The future state of clinical data capture and documentation: a report from AMIA's 2011 Policy Meeting

Lost in translation: Unveiling medical students' untold errors of medical history documentation

OBJECTIVE

The accurate documentation of a medical history interview is an important goal in medical education. As students' documentation of medical history interviews is mostly decentralised on the wards, a systematic assessment of documentation quality is missing. We therefore evaluated the extent of details missed in students' medical history reports in a standardised setting.

METHODS

In this prospective, observational study, 123 of 380 students (32.4%) participated in an Objective Structured Clinical Examination (OSCE) regarding history taking and documentation. Based on the interviews and nine deductively selected main categories, a categorical system was established using a summarising qualitative content analysis. The items in the transcripts (defined as ground truth) and in students' reports were labelled and assigned to the correct subcategory. The ground truth and students' reports were compared to quantify students' documentation completeness.

RESULTS

Next to the nine deductively selected main categories, 61 subcategories were defined. A total of 8943 items were labelled in the 123 interview transcripts (ground truth), compared with 5870 items labelled in students' reports (65.6% completeness of students' reports compared with ground truth). The main category personal details overlapped with 94.2% between students' report and ground truth in contrast to the main category with the highest discrepancy, allergy, with 41.1% overlap. Pertinent negative items and non-numerical quantifications were often missed.

CONCLUSIONS

Medical students show incomplete documentation of medical history interviews. Therefore, accurate documentation should be taught as an important goal in medical education.

Quantifying the advantages and acceptability of linking dialysis machines to an electronic medical record

AIM

To establish and quantify the time saved by redirecting nursing workload from recording and entering haemodynamic data during chronic dialysis sessions by linking dialysis machines directly to the electronic medical record.

METHODS

We developed a bespoke interface from the HL7 feed from the dialysis machines (largely Fresenius 5008) to our EMR system (Cerner). We quantified the time nurses spent with the patient, computer, dialysis machine and sorting our patient related issues by observation using independent observers in a time and motion study. We performed these observations before and after implementation of the computer interface. We established patient and nursing acceptance by survey. We established adequacy of observations by counting the number of patients who received the minimum number of observations recorded in the system before and after implementation.

RESULTS

Implementation of a dialysis machine direct EMR interface reduced the time the nurses spent with the computer significantly by ∼9 % (around 28 min, p < 0.05) per dialysis shift, and this was accompanied by a similar increase in time spent sorting out patient-related issues. The interface was well accepted by staff and patients. An immediate benefit was a ∼60 % improvement in the adequacy of recording vital signs in our dialysis patients. Then simply by showing these results to the nursing staff there was further improvement.

CONCLUSIONS

In these days of machine interconnectivity there is really no good reason why dialysis nurses should be used to transfer data between machines. It is far better to utilise their skills in helping patients with their medical issues. We have shown that such a link improves efficiency, patient and staff satisfaction and dialysis governance.

Lessons learned from examination of Canadian medico-legal cases related to interventional therapies for chronic pain management

PURPOSE

Chronic pain is a common condition affecting almost one in five Canadians. One of the methods used to treat chronic pain is injection therapies. While they are considered relatively safe procedures, they do carry inherent risk that can result in adverse events. Our goal was to investigate these patient safety events to identify themes that could be used to shape practice guidelines and standards and improve patient safety.

METHODS

We looked at closed civil legal actions and regulatory college complaints associated with injection therapies for chronic pain in the Canadian Medical Protection Association database from 2015 to 2019. Injury was defined as that arising from, or associated with, plans or actions taken during the provision of health care, rather than an underlying disease or injury.

RESULTS

Of the 91 cases identified, the most common reported complications were neurologic-related symptoms, injury, and infection. Fifty-eight percent (53/91) of patients experienced health care-related harm that had a negative effect on their health or quality of life. Peer experts were critical of the clinical care provided in 74% (67/91) of the cases. Provider-related (60%, 40/67), team-related (75%, 50/67), and system-related factors (21%, 14/67) were identified as contributing factors in these cases. Common examples of provider-related factors were deficiencies in clinical decision-making (48%, 19/40), failure to follow established procedures (43%, 17/40), and situational awareness (38%, 15/40). Common examples of team-related factors were deficiencies in medical record keeping (80%, 40/50) and communication breakdowns (56%, 28/50). All system-related factors were related to inadequate office procedures.

CONCLUSION

We recommend that clinicians conduct appropriate physical examinations, keep up-to-date with clinical standards, and ensure their documentation reflects their assessment, the patient's condition, and the treatment rationale.

A health terminological system for inherited retinal diseases: Content coverage evaluation and a proposed classification

PURPOSE

To present a classification of inherited retinal diseases (IRDs) and evaluate its content coverage in comparison with common standard terminology systems.

METHODS

In this comparative cross-sectional study, a panel of subject matter experts annotated a list of IRDs based on a comprehensive review of the literature. Then, they leveraged clinical terminologies from various reference sets including Unified Medical Language System (UMLS), Online Mendelian Inheritance in Man (OMIM), International Classification of Diseases (ICD-11), Systematized Nomenclature of Medicine (SNOMED-CT) and Orphanet Rare Disease Ontology (ORDO).

RESULTS

Initially, we generated a hierarchical classification of 62 IRD diagnosis concepts in six categories. Subsequently, the classification was extended to 164 IRD diagnoses after adding concepts from various standard terminologies. Finally, 158 concepts were selected to be classified into six categories and genetic subtypes of 412 cases were added to the related concepts. UMLS has the greatest content coverage of 90.51% followed respectively by SNOMED-CT (83.54%), ORDO (81.01%), OMIM (60.76%), and ICD-11 (60.13%). There were 53 IRD concepts (33.54%) that were covered by all five investigated systems. However, 2.53% of the IRD concepts in our classification were not covered by any of the standard terminologies.

CONCLUSIONS

This comprehensive classification system was established to organize IRD diseases based on phenotypic and genotypic specifications. It could potentially be used for IRD clinical documentation purposes and could also be considered a preliminary step forward to developing a more robust standard ontology for IRDs or updating available standard terminologies. In comparison, the greatest content coverage of our proposed classification was related to the UMLS Metathesaurus.

Early Performance of the Patients Over Paperwork Initiative among Family Medicine Physicians

OBJECTIVES

In 2019, the Centers for Medicare & Medicaid Services began implementing the Patients Over Paperwork (POP) initiative in response to clinicians reporting burdensome documentation regulations. To date, no study has evaluated how these policy changes have influenced documentation burden.

METHODS

Our data came from the electronic health records of an academic health system. Using quantile regression models, we assessed the association between the implementation of POP and clinical documentation word count using data from family medicine physicians in an academic health system from January 2017 to May 2021 inclusive. Studied quantiles included the 10th, 25th, 50th, 75th, and 90th quantiles. We controlled for patient-level (race/ethnicity, primary language, age, comorbidity burden), visit-level (primary payer, level of clinical decision making involved, whether a visit was done through telemedicine, whether a visit was for a new patient), and physician-level (sex) characteristics.

RESULTS

We found that the POP initiative was associated with lower word counts across all of the quantiles. In addition, we found lower word counts among notes for private payers and telemedicine visits. Conversely, higher word counts were observed in notes that were written by female physicians, notes for new patient visits, and notes involving patients with greater comorbidity burden.

CONCLUSIONS

Our initial evaluation suggests that documentation burden, as measured by word count, has declined over time, particularly following implementation of the POP in 2019. Additional research is needed to see whether the same occurs when examining other medical specialties, clinician types, and longer evaluation periods.

Merit-based incentive payment system participation and after-hours documentation among US office-based physicians: Findings from the 2021 National Electronic Health Records Survey

BACKGROUND

After-hours documentation burden among US clinicians is often uncompensated work and has been associated with burnout, leading health systems to identify root causes and seek interventions to reduce this. A few studies have suggested quality programme participation (e.g., Merit-Based Incentive Payment System [MIPS]) was associated with a higher administrative burden. However, the association between MIPS participation and after-hours documentation has not been fully explored. Thus, this study aims to assess whether participation in the MIPS programme was independently associated with after-hours documentation burden.

METHODS

We used 2021 data from the National Electronic Health Records Survey. We used a multivariable ordinal logistic regression model to assess whether MIPS participation was associated with the amount of after-hours documentation burden when controlling for other factors. We controlled for physician age, specialty, sex, number of practice locations, number of physicians, practice ownership, whether team support (e.g., scribes) is used for documentation tasks, and whether the practice accepts Medicaid patients.

RESULTS

We included 1801 office-based US physician respondents with complete data for variables of interest. After controlling for other factors, MIPS participation was associated with greater odds of spending a greater number of hours on after-hours documentation (odds ratio = 1.44, 95% confidence interval 1.06-1.95).

CONCLUSIONS

MIPS participation may increase after-hours documentation burden among US office-based physicians, suggesting that physicians may require additional resources to more efficiently report data.

Evolution - removing paper and digitising the hospital

Purpose

A transition from paper to Electronic Health Records has numerous benefits, including better communication and information exchange and decreased errors by medical staff. However, if managed poorly, it can result in frustration, causing errors in patient care and reduced patient-clinician interaction. Furthermore, a drop in staff morale and clinician burnout due to familiarising themselves with the technology has been mentioned in previous studies. Therefore, the aim of this project is to monitor the change in morale of staff of the Oral and Maxillofacial Department in a hospital which underwent the change in October 2020. Objectives: To observe staff morale during transition from paper to Electronic Health Records; to encourage feedback.

Methods

After carrying out a Patient & Public Involvement consultation and receiving local research and development approval, a questionnaire was distributed to all members of the maxillofacial outpatients department on a regular basis.

Results

On average, around 25 members responded to the questionnaire during each collection. There was a noticeable divergence in responses week on week according to job role and age, but minimal difference is noted from gender point of view after the first week. The study emphasised the position that not all members were happy with the new system but only a small minority would want to return to paper notes.

Conclusion

Staff members adapt to change at different rates, which are multifactorial in nature. A change of this scale should be monitored closely to allow for a smoother transition and ensure staff burnout is minimised.

An offline English optical character recognition and NER using LSTM and adaptive neuro-fuzzy inference system

Everything becomes smart in the modern era, for everything we need a better plan or arrangements. In the olden days, essential information was noted as a document with the help of paper and pen or printed texts. But the intelligent world needs a paperless environment by converting handwritten or printed text documents into software copies. This can be achieved by the electronic data conversion concept called Optical Character Recognition (OCR). OCR of some documents is complex because of different writing styles and quality of scanned image issues, which can be solved by adopting a deep learning technique for better accuracy. We employed Long Short Term Memory (LSTM) for English Optical Character Recognition for paperless and effortless data storage and fast access in this work. Still, the records may contain the entities like names, contact details, drug details, diseases, educational qualifications, dates, etc. These entities cannot be separated by employing OCR alone; we need an entity recognition framework for deeper and faster data analysis. For efficient Named Entity Recognition, we utilize the Adaptive Fuzzy Inference System (ANFIS) powered by the algorithms CRF and BERT to automatically labels each entity by training the vast amount of unlabeled text data. The ANFIS model is equipped with both linguistic and numerical knowledge. It is more accurate than the ANN when it comes to identifying patterns and classification data. Also, it is more transparent to the user. Our proposed framework aims to improve the performance of the character recognition system by using a feed-forward network. One of the main issues that have been identified in the development of this system is noise. Through this network, we can provide a single input and one output layer. The main components of the system are the training and recognition sections. These two sections are mainly focused on image acquisition and feature extraction. Besides these, they also include training and simulation of the classifier. The first step in the process of image recognition is to extract the features from the normalized image matrix. We then train the network using a proposed training algorithm. Experimentation on medical records attains a higher accuracy value of 0.9637, recall value of 0.9627, and f1 score of 0.9627, respectively.

Challenges in inpatient care coordinators’ clinical workflow and opportunities in designing a health IT solution: A mixed methods study

Introduction

Inpatient care coordinators (ICCs) in the United States play a critical role in case management and care transition. ICCs spend a large amount of time in chart review and documentation through electronic health record (EHR) systems. However, significant knowledge gaps exist regarding their workflow barriers and their use of health information technology (Health IT). Using only quantitative or quantitative methods does not provide a comprehensive picture about ICC’s workflow due to its complex and dynamic nature. This work aimed to address this gap by conducting a mixed-methods study to understand the workflow of ICCs and identifying challenges in care deliver and documentation activities.

Methods

The study adopted a concurrent triangulation design including qualitative interviews with 12 ICC staff members in the United States followed by extraction of their EHR event logs for one month. The qualitative interview data were analyzed thematically, and the log data were analyzed statistically. The results were triangulated and interpreted.

Results

Three major workflow barriers faced by ICCs were identified: long travel time, heavy documentation load, and suboptimal communication. The event logs provided empirical evidence to support the workflow barriers identified in the interviews, especially in travel time and documentation load.

Discussion

ICC workflow has several inefficiencies. The study generated four design considerations to develop a Health IT solution: Mobility, EHR integration, Team-based Communication, and User Adoption to improve workflow efficiency and care coordination. Using a mixed-methods approach is effective and efficient in collecting and analyzing clinical workflow.

The Impact of Structured and Standardized Documentation on Documentation Quality; a Multicenter, Retrospective Study

The reuse of healthcare data for various purposes will become increasingly important in the future. To enable the reuse of clinical data, structured and standardized documentation is conditional. However, the primary purpose of clinical documentation is to support high-quality patient care. Therefore, this study investigated the effect of increased structured and standardized documentation on the quality of notes in the Electronic Health Record. A multicenter, retrospective design was used to assess the difference in note quality between 144 unstructured and 144 structured notes. Independent reviewers measured note quality by scoring the notes with the Qnote instrument. This instrument rates all note elements independently using and results in a grand mean score on a 0–100 scale. The mean quality score for unstructured notes was 64.35 (95% CI 61.30–67.35). Structured and standardized documentation improved the Qnote quality score to 77.2 (95% CI 74.18–80.21), a 12.8 point difference (p < 0.001). Furthermore, results showed that structured notes were significantly longer than unstructured notes. Nevertheless, structured notes were more clear and concise. Structured documentation led to a significant increase in note quality. Moreover, considering the benefits of structured data recording in terms of data reuse, implementing structured and standardized documentation into the EHR is recommended.

A Practical Approach for Monitoring the Use of Copy-Paste in Clinical Notes

The use of copy-paste in authoring clinical notes has been widely embraced by busy providers, but inappropriate copy-paste has been lambasted by critics for introducing risks related to patient safety and regulatory compliance. At an integrated academic health system with over 4,100 providers writing notes, we developed a pragmatic approach to assess the use of copy-paste. From January 1-December 31, 2020, approximately 2.3M inpatient notes and 6.6M ambulatory clinic notes were authored in our electronic health record. Of the inpatient notes, 42% used copy-paste, and 19% of overall note content was copied; in ambulatory notes, 18% used copy-paste and 12% of note content was copied. We describe an approach for including providers' copy-paste usage statistics into the ongoing professional practice evaluation process required for hospital accreditation, thereby offering individual training opportunities related to the lack of use of copy-paste or its potential overuse.

Feeling and thinking: can theories of human motivation explain how EHR design impacts clinician burnout?

The psychology of motivation can help us understand the impact of electronic health records (EHRs) on clinician burnout both directly and indirectly. Informatics approaches to EHR usability tend to focus on the extrinsic motivation associated with successful completion of clearly defined tasks in clinical workflows. Intrinsic motivation, which includes the need for autonomy, sense-making, creativity, connectedness, and mastery is not well supported by current designs and workflows. This piece examines existing research on the importance of 3 psychological drives in relation to healthcare technology: goal-based decision-making, sense-making, and agency/autonomy. Because these motives are ubiquitous, foundational to human functioning, automatic, and unconscious, they may be overlooked in technological interventions. The results are increased cognitive load, emotional distress, and unfulfilling workplace environments. Ultimately, we hope to stimulate new research on EHR design focused on expanding functionality to support intrinsic motivation, which, in turn, would decrease burnout and improve care.

A retrospective look at the predictions and recommendations from the 2009 AMIA policy meeting: did we see EHR-related clinician burnout coming?

Clinicians often attribute much of their burnout experience to use of the electronic health record, the adoption of which was greatly accelerated by the Health Information Technology for Economic and Clinical Health Act of 2009. That same year, AMIA's Policy Meeting focused on possible unintended consequences associated with rapid implementation of electronic health records, generating 17 potential consequences and 15 recommendations to address them. At the 2020 annual meeting of the American College of Medical Informatics (ACMI), ACMI fellows participated in a modified Delphi process to assess the accuracy of the 2009 predictions and the response to the recommendations. Among the findings, the fellows concluded that the degree of clinician burnout and its contributing factors, such as increased documentation requirements, were significantly underestimated. Conversely, problems related to identify theft and fraud were overestimated. Only 3 of the 15 recommendations were adjudged more than half-addressed.

Standardisation, multi-measure, data quality and trending: A qualitative study on multidisciplinary perspectives to improve intensive care early mobility monitoring

OBJECTIVE

To explore multi-clinician perspectives on intensive care early mobility, monitoring and to assess the perceived value of technology-generated mobility metrics to provide user feedback to inform research, practice improvement, and technology development.

METHODS

We performed a qualitative descriptive study. Three focus groups were conducted with critical care clinicians, including nurses (n = 10), physical therapists (n = 8) and physicians (n = 8) at an academic medical centre that implemented an intensive care early mobility programme in 2012. Qualitative thematic analysis was used to code transcripts and identify overarching themes.

FINDINGS

Along with reaffirming the value of performing early mobility interventions, four themes for improving mobility monitoring emerged, including the need for: 1) standardised indicators for documenting mobility; 2) inclusion of both quantitative and qualitative metrics to measure mobility 3) a balance between quantity and quality of data; and 4) trending mobility metrics over time.

CONCLUSION

Intensive care mobility monitoring should be standardised and data generated should be high quality, capable of supporting trend analysis, and meaningful. By improving measurement and monitoring of mobility, future researchers can examine the arc of activity that patients in the intensive care unit undergo and develop models to understand factors that influence successful implementation.

Clinician Perspectives and Design Implications in Using Patient-Generated Health Data to Improve Mental Health Practices: Mixed Methods Study

Background

Patient-generated health data (PGHD) have been largely collected through mobile health (mHealth) apps and wearable devices. PGHD can be especially helpful in mental health, as patients’ illness history and symptom narratives are vital to developing diagnoses and treatment plans. However, the extent to which clinicians use mental health–related PGHD is unknown.

Objective

A mixed methods study was conducted to understand clinicians’ perspectives on PGHD and current mental health apps. This approach uses information gathered from semistructured interviews, workflow analysis, and user-written mental health app reviews to answer the following research questions: (1) What is the current workflow of mental health practice and how are PGHD integrated into this workflow, (2) what are clinicians’ perspectives on PGHD and how do they choose mobile apps for their patients, (3) and what are the features of current mobile apps in terms of interpreting and sharing PGHD?

Methods

The study consists of semistructured interviews with 12 psychiatrists and clinical psychologists from a large academic hospital. These interviews were thematically and qualitatively analyzed for common themes and workflow elements. User-posted reviews of 56 sleep and mood tracking apps were analyzed to understand app features in comparison with the information gathered from interviews.

Results

The results showed that PGHD have been part of the workflow, but its integration and use are not optimized. Mental health clinicians supported the use of PGHD but had concerns regarding data reliability and accuracy. They also identified challenges in selecting suitable apps for their patients. From the app review, it was discovered that mHealth apps had limited features to support personalization and collaborative care as well as data interpretation and sharing.

Conclusions

This study investigates clinicians’ perspectives on PGHD use and explored existing app features using the app review data in the mental health setting. A total of 3 design guidelines were generated: (1) improve data interpretation and sharing mechanisms, (2) consider clinical workflow and electronic health record integration, and (3) support personalized and collaborative care. More research is needed to demonstrate the best practices of PGHD use and to evaluate their effectiveness in improving patient outcomes.

A qualitative investigation into clinical documentation: why do clinicians document the way they do?

BACKGROUND

Clinical documentation is a fundamental component of patient care. The transition from paper based to electronic medical records/electronic health records has highlighted a number of issues associated with documentation practices including duplication. Developing new ways to document the care provided to patients and in turn, persuading clinicians to accept a change, must be supported by evidence that a change is required. In Australia, there has been a limited number of studies exploring the clinical documentation practices and beliefs of clinicians.

OBJECTIVE

To gain an in-depth understanding of clinician documentation practices.

METHOD

A qualitative design using semi-structured interviews with clinicians (allied health professionals, doctors (physicians) and nurses) working in a tertiary-level hospital in South-East Queensland, Australia.

RESULTS

Several themes emerged from the data: environmental factors, including departmental policy and systemic issues, and personal factors, including verification, clinical reasoning and experience influencing documentation practices.

CONCLUSION

Our study identified that the documentation practices of clinicians are complex, being driven by both environmental and systemic factors and personal factors. This in turn leads to duplication and some redundancy. The documentation burden of duplication could be reduced by changes in policy, supported by multidisciplinary documentation procedures and electronic systems aligned with clinician workflows, while retaining some flexible documentation practices. The documentation practices of individuals, when considered from the perspective of enhancing quality care, are considered legitimate and therefore will continue to form part of the health (medical) record regardless of the format.

Electronic Documentation in Pediatrics: The Rationale and Functionality Requirements

Clinical documentation is a fundamental component of the practice of medicine. It has significantly evolved over the past decade, largely because of the growth of health information technology and electronic health records. Although government agencies and other professional organizations have published position statements on the structure and use of electronic documentation, few have specifically addressed the documentation needs for the care of children. A policy statement on electronic documentation of clinical care by general pediatric and subspecialist providers by the American Academy of Pediatrics is needed. This statement provides insight on the unmet needs of key stakeholders to direct future research and development of the electronic media necessary to enhance the wellness of children and improve health care delivery. It also addresses the challenges and opportunities for efficient and effective clinical documentation in pediatrics.

Quantifying Mobility in the ICU: Comparison of Electronic Health Record Documentation and Accelerometer-Based Sensors to Clinician-Annotated Video

Supplemental Digital Content is available in the text.

To compare the accuracy of electronic health record clinician documentation and accelerometer-based sensors with a gold standard dataset derived from clinician-annotated video to quantify early mobility activities in adult ICU patients.

Clinical Documentation as End-User Programming

As healthcare providers have transitioned from paper to electronic health records they have gained access to increasingly sophisticated documentation aids such as custom note templates. However, little is known about how providers use these aids. To address this gap, we examine how 48 ophthalmologists and their staff create and use content-importing phrases - a customizable and composable form of note template - to document office visits across two years. In this case study, we find 1) content-importing phrases were used to document the vast majority of visits (95%), 2) most content imported by these phrases was structured data imported by data-links rather than boilerplate text, and 3) providers primarily used phrases they had created while staff largely used phrases created by other people. We conclude by discussing how framing clinical documentation as end-user programming can inform the design of electronic health records and other documentation systems mixing data and narrative text.

Assessing Anticoagulation Management and Shared Decision-Making Documentation From Providers Participating in the SUPPORT-AF II Study

BACKGROUND

A previously tested intervention featured educational outreach with modified academic detailing (AD) to increase anticoagulation use in patients with atrial fibrillation. Currently, this study compares providers receiving and not receiving AD in terms of inclusion of AD educational topics and shared decision-making elements in documentation.

METHODS

Physicians reviewed themes discussed with providers during AD and evaluated charts for evidence of shared decision-making. Frequencies of documentation of individual items for providers receiving AD versus non-AD providers were compared. To understand baseline documentation practices of AD providers, encounters of AD providers before their AD participation were randomly selected.

RESULTS

There were 113 eligible encounters in the four months after AD-36 from AD providers and 77 from non-AD providers. Thirty-five encounters were identified from AD providers before participating in the intervention. Providers infrequently documented many reviewed items (% documenting): anticoagulation mentioned (44%), multiple options for anticoagulation (5%), CHA2DS2-VASc score (11%), bleeding risk factors (2%). Compared with non-AD providers, AD providers had statistically significant higher percentages for the following items: mention of anticoagulation (64% versus 35%), stroke risk (11% versus 0%), anticoagulation benefits (8% versus 0%), and patient involvement (17% versus 0%). There was no improvement, however, for AD providers compared with baseline documentation percentages.

DISCUSSION

Providers infrequently documented important items in anticoagulation management and shared decision-making. AD participation did not improve documentation. Improving adoption of AD educational items may require more prolonged interaction with providers. Improving shared decision-making may require an intervention more focused on it and its documentation.

Impact of problem-based charting on the utilization and accuracy of the electronic problem list

Objective

Problem-based charting (PBC) is a method for clinician documentation in commercially available electronic medical record systems that integrates note writing and problem list management. We report the effect of PBC on problem list utilization and accuracy at an academic intensive care unit (ICU).

Materials and Methods

An interrupted time series design was used to assess the effect of PBC on problem list utilization, which is defined as the number of new problems added to the problem list by clinicians per patient encounter, and of problem list accuracy, which was determined by calculating the recall and precision of the problem list in capturing 5 common ICU diagnoses.

Results

In total, 3650 and 4344 patient records were identified before and after PBC implementation at Stanford Hospital. An increase of 2.18 problems (>50% increase) in the mean number of new problems added to the problem list per patient encounter can be attributed to the initiation of PBC. There was a significant increase in recall attributed to the initiation of PBC for sepsis (β = 0.45, P < .001) and acute renal failure (β = 0.2, P = .007), but not for acute respiratory failure, pneumonia, or venous thromboembolism.

Discussion

The problem list is an underutilized component of the electronic medical record that can be a source of clinician-structured data representing the patient's clinical condition in real time. PBC is a readily available tool that can integrate problem list management into physician workflow.

Conclusion

PBC improved problem list utilization and accuracy at an academic ICU.

Unintended Consequences of Nationwide Electronic Health Record Adoption: Challenges and Opportunities in the Post-Meaningful Use Era

The US health system has recently achieved widespread adoption of electronic health record (EHR) systems, primarily driven by financial incentives provided by the Meaningful Use (MU) program. Although successful in promoting EHR adoption and use, the program, and other contributing factors, also produced important unintended consequences (UCs) with far-reaching implications for the US health system. Based on our own experiences from large health information technology (HIT) adoption projects and a collection of key studies in HIT evaluation, we discuss the most prominent UCs of MU: failed expectations, EHR market saturation, innovation vacuum, physician burnout, and data obfuscation. We identify challenges resulting from these UCs and provide recommendations for future research to empower the broader medical and informatics communities to realize the full potential of a now digitized health system. We believe that fixing these unanticipated effects will demand efforts from diverse players such as health care providers, administrators, HIT vendors, policy makers, informatics researchers, funding agencies, and outside developers; promotion of new business models; collaboration between academic medical centers and informatics research departments; and improved methods for evaluations of HIT.

Quantifying and Visualizing Nursing Flowsheet Documentation Burden in Acute and Critical Care

Documentation burden is a well-documented problem within healthcare, and improvement requires understanding of the scope and depth of the problem across domains. In this study we quantified documentation burden within EHR flowsheets, which are primarily used by nurses to document assessments and interventions. We found mean rates of 633-689 manual flowsheet data entries per 12-hour shift in the ICU and 631-875 manual flowsheet data entries per 12-hour shift in acute care, excluding device data. Automated streaming of device data only accounted for 5-20% of flowsheet data entries across our sample. Reported rates averaged to a nurse documenting 1 data point every 0.82-1.14 minutes, despite only a minimum data-set of required documentation. Increased automated device integration and novel approaches to decrease data capture burden (e.g., voice recognition), may increase nurses' available time for interpretation, annotation, and synthesis of patient data while also further advancing the richness of information within patient records.

Linking Pediatrics Patients and Nurses With the Pharmacy and Electronic Health Record System Through the Inpatient Television: A Novel Interactive Pain-Management Tool

OBJECTIVES

Implement a novel pain-management interface that is used to bring real-time, patient-reported pain assessments to the inpatient television and evaluate the impact of implementation on the pain-management clinical workflow, patient engagement, and nursing pain reassessments.

METHODS

We developed a pain-management tool interfacing 4 stand-alone technologies: a television-based, interactive patient care system; electronic health record system; nursing call system; and pharmacy inventory-management system. The workflow is triggered when pain medications are dispensed by sending an automatic pain assessment rating question via the patient's television at a predefined time. To measure the effects of implementation, we calculated patient and/or parent use rates and pain reassessment timely documentation rates. Data were extracted from the electronic health record for a period of 22 months and covered pre- and postimplementation.

RESULTS

A total of 56 931 patient records were identified during the study period, representing 2447 unique patients. In total, 608 parents and/or patients reported their pain through the tool. Use rates were 6.5% for responding to the pain rating prompt and 13.3% for the follow-up prompt, in which additional nonpharmacologic strategies to eliminate pain were offered. A modest increase was found in the mean timely documentation rates on the basis of nursing documentation standards (26.1% vs 32.8%, a percentage increase of 25.7%; P < .001) along with decreased median time to pain reassessment documentation (29 minutes versus 25 minutes, a percentage decrease of 13.8%; P < .001).

CONCLUSIONS

With this novel tool, we offer a potentially scalable approach in supporting the pain-management clinical workflow, integration of technologies, and promoting of patient and/or parent engagement in the inpatient setting.

Provider Adoption of Speech Recognition and its Impact on Satisfaction, Documentation Quality, Efficiency, and Cost in an Inpatient EHR

This study utilizes qualitative and quantitative methods to measure the adoption of speech recognition (SR) and its impact ON provider satisfaction, documentation quality, efficiency, and cost when used for clinical documentation within the electronic health record (EHR). Qualitative surveys gauged providers' expectations and experiences regarding documentation before and after SR implementation. A new methodology was developed to measure SR adoption as a proportion of total documentation volume. Quantitative data was collected from the EHR, medical transcription and SR solutions to measure SR adoption and cost savings. Study results revealed significant improvements in satisfaction, documentation quality, and efficiency among providers as a direct result of SR use. An improved provider experience correlated to an 81% reduction in monthly medical transcription costs, an increase from 20% to 77% in electronic clinical documentation adoption, and a 74% SR adoption rate.

Using a Bedside Interactive Technology to Solicit and Record Pediatric Pain Reassessments: Parent and Nursing Perspectives on a Novel Workflow

To measure the impact of a novel interactive inpatient pediatric pain management solution integrating our hospital's electronic health record system, the nurse communication phones, and the pharmacy dispensing system, we assessed parent and nurse perspectives on the tool's potential value, benefits, and challenges. A mixed-methods approach with survey instruments containing closed-ended and open-ended questions was administered to 30 parents and 59 nurses (66% and 23% response rate respectively). Overall, parents were more satisfied with the interactive technology experience (90%) compared to nurses (50%) with both indicating timely reassessments of pain being the most valuable feature. Qualitative analysis of nurses' responses yielded 6 themes for technology benefits and 12 for challenges. While patient-interactive technology solutions appear well-received particularly by parent end-users for pediatric hospital pain management, nurse training and interface improvements may result in higher efficacy, ultimately empowering patients/parents, promoting patient engagement and satisfaction.

Gap Analysis and Refinement Recommendations of Skin Alteration and Pressure Ulcer Enterprise Reference Models against Nursing Flowsheet Data Elements

Reference models are an essential instrument to provide structure and guidance in the creation and use of data elements within an organizations' electronic health record (EHR). Standardization of data elements is imperative to ensure clinical data is consistently and reliably captured for use in clinical documentation, care communication, and a variety of downstream data uses. Ongoing assessment and refinement of reference models and data elements are necessary to ascertain clinical data capture is applicable and inclusive across a variety of caregivers and domains. We performed a gap analysis on current state nursing data elements against two validated interprofessional reference models: skin alteration and pressure ulcer assessments. We present our findings along with recommendations for reference model refinements. We also highlight additional findings of inconsistencies and redundancies within data elements used for nursing documentation and highlight recommendations for improvement.

Two-year longitudinal assessment of physicians' perceptions after replacement of a longstanding homegrown electronic health record: does a J-curve of satisfaction really exist?

This report describes a 2-year prospective, longitudinal survey of attending physicians in 3 clinical areas (family medicine, general pediatrics, internal medicine) who experienced a transition from a homegrown electronic health record (EHR) to a vendor EHR. Participants were already highly familiar with using EHRs. Data were collected 1 month before and 3, 6, 13, and 25 months post implementation. Our primary goal was to determine if perceptions followed a J-curve pattern in which they initially dropped but eventually surpassed baseline measures. A J-curve was not found for any measures, including workflow, safety, communication, and satisfaction. Only the reminders and alerts measure dropped and then returned to baseline (U-curve); a few remained flatlined. Most dropped and remained below baseline (L-curve). The only measure that remained above baseline was documenting in the exam room with the patient. This study adds to the literature about current controversies surrounding EHR adoption and physician satisfaction.

Clinical Informatics Researcher's Desiderata for the Data Content of the Next Generation Electronic Health Record

OBJECTIVE

Clinical informatics researchers depend on the availability of high-quality data from the electronic health record (EHR) to design and implement new methods and systems for clinical practice and research. However, these data are frequently unavailable or present in a format that requires substantial revision. This article reports the results of a review of informatics literature published from 2010 to 2016 that addresses these issues by identifying categories of data content that might be included or revised in the EHR.

MATERIALS AND METHODS

We used an iterative review process on 1,215 biomedical informatics research articles. We placed them into generic categories, reviewed and refined the categories, and then assigned additional articles, for a total of three iterations.

RESULTS

Our process identified eight categories of data content issues: Adverse Events, Clinician Cognitive Processes, Data Standards Creation and Data Communication, Genomics, Medication List Data Capture, Patient Preferences, Patient-reported Data, and Phenotyping.

DISCUSSION

These categories summarize discussions in biomedical informatics literature that concern data content issues restricting clinical informatics research. These barriers to research result from data that are either absent from the EHR or are inadequate (e.g., in narrative text form) for the downstream applications of the data. In light of these categories, we discuss changes to EHR data storage that should be considered in the redesign of EHRs, to promote continued innovation in clinical informatics.

CONCLUSION

Based on published literature of clinical informaticians' reuse of EHR data, we characterize eight types of data content that, if included in the next generation of EHRs, would find immediate application in advanced informatics tools and techniques.

Crossing the health IT chasm: considerations and policy recommendations to overcome current challenges and enable value-based care

While great progress has been made in digitizing the US health care system, today's health information technology (IT) infrastructure remains largely a collection of systems that are not designed to support a transition to value-based care. In addition, the pursuit of value-based care, in which we deliver better care with better outcomes at lower cost, places new demands on the health care system that our IT infrastructure needs to be able to support. Provider organizations pursuing new models of health care delivery and payment are finding that their electronic systems lack the capabilities needed to succeed. The result is a chasm between the current health IT ecosystem and the health IT ecosystem that is desperately needed.In this paper, we identify a set of focal goals and associated near-term achievable actions that are critical to pursue in order to enable the health IT ecosystem to meet the acute needs of modern health care delivery. These ideas emerged from discussions that occurred during the 2015 American Medical Informatics Association Policy Invitational Meeting. To illustrate the chasm and motivate our recommendations, we created a vignette from the multistakeholder perspectives of a patient, his provider, and researchers/innovators. It describes an idealized scenario in which each stakeholder's needs are supported by an integrated health IT environment. We identify the gaps preventing such a reality today and present associated policy recommendations that serve as a blueprint for critical actions that would enable us to cross the current health IT chasm by leveraging systems and information to routinely deliver high-value care.

Identification of patients with congenital hemophilia in a large electronic health record database

BACKGROUND

Electronic health records (EHRs) are an important source of information with regard to diagnosis and treatment of rare health conditions, such as congenital hemophilia, a bleeding disorder characterized by deficiency of factor VIII (FVIII) or factor IX (FIX).

OBJECTIVE

To identify patients with congenital hemophilia using EHRs.

DESIGN

An EHR database study.

SETTING

EHRs were accessed from Humedica between January 1, 2007, and July 31, 2013.

PATIENTS

Selection criteria were applied for an initial ICD-9-CM diagnosis of 286.0 (hemophilia A) or 286.1 (hemophilia B), and confirmation of records 6 months before and 12 months after the first diagnosis. Additional selection criteria included mention of "hemophilia" and "blood" or "bleed" within physician notes identified via natural language processing.

RESULTS

A total of 129 males and 35 females were identified as the analysis population. Of those patients for whom both prothrombin time and activated partial thromboplastin time test results were available, only 56% of males and 7% of females exhibited a pattern of test results consistent with congenital hemophilia (normal prothrombin time and prolonged activated partial thromboplastin time). Few patients had a prescription for a hemophilia treatment; males most commonly received Amicar (10.8%) or FVIII (9.0%), whereas females most commonly received DDAVP (11.0%). The most identifiable sites of pain were the chest and the abdomen; 41% of males and 37% of females had joint pain. To evaluate whether patients had been correctly identified with congenital hemophilia, EHRs of 6 patients were reviewed; detailed assessment of their data was found to be inconsistent with a conclusive diagnosis of congenital hemophilia.

LIMITATIONS

Inconsistent coding practices may affect data integrity.

CONCLUSION

A potentially high number of false positive identifications, particularly among female patients, suggests that ICD-9-CM coding alone may be insufficient to identify patient cohorts. In-depth reviews and multimodal analysis of chart notes may improve data integrity.

Identification of people with acquired hemophilia in a large electronic health record database

Background

Electronic health records (EHRs) can provide insights into diagnoses, treatment patterns, and clinical outcomes. Acquired hemophilia (AH) is an ultrarare bleeding disorder characterized by factor VIII inhibiting autoantibodies.

Aim

To identify patients with AH using an EHR database.

Methods

Records were accessed from a large EHR database (Humedica) between January 1, 2007 and July 31, 2013. Broad selection criteria were applied using the International Classification of Diseases, Ninth Revision, clinical modification (ICD-9-CM) code for intrinsic circulating anticoagulants (286.5 and all subcodes) and confirmation of records 6 months before and 12 months after the first diagnosis. Additional selection criteria included mention of “bleeding” within physician notes identified via natural language processing output and a normal prothrombin time and prolonged activated partial thromboplastin time.

Results

Of 6,348 patients with a diagnosis code of 286.5 or any subcodes, 16 males and 15 females met the selection criteria. The most common bleeding locations reported was gastrointestinal (23%), vaginal (16%), and endocrine (13%). A wide range of comorbidities was reported. Natural language processing identified chart note mention of “hemophilia” in 3 patients (10%), “bruise” in 15 patients (48%), and “pain” in all 31 patients. No patients received a prescription for approved/recommended AH treatments. Four patient cases were reviewed to validate whether the identified cohort had AH; each patient had bleeding symptoms and a normal prothrombin time and prolonged activated partial thromboplastin time, although none received hemostatic treatments.

Conclusion

In ultrarare disorders, ICD-9-CM coding alone may be insufficient to identify patient cohorts; multimodal analysis combined with in-depth reviews of physician notes may be more effective.

Rapid Development of Specialty Population Registries and Quality Measures from Electronic Health Record Data*. An Agile Framework

BACKGROUND

Creation of a new electronic health record (EHR)-based registry often can be a "one-off" complex endeavor: first developing new EHR data collection and clinical decision support tools, followed by developing registry-specific data extractions from the EHR for analysis. Each development phase typically has its own long development and testing time, leading to a prolonged overall cycle time for delivering one functioning registry with companion reporting into production. The next registry request then starts from scratch. Such an approach will not scale to meet the emerging demand for specialty registries to support population health and value-based care.

OBJECTIVE

To determine if the creation of EHR-based specialty registries could be markedly accelerated by employing (a) a finite core set of EHR data collection principles and methods, (b) concurrent engineering of data extraction and data warehouse design using a common dimensional data model for all registries, and (c) agile development methods commonly employed in new product development.

METHODS

We adopted as guiding principles to (a) capture data as a byproduct of care of the patient, (b) reinforce optimal EHR use by clinicians, (c) employ a finite but robust set of EHR data capture tool types, and (d) leverage our existing technology toolkit. Registries were defined by a shared condition (recorded on the Problem List) or a shared exposure to a procedure (recorded on the Surgical History) or to a medication (recorded on the Medication List). Any EHR fields needed - either to determine registry membership or to calculate a registry-associated clinical quality measure (CQM) - were included in the enterprise data warehouse (EDW) shared dimensional data model. Extract-transform-load (ETL) code was written to pull data at defined "grains" from the EHR into the EDW model. All calculated CQM values were stored in a single Fact table in the EDW crossing all registries. Registry-specific dashboards were created in the EHR to display both (a) real-time patient lists of registry patients and (b) EDW-generated CQM data. Agile project management methods were employed, including co-development, lightweight requirements documentation with User Stories and acceptance criteria, and time-boxed iterative development of EHR features in 2-week "sprints" for rapid-cycle feedback and refinement.

RESULTS

Using this approach, in calendar year 2015 we developed a total of 43 specialty chronic disease registries, with 111 new EHR data collection and clinical decision support tools, 163 new clinical quality measures, and 30 clinic-specific dashboards reporting on both real-time patient care gaps and summarized and vetted CQM measure performance trends.

CONCLUSIONS

This study suggests concurrent design of EHR data collection tools and reporting can quickly yield useful EHR structured data for chronic disease registries, and bodes well for efforts to migrate away from manual abstraction. This work also supports the view that in new EHR-based registry development, as in new product development, adopting agile principles and practices can help deliver valued, high-quality features early and often.

Education in Neurology Resident Documentation Using Payroll Simulation

BACKGROUND

Approaches for teaching neurology documentation include didactic lectures, workshops, and face-to-face meetings. Few studies have assessed their effectiveness.

OBJECTIVE

To improve the quality of neurology resident documentation through payroll simulation.

METHODS

A documentation checklist was created based on Medicaid and Medicare evaluation and management (E/M) guidelines. In the preintervention phase, neurology follow-up clinic charts were reviewed over a 16-week period by evaluators blinded to the notes' authors. Current E/M level, ideal E/M level, and financial loss were calculated by the evaluators. Ideal E/M level was defined as the highest billable level based on the documented problems, alongside a supporting history and examination. We implemented an educational intervention that consisted of a 1-hour didactic lecture, followed by e-mail feedback "paystubs" every 2 weeks detailing the number of patients seen, income generated, income loss, and areas for improvement. Follow-up charts were assessed in a similar fashion over a 16-week postintervention period.

RESULTS

Ten of 11 residents (91%) participated. Of 214 charts that were reviewed preintervention, 114 (53%) had insufficient documentation to support the ideal E/M level, leading to a financial loss of 24% ($5,800). Inadequate documentation was seen in all 3 components: history (47%), examination (27%), and medical decision making (37%). Underdocumentation did not differ across residency years. Postintervention, underdocumentation was reduced to 14% of 273 visits (P < .001), with a reduction in the financial loss to 6% ($1,880).

CONCLUSIONS

Improved documentation and increased potential reimbursement was attained following a didactic lecture and a 16-week period in which individual, specific feedback to neurology residents was provided.

Measuring Practicing Clinicians' Information Literacy. An Exploratory Analysis in the Context of Panel Management

BACKGROUND

As healthcare moves towards technology-driven population health management, clinicians must adopt complex digital platforms to access health information and document care.

OBJECTIVES

This study explored information literacy, a set of skills required to effectively navigate population health information systems, among primary care providers in one Veterans' Affairs (VA) medical center.

METHODS

Information literacy was assessed during an 8-month randomized trial that tested a population health (panel) management intervention. Providers were asked about their use and comfort with two VA digital tools for panel management at baseline, 16 weeks, and post-intervention. An 8-item scale (range 0-40) was used to measure information literacy (Cronbach's α=0.84). Scores between study arms and provider types were compared using paired t-tests and ANOVAs. Associations between self-reported digital tool use and information literacy were measured via Pearson's correlations.

RESULTS

Providers showed moderate levels of information literacy (M= 27.4, SD 6.5). There were no significant differences in mean information literacy between physicians (M=26.4, SD 6.7) and nurses (M=30.5, SD 5.2, p=0.57 for difference), or between intervention (M=28.4, SD 6.5) and control groups (M=25.1, SD 6.2, p=0.12 for difference). Information literacy was correlated with higher rates of self-reported information system usage (r=0.547, p=0.001). Clinicians identified data access, accuracy, and interpretability as potential information literacy barriers.

CONCLUSIONS

While exploratory in nature, cautioning generalizability, the study suggests that measuring and improving clinicians' information literacy may play a significant role in the implementation and use of digital information tools, as these tools are rapidly being deployed to enhance communication among care teams, improve health care outcomes, and reduce overall costs.

New Unintended Adverse Consequences of Electronic Health Records

Although the health information technology industry has made considerable progress in the design, development, implementation, and use of electronic health records (EHRs), the lofty expectations of the early pioneers have not been met. In 2006, the Provider Order Entry Team at Oregon Health & Science University described a set of unintended adverse consequences (UACs), or unpredictable, emergent problems associated with computer-based provider order entry implementation, use, and maintenance. Many of these originally identified UACs have not been completely addressed or alleviated, some have evolved over time, and some new ones have emerged as EHRs became more widely available. The rapid increase in the adoption of EHRs, coupled with the changes in the types and attitudes of clinical users, has led to several new UACs, specifically: complete clinical information unavailable at the point of care; lack of innovations to improve system usability leading to frustrating user experiences; inadvertent disclosure of large amounts of patient-specific information; increased focus on computer-based quality measurement negatively affecting clinical workflows and patient-provider interactions; information overload from marginally useful computer-generated data; and a decline in the development and use of internally-developed EHRs. While each of these new UACs poses significant challenges to EHR developers and users alike, they also offer many opportunities. The challenge for clinical informatics researchers is to continue to refine our current systems while exploring new methods of overcoming these challenges and developing innovations to improve EHR interoperability, usability, security, functionality, clinical quality measurement, and information summarization and display.

Natural Language Processing-Enabled and Conventional Data Capture Methods for Input to Electronic Health Records: A Comparative Usability Study

Background

The process of documentation in electronic health records (EHRs) is known to be time consuming, inefficient, and cumbersome. The use of dictation coupled with manual transcription has become an increasingly common practice. In recent years, natural language processing (NLP)–enabled data capture has become a viable alternative for data entry. It enables the clinician to maintain control of the process and potentially reduce the documentation burden. The question remains how this NLP-enabled workflow will impact EHR usability and whether it can meet the structured data and other EHR requirements while enhancing the user’s experience.

Objective

The objective of this study is evaluate the comparative effectiveness of an NLP-enabled data capture method using dictation and data extraction from transcribed documents (NLP Entry) in terms of documentation time, documentation quality, and usability versus standard EHR keyboard-and-mouse data entry.

Methods

This formative study investigated the results of using 4 combinations of NLP Entry and Standard Entry methods (“protocols”) of EHR data capture. We compared a novel dictation-based protocol using MediSapien NLP (NLP-NLP) for structured data capture against a standard structured data capture protocol (Standard-Standard) as well as 2 novel hybrid protocols (NLP-Standard and Standard-NLP). The 31 participants included neurologists, cardiologists, and nephrologists. Participants generated 4 consultation or admission notes using 4 documentation protocols. We recorded the time on task, documentation quality (using the Physician Documentation Quality Instrument, PDQI-9), and usability of the documentation processes.

Results

A total of 118 notes were documented across the 3 subject areas. The NLP-NLP protocol required a median of 5.2 minutes per cardiology note, 7.3 minutes per nephrology note, and 8.5 minutes per neurology note compared with 16.9, 20.7, and 21.2 minutes, respectively, using the Standard-Standard protocol and 13.8, 21.3, and 18.7 minutes using the Standard-NLP protocol (1 of 2 hybrid methods). Using 8 out of 9 characteristics measured by the PDQI-9 instrument, the NLP-NLP protocol received a median quality score sum of 24.5; the Standard-Standard protocol received a median sum of 29; and the Standard-NLP protocol received a median sum of 29.5. The mean total score of the usability measure was 36.7 when the participants used the NLP-NLP protocol compared with 30.3 when they used the Standard-Standard protocol.

Conclusions

In this study, the feasibility of an approach to EHR data capture involving the application of NLP to transcribed dictation was demonstrated. This novel dictation-based approach has the potential to reduce the time required for documentation and improve usability while maintaining documentation quality. Future research will evaluate the NLP-based EHR data capture approach in a clinical setting. It is reasonable to assert that EHRs will increasingly use NLP-enabled data entry tools such as MediSapien NLP because they hold promise for enhancing the documentation process and end-user experience.

Clinical Decision Support: a 25 Year Retrospective and a 25 Year Vision

OBJECTIVE

The objective of this review is to summarize the state of the art of clinical decision support (CDS) circa 1990, review progress in the 25 year interval from that time, and provide a vision of what CDS might look like 25 years hence, or circa 2040.

METHOD

Informal review of the medical literature with iterative review and discussion among the authors to arrive at six axes (data, knowledge, inference, architecture and technology, implementation and integration, and users) to frame the review and discussion of selected barriers and facilitators to the effective use of CDS.

RESULT

In each of the six axes, significant progress has been made. Key advances in structuring and encoding standardized data with an increased availability of data, development of knowledge bases for CDS, and improvement of capabilities to share knowledge artifacts, explosion of methods analyzing and inferring from clinical data, evolution of information technologies and architectures to facilitate the broad application of CDS, improvement of methods to implement CDS and integrate CDS into the clinical workflow, and increasing sophistication of the end-user, all have played a role in improving the effective use of CDS in healthcare delivery.

CONCLUSION

CDS has evolved dramatically over the past 25 years and will likely evolve just as dramatically or more so over the next 25 years. Increasingly, the clinical encounter between a clinician and a patient will be supported by a wide variety of cognitive aides to support diagnosis, treatment, care-coordination, surveillance and prevention, and health maintenance or wellness.

Clinical documentation of dental care in an era of electronic health record use

BACKGROUND

Although complete and accurate clinical records do not guarantee the provision of excellent dental care, they do provide an opportunity to evaluate the quality of care provided. However, a lack of universally accepted documentation standards, incomplete record-keeping practices, and unfriendly electronic health care record (EHR) user interfaces are factors that have allowed for persistent poor dental patient record keeping.

METHODS

Using 2 different methods-a validated survey, and a 2-round Delphi process-involving 2 appropriately different sets of participants, we explored what a dental clinical record should contain and the frequency of update of each clinical entry.

RESULTS

For both the closed-ended survey questions and the open-ended Delphi process questions, respondents had a significant degree of agreement on the "clinical entry" components of an adequate clinical record. There was, however, variance on how frequently each of those clinical entries should be updated.

SUMMARY

Dental providers agree that complete and accurate record keeping is essential and that items such as histories, examination findings, diagnosis, radiographs, treatment plans, consents, and clinic notes should be documented. There, however, does not seem to be universal agreement how frequently such items should be recorded.

CLINICAL IMPLICATIONS

As the dental profession moves towards prevalent use of electronic health care records, the issue of standardization and interoperability becomes ever more pressing. Settling issues of standardization, including record documentation, must begin with guideline-creating dental professional bodies, who need to clearly define and disseminate what these standards should be and everyday dentists who will ultimately ensure that these standards are met and kept.

Creating value in health care through big data: opportunities and policy implications

Big data has the potential to create significant value in health care by improving outcomes while lowering costs. Big data's defining features include the ability to handle massive data volume and variety at high velocity. New, flexible, and easily expandable information technology (IT) infrastructure, including so-called data lakes and cloud data storage and management solutions, make big-data analytics possible. However, most health IT systems still rely on data warehouse structures. Without the right IT infrastructure, analytic tools, visualization approaches, work flows, and interfaces, the insights provided by big data are likely to be limited. Big data's success in creating value in the health care sector may require changes in current polices to balance the potential societal benefits of big-data approaches and the protection of patients' confidentiality. Other policy implications of using big data are that many current practices and policies related to data use, access, sharing, privacy, and stewardship need to be revised.

An electronic documentation system improves the quality of admission notes: a randomized trial

OBJECTIVE

There are concerns that structured electronic documentation systems can limit expressivity and encourage long and unreadable notes. We assessed the impact of an electronic clinical documentation system on the quality of admission notes for patients admitted to a general medical unit.

METHODS

This was a prospective randomized crossover study comparing handwritten paper notes to electronic notes on different patients by the same author, generated using a semistructured electronic admission documentation system over a 2-month period in 2014. The setting was a 4-team, 80-bed general internal medicine clinical teaching unit at a large urban academic hospital. The quality of clinical documentation was assessed using the QNOTE instrument (best possible score = 100), and word counts were assessed for free-text sections of notes.

RESULTS

Twenty-one electronic-paper note pairs (42 notes) written by 21 authors were randomly drawn from a pool of 303 eligible notes. Overall note quality was significantly higher in electronic vs paper notes (mean 90 vs 69, P < .0001). The quality of free-text subsections (History of Present Illness and Impression and Plan) was significantly higher in the electronic vs paper notes (mean 93 vs 78, P < .0001; and 89 vs 77, P = .001, respectively). The History of Present Illness subsection was significantly longer in electronic vs paper notes (mean 172.4 vs 92.4 words, P = .0001).

CONCLUSIONS

An electronic admission documentation system improved both the quality of free-text content and the overall quality of admission notes. Authors wrote more in the free-text sections of electronic documents as compared to paper versions.

Harnessing next-generation informatics for personalizing medicine: a report from AMIA's 2014 Health Policy Invitational Meeting

The American Medical Informatics Association convened the 2014 Health Policy Invitational Meeting to develop recommendations for updates to current policies and to establish an informatics research agenda for personalizing medicine. In particular, the meeting focused on discussing informatics challenges related to personalizing care through the integration of genomic or other high-volume biomolecular data with data from clinical systems to make health care more efficient and effective. This report summarizes the findings (n = 6) and recommendations (n = 15) from the policy meeting, which were clustered into 3 broad areas: (1) policies governing data access for research and personalization of care; (2) policy and research needs for evolving data interpretation and knowledge representation; and (3) policy and research needs to ensure data integrity and preservation. The meeting outcome underscored the need to address a number of important policy and technical considerations in order to realize the potential of personalized or precision medicine in actual clinical contexts.

Integrating Real Time Data to Improve Outcomes in Acute Kidney Injury

Critically ill patients with acute kidney injury requiring renal replacement therapy have a poor prognosis. Despite well-known factors, which contribute to outcomes, including dose delivery, patients frequently miss the target dose and volume removal. One major barrier to effective care of these patients is the traditional dissociation of dialysis device data from other clinical information systems, notably the electronic health record (EHR). This lack of integration and the resulting manual documentation leads to errors and biases in documentation and missed opportunities to intervene in a timely fashion. This review summarizes the technological advancements facilitating direct connection of dialysis devices to EHRs. This connection facilitates automated data capture of many variables - including delivered dose, ultrafiltration rate and pressure measurements - which in turn can be leveraged for data mining, quality improvement and real-time targeted therapy adjustments. These interventions hold the promise to significantly improve outcomes for this patient population.

Challenges Associated With Using Large Data Sets for Quality Assessment and Research in Clinical Settings

The rapidly expanding use of electronic records in health-care settings is generating unprecedented quantities of data available for clinical, epidemiological, and cost-effectiveness research. Several challenges are associated with using these data for clinical research, including issues surrounding access and information security, poor data quality, inconsistency of data within and across institutions, and a paucity of staff with expertise to manage and manipulate large clinical data sets. In this article, we describe our experience with assembling a data-mart and conducting clinical research using electronic data from four facilities within a single hospital network in New York City. We culled data from several electronic sources, including the institution's admission-discharge-transfer system, cost accounting system, electronic health record, clinical data warehouse, and departmental records. The final data-mart contained information for more than 760,000 discharges occurring from 2006 through 2012. Using categories identified by the National Institutes of Health Big Data to Knowledge initiative as a framework, we outlined challenges encountered during the development and use of a domain-specific data-mart and recommend approaches to overcome these challenges.