Dataset Information

Comparison of learning needs priorities between healthcare providers and patients with heart failure.

ABSTRACT: It is necessary to understand the learning needs of heart failure (HF) patients to provide adequate patient education. It is necessary to identify what HF patients want to know and how this differs from the educational needs of healthcare providers. The aim of this descriptive and exploratory study was to evaluate and compare the learning needs priorities between HF patients and their healthcare providers. One hundred patients with HF and 20 healthcare providers were recruited from cardiovascular outpatient clinics at 2 large tertiary medical centers in South Korea. Learning needs were measured using a self-administered questionnaire with the Heart Failure Patients' Learning Needs Inventory. Data were analyzed using SPSS 23.0 program. Overall rank orders for 48 items were similar in both groups (Spearman rank order correlation 0.605, p < .001). The educational topics of medications and worsening signs and symptoms ranked highest in both groups. However, healthcare providers were more concerned with diet management than were the patients (mean score 4.18 vs. 3.62; p = .001). The study showed both similarities and differences between the assessments of the patients and healthcare providers of detailed educational learning needs. It is important to develop patient-centered educational materials considering HF patients' actual learning needs, and also to provide comprehensive and practical patient education based on a supportive understanding of healthcare provider needs.

SUBMITTER: Min D

PROVIDER: S-EPMC7514042 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comparison of learning needs priorities between healthcare providers and patients with heart failure.

Min Deulle D Park Jin-Sun JS Choi Eui-Young EY Ahn Jeong-Ah JA

PloS one 20200924 9

It is necessary to understand the learning needs of heart failure (HF) patients to provide adequate patient education. It is necessary to identify what HF patients want to know and how this differs from the educational needs of healthcare providers. The aim of this descriptive and exploratory study was to evaluate and compare the learning needs priorities between HF patients and their healthcare providers. One hundred patients with HF and 20 healthcare providers were recruited from cardiovascula ...[more]

PMID: 32970770

Similar Datasets

Project description:BackgroundSevere combined immunodeficiency (SCID) is a group of life-threatening genetic disorders responsible for severe dysfunctions of the immune system. Despite the expansion of newborn screening in the U.S., there are gaps in healthcare providers' knowledge of SCID.MethodsWe recruited 277 U.S. healthcare providers for an online survey. The survey assessed providers' experience with SCID patients, knowledge about SCID, and needs and preferred formats for SCID-related informational resources. We examined differences between providers who have seen 2 or more patients with SCID (SCID provider group) and those who have seen 0-1 SCID patients (non-SCID provider group).ResultsOverall, 210 (75.8%) providers were included in the non-SCID provider group, and 121 (57.6%) of these providers were pediatricians. Compared to the SCID provider group, non-SCID provider group reported lower mean rating of SCID knowledge (x̄ = 4.8 vs. x̄ = 8.6, p < 0.0001) and higher informational needs. The largest informational needs identified by the non-SCID provider group were "understanding specific type of SCID" and "understanding what to expect across the lifespan." In the SCID provider group, the highest rated informational need was "family support referrals." Participants in the non-SCID provider group identified scientific publications and websites as preferred formats, with some variation between medical specialties.ConclusionBased on their experience with treating SCID patients, providers have varying levels of SCID knowledge and different informational needs. For providers who have encountered few SCID patients, informational needs start early, usually immediately after receiving a positive newborn screening result. These findings provide useful direction for the development and preferred outlets for receiving SCID-related information, with some variations between different types of providers. Results from this study will serve as a guide for creating relevant and accessible SCID resources for providers who can utilize them to improve care for SCID patients.

Project description:BackgroundThere are increasing calls to establish heart failure (HF) clinics due to their effectiveness in the interdisciplinary management of people living with HF. However, although a recommendation exists for palliative care (PC) providers to be part of the interdisciplinary team, few of the established HF clinics include them in their teams. Therefore, in this qualitative study, we aimed to understand the unmet PC needs of patients with HF attending an already established HF clinic.MethodsSecondary qualitative analysis of structured interviews undertaken within a larger study to validate the German version of the Needs Assessment Tool: Progressive Disease-Heart Failure (NAT: PD-HF). The NAT: PD-HF is a tool that aims to assess unmet needs in patients with HF. The interviews took place between January and March 2020 with patients from the ambulatory HF Clinic of a University Hospital in Switzerland. For this analysis, we transcribed and thematically analyzed the longest and most content-rich interviews until we reached data saturation at 31 participants. The interviews lasted 31 min on average (24-48 min).ResultsParticipants (n = 31) had a median age of 64 years (IQR 56-77), the majority had reduced ejection fraction, were men, and were classified as having a New York Heart Association functional class II. Participants were in general satisfied with the treatment and information received at the HF clinic. However, they reported several unmet needs. We therefore identified three ambivalences as main themes: (I) "feeling well-informed but missing essential discussions", (II) "although feeling mostly satisfied with the care, remaining with unmet care needs", and (III) "fearing a referral to palliative care but acknowledging its importance".ConclusionAlthough patients who are receiving multidisciplinary management in ambulatory HF clinics are generally satisfied with the care received, they remain with unmet needs. These unmet needs, such as the need for advance care planning or the need for timely and tactful end-of-life discussions, can be fulfilled by PC providers. Including personnel trained in PC as part of the multidisciplinary team could help to address patients' needs, thus improving the quality of care and the quality of life of people living with HF.

Project description:IntroductionUnrecognized pain in the Intensive Care Unit (ICU), due to inadequate assessment and therapeutic management, is associated with increased morbidity and mortality. Despite the availability of validated pain monitoring tools, such as the Critical-Care Pain Observational Tool (CPOT), these scales are not commonly used in clinical practice, with healthcare professionals often relying on their clinical impression. Our study aims to determine the agreement between the pain examination performed by ICU professionals and the CPOT.MethodsProspective cohort study that included critically ill patients and physicians, nurses and physiotherapists from an ICU in Bahia, Brazil. During bedside clinical rounds, the CPOT score was applied to assess the pain of hospitalized patients, and health professionals were interviewed to ascertain their perception of the patient's pain for a maximum of five consecutive days. Correlations were assessed using the Spearman rank tests. Hierarchical cluster analysis was employed to show the results of CPOT score and pain assessment by healthcare professionals at each study time. And the Kappa statistic was calculated to assess the agreement between the CPOT score vs. the pain assessment by healthcare providers.ResultsOne hundred one patients were included in the study with median age of 74 years (IQR 61.5-83.5), a predominance of women (55.4%) and a median SAPS 3 score of 45 (IQR 39.5-53.0). The correlation between the professional's pain assessment and the CPOT were mostly statistically significant, ranged from negligible to weak, being the highest index obtained in the evaluation of nurses on day 5 (Kappa index = 0.43, p = 0.005). Physician assessments were significant only in day 1. On the presence of pain, the professionals' assessments and CPOT revealed mild to a moderate agreement.ConclusionHealthcare professional's pain assessment displayed a weak positive correlation with a validated pain scale and poor agreement amongst members of the ICU team, particularly when the pain was felt to be absent. Thus, this study highlights the importance of routine tools for pain assessment in the ICU for all members of multidisciplinary teams.

Project description:BackgroundHeart failure (HF) is highly prevalent in the United States. Approximately one-third to one-half of HF cases are categorized as HF with reduced ejection fraction (HFrEF). Patients with HFrEF are at risk of worsening HF, have a high risk of adverse outcomes, and experience higher health care use and costs. Therefore, it is crucial to identify patients with HFrEF who are at high risk of subsequent events after HF hospitalization.ObjectiveMachine learning (ML) has been used to predict HF-related outcomes. The objective of this study was to compare different ML prediction models and feature construction methods to predict 30-, 90-, and 365-day hospital readmissions and worsening HF events (WHFEs).MethodsWe used the Veradigm PINNACLE outpatient registry linked to Symphony Health's Integrated Dataverse data from July 1, 2013, to September 30, 2017. Adults with a confirmed diagnosis of HFrEF and HF-related hospitalization were included. WHFEs were defined as HF-related hospitalizations or outpatient intravenous diuretic use within 1 year of the first HF hospitalization. We used different approaches to construct ML features from clinical codes, including frequencies of clinical classification software (CCS) categories, Bidirectional Encoder Representations From Transformers (BERT) trained with CCS sequences (BERT + CCS), BERT trained on raw clinical codes (BERT + raw), and prespecified features based on clinical knowledge. A multilayer perceptron neural network, extreme gradient boosting (XGBoost), random forest, and logistic regression prediction models were applied and compared.ResultsA total of 30,687 adult patients with HFrEF were included in the analysis; 11.41% (3184/27,917) of adults experienced a hospital readmission within 30 days of their first HF hospitalization, and nearly half (9231/21,562, 42.81%) of the patients experienced at least 1 WHFE within 1 year after HF hospitalization. The prediction models and feature combinations with the best area under the receiver operating characteristic curve (AUC) for each outcome were XGBoost with CCS frequency (AUC=0.595) for 30-day readmission, random forest with CCS frequency (AUC=0.630) for 90-day readmission, XGBoost with CCS frequency (AUC=0.649) for 365-day readmission, and XGBoost with CCS frequency (AUC=0.640) for WHFEs. Our ML models could discriminate between readmission and WHFE among patients with HFrEF. Our model performance was mediocre, especially for the 30-day readmission events, most likely owing to limitations of the data, including an imbalance between positive and negative cases and high missing rates of many clinical variables and outcome definitions.ConclusionsWe predicted readmissions and WHFEs after HF hospitalizations in patients with HFrEF. Features identified by data-driven approaches may be comparable with those identified by clinical domain knowledge. Future work may be warranted to validate and improve the models using more longitudinal electronic health records that are complete, are comprehensive, and have a longer follow-up time.

Dataset Information

Comparison of learning needs priorities between healthcare providers and patients with heart failure.

Publications

Comparison of learning needs priorities between healthcare providers and patients with heart failure.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets