Explore the vast range of titles available.

AbstractObjectiveTo determine whether electronic health record alerts for acute kidney injury would improve patient outcomes of mortality, dialysis, and progression of acute kidney injury.DesignDouble blinded, multicenter, parallel, randomized controlled trial.SettingSix hospitals (four teaching and two non-teaching) in the Yale New Haven Health System in Connecticut and Rhode Island, US, ranging from small community hospitals to large tertiary care centers.Participants6030 adult inpatients with acute kidney injury, as defined by the Kidney Disease: Improving Global Outcomes (KDIGO) creatinine criteria.InterventionsAn electronic health record based “pop-up” alert for acute kidney injury with an associated acute kidney injury order set upon provider opening of the patient’s medical record.Main outcome measuresA composite of progression of acute kidney injury, receipt of dialysis, or death within 14 days of randomization. Prespecified secondary outcomes included outcomes at each hospital and frequency of various care practices for acute kidney injury.Results6030 patients were randomized over 22 months. The primary outcome occurred in 653 (21.3%) of 3059 patients with an alert and in 622 (20.9%) of 2971 patients receiving usual care (relative risk 1.02, 95% confidence interval 0.93 to 1.13, P=0.67). Analysis by each hospital showed worse outcomes in the two non-teaching hospitals (n=765, 13%), where alerts were associated with a higher risk of the primary outcome (relative risk 1.49, 95% confidence interval 1.12 to 1.98, P=0.006). More deaths occurred at these centers (15.6% in the alert group v 8.6% in the usual care group, P=0.003). Certain acute kidney injury care practices were increased in the alert group but did not appear to mediate these outcomes.ConclusionsAlerts did not reduce the risk of our primary outcome among patients in hospital with acute kidney injury. The heterogeneity of effect across clinical centers should lead to a re-evaluation of existing alerting systems for acute kidney injury.Trial registrationClinicalTrials.gov NCT02753751.

IntroductionNational audits are used to monitor care quality and safety and are anticipated to reduce unexplained variations in quality by stimulating quality improvement (QI). However, variation within and between providers in the extent of engagement with national audits means that the potential for national audit data to inform QI is not being realised. This study will undertake a feasibility evaluation of QualDash, a quality dashboard designed to support clinical teams and managers to explore data from two national audits, the Myocardial Ischaemia National Audit Project (MINAP) and the Paediatric Intensive Care Audit Network (PICANet).Methods and analysisRealist evaluation, which involves building, testing and refining theories of how an intervention works, provides an overall framework for this feasibility study. Realist hypotheses that describe how, in what contexts, and why QualDash is expected to provide benefit will be tested across five hospitals. A controlled interrupted time series analysis, using key MINAP and PICANet measures, will provide preliminary evidence of the impact of QualDash, while ethnographic observations and interviews over 12 months will provide initial insight into contexts and mechanisms that lead to those impacts. Feasibility outcomes include the extent to which MINAP and PICANet data are used, data completeness in the audits, and the extent to which participants perceive QualDash to be useful and express the intention to continue using it after the study period.Ethics and disseminationThe study has been approved by the University of Leeds School of Healthcare Research Ethics Committee. Study results will provide an initial understanding of how, in what contexts, and why quality dashboards lead to improvements in care quality. These will be disseminated to academic audiences, study participants, hospital IT departments and national audits. If the results show a trial is feasible, we will disseminate the QualDash software through a stepped wedge cluster randomised trial.

Electronic Health Records: An Audit and Internal Control Guide describes the infrastructure of electronic health records and the impact that the government's new criteria will have on the private and public marketplace. Understand what to look for in a health care record management system and find tips and helpful guidance for implementation. If you are trying to facilitate an audit of a health record management system, you can apply the example described in the model, which will serve as a timely model and invaluable resource.

Context: The extensive research literature on electronic patient records (EPRs) presents challenges to systematic reviewers because it covers multiple research traditions with different underlying philosophical assumptions and methodological approaches. Methods: Using the meta-narrative method and searching beyond the Medline-indexed literature, this review used \"conflicting\" findings to address higher-order questions about how researchers had differently conceptualized and studied the EPR and its implementation. Findings: Twenty-four previous systematic reviews and ninety-four further primary studies were considered. Key tensions in the literature centered on (1) the EPR (\"container\" or \"itinerary\"); (2) the EPR user (\"information-processer\" or \"member of socio-technical network\"); (3) organizational context (\"the setting within which the EPR is implemented\" or \"the EPR-in-use\"); (4) clinical work (\"decision making\" or \"situated practice\"); (5) the process of change (\"the logic of determinism\" or \"the logic of opposition\"); (6) implementation success (\"objectively defined\" or \"socially negotiated\"); and (7) complexity and scale (\"the bigger the better\" or \"small is beautiful\"). Conclusions: The findings suggest that EPR use will always require human input to recontextualize knowledge; that even though secondary work (audit, research, billing) may be made more efficient by the EPR, primary clinical work may be made less efficient; that paper may offer a unique degree of ecological flexibility; and that smaller EPR systems may sometimes be more efficient and effective than larger ones. We suggest an agenda for further research.

ABSTRACT BACKGROUND Non-adherence to essential medications represents an important public health problem. Little is known about the frequency with which patients fail to fill prescriptions when new medications are started (“primary non-adherence”) or predictors of failure to fill. OBJECTIVE Evaluate primary non-adherence in community-based practices and identify predictors of non-adherence. PARTICIPANTS 75,589 patients treated by 1,217 prescribers in the first year of a community-based e-prescribing initiative. DESIGN We compiled all e-prescriptions written over a 12-month period and used filled claims to identify filled prescriptions. We calculated primary adherence and non-adherence rates for all e-prescriptions and for new medication starts and compared the rates across patient and medication characteristics. Using multivariable regressions analyses, we examined which characteristics were associated with non-adherence. MAIN MEASURES Primary medication non-adherence. KEY RESULTS Of 195,930 e-prescriptions, 151,837 (78%) were filled. Of 82,245 e-prescriptions for new medications, 58,984 (72%) were filled. Primary adherence rates were higher for prescriptions written by primary care specialists, especially pediatricians (84%). Patients aged 18 and younger filled prescriptions at the highest rate (87%). In multivariate analyses, medication class was the strongest predictor of adherence, and non-adherence was common for newly prescribed medications treating chronic conditions such as hypertension (28.4%), hyperlipidemia (28.2%), and diabetes (31.4%). CONCLUSIONS Many e-prescriptions were not filled. Previous studies of medication non-adherence failed to capture these prescriptions. Efforts to increase primary adherence could dramatically improve the effectiveness of medication therapy. Interventions that target specific medication classes may be most effective.

The 21st Century Cures Act requires that certified health IT products have an application programming interface that allows health data to be accessed and exchanged. The provision could shape the way that physicians and patients experience health care for years to come. Data generated as a by-product of the day-to-day work of delivery systems are a fundamental currency of the 21st Century Cures Act. How efficiently and effectively we use this “real-world” evidence will shape the way medicine is practiced and the way drugs are approved. 1 In 2009, the Health Information Technology for Economic and Clinical Health (HITECH) Act established an incentive payment program geared toward “meaningful use” of information technology (IT), which ultimately disbursed more than $34 billion for the promotion and purchase of electronic health records (EHRs). That federal investment was complemented by a substantially larger private investment by physicians . . .

Internet hospitals (IHs) have rapidly developed as a promising strategy to address supply-demand imbalances in China's medical industry, with their capabilities directly dependent on information platform functionality. Furthermore, a novel theory of \"Trinity\" smart hospital has provided advanced guidelines on IH constructions. This study aimed to explore the construction experience, construction models, and development prospects based on operational data from IHs. Based on existing information systems and internet service functionalities, our hospital has built a \"Smart Hospital Internet Information Platform (SHIIP)\" for IH operations, actively to expand online services, digitalize traditional health care, and explore health care services modes throughout the entire process and lifecycle. This article encompasses the platform architecture design, technological applications, patient service content and processes, health care professional support features, administrative management tools, and associated operational data. Our platform has presented a set of data, including 82,279,669 visits, 420,120 online medical consultations, 124,422 electronic prescriptions, 92,285 medication deliveries, 6,965,566 prediagnosis triages, 4,995,824 offline outpatient appointments, 2025 medical education articles with a total of 15,148,310 views, and so on. These data demonstrate the significant role of IH as an indispensable component of our physical hospital services, with deep integration between online and offline health care systems. The upward trends in various data metrics indicate that our IH has gained significant recognition and usage among both the public and healthcare workers, and may have promising development prospects. Additionally, the platform construction approach, which prioritizes comprehensive service digitization and the 'Trinity' of the public, healthcare workers, and managers, serves as an effective means of promoting the development of Internet Hospitals. Such insights may prove invaluable in guiding the development of IH and facilitating the continued evolution of the Internet healthcare sector.

Patients with chronic illness often receive care from multiple providers in multiple settings and require coordination of their complex care. This report assesses the quality of the coordination of care, describes barriers to coordinated care, and discusses some solutions to improve care coordination in the United States. Patients with chronic illness often receive care from multiple providers in multiple settings and require coordination of their complex care. This report assesses the quality of the coordination of care, describes barriers to coordinated care, and discusses some solutions to improve care coordination in the United States. In the United States, 125 million people are living with chronic illness, disability, or functional limitation. 1 The nature of modern medicine requires that these patients receive assistance from a number of different care providers. Between 2000 and 2002, the typical Medicare beneficiary saw a median of two primary care physicians and five specialists each year, in addition to accessing diagnostic, pharmacy, and other services. Patients with several chronic conditions may visit up to 16 physicians in a year. 2 Care among multiple providers must be coordinated to avoid wasteful duplication of diagnostic testing, perilous polypharmacy, and confusion about conflicting care plans. . . .

Emerging electronic health record models present numerous challenges to health care systems, physicians, and regulators. This article provides explanation of some of the reasons driving the development of the electronic health record, describes two national electronic health record models (currently developing in the United States and Australia) and one distributed, personal model. The US and Australian models are contrasted in their different architectures (\"pull\" versus \"push\") and their different approaches to patient autonomy, privacy, and confidentiality. The article also discusses some of the professional, practical, and legal challenges that health care providers potentially face both during and after electronic health record implementation.

Background Case registers have been used extensively in mental health research. Recent developments in electronic medical records, and in computer software to search and analyse these in anonymised format, have the potential to revolutionise this research tool. Methods We describe the development of the South London and Maudsley NHS Foundation Trust (SLAM) Biomedical Research Centre (BRC) Case Register Interactive Search tool (CRIS) which allows research-accessible datasets to be derived from SLAM, the largest provider of secondary mental healthcare in Europe. All clinical data, including free text, are available for analysis in the form of anonymised datasets. Development involved both the building of the system and setting in place the necessary security (with both functional and procedural elements). Results Descriptive data are presented for the Register database as of October 2008. The database at that point included 122,440 cases, 35,396 of whom were receiving active case management under the Care Programme Approach. In terms of gender and ethnicity, the database was reasonably representative of the source population. The most common assigned primary diagnoses were within the ICD mood disorders (n = 12,756) category followed by schizophrenia and related disorders (8158), substance misuse (7749), neuroses (7105) and organic disorders (6414). Conclusion The SLAM BRC Case Register represents a 'new generation' of this research design, built on a long-running system of fully electronic clinical records and allowing in-depth secondary analysis of both numerical, string and free text data, whilst preserving anonymity through technical and procedural safeguards.