No abstract

It is customary to increase the sensitivity of a control chart using an efficient estimator of the underlying process parameter which is being monitored. In this paper, using an auxiliary information‐based (AIB) mean estimator, we propose dual multivariate CUSUM (DMCUSUM) and mixed DMCUSUM (MDMCUSUM) charts, called the AIB‐DMCUSUM and AIB‐MDMCUSUM charts, with and without fast initial response features for monitoring the mean vector of a multivariate normally distributed process. The DMCUSUM chart combines two similar‐type multivariate CUSUM (MCUSUM) charts while the MDMCUSUM chart combines two different‐type MCUSUM charts, into a single chart. The objective of two multivariate subcharts in the DMCUSUM/MDMCUSUM chart is to simultaneously detect small‐to‐moderate and moderate‐to‐large shifts in the process mean vector. Monte Carlo simulations are used to compute the run length characteristics, including the average run length (ARL), extra quadratic loss, and integral of the relative ARL. Based on detailed run length comparisons, it turns out that the AIB‐DMCUSUM and AIB‐MDMCUSUM charts uniformly and substantially outperform the DMCUSUM and MDMCUSUM charts when detecting different sizes of shift in the process mean vector. A real dataset is used to explain the implementation of proposed AIB multivariate charts.

Background In response to the COVID-19 pandemic, concerted efforts were made by provincial and federal governments to invest in critical care infrastructure and medical equipment to bridge the gap of resource-limitation in intensive care units (ICUs) across Pakistan. An initial step in creating a plan toward strengthening Pakistan’s baseline critical care capacity was to carry out a needs-assessment within the country to assess gaps and devise strategies for improving the quality of critical care facilities. Methods To assess the baseline critical care capacity of Pakistan, we conducted a series of cross-sectional surveys of hospitals providing COVID-19 care across the country. These hospitals were pre-identified by the Health Services Academy (HSA), Pakistan. Surveys were administered via telephonic and on-site interviews and based on a unique checklist for assessing critical care units which was created from the Partners in Health 4S Framework, which is: Space, Staff, Stuff, and Systems. These components were scored, weighted equally, and then ranked into quartiles. Results A total of 106 hospitals were surveyed, with the majority being in the public sector (71.7%) and in the metropolitan setting (56.6%). We found infrastructure, staffing, and systems lacking as only 19.8% of hospitals had negative pressure rooms and 44.4% had quarantine facilities for staff. Merely 36.8% of hospitals employed accredited intensivists and 54.8% of hospitals maintained an ideal nurse-to-patient ratio. 31.1% of hospitals did not have a staffing model, while 37.7% of hospitals did not have surge policies. On Chi-square analysis, statistically significant differences (p < 0.05) were noted between public and private sectors along with metropolitan versus rural settings in various elements. Almost all ranks showed significant disparity between public–private and metropolitan–rural settings, with private and metropolitan hospitals having a greater proportion in the 1st rank, while public and rural hospitals had a greater proportion in the lower ranks. Conclusion Pakistan has an underdeveloped critical care network with significant inequity between public–private and metropolitan–rural strata. We hope for future resource allocation and capacity development projects for critical care in order to reduce these disparities.

BackgroundPatient safety is a top priority for many healthcare organisations worldwide. However, most of the initiatives aimed at the measurement and improvement of patient safety culture have been undertaken in developed countries. The purpose of this study was to measure the patient safety culture at a tertiary care hospital in Pakistan using the Hospital Survey on Patient Safety Culture (HSOPSC).MethodsThe HSOPSC was used to measure the patient safety culture across 12 dimensions at Aga Khan University Hospital, Karachi. 2,959 individuals, who had been working at the hospital, were administered the HSOPSC in paper form between June and September 2019.ResultsThe response rate of the survey was 50%. In the past 12 months, 979 respondents (33.1%) had submitted at least one event report. Results showed that the personnel viewed the patient safety culture at their hospital favourably. Overall, respondents scored highest in the following dimensions: ‘feedback and communication on error’ (91%), ‘organisational learning and continuous improvement’ (85%), ‘teamwork within units’ (83%), ‘teamwork across units’ (76%). The dimensions with the lowest positive per cent scores included ‘staffing’ (40%) and ‘non-punitive response to error’ (41%). Only the reliability of the ‘handoffs and transitions’, ‘frequency of events reported’, ‘organisational learning’ and ‘teamwork within units’ was higher than Cronbach’s alpha of 0.7. Upon regression analysis of positive responses, physicians and nurses were found to have responded less favourably than the remaining professional groups for most dimensions.ConclusionThe measurement of safety culture is both feasible and informative in developing countries and could be broadly implemented to inform patient safety efforts. Current data suggest that it compares favourably with benchmarks from hospitals in the USA. Like the USA, high staff workload is a significant safety concern among staff. This study lays the foundation for further context-specific research on patient safety culture in developing countries.

Child malnutrition is considered one of the most focused areas of development, globally. The situation in developing countries, with lower literacy rate and lesser health awareness, is even more alarming and unpleasant. Pakistan - a country of 220 million population with literacy rate of 65 percent, remains a prime candidate, worth studying the diverse nature of the issue. This research focuses on the analysis of Punjab based data – the most populated province of Pakistan, sharing 50 percent of the total population of the country. Principally, this research advances the existing literature mainly on two fronts. Firstly, we study children nourishment status through ordinal scale and thus identify the more vulnerable and priority groups existent in the population. Secondly, we propose the use of WHO Infant and Young Children Feeding guidelines (IYCF) for food quality, as a determinant of child nourishment status. Also, we consider weight-for-age, as a composite anthropometric indicator to quantify the nourishment status of children of age under five years. Based on this indicator, child nourishment status is then categorized into three distinctive and hierarchical groups: severely malnourished \((<- 3.0 \text{Z}-\text{s}\text{c}\text{o}\text{r}\text{e}\)), moderately malnourished (\(-3.0 \text{t}\text{o}-2.01 \text{Z}-\text{s}\text{c}\text{o}\text{r}\text{e}\)) and not malnourished (\(\ge 2.0 \text{Z} \text{s}\text{c}\text{o}\text{r}\text{e})\). The objectives are achieved by using the Multiple Indicator Cluster Survey (MICS) 2017–2018 data for the Punjab province comprehending a sample of 25211 children. We observe that 7% children can be ranked as severely malnourished whereas, 14.5% children stayed in the moderately malnourished category. Moreover, bivariate analysis reveals statistically significant association between children nourishment status and, food intake diversity, mother education and health awareness, child previous health history and economic status of the household. The explanatory power of the determinants of malnourishment is assessed by employing various modeling strategies capable of entertaining diverse ordinal structures. We use proportional odds model (POM), non-proportional odds model (NPOM). Based on keen application of statistical modeling techniques, our study suggests that NPOM can be considered as a more sophisticated approach to explore the factors affecting the child malnutrition. The findings of this research imply that, government and development organizations need to focus, not only, on improvement of overall household well-being but also required to advocate the urgency for balanced food.