Evaluation of the national nursing model and four nursing documentation systems in Finland--lessons learned and directions for the future

ObjectivesTo evaluate the feasibility of the national nursing model and usability of four widely used nursing documentation systems and to study their usefulness in multi-professional collaboration and information exchange.MethodsQualitative usability study methods were used, including the use of scenario walkthroughs, contextual inquiries, thematic interviews and inspection-based expert reviews in the users’ clinical contexts.ResultsThe nursing process model was shown to be feasible in nursing practice but the national nursing classification was considered too detailed, multi-layered and difficult to use and understand. The four evaluated nursing documentation systems had many usability problems which resulted in them being difficult to use and produced extra documentation workload. Generally, electronic nursing documentation improves patients’ and health professionals’ legal protection and makes nursing care more transparent; however, the documentation systems did not provide good support for multi-professional care and information exchange.ConclusionsNursing models should comply better with nursing practices and support nurses in patient care and interventions. An essential improvement in practice would be the use of specific templates that are easy to apply in specific situations with homogeneous patient groups. Collaborative care aspects and better utilization of information require that the nursing model is designed to support not just documentation but also information utilization.     

Impact of errors in paper-based and computerized diabetes management with decision support for hospitalized patients with type 2 diabetes. A post-hoc analysis of a before and after study

ObjectiveMost preventable adverse drug events and medication errors occur during medication ordering. Medication order entry and clinical decision support are available on paper or as computerized systems. In this post-hoc analysis we investigated frequency and clinical impact of blood glucose (BG) documentation- and user-related calculation errors as well as workflow deviations in diabetes management. We aimed to compare a paper-based protocol to a computerized medication management system combined with clinical workflow and decision support.MethodsSeventy-nine hospitalized patients with type 2 diabetes mellitus were treated with an algorithm driven basal-bolus insulin regimen. BG measurements, which were the basis for insulin dose calculations, were manually entered either into the paper-based workflow protocol (PaperG: 37 patients) or into GlucoTab^®—a mobile tablet PC based system (CompG: 42 patients). We used BG values from the laboratory information system as a reference. A workflow simulator was used to determine user calculation errors as well as workflow deviations and to estimate the effect of errors on insulin doses. The clinical impact of insulin dosing errors and workflow deviations on hypo- and hyperglycemia was investigated.ResultsThe BG documentation error rate was similar for PaperG (4.9%) and CompG group (4.0%). In PaperG group, 11.1% of manual insulin dose calculations were erroneous and the odds ratio (OR) of a hypoglycemic event following an insulin dosing error was 3.1 (95% CI: 1.4–6.8). The number of BG values influenced by insulin dosing errors was eightfold higher than in the CompG group. In the CompG group, workflow deviations occurred in 5.0% of the tasks which led to an increased likelihood of hyperglycemia, OR 2.2 (95% CI: 1.1–4.6).DiscussionManual insulin dose calculations were the major source of error and had a particularly strong influence on hypoglycemia. By using GlucoTab^®, user calculation errors were entirely excluded. The immediate availability and automated handling of BG values from medical devices directly at the point of care has a high potential to reduce errors. Computerized systems facilitate the safe use of more complex insulin dosing algorithms without compromising usability. In CompG group, missed or delayed tasks had a significant effect on hyperglycemia, while in PaperG group insufficient precision of documentation times limited analysis. The use of old BG measurements was clinically less relevant.ConclusionInsulin dosing errors and workflow deviations led to measurable changes in clinical outcome. Diabetes management systems including decision support should address nurses as well as physicians in a computerized way. Our analysis shows that such systems reduce the frequency of errors and therefore decrease the probability of hypo- and hyperglycemia.     

Regenstrief Institute's Medical Gopher: A next-generation homegrown electronic medical record system

ObjectiveRegenstrief Institute developed one of the seminal computerized order entry systems, the Medical Gopher, for implementation at Wishard Hospital nearly three decades ago. Wishard Hospital and Regenstrief remain committed to homegrown software development, and over the past 4 years we have fully rebuilt Gopher with an emphasis on usability, safety, leveraging open source technologies, and the advancement of biomedical informatics research. Our objective in this paper is to summarize the functionality of this new system and highlight its novel features.Materials and methodsApplying a user-centered design process, the new Gopher was built upon a rich-internet application framework using an agile development process. The system incorporates order entry, clinical documentation, result viewing, decision support, and clinical workflow. We have customized its use for the outpatient, inpatient, and emergency department settings.ResultsThe new Gopher is now in use by over 1100 users a day, including an average of 433 physicians caring for over 3600 patients daily. The system includes a wizard-like clinical workflow, dynamic multimedia alerts, and a familiar ‘e-commerce’-based interface for order entry. Clinical documentation is enhanced by real-time natural language processing and data review is supported by a rapid chart search feature.DiscussionAs one of the few remaining academically developed order entry systems, the Gopher has been designed both to improve patient care and to support next-generation informatics research. It has achieved rapid adoption within our health system and suggests continued viability for homegrown systems in settings of close collaboration between developers and providers.     

Integrating evidence into clinical information systems for nursing decision support

PURPOSE: To illustrate approaches for providing decision support for evidence-based nursing practice through integration of evidence into clinical information systems (CISs) with examples from our experience at Columbia University Medical Center. ORGANIZING CONSTRUCT: Examples are organized according to three types of decision support functions: information management, focusing attention, and patient-specific consultation. METHODS: Three decision support tools that are integrated into three types of CISs are discussed: (1) infobuttons that provide context-specific access to digital sources of evidence; (2) automated Fall-Injury Risk Assessment; and (3) personal digital assistant-based screening reminders, screening assessments, and tailored documentation templates for the identification and management of obesity, depression, and tobacco cessation. The informatics infrastructure for implementing these decision support tools is described from the perspective of components identified in the published literature. CONCLUSIONS: Efforts to facilitate application of evidence into nursing practice are unlikely to be successful unless the approaches used are integrated into the clinical workflow. Our approaches use a variety of informatics methods to integrate evidence into CISs as a mechanism for providing decision support for evidence-based practice in a manner consistent with nursing workflow.     

Toward the Design of Personalized Continuum Surgical Robots

Robot-assisted minimally invasive surgical systems enable procedures with reduced pain, recovery time, and scarring compared to traditional surgery. While these improvements benefit a large number of patients, safe access to diseased sites is not always possible for specialized patient groups, including pediatric patients, due to their anatomical differences. We propose a patient-specific design paradigm that leverages the surgeon’s expertise to design and fabricate robots based on preoperative medical images. The components of the patient-specific robot design process are a virtual reality design interface enabling the surgeon to design patient-specific tools, 3-D printing of these tools with a biodegradable polyester, and an actuation and control system for deployment. The designed robot is a concentric tube robot, a type of continuum robot constructed from precurved, elastic, nesting tubes. We demonstrate the overall patient-specific design workflow, from preoperative images to physical implementation, for an example clinical scenario: nonlinear renal access to a pediatric kidney. We also measure the system’s behavior as it is deployed through real and artificial tissue. System integration and successful benchtop experiments in ex vivo liver and in a phantom patient model demonstrate the feasibility of using a patient-specific design workflow to plan, fabricate, and deploy personalized, flexible continuum robots.     

PARAMO: A PARAllel predictive MOdeling platform for healthcare analytic research using electronic health records

ObjectiveHealthcare analytics research increasingly involves the construction of predictive models for disease targets across varying patient cohorts using electronic health records (EHRs). To facilitate this process, it is critical to support a pipeline of tasks: (1) cohort construction, (2) feature construction, (3) cross-validation, (4) feature selection, and (5) classification. To develop an appropriate model, it is necessary to compare and refine models derived from a diversity of cohorts, patient-specific features, and statistical frameworks. The goal of this work is to develop and evaluate a predictive modeling platform that can be used to simplify and expedite this process for health data.MethodsTo support this goal, we developed a PARAllel predictive MOdeling (PARAMO) platform which (1) constructs a dependency graph of tasks from specifications of predictive modeling pipelines, (2) schedules the tasks in a topological ordering of the graph, and (3) executes those tasks in parallel. We implemented this platform using Map-Reduce to enable independent tasks to run in parallel in a cluster computing environment. Different task scheduling preferences are also supported.ResultsWe assess the performance of PARAMO on various workloads using three datasets derived from the EHR systems in place at Geisinger Health System and Vanderbilt University Medical Center and an anonymous longitudinal claims database. We demonstrate significant gains in computational efficiency against a standard approach. In particular, PARAMO can build 800 different models on a 300,000 patient data set in 3 h in parallel compared to 9 days if running sequentially.ConclusionThis work demonstrates that an efficient parallel predictive modeling platform can be developed for EHR data. This platform can facilitate large-scale modeling endeavors and speed-up the research workflow and reuse of health information. This platform is only a first step and provides the foundation for our ultimate goal of building analytic pipelines that are specialized for health data researchers.     

“Lost in translation”: The challenges of seamless integration in nursing practices

PurposeTo explore and characterize how the implementation and use of an electronic nursing module supports the care process, the interrelation of interdisciplinary documentation and the role of redundant information in the interplay between technology and clinical practice.MethodA qualitative case study was carried out at a surgical ward and a post-anesthesia care unit (PACU). A mixed method of data collection was used, including semi-structured interviews, observation and document analysis.ResultsThe study revealed that the electronic care plan was used in daily practice, and international nursing classifications were extensively used. However, the study also illustrates a gap between nurse-specific documentation (care plans) and other sources of information used in the documentation of the care process, such as the medication sheet, medical chart, and a custom-designed medical chart used by the post-anesthesia care unit (PACU). Moreover, the study also highlights how redundant information can serve as a “glue” in the socio-technical network to facilitate information sharing and coordination across domain-specific boundaries.ConclusionDifferentiating between negative and positive redundancy provides increased understanding of how the correlation of supplementary information has a role in the integration between work processes and computer systems. Coordination and pragmatic redundancies are emphasized to inform the further design and implementation of process-based electronic patient records (EPR).     

Electronic health records implementation: An evaluation of information system impact and contingency factors

ObjectiveThis paper provides a review of EHR (electronic health record) implementations around the world and reports on findings including benefits and issues associated with EHR implementation.Materials and methodsA systematic literature review was conducted from peer-reviewed scholarly journal publications from the last 10 years (2001–2011). The search was conducted using various publication collections including: Scopus, Embase, Informit, Medline, Proquest Health and Medical Complete. This paper reports on our analysis of previous empirical studies of EHR implementations. We analysed data based on an extension of DeLone and McLean's information system (IS) evaluation framework. The extended framework integrates DeLone and McLean's dimensions, including information quality, system quality, service quality, intention of use and usage, user satisfaction and net benefits, together with contingent dimensions, including systems development, implementation attributes and organisational aspects, as identified by Van der Meijden and colleagues.ResultsA mix of evidence-based positive and negative impacts of EHR was found across different evaluation dimensions. In addition, a number of contingent factors were found to contribute to successful implementation of EHR.LimitationsThis review does not include white papers or industry surveys, non-English papers, or those published outside the review time period.ConclusionThis review confirms the potential of this technology to aid patient care and clinical documentation; for example, in improved documentation quality, increased administration efficiency, as well as better quality, safety and coordination of care. Common negative impacts include changes to workflow and work disruption. Mixed observations were found on EHR quality, adoption and satisfaction. The review warns future implementers of EHR to carefully undertake the technology implementation exercise. The review also informs healthcare providers of contingent factors that potentially affect EHR development and implementation in an organisational setting. Our findings suggest a lack of socio-technical connectives between the clinician, the patient and the technology in developing and implementing EHR and future developments in patient-accessible EHR. In addition, a synthesis of DeLone and McLean's framework and Van der Meijden and colleagues’ contingent factors has been found useful in comprehensively understanding and evaluating EHR implementations.     

A comparative observational study of inpatient clinical note-entry and reading/retrieval styles adopted by physicians

ObjectiveThe objective of this study is to understand physicians’ usage of inpatient notes by (i) ascertaining different clinical note-entry and reading/retrieval styles in two different and widely used Electronic Health Record (EHR) systems, (ii) extrapolating potential factors leading to adoption of various note-entry and reading/retrieval styles and (iii) determining the amount of time to task associated with documenting different types of clinical notes.MethodsIn order to answer “what” and “why” questions on physicians’ adoption of certain-note-entry and reading/retrieval styles, an ethnographic study entailing Internal Medicine residents, with a mixed data analysis approach was performed. Participants were observed interacting with two different EHR systems in inpatient settings. Data was collected around the use and creation of History and Physical (H&P) notes, progress notes and discharge summaries.ResultsThe highest variability in template styles was observed with progress notes and the least variability was within discharge summaries, while note-writing styles were most consistent for H&P notes. The first sections to be read in a H&P and progress note were the Chief Complaint and Assessment & Plan sections, respectively. The greatest note retrieval variability, with respect to the order of how note sections were reviewed, was observed with H&P and progress notes. Physician preference for adopting a certain reading/retrieval order appeared to be a function of what best fits their workflow while fulfilling the stimulus demands. The time spent entering H&P, discharge summaries and progress notes were similar in both EHRs.ConclusionThis research study unveils existing variability in clinical documentation processes and provides us with important information that could help in designing a next generation EHR Graphical User Interface (GUI) that is more congruent with physicians’ mental models, task performance needs, and workflow requirements.     

Factors affecting physicians’ use of a dedicated overview interface in an electronic health record: The importance of standard information and standard documentation

BackgroundIt remains a continual challenge to present information in user interfaces in large IT systems to support overview in the best possible way. We here examine how an electronic health record (EHR) supports the creation of overview among hospital physicians with a particular focus on the use of an interface designed to provide clinicians with a patient information overview. The overview interface integrates information flexibly from diverse places in the EHR and presents this information in one screen display. Our study revealed widespread non-use of the overview interface. We explore the reasons for its use and non-use.MethodWe conducted exploratory ethnographic fieldwork among physicians in two hospitals and gathered statistical data on their use of the overview interface. From the quantitative data, we identified where the interface was used most and conducted 18 semi-structured, open-ended interviews framed by the theoretical framework and the findings of the initial ethnographic fieldwork. We interviewed both physicians and employees from the IT units in different hospitals. We then analysed notes from the ethnographic fieldwork and the interviews and ordered these into themes forming the basis for the presentation of findings.ResultsThe overview interface was most used in departments or situations where the problem at hand and the need for information could be standardized—in particular, in anesthesiological departments and outpatient clinics. However, departments with complex and long patient histories did not make much use of the overview interface. Design and layout were not mentioned as decisive factors affecting its use or non-use. Many physicians questioned the completeness of data in the overview interface—either because they were skeptical about the hospital’s or the department’s documentation practices, or because they could not recognize the structure of the interface. This uncertainty discouraged physicians from using the overview interface.ConclusionDedicating a specific function or interface to supporting overview works best where information needs can be standardized. The narrative and contextual nature of creating clinical overview is unlikely to be optimally supported by using the overview interface alone. The use of these kinds of interfaces requires trust in data completeness and other clinicians' and administrative staff's documentation practices, as well as an understanding of the underlying structure of the EHR and how information is filtered when data are aggregated for the interface.     

Countering imbalanced datasets to improve adverse drug event predictive models in labor and delivery

BackgroundThe IOM report, Preventing Medication Errors, emphasizes the overall lack of knowledge of the incidence of adverse drug events (ADE). Operating rooms, emergency departments and intensive care units are known to have a higher incidence of ADE. Labor and delivery (L&;D) is an emergency care unit that could have an increased risk of ADE, where reported rates remain low and under-reporting is suspected. Risk factor identification with electronic pattern recognition techniques could improve ADE detection rates.ObjectiveThe objective of the present study is to apply Synthetic Minority Over Sampling Technique (SMOTE) as an enhanced sampling method in a sparse dataset to generate prediction models to identify ADE in women admitted for labor and delivery based on patient risk factors and comorbidities.ResultsBy creating synthetic cases with the SMOTE algorithm and using a 10-fold cross-validation technique, we demonstrated improved performance of the Naïve Bayes and the decision tree algorithms. The true positive rate (TPR) of 0.32 in the raw dataset increased to 0.67 in the 800% over-sampled dataset.ConclusionEnhanced performance from classification algorithms can be attained with the use of synthetic minority class oversampling techniques in sparse clinical datasets. Predictive models created in this manner can be used to develop evidence based ADE monitoring systems.     

The effects of EMR deployment on doctors' work practices: a qualitative study in the emergency department of a teaching hospital

ObjectiveThe goal of this study was to examine the effects of medical notes (MD) in an electronic medical records (EMR) system on doctors’ work practices at an Emergency Department (ED).MethodsWe conducted a six-month qualitative study, including in situ field observations and semi-structured interviews, in an ED affiliated with a large teaching hospital during the time periods of before, after, and during the paper-to-electronic transition of the rollout of an EMR system. Data were analyzed using open coding method and various visual representations of workflow diagrams.ResultsThe use of the EMR in the ED resulted in both direct and indirect effects on ED doctors’ work practices. It directly influenced the ED doctors’ documentation process: (i) increasing documentation time four to five fold, which in turn significantly increased the number of incomplete charts, (ii) obscuring the distinction between residents’ charting inputs and those of attendings, shifting more documentation responsibilities to the residents, and (iii) leading to the use of paper notes as documentation aids to transfer information from the patient bedside to the charting room. EMR use also had indirect consequences: it increased the cognitive burden of doctors, since they had to remember multiple patients’ data; it aggravated doctors’ multi-tasking due to flexibility in the system use allowing more interruptions; and it caused ED doctors’ work to become largely stationary in the charting room, which further contributed to reducing doctors’ time with patients and their interaction with nurses.DiscussionWe suggest three guidelines for designing future EMR systems to be used in teaching hospitals. First, the design of documentation tools in EMR needs to take into account what we called “note-intensive tasks” to support the collaborative nature of medical work. Second, it should clearly define roles and responsibilities. Lastly, the system should provide a balance between flexibility and interruption to better manage the complex nature of medical work and to facilitate necessary interactions among ED staff and patients in the work environment.     

REDLetr: Workflow and tools to support the migration of legacy clinical data capture systems to REDCap

ObjectiveA memory clinic at an academic medical center has relied on several ad hoc data capture systems including Microsoft Access and Excel for cognitive assessments over the last several years. However these solutions are challenging to maintain and limit the potential of hypothesis-driven or longitudinal research. REDCap, a secure web application based on PHP and MySQL, is a practical solution for improving data capture and organization. Here, we present a workflow and toolset to facilitate legacy data migration and real-time clinical research data collection into REDCap as well as challenges encountered.Materials and methodsLegacy data consisted of neuropsychological tests stored in over 4000 Excel workbooks. Functions for data extraction, norm scoring, converting to REDCap-compatible formats, accessing the REDCap API, and clinical report generation were developed and executed in Python.ResultsOver 400 unique data points for each workbook were migrated and integrated into our REDCap database. Moving forward, our REDCap-based system replaces the Excel-based data collection method as well as eases the integration into the standard clinical research workflow and Electronic Health Record.ConclusionIn the age of growing data, efficient organization and storage of clinical and research data is critical for advancing research and providing efficient patient care. We believe that the workflow and tools described in this work to promote legacy data integration as well as real time data collection into REDCap ultimately facilitate these goals.     

一种面向医疗安全的智能清单系统

安全清单是一种规范化诊疗行为的有效工具,在临床上日益受到重视。安全清单要求医务工作者在诊疗流程中的关键环节对任务的准备情况或完成情况按临床规范进行核对,从而保证医疗安全。但传统的安全清单难与临床工作流程集成,对病人缺乏针对性,并且缺乏信息系统支持,因而临床应用效果不佳。通过研究清单的计算机化表达方法,将安全清单分解为诊疗流程、清单表格、医学算法和辅助信息等4个层次的知识;设计一套执行机制,利用工作流引擎和规则引擎对这些知识进行执行,并在此基础上开发一套智能清单系统来实现此机制。通过一个心内科经皮冠状动脉介入治疗清单案例,对系统进行评估。该系统将清单细化成11个对应于流程中关键场景的清单,在恰当时机将清单推送给预定义的医护人员,从而使清单融入他们的诊疗工作。每个场景的清单都是由预定义的医学算法结合病人实际情况动态生成,从而确保清单的针对性。结果表明,这种方法可以有效支持智能清单的表达和执行,提供能够与诊疗流程集成的病人个体化清单,方便医护人员的使用。     

Description and comparison of quality of electronic versus paper-based resident admission forms in Australian aged care facilities

PurposeTo describe the paper-based and electronic formats of resident admission forms used in several aged care facilities in Australia and to compare the extent to which resident admission information was documented in paper-based and the electronic health records.MethodsRetrospective auditing and comparison of the documentation quality of paper-based and electronic resident admission forms were conducted. A checklist of admission data was qualitatively derived from different formats of the admission forms collected. Three measures were used to assess the quality of documentation of the admission forms, including completeness rate, comprehensiveness rate and frequency of documented data element. The associations between the number of items and their completeness and comprehensiveness rates were estimated at a general level and at each information category level.ResultsVarious paper-based and electronic formats of admission forms were collected, reflecting varying practice among the participant facilities. The overall completeness and comprehensiveness rates of the admission forms were poor, but were higher in the electronic health records than in the paper-based records (60% versus 56% and 40% versus 29% respectively, p < 0.01). There were differences in the overall completeness and comprehensiveness rates between the different formats of admission forms (p < 0.01). At each information category level, varying degrees of difference in the completeness and comprehensiveness rates were found between different form formats and between the paper-based and the electronic records. A negative association between the completeness rate and the number of items in a form was found at each information category level (p < 0.01), i.e., more data items designed in a form, the less likely that the items would be completely filled. However, the associations between the comprehensiveness rates and the number of items were highly positive at both overall and individual information category levels (p < 0.01), suggesting more items designed in a form, more information would be captured.ConclusionBetter quality of documentation in resident admission forms was identified in the electronic documentation systems than in previous paper-based systems, but still needs to be further improved in practice. The quality of documentation of resident admission data should be further analysed in relation to its specific content.     

Comparison of Electronic Health Record System Functionalities to support the patient recruitment process in clinical trials

ObjectivesReusing data from electronic health records for clinical and translational research and especially for patient recruitment has been tackled in a broader manner since about a decade. Most projects found in the literature however focus on standalone systems and proprietary implementations at one particular institution often for only one singular trial and no generic evaluation of EHR systems for their applicability to support the patient recruitment process does yet exist. Thus we sought to assess whether the current generation of EHR systems in Germany provides modules/tools, which can readily be applied for IT-supported patient recruitment scenarios.MethodsWe first analysed the EHR portfolio implemented at German University Hospitals and then selected 5 sites with five different EHR implementations covering all major commercial systems applied in German University Hospitals. Further, major functionalities required for patient recruitment support have been defined and the five sample EHRs and their standard tools have been compared to the major functionalities.ResultsIn our analysis of the site's hospital information system environments (with four commercial EHR systems and one self-developed system) we found that – even though no dedicated module for patient recruitment has been provided – most EHR products comprise generic tools such as workflow engines, querying capabilities, report generators and direct SQL-based database access which can be applied as query modules, screening lists and notification components for patient recruitment support. A major limitation of all current EHR products however is that they provide no dedicated data structures and functionalities for implementing and maintaining a local trial registry.ConclusionsAt the five sites with standard EHR tools the typical functionalities of the patient recruitment process could be mostly implemented. However, no EHR component is yet directly dedicated to support research requirements such as patient recruitment. We recommend for future developments that EHR customers and vendors focus much more on the provision of dedicated patient recruitment modules.     

Improving pathway compliance and clinician performance by using information technology

To deliver patient-specific advice at the time and place of a consultation is an important contribution to improving clinician performance. Using computer-based decision support on the basis of clinical pathways is a promising strategy to achieve this goal. Thereby integration of IT applications into the clinical workflow is a core precondition for success. User acceptance and usability play a critical role: additional effort has to be balanced with enough benefit for the users and interaction design and evaluation should be handled as an intertwined, continuous process. Experiences from routine use of an online surgical pathway at Marburg University Medical Center show that it is possible to successfully address this issue by seamlessly integrating patient-specific pathway recommendations with documentation tasks which have to be done anyway, by substantially reusing entered data to accelerate routine tasks (e.g. by automatically generating orders and reports), and by continuously and systematically monitoring pathway conformance and documentation quality.