Precision diagnosis: a view of the clinical decision support systems (CDSS) landscape through the lens of critical care

Personalized medicine for patients with COPD: where are we?

Chronic airflow limitation is the common denominator of patients with chronic obstructive pulmonary disease (COPD). However, it is not possible to predict morbidity and mortality of individual patients based on the degree of lung function impairment, nor does the degree of airflow limitation allow guidance regarding therapies. Over the last decades, understanding of the factors contributing to the heterogeneity of disease trajectories, clinical presentation, and response to existing therapies has greatly advanced. Indeed, diagnostic assessment and treatment algorithms for COPD have become more personalized. In addition to the pulmonary abnormalities and inhaler therapies, extra-pulmonary features and comorbidities have been studied and are considered essential components of comprehensive disease management, including lifestyle interventions. Despite these advances, predicting and/or modifying the course of the disease remains currently impossible, and selection of patients with a beneficial response to specific interventions is unsatisfactory. Consequently, non-response to pharmacologic and non-pharmacologic treatments is common, and many patients have refractory symptoms. Thus, there is an ongoing urgency for a more targeted and holistic management of the disease, incorporating the basic principles of P4 medicine (predictive, preventive, personalized, and participatory). This review describes the current status and unmet needs regarding personalized medicine for patients with COPD. Also, it proposes a systems medicine approach, integrating genetic, environmental, (micro)biological, and clinical factors in experimental and computational models in order to decipher the multilevel complexity of COPD. Ultimately, the acquired insights will enable the development of clinical decision support systems and advance personalized medicine for patients with COPD.

Precision health research and implementation reviewed through the conNECT framework

BACKGROUND

Precision health is a population-based approach that incorporates big-data strategies to understand the complex interactions between biological, environmental, lifestyle, and psychosocial factors that influence health.

PURPOSE

A promising tool to facilitate precision health research and its dissemination is the ConNECT Framework.

METHODS

Here, we discuss the relationship of the five broad and synergistic principles within the ConNECT Framework as they may apply to nursing science research: (1) Integrating Context, (2) Fostering a Norm of Inclusion, (3) Ensuring Equitable Diffusion of Innovations, (4) Harnessing Communication Technology, and (5) Prioritizing Specialized Training.

DISCUSSION/CONCLUSION

The principles within this framework can be used by nurse scientists and educators to guide and disseminate precision health research.

The Uniformed Services University's Surgical Critical Care Initiative (SC2i): Bringing Precision Medicine to the Critically Ill

Precision medicine endeavors to leverage all available medical data in pursuit of individualized diagnostic and therapeutic plans to improve patient outcomes in a cost-effective manner. Its promise in the field of critical care remains incompletely realized. The Department of Defense has a vested interest in advancing precision medicine for those sent into harm's way and specifically seeks means of individualizing care in the context of complex and highly dynamic combat clinical decision environments. Building on legacy research efforts conducted during the Afghanistan and Iraq conflicts, the Uniformed Service University (USU) launched the Surgical Critical Care Initiative (SC2i) in 2013 to develop clinical- and biomarker-driven Clinical Decision Support Systems (CDSS), with the goals of improving both patient-specific outcomes and resource utilization for conditions with a high risk of morbidity or mortality. Despite technical and regulatory challenges, this military-civilian partnership is beginning to deliver on the promise of personalized care, organizing and analyzing sizable, real-time medical data sets to support complex clinical decision-making across critical and surgical care disciplines. We present the SC2i experience as a generalizable template for the national integration of federal and non-federal research databanks to foster critical and surgical care precision medicine.

Rapid intra-operative diagnosis of kidney cancer by attenuated total reflection infrared spectroscopy of tissue smears

Herein, a technique to analyze air-dried kidney tissue impression smears by means of attenuated total reflection infrared (ATR-IR) spectroscopy is presented. Spectral tumor markers-absorption bands of glycogen-are identified in the ATR-IR spectra of the kidney tissue smear samples. Thin kidney tissue cryo-sections currently used for IR spectroscopic analysis lack such spectral markers as the sample preparation causes irreversible molecular changes in the tissue. In particular, freeze-thaw cycle results in degradation of the glycogen and reduction or complete dissolution of its content. Supervised spectral classification was applied to the recorded spectra of the smears and the test spectra were classified with a high accuracy of 92% for normal tissue and 94% for tumor tissue, respectively. For further development, we propose that combination of the method with optical fiber ATR probes could potentially be used for rapid real-time intra-operative tissue analysis without interfering with either the established protocols of pathological examination or the ordinary workflow of operating surgeon. Such approach could ensure easier transition of the method to clinical applications where it may complement the results of gold standard histopathology examination and aid in more precise resection of kidney tumors.

Reasons For Physicians Not Adopting Clinical Decision Support Systems: Critical Analysis

Background

Clinical decision support systems (CDSSs) are an integral component of today’s health information technologies. They assist with interpretation, diagnosis, and treatment. A CDSS can be embedded throughout the patient safety continuum providing reminders, recommendations, and alerts to health care providers. Although CDSSs have been shown to reduce medical errors and improve patient outcomes, they have fallen short of their full potential. User acceptance has been identified as one of the potential reasons for this shortfall.

Objective

The purpose of this paper was to conduct a critical review and task analysis of CDSS research and to develop a new framework for CDSS design in order to achieve user acceptance.

Methods

A critical review of CDSS papers was conducted with a focus on user acceptance. To gain a greater understanding of the problems associated with CDSS acceptance, we conducted a task analysis to identify and describe the goals, user input, system output, knowledge requirements, and constraints from two different perspectives: the machine (ie, the CDSS engine) and the user (ie, the physician).

Results

Favorability of CDSSs was based on user acceptance of clinical guidelines, reminders, alerts, and diagnostic suggestions. We propose two models: (1) the user acceptance and system adaptation design model, which includes optimizing CDSS design based on user needs/expectations, and (2) the input-process-output-engagemodel, which reveals to users the processes that govern CDSS outputs.

Conclusions

This research demonstrates that the incorporation of the proposed models will improve user acceptance to support the beneficial effects of CDSSs adoption. Ultimately, if a user does not accept technology, this not only poses a threat to the use of the technology but can also pose a threat to the health and well-being of patients.

Management of Mangled Extremities and Orthopaedic War Injuries

In 16 years of conflict, primarily in Iraq and Afghanistan, wounded warriors have primarily been subjected to blast type of injuries. Evacuation strategies have led to unprecedented survival rates in blast-injured soldiers, resulting in large numbers of wounded warriors with complex limb trauma. Bone and soft tissue defects have resulted in increased use of complex reconstructive algorithms to restore limbs and function. In addition, in failed salvage attempts, advances in amputation options are being developed. In this review, we summarize state-of-the-art limb-salvage methods for both soft tissue and bone. In addition, we discuss advances in diagnostic methods with development of personalized clinical decision support tools designed to optimize outcomes after severe blast injuries. Finally, we present new advances in osteointegrated prostheses for above-knee amputations.

Use of Electronic Clinical Decision Support and Hard Stops to Decrease Unnecessary Thyroid Function Testing

NewYork-Presbyterian Brooklyn Methodist Hospital embarked on a Zero Unnecessary Study (ZEUS) initiative, whereby all aspects of clinical care were evaluated and strategies were implemented to mitigate waste. An opportunity was found in regards to thyroid function testing. It has been shown that certain TFTs are ordered far more often than clinically indicated. Free T3 (fT3) and Free T4 (fT4) are only indicated when the TSH is abnormal in the inpatient setting, with rare exceptions. Thus, a clinical algorithm for Clinical Decision Support (CDS) and Hard Stops (HS) were incorporated into the Electronic Medical Record (EMR) to prevent fT3 or fT4 to be ordered without an abnormal TSH, with certain predefined exceptions. In addition, a reflex rule was built which automatically orders (reflex) fT3 and fT4 if the TSH is abnormal. The pre and post-intervention ratios of fT3 and fT4 orders per total TSH orders were analyzed. Pre-intervention data revealed that fT4 was the most frequently ordered TFT laboratory test on admission, after TSH. Post-Intervention, there was a decrease in the ratio of fT4 to TSH orders (fT4/TSH) of 35.2%, from 44.6% to 28.9%. The percentage of fT4 ordered due to abnormal TSH increased by 126.1%, from 36.8% to 83.2%. The fT3 to TSH ordering ratio similarly decreased by 55.2%, from 6.2% to 2.9%. The decreases in both fT3/TSH and fT4/TSH ratios were statistically significant. Any unnecessary orders are a burden on healthcare. It is now possible to achieve goals that were not previously thought to be possible because of advancement in medicine and technology. By making small changes and saving costs, we can target our energy and resources toward effectively treating patients.