Reducing Cardiovascular Risk for Patients With Diabetes: An Evidence-Based, Population Health Management Program.

ABSTRACT: Those with diabetes are at an increased risk of cardiovascular disease (CVD). Safety net clinics serve populations that bear a significant burden of disease and disparities and are a key setting in which to focus on reducing CVD. An integrated health system provided funding and technical assistance (TA) to safety net organizations (community health centers and public hospitals) in Northern California to decrease the risk of cardiovascular events for patients with diabetes. This was a program called Preventing Heart Attacks and Strokes Everyday (PHASE), which combined an evidence-based medication protocol with population health management and team-based care strategies. The TA supported organizations by sharing best practices, providing quality improvement coaching, and facilitating peer learning. A mixed-methods evaluation found that organizations involved in PHASE improved rates of blood pressure control and cardioprotective medication prescriptions for patients with diabetes. They made progress on these measures through strategies such as leveraging team-based care, providing education on evidence-based protocols, and using data to drive improvements. The evaluation concluded that financially supporting and providing focused TA to safety net organizations can help them build capacity and leverage their strengths to improve outcomes and potentially decrease the risk of heart attacks and strokes in communities.

Stratifying Deterioration Risk by Acuity at Admission Offers Triage Insights for Coronavirus Disease 2019 Patients.

OBJECTIVES: Triaging patients at admission to determine subsequent deterioration risk can be difficult. This is especially true of coronavirus disease 2019 patients, some of whom experience significant physiologic deterioration due to dysregulated immune response following admission. A well-established acuity measure, the Rothman Index, is evaluated for stratification of patients at admission into high or low risk of subsequent deterioration. DESIGN: Multicenter retrospective study. SETTING: One academic medical center in Connecticut, and three community hospitals in Connecticut and Maryland. PATIENTS: Three thousand four hundred ninety-nine coronavirus disease 2019 and 14,658 noncoronavirus disease 2019 adult patients admitted to a medical service between January 1, 2020, and September 15, 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Performance of the Rothman Index at admission to predict in-hospital mortality or ICU utilization for both general medical and coronavirus disease 2019 populations was evaluated using the area under the curve. Precision and recall for mortality prediction were calculated, high- and low-risk thresholds were determined, and patients meeting threshold criteria were characterized. The Rothman Index at admission has good to excellent discriminatory performance for in-hospital mortality in the coronavirus disease 2019 (area under the curve, 0.81-0.84) and noncoronavirus disease 2019 (area under the curve, 0.90-0.92) populations. We show that for a given admission acuity, the risk of deterioration for coronavirus disease 2019 patients is significantly higher than for noncoronavirus disease 2019 patients. At admission, Rothman Index-based thresholds segregate the majority of patients into either high- or low-risk groups; high-risk groups have mortality rates of 34-45% (coronavirus disease 2019) and 17-25% (noncoronavirus disease 2019), whereas low-risk groups have mortality rates of 2-5% (coronavirus disease 2019) and 0.2-0.4% (noncoronavirus disease 2019). Similarly large differences in ICU utilization are also found. CONCLUSIONS: Acuity level at admission may support rapid and effective risk triage. Notably, in-hospital mortality risk associated with a given acuity at admission is significantly higher for coronavirus disease 2019 patients than for noncoronavirus disease 2019 patients. This insight may help physicians more effectively triage coronavirus disease 2019 patients, guiding level of care decisions and resource allocation.

A Novel Model for Enhanced Prediction and Understanding of Unplanned 30-Day Pediatric Readmission.

OBJECTIVES: To develop a model to assist clinicians in reducing 30-day unplanned pediatric readmissions and to enhance understanding of risk factors leading to such readmissions. METHODS: Data consisting of 38 143 inpatient clinical encounters at a tertiary pediatric hospital were retrieved, and 50% were used for training on a multivariate logistic regression model. The pediatric Rothman Index (pRI) was 1 of the novel candidate predictors considered. Multivariate model selection was conducted by minimization of Akaike Information Criteria. The area under the receiver operator characteristic curve (AUC) and values for sensitivity, specificity, positive predictive value, relative risk, and accuracy were computed on the remaining 50% of the data. RESULTS: The multivariate logistic regression model of readmission consists of 7 disease diagnosis groups, 4 measures of hospital resource use, 3 measures of disease severity and/or medical complexities, and 2 variables derived from the pRI. Four of the predictors are novel, including history of previous 30-day readmissions within last 6 months (P < .001), planned admissions (P < .001), the discharge pRI score (P < .001), and indicator of whether the maximum pRI occurred during the last 24 hours of hospitalization (P = .005). An AUC of 0.79 (0.77-0.80) was obtained on the independent test data set. CONCLUSIONS: Our model provides significant performance improvements in the prediction of unplanned 30-day pediatric readmissions with AUC higher than the LACE readmission model and other general unplanned 30-day pediatric readmission models. The model is expected to provide an opportunity to capture 39% of readmissions (at a selected operating point) and may therefore assist clinicians in reducing avoidable readmissions.

Development and validation of a continuously age-adjusted measure of patient condition for hospitalized children using the electronic medical record.

Awareness of a patient's clinical status during hospitalization is a primary responsibility for hospital providers. One tool to assess status is the Rothman Index (RI), a validated measure of patient condition for adults, based on empirically derived relationships between 1-year post-discharge mortality and each of 26 clinical measurements available in the electronic medical record. However, such an approach cannot be used for pediatrics, where the relationships between risk and clinical variables are distinct functions of patient age, and sufficient 1-year mortality data for each age group simply do not exist. We report the development and validation of a new methodology to use adult mortality data to generate continuously age-adjusted acuity scores for pediatrics. Clinical data were extracted from EMRs at three pediatric hospitals covering 105,470 inpatient visits over a 3-year period. The RI input variable set was used as a starting point for the development of the pediatric Rothman Index (pRI). Age-dependence of continuous variables was determined by plotting mean values versus age. For variables determined to be age-dependent, polynomial functions of mean value and mean standard deviation versus age were constructed. Mean values and standard deviations for adult RI excess risk curves were separately estimated. Based on the "find the center of the channel" hypothesis, univariate pediatric risk was then computed by applying a z-score transform to adult mean and standard deviation values based on polynomial pediatric mean and standard deviation functions. Multivariate pediatric risk is estimated as the sum of univariate risk. Other age adjustments for categorical variables were also employed. Age-specific pediatric excess risk functions were compared to age-specific expert-derived functions and to in-hospital mortality. AUC for 24-h mortality and pRI scores prior to unplanned ICU transfers were computed. Age-adjusted risk functions correlated well with similar functions in Bedside PEWS and PAWS. Pediatric nursing data correlated well with risk as measured by mortality odds ratios. AUC for pRI for 24-h mortality was 0.93 (0.92, 0.94), 0.93 (0.93, 0.93) and 0.95 (0.95, 0.95) at the three pediatric hospitals. Unplanned ICU transfers correlated with lower pRI scores. Moreover, pRI scores declined prior to such events. A new methodology to continuously age-adjust patient acuity provides a tool to facilitate timely identification of physiologic deterioration in hospitalized children.

Sepsis as 2 problems: Identifying sepsis at admission and predicting onset in the hospital using an electronic medical record-based acuity score.

PURPOSE: Early identification and treatment improve outcomes for patients with sepsis. Current screening tools are limited. We present a new approach, recognizing that sepsis patients comprise 2 distinct and unequal populations: patients with sepsis present on admission (85%) and patients who develop sepsis in the hospital (15%) with mortality rates of 12% and 35%, respectively. METHODS: Models are developed and tested based on 258 836 adult inpatient records from 4 hospitals. A "present on admission" model identifies patients admitted to a hospital with sepsis, and a "not present on admission" model predicts postadmission onset. Inputs include common clinical measurements and the Rothman Index. Sepsis was determined using International Classification of Diseases, Ninth Revision, codes. RESULTS: For sepsis present on admission, area under the curves ranged from 0.87 to 0.91. Operating points chosen to yield 75% and 50% sensitivity achieve positive predictive values of 17% to 25% and 29% to 40%, respectively. For sepsis not present on admission, at 65% sensitivity, positive predictive values ranged from 10% to 20% across hospitals. CONCLUSIONS: This approach yields good to excellent discriminatory performance among adult inpatients for predicting sepsis present on admission or developed within the hospital and may aid in the timely delivery of care.

Measuring the modified early warning score and the Rothman index: advantages of utilizing the electronic medical record in an early warning system.

Early detection of an impending cardiac or pulmonary arrest is an important focus for hospitals trying to improve quality of care. Unfortunately, all current early warning systems suffer from high false-alarm rates. Most systems are based on the Modified Early Warning Score (MEWS); 4 of its 5 inputs are vital signs. The purpose of this study was to compare the accuracy of MEWS against the Rothman Index (RI), a patient acuity score based upon summation of excess risk functions that utilize additional data from the electronic medical record (EMR). MEWS and RI scores were computed retrospectively for 32,472 patient visits. Nursing assessments, a category of EMR inputs only used by the RI, showed sharp differences 24 hours before death. Receiver operating characteristic curves for 24-hour mortality demonstrated superior RI performance with c-statistics, 0.82 and 0.93, respectively. At the point where MEWS triggers an alarm, we identified the RI point corresponding to equal sensitivity and found the positive likelihood ratio (LR+) for MEWS was 7.8, and for the RI was 16.9 with false alarms reduced by 53%. At the RI point corresponding to equal LR+, the sensitivity for MEWS was 49% and 77% for RI, capturing 54% more of those patients who will die within 24 hours.

Development and validation of a continuous measure of patient condition using the Electronic Medical Record.

Patient condition is a key element in communication between clinicians. However, there is no generally accepted definition of patient condition that is independent of diagnosis and that spans acuity levels. We report the development and validation of a continuous measure of general patient condition that is independent of diagnosis, and that can be used for medical-surgical as well as critical care patients. A survey of Electronic Medical Record data identified common, frequently collected non-static candidate variables as the basis for a general, continuously updated patient condition score. We used a new methodology to estimate in-hospital risk associated with each of these variables. A risk function for each candidate input was computed by comparing the final pre-discharge measurements with 1-year post-discharge mortality. Step-wise logistic regression of the variables against 1-year mortality was used to determine the importance of each variable. The final set of selected variables consisted of 26 clinical measurements from four categories: nursing assessments, vital signs, laboratory results and cardiac rhythms. We then constructed a heuristic model quantifying patient condition (overall risk) by summing the single-variable risks. The model's validity was assessed against outcomes from 170,000 medical-surgical and critical care patients, using data from three US hospitals. Outcome validation across hospitals yields an area under the receiver operating characteristic curve(AUC) of ≥0.92 when separating hospice/deceased from all other discharge categories, an AUC of ≥0.93 when predicting 24-h mortality and an AUC of 0.62 when predicting 30-day readmissions. Correspondence with outcomes reflective of patient condition across the acuity spectrum indicates utility in both medical-surgical units and critical care units. The model output, which we call the Rothman Index, may provide clinicians with a longitudinal view of patient condition to help address known challenges in caregiver communication, continuity of care, and earlier detection of acuity trends.

Placing clinical variables on a common linear scale of empirically based risk as a step towards construction of a general patient acuity score from the electronic health record: a modelling study.

OBJECTIVE: To explore the hypothesis that placing clinical variables of differing metrics on a common linear scale of all-cause postdischarge mortality provides risk functions that are directly correlated with in-hospital mortality risk. DESIGN: Modelling study. SETTING: An 805-bed community hospital in the southeastern USA. PARTICIPANTS: 42302 inpatients admitted for any reason, excluding obstetrics, paediatric and psychiatric patients. OUTCOME MEASURES: All-cause in-hospital and postdischarge mortalities, and associated correlations. RESULTS: Pearson correlation coefficients comparing in-hospital risks with postdischarge risks for creatinine, heart rate and a set of 12 nursing assessments are 0.920, 0.922 and 0.892, respectively. Correlation between postdischarge risk heart rate and the Modified Early Warning System (MEWS) component for heart rate is 0.855. The minimal excess risk values for creatinine and heart rate roughly correspond to the normal reference ranges. We also provide the risks for values outside that range, independent of expert opinion or a regression model. By summing risk functions, a first-approximation patient risk score is created, which correctly ranks 6 discharge categories by average mortality with p<0.001 for differences in category means, and Tukey's Honestly Significant Difference Test confirmed that the means were all different at the 95% confidence level. CONCLUSIONS: Quantitative or categorical clinical variables can be transformed into risk functions that correlate well with in-hospital risk. This methodology provides an empirical way to assess inpatient risk from data available in the Electronic Health Record. With just the variables in this paper, we achieve a risk score that correlates with discharge disposition. This is the first step towards creation of a universal measure of patient condition that reflects a generally applicable set of health-related risks. More importantly, we believe that our approach opens the door to a way of exploring and resolving many issues in patient assessment.

Clinical implications and validity of nursing assessments: a longitudinal measure of patient condition from analysis of the Electronic Medical Record.

OBJECTIVES: This study investigates risk of mortality associated with nurses' assessments of patients by physiological system. We hypothesise that nursing assessments of in-patients performed at entry correlate with in-hospital mortality, and those performed just before discharge correlate with postdischarge mortality. DESIGN: Cohort study of in-hospital and postdischarge mortality of patients over two 1-year periods. SETTING: An 805-bed community hospital in Sarasota, Florida, USA. SUBJECTS: 42 302 inpatients admitted for any reason, excluding obstetrics, paediatric and psychiatric patients. OUTCOME MEASURES: All-cause mortalities and mortality OR. RESULTS: Patients whose entry nursing assessments, other than pain, did not meet minimum standards had significantly higher in-hospital mortality than patients meeting minimums; and final nursing assessments before discharge had large OR for postdischarge mortality. In-hospital mortality OR were found to be: food, 7.0; neurological, 9.4; musculoskeletal, 6.9; safety, 5.6; psychosocial, 6.7; respiratory, 8.1; skin, 5.2; genitourinary, 3.0; gastrointestinal, 2.3; peripheral-vascular, 3.9; cardiac, 2.8; and pain, 1.1. CI at 95% are within ±20% of these values, with p<0.001 (except for pain). Similar results applied to postdischarge mortality. All results were comparable across the two 1-year periods, with 0.85 intraclass correlation coefficient. CONCLUSIONS: Nursing assessments are strongly correlated with in-hospital and postdischarge mortality. No multivariate analysis has yet been performed, and will be the subject of a future study, thus there may be confounding factors. Nonetheless, we conclude that these assessments are clinically meaningful and valid. Nursing assessment data, which are currently unused, may allow physicians to improve patient care. The mortality OR and the dynamic nature of nursing assessments suggest that nursing assessments are sensitive indicators of a patient's condition. While these conclusions must remain qualified, pending future multivariate analyses, nursing assessment data ought to be incorporated in risk-related health research, and changes in record-keeping software are needed to make this information more accessible.

Marital satisfaction across the transition to parenthood.

The purpose of the present study was to discriminate between the 2 dominant perspectives governing research on the nature of marital change over the transition to parenthood. Progress can be made in understanding this transition by recognizing the role of uncontrolled sources of variability in research designs, defining and using control groups, and timing of data collection around the child's arrival, and the authors conducted a study incorporating these methodological refinements. Growth curve analyses were conducted on marital satisfaction data collected twice before and twice after the birth of the 1st child and at corresponding points for voluntarily childless couples (N = 156 couples). Spouses who were more satisfied prior to pregnancy had children relatively early in marriage, and parents experienced greater declines in marital satisfaction compared to nonparents. Couples with planned pregnancies had higher prepregnancy satisfaction scores, and planning slowed husbands' (but not wives') postpartum declines. In sum, parenthood hastens marital decline--even among relatively satisfied couples who select themselves into this transition--but planning status and prepregnancy marital satisfaction generally protect marriages from these declines.

Computed Tomography is Diagnostic in the Cervical Imaging of Helmeted Football Players With Shoulder Pads.

OBJECTIVE: Prospective, observational case series evaluating the value of cervical spine computed tomography (CT) scans in the initial evaluation of a helmeted football player with suspected cervical spine injury. SUBJECTS: Five asymptomatic male football players, fully equipped and immobilized on a backboard. DESIGN: Multiple 3.0-mm, helically acquired, axially displayed CT images of the cervical spine were obtained from the skull base inferiorly through T1, with images filmed at soft tissue and bone windows. Sagittal and coronal reformatted images were performed. Software was used to minimize metallic artifact. MEASUREMENTS: All series were reviewed by a Board-certified neuroradiologist for image clarity and diagnostic capability. RESULTS: Lateral scout films demonstrated mild segmental degradation, depending on the location of the metallic snaps overlying the spine. Anteroposterior scout films and bone window images were of diagnostic quality. The soft tissue windows showed minimal localized artifact occurring at the same levels as in the lateral scout views. This minimal beam-hardening streak artifact did not affect the diagnostic quality of the soft tissue windows. Reconstructed images were uniformly of clinical diagnostic quality. DISCUSSION: When CT scans were reviewed as a unit, sufficient information was available to allow reliable clinical decisions about the helmeted football player. In light of recent publications demonstrating the difficulty of obtaining adequate radiographs to evaluate cervical spine injury in equipped football players, helmeted athletes may undergo CT scanning without any significant diagnostic limitations.

MRI is nondiagnostic in cervical spine imaging of the helmeted football player with shoulder pads.

BACKGROUND: It is currently recommended that helmet and shoulder pads remain in place during the initial clinical and radiographic evaluation of the helmeted athlete with a potential cervical spine injury. The objective of this prospectively designed, single-subject study was to determine whether MRI may play a role in the initial evaluation and management of the helmeted football player with a cervical spine injury. METHODS: One male athlete was fitted using equipment (football helmet [Riddell], shoulder pads [Douglas]) worn during the collegiate season at Lehigh University. Standard MRI using a routine clinical 0.7 T high field open MRI scanner (GE Signa System, Milwaukee, WI) was employed for the evaluation using standard clinical parameters (sagittal T1, fast spin echo [FSE] T2, STIR, and axial FSE T2 series). A single board-certified, fellowship-trained neuroradiologist reviewed all series. Studies were evaluated for image clarity and diagnostic capability in this clinical setting. RESULTS: All standard MRI series were of extremely limited quality, even using sequences and slice selection designed to minimize artifact associated with metals (FSE T2-weighted series). When all MRI series were reviewed as a whole, sufficient evidence was not available to allow clinical decision making. CONCLUSIONS: The amount and type of metal within the standard football helmet and shoulder pads result in sufficient field inhomogeneity and SKEW artifact to preclude adequate evaluation of the cervical structures, rendering MRI evaluation in this setting not clinically useful. This study shows that current MRI techniques play no role in the clearance of the cervical spine (with currently available brands of helmet and shoulder pads in place) without prior equipment removal or manipulation.

Pursuing perfection: an interview with Don Berwick and Michael Rothman. Interview by Andrea Kabcenell and Jane Roessner.

Don Berwick and Michael Rothman discuss the Pursuing Perfection initiative, which is intended to help health care organizations integrate improvement work into day-to-day life, with systemwide changes in infrastructure, project management, care, and leadership.