Michelle Cunich

Integrating evidence and individual preferences using a web-based multi-criteria decision analytic tool: An application to prostate cancer screening

AbstractBackground: Annalisa© (AL) is a web-based decision-support template grounded in multi-criteria decision analysis (MCDA). It uses a simple expected value algorithm to calculate a score for each option by taking into account the individual’s preferences for different criteria (as importance weights) and the evidence of the performance of each option on each criterion. Given the uncertainty surrounding the trade offs between benefits and harms for prostate cancer screening, this topic was chosen as the vehicle to introduce this new decision-support template. Objective: The aim of the study was to introduce a new decision-support template, AL, and to develop and pilot a decision-support tool for prostate cancer screening using it. Methods: A decision-support tool for prostate cancer screening (ALProst) was implemented in the AL template. ALProst incorporated evidence on both the benefits and the potential harms of prostate cancer screening (the ‘attributes’) from published randomized controlled trials (RCTs). Individual weights for each attribute were elicited during interviews. By combining the individual’s preferences and the evidence, the best option for the user was identified on the basis of quantified scores.A convenience sample of computer-proficient primary-care physicians (general practitioners [GPs] in Australia) from the Sydney Metropolitan area (Australia) were invited to complete a face-to-face interview involving the decision-support tool. Preference for undergoing prostate-specific antigen testing for prostate cancer, both personally and for their patients, was sought prior to seeing the tool. After gaining hands-on experience with using the tool, GPs were asked to comment on the merits of the template and the tool. Preference for presenting the benefits of prostate cancer screening as the relative or absolute risk reduction in prostate cancer-specific mortality was also sought. Results: Of 60 GPs approached, ten (six men and four women) completed an interview (16.7% response rate). Most GPs agreed/strongly agreed with positive statements about the ease with which they could use AL (seven GPs), and understand the information in, and format of, AL (nine and eight, respectively). Eight agreed/strongly agreed that ALProst would be a useful tool for discussing prostate cancer screening with their patients. GPs were also asked to nominate difficult clinical decisions that they, and their patients, have had to make; responses included cancer screening (including prostate cancer); treating patients with multiple illnesses/diseases; managing multiple cardiovascular disease risk factors; and managing patients who are receiving multiple medications. The common element was the need to consider multiple factors in making these complex decisions. Conclusions: AL is distinguishable from most other decision-support templates available today by its underlying conceptual framework, MCDA, and its power to combine individual preferences with evidence to derive the best option for the user quantitatively. It therefore becomes potentially useful for all decisions at all levels in the healthcare system. Moreover, it will provide a universal graphic ‘language’ that can overcome the burden to patients of encountering a plethora of widely varying decision aids for different conditions during their lifetime.

The impact of socioeconomic status on changes in the general and mental health of women over time: evidence from a longitudinal study of Australian women

IntroductionGenerally, men and women of higher socioeconomic status (SES) have better health. Little is known about how socioeconomic factors are associated with changes in health as women progress through mid-life. This study uses data from six survey waves (1996 to 2010) of the Australian Longitudinal Study on Women’s Health (ALSWH) to examine associations between SES and changes in the general health and mental health of a cohort of women progressing in years from 45–50 to 59–64.MethodsParticipants were 12,709 women (born 1946–51) in the ALSWH. Outcome measures were the general health and mental health subscales of the Medical Outcomes Study Short Form 36 Questionnaire (SF-36). The measure of SES was derived from factor analysis of responses to questions in the ALSWH baseline survey (1996) on school leaving age, highest qualifications, and current or last occupation.Multi-level random coefficient models, adjusted for socio-demographic factors and health behaviors, were used to analyze repeated measures of general health and mental health. Survey year accounted for changes in factors across time. In the first set of analyses we investigated associations between the SES index, used as a “continuous” variable, and general health and mental health changes over time. To illuminate the impact of different levels of SES on health, a second analysis was conducted in which SES scores were grouped into three approximately equal sized categories or “tertiles” as reported in an earlier ALSWH study. The least square means of general and mental health scores from the longitudinal models were plotted for the three SES tertiles.ResultsThe longitudinal analysis showed that, after adjusting for the effects of time and possible confounders, the general (mental) health of this cohort of mid-aged women declined (increased) over time. Higher SES women reported better health than lower SES women, and SES significantly modified the effects of time on both general and mental health in favor of higher SES women.ConclusionsThis study contributes to our current understanding of how socioeconomic and demographic factors, health behaviors and time impact on changes in the general and mental health of women progressing in years from 45–50 to 59–64.

Towards generic online multicriteria decision support in patient-centred health care

To introduce a new online generic decision support system based on multicriteria decision analysis (MCDA), implemented in practical and user‐friendly software (Annalisa©).

Sociodemographic and health-related predictors of self-reported mammogram, faecal occult blood test and prostate specific antigen test use in a large Australian study

BackgroundWhile several studies have examined factors that influence the use of breast screening mammography, faecal occult blood tests (FOBT) for bowel cancer screening and prostate specific antigen (PSA) tests for prostate disease in Australia, research directly comparing the use of these tests is sparse. We examined sociodemographic and health-related factors associated with the use of these tests in the previous two years either alone or in combination.MethodsCross-sectional analysis of self-reported questionnaire data from 96,711 women and 82,648 men aged 50 or over in The 45 and Up Study in NSW (2006–2010).Results5.9% of men had a FOBT alone, 44.9% had a PSA test alone, 18.7% had both tests, and 30.6% had neither test. 3.2% of women had a FOBT alone, 56.0% had a mammogram alone, 16.2% had both and 24.7% had neither test. Among men, age and socioeconomic factors were largely associated with having both FOBT and PSA tests. PSA testing alone was largely associated with age, family history of prostate cancer, health insurance status and visiting a doctor. Among women, age, use of hormone replacement therapy (HRT), health insurance status, family history of breast cancer, being retired and not having a disability were associated with both FOBT and mammograms. Mammography use alone was largely associated with age, use of HRT and family history of breast cancer. FOBT use alone among men was associated with high income, living in regional areas and being fully-retired and among women, being fully-retired or sick/disabled.ConclusionsThese results add to the literature on sociodemographic discrepancies related to cancer screening uptake and highlight the fact that many people are being screened for one cancer when they could be screened for two.

Assessing decision quality in patient-centred care requires a preference-sensitive measure

A theory-based instrument for measuring the quality of decisions made using any form of decision technology, including both decision-aided and unaided clinical consultations is required to enable person- and patient-centred care and to respond positively to individual heterogeneity in the value aspects of decision making. Current instruments using the term ‘decision quality’ have adopted a decision- and thus condition-specific approach. We argue that patient-centred care requires decision quality to be regarded as both preference-sensitive across multiple relevant criteria and generic across all conditions and decisions. MyDecisionQuality is grounded in prescriptive multi criteria decision analysis and employs a simple expected value algorithm to calculate a score for the quality of a decision that combines, in the clinical case, the patient’s individual preferences for eight quality criteria (expressed as importance weights) and their ratings of the decision just taken on each of these criteria (expressed as performance rates). It thus provides an index of decision quality that encompasses both these aspects. It also provides patients with help in prioritizing quality criteria for future decision making by calculating, for each criterion, the Incremental Value of Perfect Rating, that is, the increase in their decision quality score that would result if their performance rating on the criterion had been 100%, weightings unchanged. MyDecisionQuality, which is a web-based generic and preference-sensitive instrument, can constitute a key patient-reported measure of the quality of the decision-making process. It can provide the basis for future decision improvement, especially when the clinician (or other stakeholders) completes the equivalent instrument and the extent and nature of concordance and discordance can be established. Apart from its role in decision preparation and evaluation, it can also provide real time and relevant documentation for the patient’s record.

Lost productive life years caused by chronic conditions in Australians aged 45-64 years, 2010-2030.

Objectives: To estimate (1) productive life years (PLYs) lost because of chronic conditions in Australians aged 45–64 years from 2010 to 2030, and (2) the impact of this loss on gross domestic product (GDP) over the same period.

Nurse Education and the Retention of Registered Nurses in New South Wales

The retention of registered nurses (RNs) in the nursing profession has become a key issue for governments. This article examines the impact of a change in the nature of nurse education, from hospital-based to university-based training, on the labour market behaviour of RNs. The analysis indicates that RNs trained in universities are approximately 6 per cent more likely to exit the nursing workforce than hospital-trained RNs. The analysis highlights the need to develop policies to address the low retention rates for nurses in the health system such as developing clearer career paths and enhancing the non-pecuniary aspects of nursing.

The Impact of Diabetes on the Labour Force Participation, Savings and Retirement Income of Workers Aged 45-64 Years in Australia

Background Diabetes is a debilitating and costly condition. The costs of reduced labour force participation due to diabetes can have severe economic impacts on individuals by reducing their living standards during working and retirement years. Methods A purpose-built microsimulation model of Australians aged 45-64 years in 2010, Health&WealthMOD2030, was used to estimate the lost savings at age 65 due to premature exit from the labour force because of diabetes. Regression models were used to examine the differences between the projected savings and retirement incomes of people at age 65 for those currently working full or part time with no chronic health condition, full or part time with diabetes, and people not in the labour force due to diabetes. Results All Australians aged 45-65 years who are employed full time in 2010 will have accumulated some savings at age 65; whereas only 90.5% of those who are out of the labour force due to diabetes will have done so. By the time they reach age 65, those who retire from the labour force early due to diabetes have a median projected savings of less than

The impact of diabetes on the labour force participation and income poverty of workers aged 45-64 years in Australia.

35,000. This is far lower than the median value of total savings for those who remained in the labour force full time with no chronic condition, projected to have

Good agreement between self-report and centralized hospitalizations data for arthritis-related surgeries

638,000 at age 65. Conclusions Not only does premature retirement due to diabetes limit the immediate income available to individuals with this condition, but it also reduces their long-term financial capacity by reducing their accumulated savings and the income these savings could generate in retirement. Policies designed to support the labour force participation of those with diabetes, or interventions to prevent the onset of the disease itself, should be a priority to preserve living standards comparable with others who do not suffer from this condition.