of 16 months after the first survey. The SF-12 was scored using both the orthogonal and correlated methods, and both scoring models were assessed for model fit and ability to discriminate between the four major disease conditions. Confirmatory factor analysis demonstrated superior model fit and improved discriminative validity when the SF-12 was scored using the correlated method instead of the default orthogonal method. Further, the correlated method demonstrated utility by producing scores that were responsive to change over time.


Sign in / Sign up

Export Citation Format

Share Document