Novel application of a discrete choice experiment to identify preferences for a national healthcare-associated infection surveillance programme: a cross-sectional study

Eliciting primary healthcare physicians' preferences for job characteristics in rural China: a discrete choice experiment

INTRODUCTION

The outflow and scarcity of physicians in rural areas can adversely affect universal health coverage and population health outcomes, which are critical concerns in China. This study explored primary healthcare physicians' job preferences using a discrete choice experiment to identify appropriate incentives for retention.

METHODS

Eight job characteristics were identified through a literature review and qualitative studies as the attributes relevant to designing the discrete choice experiment, with levels varying between two hypothetical jobs. The data were analysed using conditional logit model, mixed logit model and latent class model.

RESULTS

A total of 1781 licensed physicians (including licensed assistant physicians) from township health centres in rural areas were surveyed. Policy simulation suggested that they were sensitive to both monetary and non-monetary policy incentives. As for non-monetary job characteristics, a highly intense doctor-patient relationship, bianzhi (the number of personnel allocated to each employer by the government) and educational opportunities were highly valued by the respondents. The latent class model could identify distinct groups with different job preferences according to their memberships.

CONCLUSION

Urban jobs were much preferred to rural ones. However, policy incentives can lend themselves to effective retention strategies. It is also important to tailor policy incentives to different subgroups.

Exploring employment preferences of nurses to improve retention in rural China

BACKGROUND

The scarcity of nurses in rural China deserves serious consideration in light of the widening gap in health outcomes between rural and urban populations. The outflow of primary care nurses suggests the value of examining their employment preferences to identify possible effective incentives for their retention.

METHODS

Our research used discrete choice experiment methodology designed to quantitatively measure the relative importance of various job attributes valued by primary care nurses using conditional logit and mixed logit models. Willingness to pay and uptake rates were also calculated.

RESULTS

A total of 1744 registered nurses in township health centres were surveyed. Participants considered all the job attributes included in the study to be significant, with pay increases demonstrating the greatest potential to improve the retention of nurses. Among the non-monetary aspects of work, nurse-patient relationships, bianzhi (positions allocated to each unit by the Chinese government with special benefits) and educational opportunities ranked highest in importance for respondents. Responses to hypothetical policy proposals suggest that incentive packages are also likely to be effective.

CONCLUSIONS

Policy making regarding rural nurses' retention is an important undertaking that requires an evidence-based approach. Our findings provide a range of policy options that shed light on effective retention strategies. Tailoring policy incentives to primary care nurses is also necessary.

Changes in public preferences for technologically enhanced surveillance following the COVID-19 pandemic: a discrete choice experiment

OBJECTIVES

As governments attempt to navigate a path out of COVID-19 restrictions, robust evidence is essential to inform requirements for public acceptance of technologically enhanced communicable disease surveillance systems. We examined the value of core surveillance system attributes to the Australian public, before and during the early stages of the current pandemic.

DESIGN

A discrete choice experiment was conducted in Australia with a representative group of respondents, before and after the WHO declared COVID-19 a Public Health Emergency of International Concern. We identified and investigated the relative importance of seven attributes associated with technologically enhanced disease surveillance: respect for personal autonomy; privacy/confidentiality; data certainty/confidence; data security; infectious disease mortality prevention; infectious disease morbidity prevention; and attribution of (causal) responsibility. Specifically, we explored how the onset of the COVID-19 outbreak influenced participant responses.

SETTING AND PARTICIPANTS

2008 Australians (general public) completed the experiment: 793 before COVID-19 outbreak onset (mean age 45.9 years, 50.2% male) and 1215 after onset (mean age 47.2 years, 49% male).

RESULTS

All seven attributes significantly influenced respondents' preferences for communicable disease surveillance systems. After onset, participants demonstrated greater preference for a surveillance system that could prevent a higher number of illnesses and deaths, and were less concerned about their personal autonomy. However, they also increased their preference for a system with high data security.

CONCLUSIONS

Public acceptance of technology-based communicable disease surveillance is situation dependent. During an epidemic, there is likely to be greater tolerance of technologically enhanced disease surveillance systems that result in restrictions on personal activity if such systems can prevent high morbidity and mortality. However, this acceptance of lower personal autonomy comes with an increased requirement to ensure data security. These findings merit further research as the pandemic unfolds and strategies are put in place that enable individuals and societies to live with SARS-CoV-2 endemicity.

Healthcare-associated infections in Australia: tackling the 'known unknowns'

Australia does not have a national healthcare-associated infection (HAI) surveillance program. Without national surveillance, we do not understand the burden of HAIs, nor can we accurately assess the effects of national infection prevention initiatives. Recent research has demonstrated disparity between existing jurisdictional-based HAI surveillance activity while also identifying broad key stakeholder support for the establishment of a national program. A uniform surveillance program will also address growing concerns about hospital performance measurements and enable public reporting of hospital data.

Establishing the prevalence of healthcare-associated infections in Australian hospitals: protocol for the Comprehensive Healthcare Associated Infection National Surveillance (CHAINS) study

INTRODUCTION

A healthcare-associated infection (HAI) data point prevalence study (PPS) conducted in 1984 in Australian hospitals estimated the prevalence of HAI to be 6.3%. Since this time, there have been no further national estimates undertaken. In the absence of a coordinated national surveillance programme or regular PPS, there is a dearth of national HAI data to inform policy and practice priorities.

METHODS AND ANALYSIS

A national HAI PPS study will be undertaken based on the European Centres for Disease Control method. Nineteen public acute hospitals will participate. A standardised algorithm will be used to detect HAIs in a two-stage cluster design, random sample of adult inpatients in acute wards and all intensive care unit patients. Data from each hospital will be collected by two trained members of the research team. We will estimate the prevalence of HAIs, invasive device use, single room placement and deployment of transmission-based precautions.

ETHICS AND DISSEMINATION

Ethics approval was obtained from the Alfred Health Human Research Ethics Committee (HREC/17/Alfred/203) via the National Mutual Assessment. A separate approval was obtained from the Tasmanian Health and Medical Human Research Committee (H0016978) for participating Tasmanian hospitals. Findings will be disseminated in individualised participating hospital reports, peer-reviewed publications and conference presentations.

Estimating the Direct Medical Economic Burden of Health Care-Associated Infections in Public Tertiary Hospitals in Hubei Province, China

This study estimated the attributable direct medical economic burden of health care-associated infections (HAIs) in China. Data were extracted from hospitals' information systems. Inpatient cases with HAIs and non-HAIs were grouped by the propensity score matching (PSM) method. Attributable hospitalization expenditures and length of hospital stay were measured to estimate the direct medical economic burden of HAIs. STATA 12.0 was used to conduct descriptive analysis, bivariate χ² test, paired Z test, PSM ( r = 0.25σ, nearest neighbor 1:1 matching), and logistic regress analysis. The statistically significant level was set at .05. The HAIs group had statistically significant higher expenditures and longer hospitalization stay than the non-HAIs group during 2013 to 2015 ( P < .001). The annual average HAI attributable total expenditure, medicines expenditure, out-of-pocket expenditure, and number of hospitalization days per inpatient were (2015 US$) 6173.02, 2257.98, and 1958.25 and 25 days during 2013 to 2015. The direct medical cost savings was estimated at more than 2015 US$12 billion per year in Chinese tertiary hospitals across the country. The significant attributable direct medical economic burden of HAIs calls for more effective HAI surveillance and better control with appropriate incentives.