Using QALYs as an Outcome for Assessing Global Prediction Accuracy in Diabetes Simulation Models.

OBJECTIVES: (1) To demonstrate the use of quality-adjusted life-years (QALYs) as an outcome measure for comparing performance between simulation models and identifying the most accurate model for economic evaluation and health technology assessment. QALYs relate directly to decision making and combine mortality and diverse clinical events into a single measure using evidence-based weights that reflect population preferences. (2) To explore the usefulness of Q2, the proportional reduction in error, as a model performance metric and compare it with other metrics: mean squared error (MSE), mean absolute error, bias (mean residual), and R2. METHODS: We simulated all EXSCEL trial participants (N = 14,729) using the UK Prospective Diabetes Study Outcomes Model software versions 1 (UKPDS-OM1) and 2 (UKPDS-OM2). The EXSCEL trial compared once-weekly exenatide with placebo (median 3.2-y follow-up). Default UKPDS-OM2 utilities were used to estimate undiscounted QALYs over the trial period based on the observed events and survival. These were compared with the QALYs predicted by UKPDS-OM1/2 for the same period. RESULTS: UKPDS-OM2 predicted patients' QALYs more accurately than UKPDS-OM1 did (MSE: 0.210 v. 0.253; Q2: 0.822 v. 0.786). UKPDS-OM2 underestimated QALYs by an average of 0.127 versus 0.150 for UKPDS-OM1. UKPDS-OM2 predictions were more accurate for mortality, myocardial infarction, and stroke, whereas UKPDS-OM1 better predicted blindness and heart disease. Q2 facilitated comparisons between subgroups and (unlike R2) was lower for biased predictors. CONCLUSIONS: Q2 for QALYs was useful for comparing global prediction accuracy (across all clinical events) of diabetes models. It could be used for model registries, choosing between simulation models for economic evaluation and evaluating the impact of recalibration. Similar methods could be used in other disease areas. HIGHLIGHTS: Diabetes simulation models are currently validated by examining their ability to predict the incidence of individual events (e.g., myocardial infarction, stroke, amputation) or composite events (e.g., first major adverse cardiovascular event).We introduce Q2, the proportional reduction in error, as a measure that may be useful for evaluating and comparing the prediction accuracy of econometric or simulation models.We propose using the Q2 or mean squared error for QALYs as global measures of model prediction accuracy when comparing diabetes models' performance for health technology assessment; these can be used to select the most accurate simulation model for economic evaluation and to evaluate the impact of model recalibration in diabetes or other conditions.

Chewing gum to treat postoperative nausea and vomiting in female patients: a multicenter randomized trial.

BACKGROUND: Postoperative nausea and vomiting (PONV) is common after general anesthesia, with consequences for patient outcomes, satisfaction with care and healthcare costs. Our aim was to compare a new treatment, chewing gum, with a widely-used intravenous agent, ondansetron, to treat PONV in female patients in the post anesthesia care unit (PACU). METHODS: We conducted a multicenter, randomized, controlled non-inferiority trial in 17 hospitals in Australia and New Zealand. Female patients aged ≥12 years undergoing volatile anesthetic-based general anesthesia for laparoscopic or breast surgery were enrolled. Protocolized anti-emetic prophylaxis was administered. Patients who developed PONV in the PACU were randomized to either 15 min of chewing gum or 4 mg of intravenous ondansetron. The primary outcome was cessation of nausea, retching or vomiting, with no recurrence nor rescue medication for 2 h after administration of the randomized intervention (i.e., complete response). RESULTS: Of 865 enrolled patients, 218 were randomized. In a per-protocol analysis, 50 of 105 (47.6%) ondansetron-treated patients compared with 31 of 103 (30.1%) chewing gum-treated patients achieved the primary outcome (absolute risk difference [95% confidence interval (CI)] -17.3 [-30.4 to -4.3] %), not reaching our prespecified non-inferiority limit. Time to complete response was longer for patients randomized to chewing gum (hazard ratio [95% CI] 0.53 [0.34, 0.83]), and they were more likely to receive antiemetics in the 24 h after surgery (absolute risk difference [95% CI] 14.07 [1.65, 26.49]). CONCLUSIONS: Chewing gum cannot be recommended as an alternative to ondansetron for treatment of PONV in female patients administered antiemetic prophylaxis.

The Impact of Unrelated Future Medical Costs on Economic Evaluation Outcomes for Different Models of Diabetes.

OBJECTIVE: This study leveraged data from 11 independent international diabetes models to evaluate the impact of unrelated future medical costs on the outcomes of health economic evaluations in diabetes mellitus. METHODS: Eleven models simulated the progression of diabetes and occurrence of its complications in hypothetical cohorts of individuals with type 1 (T1D) or type 2 (T2D) diabetes over the remaining lifetime of the patients to evaluate the cost effectiveness of three hypothetical glucose improvement interventions versus a hypothetical control intervention. All models used the same set of costs associated with diabetes complications and interventions, using a United Kingdom healthcare system perspective. Standard utility/disutility values associated with diabetes-related complications were used. Unrelated future medical costs were assumed equal for all interventions and control arms. The statistical significance of changes on the total lifetime costs, incremental costs and incremental cost-effectiveness ratios (ICERs) before and after adding the unrelated future medical costs were analysed using t-test and summarized in incremental cost-effectiveness diagrams by type of diabetes. RESULTS: The inclusion of unrelated costs increased mean total lifetime costs substantially. However, there were no significant differences between the mean incremental costs and ICERs before and after adding unrelated future medical costs. Unrelated future medical cost inclusion did not alter the original conclusions of the diabetes modelling evaluations. CONCLUSIONS: For diabetes, with many costly noncommunicable diseases already explicitly modelled as complications, and with many interventions having predominantly an effect on the improvement of quality of life, unrelated future medical costs have a small impact on the outcomes of health economic evaluations.

Health-related quality of life assessment in health economic analyses involving type 2 diabetes.

AIM: Incorporating health-related quality of life (HRQoL) measures into health economic analyses can help to provide evidence to inform decisions about how to improve patient outcomes in the most cost-effective manner. The aim of this narrative review was to assess which HRQoL instruments have been used in economic evaluations of type 2 diabetes management including in Indigenous communities. METHOD: MEDLINE (Ovid), Embase (Ovid) and Cochrane were searched from inception to June 2022. Studies included patients with type 2 diabetes; economic evaluations, derived scores from direct questioning of individuals; and were in English. Records were assessed for bias using the JBI critical appraisal tools. RESULTS: A total of 3737 records were identified, with 22 publications meeting the criteria for inclusion. Across those 22 articles, nine HRQoL instruments had been utilised. Generic tools were most frequently used to measure HRQoL, including EQ-5D (-3 L and -5 L) (n = 10, 38%); SF-12 (n = 5, 19%); and SF-36 (n = 4, 15%). Two tools addressing the specific stressors faced by people with type 2 diabetes were utilised: Problem Areas In Diabetes tool (n = 1, 4%) and Diabetes Distress Scale (n = 1, 4%). Two publications reported whether the study population included Indigenous peoples. CONCLUSION: A wide range of HRQoL instruments are used in economic evaluations of type 2 diabetes management, with the most frequent being varying forms of the EQ-5D. Few economic evaluations noted whether Indigenous peoples were featured in the study population. More research into HRQoL in people living with type 2 diabetes is urgently needed to improve evidence on effectiveness and cost-effectiveness of interventions.

Examining the Impact of Structural Uncertainty Across 10 Type 2 Diabetes Models: Results From the 2022 Mount Hood Challenge.

OBJECTIVES: The Mount Hood Diabetes Challenge Network aimed to examine the impact of model structural uncertainty on the estimated cost-effectiveness of interventions for type 2 diabetes. METHODS: Ten independent modeling groups completed a blinded simulation exercise to estimate the cost-effectiveness of 3 interventions in 2 type 2 diabetes populations. Modeling groups were provided with a common baseline population, cost and utility values associated with different model health states, and instructions regarding time horizon and discounting. We collated the results to identify variation in predictions of net monetary benefit (NMB) and the drivers of those differences. RESULTS: Overall, modeling groups agreed which interventions had a positive NMB (ie, were cost-effective), Although estimates of NMB varied substantially-by up to £23 696 for 1 intervention. Variation was mainly driven through differences in risk equations for complications of diabetes and their implementation between models. The number of modeled health states was also a significant predictor of NMB. CONCLUSIONS: This exercise demonstrates that structural uncertainty between different health economic models affects cost-effectiveness estimates. Although it is reassuring that a decision maker would likely reach similar conclusions on which interventions were cost-effective using most models, the range in numerical estimates generated across different models would nevertheless be important for price-setting negotiations with intervention developers. Minimizing the impact of structural uncertainty on healthcare decision making therefore remains an important priority. Model registries, which record and compare the impact of structural assumptions, offer one potential avenue to improve confidence in the robustness of health economic modeling.

Recovering from COVID-19 (ReCOV): Feasibility of an Allied-Health-Led Multidisciplinary Outpatient Rehabilitation Service for People with Long COVID.

BACKGROUND: A multidisciplinary approach is required for the management of long COVID. The aim of this study was to determine the feasibility (demand, implementation, practicality, acceptability, and limited efficacy) of an allied-health-led multidisciplinary symptom management service (ReCOV) for long COVID. METHODS: A single-group observational cohort feasibility study was conducted to determine demand (referrals), acceptability (survey), implementation (waitlist times, health professions seen), practicality (adverse events), and limited efficacy (admission and discharge scores from the World Health Organization Disability Assessment Scale, Brief Illness Perception Questionnaire (BIPQ), Patient Health Questionnaire, and EuroQol 5D-5L). Data are presented as median [interquartile range] or count (percentage). RESULTS: During the study, 143 participants (aged 42.00 [32.00-51.00] years, 68% women) participated in ReCOV. Participants were waitlisted for 3.86 [2.14-9.86] weeks and engaged with 5.00 [3.00-6.00] different health professionals. No adverse events occurred. The thematic analysis revealed that ReCOV was helpful but did not fully meet the needs of all participants. Limited efficacy testing indicated that participants had improved understanding and control (p < 0.001) of symptoms (BIPQ) and a small improvement in EQ VAS score (median difference 5.50 points [0.00-25.00], p = 0.004]). CONCLUSIONS: A multidisciplinary service was safe and mostly acceptable to participants for the management of long COVID. Further research should investigate the clinical and cost effectiveness of such a service, including optimal service duration and patient outcomes.

Can flash glucose monitoring improve glucose management for Aboriginal and Torres Strait Islander peoples with type 2 diabetes? A protocol for a randomised controlled trial.

BACKGROUND: Aboriginal and Torres Strait Islander peoples are disproportionately impacted by type 2 diabetes. Continuous glucose monitoring (CGM) technology (such as Abbott Freestyle Libre 2, previously referred to as Flash Glucose Monitoring) offers real-time glucose monitoring that is convenient and easy to use compared to self-monitoring of blood glucose (SMBG). However, this technology's use is neither widespread nor subsidised for Aboriginal and Torres Strait Islander peoples with type 2 diabetes. Building on existing collaborations with a national network of Aboriginal and Torres Strait Islander communities, this randomised controlled trial aims to assess the effect of CGM compared to SMBG on (i) haemoglobin A1c (HbA1c), (ii) achieving blood glucose targets, (iii) reducing hypoglycaemic episodes and (iv) cost-effective healthcare in an Aboriginal and Torres Strait Islander people health setting. METHODS: This is a non-masked, parallel-group, two-arm, individually randomised, controlled trial (ACTRN12621000753853). Aboriginal and Torres Strait Islander adults with type 2 diabetes on injectable therapy and HbA1c ≥ 7.5% (n = 350) will be randomised (1:1) to CGM or SMBG for 6 months. The primary outcome is change in HbA1c level from baseline to 6 months. Secondary outcomes include (i) CGM-derived metrics, (ii) frequency of hypoglycaemic episodes, (iii) health-related quality of life and (iv) incremental cost per quality-adjusted life year gained associated with the CGM compared to SMBG. Clinical trial sites include Aboriginal Community Controlled Organisations, Aboriginal Medical Services, primary care centres and tertiary hospitals across urban, rural, regional and remote Australia. DISCUSSION: The trial will assess the effect of CGM compared to SMBG on HbA1c for Aboriginal and Torres Strait Islander people with type 2 diabetes in Australia. This trial could have long-term benefits in improving diabetes management and providing evidence for funding of CGM in this population. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry ACTRN12621000753853. Registered on 15th June 2021.

A Randomized Noninferiority Trial to Compare Enteral to Parenteral Phosphate Replacement on Biochemistry, Waste, and Environmental Impact and Healthcare Cost in Critically Ill Patients With Mild to Moderate Hypophosphatemia.

OBJECTIVES: Hypophosphatemia occurs frequently. Enteral, rather than IV, phosphate replacement may reduce fluid replacement, cost, and waste. DESIGN: Prospective, randomized, parallel group, noninferiority clinical trial. SETTING: Single center, 42-bed state trauma, medical and surgical ICUs, from April 20, 2022, to July 1, 2022. PATIENTS: Patients with serum phosphate concentration between 0.3 and 0.75 mmol/L. INTERVENTIONS: We randomized patients to either enteral or IV phosphate replacement using electronic medical record-embedded program. MEASUREMENT AND MAIN RESULTS: Our primary outcome was serum phosphate at 24 hours with a noninferiority margin of 0.2 mmol/L. Secondary outcomes included cost savings and environmental waste reduction and additional IV fluid administered. The modified intention-to-treat cohort comprised 131 patients. Baseline phosphate concentrations were similar between the two groups. At 24 hours, mean ( sd ) serum phosphate concentration were enteral 0.89 mmol/L (0.24 mmol/L) and IV 0.82 mmol/L (0.28 mmol/L). This difference was noninferior at the margin of 0.2 mmol/L (difference, 0.07 mmol/L; 95% CI, -0.02 to 0.17 mmol/L). When assigned IV replacement, patients received 408 mL (372 mL) of solvent IV fluid. Compared with IV replacement, the mean cost per patient was ten-fold less with enteral replacement ($3.7 [$4.0] vs. IV: $37.7 [$31.4]; difference = $34.0 [95% CI, $26.3-$41.7]) and weight of waste was less (7.7 g [8.3 g] vs. 217 g [169 g]; difference = 209 g [95% CI, 168-250 g]). C O2 emissions were 60-fold less for comparable phosphate replacement (enteral: 2 g producing 14.2 g and 20 mmol of potassium dihydrogen phosphate producing 843 g of C O2 equivalents). CONCLUSIONS: Enteral phosphate replacement in ICU is noninferior to IV replacement at a margin of 0.2 mmol/L but leads to a substantial reduction in cost and waste.

Feasibility of Embedding a Randomised Clinical Trial (RCT) into an Electronic Medical Record (EMR) for Patients Admitted to an Intensive Care Unit (ICU).

To establish the feasibility of embedding an RCT into EMR in the ICU, we evaluated the route of phosphate replacement. The EMR screened 207 patients who met the inclusion criteria from 20 April 2022 to 30 June 2022. 162 patients were randomised and 145 patients allocated to treatment. Our study showed that it was feasible to embed screening, randomisation, and treatment allocation for an RCT within an EMR in the ICU.

Health-related quality of life in patients with extremity bone sarcoma after surgical treatment: a systematic review.

PURPOSE: We conducted a systematic review of studies reporting on measurement of health-related quality of life (HRQoL), with a special focus on the use of the preference-weighted instruments, in patients with extremity bone sarcoma treated with limb-salvage surgery or amputation. METHODS: We searched MedLine, Embase, Cochrane Library and Web of Science for English-language studies reporting on HRQoL of patients with bone sarcoma from inception to 28 August 2023. All records found were independently reviewed by two reviewers. We used the Newcastle-Ottawa Scale (NOS) and the CONSORT 2010 checklist to assess the quality of the cohort and randomised studies, respectively. RESULTS: The search identified 1225 records, of which 16 studies were included for data extraction. Only one study used a preference-weighted instrument for measuring HRQoL in a small sample of patients (n = 28). Ten studies used the generic SF-36 questionnaire, but no preference-weighted HRQoL based on SF-6D was derived from the SF-36 scores. Most studies comparing HRQoL between amputation and limb-salvage surgery reported no significant differences. Twelve cohort studies scored six or more out of nine points based on the NOS. The only randomised study scored 54% on the CONSORT 2010 checklist. CONCLUSIONS: The approaches used to measure HRQoL were inconsistent and outcome scores varied substantially. Only one study used preference-weighted instruments for HRQoL measurement. Future research into the surgical treatment of extremity bone sarcoma should consider the use of preference-weighted instruments to measure HRQoL, which will therefore enable economic evaluation for the growing orthopaedic armamentarium of novel surgical interventions. REGISTRATION: This systematic review was registered with the PROSPERO International prospective register of systematic reviews (CRD42021282380).

Impact of health risk factors on healthcare resource utilization, work-related outcomes and health-related quality of life of Australians: a population-based longitudinal data analysis.

Background: Health risk factors, including smoking, excessive alcohol consumption, overweight, obesity, and insufficient physical activity, are major contributors to many poor health conditions. This study aimed to assess the impact of health risk factors on healthcare resource utilization, work-related outcomes and health-related quality of life (HRQoL) in Australia. Methods: We used two waves of the nationally representative Household, Income, and Labor Dynamics in Australia (HILDA) Survey from 2013 and 2017 for the analysis. Healthcare resource utilization included outpatient visits, hospitalisations, and prescribed medication use. Work-related outcomes were assessed through employment status and sick leave. HRQoL was assessed using the SF-6D scores. Generalized estimating equation (GEE) with logit or log link function and random-effects regression models were used to analyse the longitudinal data on the relationship between health risk factors and the outcomes. The models were adjusted for age, sex, marital status, education background, employment status, equilibrium household income, residential area, country of birth, indigenous status, and socio-economic status. Results: After adjusting for all other health risk factors covariates, physical inactivity had the greatest impact on healthcare resource utilization, work-related outcomes, and HRQoL. Physical inactivity increased the likelihood of outpatient visits (AOR = 1.60, 95% CI = 1.45, 1.76 p < 0.001), hospitalization (AOR = 1.83, 95% CI = 1.66-2.01, p < 0.001), and the probability of taking sick leave (AOR = 1.31, 95% CI = 1.21-1.41, p < 0.001), and decreased the odds of having an above population median HRQoL (AOR = 0.48, 95% CI = 0.45-0.51, p < 0.001) after adjusting for all other health risk factors and covariates. Obesity had the greatest impact on medication use (AOR = 2.02, 95% CI = 1.97-2.29, p < 0.001) after adjusting for all other health risk factors and covariates. Conclusion: Our study contributed to the growing body of literature on the relative impact of health risk factors for healthcare resource utilization, work-related outcomes and HRQoL. Our results suggested that public health interventions aim at improving these risk factors, particularly physical inactivity and obesity, can offer substantial benefits, not only for healthcare resource utilization but also for productivity.

Telehealth in oncology: a cost analysis to evaluate the financial impact of implementing regional trial hubs within a phase 3 cancer clinical trial.

This cost analysis, from a societal perspective, compared the cost difference of a networked teletrial model (NTTM) with four regional hubs versus conventional trial operation at a single metropolitan specialist centre. The Australian phase 3 cancer interventional randomised controlled trial included 152 of 328 regional participants (patient enrolment 2018-2021; 6-month primary end point). The NTTM significantly reduced (AU$2155 per patient) patient travel cost and time and lost productivity.

Trial of Vancomycin and Cefazolin as Surgical Prophylaxis in Arthroplasty.

BACKGROUND: The addition of vancomycin to beta-lactam prophylaxis in arthroplasty may reduce surgical-site infections; however, the efficacy and safety are unclear. METHODS: In this multicenter, double-blind, superiority, placebo-controlled trial, we randomly assigned adult patients without known methicillin-resistant Staphylococcus aureus (MRSA) colonization who were undergoing arthroplasty to receive 1.5 g of vancomycin or normal saline placebo, in addition to cefazolin prophylaxis. The primary outcome was surgical-site infection within 90 days after surgery. RESULTS: A total of 4239 patients underwent randomization. Among 4113 patients in the modified intention-to-treat population (2233 undergoing knee arthroplasty, 1850 undergoing hip arthroplasty, and 30 undergoing shoulder arthroplasty), surgical-site infections occurred in 91 of 2044 patients (4.5%) in the vancomycin group and in 72 of 2069 patients (3.5%) in the placebo group (relative risk, 1.28; 95% confidence interval [CI], 0.94 to 1.73; P = 0.11). Among patients undergoing knee arthroplasty, surgical-site infections occurred in 63 of 1109 patients (5.7%) in the vancomyin group and in 42 of 1124 patients (3.7%) in the placebo group (relative risk, 1.52; 95% CI, 1.04 to 2.23). Among patients undergoing hip arthroplasty, surgical-site infections occurred in 28 of 920 patients (3.0%) in the vancomyin group and in 29 of 930 patients (3.1%) in the placebo group (relative risk, 0.98; 95% CI, 0.59 to 1.63). Adverse events occurred in 35 of 2010 patients (1.7%) in the vancomycin group and in 35 of 2030 patients (1.7%) in the placebo group, including hypersensitivity reactions in 24 of 2010 patients (1.2%) and 11 of 2030 patients (0.5%), respectively (relative risk, 2.20; 95% CI, 1.08 to 4.49), and acute kidney injury in 42 of 2010 patients (2.1%) and 74 of 2030 patients (3.6%), respectively (relative risk, 0.57; 95% CI, 0.39 to 0.83). CONCLUSIONS: The addition of vancomycin to cefazolin prophylaxis was not superior to placebo for the prevention of surgical-site infections in arthroplasty among patients without known MRSA colonization. (Funded by the Australian National Health and Medical Research Council; Australian New Zealand Clinical Trials Registry number, ACTRN12618000642280.).

Study protocol for TARGET protein: The effect of augmented administration of enteral protein to critically ill adults on clinical outcomes: A cluster randomised, cross-sectional, double cross-over, clinical trial.

Background: It is unknown whether increasing dietary protein to 1.2-2.0 g/kg/day as recommended in international guidelines compared to current practice improves outcomes in intensive care unit (ICU) patients. The TARGET Protein trial will evaluate this. Objective: To describe the study protocol for the TARGET Protein trial. Design setting and participants: TARGET Protein is a cluster randomised, cross-sectional, double cross-over, pragmatic clinical trial undertaken in eight ICUs in Australia and New Zealand. Each ICU will be randomised to use one of two trial enteral formulae for three months before crossing over to the other formula, which is then repeated, with enrolment continuing at each ICU for 12 months. All patients aged ≥16 years in their index ICU admission commencing enteral nutrition will be eligible for inclusion. Eligible patients will receive the trial enteral formula to which their ICU is allocated. The two trial enteral formulae are isocaloric with a difference in protein dose: intervention 100g/1000 ml and comparator 63g/1000 ml. Staggered recruitment commenced in May 2022. Main outcomes measures: The primary outcome is days free of the index hospital and alive at day 90. Secondary outcomes include days free of the index hospital at day 90 in survivors, alive at day 90, duration of invasive ventilation, ICU and hospital length of stay, incidence of tracheostomy insertion, renal replacement therapy, and discharge destination. Conclusion: TARGET Protein aims to determine whether augmented enteral protein delivery reduces days free of the index hospital and alive at day 90. Trial registration: Australian New Zealand Clinical Trials Registry (ACTRN12621001484831).

Understanding the measurement relationship between EQ-5D-5L, PROMIS-29 and PROPr.

PURPOSE: Many generic patient-reported instruments are available for the measurement of health outcomes, including EQ-5D-5L, and the Patient-Reported Outcome Measurement Information System (PROMIS). Assessing their measurement characteristics informs users about the consistency between, and limits of, evidence produced. The aim was to assess the measurement relationship between the EQ-5D-5L descriptive system and value sets, the PROMIS-29 and PROPr (PROMIS value set). METHODS: Data were extracted from a cross-sectional survey administering measures of quality of life online in Australia. Descriptive analysis, agreement and construct validity assessment methods were used to compare instruments at the item, domain and value set level. RESULTS: In total, 794 Australians completed the survey. Convergent validity analysis found that similar dimensions across instruments were highly correlated (> 0.50), but the PROMIS-29 assesses additional health concepts not explicitly covered by EQ-5D (sleep and fatigue). Known-group assessment found that EQ-5D-5L and PROPr were able to detect those with and without a condition (ES range 0.78-0.83) but PROPr could more precisely detect differing levels of self-reported health. Both instruments were sensitive to differences in levels of pain. DISCUSSION: There is some consistency in what the EQ-5D-5L, PROMIS-29 and PROPr measure. Differences between value set characteristics can be linked to differences what is measured and the valuation approaches used. This has implications for the use of each in assessing health outcomes, and the results can inform decisions about which instrument should be used in which context.

Predicting high health-cost users among people with cardiovascular disease using machine learning and nationwide linked social administrative datasets.

OBJECTIVES: To optimise planning of public health services, the impact of high-cost users needs to be considered. However, most of the existing statistical models for costs do not include many clinical and social variables from administrative data that are associated with elevated health care resource use, and are increasingly available. This study aimed to use machine learning approaches and big data to predict high-cost users among people with cardiovascular disease (CVD). METHODS: We used nationally representative linked datasets in New Zealand to predict CVD prevalent cases with the most expensive cost belonging to the top quintiles by cost. We compared the performance of four popular machine learning models (L1-regularised logistic regression, classification trees, k-nearest neighbourhood (KNN) and random forest) with the traditional regression models. RESULTS: The machine learning models had far better accuracy in predicting high health-cost users compared with the logistic models. The harmony score F1 (combining sensitivity and positive predictive value) of the machine learning models ranged from 30.6% to 41.2% (compared with 8.6-9.1% for the logistic models). Previous health costs, income, age, chronic health conditions, deprivation, and receiving a social security benefit were among the most important predictors of the CVD high-cost users. CONCLUSIONS: This study provides additional evidence that machine learning can be used as a tool together with big data in health economics for identification of new risk factors and prediction of high-cost users with CVD. As such, machine learning may potentially assist with health services planning and preventive measures to improve population health while potentially saving healthcare costs.

The comparative mortality of an elite group in the long run of history: an observational analysis of politicians from 11 countries.

This study aims to compare the mortality rate and life expectancy of politicians with those of the age and gender-matched general populations. This was an observational analysis of mortality rates of politicians (i.e. members of national parliaments with available data on dates of birth, death and election, gender, and life tables) in 11 developed countries. Politicians were followed from date of first election until either death or the last available year with life table data. Relative mortality differences were estimated using standardised mortality ratios (SMRs). Absolute inequalities were quantified as the difference in survival by deducting a population's remaining life expectancy from politicians' remaining life expectancy at age 45, estimated using Gompertz parametric proportional hazards models. We included 57,561 politicians (with follow-up ranging from 1816-2016 for France to 1949-2017 for Germany). In almost all countries politicians had similar rates of mortality to the general population in the early part of the twentieth century. Relative mortality and survival differences (favouring politicians) increased considerably over the course of the twentieth century, with recent SMRs ranging from 0.45 (95%CI 0.41-0.50) in Italy to 0.82 (95%CI 0.69-0.95) in New Zealand. The peak life expectancy gaps ranged from 4.4 (95% CI, 3.5-5.4) years in the Netherlands to 7.8 (95% CI, 7.2-8.4) years in the US. Our results show large relative and absolute inequalities favouring politicians in every country. In some countries, such as the US, relative inequalities are at the greatest level in over 150 years.

Exploring Structural Uncertainty and Impact of Health State Utility Values on Lifetime Outcomes in Diabetes Economic Simulation Models: Findings from the Ninth Mount Hood Diabetes Quality-of-Life Challenge.

BACKGROUND: Structural uncertainty can affect model-based economic simulation estimates and study conclusions. Unfortunately, unlike parameter uncertainty, relatively little is known about its magnitude of impact on life-years (LYs) and quality-adjusted life-years (QALYs) in modeling of diabetes. We leveraged the Mount Hood Diabetes Challenge Network, a biennial conference attended by international diabetes modeling groups, to assess structural uncertainty in simulating QALYs in type 2 diabetes simulation models. METHODS: Eleven type 2 diabetes simulation modeling groups participated in the 9th Mount Hood Diabetes Challenge. Modeling groups simulated 5 diabetes-related intervention profiles using predefined baseline characteristics and a standard utility value set for diabetes-related complications. LYs and QALYs were reported. Simulations were repeated using lower and upper limits of the 95% confidence intervals of utility inputs. Changes in LYs and QALYs from tested interventions were compared across models. Additional analyses were conducted postchallenge to investigate drivers of cross-model differences. RESULTS: Substantial cross-model variability in incremental LYs and QALYs was observed, particularly for HbA1c and body mass index (BMI) intervention profiles. For a 0.5%-point permanent HbA1c reduction, LY gains ranged from 0.050 to 0.750. For a 1-unit permanent BMI reduction, incremental QALYs varied from a small decrease in QALYs (-0.024) to an increase of 0.203. Changes in utility values of health states had a much smaller impact (to the hundredth of a decimal place) on incremental QALYs. Microsimulation models were found to generate a mean of 3.41 more LYs than cohort simulation models (P = 0.049). CONCLUSIONS: Variations in utility values contribute to a lesser extent than uncertainty captured as structural uncertainty. These findings reinforce the importance of assessing structural uncertainty thoroughly because the choice of model (or models) can influence study results, which can serve as evidence for resource allocation decisions.HighlightsThe findings indicate substantial cross-model variability in QALY predictions for a standardized set of simulation scenarios and is considerably larger than within model variability to alternative health state utility values (e.g., lower and upper limits of the 95% confidence intervals of utility inputs).There is a need to understand and assess structural uncertainty, as the choice of model to inform resource allocation decisions can matter more than the choice of health state utility values.

Evidence on the relationship between PROMIS-29 and EQ-5D: a literature review.

PURPOSE: EQ-5D and PROMIS-29 are both concise, generic measures of patient-reported outcomes accompanied by preference weights that allow the estimation of quality-adjusted life years (QALYs). Both instruments are candidates for use in economic evaluation. However, they have different features in terms of the domains selected to measure respondents' self-perceived health and the characteristics of (and methods used to obtain) the preference weights. It is important to understand the relationship between the instruments and the implications of choosing either for the evidence used in decision-making. This literature review aimed to synthesise existing evidence on the relationship between PROMIS-29 (and measures based on it, such as PROMIS-29+2) and EQ-5D (both EQ-5D-3L and EQ-5D-5L). METHODS: A literature review was conducted in PubMed and Web of Science to identify studies investigating the relationship between PROMIS-29 and EQ-5D-based instruments. RESULTS: The literature search identified 95 unique studies, of which nine studies met the inclusion criteria, i.e. compared both instruments. Six studies examined the relationship between PROMIS-29 and EQ-5D-5L. Three main types of relationship have been examined in the nine studies: (a) comparing PROMIS-29 and EQ-5D as descriptive systems; (b) mapping PROMIS-29 domains to EQ-5D utilities; and (c) comparing and transforming PROMIS-29 utilities to EQ-5D utilities. CONCLUSION: This review has highlighted the lack of evidence regarding the relationship between PROMIS-29 and EQ-5D. The impact of choosing either instrument on the evidence used in cost-effectiveness analysis is currently unclear. Further research is needed to understand the relationship between the two instruments.