Identifying infants at risk of sudden unexpected death with an automated predictive risk model

BACKGROUND/OBJECTIVE

Sudden unexpected infant death (SUID) is a common cause of infant death. We evaluated whether a predictive risk model (PRM) - Hello Baby - which was developed to stratify children by risk of entry into foster care could also identify infants at highest risk of SUID and non-fatal unsafe sleep events.

PARTICIPANTS AND SETTING

Cases: Infants with SUID or an unsafe sleep event over 5½ years in a single county.

CONTROLS

All births in the same county.

METHODS

Retrospective case-control study. Demographic and clinical data were collected and a Hello Baby PRM score was assigned. Descriptive statistics and the predictive value of a PRM score of 20 were calculated.

RESULTS

Infants with SUID (n = 62) or an unsafe sleep event (n = 37) (cases) were compared with 23,366 births (controls). Cases and controls were similar for all demographic and clinical data except that infants with unsafe sleep events were older. Median PRM score for cases was higher than controls (17.5 vs. 10, p < 0.001); 50 % of cases had a PRM score 17-20 vs. 16 % of controls (p < 0.001).

CONCLUSIONS

The Hello Baby PRM can identify newborns at high risk of SUID and non-fatal unsafe sleep events. The ability to identify high-risk newborns prior to a negative outcome allows for individualized evaluation of high-risk families for modifiable risk factors which are potentially amenable to intervention. This approach is limited by the fact that not all counties can calculate a PRM or similar score automatically.

Using predictive risk modelling to identify patients with hidden health needs in an Aboriginal and Torres Strait Islander health service

BACKGROUND AND OBJECTIVES

In partnership with an Aboriginal and Torres Strait Islander community-controlled health service, we explored the use of a machine learning tool to identify high-needs patients for whom services are harder to reach and, hence, who do not engage with primary care.

METHOD

Using deidentified electronic health record data, two predictive risk models (PRMs) were developed to identify patients who were: (1) unlikely to have health checks as an indicator of not engaging with care; and (2) likely to rate their wellbeing as poor, as a measure of high needs.

RESULTS

According to the standard metrics, the PRMs were good at predicting health checks but showed low reliability for detecting poor wellbeing.

DISCUSSION

Results and feedback from clinicians were encouraging. With additional refinement, informed by clinic staff feedback, a deployable model should be feasible.

Using electronic health record data to predict future self-harm or suicidal ideation in young people treated by child and youth mental health services

INTRODUCTION

Identifying young people who are at risk of self-harm or suicidal ideation (SHoSI) is a priority for mental health clinicians. We explore the utility of routinely collected data in developing a tool to aid early identification of those at risk.

METHOD

We used electronic health records of 4610 young people aged 5-19 years who were treated by Child and Youth Mental Health Services (CYMHS) in greater Brisbane, Australia. Two Lasso models were trained to predict the risk of future SHoSI in young people currently rated SHoSI; and those who were not.

RESULTS

For currently non-SHoSI children, an Area Under the Receiver Operating Characteristics (AUC) of 0.78 was achieved. Those with the highest risk were 4.97 (CI 4.35-5.66) times more likely to be categorized as SHoSI in the future. For current SHoSI children, the AUC was 0.62.

CONCLUSION

A prediction model with fair overall predictive power for currently non-SHoSI children was generated. Predicting persistence for SHoSI was more difficult. The electronic health records alone were not sufficient to discriminate at acceptable levels and may require adding unstructured data such as clinical notes. To optimally predict SHoSI models need to be tested and validated separately for those young people with varying degrees of risk.

Machine learning to predict poor school performance in paediatric survivors of intensive care: a population-based cohort study

PURPOSE

Whilst survival in paediatric critical care has improved, clinicians lack tools capable of predicting long-term outcomes. We developed a machine learning model to predict poor school outcomes in children surviving intensive care unit (ICU).

METHODS

Population-based study of children < 16 years requiring ICU admission in Queensland, Australia, between 1997 and 2019. Failure to meet the National Minimum Standard (NMS) in the National Assessment Program-Literacy and Numeracy (NAPLAN) assessment during primary and secondary school was the primary outcome. Routine ICU information was used to train machine learning classifiers. Models were trained, validated and tested using stratified nested cross-validation.

RESULTS

13,957 childhood ICU survivors with 37,200 corresponding NAPLAN tests after a median follow-up duration of 6 years were included. 14.7%, 17%, 15.6% and 16.6% failed to meet NMS in school grades 3, 5, 7 and 9. The model demonstrated an Area Under the Receiver Operating Characteristic curve (AUROC) of 0.8 (standard deviation SD, 0.01), with 51% specificity to reach 85% sensitivity [relative Area Under the Precision Recall Curve (rel-AUPRC) 3.42, SD 0.06]. Socio-economic status, illness severity, and neurological, congenital, and genetic disorders contributed most to the predictions. In children with no comorbidities admitted between 2009 and 2019, the model achieved a AUROC of 0.77 (SD 0.03) and a rel-AUPRC of 3.31 (SD 0.42).

CONCLUSIONS

A machine learning model using data available at time of ICU discharge predicted failure to meet minimum educational requirements at school age. Implementation of this prediction tool could assist in prioritizing patients for follow-up and targeting of rehabilitative measures.

Estimating the economic costs of Indigenous health inequities in New Zealand: a retrospective cohort analysis

OBJECTIVES

Despite significant international interest in the economic impacts of health inequities, few studies have quantified the costs associated with unfair and preventable ethnic/racial health inequities. This Indigenous-led study is the first to investigate health inequities between Māori and non-Māori adults in New Zealand (NZ) and estimate the economic costs associated with these differences.

DESIGN

Retrospective cohort analysis. Quantitative epidemiological methods and 'cost-of-illness' (COI) methodology were employed, within a Kaupapa Māori theoretical framework.

SETTING

Data for 2003-2014 were obtained from national data collections held by NZ government agencies, including hospitalisations, mortality, outpatient and primary care consultations, laboratory and pharmaceutical usage and accident claims.

PARTICIPANTS

All adults in NZ aged 15 years and above who had engagement with the health system between 2003 and 2014 (deidentified).

PRIMARY AND SECONDARY OUTCOME MEASURES

Rates of 'potentially avoidable' hospitalisations and mortality as well as 'excess or underutilisation' of healthcare were calculated, as the difference between actual rates for Māori and the rate expected if Māori had the same rates as non-Māori. These differences were then quantified using COI methodology to estimate the financial cost of ethnic inequities.

RESULTS

In this conservative estimate, health inequities between Māori and non-Māori adults cost NZ$863.3 million per year. Direct costs of NZ$39.9 million per year included costs from ambulatory sensitive hospitalisations and outpatient care, with cost savings from underutilisation of primary care. Indirect costs of NZ$823.4 million per year came from years of life lost and lost wages.

CONCLUSIONS

Indigenous adult health inequities in NZ create significant direct and indirect costs. The 'cost of doing nothing' is predominantly borne by Indigenous communities and society. The net cost of adult health inequities to the government conceals substantial savings to the government from underutilisation of primary care and accident/injury care.

Sibyl: Understanding and Addressing the Usability Challenges of Machine Learning In High-Stakes Decision Making

Machine learning (ML) is being applied to a diverse and ever-growing set of domains. In many cases, domain experts - who often have no expertise in ML or data science - are asked to use ML predictions to make high-stakes decisions. Multiple ML usability challenges can appear as result, such as lack of user trust in the model, inability to reconcile human-ML disagreement, and ethical concerns about oversimplification of complex problems to a single algorithm output. In this paper, we investigate the ML usability challenges that present in the domain of child welfare screening through a series of collaborations with child welfare screeners. Following the iterative design process between the ML scientists, visualization researchers, and domain experts (child screeners), we first identified four key ML challenges and honed in on one promising explainable ML technique to address them (local factor contributions). Then we implemented and evaluated our visual analytics tool, Sibyl, to increase the interpretability and interactivity of local factor contributions. The effectiveness of our tool is demonstrated by two formal user studies with 12 non-expert participants and 13 expert participants respectively. Valuable feedback was collected, from which we composed a list of design implications as a useful guideline for researchers who aim to develop an interpretable and interactive visualization tool for ML prediction models deployed for child welfare screeners and other similar domain experts.

Hospital Injury Encounters of Children Identified by a Predictive Risk Model for Screening Child Maltreatment Referrals: Evidence From the Allegheny Family Screening Tool

IMPORTANCE

Nearly 6 million children are reported as allegedly experiencing abuse or neglect in the US annually. Child protection agencies are increasingly turning to automated predictive risk models (PRMs) that mine information found in routinely collected administrative data and estimate a likelihood that an individual will experience some future adverse outcome.

OBJECTIVE

To test if a PRM used at the time of referral for alleged maltreatment, which automatically generates a risk stratification score indicating the relative likelihood of future foster care placement, is also predictive of injury hospitalization data.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study based on a probabilistic association between child protection and hospital encounter data was conducted in Allegheny County, Pennsylvania, and at Children's Hospital of Pittsburgh (Pittsburgh, Pennsylvania). Participants included children referred for alleged neglect or abuse in Allegheny County between April 1, 2010, and May 4, 2016.

EXPOSURES

Risk score generated from the PRM.

MAIN OUTCOMES AND MEASURES

Medical encounters (emergency department and inpatient hospitalizations) for any-cause injuries, suicide or self-inflicted harm injuries, and abuse injuries between 2002 and 2015 for children classified by the PRM to different risk levels at the time of a maltreatment referral. Cancer encounters were used as a placebo test.

RESULTS

Of 47 305 participants, 23 601 (49.9%) were girls, the mean (SD) age at referral was 8 (5.7) years, 28 211 (59.6%) were black, and 19 094 (40.4%) were nonblack. Children who scored in the highest 5% risk group by the PRM were more likely to have a medical encounter for an injury during the follow-up period than low-risk children (ie, those in the bottom 50% of risk). Specifically, among children referred for maltreatment and classified as highest risk, the rate of experiencing an any-cause injury encounter was 14.5 (95% CI, 13.1-15.9) per 100 compared with children who scored as low risk who had an any-cause injury encounter rate of 4.9 (95% CI, 4.7-5.2) per 100. For abuse-associated injury encounters, the rate for high-risk children was 2.0 (95% CI, 1.5-2.6) per 100 and that of low-risk children was 0.2 (95% CI, 0.2-0.3) per 100; for suicide and self-harm, the high-risk encounter rate was 1.0 (95% CI, 0.6-1.4) per 100 and that of low-risk children was 0.1 (95% CI, 0.1-0.1) per 100. There was no association between risk scores and cancer encounters.

CONCLUSIONS AND RELEVANCE

Findings confirm that children reported for having experienced alleged maltreatment and classified by a PRM tool to be at high risk of foster care placement are also at increased risk of emergency department and in-patient hospitalizations for injuries.

Measuring the working experience of doctors in training

Using an online tool, we report the association between tasks and 'affect' (underlying experience of feeling, emotion or mood) among 565 doctors in training, how positive and negative emotional intensity are associated with time of day, the extent to which positive affect is associated with breaks, and consideration about leaving the profession. Respondents spent approximately 25% of their day on paperwork or clinical work that did not involve patients, resulting in more negative emotions. Positive emotions were expressed for breaks, staff meetings, research, learning and clinical tasks that involved patients. Those having considered leaving the profession report more negative feelings. Systematic workplace changes (regular breaks, reducing paperwork and improved IT systems) could contribute to positive workday experiences and reduce intention to quit. Educators and employers have important roles in recognising, advocating for and implementing improvements at work to enhance wellbeing with potential to improve retention of doctors in training.

Ethnic Disparities in Childhood Prevalence of Maltreatment: Evidence From a New Zealand Birth Cohort

Objectives. To document ethnic disparities in childhood abuse and neglect among New Zealand children.Methods. We followed the 1998 New Zealand birth cohort of 56 904 children through 2016. We determined the cumulative childhood prevalence of reports to child protective services (CPS), substantiated maltreatment (by subtype), and out-of-home placements, from birth to age 18 years, by ethnic group. We also developed estimates stratified by maternal age and community deprivation levels.Results. We identified substantial ethnic differences in child maltreatment and child protection involvement. Both Māori and Pacific Islander children had a far greater likelihood of being reported to CPS, being substantiated as victims, and experiencing an out-of-home placement than other children. Across all levels of CPS interactions, rates of Māori involvement were more than twice those of Pacific Islander children and more than 3 times those of European children.Conclusions. Despite long-standing child support policies and reparation for breaches of Indigenous people's rights, significant child maltreatment disparities persist. More work is needed to understand how New Zealand's public benefit services can be more responsive to the needs of Indigenous families and their children.

Adverse childhood experiences and school readiness outcomes: results from the Growing Up in New Zealand study

AIM

The Center for Disease Control's (CDC) Adverse Childhood Experiences (ACEs) have been associated with adverse health consequences in adults and children, but less is known about any association between ACE and early learning skills. We investigated the relationship between ACEs and objective preschool measures of skills using the Growing up In New Zealand (GUiNZ) cohort study (n=5,562; 2009-2015).

METHODS

We mapped standard ACE definitions to GUiNZ to determine the prevalence of ACEs. We performed regression analysis to investigate the association between ACEs and a range of outcome measures, including counting up to 10, counting down from 10, letter recognition, affective knowledge, name writing, number writing and delayed gratification.

RESULTS

Before entering primary school, 52.8% of GUiNZ children experienced at least one ACE. We found a dose-response relationship with seven of the eight tests. For example, after statistically adjusting for multiple potential confounders, for each one additional ACE, children were 1.12 times more likely to be unable to count up from 1-10 (95% Confidence Interval 1.04-1.19).

CONCLUSIONS

Awareness of the negative impact of ACEs on school readiness should aid in the development and prioritisation of prevention strategies to reduce the occurrence and impact of ACEs in children.

Monthly spending dynamics of the elderly following a health shock: Evidence from Singapore

We use novel longitudinal data from 19 monthly waves of the Singapore Life Panel to examine the short-term dynamics of the effects health shocks have on household health and nonhealth spending and income by the elderly. The health shocks we study are the occurrence of new major conditions such as cancer, heart problems, and minor conditions (e.g., diabetes and hypertension). Our empirical strategy is based on an event study approach that exploits unanticipated changes in health status through the diagnosis of new health conditions. We find that major shocks have large and persistent effects whereas minor shocks have small and mainly contemporaneous effects. We find that household income reduces following a major shock for males but not females. Major health shocks lead to a decrease in households' nonhealth expenditures that is particularly pronounced for cancer and stroke sufferers, driven largely by reductions in leisure spending. The financial impact of major shocks on medical saving account balances occurs to those without private health insurance, whereas the impact is on cash balances for privately insured individuals.

Estimating the economic costs of ethnic health inequities: protocol for a prevalence-based cost-of-illness study in New Zealand (2003-2014)

INTRODUCTION

There is significant international interest in the economic impacts of persistent inequities in morbidity and mortality. However, very few studies have quantified the costs associated with unfair and preventable ethnic/racial inequities in health. The proposed study will investigate inequities in health between the indigenous Māori and non-Māori adult population in New Zealand (15 years and older) and estimate the economic costs associated with these differences.

METHODS AND ANALYSIS

The study will use national collections data that is held by government agencies in New Zealand including hospitalisations, mortality, outpatient consultations, laboratory and pharmaceutical claims, and accident compensation claims. Epidemiological methods will be used to calculate prevalences for Māori and non-Māori, by age-group, gender and socioeconomic deprivation (New Zealand Deprivation Index) where possible. Rates of 'potentially avoidable' hospitalisations and mortality as well as 'excess or under' utilisation of healthcare will be calculated as the difference between the actual rate and that expected if Māori were to have the same rates as non-Māori. A prevalence-based cost-of-illness approach will be used to estimate health inequities and the costs associated with treatment, as well as other financial and non-financial costs (such as years of life lost) over the person's lifetime.

ETHICS AND DISSEMINATION

This analysis has been approved by the University of Auckland Human Participants Research Committee (Ref: 018621). Dissemination of findings will occur via published peer-reviewed articles, presentations to academic, policy and community-based stakeholder groups and via social media.

Cumulative Prevalence of Maltreatment Among New Zealand Children, 1998-2015

OBJECTIVES

To document, via linked administrative data, the cumulative prevalence among New Zealand children of notifications to child protective services (CPS), substantiated maltreatment cases, and out-of-home placements.

METHODS

We followed all children born in New Zealand in 1998 until the end of 2015 (an overall sample of 55 443 children). We determined the cumulative frequencies of notifications, substantiated maltreatment cases (by subtype), and first entries into foster care from birth through the age of 17 years. We also decomposed CPS involvement by gender.

RESULTS

We found that almost 1 in 4 children had been subject to at least 1 report to CPS at age 17 years (23.5%), and 9.7% had been a victim of substantiated abuse or neglect. We also found that 3.1% had experienced out-of-home placements by age 17 years, with boys being more affected.

CONCLUSIONS

Both notifications and substantiated child maltreatment are more common in New Zealand than is generally recognized, with the incidence of notifications higher than the incidence of medicated asthma among children and the prevalence of substantiations similar to the prevalence of obesity.

Injury and Mortality Among Children Identified as at High Risk of Maltreatment

OBJECTIVES

To determine if children identified by a predictive risk model as at "high risk" of maltreatment are also at elevated risk of injury and mortality in early childhood.

METHODS

We built a model that predicted a child's risk of a substantiated finding of maltreatment by child protective services for children born in New Zealand in 2010. We assigned risk scores to the 2011 birth cohort, and flagged children as "very high risk" if they were in the top 10% of the score distribution for maltreatment. We also set a less conservative threshold for defining "high risk" and examined children in the top 20%. We then compared the incidence of injury and mortality rates between very high-risk and high-risk children and the remainder of the birth cohort.

RESULTS

Children flagged at both 10% and 20% risk thresholds had much higher postneonatal mortality rates than other children (4.8 times and 4.2 times greater, respectively), as well as a greater relative risk of hospitalization (2 times higher and 1.8 times higher, respectively).

CONCLUSIONS

Models that predict risk of maltreatment as defined by child protective services substantiation also identify children who are at heightened risk of injury and mortality outcomes. If deployed at birth, these models could help medical providers identify children in families who would benefit from more intensive supports.

Better the devil you know than the doctor you don't: is advertising drugs to doctors more harmful than advertising to patients?

Most countries ban the advertising of prescription medication directly to consumers, yet allow drug companies to promote drugs to doctors intensively. Such a differential treatment of promotion cannot be justified on economic grounds, but is a result of paternalism in health care regulation, which portrays patients as gullible and doctors as perfect agents. Instead, there should be a complete deregulation of direct-to-consumer (DTC) advertising and doctors ought to be required to reveal their relationships with drug companies. This is particularly apt, given the calls for similar transparency rules to address the potential conflict of interest between drug companies and researchers.

Economic burden of disease-associated malnutrition in China

Disease-associated malnutrition (DAM) is a well-recognized problem in many countries, but the extent of its burden on the Chinese population is unclear. This article reports the results of a burden-of-illness study on DAM in 15 diseases in China. Using data from the World Health Organization (WHO), the China Health and Nutrition Survey, and the published literature, mortality and disability-adjusted life years (DALYs) lost because of DAM were calculated; a financial value of this burden was calculated following WHO guidelines. DALYs lost annually to DAM in China varied across diseases, from a low of 2248 in malaria to a high of 1 315 276 in chronic obstructive pulmonary disease. The total burden was 6.1 million DALYs, for an economic burden of US$66 billion (Chinese ¥ 447 billion) annually. This burden is sufficiently large to warrant immediate attention from public health officials and medical providers, especially given that low-cost and effective interventions are available.

Children in the public benefit system at risk of maltreatment: identification via predictive modeling

A growing body of research links child abuse and neglect to a range of negative short- and long-term health outcomes. Determining a child's risk of maltreatment at or shortly after birth provides an opportunity for the delivery of targeted prevention services. This study presents findings from a predictive risk model (PRM) developed to estimate the likelihood of substantiated maltreatment among children enrolled in New Zealand's public benefit system. The objective was to explore the potential use of administrative data for targeting prevention and early intervention services to children and families. A data set of integrated public benefit and child protection records for children born in New Zealand between January 1, 2003, and June 1, 2006, was used to develop a risk algorithm using stepwise probit modeling. Data were analyzed in 2012. The final model included 132 variables and produced an area under the receiver operating characteristic curve of 76%. Among children in the top decile of risk, 47.8% had been substantiated for maltreatment by age 5 years. Of all children substantiated for maltreatment by age 5 years, 83% had been enrolled in the public benefit system before age 2 years. This analysis demonstrates that PRMs can be used to generate risk scores for substantiated maltreatment. Although a PRM cannot replace more-comprehensive clinical assessments of abuse and neglect risk, this approach provides a simple and cost-effective method of targeting early prevention services.

Multidisciplinary case management for patients at high risk of hospitalization: comparison of virtual ward models in the United kingdom, United States, and Canada

Virtual wards are a model for delivering multidisciplinary case management to people who are at high predicted risk of unplanned acute care hospitalization. First introduced in Croydon, England, in 2006, this concept has since been adopted and adapted by health care organizations in other parts of the United Kingdom and internationally. In this article, the authors review the model of virtual wards as originally described-with its twin pillars of (1) using a predictive model to identify people who are at high risk of future emergency hospitalization, and (2) offering these individuals a period of intensive, multidisciplinary preventive care at home using the systems, staffing, and daily routines of a hospital ward. The authors then describe how virtual wards have been modified and implemented in 6 sites in the United Kingdom, United States, and Canada where they are subject to formal evaluation. Like hospital wards, virtual wards vary in terms of patient selection, ward configuration, staff composition, and ward processes. Policy makers and researchers should be aware of these differences when considering the evaluation results of studies investigating the cost-effectiveness of virtual wards.

The cost of child health inequalities in Aotearoa New Zealand: a preliminary scoping study

BACKGROUND

Health inequalities have been extensively documented, internationally and in New Zealand. The cost of reducing health inequities is often perceived as high; however, recent international studies suggest the cost of "doing nothing" is itself significant. This study aimed to develop a preliminary estimate of the economic cost of health inequities between Māori (indigenous) and non-Māori children in New Zealand.

METHODS

Standard quantitative epidemiological methods and "cost of illness" methodology were employed, within a Kaupapa Māori theoretical framework. Data were obtained from national data collections held by the New Zealand Health Information Service and other health sector agencies.

RESULTS

Preliminary estimates suggest child health inequities between Māori and non-Māori in New Zealand are cost-saving to the health sector. However the societal costs are significant. A conservative "base case" scenario estimate is over $NZ62 million per year, while alternative costing methods yield larger costs of nearly $NZ200 million per annum. The total cost estimate is highly sensitive to the costing method used and Value of Statistical Life applied, as the cost of potentially avoidable deaths of Māori children is the major contributor to this estimate.

CONCLUSIONS

This preliminary study suggests that health sector spending is skewed towards non-Māori children despite evidence of greater Māori need. Persistent child health inequities result in significant societal economic costs. Eliminating child health inequities, particularly in primary care access, could result in significant economic benefits for New Zealand. However, there are conceptual, ethical and methodological challenges in estimating the economic cost of child health inequities. Re-thinking of traditional economic frameworks and development of more appropriate methodologies is required.

Perceptions of junior doctors in the NHS about their training: results of a regional questionnaire

OBJECTIVE

To explore the views of doctors in training about their current roles and their potential value to the National Health Service (NHS) in improving healthcare quality and productivity.

METHODS

Online questionnaire sent via email to 3766 junior doctors (foundation year one to specialist trainee year 3+) in the NHS South Central region.

RESULTS

The response rate was 1479/3766 (39.3%). Respondents recognised the importance of leadership (89.7%), team working (89.2%) and professionalism (97%). Only 3.4% of junior doctors stated they have never acted in a leadership capacity. However, respondents reported a lack of receptivity from their organisations: the majority responded that they do not feel valued by managers (83.3%), the chief executive (77.7%), the organisation (77.3%), the NHS (79.3%) and consultants (58.2%). 91.2% of respondents have had ideas for improvement in their workplace; however, only 10.7% have had their ideas for change implemented. Respondents who had been on a NHS South Central leadership development course were significantly more likely to feel valued by all groups of staff in their organisation. They were also significantly more likely to report having their ideas implemented.

CONCLUSIONS

Doctors in training have a desire and perceived ability to contribute to improvement in the NHS but do not perceive their working environment as receptive to their skills. Junior doctors who attend leadership training report higher levels of desire and ability to express these skills. This study suggests junior doctors are an untapped NHS resource and that they and their organisations would benefit from more formalised provision of training in leadership.

Predictive risk modelling in health: options for New Zealand and Australia

Predictive risk models (PRMs) are case-finding tools that enable health care systems to identify patients at risk of expensive and potentially avoidable events such as emergency hospitalisation. Examples include the PARR (Patients-at-Risk-of-Rehospitalisation) tool and Combined Predictive Model used by the National Health Service in England. When such models are coupled with an appropriate preventive intervention designed to avert the adverse event, they represent a useful strategy for improving the cost-effectiveness of preventive health care. This article reviews the current knowledge about PRMs and explores some of the issues surrounding the potential introduction of a PRM to a public health system. We make a particular case for New Zealand, but also consider issues that are relevant to Australia.

Counterheroism, common knowledge, and ergonomics: concepts from aviation that could improve patient safety

CONTEXT

Many safety initiatives have been transferred successfully from commercial aviation to health care. This article develops a typology of aviation safety initiatives, applies this to health care, and proposes safety measures that might be adopted more widely. It then presents an economic framework for determining the likely costs and benefits of different patient safety initiatives.

METHODS

This article describes fifteen examples of error countermeasures that are used in public transport aviation, many of which are not routinely used in health care at present. Examples are the sterile cockpit rule, flight envelope protection, the first-names-only rule, and incentivized no-fault reporting. It develops a conceptual schema that is then used to argue why analogous initiatives might be usefully applied to health care and why physicians may resist them. Each example is measured against a set of economic criteria adopted from the taxation literature.

FINDINGS

The initiatives considered in the article fall into three themes: safety concepts that seek to downplay the role of heroic individuals and instead emphasize the importance of teams and whole organizations; concepts that seek to increase and apply group knowledge of safety information and values; and concepts that promote safety by design. The salient costs to be considered by organizations wishing to adopt these suggestions are the compliance costs to clinicians, the administration costs to the organization, and the costs of behavioral distortions.

CONCLUSIONS

This article concludes that there is a range of safety initiatives used in commercial aviation that could have a positive impact on patient safety, and that adopting such initiatives may alter the safety culture of health care teams. The desirability of implementing each initiative, however, depends on the projected costs and benefits, which must be assessed for each situation.

Building on myths: an economist's response to the Ministerial Review Group Report on the health system

The (2009) Report of the Ministerial Review Group (MRG) recommends a number of useful measures to enhance the New Zealand health system such as reducing the number of primary health organisations (PHOs). However, the report's warnings about the "unsustainability" of the current publicly funded health system are overstated. I argue that the logic for the creation of new agencies and the break-up of the functions of the Ministry of Health has not been clearly articulated. Restructuring is an extremely expensive exercise--and should only be done when there is a compelling logic to the new structure.

The NHS as an insurer

The National Health Service (NHS) in England is not only a commissioner and provider of health care to the sick, but also offers certainty and peace of mind to all citizens--even those who do not use the health service in any year. However, due to the recent dominance of cost-effectiveness and cost-utility analysis as the central factors determining resource allocation decisions in the NHS, this second role--which we term its 'insurance value'--has increasingly become neglected. In this paper, we argue that this inattention is detrimental to the population at large. We explore some implications to the NHS of maximizing insurance value. These include requiring commissioners to take explicit account of how denial of service undermines peace of mind; requiring the National Institute for Health and Clinical Excellence (NICE) to calculate not just the health benefits, but also the peace of mind benefits of health technologies; and establishing a formal NHS 'insurance regulator' analogous to the Financial Ombudsman Service. Insurance value should be a guiding principle for NHS decision-makers.

Health insurance and imperfect competition in the health care market

We show that when health care providers have market power and engage in Cournot competition, a competitive upstream health insurance market results in over-insurance and over-priced health care. Even though consumers and firms anticipate the price interactions between these two markets - the price set in one market affects the demand expressed in the other - Pareto improvements are possible. The results suggest a beneficial role for Government intervention, either in the insurance or the health care market.

Supply-side cost sharing when patients and doctors collude

Doctors and patients generally share a common interest in maximizing the quality of care. Purchasers of health care on the other hand, desire cost-effective levels of quality. We consider the purchaser's problem of implementing supply-side cost sharing when patients and doctors are asymmetrically informed and can collude to advance their own joint interests in maximal quality. Such collusion can be interpreted as the sort of informal side-payments that are observed in transitional and developing economies. It may also be interpreted as a "formal" (but unregulated) case of physician balance billing. We show that both collusion-proof schemes and collusion-inducing schemes can implement cost-effective care. A number of policy implications are discussed. In particular, more permissive advertising of referred services (such as pharmaceuticals) and more informed patients will increase the cost of implementing collusion-proof mechanisms. If patients have a high willingness to pay or are informed, then allowing collusion may be preferred.