Natural Language Processing Application in Nursing Research: A Study Using Text Network Analysis and Topic Modeling

Although the potential of natural language processing and an increase in its application in nursing research is evident, there is a lack of understanding of the research trends. This study conducts text network analysis and topic modeling to uncover the underlying knowledge structures, research trends, and emergent research themes within nursing literature related to natural language processing. In addition, this study aims to provide a foundation for future scholarly inquiries and enhance the integration of natural language processing in the analysis of nursing research. We analyzed 443 literature abstracts and performed core keyword analysis and topic modeling based on frequency and centrality. The following topics emerged: (1) Term Identification and Communication; (2) Application of Machine Learning; (3) Exploration of Health Outcome Factors; (4) Intervention and Participant Experience; and (5) Disease-Related Algorithms. Nursing meta-paradigm elements were identified within the core keyword analysis, which led to understanding and expanding the meta-paradigm. Although still in its infancy in nursing research with limited topics and research volumes, natural language processing can potentially enhance research efficiency and nursing quality. The findings emphasize the possibility of integrating natural language processing in nursing-related subjects, validating nursing value, and fostering the exploration of essential paradigms in nursing science.

Natural Language Processing Applied to Clinical Documentation in Post-acute Care Settings: A Scoping Review

OBJECTIVES

To determine the scope of the application of natural language processing to free-text clinical notes in post-acute care and provide a foundation for future natural language processing-based research in these settings.

DESIGN

Scoping review; reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines.

SETTING AND PARTICIPANTS

Post-acute care (ie, home health care, long-term care, skilled nursing facilities, and inpatient rehabilitation facilities).

METHODS

PubMed, Cumulative Index of Nursing and Allied Health Literature, and Embase were searched in February 2023. Eligible studies had quantitative designs that used natural language processing applied to clinical documentation in post-acute care settings. The quality of each study was appraised.

RESULTS

Twenty-one studies were included. Almost all studies were conducted in home health care settings. Most studies extracted data from electronic health records to examine the risk for negative outcomes, including acute care utilization, medication errors, and suicide mortality. About half of the studies did not report age, sex, race, or ethnicity data or use standardized terminologies. Only 8 studies included variables from socio-behavioral domains. Most studies fulfilled all quality appraisal indicators.

CONCLUSIONS AND IMPLICATIONS

The application of natural language processing is nascent in post-acute care settings. Future research should apply natural language processing using standardized terminologies to leverage free-text clinical notes in post-acute care to promote timely, comprehensive, and equitable care. Natural language processing could be integrated with predictive models to help identify patients who are at risk of negative outcomes. Future research should incorporate socio-behavioral determinants and diverse samples to improve health equity in informatics tools.

Natural Language Processing of Nursing Notes: An Integrative Review

Natural language processing includes a variety of techniques that help to extract meaning from narrative data. In healthcare, medical natural language processing has been a growing field of study; however, little is known about its use in nursing. We searched PubMed, EMBASE, and CINAHL and found 689 studies, narrowed to 43 eligible studies using natural language processing in nursing notes. Data related to the study purpose, patient population, methodology, performance evaluation metrics, and quality indicators were extracted for each study. The majority (86%) of the studies were conducted from 2015 to 2021. Most of the studies (58%) used inpatient data. One of four studies used data from open-source databases. The most common standard terminologies used were the Unified Medical Language System and Systematized Nomenclature of Medicine, whereas nursing-specific standard terminologies were used only in eight studies. Full system performance metrics (eg, F score) were reported for 61% of applicable studies. The overall number of nursing natural language processing publications remains relatively small compared with the other medical literature. Future studies should evaluate and report appropriate performance metrics and use existing standard nursing terminologies to enable future scalability of the methods and findings.

Self-reported gaps in care coordination and preventable adverse outcomes among older adults receiving home health care

BACKGROUND

Older adults see multiple outpatient providers and increasingly use home health care (HHC) services. Previous studies attempting to draw inferences about the association between HHC use and patient outcomes have been mixed. Whether HHC is associated with care coordination and how both influence outcomes are unknown. In addition, prior studies have not taken the patient perspective into account. We examined the association between receiving HHC and self-reported gaps in care coordination and separately, preventable adverse outcomes.

METHODS

The analysis for this cross-sectional study was conducted between October 2021 and June 2022, using data on 4296 Medicare beneficiaries from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study who completed a survey on care coordination from 2017 to 2018. The associations between the receipt of HHC and two outcomes (a gap in care coordination, and separately, a preventable adverse event) were examined with Poisson models with robust standard errors. Potential confounders were accounted for through propensity score-based inverse probability weighting.

RESULTS

Among 4296 participants, 430 (10%) received HHC and they were older and had more comorbidities and ambulatory visits than those without HHC. HHC was not associated with differences in self-reported gaps in care coordination (33.3% HHC vs. 32.5% no-HHC, p = 0.70). HHC recipients reported more preventable drug-drug interactions (9.1% vs. 4.0%, p < 0.001) but not more preventable ED visits or hospital admissions. In IPW-adjusted models, HHC was not associated with gaps in care coordination (p = 0.60) but was associated with double the risk of a preventable adverse outcome (aRR 2.06; CI: 1.37, 3.10, p < 0.001).

CONCLUSIONS

HHC recipients were significantly more likely (than those without HHC) to report a potentially preventable adverse event (particularly a drug-drug interaction), suggesting an opportunity to improve patient safety by leveraging the observations of older adults receiving HHC.

Skilled home healthcare clinicians' experiences in communicating with physicians: A national survey

BACKGROUND

Effective communication between skilled home healthcare (SHHC) clinicians and physicians is critical to care coordination. No studies have examined this from the point of view of SHHC clinicians at the national level. The objective is to determine in national sample issues related to how SHHC agency clinicians communicate with physicians.

DESIGN

Mailed survey.

METHODS

Mailed survey to a national representative random sample of SHHC agencies. The survey measured the experiences of SHHC clinicians in communicating with physicians. Multilevel logistic regression models examining odds of adverse patient outcomes associated with communication failures.

RESULTS

A total of 265 surveys from 168 SHHC agencies were returned for a response rate of 13.3% at the individual respondent level and 16.8% at the SHHC agency level. Agency-level characteristics were similar between responding and nonresponding agencies. The most common method of contacting physicians during routine SHHC visits was telephone; communication via the electronic health record was uncommon. Nearly 40% of SHHC clinicians report never or rarely being able to reach a physician. SHHC clinicians rate the Center for Medicare and Medicaid Services Home Health Certification and Plan of Care (CMS-485) as a useful means of communication 6.3 (SD, 2.5) scale of 1 (least useful) to 10 (most useful); only 14% could have SHHC orders signed electronically. In multilevel logistic models, compared to SHHC clinicians who could reach a physician nearly every time or always, the odds of an SHHC clinician sending someone to the emergency department were 3.66 (95% confidence interval 1.16-11.5) for SHHC clinicians who were sometimes or often able to reach a physician and 5.43 (95% CI 1.56-18.9) for those who never or rarely reached a physician.

CONCLUSIONS

In this exploratory study, SHHC clinicians experience significant communication barriers with physicians who order SHHC services. Strategies to enhance meaningful communication between SHHC clinicians and physicians must be developed.

Application of Artificial Intelligence in Community-Based Primary Health Care: Systematic Scoping Review and Critical Appraisal

BACKGROUND

Research on the integration of artificial intelligence (AI) into community-based primary health care (CBPHC) has highlighted several advantages and disadvantages in practice regarding, for example, facilitating diagnosis and disease management, as well as doubts concerning the unintended harmful effects of this integration. However, there is a lack of evidence about a comprehensive knowledge synthesis that could shed light on AI systems tested or implemented in CBPHC.

OBJECTIVE

We intended to identify and evaluate published studies that have tested or implemented AI in CBPHC settings.

METHODS

We conducted a systematic scoping review informed by an earlier study and the Joanna Briggs Institute (JBI) scoping review framework and reported the findings according to PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis-Scoping Reviews) reporting guidelines. An information specialist performed a comprehensive search from the date of inception until February 2020, in seven bibliographic databases: Cochrane Library, MEDLINE, EMBASE, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), ScienceDirect, and IEEE Xplore. The selected studies considered all populations who provide and receive care in CBPHC settings, AI interventions that had been implemented, tested, or both, and assessed outcomes related to patients, health care providers, or CBPHC systems. Risk of bias was assessed using the Prediction Model Risk of Bias Assessment Tool (PROBAST). Two authors independently screened the titles and abstracts of the identified records, read the selected full texts, and extracted data from the included studies using a validated extraction form. Disagreements were resolved by consensus, and if this was not possible, the opinion of a third reviewer was sought. A third reviewer also validated all the extracted data.

RESULTS

We retrieved 22,113 documents. After the removal of duplicates, 16,870 documents were screened, and 90 peer-reviewed publications met our inclusion criteria. Machine learning (ML) (41/90, 45%), natural language processing (NLP) (24/90, 27%), and expert systems (17/90, 19%) were the most commonly studied AI interventions. These were primarily implemented for diagnosis, detection, or surveillance purposes. Neural networks (ie, convolutional neural networks and abductive networks) demonstrated the highest accuracy, considering the given database for the given clinical task. The risk of bias in diagnosis or prognosis studies was the lowest in the participant category (4/49, 4%) and the highest in the outcome category (22/49, 45%).

CONCLUSIONS

We observed variabilities in reporting the participants, types of AI methods, analyses, and outcomes, and highlighted the large gap in the effective development and implementation of AI in CBPHC. Further studies are needed to efficiently guide the development and implementation of AI interventions in CBPHC settings.

"This Graft-vs.-Host Disease Determines My Life. That's It."-A Qualitative Analysis of the Experiences and Needs of Allogenic Hematopoietic Stem Cells Transplantation Survivors in Germany

Background: Allogeneic hematopoietic stem cell transplantation (alloHSCT) is the only curative treatment modality for many patients affected by hematologic malignancies. However, it can cause debilitating long-term effects. Understanding the impact of alloHSCT on all aspects of the patients' life is required for optimal survivorship management. Aim: To explore in-depth HSCT-survivors' experiences and needs post-transplant. Partners were included to provide further information on survivors' needs and how care could be improved in this area. Methods: We conducted semi-structured face-to-face and phone interviews with alloHSCT-survivors and their partners referred to a survivorship clinic in Germany. Theoretical sampling was used to recruit participants. Data were analyzed using framework analysis. Results: Thirty-two survivors (consent rate: 100%, response rate: 100%) and eighteen partners (consent rate: 84%, response rate: 72%) participated. Survivors were aged between 25 and 68 years (Median: 48, IQR: 25.3) and partners were aged between 26 and 64 years (Median: 54, IQR: 16, SD: 12.8). The themes emerging from the data involved survivors' needs included (i) the diversity of long-term treatment side-effects; and (ii) time post discharge as a dynamic process with individual peaks of burden. Survivors and their partners also suggested strategies for mitigating these unmet needs, i.e., (iii) transparent communication and patient empowerment; and (iv) improvement in continuity of care system and help with claiming social benefits as cornerstones of optimal survivorship care. Conclusion: To our knowledge, this is one of the first qualitative studies focused on the views of German alloHSCT-survivors on the long-term effects of alloHSCT and the first study integrating the view of their partners. Healthcare providers could better support survivors with managing their symptoms and adhering to their prescribed care by ensuring comprehensive, transparent communication that helps increase survivors' understanding and involvement in their care. Further efforts should be made to provide patient-centered, continuous survivorship care that involves additional support with navigating the healthcare and social service system. Intervention studies are required to test the effectiveness of the suggested strategies.

Machine learning vs. conventional statistical models for predicting heart failure readmission and mortality

Aims

This study aimed to review the performance of machine learning (ML) methods compared with conventional statistical models (CSMs) for predicting readmission and mortality in patients with heart failure (HF) and to present an approach to formally evaluate the quality of studies using ML algorithms for prediction modelling.

Methods and results

Following Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines, we performed a systematic literature search using MEDLINE, EPUB, Cochrane CENTRAL, EMBASE, INSPEC, ACM Library, and Web of Science. Eligible studies included primary research articles published between January 2000 and July 2020 comparing ML and CSMs in mortality and readmission prognosis of initially hospitalized HF patients. Data were extracted and analysed by two independent reviewers. A modified CHARMS checklist was developed in consultation with ML and biostatistics experts for quality assessment and was utilized to evaluate studies for risk of bias. Of 4322 articles identified and screened by two independent reviewers, 172 were deemed eligible for a full‐text review. The final set comprised 20 articles and 686 842 patients. ML methods included random forests (n = 11), decision trees (n = 5), regression trees (n = 3), support vector machines (n = 9), neural networks (n = 12), and Bayesian techniques (n = 3). CSMs included logistic regression (n = 16), Cox regression (n = 3), or Poisson regression (n = 3). In 15 studies, readmission was examined at multiple time points ranging from 30 to 180 day readmission, with the majority of studies (n = 12) presenting prediction models for 30 day readmission outcomes. Of a total of 21 time‐point comparisons, ML‐derived c‐indices were higher than CSM‐derived c‐indices in 16 of the 21 comparisons. In seven studies, mortality was examined at 9 time points ranging from in‐hospital mortality to 1 year survival; of these nine, seven reported higher c‐indices using ML. Two of these seven studies reported survival analyses utilizing random survival forests in their ML prediction models. Both reported higher c‐indices when using ML compared with CSMs. A limitation of studies using ML techniques was that the majority were not externally validated, and calibration was rarely assessed. In the only study that was externally validated in a separate dataset, ML was superior to CSMs (c‐indices 0.913 vs. 0.835).

Conclusions

ML algorithms had better discrimination than CSMs in most studies aiming to predict risk of readmission and mortality in HF patients. Based on our review, there is a need for external validation of ML‐based studies of prediction modelling. We suggest that ML‐based studies should also be evaluated using clinical quality standards for prognosis research. Registration: PROSPERO CRD42020134867

Literature review of managerial levers in primary care

PURPOSE

This study aims to analyze the managerial levers previously considered in literature in the setting of the provision of primary care and community services (in particular for patients with long-term conditions being treated also at home) as well as those scarcely explored that could potentially be adopted in the future.

DESIGN/METHODOLOGY/APPROACH

This study was a structured literature review. The authors retrieved papers, published from 2005-2020, from electronic databases (i.e. ABI/INFORM Complete, Jstor, PubMed and Scopus). Each selected paper was assigned to a framework category, and a thematic analysis was performed.

FINDINGS

Topics scarcely explored in literature were related to logistics/supply chain, economic evaluations, performance management and customer satisfaction. Some papers embraced more than one management topic, confirming the multidisciplinary nature of territorial healthcare services. The majority of research, however, focused on only one aspect of primary care services, and a lack of an integrated view regarding the provision of those services emerged.

ORIGINALITY/VALUE

This study represents a first attempt to rationalize the fragmented body of knowledge on the topic of the provision of primary and community care services. This study enabled some light to be shed on the managerial levers already explored previously in literature and also identifies a number of trajectories for future research.

Understanding the Workflow of Home Health Care for Patients with Heart Failure: Challenges and Opportunities

BACKGROUND

Readmission rates are high among heart failure (HF) patients who require home health care (HHC) after hospitalization. Although HF patients who require HHC are often sicker than those who do not, HHC delivery itself may also be suboptimal.

OBJECTIVE

We aimed to describe the workflow of HHC among adults discharged home after a HF hospitalization, including the roles of various stakeholders, and to determine where along these workflow challenges and opportunities for improvement exist.

DESIGN AND PARTICIPANTS

In this qualitative study, we used purposeful sampling to approach and recruit a variety of key stakeholders including home health aides, nurses, HF patients, family caregivers, physicians, social workers, home care agency leaders, and policy experts. The study took place in New York, NY, from March to October 2018.

APPROACH

Using a semi-structured topic guide, we elicited participants' experiences with HHC in HF through a combination of one-on-one interviews and focus groups. Data were recorded, transcribed, and analyzed thematically. We also asked selected participants to depict in a drawing their understanding of HHC workflow after hospitalization for HF patients. We synthesized the drawings into a final image.

KEY RESULTS

Study participants (N = 80) described HHC for HF patients occurring in 6 steps, with home health aides playing a main role: (1) transitioning from hospital to home; (2) recognizing clinical changes; (3) making decisions; (4) managing symptoms; (5) asking for help; and (6) calling 911. Participants identified challenges and opportunities for improvement for each step.

CONCLUSIONS

Our findings suggest that HHC for HF patients occurs in discrete steps, each with different challenges. Rather than a one-size-fits-all approach, various interventions may be required to optimize HHC delivery for HF patients in the post-discharge period.

Medication Discrepancies in Older Veterans Receiving Home Healthcare

In a prospective cohort study of Veterans and community health nurses, we enrolled hospitalized older Veterans referred to home care for skilled nursing and/or physical or occupational therapy for posthospitalization care. We assessed preadmission activities of daily living and instrumental activities of daily living, health literacy, numeracy, and cognition. Postdischarge phone calls identified medication errors and medication reconciliation efforts by home healthcare clinicians. Veterans Administration-based community health nurses completed surveys about content and timing of postdischarge interactions with home healthcare clinicians. We determined the types and frequency of medication errors among older Veterans receiving home healthcare, patient-provider communication patterns in this setting, and patient characteristics affecting medication error rates. Most Veterans (24/30, 80%) had at least one discordant medication, and only one noted that errors were identified and resolved. Veterans were asked about medications in the home healthcare setting, but far fewer were questioned about medication-taking details, adherence, and as-needed or nonoral medications. Higher numeracy was associated with fewer errors. Veterans Administration community health nurses reported contact by home healthcare clinicians in 41% of cases (7/17). Given the high rate of medication errors discovered, future work should focus on implementing best practices for medication review in this setting, as well as documenting barriers/facilitators of patient-provider communication.

Improving the design of heart failure care from the perspective of frontline providers and administrators: A qualitative case study of a large, urban health system

BACKGROUND

Heart failure patients often present with frailty and/or multi-morbidity, complicating care and service delivery. The Chronic Care Model (CCM) is a useful framework for designing care for complex patients. It assumes responsibility of several actors, including frontline providers and health-care administrators, in creating conditions for optimal chronic care management. This qualitative case study examines perceptions of care among providers and administrators in a large, urban health system in Canada, and how the CCM might inform redesign of care to improve health system functioning.

METHODS

Sixteen semi-structured interviews were conducted between August 2014 and January 2016. Interpretive analysis was conducted to identify how informants perceive care among this population and the extent to which the design of heart failure care aligns with elements of the CCM.

RESULTS

Current care approaches could better align with CCM elements. Key changes to improve health system functioning for complex heart failure patients that align with the CCM include closing knowledge gaps, standardizing treatment, improving interdisciplinary communication and improving patient care pathways following hospital discharge.

CONCLUSIONS

The CCM can be used to guide health system design and interventions for frail and multi-morbid heart failure patients. Addressing care- and service-delivery barriers has important clinical, administrative and economic implications.

Helping Older Adults Improve Their Medication Experience (HOME) by Addressing Medication Regimen Complexity in Home Healthcare

In skilled home healthcare (SHHC), communication between nurses and physicians is often inadequate for medication reconciliation and needed changes to the medication regimens are rarely made. Fragmentation of electronic health record (EHR) systems, transitions of care, lack of physician-nurse in-person contact, and poor understanding of medications by patients and their families put patients at risk for serious adverse outcomes. The aim of this study was to develop and test the HOME tool, an informatics tool to improve communication about medication regimens, share the insights of home care nurses with physicians, and highlight to physicians and nurses the complexity of medication schedules. We used human computer interaction design and evaluation principles, automated extraction from standardized forms, and modification of existing EHR fields to highlight key medication-related insights that had arisen during the SHHC visit. Separate versions of the tool were developed for physicians/nurses and patients/caregivers. A pilot of the tool was conducted using 20 SHHC encounters. Home care nurses and physicians found the tool useful for communication. Home care nurses were able to implement the HOME tool into their clinical workflow and reported improved communication with physicians about medications. This simple and largely automated tool improves understanding and communication around medications in SHHC.

Using electronic health record data for environmental and place based population health research: a systematic review

PURPOSE

We conducted a systematic review of literature published on January 2000-May 2017 that spatially linked electronic health record (EHR) data with environmental information for population health research.

METHODS

We abstracted information on the environmental and health outcome variables and the methods and data sources used.

RESULTS

The automated search yielded 669 articles; 128 articles are included in the full review. The number of articles increased by publication year; the majority (80%) were from the United States, and the mean sample size was approximately 160,000. Most articles used cross-sectional (44%) or longitudinal (40%) designs. Common outcomes were health care utilization (32%), cardiometabolic conditions/obesity (23%), and asthma/respiratory conditions (10%). Common environmental variables were sociodemographic measures (42%), proximity to medical facilities (15%), and built environment and land use (13%). The most common spatial identifiers were administrative units (59%), such as census tracts. Residential addresses were also commonly used to assign point locations, or to calculate distances or buffer areas.

CONCLUSIONS

Future research should include more detailed descriptions of methods used to geocode addresses, focus on a broader array of health outcomes, and describe linkage methods. Studies should also explore using longitudinal residential address histories to evaluate associations between time-varying environmental variables and health outcomes.

Iranian Physicians' Perspectives Regarding Nurse-Physician Professional Communication: Implications for Nurses

BACKGROUND AND PURPOSE

Nurse-physician professional communication affects the effectiveness and performance of the health care team and the quality of care delivered to the patient. This study aimed to explore the perspectives and experiences of physicians on nurse-physician professional communication in an urban area of Iran.

METHODS

Semistructured interviews were conducted with 15 physicians selected using a purposive sampling method. Physicians from different medical specialties were chosen from 4 teaching hospitals in an urban area of Iran. The data were analyzed with content analysis and themes developed.

RESULTS

Three themes developed during data analysis: "seeking the formal methods of communication to ensure patient care," "nurses' professional attributes for professional communication," and "patients' health conditions as the mediators of professional communication."

IMPLICATIONS FOR PRACTICE

Nurses need to be informed of the perspectives and experiences of physicians on professional communication. Our findings can improve nurses' understandings of professional communication that could inform the development of educational and training programs for nurses and physicians. There is a need to incorporate communication courses during degree education and design interprofessional training regarding communication in clinical settings to improve teamwork and patient care. Open discussions between nurses and physicians, training sessions about how to improve their knowledge about barriers to and facilitators of effective professional communication, and key terms and phrases commonly used in patient care are suggested.

Home Health Care: Nurse-Physician Communication, Patient Severity, and Hospital Readmission

OBJECTIVE

To evaluate whether communication failures between home health care nurses and physicians during an episode of home care after hospital discharge are associated with hospital readmission, stratified by patients at high and low risk of readmission.

DATA SOURCE/STUDY SETTING

We linked Visiting Nurse Services of New York electronic medical records for patients with congestive heart failure in 2008 and 2009 to hospitalization claims data for Medicare fee-for-service beneficiaries.

STUDY DESIGN

Linear regression models and a propensity score matching approach were used to assess the relationship between communication failure and 30-day readmission, separately for patients with high-risk and low-risk readmission probabilities.

DATA COLLECTION/EXTRACTION METHODS

Natural language processing was applied to free-text data in electronic medical records to identify failures in communication between home health nurses and physicians.

PRINCIPAL FINDINGS

Communication failure was associated with a statistically significant 9.7 percentage point increase in the probability of a patient readmission (32.6 percent of the mean) among high-risk patients.

CONCLUSIONS

Poor communication between home health nurses and physicians is associated with an increased risk of hospital readmission among high-risk patients. Efforts to reduce readmissions among this population should consider focusing attention on this factor.

Older Adults and Management of Medical Devices in the Home: Five Requirements for Appropriate Use

Medical devices, or instruments or tools to manage disease, are increasingly used in the home, yet there have been limited evaluations of how older adults and caregivers safely use these devices. This study concerns a qualitative evaluation of (1) barriers and facilitators of appropriate use, and (2) outcomes of inappropriate use, among older adults at the transition from hospital to home with skilled home health care (SHHC). Guided by a human factors engineering work system model, the authors (1) conducted direct observations with contextual inquiry of the start-of-care or resumption-of-care SHHC provider visit, and (2) semi-structured interviews with 24 older adults and their informal caregivers, and 39 SHHC providers and administrators. Five requirements for the appropriate use of home medical devices were identified. A systems approach integrating the hospital with the SHHC agency is needed to make the use of home medical devices safer.

Evaluation of an Electronic Module for Reconciling Medications in Home Health Plans of Care

OBJECTIVES

Transitions in patient care pose an increased risk to patient safety. One way to reduce this risk is to ensure accurate medication reconciliation during the transition. Here we present an evaluation of an electronic medication reconciliation module we developed to reduce the transition risk in patients referred for home healthcare.

METHODS

Nineteen physicians with experience in managing home health referrals were recruited to participate in this within-subjects experiment. Participants completed medication reconciliation for three clinical cases in each of two conditions. The first condition (paper-based) simulated current practice - reconciling medication discrepancies between a paper plan of care (CMS 485) and a simulated Electronic Health Record (EHR). For the second condition (electronic) participants used our medication reconciliation module, which we integrated into the simulated EHR. To evaluate the effectiveness of our medication reconciliation module, we employed repeated measures ANOVA to test the hypotheses that the module will: 1) Improve accuracy by reducing the number of unaddressed medication discrepancies, 2) Improve efficiency by reducing the reconciliation time, 3) have good perceived usability.

RESULTS

The improved accuracy hypothesis is supported. Participants left more discrepancies unaddressed in the paper-based condition than the electronic condition, F (1,1) = 22.3, p < 0.0001 (Paper Mean = 1.55, SD = 1.20; Electronic Mean = 0.45, SD = 0.65). However, contrary to our efficiency hypothesis, participants took the same amount of time to complete cases in the two conditions, F (1, 1) =0.007, p = 0.93 (Paper Mean = 258.7 seconds, SD = 124.4; Electronic Mean = 260.4 seconds, SD = 158.9). The usability hypothesis is supported by a composite mean ability and confidence score of 6.41 on a 7-point scale, 17 of 19 participants preferring the electronic system and an SUS rating of 86.5.

CONCLUSION

We present the evaluation of an electronic medication reconciliation module that increases detection and resolution of medication discrepancies compared to a paper-based process. Further work to integrate medication reconciliation within an electronic medical record is warranted.

Development and testing of the Dementia Symptom Management at Home (DSM-H) program: An interprofessional home health care intervention to improve the quality of life for persons with dementia and their caregivers

Home health care agencies are increasingly taking care of sicker, older patients with greater comorbidities. However, they are unequipped to appropriately manage these older adults, particular persons living with dementia (PLWD). We therefore developed the Dementia Symptom Management at Home (DSM-H) Program, a bundled interprofessional intervention, to improve the care confidence of providers, and quality of care delivered to PLWD and their caregivers. We implemented the DSM-H with 83 registered nurses, physical therapists, and occupational therapists. Overall, there was significant improvement in pain knowledge (5.9%) and confidence (26.5%), depression knowledge (14.8%) and confidence (36.1%), and neuropsychiatric symptom general knowledge (16.8%), intervention knowledge (20.9%), attitudes (3.4%) and confidence (27.1%) at a statistical significance of (P < .0001). We also found significant differences between disciplines. Overall, this disseminable program proved to be implementable and improve clinician's knowledge and confidence in caring for PLWD, with the potential to improve quality of care and quality of life, and decrease costs.