Current Electronic Health Record Research Articles

Research on the current electronic health record data access at home and abroad

The open access of electronic health record(EHR) is an important link to promote the construction and application of EHR. Starting with the definition of open data of EHR, the authors discussed the content and form of open data of electronic health records, summarized the advanced experiences of countries with higher openness of EHR in the United States, the United Kingdom and Denmark. This paper combined the current situation that the opening of EHR in China is limited within data access instead of data utilization. It also pointed out such problems in the opening of EHR in China, as unclear data ownership, weak health awareness of residents and lack of unified construction standards.From the point of view of the state and medical institutions, this paper put forward a series of policy suggestions, such as issuing standards to standardize the opening of EHR, implementing patient real-name certification, realizing the overall opening of regional platforms, and linking the scope of application and supervision with the content of data opening. Key words: Electronic health records; Open data; Data access; Healthcare information technology

How well is the electronic health record supporting the clinical tasks of hospital physicians? A survey of physicians at three Norwegian hospitals

BackgroundThe electronic health record is expected to improve the quality and efficiency of health care. Many novel functionalities have been introduced in order to improve medical decision making and communication between health care personnel. There is however limited evidence on whether these new functionalities are useful. The aim of our study was to investigate how well the electronic health record system supports physicians in performing basic clinical tasks.MethodsPhysicians of three prominent Norwegian hospitals participated in the survey. They were asked, in an online questionnaire, how well the hospital’s electronic health record system DIPS supported 49 clinical tasks as well as how satisfied they were with the system in general, including the technical performance. Two hundred and eight of 402 physicians (52%) submitted a completely answered questionnaire.ResultsSeventy-two percent of the physicians had their work interrupted or delayed because the electronic health record hangs or crashes at least once a week, while 22% had experienced this problem daily. Fifty-three percent of the physicians indicated that the electronic health record is cumbersome to use and adds to their workload. The majority of physicians were satisfied with managing tests, e.g., requesting laboratory tests, reading test results and managing radiological investigations and electrocardiograms. Physicians were less satisfied with managing referrals. There was high satisfaction with some of the decision support functionalities available for prescribing drugs. This includes drug interaction alerts and drug allergy warnings, which are displayed automatically. However, physicians were less satisfied with other aspects of prescribing drugs, including getting an overview of the ongoing drug therapy.ConclusionsIn the survey physicians asked for improvements of certain electronic health record functionalities like medication, clinical workflow support including planning and better overviews. In addition, there is apparently a need to focus on system stability, number of logins, reliability and better instructions on available electronic health record features. Considerable development is needed in current electronic health record systems to improve usefulness and satisfaction.

The Association Between Perceived Electronic Health Record Usability and Professional Burnout Among US Physicians

ObjectiveTo describe and benchmark physician-perceived electronic health record (EHR) usability as defined by a standardized metric of technology usability and evaluate the association with professional burnout among physicians. Participants and MethodsThis cross-sectional survey of US physicians from all specialty disciplines was conducted between October 12, 2017, and March 15, 2018, using the American Medical Association Physician Masterfile. Among the 30,456 invited physicians, 5197 (17.1%) completed surveys. A random 25% (n=1250) of respondents in the primary survey received a subsurvey evaluating EHR usability, and 870 (69.6%) completed it. EHR usability was assessed using the System Usability Scale (SUS; range 0-100). SUS scores were normalized to percentile rankings across more than 1300 previous studies from other industries. Burnout was measured using the Maslach Burnout Inventory. ResultsMean ± SD SUS score was 45.9±21.9. A score of 45.9 is in the bottom 9% of scores across previous studies and categorized in the “not acceptable” range or with a grade of F. On multivariate analysis adjusting for age, sex, medical specialty, practice setting, hours worked, and number of nights on call weekly, physician-rated EHR usability was independently associated with the odds of burnout with each 1 point more favorable SUS score associated with a 3% lower odds of burnout (odds ratio, 0.97; 95% CI, 0.97-0.98; P<.001). ConclusionThe usability of current EHR systems received a grade of F by physician users when evaluated using a standardized metric of technology usability. A strong dose-response relationship between EHR usability and the odds of burnout was observed.

Digital Health and the State of Interoperable Electronic Health Records.

Digital health systems and innovative care delivery within these systems have great potential to improve national health care and positively impact the health outcomes of patients. However, currently, very few countries have systems that can implement digital interventions at scale. This is partly because of the lack of interoperable electronic health records (EHRs). It is difficult to make decisions for an individual or population when the data on that person or population are dispersed over multiple incompatible systems. This viewpoint paper has highlighted some key obstacles of current EHRs and some promising successes, with the goal of promoting EHR evolution and advocating for frameworks that develop digital health systems that serve populations—a critical goal as we move further into this data-rich century with an ever-increasing number of patients who live longer and depend on health care services where resources may already be strained. This paper aimed to analyze the evolution, obstacles, and current landscape of EHRs and identify fundamental areas of hindrance for interoperability. It also aimed to highlight countries where advances have been made and extract best practices from these examples. The obstacles to EHR interoperability are not easily solved, but improving the current situation in countries where a national policy is not in place will require a focused inquiry into solutions from various sources in the public and private sector. Effort must be made on a national scale to seek solutions for optimally interoperable EHRs beyond status quo solutions. A list of considerations for best practices is suggested.

Confidentiality and Consent in the Care of the Adolescent Patient.

1. Sofya Maslyanskaya, MD* 2. Elizabeth M. Alderman, MD* 1. *Division of Adolescent Medicine, Children's Hospital at Montefiore, and Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY * Abbreviations: CDC: : Centers for Disease Control and Prevention EHR: : electronic health record EOB: : explanation of benefits HIPAA: : Health Insurance Portability and Privacy Act HIV: : human immunodeficiency virus SAHM: : Society for Adolescent Health and Medicine STD: : sexually transmitted disease Confidentiality protections are critical in the provision of comprehensive primary care of adolescent patients. The protections differ based on state laws and are limited by electronic health record documentation and billing operations of individual physician practices. Physicians need to strive to increase their knowledge regarding confidentiality protections for their adolescent patients. Moreover, physicians should understand their role in preventing possible confidentiality breaches. After completing this article, readers should be able to: 1. Define confidentiality, its limitations, and reasons for developmentally appropriate confidentiality protections for adolescents. 2. Recognize confidentiality protections for adolescents provided by state and federal laws, including the Health Insurance Portability and Privacy Act privacy rule. 3. Explain minor consent laws. 4. Describe the limitations and advantages of the electronic health record in providing confidentiality protections. 5. Identify concerns and solutions related to billing for confidential services. A 16-year-old girl who has been your patient since birth presents to an appointment alone and requests testing for sexually transmitted diseases (STDs). She also does not want her parents to find out about this visit. How would you proceed? ### Confidentiality and Autonomy The provision of confidentiality and the ability of adolescents to consent for certain health concerns are the cornerstone of optimal adolescent health-care. (1) According to this tenet, information about an adolescent’s health-care is not disclosed without his or her permission. Assurance of confidentiality is important to protect the adolescent’s health and to safeguard public health. The major causes of morbidity and mortality in adolescents are due to risky behaviors such as sexual activity and alcohol and substance use, as well as unmet mental health needs. During the past 3 decades, research has supported the importance of the …

Development and Preliminary Evaluation of a Visual Annotation Tool to Rapidly Collect Expert-Annotated Weight Errors in Pediatric Growth Charts.

Patient weights can be entered incorrectly into electronic health record (EHR) systems. These weight errors can cause significant patient harm especially in pediatrics where weight-based dosing is pervasively used. Determining weight errors through manual chart reviews is impractical in busy clinics, and current EHR alerts are rudimentary. To address these issues, we seek to develop an advanced algorithm to detect weight errors using supervised machine learning techniques. The critical first step is to collect labelled weight errors for algorithm training. In this paper, we designed and preliminarily evaluated a visual annotation tool using Agile software development to achieve the goal of supporting the rapid collection of expert-annotated weight errors. The design was based on the fact that weight errors are infrequent and medical experts can easily spot potential errors. The results show positive user feedback and prepared us for the formal user-centered evaluation as the next step.

A blockchain‐based architecture for securing electronic health record systems

SummaryThis paper presents a blockchain‐based architecture for our current electronic health record (EHR) systems. Being built on top of existing databases maintained by health providers, the architecture implements a blockchain solution to ensure the integrity of data records and improve interoperability of the systems through tracking all events that happen to the data in the databases. In this proposed architecture, we also introduce a new incentive mechanism for the creation of new blocks on the blockchain. The architecture is independent of any specific blockchain platforms and open to further extensions; hence, it potentially fits in with other electronic record systems that require protection against data misuse.

PC-FACS

PC-FACS

Prediction of emergency department revisits using area-level social determinants of health measures and health information exchange information

IntroductionInteroperable health information technologies, like electronic health records (EHR) and health information exchange (HIE), provide greater access to patient information from across multiple organizations. Also, an increasing number of public data sources exist to describe social determinant of health factors. These data may help better inform risk prediction models, but the relative importance or value of these data has not been established. This study assessed the performance of different classes of information individually, and in combination, in predicting emergency department (ED) revisits. MethodsIn a sample of 279,611 adult ED encounters. We compared the performance of Two-Class Boosted Decision Trees machine learning algorithm using 5 classes of information: 1) social determinants of health measures only, 2) current visit EHR information only, 3) current and historical EHR information, 4) HIE information only, and 5) all available information combined. ResultsThe social determinants of health measure only model had the overall worst performance with an area under the curve AUC of 0.61. The model using all information classes together had the best performance (AUC = 0.732). The model using HIE information only performed better than all other single information class models. ConclusionsBroad information sources, which are reflective of patients’ reliance on multiple organizations for care, better support risk prediction modeling in the emergency department.

The Association between Hospital Ownership Type and Health Information Exchange in the Emergency Departments

Interoperable health information technologies, like electronic health records (EHR) and health information exchange (HIE), provide greater access to patient information from across multiple organizations. Also, an increasing number of public data sources exist to describe social determinant of health factors. These data may help better inform risk prediction models, but the relative importance or value of these data has not been established. This study assessed the performance of different classes of information individually, and in combination, in predicting emergency department (ED) revisits.In a sample of 279,611 adult ED encounters. We compared the performance of Two-Class Boosted Decision Trees machine learning algorithm using 5 classes of information: 1) social determinants of health measures only, 2) current visit EHR information only, 3) current and historical EHR information, 4) HIE information only, and 5) all available information combined.The social determinants of health measure only model had the overall worst performance with an area under the curve AUC of 0.61. The model using all information classes together had the best performance (AUC = 0.732). The model using HIE information only performed better than all other single information class models.Broad information sources, which are reflective of patients’ reliance on multiple organizations for care, better support risk prediction modeling in the emergency department.

Progress towards Companion Animal Zoonotic Disease Surveillance in the U.S. Army

ObjectiveWe assesed the feasibility of a zoonotic disease surveillance system through the current EHR (ROVR) for all POAs and GOAs. Additionally, we conducted a retrospective observational study querying and collecting reported zoonoses of interest, for 2017.IntroductionDogs, cats and other companion animals have played an integral role in many aspects of human life. Human and companion animal (CAs) interactions have a wide range of benefits to human health1–3. The threat of zoonotic transmission between CAs and humans is exacerbated by proximity (56% of dog owners and 62% of cat owners sleep with their animal next to them4) and the number of diseases CAs share with humans. Many of these highlighted zoonoses are spread by direct contact, and others are vector-transmitted (e.g., fleas, ticks, flies, and mosquitos). Within the realm of the One-Health concept, CAs can serve multiple roles in zoonotic transmission chains between humans and animals. They can serve as intermediate hosts between wildlife reservoirs and humans, or as possible sentinel or proxy species for emerging diseases5. Given the large number of CAs within the United States (estimated 72 million pet dogs, 81 million pet cats), understanding and preventing the diseases prevalent in CA populations is of utmost importance.Biosurveillance is a critical component of One Health initiatives including zoonotic disease mitigation and control. As Lead Service for Veterinary Animal and Public Health Services, the Army has a responsibility to champion biosurveillance efforts to support One Health initiatives, improving Servicemember, family, and retiree health across the Joint Force. Additionally, with military personnel experiencing apparent increased rates of job-reducing ailments such as diarrheal, bacterial and viral disease6–8, it is essential that the Army focus on maximizing their operational potential by minimizing the amount of time personnel are sick from these transmissible diseases and observing potential sources of infection. By observing the zoonotic disease burden in privately owned (POAs) and government-owned (GOAs) animals, public health investigators can increase focus on what transmittable diseases are at greatest risk of being spread from companion animals to military personnel.To address this potential source of infection, the Department of Defense (DoD) sought and continues to seek to establish a centralized and integrated veterinary zoonotic surveillance system to provide Commanders with a clear picture of disease burden9. With this assigned responsibility, the Army Veterinary Service (VS) seeks to centralize and enhance surveillance efforts through the Remote Online Veterinary Record (ROVR) Electronic Health Record (EHR), an enterprise web-based application to support the Army VS, accurately establishing a zoonotic epidemiological baseline and sustaining consistent future reporting.MethodsThrough a requested effort and proof of concept, the Army Public Health Center’s (APHC) One Health Division tested the feasibility of a zoonotic disease surveillance system through the current EHR (ROVR) for all POAs and GOAs. We obtained one year (2017) worth of zoonotic encounters of interest through ROVR, querying a population of roughly 202,000 animals (n=202,217). We conducted a retrospective observational study comparing reported zoonoses of interest between CA populations. Maximum Likelihood Estimations of frequency detailed comparisons of frequency and prevalence between GOAs and POAs, within the ROVR EHR. Additionally, we evaluated the accuracy of surveillance data queried, proposed potential metrics and dashboards for commanders and stakeholders to easily observe zoonotic burden of companion animals and developed potential courses of action for future tools, collaborations, and educational interventions.ResultsOf the 512 collected zoonotic encounters, Giardia and Hookworm were the two most prevalent zoonoses overall, with 4.23 and 5.43 cases per 10,000 outpatient visits (OPVs), respectively. We observed a significant differential frequency of Giardia and Hookworm between GOAs and POAs (63% (CI: 54.6-71.4) vs 12.7% (CI: 9.7-16.1) and 2.5% (CI: 0.1-5.9) vs 41.9% (CI: 37.1-46.8) of all queried zoonotic diseases of interest, respectively). In addition to back-end database and querying improvements, we suggested the development of an educational intervention based at Army First-Year Graduate Veterinary Education program (FYGVE) locations to emphasize the important benefits of capturing zoonotic diseases of interest correctly, early stages in the clinical experience. The intervention would focus on increasing accurate data capture with the ultimate goal of a phased regional rollout through education and collaboartive buy-in.ConclusionsFrom these results and recent CDC guidance of data-driven surveillance, we’ve proposed a phased surveillance development plan focused on systematic data collection, collaboration, and evaluation. Our idenfitied overexpressed zoonoses will focus our efforts on tracking Giardia and Hookworm through multi-year trends. This assessment and proof of concept allows for illumination of gaps and limitations within the Army VS to effectively track the zoonotic burden of GOA and POA populations. Our current and future work will look to close surveillance gaps and help identify potential routes of transmission from companion animals to humans.

Development of a computerized paediatric intensive care unit septic shock pathway: improving user experience

ABSTRACTThe purpose of this study was to understand the user experience with a computerized septic shock protocol relative to the workflow of Paediatric Intensive Care Unit clinicians. The need for data-driven, condition-specific, computerized protocols in the intensive care unit helps improve decision-making at the bedside. PICU clinicians were interviewed and given pre-and post-implementation surveys asking their opinions on the current PICU septic shock protocol, as well as the current electronic health record being used at [Paediatric Academic Medical Center]. User preferences guided adjustments toward improved usability of the septic shock protocol. Computerized Physician Order Entry, a critical component of the septic shock protocol, allows for more streamlined processes, more complete records, and more time to care for patients. This study revealed that although clinicians had an unfavorable view of the EHR in general, the computerized septic shock protocol was very well-received with an overall usability score of 82.

Neurology steering board effects change for a major electronic health record vendor.

Neurologists are among the least satisfied physicians with their current electronic health record (EHR), with many known pain points and great opportunities for improved tools and workflows. Improved EHR functionality can have major implications for patient care, physician efficiency, and prevention of burnout. We describe the advocacy of the American Academy of Neurology for improved EHR usability and the resultant formation and subsequent accomplishments of a Neurology Subspecialty Steering Board at 1 major EHR vendor (Epic).

Electronic but overly eclectic: Disciplined EHR data management is needed to automate MIPS reporting.

e18074 Background: Physician reimbursement for care delivered to Medicare beneficiaries fundamentally changed with the 2015 MACRA legislation, requiring eligible clinicians to report quality measures in the Merit-Based Incentive Payment System (MIPS). To determine whether structured data in electronic health records (EHRs) were adequate to report MIPS results, EHR data ingested by ASCO’s CancerLinQ (CLQ) was analyzed. Methods: Nineteen MIPS measures specified for medical oncology, including 8 shared by other specialties, were retrieved from qpp.cms.gov and systematically evaluated to determine data elements necessary to satisfy each measure. The existence of corresponding data fields and completion of these fields with clinical data was analyzed according to EHR implementation in de-identified and aggregated CLQ data. Results: Five clinician informaticists reviewed the 19 oncology MIPS measures, and identified a consensus list of 52 discrete EHR data elements (DEs) that would be needed. CLQ-processed data from 4 commercial EHR systems implemented at 47 CLQ practices found structured data fields for 84% (43 of 52) of the DE, but fewer than half (46%) of these fields were ever populated and only 32% (17 of 52) of DE were recorded for &gt; 20% of cases. Only 3-5 of 19 MIPS measures could be reliably reported based on data element availability by most practices in this sample set. There were minimal differences between the EHRs ability to encode MIPS DE. Elements most likely to be encoded were those for registration (birthdate, gender), billing (diagnosis, meds), vital signs and smoking status, while those seldom or never encoded related to care plans (tobacco, alcohol, pain management). Other DE rarely encoded were patient events occurring outside the oncology practice (receipt/completion of consultations, dates of hospice enrollment and death), which would be dependent on data exchange between work units and practice entities or, more likely, re-entry by oncology practices. Conclusions: Only a minority of DE required to satisfy MIPS criteria are available as discrete data fields in current EHRs, limiting automated reporting efforts. Improved data quality and completeness is needed to satisfy mandated reporting.

Association of the Usability of Electronic Health Records With Cognitive Workload and Performance Levels Among Physicians

Current electronic health record (EHR) user interfaces are suboptimally designed and may be associated with excess cognitive workload and poor performance. To assess the association between the usability of an EHR system for the management of abnormal test results and physicians' cognitive workload and performance levels. This quality improvement study was conducted in a simulated EHR environment. From April 1, 2016, to December 23, 2016, residents and fellows from a large academic institution were enrolled and allocated to use either a baseline EHR (n = 20) or an enhanced EHR (n = 18). Data analyses were conducted from January 9, 2017, to March 30, 2018. The EHR with enhanced usability segregated in a dedicated folder previously identified critical test results for patients who did not appear for a scheduled follow-up evaluation and provided policy-based decision support instructions for next steps. The baseline EHR displayed all patients with abnormal or critical test results in a general folder and provided no decision support instructions for next steps. Cognitive workload was quantified subjectively using NASA-Task Load Index and physiologically using blink rates. Performance was quantified according to the percentage of appropriately managed abnormal test results. Of the 38 participants, 25 (66%) were female. The 20 participants allocated to the baseline EHR compared with the 18 allocated to the enhanced EHR demonstrated statistically significantly higher cognitive workload as quantified by blink rate (mean [SD] blinks per minute, 16 [9] vs 24 [7]; blink rate, -8 [95% CI, -13 to -2]; P = .01). The baseline group showed statistically significantly poorer performance compared with the enhanced group who appropriately managed 16% more abnormal test results (mean [SD] performance, 68% [19%] vs 98% [18%]; performance rate, -30% [95% CI, -40% to -20%]; P < .001). Relatively basic usability enhancements to the EHR system appear to be associated with better physician cognitive workload and performance; this finding suggests that next-generation systems should strip away non-value-added EHR interactions, which may help physicians eliminate the need to develop their own suboptimal workflows.

LSTM Model for Prediction of Heart Failure in Big Data.

The combination of big data and deep learning is a world-shattering technology that can make a great impact on any industry if used in a proper way. With the availability of large volume of health care datasets and progressions in deep learning techniques, systems are now well equipped in diagnosing many health problems. Utilizing the intensity of substantial historical information in electronic health record (EHR), we built up, a conventional predictive temporal model utilizing recurrent neural systems (RNN) like LSTM and connected to longitudinal time stepped EHR. Experience records were contribution to RNN to anticipate the analysis and prescription classes for a resulting visit during heart disappointment (e.g. diagnosis codes, drug codes or method codes). In this paper, we also investigated whether use of deep learning to model temporal relations among events in electronic health records (EHRs) would enhance the model performance in predicting initial diagnosis of heart failure (HF) compared to some of the traditional methods that disregard temporality. By examining these time stamped EHRs, we could recognize the associations between various diagnosis occasions and finally predicate when a patient is being analyzed for a disease. In any case, it is hard to access the current EHR data straightforwardly, since almost all data are sparse and not standardized. Along these lines, we proposed a robust model for prediction of heart failure. The fundamental commitment of this paper is to predict the failure of heart by means of a neural network model based on patient's electronic medicinal information. In order to, demonstrate the diagnosis events and prediction of heart failure, we used the medical concept vectors and the essential standards of a long short-term memory (LSTM) deep network model. The proposed LSTM model uses SiLU and tanh as activation function in the hidden layers and Softmax in output layer in the network. Bridgeout is used as a regularization technique for weight optimization throughout the network. Assessments subject to the real-time data exhibit the favorable effectiveness and feasibility of recommended model in the risk of heart failure prediction. The results showed improved accuracy in heart failure detection and the model performance is compared using the existing deep learning models. Enhanced prior detection could expose novel chances for deferring or anticipating movement to analysis of heart failure and diminish cost.

Oncologists' Views Regarding the Role of Electronic Health Records in Care Coordination.

Electronic health records (EHRs) play a significant role in complex health care processes, especially in information transfer with patients and care coordination among providers. EHRs may also generate unintended consequences, introducing new patient safety risks. To date, little investigation has been performed in oncology settings, despite the need for quality provider-patient communication and information transfer during oncology visits. In this qualitative study, we focused on oncology providers' perceptions of EHRs for supporting communication with patients and coordination of care with other providers. We conducted semistructured interviews with oncologists from an urban academic medical center to learn their perceptions of the use of EHRs before, during, and after clinic visits with patients. Our interview guide was developed on the basis of the work system model. We coded transcripts using inductive content analysis. Data analysis yielded four main themes regarding oncologists' practices in using the EHR and perceptions about EHRs: (1) EHR use for care coordination (eg, timeliness of receiving information, SmartSet documentation); (2) EHR use in the clinic visit (eg, educating patients, using as a reinforcement tool); (3) safety hazards in care coordination associated with EHRs (eg, incomplete documentation, error propagating, no filtering mechanism to capture errors); and (4) suggestions for improvements (eg, improved SmartSet functionalities, simplification of user interface). Current EHRs do not adequately support teamwork of oncology providers, which could lead to potential hazards in the care of patients with cancer. Redesigning EHR features that are tailored to support oncology care and addressing the concerns regarding information overload, improved organization of flagging abnormal results, and documentation-related workload are needed to minimize potential safety hazards.

Healthcare professionals’ experiences of interprofessional collaboration during palliative patients’ transfer of care setting: a focus group study

Introduction: Transferring palliative patients between care settings hospital, hospital’s palliative care unit, home and nursing home, is challenging and often hampers integrated care. These transfers are common due to the complexity of palliative care, demographic changes increased prevalence of multimorbidity and higher life expectancy and social changes more people living alone. As a result, transfers require efficient and effective collaboration in order to provide good quality of care. This study is part of a larger research project on integrated care for palliative patients, in a regional palliative care network in Belgium. The study aim was: - to explore healthcare professionals’ experiences of interprofessional collaboration - to explore their perceived factors influencing the continuity of care during palliative patients’ transfer of care setting. Methods: Nine focus group discussions were held, with various professionals GPs, nurses, specialists, psychologists, dieticians, social workers, coordinators. N: 53 from different palliative care settings. Constant comparative analysis was used. Results: Knowing each other personally positively influenced the interprofessional collaboration. Perceptions of hierarchy negatively influenced the interprofessional collaboration, within and between the settings. Timely and sufficient information flow between all professionals involved was considered fundamental. A perceived barrier for interprofessional collaboration was the lack of a shared electronic health record. Efficient multi-disciplinary team meetings with shared care goals were regarded essential, though often lacking. Participants reported that specialists informed the patients on disease stage and prognosis late and insufficiently. This hampered open communication on end-of-life decisions and impeded a timely transfer to the home situation or the palliative care unit. The complexity of patient’s case interfered with the hospitalization length and timely organizing optimal home care the moment of discharge. When transfer to a nursing home was deemed necessary, waiting lists negatively influenced the continuity of care Discussion: Our research shows that several clinical, organisational and service aspects of care at micro-, meso- and macro-level can be improved. At micro-level: insufficient open and timely communication towards the patient, hampers other healthcare professionals’ involvement. Together with absence of shared care goals, this negatively influences a timely referral to other settings. At meso-level: the current electronic health record system does not provide enough opportunities to share and exchange information for professionals involved, within and between the different care settings. At macro-level: continuity of care is hampered when appropriate supply of services lack: e.g., when referral to a nursing home is needed. Conclusions and lessons learned: Doctors should be trained more in bad news delivery and shared decision making. Interprofessional education modules may enhance collaboration and the discussing of shared care goals. Policy makers should invest in sufficient supply of palliative care services and the development of an electronic health record system to provide efficient and effective information transfers between settings. Limitations: We focused on only 1 palliative care network, therefor we are careful to generalize our results. Suggestions for future research: Interventions aiming to improve integrated care within the region will be evaluated.

Clinical Challenges and Opportunities With Current Electronic Health Records: Practicing Oncologists' Perspective.

Clinical Challenges and Opportunities With Current Electronic Health Records: Practicing Oncologists' Perspective.

A Call to Action for Optimizing the Electronic Health Record in the Parenteral Nutrition Workflow: Executive Summary

Parenteral nutrition (PN) is a complex therapeutic modality provided to neonates, children, and adults for various indications. Surveys have shown that current electronic health record (EHR) systems are in need of functionality enhancement for safe and optimal delivery of PN. This is a consensus statement from the American Society for Parenteral and Enteral Nutrition, the Academy of Nutrition and Dietetics, and the American Society of Health-System Pharmacists outlining some of the key challenges to prescribing, order review/verification, compounding, and administration of PN using EHRs today and is a call to action for clinicians and vendors to optimize their EHRs regarding the PN build and workflow.