OBJECTIVE: To honor the legacy of nursing informatics pioneer and visionary, Dr. Virginia Saba, the Friends of the National Library of Medicine convened a group of international experts to reflect on Dr. Saba's contributions to nursing standardized nursing terminologies. PROCESS: Experts led a day-and-a-half virtual update on nursing's sustained and rigorous efforts to develop and use valid, reliable, and computable standardized nursing terminologies over the past 5 decades. Over the course of the workshop, policymakers, industry leaders, and scholars discussed the successful use of standardized nursing terminologies, the potential for expanded use of these vetted tools to advance healthcare, and future needs and opportunities. In this article, we elaborate on this vision and key recommendations for continued and expanded adoption and use of standardized nursing terminologies across settings and systems with the goal of generating new knowledge that improves health. CONCLUSION: Much of the promise that the original creators of standardized nursing terminologies envisioned has been achieved. Secondary analysis of clinical data using these terminologies has repeatedly demonstrated the value of nursing and nursing's data. With increased and widespread adoption, these achievements can be replicated across settings and systems.

OBJECTIVE: This research brief contains results from a national survey about telehealth use reported in a random sample of U.S. nursing homes. METHODS AND MATERIALS: The sample includes nursing homes (N = 664) that completed surveys about information technology maturity, including telehealth use, beginning January 1, 2019, and ending August 4, 2020. A pre/post design was employed to examine differences in nursing home telehealth use for nursing homes completing surveys prior to and after telehealth expansion, on March 6, 2020. We calculated a cumulative telehealth score using survey data from 6 questions about extent of nursing home telehealth use (score range 0-42). We calculated proportions of nursing homes using telehealth and used logistic regression to look for differences in nursing homes based on organizational characteristics and odds ratios. RESULTS: Significant relationships were found between nursing home characteristics and telehealth use, and specifically, larger metropolitan homes reported greater telehealth use. Ownership had little effect on telehealth use. Nursing homes postexpansion used telehealth applications for resident evaluation 11.24 times more (P < .01) than did nursing homes pre-expansion. DISCUSSION: Administrators completing our survey reported a wide range of telehealth use, including approximately 16% having no telehealth use and 5% having the maximum amount of telehealth use. Mean telehealth use scores reported by the majority of these nursing homes is on the lower end of the range. CONCLUSIONS: One solution for the current pandemic is to encourage the proliferation of telehealth with continued relaxed regulations, which can reduce isolation and preserve limited resources (eg, personal protective equipment) while maintaining proper distancing parameters.

results for questions 1 and 2 were erroneously given as "250 (7.65)" and "257 (8.70)".

In celebration of the 200th birthday of Florence Nightingale, widely acknowledged as the founder of modern nursing, the World Health Organization declared 2020 as the International Year of the Nurse and Midwife. Nursing informatics is a key component of the broader field of biomedical and health informatics as well as the Nursing Informatics Working Group, a large and vibrant working group within the American Medical Informatics Association community. The American Nurses Association (ANA) defined nursing informatics as a specialty and published the first standards for its practice more than 25 years ago.1,2 As described in Journal of the American Medical Informatics Association (JAMIA), the definition has evolved through the years.3 The most recent ANA definition is the following: Nursing informatics is a specialty that integrates nursing science, computer science, and information science to manage and communicate data, information, and knowledge in nursing practice. Nursing informatics facilitates the integration of data, information, and knowledge to support patients, nurses, and other providers in their decision making in all roles and settings. This support is accomplished through the use of information structures, information processes, and information technology.4 In this editorial, we highlight 5 articles in this issue by or about nurses. We also announce the launch of a JAMIA Virtual Collection focused on nursing in celebration of the International Year of the Nurse and Midwife. Two articles focus on the “support patients” aspect of the ANA definition. Ryan Shaw, from the Duke University School of Nursing, and colleagues examined the use of multiple mobile health (mHealth) technologies to generate and transmit data from diverse patients with type 2 diabetes mellitus in between clinic visits.5 In a longitudinal feasibility trial, 60 patients were asked to self-monitor for 6 months using a variety of mHealth technologies (wireless glucometer, cellular scale, wrist-worn accelerometer, and medication adherence text message surveys) provided at baseline. In a diverse sample (60% Black/African American), they found that engagement with devices was highest for physical activity (ie, Fitbit), followed by glucose and weight. Fitbit engagement (87%) did not vary by age, hemoglobin A1C level, or race. However, engagement with the other mHealth technologies differed according to 1 or more of these variables. The authors concluded that it was feasible for participants from different socioeconomic, educational, and racial backgrounds to use and track relevant diabetes-related data from multiple mHealth technologies for 6 months, although engagement varied by patient characteristics. Patient-reported outcomes (PROs) are increasingly a component of self-monitoring of health status. Information visualizations may help patients interpret and contextualize their PROs. Turchoie et al6 assessed hospitalized patients’ objective comprehension (primary outcome) of text-only, nongraph, and graph visualizations that display longitudinal PROs. Forty patients viewed 4 conditions in a counterbalanced design that controlled for potential order effects: (1) text only, (2) text plus visual analogy, (3) text plus number line, and (4) text plus line graph. They assessed objective comprehension using the International Organization for Standardization protocol. Secondary outcomes included response times, preferences, risk perceptions, and behavioral intentions. Comprehension scores were 83% for text plus visual analogy, 70% for text plus number line, 62% for text only, and 60% for text plus line graph; the differences between text plus visual analogy and the latter 2 conditions were statistically significant. Interestingly, in participants who comprehended at least 1 condition, 14% preferred a condition that they did not comprehend. These findings highlight the need for assessing comprehension rather than preference in assessments of information visualizations. Two articles address aspects of quality and safety in nursing. Moore et al7 conducted a systematic review of the literature on the impact of health information technology (HIT) on nurses’ time. Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducting a search of articles, published between January 2004 and December 2019, 33 articles met inclusion criteria: had comparison group in the design, measured the time taken to carry out documentation or medication administration, documented the quantitative estimates of time differences between the comparisons, had nurses as subjects, and was conducted in a care home, hospital, or community clinic. Twenty-one studies reported the impact of 12 different HIT implementations on nurses’ documentation time and showed an increase in time. In contrast, the time spent carrying out medication administration after bar code medication administration implementation was reduced by 33%. In some instances, nurses’ time after HIT implementation was redistributed to “value-adding” activities, such as direct patient care and interprofessional communication. Best practice guidelines are a key component of quality and safety across health professions and healthcare organizations. Multiple organizations have initiatives related to collection of such data as part of their quality and safety programs. In 2012, the Registered Nurses’ Association of Ontario launched the Nursing Quality Indicators for Reporting and Evaluation (NQuIRE) database to collect data on quality indicators derived from Registered Nurses’ Association of Ontario best practice guidelines. In a case report in this issue, Naik et al8 present a method to standardize data quality assessments of the NQuIRE database by developing a data quality framework and assessing key dimensions of the framework (integrity, relevance, interpretability, coherence, timeliness, institutional environment) using a data quality index. The data quality index is a single key performance metric for assessing the quality of the database, which is based on an aggregation of normalized measures across the 6 framework dimensions. This approach may be useful to others wishing to develop a data quality framework for a health data repository. Nurses most often practice as part of an interprofessional team. Members of interprofessional teams share distinct information, have specific information needs, and communicate what they know through various mechanisms and pathways. Recognizing unmet information needs is an important component of patient safety in care delivery. Cohen et al9 identified the unmet information needs of clinical teams delivering care to complex patients and then generated design principles to address those needs. The observational study involved care teams in 9 community health centers and included observations and interviews focused on their use of the electronic health record (EHR) when caring for patients with complex medical needs as well as needs related to social determinants of health (SDH). Nurse practitioners, registered nurses, and registered nurse care coordinators were among the types of nurses observed and interviewed. Analyses of >300 hours of observations and 51 interviews identified 4 major categories of information needs, related to consistency of SDH documentation, SDH information prioritization and changes to this prioritization, initiation and follow-up of community resource referrals, and timely communication of SDH information. There were 10 unmet information needs within these categories that were judged to be addressable through the EHR. They proposed 5 EHR design recommendations: enhance the flexibility of EHR documentation workflows, expand the ability to exchange information within teams and between systems, balance innovation and standardization of HIT systems, organize and simplify information displays, and prioritize and reduce information. To complement the articles in this issue, JAMIA is launching a Virtual Collection focused on nursing in celebration of the International Year of the Nurse and Midwife. The Collection is located at https://academic.oup.com/jamia/pages/nursing-collection. It contains a subset of the >200 articles published by or about nurses in JAMIA from 1994 to the present. We are proud to be part of the nursing informatics community. In our roles as JAMIA Editor-in-Chief and Chair of the Nursing Informatics Working Group of the American Medical Informatics Association, we hope that all biomedical and health informaticians will join us in celebrating the International Year of the Nurse and Midwife by reading aa article in this issue and by visiting the Virtual Collection. SB drafted the highlight section of the editorial. SB and GA contributed to the remaining sections and approved the final draft of the editorial. None declared.

OBJECTIVES: We describe the development of a nursing home information technology (IT) maturity model designed to capture stages of IT maturity. MATERIALS AND METHODS: This study had 2 phases. The purpose of phase I was to develop a preliminary nursing home IT maturity model. Phase II involved 3 rounds of questionnaires administered to a Delphi panel of expert nursing home administrators to evaluate the validity of the nursing home IT maturity model proposed in phase I. RESULTS: All participants (n = 31) completed Delphi rounds 1-3. Over the 3 Delphi rounds, the nursing home IT maturity staging model evolved from a preliminary, 5-stage model (stages 1-5) to a 7-stage model (stages 0-6). DISCUSSION: Using innovative IT to improve patient outcomes has become a broad goal across healthcare settings, including nursing homes. Understanding the relationship between IT sophistication and quality performance in nursing homes relies on recognizing the spectrum of nursing home IT maturity that exists and how IT matures over time. Currently, no universally accepted nursing home IT maturity model exists to trend IT adoption and determine the impact of increasing IT maturity on quality. CONCLUSIONS: A 7-stage nursing home IT maturity staging model was successfully developed with input from a nationally representative sample of U.S. based nursing home experts. The model incorporates 7-stages of IT maturity ranging from stage 0 (nonexistent IT solutions or electronic medical record) to stage 6 (use of data by resident or resident representative to generate clinical data and drive self-management).

OBJECTIVE: To provide a report on year 1 results of a national study investigating nursing home information technology (IT) adoption, called IT sophistication. METHODS: A reliable and valid survey was used to measure IT sophistication. The target goal was 10% from each state in the United States, 1570 nursing homes. A random sample of homes from each state was recruited from Nursing Home Compare. RESULTS: The team reached 2627 nursing home administrators, among whom 1799 administrators agreed to participate and were sent a survey. A total of 815 surveys were completed (45.3% response rate), which was below the goal. Facilities in the participating sample have similar demographic characteristics (ownership, total population in a location, and bed size) to the remaining homes not participating. There are greater IT capabilities in resident care and administrative activities, less in clinical support. The extent of use of these capabilities appears to be highest in administrative activities and lowest in clinical support. IT in resident care appears to be the most integrated with internal and external stakeholders. IT capabilities appear to be greater than IT extent of use in all health domains, with the greatest difference in resident care. DISCUSSION: National evaluations of nursing home IT are rare. Measuring trends in IT adoption in a nationally representative sample provides meaningful analytics that could be more useful for policy makers and nursing home leaders in the future. CONCLUSION: Discovering national baseline assessments is a first step toward recognizing nursing home trends in IT adoption.

In alignment with a major shift toward patient-centered care as the model for improving care in our health system, informatics is transforming patient-provider relationships and overall care delivery. AMIA's 2013 Health Policy Invitational was focused on examining existing challenges surrounding full engagement of the patient and crafting a research agenda and policy framework encouraging the use of informatics solutions to achieve this goal. The group tackled this challenge from educational, technical, and research perspectives. Recommendations include the need for consumer education regarding rights to data access, the need for consumers to access their health information in real time, and further research on effective methods to engage patients. This paper summarizes the meeting as well as the research agenda and policy recommendations prioritized among the invited experts and stakeholders.

Creating linguistic summaries of data has been a goal of the artificial and computational intelligence communities for many years. Summaries of written text have garnered the most attention. More recently, creating summaries of imagery and other sensed data has become important as a means of compressing large amounts of data and communicating with humans. In this paper, we consider the question of comparing sets of summaries generated from sensed data. In an earlier work, we developed a metric between individual protoform-based summaries; and here, as a next step, we propose aggregation methods to fuse these individual distances. We provide a case study from eldercare where the goal is to compare different nighttime patterns for change detection. © 2012 Wiley Periodicals, Inc.

Ubiquitous passive, as well as active, monitoring of elders is a growing field of research and development with the goal of allowing seniors to live safe active independent lives with minimal intrusion. Much useful information, fall detection, fall risk assessment, activity recognition, early illness detection, etc. can be inferred from the mountain of data. Healthcare must be human centric and human friendly, and so, methods to consolidate the data into linguistic summaries for enhanced communication and problem detection with elders, family and healthcare providers is essential. Long term trends can be most easily identified using summarized information. This paper explores the soft computing methodology of protoforms to produce linguistic summaries of one dimensional data, motion and restlessness. The technique is demonstrated on a 15 month sensor collection for an elder participant.

Video-based tracking of contours on the human body has been shown to be useful for many applications, including gait and gesture recognition, posture estimation, and activity analysis. We present a contour tracking method that incorporates a novel edge feature and fuzzy contour template. We apply our method in tracking the motions of older adults exercising in a gym environment. The output of our system is a dynamic fuzzy representation of the spine angle of the subject. We show that the method described in this paper is capable of tracking contours even in cases where human silhouette extraction is poor.