The vast majority of the 300 000 pregnancy-related deaths every year occur in South Asia and sub-Saharan Africa. Increased access to quality antepartum and intrapartum care can reduce pregnancy-related morbidity and mortality worldwide. We used a population-based cross-sectional cohort design to: (1) examine the sociodemographic risk factors and structural barriers associated with pregnancy care-seeking and institutional delivery, and (2) investigate the influence of residential distance to the nearest primary health facility in a rural population in Mali.
A baseline household survey of Malian women aged 15–49 years was conducted between December 2016 and January 2017, and those who delivereda baby in the 5 years preceding the survey were included. This study leverages the baseline survey data from a cluster-randomised controlled trial to conduct a secondary analysis. The outcomes were percentage of women who received any antenatal care (ANC) and institutional delivery; total number of ANC visits; four or more ANC visits; first ANC visit in the first trimester.
Of the 8575 women in the study, two-thirds received any ANC in their last pregnancy, one in 10 had four or more ANC visits and among those that received any ANC, about one-quarter received it in the first trimester. For every kilometre increase in distance to the nearest facility, the likelihood of the outcomes reduced by 5 percentage points (0.95; 95% CI 0.91 to 0.98) for any ANC; 4 percentage points (0.96; 95% CI 0.94 to 0.98) for an additional ANC visit; 10 percentage points (0.90; 95% CI 0.86 to 0.95) for four or more ANC visits; 6 percentage points (0.94; 95% CI 0.94 to 0.98) for first ANC in the first trimester. In addition, there was a 35 percentage points (0.65; 95% CI 0.56 to 0.76) decrease in likelihood of institutional delivery if the residence was within 6.5 km to the nearest facility, beyond which there was no association with the place of delivery. We also found evidence of increase in likelihood of receiving any ANC care and its intensity increased with having some education or owning a business.
The findings suggest that education, occupation and distance are important determinants of pregnancy and delivery care in a rural Malian context.
Prescribing long-term opioid therapy is a nuanced clinical decision requiring careful consideration of risks versus benefits. Our goal is to understand patient, provider and context factors that impact the decision to prescribe opioids in patients with cancer.
We conducted a secondary analysis of the raw semistructured interview data gathered from 42 prescribers who participated in one of two aligned concurrent qualitative studies in the USA and Australia. We conducted a two-part analysis of the interview: first identifying all factors influencing long-term prescribing and second open coding-related content for themes.
Factors that influence long-term opioid prescribing for cancer-related pain clustered under three key domains (patient-related, provider-related and practice-related factors) each with several themes. Domain 1: Patient factors related to provider–patient continuity, patient personality, the patient’s social context and patient characteristics including racial/ethnic identity, housing and socioeconomic status. Domain 2: Provider-related factors centred around provider ‘personal experience and expertise’, training and time availability. Domain 3: Practice-related factors included healthcare interventions to promote safer opioid practices and accessibility of quality alternative pain therapies.
Despite the differences in the contexts of the two countries, providers consider similar patient, provider and practice-related factors when long-term prescribing opioids for patients with cancer. Some of these factors may be categorised as cognitive biases that may intersect in an already disadvantaged patient and exacerbate disparities in the treatment of their pain. A more systematic understanding of these factors and how they impact the quality of care can inform appropriate interventions.
Dynamic ambulance relocation means that the operators at a dispatch centre place an ambulance in a temporary location, with the goal of optimising coverage and response times in future medical emergencies. This study aimed to scope the current research on dynamic ambulance relocation.
A scoping review was conducted using a structured search in PubMed, Scopus and Web of Science. In total, 21 papers were included.
Most papers described research with experimental designs involving the use of mathematical models to calculate the optimal use and temporary relocations of ambulances. The models relied on several variables, including distances, locations of hospitals, demographic-geological data, estimation of new emergencies, emergency medical services (EMSs) working hours and other data. Some studies used historic ambulance dispatching data to develop models. Only one study reported a prospective, real-time evaluation of the models and the development of technical systems. No study reported on either positive or negative patient outcomes or real-life chain effects from the dynamic relocation of ambulances.
Current knowledge on dynamic relocation of ambulances is dominated by mathematical and technical support data that have calculated optimal locations of ambulance services based on response times and not patient outcomes. Conversely, knowledge of how patient outcomes and the working environment are affected by dynamic ambulance dispatching is lacking. This review has highlighted several gaps in the scientific coverage of the topic. The primary concern is the lack of studies reporting on patient outcomes, and the limited knowledge regarding several key factors, including the optimal use of ambulances in rural areas, turnaround times, domino effects and aspects of working environment for EMS personnel. Therefore, addressing these knowledge gaps is important in future studies.
To develop and psychometrically test the Patient-reported Experience Measure-Cancer (PREM-C), reflecting patients' perceptions of cancer care experiences according to the Institute of Medicine domains.
A three-phase cross-sectional survey was conducted.
Development, reliability and validity testing of the PREM-C measure was undertaken. Data collection included three phases: firstly (development) between October and November, 2015; secondly (psychometric testing), May 2016–June, 2017, and finally, (revision and psychometric testing) May 2019–March 2020.
The final PREM-C structure, created using the Institute of Medicine domains, was psychometrically sound with five factors identified in the Exploratory Factor Analysis, demonstrating internal reliability ranging from 0.8 to 0.9. Confirmatory Factor Analysis indicated the hypothesized model fitted well (Root mean square error of approximation = 0.076). External convergent and divergent validity was established with the PREM-C found to be moderately correlated with the Picker Patient Experience Questionnaire but weakly correlated with the WHOQoL-BREF.
The development and testing of the PREM-C demonstrated good fit as a clinically relevant measure of ambulatory cancer patients' experiences of care. To make meaningful changes to nursing practice and health services, patient experience measures such as the PREM-C might support staff to identify areas for service improvement.
Few reliable measures and less validated measures collect patients' perceptions of the quality of their healthcare provision. Rigorous psychometric testing of the newly developed PREM-C demonstrated good internal consistency, test–retest reliability, and external convergent and divergent validity. The PREM-C is a potentially relevant measure of cancer patients' experiences of care. It might be used to assess patient-centred care and guide safety and quality improvements in clinical settings. PREM-C use might inform service providers of experiences of care in their institution and inform policy and practice development. This measure is sufficiently generic, allowing potential use in other chronic disease populations.
This conduct of this study was supported by the participating patients of the hospital Cancer Outpatients Service.