A computerized decision support system did not improve personalization of exercise-based cardiac rehabilitation according to latest recommendations

Benefits of Clinical Decision Support Systems for the Management of Noncommunicable Chronic Diseases: Targeted Literature Review

BACKGROUND

Clinical decision support systems (CDSSs) are designed to assist in health care delivery by supporting medical practice with clinical knowledge, patient information, and other relevant types of health information. CDSSs are integral parts of health care technologies assisting in disease management, including diagnosis, treatment, and monitoring. While electronic medical records (EMRs) serve as data repositories, CDSSs are used to assist clinicians in providing personalized, context-specific recommendations derived by comparing individual patient data to evidence-based guidelines.

OBJECTIVE

This targeted literature review (TLR) aimed to identify characteristics and features of both stand-alone and EMR-integrated CDSSs that influence their outcomes and benefits based on published scientific literature.

METHODS

A TLR was conducted using the Embase, MEDLINE, and Cochrane databases to identify data on CDSSs published in a 10-year frame (2012-2022). Studies on computerized, guideline-based CDSSs used by health care practitioners with a focus on chronic disease areas and reporting outcomes for CDSS utilization were eligible for inclusion.

RESULTS

A total of 49 publications were included in the TLR. Studies predominantly reported on EMR-integrated CDSSs (ie, connected to an EMR database; n=32, 65%). The implementation of CDSSs varied globally, with substantial utilization in the United States and within the domain of cardio-renal-metabolic diseases. CDSSs were found to positively impact "quality assurance" (n=35, 69%) and provide "clinical benefits" (n=20, 41%), compared to usual care. Among CDSS features, treatment guidance and flagging were consistently reported as the most frequent elements for enhancing health care, followed by risk level estimation, diagnosis, education, and data export. The effectiveness of a CDSS was evaluated most frequently in primary care settings (n=34, 69%) across cardio-renal-metabolic disease areas (n=32, 65%), especially in diabetes (n=13, 26%). Studies reported CDSSs to be commonly used by a mixed group (n=27, 55%) of users including physicians, specialists, nurses or nurse practitioners, and allied health care professionals.

CONCLUSIONS

Overall, both EMR-integrated and stand-alone CDSSs showed positive results, suggesting their benefits to health care providers and potential for successful adoption. Flagging and treatment recommendation features were commonly used in CDSSs to improve patient care; other features such as risk level estimation, diagnosis, education, and data export were tailored to specific requirements and collectively contributed to the effectiveness of health care delivery. While this TLR demonstrated that both stand-alone and EMR-integrated CDSSs were successful in achieving clinical outcomes, the heterogeneity of included studies reflects the evolving nature of this research area, underscoring the need for further longitudinal studies to elucidate aspects that may impact their adoption in real-world scenarios.

Appropriate exercise prescription in primary and secondary prevention of cardiovascular disease: why this skill remains to be improved among clinicians and healthcare professionals. A call for action from the EXPERT Network†

In Europe alone, on a yearly basis, millions of people need an appropriate exercise prescription to prevent the occurrence or progression of cardiovascular disease (CVD). A general exercise recommendation can be provided to these individuals (at least 150 min of moderate-intensity endurance exercise, spread over 3-5 days/week, complemented by dynamic moderate-intensity resistance exercise 2 days/week). However, recent evidence shows that this one size does not fit all and that individual adjustments should be made according to the patient's underlying disease(s), risk profile, and individual needs, to maximize the clinical benefits of exercise. In this paper, we (i) argue that this general exercise prescription simply provided to all patients with CVD, or elevated risk for CVD, is insufficient for optimal CVD prevention, and (ii) show that clinicians and healthcare professionals perform heterogeneously when asked to adjust exercise characteristics (e.g. intensity, volume, and type) according to the patient's condition, thereby leading to suboptimal CVD risk factor control. Since exercise training is a class 1A intervention in the primary and secondary prevention of CVD, the awareness of the need to improve exercise prescription has to be raised among clinicians and healthcare professionals if optimized prevention of CVD is ambitioned.

Exercise prescription by physiotherapists to patients with cardiovascular disease is in greater agreement with European recommendations after using the EXPERT training tool

BACKGROUND

Exercise prescriptions by clinicians to patients with cardiovascular disease (CVD) often disagree with recommendations, thus requiring improvement.

AIM

To assess whether exercise prescriptions by physiotherapists to patients with CVD are better in agreement with European (ESC/EAPC) recommendations when the EXPERT (EXercise Prescription in Everyday practice & Rehabilitative Training) Training tool is used for digital educational training.

DESIGN

In a prospective non-randomized intervention study.

METHODS

Twenty-three belgian physiotherapists first prescribed exercise intensity, frequency, session duration, program duration and exercise type (endurance or strength training) for the same three patient cases, from which the agreement with ESC/EAPC recommendations (based on a maximal score of 60/per case: agreement score) was assessed. Next, they completed a one-month digital training by using the EXPERT Training tool and completed 31 ± 13 training cases. The EXPERT tool is a training and decision support system that automatically generates a (personalised) exercise prescription according to the patient's characteristics, thus integrating the exercise prescriptions for different CVDs and risk factors, all based on ESC/EAPC recommendations. Thereafter, the same three patient cases as at entry of study were filled out again, with re-assessment of level of agreement with ESC/EAPC recommendations.

RESULTS

After using the EXPERT Training tool, the physiotherapists prescribed significantly greater exercise frequencies, program durations and total exercise volumes in all three patient cases (p < 0.05). In cases 1, 2 and 3, the agreement score increased from 29 ± 9 (out of 60), 28 ± 9, and 34 ± 7 to 41 ± 9, 41 ± 10, and 45 ± 8, respectively (p < 0.001). Hence, the total agreement score increased from 91 ± 17 (out of 180) to 127 ± 19 (p < 0.001, +44 ± 32%). A lower starting agreement score and younger age correlated with a greater improvement in total agreement score (p < 0.05).

CONCLUSIONS

Exercise prescriptions to patients with CVD, generated by physiotherapists, are significantly better in agreement with European recommendations when the EXPERT Training tool is used, indicating its educational potential.