Search

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.To identify current challenges in health system-wide, pharmacist-led detection of newly emergent medication-related symptoms and technology-based opportunities to increase the patient-centeredness of postmarketing pharmacosurveillance efforts toward a more accountable, patient-centered, and equitable medication prescribing cycle.Pharmacists have an important role to play in detection and evaluation of adverse drug reactions (ADRs). The pharmacist's role in medication management should extend beyond simply dispensing drugs, and this article delineates the rationale and proactive approaches for pharmacist detection and assessment of ADRs. We describe a stepwise approach for assessment, best practices, and lessons learned from a pharmacist-led randomized trial, the CEDAR (Calling for Detection of Adverse Drug Reactions) project.Health systems need to be redesigned to more fully utilize health information technologies and pharmacists in detecting and responding to ADRs.

Disparities in health by race, ethnicity, and socioeconomic status within obstetrics and gynecology are well described and prompt evaluation for structural barriers. Academic medicine has a historical role in caring for marginalized populations, with medical trainees often serving as first-line clinicians for outpatient care. The ubiquitous approach of concentrating care of marginalized patients within resident and trainee clinics raises ethical questions regarding equity and sends a clear message of value that is internalized by learners and patients. A path forward is elimination of the structural inequities caused by maintenance of clinics stratified by training level, thereby creating an integrated patient pool for trainees and attending physicians alike. In this model, demographic and insurance information is blinded and patient triage is guided by clinical acuity and patient preference alone. To address structural inequities in our health care delivery system, we implemented changes in our department. Our goals were to improve access and patient experience and to send a unified message to our patients, learners, and faculty-our clinical staff, across all training levels, are committed to giving the highest standard of care to all people, regardless of insurance status or ability to pay. Academic medical centers must look internally for structural barriers that contribute to health care disparities within obstetrics and gynecology as we aim to make progress toward equity.

Background and ObjectivesFollowing brain injury, clinical assessments of residual and emerging cognitive function are difficult and fraught with errors. In adults, recent American Academy of Neurology (AAN) practice guidelines recommend objective neuroimaging and neurophysiologic measures to support diagnosis. Equivalent measures are lacking in pediatrics—an especially great challenge due to the combined heterogeneity of both brain injury and pediatric development. Therefore, we aim to establish quantitative, clinically practicable measures of cognitive function following pediatric brain injury.MethodsParticipants with and without brain injury were aged 8–18 years, clinically classified according to cognitive recovery state: N = 8 in disorders of consciousness (DoC), N = 7 in confusional state, N = 19 cognitively impaired, and N = 13 typically developing uninjured controls. We prospectively measured electroencephalographic markers of sensory processing and attention in an auditory oddball paradigm, and of covert movement attempts in a command-following paradigm.ResultsIn 3 participants with DoC, EEG markers of active attempted command following revealed cognitive function that clinical assessment had failed to detect. These same 3 individuals could also be distinguished from the rest of their group by 2 event-related potentials that correlate with sensory processing and orienting attention in the oddball paradigm. Considered across the whole participant group, magnitudes of these 2 ERP markers significantly increased as cognitive recovery progressed (ANOVA: each p < 0.001); viewed jointly, the 2 ERP markers cleanly delineated the 4 cognitive states.DiscussionDespite heterogeneity of brain injuries and brain development, our objective EEG markers reflected cognitive recovery independent of motor function. Two of these markers required no active participation. Together, they allowed us to identify 3 individuals who meet the criteria for cognitive-motor dissociation. To diagnose, prognose, and track cognitive recovery accurately, such markers should be used in pediatrics.

Tools assaying the neural networks that modulate consciousness may facilitate tracking of recovery after acute severe brain injury. The ABCD framework classifies resting-state EEG into categories reflecting levels of thalamocortical network function that correlate with outcome in post-cardiac arrest coma. In this longitudinal cohort study, we applied the ABCD framework to 20 patients with acute severe traumatic brain injury requiring intensive care (12 of whom were also studied at ≥6-months post-injury) and 16 healthy controls. We tested four hypotheses: 1) EEG ABCD classifications are spatially heterogeneous and temporally variable; 2) ABCD classifications improve longitudinally, commensurate with the degree of behavioral recovery; 3) ABCD classifications correlate with behavioral level of consciousness; and 4) the Coma Recovery Scale-Revised arousal facilitation protocol yields improved ABCD classifications. Channel-level EEG power spectra were classified based on spectral peaks within pre-defined frequency bands: 'A' = no peaks above delta (4 Hz) range (complete thalamocortical disruption); 'B' = theta (4-8 Hz) peak (severe thalamocortical disruption); 'C' = theta and beta (13-24 Hz) peaks (moderate thalamocortical disruption); or 'D' = alpha (8-13 Hz) and beta peaks (normal thalamocortical function). Acutely, 95% of patients demonstrated 'D' signals in at least one channel but exhibited within-session temporal variability and spatial heterogeneity in the proportion of different channel-level ABCD classifications. By contrast, healthy participants and patients at follow-up consistently demonstrated signals corresponding to intact thalamocortical network function. Patients demonstrated longitudinal improvement in ABCD classifications (p .05) and ABCD classification distinguished patients with and without command-following in the subacute-to-chronic phase of recovery (p .01). In patients studied acutely, ABCD classifications improved after the Coma Recovery Scale-Revised arousal facilitation protocol (p .05) but did not correspond with behavioral level of consciousness. These findings support the use of the ABCD framework to characterize channel-level EEG dynamics and track fluctuations in functional thalamocortical network integrity in spatial detail.

Opioid misuse has resulted in significant morbidity and mortality in the United States, and safer opioid use represents an important challenge in the primary care setting. This article describes a research collaborative of health service researchers, systems engineers, and clinicians seeking to improve processes for safer chronic opioid therapy management in an academic primary care center. We present implementation results and lessons learned along with an intervention toolkit that others may consider using within their organization.Using iterative improvement lifecycles and systems engineering principles, we developed a risk-based workflow model for patients on chronic opioids. Two key safe opioid use process metrics-percent of patients with recent opioid treatment agreements and urine drug tests-were identified, and processes to improve these measures were designed, tested, and implemented. Focus groups were conducted after the conclusion of implementation, with barriers and lessons learned identified via thematic analysis.Initial surveys revealed a lack of knowledge regarding resources available to patients and prescribers in the primary care clinic. In addition, 18 clinicians (69%) reported largely "inheriting" (rather than initiating) their chronic opioid therapy patients. We tracked 68 patients over a 4-year period. Although process measures improved, full adherence was not achieved for the entire population. Barriers included team structure, the evolving opioid environment, and surveillance challenges, along with disruptions resulting from the 2019 novel coronavirus.Safe primary care opioid prescribing requires ongoing monitoring and management in a complex environment. The application of a risk-based approach is possible but requires adaptability and redundancies to be reliable.

Objectives To understand the relationship between stressful work environments and patient care by assessing work conditions, burnout, and elements of the diagnostic process. Methods Notes and transcripts of audiotaped encounters were assessed for verbal and written documentation related to psychosocial data, differential diagnosis, acknowledgement of uncertainty, and other diagnosis-relevant contextual elements using 5-point Likert scales in seven primary care physicians (PCPs) and 28 patients in urgent care settings. Encounter time spent vs time needed (time pressure) was collected from time stamps and clinician surveys. Study physicians completed surveys on stress, burnout, and work conditions using the Mini-Z survey. Results Physicians with high stress or burnout were less likely to record psychosocial information in transcripts and notes (psychosocial information noted in 0% of encounters in 4 high stress/burned-out physicians), whereas low stress physicians (n=3) recorded psychosocial information consistently in 67% of encounters. Burned-out physicians discussed a differential diagnosis in only 31% of encounters (low counts concentrated in two physicians) vs. in 73% of non-burned-out doctors’ encounters. Burned-out and non-burned-out doctors spent comparable amounts of time with patients (about 25 min). Conclusions Key diagnostic elements were seen less often in encounter transcripts and notes in burned-out urgent care physicians.

Assessing cognitive function—especially language processing—in severely brain-injured patients is critical for prognostication, care, and development of communication devices (e.g. brain–computer interfaces). In patients with diminished motor function, language processing has been probed using EEG measures of command-following in motor imagery tasks. While such tests eliminate the need for motor response, they require sustained attention. However, passive listening tasks, with an EEG response measure can reduce both motor and attentional demands. These considerations motivated the development of two assays of low-level language processing—identification of differential phoneme-class responses and tracking of the natural speech envelope. This cross-sectional study looks at a cohort of 26 severely brain-injured patient subjects and 10 healthy controls. Patients’ level of function was assessed via the coma recovery scale–revised at the bedside. Patients were also tested for command-following via EEG and/or MRI assays of motor imagery. For the present investigation, EEG was recorded while presenting a 148 s audio clip of Alice in Wonderland. Time-locked EEG responses to phoneme classes were extracted and compared to determine a differential phoneme-class response. Tracking of the natural speech envelope was assessed from the same recordings by cross-correlating the EEG response with the speech envelope. In healthy controls, the dynamics of the two measures were temporally similar but spatially different: a central parieto-occipital component of differential phoneme-class response was absent in the natural speech envelope response. The differential phoneme-class response was present in all patient subjects, including the six classified as vegetative state/unresponsive wakefulness syndrome by behavioural assessment. However, patient subjects with evidence of language processing either by behavioural assessment or motor imagery tests had an early bilateral response in the first 50 ms that was lacking in patient subjects without any evidence of language processing. The natural speech envelope tracking response was also present in all patient subjects and responses in the first 100 ms distinguished patient subjects with evidence of language processing. Specifically, patient subjects with evidence of language processing had a more global response in the first 100 ms whereas those without evidence of language processing had a frontopolar response in that period. In summary, we developed two passive EEG-based methods to probe low-level language processing in severely brain-injured patients. In our cohort, both assays showed a difference between patient subjects with evidence of command-following and those with no evidence of command-following: a more prominent early bilateral response component.

Purpose: To examine whether longitudinal exposure to neighborhood poverty throughout midlife influences the degree of subclinical CVD (SCVD) burden experienced in early old age in a racially and ethnically-diverse cohort of women transitioning through menopause. Methods: We used longitudinal data on 1,212 women (aged 42-52 at baseline) from The Study of Women’s Health Across the Nation . Residential address histories were collected annually for eleven years across midlife (1996-2007). The following carotid ultrasound SCVD measures were collected during a subsequent follow-up visit (2009-2013): intima media thickness (CIMT), inter-adventitial diameter (IAD), and plaque presence. Values >75th percentile of each were considered high (CIMT > 0.79 mm; IAD > 7.21 mm; plaque index >=2) and were summed together to create our composite SCVD index (range: 0-3). We used longitudinal latent class analysis to identify distinct patterns of exposure to high neighborhood poverty among women across midlife, and used ordinal logistic regression models to determine if a woman’s neighborhood poverty class throughout midlife was associated with her future SCVD burden. Results: We identified five longitudinal neighborhood poverty classes across midlife: consistent low (72% of total), decreasing (6.4%), early-increasing (7.3%), late-increasing (5.5%), and consistent high (8.4%). In age and site-adjusted models, the odds of having greater SCVD burden were 70% higher among women living in consistently high poverty neighborhoods (OR=1.70, 95% CI: 1.14-2.54), 52% higher among women experiencing early increases in neighborhood poverty (OR=1.52, 95% CI: 0.97-2.38), and 69% higher among women experiencing late increases in neighborhood poverty (OR=1.69, 95% CI: 1.04-2.74), compared to women living in consistent low poverty throughout midlife. Controlling for social, behavioral, and menopause-associated factors reduced the magnitude and significance of the estimated effects towards the null. Adjusting for baseline age, race/ethnicity, site, education, marital status, employment, alcohol use, smoking, depressive symptoms, physical activity, menopausal status, hypertension, diabetes, and obesity, the estimated odds of greater SCVD burden were 6% higher among women living in consistently high poverty neighborhoods (95% CI: 0.69-1.63), 10% higher among women experiencing early increases in poverty (95% CI: 0.68-1.76), and 17% higher among women experiencing late increases in poverty (95% CI: 0.70-1.94), relative to women living in consistent low poverty neighborhoods across midlife. Conclusions: Women living in neighborhoods with higher levels of poverty throughout midlife had greater SCVD burden in early old age. Associations between neighborhood poverty trajectories and SCVD burden were largely accounted for by individual-level social, behavioral, and biomedical confounders.

Background Problem lists represent an integral component of high-quality care. However, they are often inaccurate and incomplete. We studied the effects of alerts integrated into the inpatient and outpatient computerized provider order entry systems to assist in adding problems to the problem list when ordering medications that lacked a corresponding indication. Methods We analyzed medication orders from 2 healthcare systems that used an innovative indication alert. We collected data at site 1 between December 2018 and January 2020, and at site 2 between May and June 2021. We reviewed random samples of 100 charts from each site that had problems added in response to the alert. Outcomes were: (1) alert yield, the proportion of triggered alerts that led to a problem added and (2) problem accuracy, the proportion of problems placed that were accurate by chart review. Results Alerts were triggered 131 134, and 6178 times at sites 1 and 2, respectively, resulting in a yield of 109 055 (83.2%) and 2874 (46.5%), P< .001. Orders were abandoned, for example, not completed, in 11.1% and 9.6% of orders, respectively, P Conclusions Indication alerts triggered by medication orders initiated in the absence of a justifying diagnosis were useful for populating problem lists, with yields of 83.2% and 46.5% at 2 healthcare systems. Problems were placed with a reasonable level of accuracy, with 90% ± 2% of problems deemed accurate based on chart review.

This is the first article in a two-part series describing subject and family perspectives from the central thalamic deep brain stimulation for the treatment of traumatic brain injury using the Medtronic PC + S first-in-human invasive neurological device trial to achieve cognitive restoration in moderate to severe traumatic brain injury, with subjects who were deemed capable of providing voluntary informed consent. In this article, we report on interviews conducted prior to surgery wherein we asked participants about their experiences recovering from brain injury and their perspectives on study enrollment and participation. We asked how risks and benefits were weighed, what their expectations and fears were, and how decisions were reached about trial participation. We found that informed consent and enrollment decisions are fraught. Subjects and families were often split, with subjects more focused on putative benefits and families concerned about incremental risk. Both subjects and families viewed brain injury as disruptive to personal identity and relationships. As decisions were made about study enrollment, families struggled with recognizing the re-emergent agency of subjects and ceding decision-making authority to subjects who had previously been dependent upon them for protection and guidance. Subjects and family members reported a hope for the relief of cognitive disabilities, improved quality of life, normalization of interpersonal interactions, and a return to work or school as reasons for study participation, along with altruism and a desire to advance science. Despite these aspirations, both subjects and families appreciated the risks of the intervention and did not suffer from a therapeutic misconception. A second essay to be published in the next issue of Cambridge Quarterly of Healthcare Ethics—Clinical Neuroethics will describe interviews conducted after surgery, the effects of cognitive restoration for subjects, families, and challenges presented to the social structures they will call upon to support them through recovery. This subsequent article will be available online prior to its formal publication in October 2023.

The COVID-19 pandemic has created a large population of patients who are slow to recover consciousness following mechanical ventilation and sedation in the intensive care unit. Few clinical scenarios are comparable. Possible exceptions are the rare patients in post-cardiac arrest coma with minimal to no structural brain injuries who recovered cognitive and motor functions after prolonged delays. A common electroencephalogram (EEG) signature seen in these patients is burst suppression [8]. Biophysical modeling has shown that burst suppression is likely a signature of a neurometabolic state that preserves basic cellular function “during states of lowered energy availability.” These states likely act as a brain protective mechanism [9]. Similar EEG patterns are observed in the anoxia resistant painted turtle [24]. We present a conceptual analysis to interpret the brain state of COVID-19 patients suffering prolonged recovery of consciousness. We begin with the Ching model and integrate findings from other clinical scenarios and studies of the anoxia-tolerant physiology of the painted turtle. We postulate that prolonged recovery of consciousness in COVID-19 patients could reflect the effects of modest hypoxic injury to neurons and the unmasking of latent neuroprotective mechanisms in the human brain. This putative protective down-regulated state appears similar to that observed in the painted turtle and suggests new approaches to enhancing coma recovery [12].

We present an exploratory analysis of the occurrence of early corticothalamic connectivity disruption after aneurysmal subarachnoid hemorrhage (SAH) and its correlation with clinical outcomes. We conducted a retrospective study of patients with acute SAH who underwent continuous electroencephalography (EEG) for impairment of consciousness. Only patients undergoing endovascular aneurysm treatment were included. Continuous EEG tracings were reviewed to obtain artifact-free segments. Power spectral analyses were performed, and segments were classified as A (only delta power), B (predominant delta and theta), C (predominant theta and beta), or D (predominant alpha and beta). Each incremental category from A to D implies greater preservation of corticothalamic connectivity. We dichotomized categories as AB for poor connectivity and CD for good connectivity. The modified Rankin Scale score at follow-up and in-hospital mortality were used as outcome measures. Sixty-nine patients were included, of whom 58 had good quality EEG segments for classification: 28 were AB and 30 were CD. Hunt and Hess and World Federation of Neurological Surgeons grades were higher and the initial Glasgow Coma Scale score was lower in the AB group compared with the CD group. AB classification was associated with an adjusted odds ratio of 5.71 (95% confidence interval 1.61–20.30; p

To investigate the prognostic value of a simple stratification system of electroencephalographical (EEG) patterns and spectral types for patients after cardiac arrest.In this prospectively enrolled cohort, using manually selected EEG segments, patients after cardiac arrest were stratified into five independent EEG patterns (based on background continuity and burden of highly epileptiform discharges) and four independent power spectral types (based on the presence of frequency components). The primary outcome is cerebral performance category (CPC) at discharge. Results from multimodal prognostication testing were included for comparison.Of a total of 72 patients, 6 had CPC 1-2 by discharge, all of whom had mostly continuous EEG background without highly epileptiform activity at day 3. However, for the same EEG background pattern at day 3, 19 patients were discharged at CPC 3 and 15 patients at CPC 4-5. After adding spectral analysis, overall sensitivity for predicting good outcomes (CPC 1-2) was 83.3% (95% confidence interval 35.9% to 99.6%) and specificity was 97.0% (89.5% to 99.6%). In this cohort, standard prognostication testing all yielded 100% specificity but low sensitivity, with imaging being the most sensitive at 54.1% (36.9% to 70.5%).Adding spectral analysis to qualitative EEG analysis may further improve the diagnostic accuracy of EEG and may aid developing novel measures linked to good outcomes in postcardiac arrest coma.

Supplemental Digital Content is Available in the Text., COVID-19 necessitated significant care redesign, including new ambulatory workflows to handle surge volumes, protect patients and staff, and ensure timely reliable care. Opportunities also exist to harvest lessons from workflow innovations to benefit routine care. We describe a dedicated COVID-19 ambulatory unit for closing testing and follow-up loops characterized by standardized workflows and electronic communication, documentation, and order placement. More than 85% of follow-ups were completed within 24 hours, with no observed staff, nor patient infections associated with unit operations. Identified issues include role confusion, staffing and gatekeeping bottlenecks, and patient reluctance to visit in person or discuss concerns with phone screeners.

Coma and disorders of consciousness (DoC) are highly prevalent and constitute a burden for patients, families, and society worldwide. As part of the Curing Coma Campaign, the Neurocritical Care Society partnered with the National Institutes of Health to organize a symposium bringing together experts from all over the world to develop research targets for DoC. The conference was structured along six domains: (1) defining endotype/phenotypes, (2) biomarkers, (3) proof-of-concept clinical trials, (4) neuroprognostication, (5) long-term recovery, and (6) large datasets. This proceedings paper presents actionable research targets based on the presentations and discussions that occurred at the conference. We summarize the background, main research gaps, overall goals, the panel discussion of the approach, limitations and challenges, and deliverables that were identified. Supplementary Information The online version contains supplementary material available at 10.1007/s12028-021-01260-x.

ObjectivesThe quest to measure and improve diagnosis has proven challenging; new approaches are needed to better understand and measure key elements of the diagnostic process in clinical encounters. The aim of this study was to develop a tool assessing key elements of the diagnostic assessment process and apply it to a series of diagnostic encounters examining clinical notes and encounters’ recorded transcripts. Additionally, we aimed to correlate and contextualise these findings with measures of encounter time and physician burnout.DesignWe audio-recorded encounters, reviewed their transcripts and associated them with their clinical notes and findings were correlated with concurrent Mini Z Worklife measures and physician burnout.SettingThree primary urgent-care settings.ParticipantsWe conducted in-depth evaluations of 28 clinical encounters delivered by seven physicians.ResultsComparing encounter transcripts with clinical notes, in 24 of 28 (86%) there was high note/transcript concordance for the diagnostic elements on our tool. Reliably included elements were red flags (92% of notes/encounters), aetiologies (88%), likelihood/uncertainties (71%) and follow-up contingencies (71%), whereas psychosocial/contextual information (35%) and mentioning common pitfalls (7%) were often missing. In 22% of encounters, follow-up contingencies were in the note, but absent from the recorded encounter. There was a trend for higher burnout scores being associated with physicians less likely to address key diagnosis items, such as psychosocial history/context.ConclusionsA new tool shows promise as a means of assessing key elements of diagnostic quality in clinical encounters. Work conditions and physician reactions appear to correlate with diagnostic behaviours. Future research should continue to assess relationships between time pressure and diagnostic quality.