Measuring multimorbidity series-an overlooked complexity comparison of self-report vs. administrative data in community-living adults: paper 2. Prevalence estimates depend on the data source

Impact of age, comorbidity, and polypharmacy on receipt of systemic therapy in advanced cancers: A retrospective population-based study

INTRODUCTION

Cancer incidence, comorbidity, and polypharmacy increase with age, but the interplay between these factors on receipt of systemic therapy (ST) in advanced cancer has rarely been studied.

MATERIALS AND METHODS

A retrospective cohort study was conducted including patients aged ≥18 years diagnosed from 2004 to 2015 with multiple myeloma (MM) (all stages), lung cancer (stage IV), and stage III-IV non-Hodgkin's lymphoma (NHL), breast, colorectal (CRC), prostate, or ovarian cancer in Manitoba, Canada. Clinical and administrative health data were used to determine demographic and cancer characteristics, treatment history, comorbidity (Charlson Comorbidity Index [CCI] and Resource Utilization Band [RUB]), and polypharmacy (≥6 medications). Multivariable logistic regression was used to evaluate variable associations with receipt of ST and interaction with age.

RESULTS

In total, 17,228 patients were diagnosed with advanced cancer. Ages were distributed as follows: 7% <50 years, 16% 50-59 years, 26% 60-69, 26% 70-79, 24% ≥80 years. ST was administered to 50% of patients. Increased age, polypharmacy, and comorbidity each independently decreased the likelihood of receiving ST. Significant interaction effects were found between age at diagnosis with stage of cancer and cancer type. Differences in probability of ST by cancer stage converged as age increased. In multivariable analysis, adjusting for covariates, patients with MM had the highest odds and lung cancer the lowest odds to receive ST. The impact of comorbidity and polypharmacy did not differ meaningfully with increasing age.

DISCUSSION

Increased age, polypharmacy, and comorbidity were each independently associated with decreased receipt of ST in people with advanced cancers. The impact of comorbidity and polypharmacy did not differ meaningfully with increasing age, while age meaningfully interacted with stage and cancer type.

Agreement Between Self-Reported Information and Health Register Data on Chronic Diseases in the Oldest Old

Purpose

To study the agreement on disease prevalence between survey data and national health register data among people aged over 90.

Patients and Methods

The survey data were from the Vitality 90+ Study conducted among 1637 community dwellers and persons in long-term care aged 90 and over in Tampere, Finland. The survey was linked with two national health registers, including hospital discharge data and prescription information. The prevalence of 10 age-related chronic diseases was calculated for each data source and the agreement between the survey and the registers was estimated using Cohen's kappa statistics and positive and negative percent agreement.

Results

The prevalence of most diseases was higher in the survey than in the registers. The level of agreement was highest when the survey was compared with information combined from both registers. Agreement was almost perfect for Parkinson's disease (ĸ=0.81) and substantial for diabetes (ĸ=0.75) and dementia (ĸ=0.66). For heart disease, hypertension, stroke, cancer, osteoarthritis, depression, and hip fracture, the agreement ranged from fair to moderate.

Conclusion

Self-reported information on chronic diseases shows acceptable agreement with health register data to warrant the use of survey methods in population-based health studies among the oldest old. It is important to acknowledge the gaps in health registers when validating self-reported information against register data.

Defining and measuring multimorbidity in primary care in Singapore: Results of an online Delphi study

Multimorbidity, common in the primary care setting, has diverse implications for both the patient and the healthcare system. However, there is no consensus on the definition of multimorbidity globally. Thus, we aimed to conduct a Delphi study to gain consensus on the definition of multimorbidity, the list and number of chronic conditions used for defining multimorbidity in the Singapore primary care setting. Our Delphi study comprised three rounds of online voting from purposively sampled family physicians in public and private settings. Delphi round 1 included open-ended questions for idea generation. The subsequent two rounds used questions with pre-selected options. Consensus was achieved based on a pre-defined criteria following an iterative process. The response rates for the three rounds were 61.7% (37/60), 86.5% (32/37) and 93.8% (30/32), respectively. Among 40 panellists who responded, 46.0% were 31-40 years old, 64.9% were male and 73.0% were from the public primary healthcare setting. Based on the findings of rounds 1, 2 and 3, consensus on the definition of a chronic condition, multimorbidity and finalised list of chronic conditions were achieved. For a condition to be chronic, it should last for six months or more, be recurrent or persistent, impact patients across multiple domains and require long-term management. The consensus-derived definition of multimorbidity is the presence of three or more chronic conditions from a finalised list of 23 chronic conditions. We anticipate that our findings will inform multimorbidity conceptualisation at the national level, standardise multimorbidity measurement in primary care and facilitate resource allocation for patients with multimorbidity.

Examining the prevalence and correlates of multimorbidity among community-dwelling older adults: cross-sectional evidence from the Canadian Longitudinal Study on Aging (CLSA) first-follow-up data

INTRODUCTION

multimorbidity has become an increasingly important issue for many populations around the world, including Canada. The objectives of this study were to estimate the prevalence of multimorbidity at first follow-up and to identify factors associated with multimorbidity using data from the Canadian Longitudinal Study on Aging (CLSA).

METHODS

this study included 27,701 community-dwelling participants in the first follow-up of the CLSA. Multimorbidity was operationalised using two definitions (Public Health and Primary Care), as well as the cut-points of two or more chronic conditions (MM2+) and three or more chronic conditions (MM3+). The prevalence of multimorbidity was calculated at first follow-up and multivariable regression models were used to identify correlates of multimorbidity occurrence.

RESULTS

the prevalence of multimorbidity at first follow-up was 32.3% among males and 39.3% among females when using the MM2+ Public Health definition, whereas the prevalence was 67.2% among males and 75.8% among females when using the MM2+ Primary Care definition. Older age, lower alcohol consumption, lower physical activity levels, dissatisfaction with sleep quality, dissatisfaction with life and experiencing social limitations due to health conditions were significantly associated with increased odds of multimorbidity for both males and females, regardless of the definition of multimorbidity used.

CONCLUSION

various sociodemographic, behavioural and psychosocial factors are associated with multimorbidity. Future research should continue to examine how the prevalence of multimorbidity changes with time and how these changes may be related to specific risk factors. This future research should be supplemented with studies examining the longitudinal impacts of multimorbidity over time.

The impact of multimorbidity level and functional limitations on the accuracy of using self-reported survey data compared to administrative data to measure general practitioner and specialist visits in community-living adults

Background

Researchers often use survey data to study the effect of health and social variables on physician use, but how self-reported physician use compares to administrative data, the gold standard, in particular within the context of multimorbidity and functional limitations remains unclear. We examine whether multimorbidity and functional limitations are related to agreement between self-reported and administrative data for physician use.

Methods

Cross-sectional data from 52,854 Ontario participants of the Canadian Community Health Survey linked to administrative data were used to assess agreement on physician use. The number of general practitioner (GP) and specialist visits in the previous year was assessed using both data sources; multimorbidity and functional limitation were from self-report.

Results

Fewer participants self-reported GP visits (84.8%) compared to administrative data (89.1%), but more self-reported specialist visits (69.2% vs. 64.9%). Sensitivity was higher for GP visits (≥90% for all multimorbidity levels) compared to specialist visits (approximately 75% for 0 to 90% for 4+ chronic conditions). Specificity started higher for GP than specialist visits but decreased more swiftly with multimorbidity level; in both cases, specificity levels fell below 50%. Functional limitations, age and sex did not impact the patterns of sensitivity and specificity seen across level of multimorbidity.

Conclusions

Countries around the world collect health surveys to inform health policy and planning, but the extent to which these are linked with administrative, or similar, data are limited. Our study illustrates the potential for misclassification of physician use in self-report data and the need for sensitivity analyses or other corrections.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07160-2.

Examine the association between key determinants identified by the chronic disease indicator framework and multimorbidity by rural and urban settings

Background

Multimorbidity, often defined as having two or more chronic conditions is a global phenomenon. This study examined the association between key determinants identified by the chronic disease indicator framework and multimorbidity by rural and urban settings. The prevalence of individual diseases was also investigated by age and sex.

Methods

The Canada Community Health Survey and linked health administrative databases were used to examine the association between multimorbidity, sociodemographic, behavioral, and other risk factors in the province of Ontario. A multivariable logistic regression model was used to conduct the main analysis.

Results

Analyses were stratified by age (20-64 and 65-95) and area of residence (rural and urban). A total sample of n = 174,938 residents between the ages of 20-95 were examined in the Ontario province, of which 18.2% (n = 31,896) were multimorbid with 2 chronic conditions, and 23.4% (n = 40,883) with 3+ chronic conditions. Females had a higher prevalence of 2 conditions (17.9% versus 14.6%) and 3+ conditions (19.7% vs. 15.6%) relative to males. Out of all examined variables, poor self-perception of health, age, Body Mass Index, and income were most significantly associated with multimorbidity. Smoking was a significant risk factor in urban settings but not rural, while drinking was significant in rural and not urban settings. Income inequality was associated with multimorbidity with greater magnitude in rural areas. Prevalence of multimorbidity and having three or more chronic conditions were highest among low-income populations.

Conclusion

Interventions targeting population weight, age/sex specific disease burdens, and additional focus on stable income are encouraged.

Sex differences in multimorbidity and polypharmacy trends: A repeated cross-sectional study of older adults in Ontario, Canada

Background

Multimorbidity is increasing among older adults, but the impact of these recent trends on the extent and complexity of polypharmacy and possible variation by sex remains unknown. We examined sex differences in multimorbidity, polypharmacy (5+ medications) and hyper-polypharmacy (10+ medications) in 2003 vs 2016, and the interactive associations between age, multimorbidity level, and time on polypharmacy measures.

Methods and findings

We employed a repeated cross-sectional study design with linked health administrative databases for all persons aged ≥66 years eligible for health insurance in Ontario, Canada at the two index dates. Descriptive analyses and multivariable logistic regression models were conducted; models included interaction terms between age, multimorbidity level, and time period to estimate polypharmacy and hyper-polypharmacy probabilities, risk differences and risk ratios for 2016 vs 2003. Multimorbidity, polypharmacy and hyper-polypharmacy increased significantly over the 13 years. At both index dates prevalence estimates for all three were higher in women, but a greater absolute increase in polypharmacy over time was observed in men (6.6% [from 55.7% to 62.3%] vs 0.9% [64.2%-65.1%] for women) though absolute increases in multimorbidity were similar for men and women (6.9% [72.5%-79.4%] vs 6.2% [75.9%-82.1%], respectively). Model findings showed that polypharmacy decreased over time among women aged < 90 years (especially for younger ages and those with fewer conditions), whereas it increased among men at all ages and multimorbidity levels (with larger absolute increases typically at older ages and among those with 4 or fewer conditions).

Conclusions

There are sex and age differences in the impact of increasing chronic disease burden on changes in measures of multiple medication use among older adults. Though the drivers and health consequences of these trends warrant further investigation, the findings support the heterogeneity and complexity in the evolving association between multimorbidity and polypharmacy measures in older populations.

The hidden complexity of measuring number of chronic conditions using administrative and self-report data: A short report

OBJECTIVE

To examine agreement between administrative and self-reported data on the number of and constituent chronic conditions (CCs) used to measure multimorbidity.

STUDY DESIGN AND SETTING

Cross-sectional self-reported survey data from four Canadian Community Health Survey waves were linked to administrative data for residents of Ontario, Canada. Agreement for each of 12 CCs was assessed using kappa (κ) statistics. For the overall number of CCs, perfect agreement was defined as agreement on both the number and constituent CCs. Jackknife methods were used to assess the impact of individual CCs on perfect agreement.

RESULTS

The level of chance-adjusted agreement between self-report and administrative data for individual CCs varied widely, from κ = 5.5% (inflammatory bowel disease) to κ = 77.5% (diabetes), and there was no clear pattern on whether using administrative data or self-reported data led to higher prevalence estimates. Only 26.9% of participants had perfect agreement on the number and constituent CCs; 10.6% agreed on the number but not constituent CCs. The impact of each CC on perfect agreement depended on both the level of agreement and the prevalence of the individual CC.

CONCLUSION

Our results show that measuring agreement on multimorbidity is more complex than for individual CCs and that even small levels of individual condition disagreement can have a large impact on the agreement on the number of CCs.