Centering Equity and Fostering Stakeholder Collaboration and Trust-Pillars of the Maternal Health Innovation Program in Maryland.

Objective: To describe two main pillars of the Maryland Maternal Health Innovation Program (MDMOM): (1) centering equity and (2) fostering broad stakeholder collaboration and trust. Methods: We summarized MDMOM's key activities and used severe maternal morbidity (SMM) surveillance and program monitoring data to quantify MDMOM's work on the two pillars. We developed measures of hospital engagement with MDMOM (participation in quality improvement [QI] activities, participation in check-in meetings, staff involvement) and with other partners (participation in QI activities, representation in state-level groups). We examined Bonferroni-adjusted correlations between these hospital engagement measures and with key hospital characteristics: level of maternity care, annual delivery volume, and SMM rate. Results: Over 100 national and state organizations and individual stakeholders contributed to our building the MDMOM program and implementing key activities centering equity: hospital-based SMM surveillance in 20 of Maryland's 32 hospitals; almost 5,000 trainings offered to perinatal health care providers; two telemedicine/telehealth interventions; training of home visitors and community-based organization staff. Birthing hospitals represent MDMOM's main implementation partners. The strength of their participation in MDMOM QI activities is positively correlated to their participation in check-in meetings and with the degree of involvement by physicians in such activities. Higher engagement in MDMOM QI activities is also positively correlated to hospitals' participation in other state-level maternal health initiatives or groups. Conclusion: Our experience with the MDMOM program demonstrates that an equity focus and broad stakeholder collaboration building strong relationships and providing implementation support can lead to high levels of engagement in innovative maternal health interventions.

Findings From Severe Maternal Morbidity Surveillance and Review in Maryland.

Importance: In the US, more than 50 000 women experience severe maternal morbidity (SMM) each year, and the SMM rate more than doubled during the past 25 years. In response, professional organizations called for birthing facilities to routinely identify and review SMM events and identify prevention opportunities. Objective: To examine SMM levels, primary causes, and factors associated with the preventability of SMM using Maryland's SMM surveillance and review program. Design, Setting, and Participants: This cross-sectional study included pregnant and postpartum patients at 42 days or less after delivery who were hospitalized at 1 of 6 birthing hospitals in Maryland between August 1, 2020, and November 30, 2021. Hospital-based SMM surveillance was conducted through a detailed review of medical records. Exposures: Hospitalization during pregnancy or within 42 days post partum. Main Outcomes and Measures: The main outcomes were admission to an intensive care unit, having at least 4 U of red blood cells transfused, and/or having COVID-19 infection requiring inpatient hospital care. Results: A total of 192 SMM events were identified and reviewed. Patients with SMM had a mean [SD] age of 31 [6.49] years; 9 [4.7%] were Asian, 27 [14.1%] were Hispanic, 83 [43.2%] were non-Hispanic Black, and 68 [35.4%] were non-Hispanic White. Obstetric hemorrhage was the leading primary cause of SMM (83 [43.2%]), followed by COVID-19 infection (57 [29.7%]) and hypertensive disorders of pregnancy (17 [8.9%]). The SMM rate was highest among Hispanic patients (154.9 per 10 000 deliveries), primarily driven by COVID-19 infection. The rate of SMM among non-Hispanic Black patients was nearly 50% higher than for non-Hispanic White patients (119.9 vs 65.7 per 10 000 deliveries). The SMM outcome assessed could have been prevented in 61 events (31.8%). Clinician-level factors and interventions in the antepartum period were most frequently cited as potentially altering the SMM outcome. Practices that were performed well most often pertained to hospitals' readiness and adequate response to managing pregnancy complications. Recommendations for care improvement focused mainly on timely recognition and rapid response to such. Conclusions and Relevance: The findings of this cross-sectional study, which used hospital-based SMM surveillance and review beyond the mere exploration of administrative data, offers opportunities for identifying valuable quality improvement strategies to reduce SMM. Immediate strategies to reduce SMM in Maryland should target its most common causes and address factors associated with preventability identified at individual hospitals.

Covid-19 Mortality in an Acute Care Hospital: Association of Patient Factors With Decision to Forego the Intensive Care Unit.

BACKGROUND: Public awareness of the large mortality toll of COVID-19 particularly among elderly and frail persons is high. This public awareness represents an enhanced opportunity for early and urgent goals-of-care discussions to reduce medically ineffective care. OBJECTIVE: To assess the end-of-life experiences of hospitalized patients dying of COVID-19 with respect to identifying the clinical factors associated with utilization or non-utilization of the ICU. METHODS: Retrospective cohort study of hospital outcomes using electronic medical records and individual chart review from March 15, 2020 to October 15, 2020 of every patient with a COVID-19 diagnosis who died or was admitted to hospice while hospitalized. Logistic regression multivariate analysis was used to identify the clinical and demographic factors associated with non-utilization of the ICU. RESULTS: 133/749 (18%) of hospitalized COVID-19 patients died or were admitted to hospice as a result of COVID-19. Of the 133, 66 (49.6%) had no ICU utilization. In multivariate analysis, the significant patient factors associated with non-ICU utilization were increasing age, normal body mass index, and the presence of an advanced directive calling for limited life sustaining therapies. Race and residence at time of admission (home vs. facility) were significant only in the unadjusted analyses but not in adjusted. Gender was not significant in either form of analyses. CONCLUSION: Goals of care discussions performed by an augmented palliative care team and other bedside clinicians had renewed urgency during COVID-19. Large percentages of patients and surrogates, perhaps motivated by public awareness of poor outcomes, opted not to utilize the ICU.

Risk factors for severe illness in hospitalized Covid-19 patients at a regional hospital.

BACKGROUND: The Covid-19 pandemic threatens to overwhelm scarce clinical resources. Risk factors for severe illness must be identified to make efficient resource allocations. OBJECTIVE: To evaluate risk factors for severe illness. DESIGN: Retrospective, observational case series. SETTING: Single-institution. PARTICIPANTS: First 117 consecutive patients hospitalized for Covid-19 from March 1 to April 12, 2020. EXPOSURE: None. MAIN OUTCOMES AND MEASURES: Intensive care unit admission or death. RESULTS: In-hospital mortality was 24.8% and average total length of stay was 11.82 days (95% CI: 10.01 to 13.63 days). 30.8% of patients required intensive care unit admission and 29.1% required mechanical ventilation. Multivariate regression identified the amount of supplemental oxygen required at admission (OR: 1.208, 95% CI: 1.011-1.443, p = .037), sputum production (OR: 6.734, 95% CI: 1.630-27.812, p = .008), insulin dependent diabetes mellitus (OR: 11.873, 95% CI: 2.218-63.555, p = .004) and chronic kidney disease (OR: 4.793, 95% CI: 1.528-15.037, p = .007) as significant risk factors for intensive care unit admission or death. Of the 48 patients who were admitted to the intensive care unit or died, this occurred within 3 days of arrival in 42%, within 6 days in 71%, and within 9 days in 88% of patients. CONCLUSIONS: At our regional medical center, patients with Covid-19 had an average length of stay just under 12 days, required ICU care in 31% of cases, and had a 25% mortality rate. Patients with increased sputum production and higher supplemental oxygen requirements at admission, and insulin dependent diabetes or chronic kidney disease may be at increased risk for severe illness. A model for predicting intensive care unit admission or death with excellent discrimination was created that may aid in treatment decisions and resource allocation. Early identification of patients at increased risk for severe illness may lead to improved outcomes in patients hospitalized with Covid-19.

The Perceptions of Cancer Patients Regarding the Causes and Preventability of Unplanned Hospital Admissions.

OBJECTIVE: The objective of this study was to determine the attitudes of oncology patients regarding the causes and preventability of unplanned hospitalizations. METHODS: Convenience sample using a 36-question survey instrument adapted from prior studies of hospital readmissions. RESULTS: A total of 95 evaluable patients answered >75% of survey items. Majorities (64%) agreed that they desired to avoid the admission, but disagreed (79%) that their own admission was preventable. Patients did not generally express lack confidence in their overall self-management abilities (only 36% agreed) or dissatisfaction with the level of home support, emotional or equipment (only 11% to 26% agreed). Patients did not complain of an inability to access their oncology care team (only 14% agreed), yet a strong majority (79%) endorsed the idea that emergency department visits represent the "quickest and easiest way to get needed care" and that the "hospital is the best place for me when I am sick" (60%). Overall, 79% indicated that their oncology care team directed them to visit the emergency department for evaluation. Most results did not differ by demographic factors. CONCLUSIONS: These results differ from previous results that use methods other than a direct patient survey to determine the preventability or root causes of unplanned hospital admissions/ or readmissions. Accordingly, patient support programs may not address the root causes of unplanned admissions. The use of the emergency department for unplanned care may represent local culture and institutions planning reduction efforts should include patent perceptions to plan a holistic solution.

Retrospective Observational Study of the Clinical Performance Characteristics of a Machine Learning Approach to Early Sepsis Identification.

To estimate performance characteristics and impact on care processes of a machine learning, early sepsis recognition tool embedded in the electronic medical record. DESIGN: Retrospective review of electronic medical records and outcomes to determine sepsis prevalence among patients about whom a warning was received in real time and timing of that warning compared with clinician recognition of potential sepsis as determined by actions documented in the electronic medical record. SETTING: Acute care, nonteaching hospital. PATIENTS: Patients in the emergency department, observation unit, and adult inpatient care units who had sepsis diagnosed either by clinical codes or by Center for Medicare and Medicaid Services Severe Sepsis and Septic Shock: Management Bundle (SEP-1) criteria for severe sepsis and patients who had machine learning-generated advisories about a high risk of sepsis. INTERVENTIONS: Noninterventional study. MEASUREMENTS AND MAIN RESULTS: Using two different definitions of sepsis as "true" sepsis, we measured the sensitivity and early warning clinical utility. Using coded sepsis to define true positives, we measured the positive predictive value of the early warnings. Sensitivity was 28.6% and 43.6% for coded sepsis and severe sepsis, respectively. The positive predictive value of an alert was 37.9% for coded sepsis. Clinical utility (true positive and earlier advisory than clinical recognition) was 2.2% and 1.6% for the two different definitions of sepsis. Use of the tool did not improve sepsis mortality rates. CONCLUSIONS: Performance characteristics were different than previously described in this retrospective assessment of real-time warnings. Real-world testing of retrospectively validated models is essential. The early warning clinical utility may vary depending on a hospital's state of sepsis readiness and embrace of sepsis order bundles.

Implementation of solutions to reduce opioid-induced oversedation and respiratory depression.

PURPOSE: The implementation of interventions to mitigate the causes of opioid-induced oversedation and respiratory depression (OSRD) is reported. SUMMARY: A single-site retrospective review of eligible rescue naloxone cases was conducted to identify the causes of opioid-induced OSRD in a hospital as well as to identify risk factors. A survey was used to assess potential opioid knowledge deficits among hospitalist prescribers. Based on the findings of the case reviews and results of the opioid knowledge assessments, a series of interventions to address noted deficiencies was implemented over the ensuing months, including enhanced monitoring for sedation, improved clinical decision support in the electronic medical record (EMR), and various adjustments to dosing for high-risk patients. The primary endpoint of our analysis was naloxone use for documented cases of opioid-induced OSRD to determine the effectiveness of the interventions. A mean of 16 OSRD events occurred per quarter before intervention implementation. An average of five risk factors (range, two to six) was found among OSRD cases, most commonly age of >60, obesity, and comorbidities of the kidneys and lungs. Deficiencies of clinical care were found in four inter-related domains: knowledge deficits, inadequate monitoring, failure to leverage the EMR, and cultural issues regarding pain assessments and sedation management. CONCLUSION: Implementation of solution bundles that utilized an EMR to create meaningful clinical decision support and cultural changes related to pain goals and communication about sedation level at an acute care hospital resulted in a fivefold reduction in OSRD events that has been sustained for two years.

End-of-Life Care Patterns at a Community Hospital: The Rest of the Story.

We undertook a retrospective review of a subset of expired patients at our community hospital to evaluate end-of-life care patterns and the use of advanced care planning tools among patients who died in the hospital. These 162 expired patients fell into 1 of the 3 diagnosis-related groups of cardiac, respiratory, or infectious disease. Seventy-nine percent of patients arrived to the hospital with no requested limitations in the extent of resuscitative efforts, even though 98% of all patients had major or extreme severity of illness and risk of mortality scores. The presence of an advance directive requesting a limitation of resuscitative efforts modestly impacted resources and procedures, even though utilization in this group was high. Among the 21% of patients with preexisting limits, 21% requested more aggressive support during their course. Critical care unit utilization was seen in 69% of patients for a median of 48 hours. A request for palliative care consultation was received in 44% of patients but only occurred in 30% of all patients due to the short period between the consultation request and patient death (median 37 hours). Among this group of dying patients, engagement of the palliative care team came too late in the course of many patients, suggesting that automated tools embedded in the electronic medical record might be helpful in the identification of appropriate patients earlier.