Can administrative health utilisation data provide an accurate diabetes prevalence estimate for a geographical region?

AIM: To validate the New Zealand Ministry of Health (MoH) Virtual Diabetes Register (VDR) using longitudinal laboratory results and to develop an improved algorithm for estimating diabetes prevalence at a population level. METHODS: The assigned diabetes status of individuals based on the 2014 version of the MoH VDR is compared to the diabetes status based on the laboratory results stored in the Auckland regional laboratory result repository (TestSafe) using the New Zealand diabetes diagnostic criteria. The existing VDR algorithm is refined by reviewing the sensitivity and positive predictive value of the each of the VDR algorithm rules individually and as a combination. RESULTS: The diabetes prevalence estimate based on the original 2014 MoH VDR was 17% higher (n = 108,505) than the corresponding TestSafe prevalence estimate (n = 92,707). Compared to the diabetes prevalence based on TestSafe, the original VDR has a sensitivity of 89%, specificity of 96%, positive predictive value of 76% and negative predictive value of 98%. The modified VDR algorithm has improved the positive predictive value by 6.1% and the specificity by 1.4% with modest reductions in sensitivity of 2.2% and negative predictive value of 0.3%. At an aggregated level the overall diabetes prevalence estimated by the modified VDR is 5.7% higher than the corresponding estimate based on TestSafe. CONCLUSION: The Ministry of Health Virtual Diabetes Register algorithm has been refined to provide a more accurate diabetes prevalence estimate at a population level. The comparison highlights the potential value of a national population long term condition register constructed from both laboratory results and administrative data.

Adjusting health spending for the presence of comorbidities: an application to United States national inpatient data.

BACKGROUND: One of the major challenges in estimating health care spending spent on each cause of illness is allocating spending for a health care event to a single cause of illness in the presence of comorbidities. Comorbidities, the secondary diagnoses, are common across many causes of illness and often correlate with worse health outcomes and more expensive health care. In this study, we propose a method for measuring the average spending for each cause of illness with and without comorbidities. METHODS: Our strategy for measuring cause of illness-specific spending and adjusting for the presence of comorbidities uses a regression-based framework to estimate excess spending due to comorbidities. We consider multiple causes simultaneously, allowing causes of illness to appear as either a primary diagnosis or a comorbidity. Our adjustment method distributes excess spending away from primary diagnoses (outflows), exaggerated due to the presence of comorbidities, and allocates that spending towards causes of illness that appear as comorbidities (inflows). We apply this framework for spending adjustment to the National Inpatient Survey data in the United States for years 1996-2012 to generate comorbidity-adjusted health care spending estimates for 154 causes of illness by age and sex. RESULTS: The primary diagnoses with the greatest number of comorbidities in the NIS dataset were acute renal failure, septicemia, and endocarditis. Hypertension, diabetes, and ischemic heart disease were the most common comorbidities across all age groups. After adjusting for comorbidities, chronic kidney diseases, atrial fibrillation and flutter, and chronic obstructive pulmonary disease increased by 74.1%, 40.9%, and 21.0%, respectively, while pancreatitis, lower respiratory infections, and septicemia decreased by 21.3%, 17.2%, and 16.0%. For many diseases, comorbidity adjustments had varying effects on spending for different age groups. CONCLUSIONS: Our methodology takes a unified approach to account for excess spending caused by the presence of comorbidities. Adjusting for comorbidities provides a substantially altered, more accurate estimate of the spending attributed to specific cause of illness. Making these adjustments supports improved resource tracking, accountability, and planning for future resource allocation.

US Spending on Personal Health Care and Public Health, 1996-2013.

Importance: US health care spending has continued to increase, and now accounts for more than 17% of the US economy. Despite the size and growth of this spending, little is known about how spending on each condition varies by age and across time. Objective: To systematically and comprehensively estimate US spending on personal health care and public health, according to condition, age and sex group, and type of care. Design and Setting: Government budgets, insurance claims, facility surveys, household surveys, and official US records from 1996 through 2013 were collected and combined. In total, 183 sources of data were used to estimate spending for 155 conditions (including cancer, which was disaggregated into 29 conditions). For each record, spending was extracted, along with the age and sex of the patient, and the type of care. Spending was adjusted to reflect the health condition treated, rather than the primary diagnosis. Exposures: Encounter with US health care system. Main Outcomes and Measures: National spending estimates stratified by condition, age and sex group, and type of care. Results: From 1996 through 2013, $30.1 trillion of personal health care spending was disaggregated by 155 conditions, age and sex group, and type of care. Among these 155 conditions, diabetes had the highest health care spending in 2013, with an estimated $101.4 billion (uncertainty interval [UI], $96.7 billion-$106.5 billion) in spending, including 57.6% (UI, 53.8%-62.1%) spent on pharmaceuticals and 23.5% (UI, 21.7%-25.7%) spent on ambulatory care. Ischemic heart disease accounted for the second-highest amount of health care spending in 2013, with estimated spending of $88.1 billion (UI, $82.7 billion-$92.9 billion), and low back and neck pain accounted for the third-highest amount, with estimated health care spending of $87.6 billion (UI, $67.5 billion-$94.1 billion). The conditions with the highest spending levels varied by age, sex, type of care, and year. Personal health care spending increased for 143 of the 155 conditions from 1996 through 2013. Spending on low back and neck pain and on diabetes increased the most over the 18 years, by an estimated $57.2 billion (UI, $47.4 billion-$64.4 billion) and $64.4 billion (UI, $57.8 billion-$70.7 billion), respectively. From 1996 through 2013, spending on emergency care and retail pharmaceuticals increased at the fastest rates (6.4% [UI, 6.4%-6.4%] and 5.6% [UI, 5.6%-5.6%] annual growth rate, respectively), which were higher than annual rates for spending on inpatient care (2.8% [UI, 2.8%-2.8%] and nursing facility care (2.5% [UI, 2.5%-2.5%]). Conclusions and Relevance: Modeled estimates of US spending on personal health care and public health showed substantial increases from 1996 through 2013; with spending on diabetes, ischemic heart disease, and low back and neck pain accounting for the highest amounts of spending by disease category. The rate of change in annual spending varied considerably among different conditions and types of care. This information may have implications for efforts to control US health care spending.

30-Year Trends in Stroke Rates and Outcome in Auckland, New Zealand (1981-2012): A Multi-Ethnic Population-Based Series of Studies.

BACKGROUND: Insufficient data exist on population-based trends in morbidity and mortality to determine the success of prevention strategies and improvements in health care delivery in stroke. The aim of this study was to determine trends in incidence and outcome (1-year mortality, 28-day case-fatality) in relation to management and risk factors for stroke in the multi-ethnic population of Auckland, New Zealand (NZ) over 30-years. METHODS: Four stroke incidence population-based register studies were undertaken in adult residents (aged ≥15 years) of Auckland NZ in 1981-1982, 1991-1992, 2002-2003 and 2011-2012. All used standard World Health Organization (WHO) diagnostic criteria and multiple overlapping sources of case-ascertainment for hospitalised and non-hospitalised, fatal and non-fatal, new stroke events. Ethnicity was consistently self-identified into four major groups. Crude and age-adjusted (WHO world population standard) annual incidence and mortality with corresponding 95% confidence intervals (CI) were calculated per 100,000 people, assuming a Poisson distribution. RESULTS: 5400 new stroke patients were registered in four 12 month recruitment phases over the 30-year study period; 79% were NZ/European, 6% Maori, 8% Pacific people, and 7% were of Asian or other origin. Overall stroke incidence and 1-year mortality decreased by 23% (95% CI 5%-31%) and 62% (95% CI 36%-86%), respectively, from 1981 to 2012. Whilst stroke incidence and mortality declined across all groups in NZ from 1991, Maori and Pacific groups had the slowest rate of decline and continue to experience stroke at a significantly younger age (mean ages 60 and 62 years, respectively) compared with NZ/Europeans (mean age 75 years). There was also a decline in 28-day stroke case fatality (overall by 14%, 95% CI 11%-17%) across all ethnic groups from 1981 to 2012. However, there were significant increases in the frequencies of pre-morbid hypertension, myocardial infarction, and diabetes mellitus, but a reduction in frequency of current smoking among stroke patients. CONCLUSIONS: In this unique temporal series of studies spanning 30 years, stroke incidence, early case-fatality and 1-year mortality have declined, but ethnic disparities in risk and outcome for stroke persisted suggesting that primary stroke prevention remains crucial to reducing the burden of this disease.

Burden of Traumatic Brain Injury in New Zealand: Incidence, Prevalence and Disability-Adjusted Life Years.

OBJECTIVE: The study aimed to estimate the incidence, prevalence and disability-adjusted life years (DALY) for traumatic brain injury (TBI) in New Zealand (NZ) in 2010. METHODS: A multi-state life table model was constructed using inputs from the Brain Injury Outcomes New Zealand in the Community study for the first-ever incidence of TBI in a lifetime and its severity distribution, from the NZ Ministry of Health's Mortality Collection for the data on TBI mortality and from Statistics of NZ for the population data. The modeled estimate of prevalence was combined with the disability weights for TBI (by stage and severity level) from the Global Burden of Disease 2010 study to obtain estimates of health loss (DALYs) for TBI. RESULTS: Approximately, 11,300 first-ever incident TBIs occurred in NZ during 2010, with 527,000 New Zealanders estimated to have ever experienced a TBI (prevalent cases). The estimated 20,300 DALYs attributable to TBI accounted for 27% of total injury-related health loss and 2.4% of DALYs from all causes. Of the total DALYs attributable to TBI, 71% resulted from fatal injuries. However, non-fatal outcomes accounted for a substantial share of the burden (29%) with mild TBI making the greater contribution of non-fatal outcomes (56%). CONCLUSIONS: The burden of TBI in NZ is substantial, and mild TBI contributes to a major part of non-fatal outcomes.

Causes of international increases in older age life expectancy.

In high-income countries, life expectancy at age 60 years has increased in recent decades. Falling tobacco use (for men only) and cardiovascular disease mortality (for both men and women) are the main factors contributing to this rise. In high-income countries, avoidable male mortality has fallen since 1980 because of decreases in avoidable cardiovascular deaths. For men in Latin America, the Caribbean, Europe, and central Asia, and for women in all regions, avoidable mortality has changed little or increased since 1980. As yet, no evidence exists that the rate of improvement in older age mortality (60 years and older) is slowing down or that older age deaths are being compressed into a narrow age band as they approach a hypothesised upper limit to longevity.

Cost of traumatic brain injury in New Zealand: evidence from a population-based study.

OBJECTIVE: We aimed to estimate from a societal perspective the 1-year and lifetime direct and indirect costs of traumatic brain injury (TBI) for New Zealand (NZ) in 2010 projected to 2020. METHODS: An incidence-based cost of illness model was developed using data from the Brain Injury Outcomes New Zealand in the Community Study. Details of TBI-related resource use during the first 12 months after injury were obtained for 725 cases using resource utilization information from participant surveys and medical records. Total costs are presented in US dollars year 2010 value. RESULTS: In 2010, 11,301 first-ever TBI cases were estimated to have occurred in NZ; total first-year cost of all new TBI cases was estimated to be US $47.9 million with total prevalence costs of US $101.4 million. The average cost per new TBI case during the first 12 months and over a lifetime was US $5,922 (95% confidence interval [CI] $4,777-$7,858), varying from US $4,636 (95% CI $3,756-$5,561) for mild cases to US $36,648 (95% CI $16,348-$65,350) for moderate/severe cases. Because of the unexpectedly large number of mild TBI cases (95% of all TBI cases), the total cost of treating these cases is nearly 3 times that of moderate/severe. The total lifetime cost of all TBI survivors in 2010 was US $146.5 million and is expected to increase to US $177.1 million in 2020. CONCLUSION: The results suggest that there is an urgent need to develop effective interventions to prevent both mild and moderate/severe TBI.

Migration and Pacific mortality: estimating migration effects on Pacific mortality rates using Bayesian models.

Pacific people living in New Zealand have higher mortality rates than New Zealand residents of European/Other ethnicity. The aim of this paper is to see whether Pacific mortality rates vary by natality and duration of residence. We used linked census-mortality information for 25- to 74-year-olds in the 2001 census followed for up to three years. Hierarchical Bayesian modeling provided a means of handling sparse data. Posterior mortality rates were directly age-standardized. We found little evidence of mortality differences between the overseas-born and the New Zealand-born for all-cause, cancer, and cardiovascular disease (CVD) mortality. However, we found evidence for lower all-cause (and possibly cancer and CVD) mortality rates for Pacific migrants resident in New Zealand for less than 25 years relative to those resident for more than 25 years. This result may arise from a combination of processes operating over time, including health selection effects from variations in New Zealand's immigration policy, the location of Pacific migrants within the social, political, and cultural environment of the host community, and health impacts of the host culture. We could not determine the relative importance of these processes, but identifying the (modifiable) drivers of the inferred long-term decline in health of the overseas-born Pacific population relative to more-recent Pacific migrants is important to Pacific communities and from a national health and policy perspective.

The burden of cancer in New Zealand: a comparison of incidence and DALY metrics and its relevance for ethnic disparities.

AIM: Cancer burden measured in disability adjusted life years (DALYs) captures survival and disability impacts of incident cancers. In this paper, we estimate the prospective burden of disease arising from 27 cancer sites diagnosed in 2006, by sex and ethnicity; and determine how its distribution differs from that for incidence rates alone. METHODS: Using a prospective approach, Markov and cancer disease models were used to estimate DALYs with inputs of population counts, incidence and excess mortality rates, disability weights, and background mortality. DALYs were discounted at 3.5% per year. RESULTS: The age standardised Maori:non-Maori incidence rate ratios were 1.00 for males and 1.19 for females, whereas for DALYs they were greater at 1.42 for males and 1.68 for females. The total burden of cancer for 2006 incident cases (i.e. not age standardised) was estimated to be approximately 127,000 DALYs. Breast (27%), lung (14%) and colorectal (13%) cancers for females and lung (16%), colorectal (14%), and prostate (16%) cancers for males were the top contributors. By ethnicity, Maori experienced a substantially higher burden from lung cancer (around 25% for both sexes). CONCLUSIONS: Due to Maori both having higher rates of cancers with a worse survival (e.g. lung cancer), and tending to have worse survival for each cancer site, ethnic disparities in the age-standardised DALY burden were greater than those for incidence (rate ratios of 1.52 and 1.07 respectively, sexes pooled).

Self-reported experience of racial discrimination and health care use in New Zealand: results from the 2006/07 New Zealand Health Survey.

OBJECTIVES: We investigated whether reported experience of racial discrimination in health care and in other domains was associated with cancer screening and negative health care experiences. METHODS: We used 2006/07 New Zealand Health Survey data (n = 12 488 adults). We used logistic regression to examine the relationship of reported experience of racial discrimination in health care (unfair treatment by a health professional) and in other domains (personal attack, unfair treatment in work and when gaining housing) to breast and cervical cancer screening and negative patient experiences adjusted for other variables. RESULTS: Racial discrimination by a health professional was associated with lower odds of breast (odds ratio [OR] = 0.37; 95% confidence interval [CI] = 0.14, 0.996) and cervical cancer (OR = 0.51; 95% CI = 0.30, 0.87) screening among Maori women. Racial discrimination by a health professional (OR = 1.57; 95% CI = 1.15, 2.14) and racial discrimination more widely (OR = 1.55; 95% CI = 1.35, 1.79) were associated with negative patient experiences for all participants. CONCLUSIONS: Experience of racial discrimination in both health care and other settings may influence health care use and experiences of care and is a potential pathway to poor health.

The pervasive effects of racism: experiences of racial discrimination in New Zealand over time and associations with multiple health domains.

Self-reported experience of racial discrimination has been linked to a range of health outcomes in various countries and for different ethnic groups. This study builds on previous work in New Zealand to further investigate the prevalence of self-reported experience of racial discrimination by ethnicity, changes over time and associations with multiple health measures. The study uses data from the 2002/03 (n=12,500) and 2006/07 (n=12,488) New Zealand Health Surveys, nationally representative population-based surveys of adults (15+ years). Reported experience of racial discrimination was measured in both surveys and covered 5 items: experience of an ethnically motivated physical or verbal attack; and unfair treatment because of ethnicity by a health professional, in work, or when gaining housing. Ethnicity was classified as Maori, Pacific, Asian or European. Health indicators included measures of: mental health (SF36 mental health scale, psychological distress, doctor diagnosed mental health condition); physical health (self-rated health, SF36 physical functioning scale, cardiovascular disease); and health risk (smoking, hazardous drinking, excess body fat). Logistic regression was used to examine changes in prevalence of reported experience of racial discrimination over time and associations with health. Reported experience of racial discrimination increased between 2002/03 (28.1% ever) and 2006/07 (35.0% ever) among Asian peoples but remained largely unchanged for other ethnic groupings (Maori 29.5%, Pacific 23.0%, European 13.5%). Experience of racial discrimination was associated with all negative health measures except excess body fat. Where there were significant associations, a dose-response relationship was also evident. We conclude that racial discrimination experienced across a range of settings has the potential to impact on a wide range of health outcomes and risk factors. While ongoing research is needed to understand the multifarious nature of racism and the pathways by which it leads to poor health, it is feasible to monitor experiences of racial discrimination in national surveys.

Mortality among the working age population receiving incapacity benefits in New Zealand, 1981-2004.

Like many OECD countries New Zealand has experienced a large increase in the number of working-age people receiving incapacity benefits in the last 3 decades, despite apparent improvements in population health. This paper examines trends in mortality rates of people receiving sickness benefit or invalid's benefit (SBIB) between 1981 and 2004 using repeated cohort studies (linking the 1981, 1986, 1991, 1996, and 2001 censuses to mortality data). Mortality rates, standardised for age and ethnicity, were calculated for each census cohort for 25-64 year olds by benefit receipt status. Standardised rate differences and rate ratios and 95% confidence intervals were calculated to measure disparities on both absolute and relative scales. Between 1981 and 2004 overall SBIB receipt increased from 2% to 5% of the working age population. Mortality rates were at least three times higher in the SBIB than the non-SBIB group at all points in time for men and women. Mortality rates declined in all groups, for example in men receiving SBIB, mortality decreased from 2354/100,000 in the 1981-84 cohort to 1371/100,000 in the 2001-04 cohort. Absolute inequalities between SBIB and non-SBIB declined in both men and women (for example in women standardised rate differences decreased from 954/100,000 to 688/100,000) but relative inequalities remained largely stable (for example in men the risk ratio increased from 4.27 to 4.54). Mortality rates declined more in sickness benefit than invalid's benefit recipients. The substantial expansion of SBIB receipt in New Zealand has not been accompanied by any reduction in the excess mortality risk experienced by SBIB recipients. These findings are likely to reflect the changing nature of the economy, labour force and disability experience in New Zealand.

The health of children in sole-parent families in New Zealand: results of a population-based cross-sectional survey.

OBJECTIVE: To investigate whether children in sole-parent families in New Zealand bear excess risks of poor mental and physical health relative to children in two parent families. DATA SOURCES AND STATISTICAL METHODS: The data source was the 2006/07 New Zealand Health Survey, a nationally representative household survey that sampled 502 children (5-14 years) of sole mothers and 1,281 children of partnered mothers. RESULTS: Children of sole mothers were 1.26 (0.94 - 2.69) times as likely as children of partnered mothers to return a low PhS score. Adjusting for maternal health and family socio-economic disadvantage eliminated this weak association (which in any case was of borderline statistical significance). Children of sole mothers were more than twice as likely as children of partnered mothers to return a low PsS score, adjusting for demographic variables only. CONCLUSIONS: There is only a weak negative association (if any) between sole-parenting and child physical health, but a stronger association with child mental health - consistent with most of the New Zealand and international literature. The association with child mental health is largely (but possibly not completely) 'explained' by the poorer mental health of sole-parents and the poorer socio-economic circumstances of single-parent families (on average). IMPLICATIONS: These findings support policies aiming to improve access of sole-parents and their children to community mental health services, and (more especially) policies aiming to ameliorate the disadvantaged economic circumstances of single parent families.

Application of a system dynamics model to inform investment in smoking cessation services in New Zealand.

OBJECTIVES: We estimated the long-term effects of smoking cessation interventions to inform government decision-making regarding investment in tobacco control. METHODS: We extracted data from the 2006 New Zealand Tobacco Use Survey and other sources and developed a system dynamics model with the iThink computer simulation package. The model derived estimates of population cessation rates from smoking behaviors and applied these over a 50-year period, from 2001 to 2051, under business-as-usual and enhanced cessation intervention scenarios. RESULTS: The model predicted larger effects by 2051 with the enhanced cessation than with the business-as-usual scenario, including: an 11% greater decline in adult current smoking prevalence (9 versus 10 per 100 people), 16% greater decline in per capita tobacco consumption (370 versus 440 cigarette equivalents per year), and 11% greater reduction in tobacco-attributable mortality (3000 versus 3300 deaths per year). CONCLUSIONS: The model generated reliable estimates of the effects on health and on tobacco use of interventions designed to enhance smoking cessation. These results informed a decision announced in May 2007 to increase funding for smoking cessation by NZ $42 million over 4 years.

The burden of coronary heart disease in Maori: population-based estimates for 2000-02.

OBJECTIVE: To estimate coronary heart disease (CHD) incidence, prevalence, survival, case fatality and mortality for Maori, in order to support service planning and resource allocation. METHODS: Incidence was defined as first occurrence of a major coronary event, i.e. the sum of first CHD hospital admissions and out-of-hospital CHD deaths in people without a hospital admission for CHD in the preceding five years. Data for the years 2000-02 were sourced from the New Zealand Health Information Service and record linkage was carried out using a unique national identifier, the national health index. RESULTS: Compared to the non-Maori population, Maori had both elevated CHD incidence and higher case fatality. Median age at onset of CHD was younger for Maori, reflecting both higher age specific risks and younger population age structure. The lifetable risk of CHD for Maori was estimated at 37% (males) and 34% (females), only moderately higher than the corresponding estimates for the non-Maori population, despite higher Maori CHD incidence. This reflects the offsetting effect of the higher 'other cause' mortality experienced by Maori. Median duration of survival with CHD was similar to that of the non-Maori population for Maori males but longer for Maori females, which is most likely related to the earlier age of onset. CONCLUSIONS: This study has generated consistent estimates of CHD incidence, prevalence, survival, case fatality and mortality for Maori in 2000-02. The inequality identified in CHD incidence calls for a renewed effort in primary prevention. The inequality in CHD case fatality calls for improvement in access for Maori to secondary care services.

Do ethnic and socio-economic inequalities in mortality vary by region in New Zealand? An application of hierarchical Bayesian modelling.

We hypothesised that ethnic and socio-economic inequality in mortality might vary by region in New Zealand. Linked 2001-2004 census-mortality data were stratified by region (District Health Boards or DHBs), sex, age and ethnic groups, and income quintiles. To accommodate data sparseness, and to achieve accurate estimates of DHB-specific mortality rates and rate ratios by ethnicity and income, we used hierarchical Bayesian methods. To aid presentation of results, we used posterior mortality rates from the models to calculate directly standardised rates and rate ratios, with credible intervals. Maori-European/Other mortality rate ratios were often similar across DHBs, but Waitemata and Canterbury DHBs (both predominantly urban areas with low Maori population) had significantly lower rate ratios. In contrast, Bay of Plenty and Waikato DHBs (heterogeneous by both ethnicity and socio-economic position) had significantly higher rate ratios. There was little variation in mortality inequalities by income across DHBs. Examining the underlying rates for ethnic and income groups separately, there were significant variations across DHBs, but these were often correlated such that the ethnic or income rate ratio was similar across DHBs. The application of hierarchical Bayesian allowed more definitive conclusions than routine empirical methods when comparing small populations such as social groups across regions. The range of hierarchical Bayesian estimates of Maori mortality and Maori:European rate ratios across regions was considerably narrower than empirical standardisation estimates.