Diagnostic error increases mortality and length of hospital stay in patients presenting through the emergency room

Background: Diagnostic errors occur frequently, especially in the emergency room. Estimates about the consequences of diagnostic error vary widely and little is known about the factors predicting error. Our objectives thus was to determine the rate of discrepancy between diagnoses at hospital admission and discharge in patients presenting through the emergency room, the discrepancies’ consequences, and factors predicting them. Methods: Prospective observational clinical study combined with a survey in a University-affiliated tertiary care hospital. Patients’ hospital discharge diagnosis was compared with the diagnosis at hospital admittance through the emergency room and classified as similar or discrepant according to a predefined scheme by two independent expert raters. Generalized linear mixed-effects models were used to estimate the effect of diagnostic discrepancy on mortality and length of hospital stay and to determine whether characteristics of patients, diagnosing physicians, and context predicted diagnostic discrepancy. Results: 755 consecutive patients (322 [42.7%] female; mean age 65.14 years) were included. The discharge diagnosis differed substantially from the admittance diagnosis in 12.3% of cases. Diagnostic discrepancy was associated with a longer hospital stay (mean 10.29 vs. 6.90 days; Cohen’s d 0.47; 95% confidence interval 0.26 to 0.70; P = 0.002) and increased patient mortality (8 (8.60%) vs. 25(3.78%); OR 2.40; 95% CI 1.05 to 5.5 P = 0.038). A factor available at admittance that predicted diagnostic discrepancy was the diagnosing physician’s assessment that the patient presented atypically for the diagnosis assigned (OR 3.04; 95% CI 1.33–6.96; P = 0.009). Conclusions: Diagnostic discrepancies are a relevant healthcare problem in patients admitted through the emergency room because they occur in every ninth patient and are associated with increased in-hospital mortality. Discrepancies are not readily predictable by fixed patient or physician characteristics; attention should focus on context

Safer clinical systems : interim report, August 2010

Safer Clinical Systems is the Health Foundation’s new five year programme of work to test and demonstrate ways to improve healthcare systems and processes, to develop safer systems that improve patient safety. It builds on learning from the Safer Patients Initiative (SPI) and models of system improvement from both healthcare and other industries. Learning from the SPI highlighted the need to take a clinical systems approach to improving safety. SPI highlighted that many hospitals struggle to implement improvement in clinical areas due to inherent problems with support mechanisms. Clinical processes and systems, rather than individuals, are often the contributors to breakdown in patient safety. The Safer Clinical Systems programme aimed to measure the reliability of clinical processes, identify defects within those processes, and identify the systems that result in those defects. Methods to improve system reliability were then to be tested and re-developed in order to reduce the risk of harm being caused to patients. Such system-level awareness should lead to improvements in other patient care pathways. The relationship between system reliability and actual harm is challenging to identify and measure. Specific, well-defined, small-scale processes have been used in other programmes, and system reliability has been shown to have a direct causal relationship with harm (e.g. care bundle compliance in an intensive care unit can reduce the incidence of ventilator-associated pneumonia). However, it has become evident that harm can be caused by a variety of factors over time; when working in broader, more complex and dynamic systems, change in outcome can be difficult to attribute to specific improvements and difficulties are also associated with relating evidence to resulting harm. The overall aim of Phase 1 of the Safer Clinical Systems programme was to demonstrate proof-of-concept that using a systems-based approach could contribute to improved patient safety. In Phase 1, experienced NHS teams from four locations worked together with expert advisers to co-design the Safer Clinical Systems programme

Physicians' Practice of Dispensing Medicines: A Qualitative Study

Objectives: The physical act of giving medication to patients to administer away from a health care setting, dispensing, is normally performed by pharmacists. Dispensing of medication by physicians is a neglected patient safety issue, and having observed considerable variation in practice, the lead author sought to explore this issue further. A literature review yielded zero articles pertaining to this, so an exploratory study was commenced. The qualitative arm, relating to junior physicians' experience of, and training in, dispensing, is reported here. Methods: Focus groups were conducted to explore the beliefs, ideas, and experiences of physicians-in-training pertaining to dispensing of medication. These were recorded and transcribed. The transcriptions were thematically analyzed using the grounded theory. Results: The emergency department was the most common site of dispensing. No formal training in dispensing had been received. Informal training was variable in content and utility. The physicians felt that dispensing was part of their role. Conclusions: Despite being expected to dispense, and the patient safety issues involved in giving drugs to patients to use at home, physicians do not feel that they have been trained to undertake this task. These findings from 1 hospital raise questions about thewider quality and safety of this practic

A pragmatics' view of patient identification.

Patient identification is a central safety critical aspect of healthcare work. Most healthcare activities require identification of patients by healthcare staff, often in connection with the use of patient records. Indeed, the increasing reliance on electronic systems makes the correct matching of patients with their records a keystone for patient safety. Most research on patient identification has been carried out in hospital settings. The aim was to investigate the process of identification of patients and their records in the context of a primary healthcare clinic

Effect of Mass Supplementation with Ready-to-Use Supplementary Food during an anticipated nutritional emergency

Previous studies have shown the benefits of ready-to-use supplementary food (RUSF) distribution in reducing the incidence and prevalence of severe acute malnutrition

A Process Modelling Framework Based on Point Interval Temporal Logic with an Application to Modelling Patient Flows

This thesis considers an application of a temporal theory to describe and model the patient journey in the hospital accident and emergency (A&E) department. The aim is to introduce a generic but dynamic method applied to any setting, including healthcare. Constructing a consistent process model can be instrumental in streamlining healthcare issues. Current process modelling techniques used in healthcare such as flowcharts, unified modelling language activity diagram (UML AD), and business process modelling notation (BPMN) are intuitive and imprecise. They cannot fully capture the complexities of the types of activities and the full extent of temporal constraints to an extent where one could reason about the flows. Formal approaches such as Petri have also been reviewed to investigate their applicability to the healthcare domain to model processes. Additionally, to schedule patient flows, current modelling standards do not offer any formal mechanism, so healthcare relies on critical path method (CPM) and program evaluation review technique (PERT), that also have limitations, i.e. finish-start barrier. It is imperative to specify the temporal constraints between the start and/or end of a process, e.g., the beginning of a process A precedes the start (or end) of a process B. However, these approaches failed to provide us with a mechanism for handling these temporal situations. If provided, a formal representation can assist in effective knowledge representation and quality enhancement concerning a process. Also, it would help in uncovering complexities of a system and assist in modelling it in a consistent way which is not possible with the existing modelling techniques. The above issues are addressed in this thesis by proposing a framework that would provide a knowledge base to model patient flows for accurate representation based on point interval temporal logic (PITL) that treats point and interval as primitives. These objects would constitute the knowledge base for the formal description of a system. With the aid of the inference mechanism of the temporal theory presented here, exhaustive temporal constraints derived from the proposed axiomatic system’ components serves as a knowledge base. The proposed methodological framework would adopt a model-theoretic approach in which a theory is developed and considered as a model while the corresponding instance is considered as its application. Using this approach would assist in identifying core components of the system and their precise operation representing a real-life domain deemed suitable to the process modelling issues specified in this thesis. Thus, I have evaluated the modelling standards for their most-used terminologies and constructs to identify their key components. It will also assist in the generalisation of the critical terms (of process modelling standards) based on their ontology. A set of generalised terms proposed would serve as an enumeration of the theory and subsume the core modelling elements of the process modelling standards. The catalogue presents a knowledge base for the business and healthcare domains, and its components are formally defined (semantics). Furthermore, a resolution theorem-proof is used to show the structural features of the theory (model) to establish it is sound and complete. After establishing that the theory is sound and complete, the next step is to provide the instantiation of the theory. This is achieved by mapping the core components of the theory to their corresponding instances. Additionally, a formal graphical tool termed as point graph (PG) is used to visualise the cases of the proposed axiomatic system. PG facilitates in modelling, and scheduling patient flows and enables analysing existing models for possible inaccuracies and inconsistencies supported by a reasoning mechanism based on PITL. Following that, a transformation is developed to map the core modelling components of the standards into the extended PG (PG*) based on the semantics presented by the axiomatic system. A real-life case (from the King’s College hospital accident and emergency (A&E) department’s trauma patient pathway) is considered to validate the framework. It is divided into three patient flows to depict the journey of a patient with significant trauma, arriving at A&E, undergoing a procedure and subsequently discharged. Their staff relied upon the UML-AD and BPMN to model the patient flows. An evaluation of their representation is presented to show the shortfalls of the modelling standards to model patient flows. The last step is to model these patient flows using the developed approach, which is supported by enhanced reasoning and scheduling

The 1983-84 Suspensions of EDB Under FIFRA and the 1989 Asbestos Ban and Phaseout Rule Under TSCA: Two Case Studies in EPA's Use of Science

This paper discusses EPA's acquisition and use of science in a decision under the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA): the 1983-84 suspensions of ethylene dibromide (EDB); and in a decision under the Toxic Substances Control Act (TSCA): the 1989 Asbestos Ban and Phaseout Rule. By requiring EPA to balance the risks and benefits of the commercial use of toxic substances, both statutes place considerable analytical burdens on the agency, though TSCA places a more substantial burden on EPA for acquiring science and demonstrating unreasonable risks. In the case of EDB, data produced outside EPA over which the agency had no control incited a public alarm. Because a senior EPA official had contaminated the agency's reservoir of public trust by cooking the scientific data to provide regulatory relief, EPA had no credibility to portray the health risks of EDB in an objective manner. In the case of asbestos, the reviewing court, despite its limited scientific capability and lack of political accountability, substituted its own science policy judgment for that of politically accountable decisionmakers of the more expert administrative agency. The court was arguably invited to do so, however, by the substantial evidentiary judicial review standard specified for TSCA by the legislature. Both cases illustrate the need for and difficulty of generating and considering scientific information regarding tradeoffs among risks in environmental regulatory decision-making.

Measuring adult mortality in developing countries : a review and assessment of methods

In most developing countries, data collection methods in the civil registration system and health services are woefully inadequate and methods for adjusting them apply only at the national level. The authors argue that the best way to collect data on adult mortality is probably to combine sample community based health reporting systems and singleround surveys in which respondents are asked about the survival of various relatives. The method's main limitation is that it provides rather broad, nonspecific measures of mortality - but these are adequate for allocation of resources, which is likely to be affected only by large differences.Health Monitoring&Evaluation,Demographics,Health Systems Development&Reform,Health Economics&Finance,Adolescent Health