Development and Implementation of the Clinical Decision Support System for Patients With Cancer and Nurses' Experiences Regarding the System

Oncology Nurses' Experiences of Using Health Information Systems in the Delivery of Cancer Care in a Range of Care Settings: A Systematic Integrative Review

OBJECTIVES

This systematic review aimed to identify oncology nurses' experiences of using health information systems (HIS) in the delivery of cancer care.

DATA SOURCES

The electronic databases searched included CINAHL, MEDLINE (EBSCO host), SCOPUS, Web of Science Core Collection, Google Scholar, OVID, and ProQuest Central (using advanced search strategy) and hand searching of reference lists of the included articles and relevant systematic reviews. Studies published in English language were examined.

CONCLUSION

Twenty-six studies were included. Three themes emerged: (1) the transparency and application of the nursing process within HIS, (2) HIS enhancing and facilitating communication between nurses and patients, and (3) the impact of HIS on the elements of person-centered care. Nurses' experiences with HIS were overall positive. However, digital systems do not fully capture all elements of the nursing processes; this was confirmed in this review, through the nurses' lens. Most studies used HIS for symptom reporting and monitoring within non-inpatient settings and largely biomedical and lack insight into the person-centeredness and overall holistic care.

IMPLICATIONS FOR NURSING PRACTICE

There are evidently varied views of HIS adoption across the globe. HIS can improve health-related quality of life and symptom burden, including self-reporting of symptoms among patients. However, there is a need for ongoing high-quality research, and clearer reporting than is evident in the current 26 studies, to fully understand the impact of HIS within the nursing processes and patient outcomes across all specialty cancer fields.

Identifying barriers and facilitators to successful implementation of computerized clinical decision support systems in hospitals: a NASSS framework-informed scoping review

BACKGROUND

Successful implementation and utilization of Computerized Clinical Decision Support Systems (CDSS) in hospitals is complex and challenging. Implementation science, and in particular the Nonadoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) framework, may offer a systematic approach for identifying and addressing these challenges. This review aimed to identify, categorize, and describe barriers and facilitators to CDSS implementation in hospital settings and map them to the NASSS framework. Exploring the applicability of the NASSS framework to CDSS implementation was a secondary aim.

METHODS

Electronic database searches were conducted (21 July 2020; updated 5 April 2022) in Ovid MEDLINE, Embase, Scopus, PyscInfo, and CINAHL. Original research studies reporting on measured or perceived barriers and/or facilitators to implementation and adoption of CDSS in hospital settings, or attitudes of healthcare professionals towards CDSS were included. Articles with a primary focus on CDSS development were excluded. No language or date restrictions were applied. We used qualitative content analysis to identify determinants and organize them into higher-order themes, which were then reflexively mapped to the NASSS framework.

RESULTS

Forty-four publications were included. These comprised a range of study designs, geographic locations, participants, technology types, CDSS functions, and clinical contexts of implementation. A total of 227 individual barriers and 130 individual facilitators were identified across the included studies. The most commonly reported influences on implementation were fit of CDSS with workflows (19 studies), the usefulness of the CDSS output in practice (17 studies), CDSS technical dependencies and design (16 studies), trust of users in the CDSS input data and evidence base (15 studies), and the contextual fit of the CDSS with the user's role or clinical setting (14 studies). Most determinants could be appropriately categorized into domains of the NASSS framework with barriers and facilitators in the "Technology," "Organization," and "Adopters" domains most frequently reported. No determinants were assigned to the "Embedding and Adaptation Over Time" domain.

CONCLUSIONS

This review identified the most common determinants which could be targeted for modification to either remove barriers or facilitate the adoption and use of CDSS within hospitals. Greater adoption of implementation theory should be encouraged to support CDSS implementation.

The Application of Knowledge-Based Clinical Decision Support Systems to Enhance Adherence to Evidence-Based Medicine in Chronic Disease

Among the technology-based solutions, clinical decision support systems (CDSSs) have the ability to keep up with clinicians with the latest evidence in a smart way. Hence, the main objective of our study was to investigate the applicability and characteristics of CDSSs regarding chronic disease. The Web of Science, Scopus, OVID, and PubMed databases were searched using keywords from January 2000 to February 2023. The review was completed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Then, an analysis was done to determine the characteristics and applicability of CDSSs. The quality of the appraisal was assessed using the Mixed Methods Appraisal Tool checklist (MMAT). A systematic database search yielded 206 citations. Eventually, 38 articles from sixteen countries met the inclusion criteria and were accepted for final analysis. The main approaches of all studies can be classified into adherence to evidence-based medicine (84.2%), early and accurate diagnosis (81.6%), identifying high-risk patients (50%), preventing medical errors (47.4%), providing up-to-date information to healthcare providers (36.8%), providing patient care remotely (21.1%), and standardizing care (71.1%). The most common features among the knowledge-based CDSSs included providing guidance and advice for physicians (92.11%), generating patient-specific recommendations (84.21%), integrating into electronic medical records (60.53%), and using alerts or reminders (60.53%). Among thirteen different methods to translate the knowledge of evidence into machine-interpretable knowledge, 34.21% of studies utilized the rule-based logic technique while 26.32% of studies used rule-based decision tree modeling. For CDSS development and translating knowledge, diverse methods and techniques were applied. Therefore, the development of a standard framework for the development of knowledge-based decision support systems should be considered by informaticians.

Specifications of a Queuing Model-Driven Decision Support System for Predicting the Healthcare Performance Indicators Pertaining to the Patient Flow

This article has developed specifications for a new model-driven decision support system (DSS) that aids the key stakeholders of public hospitals in estimating and tracking a set of crucial performance indicators pertaining to the patients flow. The developed specifications have considered several requirements for ensuring an effective system, including tracking the performance indicator on the level of the entire patients flow system, paying attention to the dynamic change of the values of the indicator’s parameters, and considering the heterogeneity of the patients. According to these requirements, the major components of the proposed system, which include a comprehensive object-based queuing model and an object-oriented database, have been specified. In addition to these components, the system comprises the equations that produce the required predictions. From the system output perspective, these predictions act as a foundation for evaluating the performance indicators as well as developing policies for managing the patients flow in the public hospitals.

Nurses' decision-making about cancer patients' end-of-life skin care in Wales: an exploratory mixed-method vignette study protocol

INTRODUCTION

Patients with cancer are at high risk of developing pressure ulcers at the end of life as a result of their underlying condition or cancer treatment. There are many guidelines which set out best practice with regard to end-of-life skin care. However, the complexity of palliative cancer care often means that it is challenging for nurses to make the appropriate person-centred decisions about end-of-life skin care. This study seeks to explore the perceived importance that nurses place on different factors in their end-of-life skin care for patients with cancer. The utility, face validity and content validity of a prototype decision-making tool for end-of-life skin care will also be evaluated.

METHODS AND ANALYSIS

A mixed-method design will be used to gather data from primary and secondary care nurses working in different hospitals and local authority areas across Wales. Clinical vignettes will be used to gather qualitative and quantitative data from nurses in individual interviews. Qualitative data will be subject to thematic analysis and quantitative data will be subject to descriptive statistical analysis. Qualitative and quantitative data will then be synthesised, which will enhance the rigour of this study, and pertinently inform the further development of an end-of-life skin care decision-making tool for patients with cancer.

ETHICS AND DISSEMINATION

Ethical approval to undertake the study has been granted by Cardiff University School of Healthcare Sciences Research Governance and Ethics Screening Committee. Informed consent will be obtained in writing from all the participants in this study. The results of this study will be disseminated through journal articles, as well as presentations at national and international conferences. We will also report our findings to patient and public involvement groups with an interest in improving cancer care, palliative care as well as skin care.

Clinical Decision Support Tools Improving Cancer Care

OBJECTIVES

To describe the clinical decision support tools and advancements in health information technology currently utilized at a National Cancer Institute designated cancer center to aid in achieving the Institute for Healthcare Improvement Triple Aim project.

DATA SOURCES

Published literature, Web sites.

CONCLUSION

Advances in health information technology facilitate increasing quality and satisfaction with care, improving the health of populations, and reducing the cost of care. New technology includes integration of the oncology electronic medical record (EMR), smart IV pumps, EMR after-hours nurse triage protocols, and bio-repository data warehouses.

IMPLICATIONS FOR NURSING PRACTICE

Cancer patients, oncology nurses, and oncologists have an increasing amount of clinical decision support tools available to help achieve the Institute for Healthcare Improvement's Triple Aim.