Conventional and advanced time series estimation: application to the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database, 1993-2006

The projected increase of vertebral osteomyelitis in Germany implies a demanding challenge for future healthcare management of aging populations

PURPOSE

Since an increase in the occurrence of native vertebral osteomyelitis (VO) is expected and reliable projections are missing, it is urgent to provide a reliable forecast model and make it a part of future health care considerations.

METHODS

Comprehensive nationwide data provided by the Federal Statistical Office of Germany were used to forecast total numbers and incidence rates (IR) of VO as a function of age and gender until 2040. Projections were done using autoregressive integrated moving average model on historical data from 2005 to 2019 in relation to official population projections from 2020 to 2040.

RESULTS

The IR of VO is expected to increase from 12.4 in 2019 to 21.5 per 100,000 inhabitants [95% CI 20.9-22.1] in 2040. The highest increase is predicted in patients over 75 years of age for both men and women leading to a steep increase in absolute numbers, which is fourfold higher compared to patients younger than 75 years. While the IR per age group will not increase any further after 2035, the subsequent increase is due to a higher number of individuals aged 75 years or older.

CONCLUSIONS

Our data suggest that increasing IR of VO will seriously challenge healthcare systems, particularly due to demographic change and increasing proportions of populations turning 75 years and older. With respect to globally fast aging populations, future health care policies need to address this burden by anticipating limitations in financial and human resources and developing high-level evidence-based guidelines for prevention and interdisciplinary treatment.

Projections From Surgical Use Models in Germany Suggest a Rising Number of Spinal Fusions in Patients 75 Years and Older Will Challenge Healthcare Systems Worldwide

BACKGROUND

Spinal fusion is a well-established procedure in the treatment of degenerative spinal diseases. Previous research shows that the use of this operative treatment has been growing in recent decades in industrialized countries and has become one of the most cost-intensive surgical procedures. It seems that in some countries such as Germany-with its large, industrialized, European population-this increase is mainly driven by demographic changes with low fertility rates, increasing life expectancy, and an aging population. Based on current projections, however, Germany faces a population trend that many other countries are likely to follow within a few decades. An increasingly shrinking and aging working population may eventually put the healthcare system under enormous pressure, with greater demands for spinal fusions and associated higher costs. Thus, we aimed to provide reliable projections regarding the future demand for posterior spinal fusion procedures including age- and gender-related trends up to 2060, which will be necessary for future resource planning and possible improvements in actual treatment strategies.

QUESTIONS/PURPOSES

(1) How is the use of posterior spinal fusions in Germany expected to change from 2019 through 2060, if currents trends continue? (2) How is the use of posterior spinal fusions in Germany expected to change depending on patients' age and gender during this time period?

METHODS

Comprehensive nationwide data provided by the Federal Statistical Office, the official institution for documenting all data on operations and procedures performed in Germany, were used to quantify posterior spinal fusion rates as a function of calendar year, age, and gender. Because there is a lack of evidence regarding future trends in the use of posterior spinal fusions, an autoregressive integrated moving average model on historical procedure rates from 2005 to 2019 in relation to official population projections from 2020 to 2060 was chosen to forecast future absolute numbers and incidence rates of this procedure in Germany. Long-term forecasting is more prone to unexpected disruptions than forecasting over short-term periods; however, longer spans facilitate estimates of how trends may challenge future healthcare systems if those trends continue, and thus are useful for research and planning.

RESULTS

The incidence rate of posterior spinal fusion was projected to increase by approximately 83% (95% CI 28% to 139%) to 102% per 100,000 inhabitants (95% CI 71% to 133%) in 2060, with a 1.3-fold higher rate of women undergoing surgery in terms of absolute numbers. The highest increase identified by the model occurred in patients 75 years and older with 38,974 (95% CI 27,294 to 50,653) posterior spinal fusions in 2060, compared with 14,657 in 2019. This trend applied for both women and men, with a 246% (95% CI 138% to 355%) increase in the total number of posterior spinal fusions for women 75 years and older and a 296% (95% CI 222% to 370%) increase for men 75 years and older. At the same time, posterior spinal fusions in all age groups younger than 55 years were projected to follow a constant or even negative trend up to 2060.

CONCLUSION

Our findings suggest that increasing use of posterior spinal fusion, particularly in patients 75 years and older, will challenge healthcare systems worldwide if current trends persist. This study may serve as a model for many other industrialized countries facing similar demographic and procedure-specific developments in the future. This emphasizes the need to focus on frailty research as well as appropriate financial and human resource management. Effective perioperative medical management, multidisciplinary treatment, and interinstitutional protocols are warranted, especially in older patients as we attempt to manage these trends in the future.

LEVEL OF EVIDENCE

Level III, economic and decision analysis.

The projected volume of primary and revision total knee arthroplasty will place an immense burden on future health care systems over the next 30 years

PURPOSE

Total knee arthroplasty (TKA) rates have increased substantially in the recent decades worldwide, with Germany being one of the leading countries in the prevalence of TKA. The aim of this study was to provide an overview of treatment changes during the last decade and to project the expected burden of primary and revision TKA (rTKA) for the next 30 years.

METHODS

Comprehensive nationwide data from Germany was used to quantify primary and revision TKA rates as a function of age and gender. Projections were performed with use of a Poisson regression models and a combination of exponential smoothing and autoregressive integrated moving average models on historical procedure rates in relation to official population projections from 2020 to 2050.

RESULTS

The incidence rate of primary TKAs is projected to increase by around 43% to 299 per 100,000 inhabitants [95% CI 231-368], leading to a projected total number of 225,957 primary TKAs in 2050 (95% CI 178,804-276,442). This increase has been related to a growing number of TKA performed in male patients, with the highest increase modelled in patients between 50 and 65 years of age. At the same time, the annual total number of revision procedures is forecast to increase even more rapidly by almost 90%, accounting for 47,313 (95% CI 15,741-78,885; IR = 62.7 per 100,000, 95% CI 20.8-104.5) procedures by 2050. Those numbers are primarily associated with a rising number of rTKAs secondary to periprosthetic joint infection (PJI).

CONCLUSIONS

Using this country- specific forecast approach, a rising number of primary TKA and an even more rapidly growing number of rTKA, especially for PJI, has been projected until 2050, which will inevitably provide a huge challenge for the future health care system. As many other industrialized nations will face similar demographic and procedure-specific developments, these forecasts should be alarming for many health care systems worldwide and emphasize the tremendous need for an appropriate financial and human resource management in the future.

LEVEL OF EVIDENCE

Level III, prognostic study, economic and decision analysis.

Identifying unusual performance in Australian and New Zealand intensive care units from 2000 to 2010

Background

The Australian and New Zealand Intensive Care Society (ANZICS) Adult Patient Database (APD) collects voluntary data on patient admissions to Australian and New Zealand intensive care units (ICUs). This paper presents an in-depth statistical analysis of risk-adjusted mortality of ICU admissions from 2000 to 2010 for the purpose of identifying ICUs with unusual performance.

Methods

A cohort of 523,462 patients from 144 ICUs was analysed. For each ICU, the natural logarithm of the standardised mortality ratio (log-SMR) was estimated from a risk-adjusted, three-level hierarchical model. This is the first time a three-level model has been fitted to such a large ICU database anywhere. The analysis was conducted in three stages which included the estimation of a null distribution to describe usual ICU performance. Log-SMRs with appropriate estimates of standard errors are presented in a funnel plot using 5% false discovery rate thresholds. False coverage-statement rate confidence intervals are also presented. The observed numbers of deaths for ICUs identified as unusual are compared to the predicted true worst numbers of deaths under the model for usual ICU performance.

Results

Seven ICUs were identified as performing unusually over the period 2000 to 2010, in particular, demonstrating high risk-adjusted mortality compared to the majority of ICUs. Four of the seven were ICUs in private hospitals. Our three-stage approach to the analysis detected outlying ICUs which were not identified in a conventional (single) risk-adjusted model for mortality using SMRs to compare ICUs. We also observed a significant linear decline in mortality over the decade. Distinct yearly and weekly respiratory seasonal effects were observed across regions of Australia and New Zealand for the first time.

Conclusions

The statistical approach proposed in this paper is intended to be used for the review of observed ICU and hospital mortality. Two important messages from our study are firstly, that comprehensive risk-adjustment is essential in modelling patient mortality for comparing performance, and secondly, that the appropriate statistical analysis is complicated.

Impact of pay for performance on prescribing of long-acting reversible contraception in primary care: an interrupted time series study

BACKGROUND

The aim of this study was to evaluate the impact of Quality and Outcomes Framework (QOF), a major pay-for-performance programme in the United Kingdom, on prescribing of long-acting reversible contraceptives (LARC) in primary care.

METHODS

Negative binomial interrupted time series analysis using practice level prescribing data from April 2007 to March 2012. The main outcome measure was the prescribing rate of long-acting reversible contraceptives (LARC), including hormonal and non hormonal intrauterine devices and systems (IUDs and IUSs), injectable contraceptives and hormonal implants.

RESULTS

Prescribing rates of Long-Acting Reversible Contraception (LARC) were stable before the introduction of contraceptive targets to the QOF and increased afterwards by 4% annually (rate ratios  = 1.04, 95% CI = 1.03, 1.06). The increase in LARC prescribing was mainly driven by increases in injectables (increased by 6% annually), which was the most commonly prescribed LARC method. Of other types of LARC, the QOF indicator was associated with a step increase of 20% in implant prescribing (RR =  1.20, 95% CI =  1.09, 1.32). This change is equivalent to an additional 110 thousand women being prescribed with LARC had QOF points not been introduced.

CONCLUSIONS

Pay for performance incentives for contraceptive counselling in primary care with women seeking contraceptive advice has increased uptake of LARC methods.

Statistical process control of mortality series in the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database: implications of the data generating process

Background

Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency.

Methods

Monthly mean raw mortality (at hospital discharge) time series, 1995–2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) “in-control” status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance.

Results

The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag₄₀ and 35% had autocorrelation through to lag₄₀; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals which were in-control with respect to EWMA control limits and one-step prediction error limits (3SE). The expected series was modelled with a multiplicative seasonal autoregressive model.

Conclusions

The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues.