Addressing the Quality and Safety Gap Part I: Case Studies in Transforming Hospital Nursing and Building Cultures of Safety

Presents case studies of strategies four healthcare systems and a state government are using to address underlying causes in flawed systems: strengthening care processes, optimizing staffing, and promoting safe work habits. Lists policy recommendations

The costs of preventing and treating chagas disease in Colombia

Background: The objective of this study is to report the costs of Chagas disease in Colombia, in terms of vector disease control programmes and the costs of providing care to chronic Chagas disease patients with cardiomyopathy. Methods: Data were collected from Colombia in 2004. A retrospective review of costs for vector control programmes carried out in rural areas included 3,084 houses surveyed for infestation with triatomine bugs and 3,305 houses sprayed with insecticide. A total of 63 patient records from 3 different hospitals were selected for a retrospective review of resource use. Consensus methodology with local experts was used to estimate care seeking behaviour and to complement observed data on utilisation. Findings: The mean cost per house per entomological survey was $4.4 (in US$ of 2004), whereas the mean cost of spraying a house with insecticide was $27. The main cost driver of spraying was the price of the insecticide, which varied greatly. Treatment of a chronic Chagas disease patient costs between$46.4 and $7,981 per year in Colombia, depending on severity and the level of care used. Combining cost and utilisation estimates the expected cost of treatment per patient-year is$1,028, whereas lifetime costs averaged $11,619 per patient. Chronic Chagas disease patients have limited access to healthcare, with an estimated 22% of patients never seeking care. Conclusion: Chagas disease is a preventable condition that affects mostly poor populations living in rural areas. The mean costs of surveying houses for infestation and spraying infested houses were low in comparison to other studies and in line with treatment costs. Care seeking behaviour and the type of insurance affiliation seem to play a role in the facilities and type of care that patients use, thus raising concerns about equitable access to care. Preventing Chagas disease in Colombia would be cost-effective and could contribute to prevent inequalities in health and healthcare.Wellcome Trus

How effective are incident reporting systems for improving patient safety? A systematic literature review

Context: Incident reporting systems (IRSs) are used to gather information on patient safety incidents. However, and despite the financial burden they imply, little is known about their effectiveness. This paper reviews systematically the effectiveness of IRSs as a method of improving patient safety through organizational learning. Method: This systematic literature review identified two groups of studies: a) studies comparing the effectiveness of IRSs relative to other methods of error reporting and b) studies examining the effectiveness of IRSs on settings, structures and outcomes in respect of improvements to patient safety. We used thematic analysis to compare the effectiveness of IRSs with other methods and to synthesize what was effective, where and why. Then, to assess the evidence concerning the ability of IRSs to facilitate organizational learning, we analyzed studies using the concepts of single loop and double loop learning. Findings: In total, 43 studies were identified. Eight studies compared IRSs with other methods, while 35 explored the effectiveness of IRSs on settings, structures and outcomes. We did not find strong evidence that IRSs perform better than other methods. We found some evidence of single loop learning, that is, changes to clinical settings or processes as a consequence of learning from IRSs, but little evidence either of improvements to outcomes or of changes to latent managerial factors involved in error production. In addition, there was insubstantial evidence of IRSs enabling double loop learning that is, cultural change or change of mindset. Conclusions: The results indicate IRSs could be more effective if there were explicit criteria for what counts as an incident; they are owned and led by clinical teams rather than centralized hospital departments; and embedded within organizations as part of wider safety programs

A framework for enhancing the query and medical record representations for patient search

Electronic medical records (EMRs) are digital documents stored by medical institutions that detail the observed symptoms, the conducted diagnostic tests, the identified diagnoses and the prescribed treatments. These EMRs are being increasingly used worldwide to improve healthcare services. For example, when a doctor compiles the possible treatments for a patient showing some particular symptoms, it is advantageous to consult the information about patients who were previously treated for those same symptoms. However, finding patients with particular medical conditions is challenging, due to the implicit knowledge inherent within the patients' medical records and queries - such knowledge may be known by medical practitioners, but may be hidden from an information retrieval (IR) system. For instance, the mention of a treatment such as a drug may indicate to a practitioner that a particular diagnosis has been made for the patient, but this diagnosis may not be explicitly mentioned in the patient's medical records. Moreover, the use of negated language (e.g.\ `without', `no') to describe a medical condition of a patient (e.g.\ the patient has no fever) may cause a search system to erroneously retrieve that patient for a query when searching for patients with that medical condition (e.g.\ find patients with fever). This thesis focuses on enhancing the search of EMRs, with the aim of identifying patients with medical histories relevant to the medical conditions stated in a text query. During retrieval, a healthcare practitioner indicates a number of inclusion criteria describing the medical conditions of the patients of interest. To attain effective retrieval performance, we hypothesise that, in a patient search system, both the information needs and patients' histories should be represented based upon \emph{the medical decision process}. In particular, this thesis argues that since the medical decision process typically encompasses four aspects (symptom, diagnostic test, diagnosis and treatment), a patient search system should take into account these aspects and apply inferences to recover the possible implicit knowledge. We postulate that considering these aspects and their derived implicit knowledge at three different levels of the retrieval process (namely, sentence, medical record and inter-record levels) enhances the retrieval performance. Indeed, we propose a novel framework that can gain insights from EMRs and queries, by modelling and reasoning upon information during retrieval in terms of the four aforementioned aspects at the three levels of the retrieval process, and can use these insights to enhance patient search. Firstly, at the sentence level, we extract the medical conditions in the medical records and queries. In particular, we propose to represent only the medical conditions related to the four medical aspects in order to improve the accuracy of our search system. In addition, we identify the context (negative/positive) of terms, which leads to an accurate representation of the medical conditions both in the EMRs and queries. In particular, we aim to prevent patients whose EMRs state the medical conditions in the contexts different from the query from being ranked highly. For example, preventing patients whose EMRs state ``no history of dementia'' from being retrieved for a query searching for patients with dementia. Secondly, at the medical record level, using external knowledge-based resources (e.g.\ ontologies and health-related websites), we leverage the relationships between medical terms to infer the wider medical history of the patient in terms of the four medical aspects. In particular, we estimate the relevance of a patient to the query by exploiting association rules that we extract from the semantic relationships between medical terms using the four aspects of the medical process. For example, patients with a medical history involving a \emph{CABG surgery} (treatment) can be inferred as relevant to a query searching for a patient suffering from \emph{heart disease} (diagnosis), since a CABG surgery is a treatment of heart disease. Thirdly, at the inter-record level, we enhance the retrieval of patients in two different manners. First, we exploit knowledge about how the four medical aspects are handled by different hospital departments to gain a better understanding about the appropriateness of EMRs created by different departments for a given query. We propose to aggregate EMRs at the department level (i.e.\ inter-record level) to extract implicit knowledge (i.e.\ the expertise of each department) and model this department's expertise, while ranking patients. For instance, patients having EMRs from the cardiology department are likely to be relevant to a query searching for patients who suffered from a heart attack. Second, as a medical query typically contains several medical conditions that the relevant patients should satisfy, we propose to explicitly model the relevance towards multiple query medical conditions in the EMRs related to a particular patient during retrieval. In particular, we rank highly those patients that match all the stated medical conditions in the query by adapting coverage-based diversification approaches originally proposed for the web search domain. Finally, we examine the combination of our aforementioned approaches that exploit the implicit knowledge at the three levels of the retrieval process to further improve the retrieval performance by adapting techniques from the fields of data fusion and machine learning. In particular, data fusion techniques, such as CombSUM and CombMNZ, are used to combine the relevance scores computed by the different approaches of the proposed framework. On the other hand, we deploy state-of-the-art learning to rank approaches (e.g.\ LambdaMART and AdaRank) to learn from a set of training data an effective combination of the relevance scores computed by the approaches of the framework. In addition, we introduce a novel selective ranking approach that uses a classifier to effectively apply one of the approaches of the framework on a per-query basis. This thesis draws insights from a thorough evaluation and analysis of the proposed framework using a standard test collection provided by the TREC Medical Records track. The experimental results show the effectiveness of the framework. In particular, the results demonstrate the importance of dealing with the implicit knowledge in patient search by focusing on the medical decision criteria aspects at the three levels of the retrieval process

Triumph of hope over experience: learning from interventions to reduce avoidable hospital admissions identified through an Academic Health and Social Care Network.

BACKGROUND: Internationally health services are facing increasing demands due to new and more expensive health technologies and treatments, coupled with the needs of an ageing population. Reducing avoidable use of expensive secondary care services, especially high cost admissions where no procedure is carried out, has become a focus for the commissioners of healthcare. METHOD: We set out to identify, evaluate and share learning about interventions to reduce avoidable hospital admission across a regional Academic Health and Social Care Network (AHSN). We conducted a service evaluation identifying initiatives that had taken place across the AHSN. This comprised a literature review, case studies, and two workshops. RESULTS: We identified three types of intervention: pre-hospital; within the emergency department (ED); and post-admission evaluation of appropriateness. Pre-hospital interventions included the use of predictive modelling tools (PARR - Patients at risk of readmission and ACG - Adjusted Clinical Groups) sometimes supported by community matrons or virtual wards. GP-advisers and outreach nurses were employed within the ED. The principal post-hoc interventions were the audit of records in primary care or the application of the Appropriateness Evaluation Protocol (AEP) within the admission ward. Overall there was a shortage of independent evaluation and limited evidence that each intervention had an impact on rates of admission. CONCLUSIONS: Despite the frequency and cost of emergency admission there has been little independent evaluation of interventions to reduce avoidable admission. Commissioners of healthcare should consider interventions at all stages of the admission pathway, including regular audit, to ensure admission thresholds don't change

Is There an App for That? Electronic Health Records (EHRs) and a New Environment of Conflict Prevention and Resolution

Katsh discusses the new problems that are a consequence of a new technological environment in healthcare, one that has an array of elements that makes the emergence of disputes likely. Novel uses of technology have already addressed both the problem and its source in other contexts, such as e-commerce, where large numbers of transactions have generated large numbers of disputes. If technology-supported healthcare is to improve the field of medicine, a similar effort at dispute prevention and resolution will be necessary

The Effects of Cardiac Specialty Hospitals on the Cost and Quality of Medical Care

The recent rise of specialty hospitals -- typically for-profit firms that are at least partially owned by physicians -- has led to substantial debate about their effects on the cost and quality of care. Advocates of specialty hospitals claim they improve quality and lower cost; critics contend they concentrate on providing profitable procedures and attracting relatively healthy patients, leaving (predominantly nonprofit) general hospitals with a less-remunerative, sicker patient population. We find support for both sides of this debate. Markets experiencing entry by a cardiac specialty hospital have lower spending for cardiac care without significantly worse clinical outcomes. In markets with a specialty hospital, however, specialty hospitals tend to attract healthier patients and provide higher levels of intensive procedures than general hospitals.