Health insurance system fragmentation and COVID-19 mortality: Evidence from Peru.

Peru has a fragmented health insurance system in which most insureds can only access the providers in their insurer's network. The two largest sub-systems covered about 53% and 30% of the population at the start of the pandemic; however, some individuals have dual insurance and can thereby access both sets of providers. We use data on 24.7 million individuals who belonged to one or both sub-systems to investigate the effect of dual insurance on COVID-19 mortality. We estimate recursive bivariate probit models using the difference in the distance to the nearest hospital in the two insurance sub-systems as Instrumental Variable. The effect of dual insurance was to reduce COVID-19 mortality risk by 0.23% compared with the sample mean risk of 0.54%. This implies that the 133,128 COVID-19 deaths in the sample would have been reduced by 56,418 (95%CI: 34,894, 78,069) if all individuals in the sample had dual insurance.

Addressing recall bias in (post-)conflict data collection and analysis: lessons from a large-scale health survey in Colombia.

BACKGROUND: Much applied research on the consequences of conflicts for health suffers from data limitations, particularly the absence of longitudinal data spanning pre-, during- and post-conflict periods for affected individuals. Such limitations often hinder reliable measurement of the causal effects of conflict and their pathways, hampering also the design of effective post-conflict health policies. Researchers have sought to overcome these data limitations by conducting ex-post surveys, asking participants to recall their health and living standards before (or during) conflict. These questions may introduce important analytical biases due to recall error and misreporting. METHODS: We investigate how to implement ex-post health surveys that collect recall data, for conflict-affected populations, which is reliable for empirical analysis via standard quantitative methods. We propose two complementary strategies based on methods developed in the psychology and psychometric literatures-the Flashbulb and test-retest approaches-to identify and address recall bias in ex-post health survey data. We apply these strategies to the case study of a large-scale health survey which we implemented in Colombia in the post-peace agreement period, but that included recall questions referring to the conflict period. RESULTS: We demonstrate how adapted versions of the Flashbulb and test-retest strategies can be used to test for recall bias in (post-)conflict survey responses. We also show how these test strategies can be incorporated into post-conflict health surveys in their design phase, accompanied by further ex-ante mitigation strategies for recall bias, to increase the reliability of survey data analysis-including by identifying the survey modules, and sub-populations, for which empirical analysis is likely to yield more reliable causal inference about the health consequences of conflict. CONCLUSIONS: Our study makes a novel contribution to the field of applied health research in humanitarian settings, by providing practical methodological guidance for the implementation of data collection efforts in humanitarian contexts where recall information, collected from primary surveys, is required to allow assessments of changes in health and wellbeing. Key lessons include the importance of embedding appropriate strategies to test and address recall bias into the design of any relevant data collection tools in post-conflict or humanitarian contexts.

The impact of moving to a 12h shift pattern on employee wellbeing: A qualitative study in an acute mental health setting.

BACKGROUND: Against a backdrop of increasing demand for mental health services, and difficulties in recruitment and retention of mental health staff, employers may consider implementation of 12 h shifts to reduce wage costs. Mixed evidence regarding the impact of 12 h shifts may arise because research is conducted in divergent contexts. Much existing research is cross sectional in design and evaluates impact during the honeymoon phase of implementation. Previous research has not examined the impact of 12 h shifts in mental health service settings. OBJECTIVE: To evaluate how employees in acute mental health settings adapt and respond to a new 12 h shift system from a wellbeing perspective. DESIGN: A qualitative approach was adopted to enable analysis of subjective employee experiences of changes to organisation contextual features arising from the shift pattern change, and to explore how this shapes wellbeing. SETTING(S): Six acute mental health wards in the same geographical area of a large mental health care provider within the National Health Service in England. PARTICIPANTS: 70 participants including modern matrons, ward managers, clinical leads, staff nurses and healthcare assistants. METHODS: Semi-structured interviews with 35 participants at 6 months post-implementation of a new 12 h shift pattern, with a further 35 interviewed at 12 months post-implementation. RESULTS: Thematic analysis identified unintended consequences of 12 h shifts as these patterns changed roles and the delivery of care, diminishing perceptions of quality of patient care, opportunities for social support, with reports of pacing work to preserve emotional and physical stamina. These features were moderated by older age, commitment to the public healthcare sector, and fit to individual circumstances in the non-work domain leading to divergent work-life balance outcomes. CONCLUSIONS: Findings indicate potential exists for differential wellbeing outcomes of a 12 h shift pattern and negative effects are exacerbated in a stressful and dynamic acute mental health ward context. In a tight labour market with an ageing workforce, employee flexibility and choice are key to retention and wellbeing. Compulsory 12 h shift patterns should be avoided in this setting.

The impact of extending nurse working hours on staff sickness absence: Evidence from a large mental health hospital in England.

BACKGROUND: A pressing international concern is the issue of mental health workforce capacity, which is also of concern in England where staff attrition rates are significantly higher than in physical health services. Increasing demand for mental health services has led to severe financial pressures resulting in staff shortages, increased workloads, and work-related stress, with health care providers testing new models of care to reduce cost. Previous evidence suggests shift work can negatively affect health and wellbeing (increased accidents, fatigue, absenteeism) but can be perceived as beneficial by both employers and employees (fewer handovers, less overtime, cost savings). OBJECTIVE: This study reports an evaluation of the impact of extending the shifts of nurses and health care assistants from 8 to 12 hours. Using data before and after the policy change, the effect of extended working hours on short term sickness (< 7 days) on staff is examined. SETTING: The setting is six inpatient wards within a large mental health hospital in England where the shift extension took place between June and October 2017. The Data come from wards administrative records and the analysis is performed using weekly data (N=463). METHODS: Causal inference methods (Interrupted Time Series and Difference-in-Difference) are used to compare staff sickness rates before and after the implementation, where the outcome variable is defined as the ratio of total sickness hours over the total scheduled working hours (full time equivalents) in a given week. Patient casemix, staff demographics, ward and time variables are included as controls. RESULTS: Estimation results establish that the extended shifts are associated with an increased percentage of sickness hours per week of between 0.73% and 0.98%, the equivalent of a complete shift per week per ward. CONCLUSION: This is the first study to use causal inference to measure the impact of longer shifts on sickness absences for mental health workforce. The analysis is relevant to other providers which may increasingly look towards these shift patterns as a means of cost saving.

Potential determinants of health system efficiency: Evidence from Latin America and the Caribbean.

This paper examines the levels of health system efficiency and their possible determinants across Latin American and Caribbean (LAC) countries using national-level data for those countries, as well as for other emerging and developed countries. The data are analyzed using data envelopment analyses and econometric advances that yield reliable estimations of the relationship between system efficiency and its potential determinants. We find that there is substantial room for efficiency improvements in the health system of most LAC countries. For example, LAC countries could improve life expectancy at birth by about five years on average at current public spending levels if they followed best practices. Furthermore, the paper assesses what factors amenable to policy act as the main possible levers for some countries to be able to translate a given level of health financing into better performance on access to care and health outcomes. Our econometric analyses suggest that efforts to increase health system efficiency could be focused in a few key policy areas associated with broader access to health services and better outcomes. These areas include general governance aspects, in addition to improvements in specific dimensions of the quality of health system institutions, notably stronger reliance on results-based management in the production of healthcare goods and services.