2 research outputs found
Initial development of Supportive care Assessment, Prioritization and Recommendations for Kids (SPARK), a symptom screening and management application
Abstract Background We developed Supportive care Prioritization, Assessment and Recommendations for Kids (SPARK), a web-based application designed to facilitate symptom screening by children receiving cancer treatments and access to supportive care clinical practice guidelines primarily by healthcare providers. The objective was to describe the initial development and evaluation of SPARK from the perspective of children. Implementation Development and evaluation occurred in three phases: (1) low fidelity focused on functionality, (2) design focused on “look and feel” and (3) high fidelity confirmed functionality and design. Cognitive interviews were conducted with children receiving cancer treatments 8–18 years of age. Evaluation occurred after every five interviews and changes were guided by a Review Panel. Quantitative evaluation included SPARK ease of use and understandability of SPARK reports. Results The number of children included by phase were: low fidelity (n = 30), design (n = 30) and high fidelity (n = 30). Across phases, the median age was 13.2 (range 8.5 to 18.4) years. During low-fidelity and design phases, iterative refinements to SPARK improved website navigation, usability and likability from the perspective of children and established symptom report design. Among the last 10 children enrolled to high-fidelity testing, all (100%) understood how to complete symptom screening, access reports and interpret reports. Among these 10 respondents, all (100%) found SPARK easy to use and 9 (90%) found SPARK reports were easy to understand. Conclusions SPARK is a web-based application which is usable and understandable, and it is now appropriate to use for research. Future efforts will focus on clinical implementation of SPARK
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Supporting Clinical Decision Making in Cancer Care Delivery
Background: Cancer treatment and management require complicated clinical decision making to provide the highest quality of care for an individual patient. This is facilitated in part with ever-increasing availability of medications and treatments but hindered due to barriers such as access to care, cost of medications, clinician knowledge, and patient preferences or clinical factors. Although guidelines for cancer treatment and many symptoms have been developed to inform clinical practice, implementation of these guidelines into practice is often delayed or does not occur. Informatics-based approaches, such as clinical decision support, may be an effective tool to improve guideline implementation by delivering patient-specific and evidence-based knowledge to the clinician at the point of care to allow shared decision making with a patient and their family. The large amount of data in the electronic health record can be utilized to develop, evaluate, and implement automated approaches; however, the quality of the data must first be examined and evaluated.
Methods: This dissertation addresses gaps the literature about clinical decision making for cancer care delivery. Specifically, following an introduction and review of the literature for relevant topics to this dissertation, the researcher presents three studies. In Study One, the researcher explores the use of clinical decision support in cancer therapeutic decision making by conducting a systematic review of the literature. In Study Two, the researcher conducts a quantitative study to describe the rate of guideline concordant care provided for prevention of acute chemotherapy-induced nausea and vomiting (CINV) and to identify predictors of receiving guideline concordant care. In Study Three, the researcher conducts a mixed-methods study to evaluate the completeness, concordance, and heterogeneity of clinician documentation of CINV. The final chapter of this dissertation is comprised of key findings of each study, the strengths and limitations, clinical and research implications, and future research.
Results: In Study One, the systematic review, the researcher identified ten studies that prospectively studied clinical decision support systems or tools in a cancer setting to guide therapeutic decision making. There was variability in these studies, including study design, outcomes measured, and results. There was a trend toward benefit, both in process and patient-specific outcomes. Importantly, few studies were integrated into the electronic health record.
In Study Two, of 180 patients age 26 years or less, 36% received guideline concordant care as defined by pediatric or adult guidelines, as appropriate. Factors associated with receiving guideline concordant care included receiving a cisplatin-based regimen, being treated in adult oncology compared to pediatric oncology, and solid tumor diagnosis.
In Study Three, of the 127 patient records reviewed for the documentation of chemotherapy-induced nausea and vomiting, 75% had prescriber assessment documented and 58% had nursing assessment documented. Of those who had documented assessments by both prescriber and nurse, 72% were in agreement of the presence/absence of chemotherapy-induced nausea and vomiting. After mapping the concept through the United Medical Language System and developing a post-coordinated expression to identify chemotherapy-induced nausea and vomiting in the text, 85% of prescriber documentation and 100% of nurse documentation could be correctly categorized as present/absent. Further descriptors of the symptoms, such as severity or temporality, however, were infrequently reported.
Conclusion: In summary, this dissertation provides new knowledge about decision making in cancer care delivery. Specifically, in Study One the researcher describes that clinical decision support, one potential implementation strategy to improve guideline concordant care, is understudied or under published but a promising potential intervention. In Study Two, I identified factors that were associated with receipt of guideline concordant care for CINV, and these should be further explored to develop interventions. Finally, in Study Three, I report on the limitations of the data quality of CINV documentation in the electronic health record. Future work should focus on validating these results on a multi-institutional level