Preferences for a third-trimester ultrasound scan in a low-risk obstetric population: a discrete choice experiment

Patient Preferences in Diagnostic Imaging: A Scoping Review

BACKGROUND

As new diagnostic imaging technologies are adopted, decisions surrounding diagnostic imaging become increasingly complex. As such, understanding patient preferences in imaging decision making is imperative.

OBJECTIVES

We aimed to review quantitative patient preference studies in imaging-related decision making, including characteristics of the literature and the quality of the evidence.

METHODS

The Pubmed, Embase, EconLit, and CINAHL databases were searched to identify studies involving diagnostic imaging and quantitative patient preference measures from January 2000 to June 2022. Study characteristics that were extracted included the preference elicitation method, disease focus, and sample size. We employed the PREFS (Purpose, Respondents, Explanation, Findings, Significance) checklist as our quality assessment tool.

RESULTS

A total of 54 articles were included. The following methods were used to elicit preferences: conjoint analysis/discrete choice experiment methods (n = 27), contingent valuation (n = 16), time trade-off (n = 4), best-worst scaling (n = 3), multicriteria decision analysis (n = 3), and a standard gamble approach (n = 1). Half of the studies were published after 2016 (52%, 28/54). The most common scenario (n = 39) for eliciting patient preferences was cancer screening. Computed tomography, the most frequently studied imaging modality, was included in 20 studies, and sample sizes ranged from 30 to 3469 participants (mean 552). The mean PREFS score was 3.5 (standard deviation 0.8) for the included studies.

CONCLUSIONS

This review highlights that a variety of quantitative preference methods are being used, as diagnostic imaging technologies continue to evolve. While the number of preference studies in diagnostic imaging has increased with time, most examine preventative care/screening, leaving a gap in knowledge regarding imaging for disease characterization and management.

Conceptualization, measurement, and effects of pregnancy-specific stress: review of research using the original and revised Prenatal Distress Questionnaire

Pregnancy-specific stress (PSS) arises from the numerous changes that women experience during pregnancy and from their concerns about childbirth and the health of their offspring. Prolonged or elevated maternal stress heightens risk for poor fetal, infant, and child outcomes. The Prenatal Distress Questionnaire (PDQ) and its expanded successor, the revised Prenatal Distress Questionnaire (NuPDQ), were developed to assess PSS, but their psychometric properties and findings are not well-documented. We reviewed research using the PDQ (n = 45) or NuPDQ (n = 37). Results establish that PSS as measured by these instruments is common in pregnancy; PSS is associated with sociodemographic and obstetric characteristics, perceptions of pregnancy, health behaviors, maternal health, and birth outcomes. The NuPDQ is an especially appropriate tool to assess PSS, with demonstrated reliability and convergent, concurrent, and predictive validity. The ability to assess PSS in a reliable and valid manner is critical to advance research and improve maternal and child health.

Preferences for aspects of antenatal and newborn screening: a systematic review

BACKGROUND

Many countries offer screening programmes to unborn and newborn babies (antenatal and newborn screening) to identify those at risk of certain conditions to aid earlier diagnosis and treatment. Technological advances have stimulated the development of screening programmes to include more conditions, subsequently changing the information required and potential benefit-risk trade-offs driving participation. Quantifying preferences for screening programmes can provide programme commissioners with data to understand potential demand, the drivers of this demand, information provision required to support the programmes and the extent to which preferences differ in a population. This study aimed to identify published studies eliciting preferences for antenatal and newborn screening programmes and provide an overview of key methods and findings.

METHODS

A systematic search of electronic databases for key terms identified eligible studies (discrete choice experiments (DCEs) or best-worst scaling (BWS) studies related to antenatal/newborn testing/screening published between 1990 and October 2018). Data were systematically extracted, tabulated and summarised in a narrative review.

RESULTS

A total of 19 studies using a DCE or BWS to elicit preferences for antenatal (n = 15; 79%) and newborn screening (n = 4; 21%) programmes were identified. Most of the studies were conducted in Europe (n = 12; 63%) but there were some examples from North America (n = 2; 11%) and Australia (n = 2; 11%). Attributes most commonly included were accuracy of screening (n = 15; 79%) and when screening occurred (n = 13; 68%). Other commonly occurring attributes included information content (n = 11; 58%) and risk of miscarriage (n = 10; 53%). Pregnant women (n = 11; 58%) and healthcare professionals (n = 11; 58%) were the most common study samples. Ten studies (53%) compared preferences across different respondents. Two studies (11%) made comparisons between countries. The most popular analytical model was a standard conditional logit model (n = 11; 58%) and one study investigated preference heterogeneity with latent class analysis.

CONCLUSION

There is an existing literature identifying stated preferences for antenatal and newborn screening but the incorporation of more sophisticated design and analytical methods to investigate preference heterogeneity could extend the relevance of the findings to inform commissioning of new screening programmes.

Discrete Choice Experiments in Health Economics: Past, Present and Future

OBJECTIVES

Discrete choice experiments (DCEs) are increasingly advocated as a way to quantify preferences for health. However, increasing support does not necessarily result in increasing quality. Although specific reviews have been conducted in certain contexts, there exists no recent description of the general state of the science of health-related DCEs. The aim of this paper was to update prior reviews (1990-2012), to identify all health-related DCEs and to provide a description of trends, current practice and future challenges.

METHODS

A systematic literature review was conducted to identify health-related empirical DCEs published between 2013 and 2017. The search strategy and data extraction replicated prior reviews to allow the reporting of trends, although additional extraction fields were incorporated.

RESULTS

Of the 7877 abstracts generated, 301 studies met the inclusion criteria and underwent data extraction. In general, the total number of DCEs per year continued to increase, with broader areas of application and increased geographic scope. Studies reported using more sophisticated designs (e.g. D-efficient) with associated software (e.g. Ngene). The trend towards using more sophisticated econometric models also continued. However, many studies presented sophisticated methods with insufficient detail. Qualitative research methods continued to be a popular approach for identifying attributes and levels.

CONCLUSIONS

The use of empirical DCEs in health economics continues to grow. However, inadequate reporting of methodological details inhibits quality assessment. This may reduce decision-makers' confidence in results and their ability to act on the findings. How and when to integrate health-related DCE outcomes into decision-making remains an important area for future research.