Developing a synthetic national population to investigate the impact of different cardiovascular disease risk management strategies: A derivation and validation study

BACKGROUND

Many national cardiovascular disease (CVD) risk factor management guidelines now recommend that drug treatment decisions should be informed primarily by patients' multi-variable predicted risk of CVD, rather than on the basis of single risk factor thresholds. To investigate the potential impact of treatment guidelines based on CVD risk thresholds at a national level requires individual level data representing the multi-variable CVD risk factor profiles for a country's total adult population. As these data are seldom, if ever, available, we aimed to create a synthetic population, representing the joint CVD risk factor distributions of the adult New Zealand population.

METHODS AND RESULTS

A synthetic population of 2,451,278 individuals, representing the actual age, gender, ethnicity and social deprivation composition of people aged 30-84 years who completed the 2013 New Zealand census was generated using Monte Carlo sampling. Each 'synthetic' person was then probabilistically assigned values of the remaining cardiovascular disease (CVD) risk factors required for predicting their CVD risk, based on data from the national census national hospitalisation and drug dispensing databases and a large regional cohort study, using Monte Carlo sampling and multiple imputation. Where possible, the synthetic population CVD risk distributions for each non-demographic risk factor were validated against independent New Zealand data sources.

CONCLUSIONS

We were able to develop a synthetic national population with realistic multi-variable CVD risk characteristics. The construction of this population is the first step in the development of a micro-simulation model intended to investigate the likely impact of a range of national CVD risk management strategies that will inform CVD risk management guideline updates in New Zealand and elsewhere.

Adolescent gambling behaviour, a single latent construct and indicators of risk: findings from a national survey of New Zealand high school students

This study explores underlying latent construct/s of gambling behaviour, and identifies indicators of "unhealthy gambling". Data were collected from Youth'07 a nationally representative sample of New Zealand secondary school students (N = 9107). Exploratory factor analyses, item-response theory analyses, multiple indicators-multiple causes, and differential item functioning analyses were used to assess dimensionality of gambling behaviour, underlying factors, and indicators of unhealthy gambling. A single underlying continuum of gambling behaviour was identified. Gambling frequency and 'gambling because I can't stop' were most strongly associated with unhealthy gambling. Gambling to 'feel better about myself' and to 'forget about things' provided the most precise discriminants of unhealthy gambling. Multivariable analyses found that school connectedness was associated with lower levels of unhealthy gambling.

Development and testing of study tools and methods to examine ethnic bias and clinical decision-making among medical students in New Zealand: The Bias and Decision-Making in Medicine (BDMM) study

BACKGROUND

Health provider racial/ethnic bias and its relationship to clinical decision-making is an emerging area of research focus in understanding and addressing ethnic health inequities. Examining potential racial/ethnic bias among medical students may provide important information to inform medical education and training. This paper describes the development, pretesting and piloting of study content, tools and processes for an online study of racial/ethnic bias (comparing Māori and New Zealand European) and clinical decision-making among final year medical students in New Zealand (NZ).

METHODS

The study was developed, pretested and piloted using a staged process (eight stages within five phases). Phase 1 included three stages: 1) scoping and conceptual framework development; 2) literature review and identification of potential measures and items; and, 3) development and adaptation of study content. Three main components were identified to assess different aspects of racial/ethnic bias: (1) implicit racial/ethnic bias using NZ-specific Implicit Association Tests (IATs); (2) explicit racial/ethnic bias using direct questions; and, (3) clinical decision-making, using chronic disease vignettes. Phase 2 (stage 4) comprised expert review and refinement. Formal pretesting (Phase 3) included construct testing using sorting and rating tasks (stage 5) and cognitive interviewing (stage 6). Phase 4 (stage 7) involved content revision and building of the web-based study, followed by pilot testing in Phase 5 (stage 8).

RESULTS

Materials identified for potential inclusion performed well in construct testing among six participants. This assisted in the prioritisation and selection of measures that worked best in the New Zealand context and aligned with constructs of interest. Findings from the cognitive interviewing (nine participants) on the clarity, meaning, and acceptability of measures led to changes in the final wording of items and ordering of questions. Piloting (18 participants) confirmed the overall functionality of the web-based questionnaire, with a few minor revisions made to the final study.

CONCLUSIONS

Robust processes are required in the development of study content to assess racial/ethnic bias in order to optimise the validity of specific measures, ensure acceptability and minimise potential problems. This paper has utility for other researchers in this area by informing potential development approaches and identifying possible measurement tools.

From positive screen to engagement in treatment: a preliminary study of the impact of a new model of care for prisoners with serious mental illness

BACKGROUND

The high prevalence of serious mental illness (SMI) in prisons remains a challenge for mental health services. Many prisoners with SMI do not receive care. Screening tools have been developed but better detection has not translated to higher rates of treatment. In New Zealand a Prison Model of Care (PMOC) was developed by forensic mental health and correctional services to address this challenge. The PMOC broadened triggers for referrals to mental health teams. Referrals were triaged by mental health nurses leading to multidisciplinary team assessment within specified timeframes. This pathway for screening, referral and assessment was introduced within existing resources.

METHOD

The PMOC was implemented across four prisons. An AB research design was used to explore the extent to which mentally ill prisoners were referred to and accepted by prison in-reach mental health teams and to determine the proportion of prison population receiving specialist mental health care.

RESULTS

The number of prisoners in the study in the year before the PMOC (n =  9,349) was similar to the year after (n = 19,421). 24.6 % of prisoners were screened as per the PMOC in the post period. Referrals increased from 491 to 734 in the post period (Z = -7.23, p < 0.0001). A greater number of triage assessments occurred after the introduction of the PMOC (pre = 458; post = 613, Z = 4.74, p < 0.0001) leading to a significant increase in the numbers accepted onto in-reach caseloads (pre = 338; post = 426, Z = 3.16, p < 0.01). Numbers of triage assessments completed within specified time frames showed no statistically significant difference before or after implementation. The proportion of prison population on in-reach caseloads increased from 5.6 % in the pre period to 7.0 % in the year post implementation while diagnostic patterns did not change, indicating more prisoners with SMI were identified and engaged in treatment.

CONCLUSIONS

The PMOC led to increased prisoner numbers across screening, referral, treatment and engagement. Gains were achieved without extra resources by consistent processes and improved clarity of professional roles and tasks. The PMOC described a more effective pathway to specialist care for people with SMI entering prison.