Development of an expert system knowledge base: a novel approach to promote guideline congruent asthma care

Multidisciplinary Development and Initial Validation of a Clinical Knowledge Base on Chronic Respiratory Diseases for mHealth Decision Support Systems

Most mobile health (mHealth) decision support systems currently available for chronic obstructive respiratory diseases (CORDs) are not supported by clinical evidence or lack clinical validation. The development of the knowledge base that will feed the clinical decision support system is a crucial step that involves the collection and systematization of clinical knowledge from relevant scientific sources and its representation in a human-understandable and computer-interpretable way. This work describes the development and initial validation of a clinical knowledge base that can be integrated into mHealth decision support systems developed for patients with CORDs. A multidisciplinary team of health care professionals with clinical experience in respiratory diseases, together with data science and IT professionals, defined a new framework that can be used in other evidence-based systems. The knowledge base development began with a thorough review of the relevant scientific sources (eg, disease guidelines) to identify the recommendations to be implemented in the decision support system based on a consensus process. Recommendations were selected according to predefined inclusion criteria: (1) applicable to individuals with CORDs or to prevent CORDs, (2) directed toward patient self-management, (3) targeting adults, and (4) within the scope of the knowledge domains and subdomains defined. Then, the selected recommendations were prioritized according to (1) a harmonized level of evidence (reconciled from different sources); (2) the scope of the source document (international was preferred); (3) the entity that issued the source document; (4) the operability of the recommendation; and (5) health care professionals' perceptions of the relevance, potential impact, and reach of the recommendation. A total of 358 recommendations were selected. Next, the variables required to trigger those recommendations were defined (n=116) and operationalized into logical rules using Boolean logical operators (n=405). Finally, the knowledge base was implemented in an intelligent individualized coaching component and pretested with an asthma use case. Initial validation of the knowledge base was conducted internally using data from a population-based observational study of individuals with or without asthma or rhinitis. External validation of the appropriateness of the recommendations with the highest priority level was conducted independently by 4 physicians. In addition, a strategy for knowledge base updates, including an easy-to-use rules editor, was defined. Using this process, based on consensus and iterative improvement, we developed and conducted preliminary validation of a clinical knowledge base for CORDs that translates disease guidelines into personalized patient recommendations. The knowledge base can be used as part of mHealth decision support systems. This process could be replicated in other clinical areas.

Adaptation and Formative Evaluation of Online Decision Support to Implement Evidence-Based Strategies to Increase HPV Vaccination Rates in Pediatric Clinics

Human papilloma virus (HPV) vaccination rates remain below national goals in the United States despite the availability of evidence-based strategies to increase rates. The Adolescent Vaccination Program (AVP) is a multi-component intervention demonstrated to increase HPV vaccination rates in pediatric clinics through the implementation of six evidence-based strategies. The purpose of this study, conducted in Houston, Texas, from 2019-2021, was to adapt the AVP into an online decision support implementation tool for standalone use and to evaluate its feasibility for use in community clinics. Phase 1 (Adaptation) comprised clinic interviews (n = 23), literature review, Adolescent Vaccination Program Implementation Tool (AVP-IT) design documentation, and AVP-IT development. Phase 2 (Evaluation) comprised usability testing with healthcare providers (HCPs) (n = 5) and feasibility testing in community-based clinics (n = 2). AVP-IT decision support provides an Action Plan with tailored guidance on implementing six evidence-based strategies (immunization champions, assessment and feedback, continuing education, provider prompts, parent reminders, and parent education). HCPs rated the AVP-IT as acceptable, credible, easy, helpful, impactful, and appealing (≥80% agreement). They rated AVP-IT supported implementation as easier and more effective compared to usual practice (p ≤ 0.05). The clinic-based AVP-IT uses facilitated strategy implementation by 3-month follow-up. The AVP-IT promises accessible, utilitarian, and scalable decision support on strategies to increase HPV vaccination rates in pediatric clinic settings. Further feasibility and efficacy testing is indicated.

Computer-based decision support for pediatric asthma management: description and feasibility of the Stop Asthma Clinical System

Clinical guidelines can assist in the management of asthma. Decision support systems (DSSs) can enhance adherence to clinical guidelines but tend not to provide clinicians with cues for behavioral change strategies to promote patient self-management. The Stop Asthma Clinical System (SACS) is a DSS designed for this purpose. To assess feasibility, seven clinicians used SACS to guide well visits with 26 predominantly persistent pediatric asthma patients. Data were collected via survey and in-depth semi-structured interviews. SACS improved assessment of asthma severity and control, classification of and intervention in medicine and environmental trigger management problems, and development of an action plan (all p < 0.05). Clinician-patient communication was enhanced. The primary challenge was that SACS increased clinic visit time. SACS can enhance clinician behavior to improve patient asthma self-management, but more studies are indicated to mitigate temporal constraints and evaluate impact on clinician and patient communication and behavior as well as clinical outcomes.

Biomedical informatics applications for asthma care: a systematic review

Asthma is a common condition associated with significant patient morbidity and health care costs. Although widely accepted evidence-based guidelines for asthma management exist, unnecessary variation in patient care remains. Application of biomedical informatics techniques is one potential way to improve care for asthmatic patients. We performed a systematic literature review to identify computerized applications for clinical asthma care. Studies were evaluated for their clinical domain, developmental stage and study design. Additionally, prospective trials were identified and analyzed for potential study biases, study effects, and clinical study characteristics. Sixty-four papers were selected for review. Publications described asthma detection or diagnosis (18 papers), asthma monitoring or prevention (13 papers), patient education (13 papers), and asthma guidelines or therapy (20 papers). The majority of publications described projects in early stages of development or with non-prospective study designs. Twenty-one prospective trials were identified, which evaluated both clinical and non-clinical impacts on patient care. Most studies took place in the outpatient clinic environment, with minimal study of the emergency department or inpatient settings. Few studies demonstrated evidence of computerized applications improving clinical outcomes. Further research is needed to prospectively evaluate the impact of using biomedical informatics to improve care of asthmatic patients.

Delivering tailored asthma family education in a pediatric emergency department setting: a pilot study

OBJECTIVE

Many children are brought to the pediatric emergency department (ED) with acute asthma symptoms. Emergency asthma care is costly, and many ED visits may be preventable. Families often do not have written asthma action plans and lack asthma self-management skills. This study tests a tailored self-management intervention delivered in the ED for families of children with asthma. The primary hypotheses were that the intervention group would have greater confidence to manage asthma 14 days postintervention and more well-asthma visits and fewer urgent care/ED visits at 9 and 12 months.

METHODS

This randomized intervention/usual-care study was part of a larger ED asthma surveillance project in 4 urban pediatric ED sites. Asthma educators used a computer-based resource to tailor the intervention messages and provide a customized asthma action plan and educational summary. Children with acute asthma were enrolled during an ED visit, and follow-up telephone interviews were conducted during the next 9 months. The ED clinician classified the child's acute and chronic severity.

RESULTS

To date, 464 subjects aged 1 to 18 years have been enrolled. The ED clinicians reported that 46% had intermittent and 54% had persistent chronic severity with 51% having mild acute severity episodes. The confidence level to prevent asthma episodes and keep them from getting worse was significantly higher in the intervention group at 14 days postintervention. More subjects in the intervention group reported well-asthma visits by 9 months. Return ED visits were significantly lower in the intervention group in those with intermittent asthma. Twelve-month follow-up is in process.

CONCLUSIONS

The tailored ED self-management intervention demonstrates significant effects on caregiver self-confidence and well-visit follow-up. Additional evaluation is needed to determine what impact this intervention has long-term.

Severity assessment in asthma: An evolving concept

BACKGROUND

Guidelines for the clinical management of asthma base specific treatment recommendations on the assessment of disease severity. Thus, the accuracy of such assessments is essential for proper clinical management. The consistency of asthma severity assessment in patients with difficult-to-treat disease is unknown.

OBJECTIVE

The objectives of this analysis were to compare the asthma severity assessment according to 3 methodologies in patients from The Epidemiology and Natural History of Asthma: Outcomes and Treatment Regimens study.

METHODS

Asthma severity on the basis of the National Asthma Education and Prevention Program and the Global Initiative for Asthma guidelines was compared with physician assessment and benchmarked against asthma-related health care use. Guideline-based asthma severity symptom components were derived from patient-reported questionnaires. Lung function levels were determined by prebronchodilator FEV(1) measurements; asthma-related medication and recent health care use were reported by patients.

RESULTS

There was a clear lack of agreement among the asthma severity assessment modalities. Asthma severity was associated with asthma-related health care use, and patients considered to have severe asthma according to both sets of guidelines and physicians' assessment had the highest health care and medication use.

CONCLUSION

Classification of asthma severity on the basis of current asthma symptoms and lung function may be useful but not completely reflective of a patient's true asthma condition. Clinical assessment of asthma severity should consider a patient's medication use and consumption of health care resources for asthma exacerbations. Additional studies that apply criteria for asthma severity longitudinally are needed to support recommendations for optimal assessment of asthma severity.