Clinical decision support software for chronic heart failure

An Electronically delivered, Patient-activation tool for Intensification of medications for Chronic Heart Failure with reduced ejection fraction: Rationale and design of the EPIC-HF trial

BACKGROUND

Heart failure with reduced ejection fraction (HFrEF) benefits from initiation and intensification of multiple pharmacotherapies. Unfortunately, there are major gaps in the routine use of these drugs. Without novel approaches to improve prescribing, the cumulative benefits of HFrEF treatment will be largely unrealized. Direct-to-consumer marketing and shared decision making reflect a culture where patients are increasingly involved in treatment choices, creating opportunities for prescribing interventions that engage patients.

HYPOTHESIS

Encouraging patients to engage providers in HFrEF prescribing decisions will improve the use of guideline-directed medical therapies.

DESIGN

The Electronically delivered, Patient-activation tool for Intensification of Chronic medications for Heart Failure with reduced ejection fraction (EPIC-HF) trial randomizes patients with HFrEF to usual care versus patient-activation tools-a 3-minute video and 1-page checklist-delivered prior to cardiology clinic visits that encourage patients to work collaboratively with their clinicians to intensify HFrEF prescribing. The study assesses the effectiveness of the EPIC-HF intervention to improve guideline-directed medical therapy in the month after its delivery while using an implementation design to also understand the reach, adoption, implementation, and maintenance of this approach within the context of real-world care delivery. Study enrollment was completed in January 2020, with a total 305 patients. Baseline data revealed significant opportunities, with <1% of patients on optimal HFrEF medical therapy.

SUMMARY

The EPIC-HF trial assesses the implementation, effectiveness, and safety of patient engagement in HFrEF prescribing decisions. If successful, the tool can be easily disseminated and may inform similar interventions for other chronic conditions.

Telemedicine, Artificial Intelligence and Humanisation of Clinical Pathways in Heart Failure Management: Back to the Future and Beyond

New technologies have been recently introduced to improve the monitoring of patients with chronic syndromes such as heart failure. Devices can now be employed to gather large amounts of data and data processing through artificial intelligence techniques may improve heart failure management and reduce costs. The analysis of large datasets using an artificial intelligence technique is leading to a paradigm shift in the era of precision medicine. However, the assessment of clinical safety and the evaluation of the potential benefits is still a matter of debate. In this article, the authors aim to focus on the development of these new tools and to draw the attention to their transition in daily clinical practice.

Computerized Advisory Decision Support for Cardiovascular Diseases in Primary Care: A Cluster Randomized Trial

PURPOSE

The purpose of this research was to evaluate the impact of an outpatient computerized advisory clinical decision support system (CDSS) on adherence to guideline-recommended treatment for heart failure, atrial fibrillation, and hyperlipidemia.

METHODS

Twenty care teams (109 clinicians) in a primary care practice were cluster-randomized to either access or no access to an advisory CDSS integrated into the electronic medical record. For patients with an outpatient visit, the CDSS determined if they had heart failure with reduced ejection fraction, hyperlipidemia, or atrial fibrillation; and if so, was the patient receiving guideline-recommended treatment. In the intervention group, an alert was visible in the medical record if there was a discrepancy between current and guideline-recommended treatment. Clicking the alert displayed the treatment discrepancy and recommended treatment. Outcomes included prescribing patterns, self-reported use of decision aids, and self-reported efficiency. The trial was conducted between May 1 and November 15, 2016, and incorporated 16,310 patient visits.

RESULTS

The advisory CDSS increased adherence to guideline-recommended treatment for heart failure (odds ratio [OR] 7.6, 95% confidence interval [CI], 1.2, 47.5) but had no impact in atrial fibrillation (OR 0.94, 95% CI 0.15, 5.94) or hyperlipidemia (OR 1.1, 95% CI 0.6, 1.8). Clinicians with access to the CDSS self-reported greater use of risk assessment tools for heart failure (3.6 [1.1] vs 2.7 [1.0], mean [standard deviation] on a 5-point scale) but not for atrial fibrillation or hyperlipidemia. The CDSS did not impact self-assessed efficiency. The overall usage of the CDSS was low (19%).

CONCLUSIONS

A computerized advisory CDSS improved adherence to guideline-recommended treatment for heart failure but not for atrial fibrillation or hyperlipidemia.

Computerized Systems Supporting Clinical Decision in Medicine

Statistics is the science of collection, summarizing, presentation and interpretation of data. Moreover, it yields methods used in the verification of research hypotheses. The presence of a statistician in a research group remarkably improves both the quality of design and research and the optimization of financial resources. Moreover, the involvement of a statistician in a research team helps the physician to effectively utilize the time and energy spent on diagnosing, which is an important aspect in view of limited healthcare resources. Precise, properly designed and implemented Computerized Clinical Decision Support Systems certainly lead to the improvement of healthcare and the quality of medical services, which increases patient satisfaction and reduces financial burdens on healthcare systems.

Value of Telemonitoring and Telemedicine in Heart Failure Management

The use of telemonitoring and telemedicine is a relatively new but quickly developing area in medicine. As new digital tools and applications are being created and used to manage medical conditions such as heart failure, many implications require close consideration and further study, including the effectiveness and safety of these telemonitoring tools in diagnosing, treating and managing heart failure compared to traditional face-to-face doctor-patient interaction. When compared to multidisciplinary intervention programs which are frequently hindered by economic, geographic and bureaucratic barriers, non-invasive remote monitoring could be a solution to support and promote the care of patients over time. Therefore it is crucial to identify the most relevant biological parameters to monitor, which heart failure sub-populations may gain real benefits from telehealth interventions and in which specific healthcare subsets these interventions should be implemented in order to maximise value.

The value of telemonitoring and ICT-guided disease management in heart failure: Results from the IN TOUCH study

AIM

It is still unclear whether telemonitoring reduces hospitalization and mortality in heart failure (HF) patients and whether adding an Information and Computing Technology-guided-disease-management-system (ICT-guided-DMS) improves clinical and patient reported outcomes or reduces healthcare costs.

METHODS

A multicenter randomized controlled trial was performed testing the effects of INnovative ICT-guided-DMS combined with Telemonitoring in OUtpatient clinics for Chronic HF patients (IN TOUCH) with in total 179 patients (mean age 69 years; 72% male; 77% in New York Heart Association Classification (NYHA) III-IV; mean left ventricular ejection fraction was 28%). Patients were randomized to ICT-guided-DMS or to ICT-guided-DMS+telemonitoring with a follow-up of nine months. The composite endpoint included mortality, HF-readmission and change in health-related quality of life (HR-QoL).

RESULTS

In total 177 patients were eligible for analyses. The mean score of the primary composite endpoint was -0.63 in ICT-guided-DMS vs. -0.73 in ICT-guided-DMS+telemonitoring (mean difference 0.1, 95% CI: -0.67 +0.82, p=0.39). All-cause mortality in ICT-guided-DMS was 12% versus 15% in ICT-guided-DMS+telemonitoring (p=0.27); HF-readmission 28% vs. 27% p=0.87; all-cause readmission was 49% vs. 51% (p=0.78). HR-QoL improved in most patients and was equal in both groups. Incremental costs were €1360 in favor of ICT-guided-DMS. ICT-guided-DMS+telemonitoring had significantly fewer HF-outpatient-clinic visits (p<0.01).

CONCLUSION

ICT-guided-DMS+telemonitoring for the management of HF patients did not affect the primary and secondary endpoints. However, we did find a reduction in visits to the HF-outpatient clinic in this group suggesting that telemonitoring might be safe to use in reorganizing HF-care with relatively low costs.

Description and pilot evaluation of the Metabolic Irregularities Narrowing down Device software: a case analysis of physician programming

Background

There is a gap between the abilities and the everyday applications of Computerized Decision Support Systems (CDSSs). This gap is further exacerbated by the different ‘worlds’ between the software designers and the clinician end-users. Software programmers often lack clinical experience whereas practicing physicians lack skills in design and engineering.

Objective

Our primary objective was to evaluate the performance of Metabolic Irregularities Narrowing down Device (MIND) intelligent medical calculator and differential diagnosis software through end-user surveys and discuss the roles of CDSS in the inpatient setting.

Setting

A tertiary care, teaching community hospital.

Study participants

Thirty-one responders answered the survey. Responders consisted of medical students, 24%; attending physicians, 16%, and residents, 60%.

Results

About 62.5% of the responders reported that MIND has the ability to potentially improve the quality of care, 20.8% were sure that MIND improves the quality of care, and only 4.2% of the responders felt that it does not improve the quality of care. Ninety-six percent of the responders felt that MIND definitely serves or has the potential to serve as a useful tool for medical students, and only 4% of the responders felt otherwise. Thirty-five percent of the responders rated the differential diagnosis list as excellent, 56% as good, 4% as fair, and 4% as poor.

Discussion

MIND is a suggesting, interpreting, alerting, and diagnosing CDSS with good performance and end-user satisfaction. In the era of the electronic medical record, the ongoing development of efficient CDSS platforms should be carefully considered by practicing physicians and institutions.

Perceived barriers of heart failure nurses and cardiologists in using clinical decision support systems in the treatment of heart failure patients

Background

Clinical Decision Support Systems (CDSSs) can support guideline adherence in heart failure (HF) patients. However, the use of CDSSs is limited and barriers in working with CDSSs have been described as a major obstacle. It is unknown if barriers to CDSSs are present and differ between HF nurses and cardiologists. Therefore the aims of this study are; 1. Explore the type and number of perceived barriers of HF nurses and cardiologists to use a CDSS in the treatment of HF patients. 2. Explore possible differences in perceived barriers between two groups. 3. Assess the relevance and influence of knowledge management (KM) on Responsibility/Trust (R&T) and Barriers/Threats (B&T).

Methods

A questionnaire was developed including; B&T, R&T, and KM. For analyses, descriptive techniques, 2-tailed Pearson correlation tests, and multiple regression analyses were performed.

Results

The response- rate of 220 questionnaires was 74%. Barriers were found for cardiologists and HF nurses in all the constructs. Sixty-five percent did not want to be dependent on a CDSS. Nevertheless thirty-six percent of HF nurses and 50% of cardiologists stated that a CDSS can optimize HF medication. No relationship between constructs and age; gender; years of work experience; general computer experience and email/internet were observed. In the group of HF nurses a positive correlation (r .33, P<.01) between years of using the internet and R&T was found. In both groups KM was associated with the constructs B&T (B=.55, P=<.01) and R&T (B=.50, P=<.01).

Conclusions

Both cardiologists and HF-nurses perceived barriers in working with a CDSS in all of the examined constructs. KM has a strong positive correlation with perceived barriers, indicating that increasing knowledge about CDSSs can decrease their barriers.

Impact of protocol watch on compliance with the surviving sepsis campaign

PURPOSE

Clinical decision support systems are intended to improve patients' care and outcomes, particularly when such systems are present at the point of care. Protocol Watch was developed as a bedside clinical decision support system to improve clinicians' adherence to the Surviving Sepsis Campaign guidelines. This pre/post-intervention pilot study was done to evaluate the effect of Protocol Watch on compliance with 5 guidelines from the Surviving Sepsis Campaign.

METHODS

Preintervention data on rates and time to complete the resuscitation and management bundles from the Surviving Sepsis Campaign and time to administer antibiotics were collected from intensive care units at 2 large teaching hospitals in the United States. Training on the Protocol Watch application was then provided to clinical staff in the units, and Protocol Watch was installed at all critical care beds in both hospitals. Data were collected on rates and time to completion for 5 Surviving Sepsis Campaign guidelines after installation of Protocol Watch, and univariate analyses were done to evaluate the effect of Protocol Watch on compliance with the guidelines.

RESULTS

Implementation of Protocol Watch was associated with significant improvements in compliance with the resuscitation bundle (P = .01) and decreased time to administer antibiotics (P = .006). No significant changes were achieved for compliance with the management bundle or time to complete the resuscitation or management bundles.

CONCLUSIONS

Clinical decision support systems such as Protocol Watch may improve adherence to the Surviving Sepsis Campaign guidelines, which potentially may contribute to reduced morbidity and mortality for critically ill patients with sepsis.

Simulation evaluation of an enhanced bedside monitor display for patients with sepsis

BACKGROUND

Most standard bedside monitors in critical care settings display multiple clinical parameters and do not provide directional signaling to alert clinicians to relevant changes in physiologic parameters. The complexity of information may delay identification of clinical changes and initiation of interventions. Clinical decision support system (CDSS) tools can present information at appropriate intervals in formats that may enhance clinical decision making.

OBJECTIVE

A 2-group, quasi-experimental design compared the effects of 2 different monitor displays on time required for nurses to recognize and initiate treatment of sepsis in response to a computer simulation.

METHODS

A convenience sample of 75 critical care nurses was randomly assigned to a standard or an enhanced bedside monitor (EBM) display during a computer-simulated sepsis scenario. Time to recognize symptoms and initiate treatment of sepsis was analyzed between the 2 displays.

RESULTS

Time to recognize symptoms and initiate sepsis treatment was significantly shorter for nurses exposed to the enhanced bedside monitor.

CONCLUSIONS

CDSS tools such as EBM may improve nurses' time to recognize and initiate treatment of sepsis.