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AnteayerCIN: Computers, Informatics, Nursing

Patient Portal Use by Adults With Heart Failure: An Integrative Review

imageHeart failure is a chronic condition affecting many with an emphasis on self-management to improve outcomes and decrease the cost of care. A potential strategy to improve the self-management of heart failure includes the use of a patient portal. The purpose of this integrative review is to synthesize what is known about patient portal use by adults with heart failure to identify contributing factors for use and areas for future research. Within the three zones of the Health Information Technology Acceptance Model, predominant themes contributing to patient portal use were identified. Within the health zone, the predominant themes were physical and mental health, quality of life, and social interaction. Within the information zone, the predominant themes included knowledge about heart failure and self-care, information sharing, and communication. Within the technology zone, the predominant themes include the barriers and facilitators of patient portal use and overall usability. Overall, the patient perceptions of the patient portal can lead to the acceptance and use of the technology that can enhance self-management. Healthcare providers should partner with adults with heart failure to maximize the features of the patient portal to support self-management.

Feasibility of Using Blood Pressure Self-Monitoring and the Epic MyChart Blood Pressure Flowsheet to Monitor Blood Pressure After Preeclampsia

imagePreeclampsia is associated with significant morbidity and mortality. Women who experienced preeclampsia require close blood pressure surveillance postpartum. Remote monitoring of blood pressure using a mobile health application may be a viable method of surveillance in this population. The purpose of this project was to assess the feasibility of using the MyWellSpan mobile application to engage postpartum women who experienced preeclampsia in blood pressure self-monitoring. Women who chose to participate were provided an automatic blood pressure cuff and educational materials and were enrolled in MyWellSpan. A survey created by the authors asked participants to rate by Likert scale their satisfaction with the program and ease of use of the blood pressure cuff and self-monitoring. The electronic health record was reviewed retrospectively to assess utilization of the MyWellSpan mobile application to document blood pressure. The majority of women who participated reported that operating the blood pressure cuff was very easy and felt that it would be very easy to monitor their blood pressure twice daily. Sixty-nine percent of those women in the program electronically submitted at least 1 blood pressure measurement, thus confirming the feasibility of self-monitoring and reporting using a mobile application.

A Machine Learning–Based Fall Risk Assessment Model for Inpatients

imageFalls are one of the most common accidents among inpatients and may result in extended hospitalization and increased medical costs. Constructing a highly accurate fall prediction model could effectively reduce the rate of patient falls, further reducing unnecessary medical costs and patient injury. This study applied data mining techniques on a hospital's electronic medical records database comprising a nursing information system to construct inpatient-fall-prediction models for use during various stages of inpatient care. The inpatient data were collected from 15 inpatient wards. To develop timely and effective fall prediction models for inpatients, we retrieved the data of multiple-time assessment variables at four points during hospitalization. This study used various supervised machine learning algorithms to build classification models. Four supervised learning and two classifier ensemble techniques were selected for model development. The results indicated that Bagging+RF classifiers yielded optimal prediction performance at all four points during hospitalization. This study suggests that nursing personnel should be aware of patients' risk factors based on comprehensive fall risk assessment and provide patients with individualized fall prevention interventions to reduce inpatient fall rates.

The Development of the Postpartum Depression Self-Management Mobile Application “Happy Mother”

imagePostpartum depression is the most common mood disorder that occurs after childbirth, rendering it a significant public health problem. Information and communication technologies hold tremendous promise for expanding the reach of quality mental healthcare and closing the treatment gap for depression. In particular, given that mobile applications are inexpensive and provide information systematically, they are suitable as a method of health management that does not require visiting a medical center. The purposes of this study were to document the process of developing a mobile application for the self-management of postpartum depression and to share usability test results. The mobile application “Happy Mother” was developed based on the first five of seven stages in the mobile application development lifecycle model. Components of cognitive behavioral therapy were adopted to guide content development for “Happy Mother.” The usability of the completed mobile application was tested in the following three steps: it increased awareness of mood, promoted self-management, and implemented specific methods a mother can use in her daily life to improve mood, including modifications made based on the results of the usability test.

Incorporating a Whole-Person Perspective in Consumer-Generated Data: Social Determinants, Resilience, and Hidden Patterns

imageGiven the complex health and social needs of older adults, the rapid growth of the aging population, and the increasing use of information technology in healthcare, there is a critical need for informatics solutions that advance gerontological nursing care and knowledge discovery. This article illustrates the value of standardized data for healthcare quality improvement throughout the life cycle of data capture and reuse. One such informatics solution is the MyStrengths+MyHealth app, which incorporates a whole-person perspective through the Simplified Omaha System Terms assessment, including the social and behavioral determinants of health, as well as resilience. The data describe whole-person health of older adults from MyStrengths+MyHealth for use in clinical encounters and as raw data for research. There is potential to use such standardized data to improve gerontological nursing care at the bedside and for population health management and research.

Testing the Use of Natural Language Processing Software and Content Analysis to Analyze Nursing Hand-off Text Data

imageNatural language processing software programs are used primarily to mine both structured and unstructured data from the electronic health record and other healthcare databases. The mined data are used, for example, to identify vulnerable at-risk populations and predicting hospital associated infections and complications. Natural language processing programs are seldomly used in healthcare research to analyze the how providers are communicating essential patient information from one provider to another or how the language that is used impacts patient outcomes. In addition to analyzing how the message is being communicated, few studies have analyzed what is communicated during the exchange in terms of data, information, and knowledge. The analysis of the “how” and “what” of healthcare provider communication both written and verbal has the potential to decrease errors and improve patient outcomes. Here, we will discuss the feasibility of using an innovative within-methods triangulation data analysis to uncover the contextual and linguistic meaning of the nurse-to-nurse change-of-shift hand-off communication. The innovative within-methods triangulation data analysis uses a natural language processing software program and content analysis to analyze the nursing hand-off communication.

Evidence-Based Facebook Recruitment of Study Participants

imageTraditional methods for research study recruitment such as snail mail lists and posting flyers may fail to reach the tech-savvy participants needed for today's healthcare studies. Word of mouth can be effective for recruiting a few participants but can rarely accomplish the numbers needed for a representative sample. Social media can be a viable avenue to reach increased numbers of sample participants; however, a good understanding of the risks and benefits of using social media is needed before embarking on active recruitment. A recent study developed an evidence-based participant recruitment plan for the use of Facebook. Potential participant misrepresentation was addressed with clear inclusion criteria, no incentives, and open-ended questions. The Facebook ads to recruit study participation targeted licensed nurses who worked in the prior 2-year period living in the United States based on information in Facebook user profiles. A total of 536 participants responded to all questions on the survey at a cost of $1.78 per completed survey. Daily activity and cost for ads were closely monitored and adjusted to maintain cost control. Facebook can be an effective tool for study participant recruitment across all age ranges for completion of online surveys.

Prototype Development and Usability Evaluation of a Clinical Decision Support Tool for Pharmacogenomic Pharmacy in Practice

imagePharmacogenetics, a subset of precision medicine, provides a way to individualize drug dosages and provide tailored drug therapy to patients. This revolution in prescribing techniques has resulted in a knowledge deficit for many healthcare providers on the proper way to use pharmacogenetics in practice. This research study explored the potential adoption of clinical decision support system mobile apps by clinicians through investigating the initial usability of the PGx prototype application in an effort to address the lack of such tools used in practice. The study method included usage of a clinical decision support system programmed within our pharmacogenomics drug dosage application (called PGx) in a simulated environment. Study participants completed the System Usability Scale survey to report on the perceived usefulness and ease of use of the mobile app. The PGx app has a higher perceived usability than 85% of all products tested, considered very good usability for a product. This general usability rating indicates that the nurse practitioner students find the application to be a clinical decision support system that would be helpful to use in practice.

In Quest of Tablet Apps for Elders With Alzheimer's Disease: A Descriptive Review

Por: Tak · Sunghee H.
imageCaregivers search for mobile device apps that offer meaningful and enjoyable activities to simultaneously enhance the preserved cognitive and functional abilities of those in their care. The purpose of this review article was to describe the current state of tablet apps with which elders with Alzheimer's disease and related forms of dementia may engage as users. Using the keywords “app,” “Alzheimer's,” and “dementia,” a sample of 83 apps was selected from the iTunes Store, Google, and discussion boards of Apple Support Communities. A descriptive content analysis was conducted using a coding scheme on the characteristics of tablet app activity and the requirements for functional abilities of the users. This review found that the activities of the selected apps included games, simple watching and viewing, music and sounds, memory training, learning and information, and social interaction starters. A high-level cognitive and physical ability such as eye-hand coordination is often required to play the majority of the game apps. A few apps are designed specifically for the population. Individuals' variability in cognitive and functional abilities necessitates a person-centered approach in designing and selecting games and activities for apps in order to increase engagement and promote positive experiences in older adults.

Development of the Benefit-Risk Assessment of Complementary and Alternative Medicine Use in People With Diabetes: A Delphi–Analytic Hierarchy Process Approach

imageThis study aimed to develop consensus on a decision-making algorithm for benefit-risk assessment of complementary and alternative medicine use in people with diabetes. Delphi–analytic hierarchy process was used with an anonymous voting scheme, based on a three-round procedure, to achieve consensus regarding the important criteria of decision-making algorithm to assess the benefit-risk ratio of complementary and alternative medicine use in people with diabetes. A total of five criteria were considered, namely, the safety of usage (weightage: 46.6%), diabetes-specific patient data (14.6%), complementary and alternative medicine attributes (14.2%), institutional culture in complementary and alternative medicine use (12.8%), and applicability of complementary and alternative medicine (11.8%). The consistency of this hierarchy structure was computed based on the following indices: λmax = 5.041, consistency index = 0.01; random consistency index =1.781; and consistency ratio = 0.009. All criteria to optimize decision-making in ensuring safe use of complementary and alternative medicine in patients with diabetes should be considered by healthcare professionals.

Nurses' Electronic Medical Record Workarounds in a Tertiary Teaching Hospital

imageThe objective of this study was to identify nurses' workarounds related to the use of electronic medical records in a tertiary teaching hospital. A total of 106 nurses (84.8%) using the electronic medical records completed 10-item questionnaires scored on a Likert scale and five open-ended questions with written responses. The numerical data were analyzed by descriptive statistics, and the written descriptions were categorized by meaning. The mean of the scored items ranged from 3.29 to 3.74. Approximately 38% to 50% of the participants reported (very) frequent workflow delays due to the use of the electronic medical records, and 46% to 64% reported (very) frequently using workarounds. Twenty-nine workarounds of the electronic medical records were due to electronic documentation, difficulty accessing the electronic medical records, medication administration, covering physician responsibilities, electronic communication with the physicians, respondents and physicians not skilled in using the electronic medical records, and connection failures between devices or machines and the electronic medical records. Although none of these identified workarounds were intended to be harmful, and certain workarounds were efficient for patient care and workflow, whether patient safety can be jeopardized by workarounds should be considered. This study contributes to the understanding of why and how workarounds occur in the hospital. It will be useful for achieving greater alignment between work contexts and the electronic medical record in the future.

Modeling for Change of Daily Nurse Calls After Surgery in an Orthopedics Ward Using Bayesian Statistics

imageNurse call data may be used to evaluate the quality of nursing. However, traditional frequency-based statistics may not easily apply to nurse calls due to the large individual variability and daily call changes. We intended to propose a probabilistic modeling of nurse calls based on Bayesian statistics. We constructed the model including nurse call daily changes, individual variability, and adjustment according to characteristics (age and sex). Nurse call differences after surgery were analyzed based on data from the orthopedic ward from April 2014 to October 2017. Results show that there were differences in nurse calls from day 1 to day 10 after surgery between patients who had undergone orthopedic surgery and those who had undergone other surgeries such as tumor surgery. Furthermore, there were differences in nurse calls from day 1 to day 8 after surgery between patients who used extra pain relief medicine and those who did not. Although the analysis required multiple comparisons regarding daily nurse call changes and fixed data samples per day, our approach using Bayesian statistics could detect the periods and significant differences. This indicates that our nurse call modeling based on Bayesian statistics may be used to analyze nurse call changes.

Status and Influential Factors of Intelligent Healthcare in Nursing Homes in China

imageWith the support of the Chinese government, nursing homes have increasingly adopted Internet and intelligent information technology to provide daily healthcare services to residents. However, no research has reported the status of intelligent healthcare in nursing homes. From September 2017 to May 2018, we conducted a survey of 197 nursing homes and collected information on their general characteristics, the intelligent healthcare services provided, the effectiveness of the application products used, and the attitudes of the staff and residents toward intelligent healthcare. Overall, 79.69% of the surveyed nursing homes have provided intelligent healthcare services, including medical care services (eg, chronic disease management and intelligent nursing) and daily life services (eg, fall monitoring and wireless positioning). Portable health monitoring devices and data management and service platforms are the most used healthcare products. The attitudes of staff probably affected the development of intelligent healthcare. Financial investment and the attitudes of staff and residents are factors that influence the effectiveness of the application of intelligent healthcare products in nursing homes. With the support of national policies, nursing homes have implemented primary intelligent healthcare. Stakeholders play pivotal roles in the provision of intelligent healthcare services.
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