An integrative review and theoretical examination of chronic illness mHealth studies using the Middle-Range Theory of Self-care of Chronic Illness.

Self-management, or self-care, by individuals and/or families is a critical element in chronic illness management as more care shifts to the home setting. Mobile device-enhanced health care, or mHealth, is being touted as a means to support self-care. Previous mHealth reviews examined the effect of mHealth on patient outcomes, however, none used a theoretical lens to examine the interventions themselves. The aims of this integrative review were to examine recent (e.g., last 10 years) chronic illness mHealth empiric studies and (1) categorize self-care behaviors engaged in the intervention according to the Middle-Range Theory of Self-care of Chronic Illness, and (2) conduct an analysis of gaps in self-care theory domains and behaviors utilized. Methods included: (1) Best practice study identification, collection, and data extraction procedures and (2) realist synthesis techniques for within and across case analysis. From a pool of 652 records, 33 primarily North American clinical trials, published between 2010 and 2019 were examined. Most mHealth interventions used apps, clinician contact, and behavioral prompts with some wireless devices. Examination found self-care maintenance behaviors were supported in most (n = 30) trials whereas self-care monitoring (n = 12) and self-care management behaviors (n = 8) were less so. Few trials (n = 2) targeted all three domains. Investigation of specific behaviors uncovered an overexamination of physical activity and diet behaviors and an underexamination of equally important behaviors. By examining chronic illness mHealth interventions using a theoretical lens we have categorized current interventions, conducted a gap analysis uncovering areas for future study, and made recommendations to move the science forward.

Preparing for the Improving Medicare Post-Acute Care Transformation Act: Incorporating A Sociotechnical Perspective to Enhance a Health Information Technology Evaluation Framework Applied to Post-Acute Care.

The Improving Medicare Post-Acute Care Transformation Act, which mandates electronic sharing of standardized patient data by post-acute care clinical settings, will likely spur further health information technology adoption and evaluation. To support evaluation, the study objective was to clarify components of an evidence-based health information technology evaluation framework, Health Information Technology Reference-based Evaluation Framework, by using the framework in home healthcare and incorporating a sociotechnical perspective in the health information technology evaluation. With 36 observations among three diverse home healthcare agencies, researchers conducted a recorded think-aloud process as nurses documented the home healthcare admission in the EHR. Thematic analysis revealed 15 themes that provided clarification for almost one-third of Health Information Technology Reference-based Evaluation Framework components and added a new concept. All themes reflected a sociotechnical perspective. The new theme added to the Health Information Technology Reference-based Evaluation Framework reflected the sociotechnical perspective: routine use. We anticipate the enhanced Health Information Technology Reference-based Evaluation Framework to be used by evaluators from diverse disciplines, to further facilitate context-dependent health information technology adoption in post-acute care settings.

Planning the Episode: Home Care Admission Nurse Decision-Making Regarding the Patient Visit Pattern.

During home health care (HHC) admissions, nurses provide input into decisions regarding the skilled nursing visit frequency and episode duration. This important clinical decision can impact patient outcomes including hospitalization. Episode duration has recently gained greater importance due to the Centers for Medicare and Medicaid Services (CMS) decrease in reimbursable episode length from 60 to 30 days. We examined admissions nurses' visit pattern decision-making and whether it is influenced by documentation available before and during the first home visit, agency standards, other disciplines being scheduled, and electronic health record (EHR) use. This observational mixed-methods study included admission document analysis, structured interviews, and a think-aloud protocol with 18 nurses from 3 diverse HHC agencies (6 at each) admitting 2 patients each (36 patients). Findings show that prior to entering the home, nurses had an information deficit; they either did not predict the patient's visit frequency and episode duration or stated them based on experience with similar patients. Following patient interaction in the home, nurses were able to make this decision. Completion of documentation using the EHR did not appear to influence visit pattern decisions. Patient condition and insurance restrictions were influential on both frequency and duration. Given the information deficit at admission, and the delay in visit pattern decision making, we offer health information technology recommendations on electronic communication of structured information, and EHR documentation and decision support.

Impact of Home Care Admission Nurses' Goals on Electronic Health Record Documentation Strategies at the Point of Care.

Home care nurses have multiple goals at the patient admission visit. Electronic health records support some of these goals, including high-quality documentation, but nurses may not complete the electronic documentation at the point of care. To characterize admission nurses' practices at the point of care and lay the foundation for design recommendations, this study investigates admission nurses' documentation strategies with respect to entering electronic data and how nursing goals affect them. We conducted 10 observations of home care agency admissions with five admission nurses in rural Pennsylvania. We collected screenshots and recorded the admission process. We asked the nurses questions outside the point of care. We coded the nurses' strategies at the data-entry screen level. Using thematic analysis, we investigated the influence of nursing goals on documentation strategies. Subject matter experts reviewed our findings. Several goals affect nurses' documentation strategies: ensure data accuracy, reduce time in the patient's home, and prevent infection. Home care admission nurses distribute the electronic documentation temporally due to their goals. Nurses developed memory aids to support completion of the documentation after leaving the patients' homes. Design and training should support the distributed manner in which home care nurses document patient encounters.

Challenges and facilitators to adoption of a point-of-care electronic health record in home care.

Electronic health records (EHRs), intended to improve the clinical process, are understudied in home care. The researchers assessed clinician satisfaction, informed by workflow and patient outcomes, to identify EHR adoption challenges. The mixed methods study setting was a Philadelphia agency with 137 clinicians. Adoption challenges included: (a) hardware problems coupled with lack of field support; (b) inadequate training; and (c) mismatch of EHR usability/functionality and workflow resulting in decreased efficiency. Adoption facilitators were support for team communication and improved clinical data timeliness. Opportunities for improved adoption included sharing with front-line clinicians EHR data related to patient care and health outcomes.

Challenges and facilitators to nurse use of a guideline-based nursing information system: recommendations for nurse executives.

AIMS: The aims of this study were to develop empirical data on how nurses used an evidenced-based nursing information system (NIS) and to identify challenges and facilitators to NIS adoption for nurse leaders. BACKGROUND: The NIS was part of the electronic health record with 200 evidence-based, interdisciplinary clinical practice guidelines from which clinicians selected to guide the patient's care. METHODS: A purposeful sample of 12 randomly selected nurses in three units across two hospitals participated in scenario-testing. Sessions were audio-recorded, transcribed, content analyzed, and coded for themes. RESULTS: Major themes emerged: computer placement in patient rooms; difficulty using NIS; documentation completeness; efficiency; time spent at the bedside; team communication; training; unintended consequences of workflow changes; perceived NIS value as challenge to adoption. CONCLUSIONS: Nurse executives' opportunities to improve adoption include enhancing communication to/from front-line clinicians about the hospitals' goals, perceived NIS value at the bedside, and constructive feedback especially for patient care/safety and software functionality.

Social Determinants of Health Screening, Referral, and Outcomes: Toward an Evidence-Based Simulation Model.

A more complete conceptual model of the social determinants of health (SDOH) screening and referral process is needed to identify effective interventions to address unmet social needs that impact health outcomes. The objective was to develop an evidence-based, complex, multi-factorial model that makes explicit the behaviors and experiences of both patients and the care team (factors) who use an SDOH platform to facilitate patient connections to community resources. The resulting model organized 88 factors among five main stages in the process and among health outcomes. Factors were grouped into eight categories among person, system, and organization levels. Most factors were related to the screening process, with sparse factors related to referral completion. The resulting model is offered as an initial step toward the development of a simulation model to assess interventions before implementation in real-world settings.

Artificial Intelligence in Nursing: Perspectives from Norwegian Nurses.

Nurses continue to face challenges in leading health information technology innovations such as Artificial Intelligence (AI). There is an acknowledged need to explore the attitude of nurses towards AI and nurses' acceptance of AI in clinical settings. We sought to address this gap in knowledge about the perceptions of AI by nursing-related professionals in their work and as a content area in the education of nursing students. Norwegian nurses and healthcare personnel interested in the topic met in a seminar in Oslo in 2023 to explore their perspectives on AI. Following a lecture on AI, audience members offered their insights in a recorded discussion. Data analysis consisted of inductive coding of concepts in the transcribed recording. Three major themes emerged: Expectations, Identified needs and related recommendations; and Policy to guard safety; as well as recommendations new to the literature.

A comparison of electronic health records at two major Peking University Hospitals in China to United States meaningful use objectives.

BACKGROUND: In accordance with the People's Republic of China's (China) National Health Reform Plan of 2009, two of the nation's leading hospitals, located in Beijing, have implemented electronic medical record (EMR) systems from different vendors.To inform future EMR adoption and policy in China, as well as informatics research in the US, this study compared the United State's Hospital Meaningful Use (MU) Objectives (phase 1) objectives to the EMR functionality of two early hospital EMR adopters in China. METHODS: At both hospitals, the researchers observed a physician using the EMR and noted MU functionality that was seen and functionality that was not seen yet was available in the EMR. The information technology department was asked about the availability of functionality neither observed nor known to the physician. RESULTS AND CONCLUSIONS: Approximately half the MU objectives were available in each EMR. Some differences between the EMRs in the study and MU objectives were attributed to operational differences between the health systems and the cultures in the two countries.

Community-based, interdisciplinary geriatric care team satisfaction with an electronic health record: a multimethod study.

This multimethod study measured the impact of an electronic health record (EHR) on clinician satisfaction with clinical process. Subjects were 39 clinicians at a Program of All-inclusive Care for Elders (PACE) site in Philadelphia utilizing an EHR. Methods included the evidence-based evaluation framework, Health Information Technology Research-Based Evaluation Framework, which guided assessment of clinician satisfaction with surveys, observations, follow-up interviews, and actual EHR use at two points in time. Mixed-methods analysis of findings provided context for interpretation and improved validity. The study found that clinicians were satisfied with the EHR; however, satisfaction declined between time periods. Use of EHR was universal and wide and was differentiated by clinical role. Between time periods, EHR use increased in volume, with increased timeliness and decreased efficiency. As the first EHR evaluation at a PACE site from the perspective of clinicians who use the system, this study provides insights into EHR use in the care of older people in community-based healthcare settings.

Addressing the Gap in Data Communication from Home Health Care to Primary Care during Care Transitions: Completeness of an Interoperability Data Standard.

In a future where home health care is no longer an information silo, patient information will be communicated along transitions in care to improve care. Evidence-based practice in the United States supports home health care patients to see their primary care team within the first two weeks of hospital discharge to reduce rehospitalization risk. We sought to identify a parsimonious set of home health care data to be communicated to primary care for the post-hospitalization visit. Anticipating electronic dataset communication, we investigated the completeness of the international reference terminology, Logical Observation Identifiers Names and Codes (LOINC), for coverage of the data to be communicated. We conducted deductive qualitative analysis in three steps: (1) identify home health care data available for the visit by mapping home health care to the information needed for the visit; (2) reduce the resulting home health care data set to a parsimonious set clinicians wanted for the post-hospitalization visit by eliciting primary care clinician input; and (3) map the parsimonious dataset to LOINC and assess LOINC completeness. Our study reduced the number of standardized home health care assessment questions by 40% to a parsimonious set of 33 concepts that primary care team physicians wanted for the post-hospitalization visit. Findings indicate all home health care concepts in the parsimonious dataset mapped to the information needed for the post-hospitalization visit, and 84% of the home health care concepts mapped to a LOINC term. The results indicate data flow of parsimonious home health care dataset to primary care for the post-hospitalization visit is possible using existing LOINC codes, and would require adding some codes to LOINC for communication of a complete parsimonious data set.

Risk of Rehospitalization or Emergency Department Visit is Significantly Higher for Patients who Receive Their First Home Health Care Nursing Visit Later than 2 Days After Hospital Discharge.

OBJECTIVES: This study explored the association between the timing of the first home health care nursing visits (start-of-care visit) and 30-day rehospitalization or emergency department (ED) visits among patients discharged from hospitals. DESIGN: Our cross-sectional study used data from 1 large, urban home health care agency in the northeastern United States. SETTING/PARTICIPANTS: We analyzed data for 49,141 home health care episodes pertaining to 45,390 unique patients who were admitted to the agency following hospital discharge during 2019. METHODS: We conducted multivariate logistic regression analyses to examine the association between start-of-care delays and 30-day hospitalizations and ED visits, adjusting for patients' age, race/ethnicity, gender, insurance type, and clinical and functional status. We defined delays in start-of-care as a first nursing home health care visit that occurred more than 2 full days after the hospital discharge date. RESULTS: During the study period, we identified 16,251 start-of-care delays (34% of home health care episodes), with 14% of episodes resulting in 30-day rehospitalization and ED visits. Delayed episodes had 12% higher odds of rehospitalization or ED visit (OR 1.12; 95% CI: 1.06-1.18) compared with episodes with timely care. CONCLUSIONS AND IMPLICATIONS: The findings suggest that timely start-of-care home health care nursing visit is associated with reduced rehospitalization and ED use among patients discharged from hospitals. With more than 6 million patients who receive home health care services across the United States, there are significant opportunities to improve timely care delivery to patients and improve clinical outcomes.

A new instrument for measuring clinician satisfaction with electronic health records.

A new survey instrument was developed and validated to measure clinician (nurse) satisfaction with electronic health record impact on clinical process. The Health Information Technology Reference-Based Evaluation Framework guided the selection of evaluation dimensions for the survey. Survey questions were gathered from existing health information technology satisfaction surveys that reflected individual evaluation concepts, such as efficiency or benefits. Decisions about data-gathering methods (e.g., item selection) were made based on reviews of literature and surveys of clinician satisfaction with health information technology and expert input. Preliminary instrument validation was accomplished using qualitative and statistical analysis of five repeated sets of responses from clinicians at the pilot site and field administrations repeated twice at electronic health record implementation and paper-based comparison sites and by analyzing convergent evidence from observations and interviews. Reliability was assessed on one sample: 30 graduate nursing students at the single pilot site. Validity was assessed on three separate samples: (1) graduate nursing students (n = 30), (2) field test at a site with electronic health record (n = 39 participants), and (3) field test at a paper-based site (n = 17). The implementation and comparison sites are Program of All-Inclusive Care for the Elderly that provide managed day care for frail elderly. Survey responses were assessed for test-retest reliability, internal consistency, and content and construct validity. The instrument design enables its administration before and after electronic health record implementation. Work to date suggests the instrument is reliable and valid; it is offered to electronic health record evaluators for further testing and application.

Transitions of Care: Completeness of the Interoperability Data Standard for Communication from Home Health Care to Primary Care.

Data sharing is necessary to address communication deficits along the transitions of care among community settings. Evidence-based practice supports home healthcare (HHC) patients to see their primary care team within the first two weeks of hospital discharge to reduce rehospitalization risk. A small subset of patient data collected at HHC admission is mandated to be transmitted to primary care, predominantly by fax. Using qualitative analysis, we assessed completeness of the United States Core Data for Interoperability (USCDI) interoperability standard, as compared to the patient data collected by the primary care team (topics) and HHC (classes) during the initial visit; and offer interoperability recommendations. Findings indicate the USCDI does not cover 74% of the 19 faxed HHC classes that mapped to the primary care topics, and 95% of the 38 not-faxed HHC classes. We offer USCDI recommendations to address these interoperability gaps.

An integrative review of chronic illness mHealth self-care interventions: Mapping technology features to patient outcomes.

Mobile health (mHealth)-hand-held technologies to address health priorities-has significant potential to answer the growing need for patient chronic illness self-care interventions. Previous reviews examined mHealth effect on patient outcomes. None have a detailed examination and mapping of specific technology features to targeted health outcomes. Examine recent chronic illness mHealth self-care interventions; map the study descriptors, mHealth technology features, and study outcomes. (1) Information extracted from PubMed, CINAHL, and Web of Science databases for clinical outcomes studies published 2010-January 2020; and (2) realist synthesis techniques for within and across case analysis. From 652 records, 32 studies were examined. Median study duration was 19.5 weeks. Median sample size was 62 participants. About 47% of interventions used solely patient input versus digital input; 50% sent tailored messages versus generic messages; 22% augmented the intervention with human interaction. Studies with positive clinical outcomes had higher use of digital input. Software descriptions were lacking. Most studies built interventions: only two incorporated target audience participation in development. We recommend researchers provide sufficient system description detail. Future research includes: data input characteristics; impact of augmentation with human interaction on outcomes; and development decisions.

Exploring Reasons for Delayed Start-of-Care Nursing Visits in Home Health Care: Algorithm Development and Data Science Study.

BACKGROUND: Delayed start-of-care nursing visits in home health care (HHC) can result in negative outcomes, such as hospitalization. No previous studies have investigated why start-of-care HHC nursing visits are delayed, in part because most reasons for delayed visits are documented in free-text HHC nursing notes. OBJECTIVE: The aims of this study were to (1) develop and test a natural language processing (NLP) algorithm that automatically identifies reasons for delayed visits in HHC free-text clinical notes and (2) describe reasons for delayed visits in a large patient sample. METHODS: This study was conducted at the Visiting Nurse Service of New York (VNSNY). We examined data available at the VNSNY on all new episodes of care started in 2019 (N=48,497). An NLP algorithm was developed and tested to automatically identify and classify reasons for delayed visits. RESULTS: The performance of the NLP algorithm was 0.8, 0.75, and 0.77 for precision, recall, and F-score, respectively. A total of one-third of HHC episodes (n=16,244) had delayed start-of-care HHC nursing visits. The most prevalent identified category of reasons for delayed start-of-care nursing visits was no answer at the door or phone (3728/8051, 46.3%), followed by patient/family request to postpone or refuse some HHC services (n=2858, 35.5%), and administrative or scheduling issues (n=1465, 18.2%). In 40% (n=16,244) of HHC episodes, 2 or more reasons were documented. CONCLUSIONS: To avoid critical delays in start-of-care nursing visits, HHC organizations might examine and improve ways to effectively address the reasons for delayed visits, using effective interventions, such as educating patients or caregivers on the importance of a timely nursing visit and improving patients' intake procedures.

Factors Associated with Timing of the Start-of-Care Nursing Visits in Home Health Care.

OBJECTIVES: Home health care patients have critical needs requiring timely care following hospital discharge. Although Medicare requires timely start-of-care nursing visits, a significant portion of home health care patients wait longer than 2 days for the first visit. No previous studies investigated the pattern of start-of-care visits or factors associated with their timing. This study's purpose was to examine variation in timing of start-of-care visits and characterize patients with visits later than 2 days postdischarge. DESIGN: Retrospective cohort study. SETTING/PARTICIPANTS: Patients admitted to a large, Northeastern US, urban home health care organization during 2019. The study included 48,497 home care episodes for 45,390 individual patients. MEASUREMENT: We calculated time to start of care from hospital discharge for 2 patient groups: those seen within 2 days vs those seen >2 days postdischarge. We examined patient factors, hospital discharge factors, and timing of start of care using multivariate logistic regression. RESULTS: Of 48,497 episodes, 16,251 (33.5%) had a start-of-care nursing visit >2 days after discharge. Increased odds of this time frame were associated with being black or Hispanic and having solely Medicaid insurance. Odds were highest for patients discharged on Fridays, Saturdays, and Mondays. Factors associated with visits within 2 days included surgical wound presence, urinary catheter, pain, 5 or more medications, and intravenous or infusion therapies at home. CONCLUSIONS AND IMPLICATIONS: Findings provide the first publication of clinical and demographic characteristics associated with home health care start-of-care timing and its variation. Further examination is needed, and adjustments to staff scheduling and improved information transfer are 2 suggested interventions to decrease variation.

Improving Patient Prioritization During Hospital-Homecare Transition: Protocol for a Mixed Methods Study of a Clinical Decision Support Tool Implementation.

BACKGROUND: Homecare settings across the United States provide care to more than 5 million patients every year. About one in five homecare patients are rehospitalized during the homecare episode, with up to two-thirds of these rehospitalizations occurring within the first 2 weeks of services. Timely allocation of homecare services might prevent a significant portion of these rehospitalizations. The first homecare nursing visit is one of the most critical steps of the homecare episode. This visit includes an assessment of the patient's capacity for self-care, medication reconciliation, an examination of the home environment, and a discussion regarding whether a caregiver is present. Hence, appropriate timing of the first visit is crucial, especially for patients with urgent health care needs. However, nurses often have limited and inaccurate information about incoming patients, and patient priority decisions vary significantly between nurses. We developed an innovative decision support tool called Priority for the First Nursing Visit Tool (PREVENT) to assist nurses in prioritizing patients in need of immediate first homecare nursing visits. OBJECTIVE: This study aims to evaluate the effectiveness of the PREVENT tool on process and patient outcomes and to examine the reach, adoption, and implementation of PREVENT. METHODS: Employing a pre-post design, survival analysis, and logistic regression with propensity score matching analysis, we will test the following hypotheses: compared with not using the tool in the preintervention phase, when homecare clinicians use the PREVENT tool, high-risk patients in the intervention phase will (1) receive more timely first homecare visits and (2) have decreased incidence of rehospitalization and have decreased emergency department use within 60 days. Reach, adoption, and implementation will be assessed using mixed methods including homecare admission staff interviews, think-aloud observations, and analysis of staffing and other relevant data. RESULTS: The study research protocol was approved by the institutional review board in October 2019. PREVENT is currently being integrated into the electronic health records at the participating study sites. Data collection is planned to start in early 2021. CONCLUSIONS: Mixed methods will enable us to gain an in-depth understanding of the complex socio-technological aspects of the hospital to homecare transition. The results have the potential to (1) influence the standardization and individualization of nurse decision making through the use of cutting-edge technology and (2) improve patient outcomes in the understudied homecare setting. TRIAL REGISTRATION: ClinicalTrials.gov NCT04136951; https://clinicaltrials.gov/ct2/show/NCT04136951. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/20184.

There's a Problem With the Problem List: Incongruence of Patient Problem Information Across the Home Care Admission.

OBJECTIVES: Illustrate patterns of patient problem information received and documented across the home health care (HHC) admission process and offer practice, policy, and health information technology recommendations to improve information transfer. DESIGN: Observational field study. SETTING AND PARTICIPANTS: Three diverse HHC agencies using different commercial point-of-care electronic health records (EHRs). Six nurses per agency each admitted 2 patients (36 total). METHODS: Researchers observed the admission process and photographed documents and EHR screens across 3 phases: referral, assessment, and plan of care (POC). To create a standardized data set, we mapped terms within medical diagnoses, signs, symptoms, and Problems to 5 of the 42 Omaha System Problem Classification Scheme problem terms. This created 180 problem pattern cases (5 problem patterns per patient). RESULTS: Each pattern of problem information being present or absent was observed. In 52 cases (28.9%), a problem did not appear. In 36 cases (20%), the problem appeared in all 3 phases. In 46 cases (25.6%), the problem appeared in referral and/or assessment phases and not on the POC. Conversely, in 37 cases (20.5%), the problem appeared in referral or assessment phases and on the POC. In 9 cases (5%), the problem only appeared on the POC. Within the EHRs, there were no rationale fields to clarify including Problems or not and no problem status fields to identify active, resolved, or potential ones. CONCLUSIONS AND IMPLICATIONS: Diagnosis or problem information transferred from the referral source or gathered during an in-home assessment did not appear in the POC. Because of the EHR structure, clinicians could not identify inactive problem or problem priority. Documentation or mapping of a structured problem list using a standardized interprofessional terminology such as the Omaha System coupled with identification of rationale could support the documentation of problem status and priority and reduce information loss.

Getting to Complete and Accurate Medication Lists During the Transition to Home Health Care.

OBJECTIVES: Characterize the work that home health care (HHC) admission nurses complete as part of the medication reconciliation tasks, explore the impact of shared electronic medication data (interoperability) from the referral source on medication reconciliation, and highlight opportunities to enhance medication reconciliation with respect to transition in care to HHC agencies. DESIGN: Observational field study. SETTINGS AND PARTICIPANTS: Three diverse Pennsylvania HHC agencies; each used different electronic health record systems with different interoperability characteristics. Six nurses per site admitted 2 patients each (36 patients total). METHODS: Researchers observed the admission process in the patient home and at the HHC agency. The nurses' tasks related to medication reconciliation were characterized by (1) number and change types (ie, medications dropped or added; changes to dose, frequency/administration time, or tablet types) made to the referrer medication list during and after the home visit, and (2) reasons that the nurse called the health provider (doctor, pharmacy) to resolve medication-related issues. Differences between interoperable and non-interoperable observations were explored. RESULTS: Polypharmacy (on average, study patients were taking more than 12 medications) and high-risk medications (on average, more than 8 per patient) were pervasive. For 91% of patients, the number of medications decreased between pre- and post-reconciliation medication lists; 41% of the medications required changes. Nurses using interoperable systems needed to make fewer changes than nurses using non-interoperable systems. In two-thirds of observations, the nurse called a provider. CONCLUSIONS AND IMPLICATIONS: Changes to the referrer medication list and calls to providers highlighted the nurses' effort to complete the medication reconciliation. Interoperability appeared to reduce the number of changes required, but did not eliminate changes or calls to providers. We highlight opportunities to enhance medication reconciliation with respect to transition in care to HHC agencies.