Estimating the completeness of physician billing claims for diabetes case ascertainment: a multiprovince investigation. / Estimation de l'exhaustivité des demandes de remboursement des médecins dans une optique de détermination des cas de diabète : étude menée dans plusieurs provinces.

INTRODUCTION: Previous research has suggested that how physicians are paid may affect the completeness of billing claims for estimating chronic disease. The purpose of this study is to estimate the completeness of physician billings for diabetes case ascertainment. METHODS: We used administrative data from eight Canadian provinces covering the period 1 April 2014 to 31 March 2016. The patient cohort was stratified into two mutually exclusive groups based on their physician remuneration type: fee-for-service (FFS), for those paid only on that basis; and non-fee-for-service (NFFS). Using diabetes prescription drug data as our reference data source, we evaluated whether completeness of disease case ascertainment varied with payment type. Diabetes incidence rates were then adjusted for completeness of ascertainment. RESULTS: The cohort comprised 86 110 patients. Overall, equal proportions received their diabetes medications from FFS and NFFS physicians. Overall, physician payment method had little impact upon the percentage of missed diabetes cases (FFS, 14.8%; NFFS, 12.2%). However, the difference in missed cases between FFS and NFFS varied widely by province, ranging from -1.0% in Nova Scotia to 29.9% in Newfoundland and Labrador. The difference between the observed and adjusted disease incidence rates also varied by province, ranging from 22% in Prince Edward Island to 4% in Nova Scotia. CONCLUSION: The difference in the loss of cases by physician remuneration method varied across jurisdictions. This loss may contribute to an underestimation of disease incidence. The method we used could be applied to other chronic diseases for which drug therapy could serve as reference data source.

Associations between SARS-CoV-2 infection and incidence of new chronic condition diagnoses: a systematic review.

Because of the large number of infected individuals, an estimate of the future burdens of the long-term consequences of SARS-CoV-2 infection is needed. This systematic review examined associations between SARS-CoV-2 infection and incidence of categories of and selected chronic conditions, by age and severity of infection (inpatient vs. outpatient/mixed care). MEDLINE and EMBASE were searched (1 January 2020 to 4 October 2022) and reference lists scanned. We included observational studies from high-income OECD countries with a control group adjusting for sex and comorbidities. Identified records underwent a two-stage screening process. Two reviewers screened 50% of titles/abstracts, after which DistillerAI acted as second reviewer. Two reviewers then screened the full texts of stage one selections. One reviewer extracted data and assessed risk of bias; results were verified by another. Random-effects meta-analysis estimated pooled hazard ratios (HR). GRADE assessed certainty of the evidence. Twenty-five studies were included. Among the outpatient/mixed SARS-CoV-2 care group, there is high certainty of a small-to-moderate increase (i.e. HR 1.26-1.99) among adults ≥65 years of any cardiovascular condition, and of little-to-no difference (i.e. HR 0.75-1.25) in anxiety disorders for individuals <18, 18-64, and ≥65 years old. Among 18-64 and ≥65 year-olds receiving outpatient/mixed care there are probably (moderate certainty) large increases (i.e. HR ≥2.0) in encephalopathy, interstitial lung disease, and respiratory failure. After SARS-CoV-2 infection, there is probably an increased risk of diagnoses for some chronic conditions; whether the magnitude of risk will remain stable into the future is uncertain.

Lifetime risk, life expectancy, and years of life lost to type 2 diabetes in 23 high-income jurisdictions: a multinational, population-based study.

BACKGROUND: Diabetes is a major public health issue. Because lifetime risk, life expectancy, and years of life lost are meaningful metrics for clinical decision making, we aimed to estimate these measures for type 2 diabetes in the high-income setting. METHODS: For this multinational, population-based study, we sourced data from 24 databases for 23 jurisdictions (either whole countries or regions of a country): Australia; Austria; Canada; Denmark; Finland; France; Germany; Hong Kong; Hungary; Israel; Italy; Japan; Latvia; Lithuania; the Netherlands; Norway; Scotland; Singapore; South Korea; Spain; Taiwan; the UK; and the USA. Our main outcomes were lifetime risk of type 2 diabetes, life expectancy in people with and without type 2 diabetes, and years of life lost to type 2 diabetes. We modelled the incidence and mortality of type 2 diabetes in people with and without type 2 diabetes in sex-stratified, age-adjusted, and calendar year-adjusted Poisson models for each jurisdiction. Using incidence and mortality, we constructed life tables for people of both sexes aged 20-100 years for each jurisdiction and at two timepoints 5 years apart in the period 2005-19 where possible. Life expectancy from a given age was computed as the area under the survival curves and lifetime lost was calculated as the difference between the expected lifetime of people with versus without type 2 diabetes at a given age. Lifetime risk was calculated as the proportion of each cohort who developed type 2 diabetes between the ages of 20 years and 100 years. We estimated 95% CIs using parametric bootstrapping. FINDINGS: Across all study cohorts from the 23 jurisdictions (total person-years 1 577 234 194), there were 5 119 585 incident cases of type 2 diabetes, 4 007 064 deaths in those with type 2 diabetes, and 11 854 043 deaths in those without type 2 diabetes. The lifetime risk of type 2 diabetes ranged from 16·3% (95% CI 15·6-17·0) for Scottish women to 59·6% (58·5-60·8) for Singaporean men. Lifetime risk declined with time in 11 of the 15 jurisdictions for which two timepoints were studied. Among people with type 2 diabetes, the highest life expectancies were found for both sexes in Japan in 2017-18, where life expectancy at age 20 years was 59·2 years (95% CI 59·2-59·3) for men and 64·1 years (64·0-64·2) for women. The lowest life expectancy at age 20 years with type 2 diabetes was observed in 2013-14 in Lithuania (43·7 years [42·7-44·6]) for men and in 2010-11 in Latvia (54·2 years [53·4-54·9]) for women. Life expectancy in people with type 2 diabetes increased with time for both sexes in all jurisdictions, except for Spain and Scotland. The life expectancy gap between those with and without type 2 diabetes declined substantially in Latvia from 2010-11 to 2015-16 and in the USA from 2009-10 to 2014-15. Years of life lost to type 2 diabetes ranged from 2·5 years (Latvia; 2015-16) to 12·9 years (Israel Clalit Health Services; 2015-16) for 20-year-old men and from 3·1 years (Finland; 2011-12) to 11·2 years (Israel Clalit Health Services; 2010-11 and 2015-16) for 20-year-old women. With time, the expected number of years of life lost to type 2 diabetes decreased in some jurisdictions and increased in others. The greatest decrease in years of life lost to type 2 diabetes occurred in the USA between 2009-10 and 2014-15 for 20-year-old men (a decrease of 2·7 years). INTERPRETATION: Despite declining lifetime risk and improvements in life expectancy for those with type 2 diabetes in many high-income jurisdictions, the burden of type 2 diabetes remains substantial. Public health strategies might benefit from tailored approaches to continue to improve health outcomes for people with diabetes. FUNDING: US Centers for Disease Control and Prevention and Diabetes Australia.

Trends in all-cause mortality among people with diagnosed diabetes in high-income settings: a multicountry analysis of aggregate data.

BACKGROUND: Population-level trends in mortality among people with diabetes are inadequately described. We aimed to examine the magnitude and trends in excess all-cause mortality in people with diabetes. METHODS: In this retrospective, multicountry analysis, we collected aggregate data from 19 data sources in 16 high-income countries or jurisdictions (in six data sources in Asia, eight in Europe, one from Australia, and four from North America) for the period from Jan 1, 1995, to Dec 31, 2016, (or a subset of this period) on all-cause mortality in people with diagnosed total or type 2 diabetes. We collected data from administrative sources, health insurance records, registries, and a health survey. We estimated excess mortality using the standardised mortality ratio (SMR). FINDINGS: In our dataset, there were approximately 21 million deaths during 0·5 billion person-years of follow-up among people with diagnosed diabetes. 17 of 19 data sources showed decreases in the age-standardised and sex-standardised mortality in people with diabetes, among which the annual percentage change in mortality ranged from -0·5% (95% CI -0·7 to -0·3) in Hungary to -4·2% (-4·3 to -4·1) in Hong Kong. The largest decreases in mortality were observed in east and southeast Asia, with a change of -4·2% (95% CI -4·3 to -4·1) in Hong Kong, -4·0% (-4·8 to -3·2) in South Korea, -3·5% (-4·0 to -3·0) in Taiwan, and -3·6% (-4·2 to -2·9) in Singapore. The annual estimated change in SMR between people with and without diabetes ranged from -3·0% (95% CI -3·0 to -2·9; US Medicare) to 1·6% (1·4 to 1·7; Lombardy, Italy). Among the 17 data sources with decreasing mortality among people with diabetes, we found a significant SMR increase in five data sources, no significant SMR change in four data sources, and a significant SMR decrease in eight data sources. INTERPRETATION: All-cause mortality in diabetes has decreased in most of the high-income countries we assessed. In eight of 19 data sources analysed, mortality decreased more rapidly in people with diabetes than in those without diabetes. Further longevity gains will require continued improvement in prevention and management of diabetes. FUNDING: US Centers for Disease Control and Prevention, Diabetes Australia Research Program, and Victoria State Government Operational Infrastructure Support Program.