A systematic review and meta-analysis on impact of suboptimal use of antidepressants, bisphosphonates, and statins on healthcare resource utilisation and healthcare cost.

BACKGROUND: Depression, osteoporosis, and cardiovascular disease impose a heavy economic burden on society. Understanding economic impacts of suboptimal use of medication due to nonadherence and non-persistence (non-MAP) for these conditions is important for clinical practice and health policy-making. OBJECTIVE: This systematic literature review aims to assess the impact of non-MAP to antidepressants, bisphosphonates and statins on healthcare resource utilisation and healthcare cost (HRUHC), and to assess how these impacts differ across medication classes. METHODS: A systematic literature review and an aggregate meta-analysis were performed. Using the search protocol developed, PubMed, Cochrane Library, ClinicalTrials.gov, JSTOR and EconLit were searched for articles that explored the relationship between non-MAP and HRUHC (i.e., use of hospital, visit to healthcare service providers other than hospital, and healthcare cost components including medical cost and pharmacy cost) published from November 2004 to April 2021. Inverse-variance meta-analysis was used to assess the relationship between non-MAP and HRUHC when reported for at least two different populations. RESULTS: Screening 1,123 articles left 10, seven and 13 articles on antidepressants, bisphosphonates, and statins, respectively. Of those, 27 were rated of good quality, three fair and none poor using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. In general, non-MAP was positively associated with HRUHC for all three medication classes and most prominently for bisphosphonates, although the relationships differed across HRUHC components and medication classes. The meta-analysis found that non-MAP was associated with increased hospital cost (26%, p = 0.02), outpatient cost (10%, p = 0.01), and total medical cost excluding pharmacy cost (12%, p<0.00001) for antidepressants, and increased total healthcare cost (3%, p = 0.07) for bisphosphonates. CONCLUSIONS: This systematic literature review is the first to compare the impact of non-MAP on HRUHC across medications for three prevalent conditions, depression, osteoporosis and cardiovascular disease. Positive relationships between non-MAP and HRUHC highlight inefficiencies within the healthcare system related to non-MAP, suggesting a need to reduce non-MAP in a cost-effective way.

Identifying temporal patterns of adherence to antidepressants, bisphosphonates and statins, and associated patient factors.

BACKGROUND: Group-based trajectory modelling (GBTM) has recently been explored internationally as an improved approach to measuring medication adherence (MA) by differentiating between alternative temporal patterns of nonadherence. To build on this international research, we use the method to identify temporal patterns of medication adherence to antidepressants, bisphosphonates or statins, and their associations with patient characteristics. OBJECTIVES: The objectives include identification of MA types using GBTM, exploration of features and associated patient characteristics of each MA type, and identification of the advantages of GBTM compared to the traditional proportion of days covered (PDC) measure. DATA AND METHODS: We used 45 and Up Study survey data which contains information about demographics, family, health, diet, work and lifestyle of 267,153 participants aged at least 45 years across New South Wales, Australia. This data was linked to participant records of medication use, outpatient and inpatient care, and death. Our study participants initiated use of antidepressants (9287 participants), bisphosphonates (1660 participants) or statins (10,242 participants) during 2012-2016. MA types were identified from 180-day patterns of medication use for antidepressants and 360-day patterns for bisphosphonates and statins. Multinomial and binomial logistic regressions were performed to estimate participant characteristics associated with GBTM MA and PDC MA, respectively. RESULTS: Three GBTM MA types were identified for antidepressants and six for bisphosphonates and statins. For all three medications, MA types included: almost fully adherent; decreasing adherence and early discontinuation. The additional nonadherent types for bisphosphonates and statins were improved adherence, low adherence and later discontinuation. Participant characteristics impacting GBTM MA and PDC MA were consistent. However, several associations were uniquely found for GBTM MA as compared to PDC MA. CONCLUSION: GBTM permits clinicians, policy-makers and researchers to differentiate between alternative nonadherence patterns, allowing them to better identify patients at risk of poor adherence and tailor interventions accordingly.

Predicting 7-year mortality for use with evidence-based guidelines for Prostate-Specific Antigen (PSA) testing: findings from a large prospective study of 123 697 Australian men.

OBJECTIVES: To develop and validate a prediction model for short-term mortality in Australian men aged ≥45years, using age and self-reported health variables, for use when implementing the Australian Clinical Practice Guidelines for Prostate-Specific Antigen (PSA) Testing and Early Management of Test-Detected Prostate Cancer. Implementation of one of the Guideline recommendations requires an estimate of 7-year mortality. DESIGN: Prospective cohort study using questionnaire data linked to mortality data. SETTING: Men aged ≥45years randomly sampled from the general population of New South Wales, Australia, participating in the 45 and Up Study. PARTICIPANTS: 123 697 men who completed the baseline postal questionnaire (distributed from 1 January 2006 to 31 December 2008) and gave informed consent for follow-up through linkage of their data to population health databases. PRIMARY OUTCOME MEASURES: The primary outcome was all-cause mortality. RESULTS: 12 160 died during follow-up (median=5.9 years). Following age-adjustment, self-reported health was the strongest predictor of all-cause mortality (C-index: 0.827; 95% CI 0.824 to 0.831). Three prediction models for all-cause mortality were validated, with predictors: Model-1: age group and self-rated health; Model-2: variables common to the 45 and Up Study and the Australian Health Survey and subselected using stepwise regression and Model-3: all variables selected using stepwise regression. Final predictions calibrated well with observed all-cause mortality rates. The 90th percentile for the 7-year mortality risks ranged from 1.92% to 83.94% for ages 45-85 years. CONCLUSIONS: We developed prediction scores for short-term mortality using age and self-reported health measures and validated the scores against national mortality rates. Along with age, simple measures such as self-rated health, which can be easily obtained without physical examination, were strong predictors of all-cause mortality in the 45 and Up Study. Seven-year mortality risk estimates from Model-3 suggest that the impact of the mortality risk prediction tool on men's decision making would be small in the recommended age (50-69 years) for PSA testing, but it may discourage testing at older ages.

A cost of living longer: Projections of the effects of prospective mortality improvement on economic support ratios for 14 advanced economies.

The economic implications of increasing life expectancy are important concerns for governments in developed countries. The aims of this study were as follows: (i) to forecast mortality for 14 developed countries from 2010 to 2050, using the Poisson Common Factor Model; (ii) to project the effects of the forecast mortality patterns on support ratios; and (iii) to calculate labour force participation increases which could offset these effects. The forecast gains in life expectancy correlate negatively with current fertility. Pre-2050 support ratios are projected to fall most in Japan and east-central and southern Europe, and least in Sweden and Australia. A post-2050 recovery is projected for most east-central and southern European countries. The increases in labour force participation needed to counterbalance the effects of mortality improvement are greatest for Japan, Poland, and the Czech Republic, and least for the USA, Canada, Netherlands, and Sweden. The policy implications are discussed.

Using linkage between hospital and ABS mortality data to enhance reporting of deaths among Aboriginal and Torres Strait Islander peoples.

OBJECTIVE: To investigate the potential of record linkage between the Australian Bureau of Statistics (ABS) mortality data and the NSW Admitted Patient Data Collection (APDC) to improve reporting of deaths among Aboriginal and Torres Strait Islander peoples. METHODS: ABS mortality data for 2002 to 2006 were linked with APDC records for 2001 to 2006. Six algorithms were developed to enumerate deaths. Possible biases by age, sex and geographic remoteness were investigated. RESULTS: Levels of reporting ranged from baseline reporting on the ABS mortality data to the largest enhancement with the 'ever reported as Aboriginal or Torres Strait Islander' algorithm. Enhancement was more likely in females, older people and residents of major cities. CONCLUSIONS: Data linkage substantially improved reporting of Aboriginal and Torres Strait Islander deaths. An algorithm that includes both the number of APDC records and the number of facilities reporting a person as Aboriginal or Torres Strait Islander was considered most promising. IMPLICATIONS: Inclusion of other datasets in the enhancement process is warranted to further improve reporting and address possible bias produced by using APDC records only. Further work should take into account the possibility that a person may be falsely reported as Aboriginal or Torres Strait Islander or not reported in either hospital or death records.