COVID-19 pandemic effects: Examining prenatal internalizing symptoms and infant temperament.

For pregnant women, the COVID-19 pandemic has resulted in unprecedented stressors, including uncertainty regarding prenatal care and the long-term consequences of perinatal infection. However, few studies have examined the role of this adverse event on maternal wellbeing and infant socioemotional development following the initial wave of the pandemic when less stringent public health restrictions were in place. The current study addressed these gaps in the literature by first comparing prenatal internalizing symptoms and infant temperament collected after the first wave of the pandemic to equivalent measures in a pre-pandemic sample. Second, associations between prenatal pandemic-related stress and infant temperament were examined. Women who were pregnant during the COVID-19 pandemic endorsed higher pregnancy-specific anxiety relative to the pre-pandemic sample. They also reported greater infant negative emotionality and lower positive affectivity and regulatory capacity at 2 months postpartum. Prenatal infection stress directly predicted infant negative affect. Both prenatal infection and preparedness stress were indirectly related to infant negative emotionality through depression symptoms during pregnancy and at 2 months postpartum. These results have implications for prenatal mental health screening procedures during the pandemic and the development of early intervention programs for infants born to mothers during this adverse event.

Perinatal hair cortisol concentrations linked to psychological distress and unpredicted birth complications.

Maternal well-being and stress during the perinatal period have been hypothesized to influence birth outcomes and the postnatal development of offspring. In the present study, we explored whether hair cortisol concentration (HCC) was related to symptoms of psychological distress during the perinatal period and with unpredicted birth complications (UBCs). Surveys measuring symptoms of perceived stress, state/trait anxiety, and depression were collected from 53 participants (mean age = 31.1, SD = 4.04; 83% Caucasian, 17% other races) during the third trimester and again at two and six months after birth, 24.5% of which reported UBCs. In a subset of participants, we measured HCC in hair samples collected during the third trimester (27-39 weeks) and six months after birth. Compared to participants reporting normal births, those reporting UBCs had significantly elevated composite stress, anxiety, and depression (SAD) scores two months after birth, but scores decreased by six months postpartum. During the third trimester, HCC was positively associated with reported SAD scores, and HCC was elevated in participants reporting birth complications. Logistic regression showed HCC, but not SAD scores, predicted UBCs (p = 0.023, pseudo R2= 19.7%). Repeated measures MANOVA showed HCC varied over the perinatal period depending on both SAD scores reported at two months postpartum and the experience of UBCs; but when SAD scores reported at six months postpartum were included in the model, the association between HCC and SAD scores and the influence of UBCs was diminished. Although generalizability is limited by our relatively small, homogeneous sample, findings support a positive association between reported psychological distress and HCC during pregnancy and at two months postpartum. We also report a novel finding that chronically elevated cortisol concentrations during pregnancy were related to the risk of UBCs and remain elevated through the early postpartum period, suggesting the importance of monitoring both psychological distress and HCC during the perinatal period.

Associations between mothers' and fathers' depression and anxiety prior to birth and infant temperament trajectories over the first year of life: Evidence from diagnoses and symptom severity.

BACKGROUND: Developmental shifts in infant temperament predict distal outcomes including emerging symptoms of psychopathology in childhood. Thus, it is critical to gain insight into factors that shape these developmental shifts. Although parental depression and anxiety represent strong predictors of infant temperament in cross-sectional research, few studies have examined how these factors influence temperament trajectories across infancy. METHODS: We used latent growth curve modeling to examine whether mothers' and fathers' anxiety and depression, measured in two ways - as diagnostic status and symptom severity - serve as unique predictors of developmental shifts in infant temperament from 3 to 12 months. Participants included mothers (N = 234) and a subset of fathers (N = 142). Prior to or during pregnancy, both parents were assessed for lifetime diagnoses of depression and anxiety as well as current severity levels. Mothers rated their infants' temperament at 3, 6, and 12 months of age. RESULTS: Mothers' depression and anxiety primarily predicted initial levels of temperament at 3 months. Controlling for mothers' symptoms, fathers' depression and anxiety largely related to temperament trajectories across infancy. Lifetime diagnoses and symptom severities were associated with distinct patterns. LIMITATIONS: Infant temperament was assessed using a parent-report measure. Including an observational measure would provide a more comprehensive picture of the infants' functioning. CONCLUSIONS: These results indicate that mothers' and fathers' mental health are uniquely associated with infant temperament development when measured using diagnostic status and/or symptom severity. Future studies should examine whether these temperament trajectories mediate intergenerational transmission of risk for depression and anxiety.

Prenatal internalizing symptoms as a mediator linking maternal adverse childhood experiences with infant temperament.

BACKGROUND: Maternal adverse childhood experiences are known to significantly influence offspring development. However, mediators linking maternal early-life adversity with infant temperament remain largely unknown. AIMS: The current study investigated whether prenatal internalizing symptoms mediate the association between maternal adverse childhood experiences and infant temperament at two months. Maternal sensitivity/responsiveness during the postpartum period was also examined as a moderator of these associations. STUDY DESIGN: We used a repeated-measures design, with self-report measures administered during pregnancy. Self-report and observational data were also collected at 2 months postpartum. SUBJECTS: The study included a community sample of 64 pregnant women and their infants. OUTCOME MEASURES: Participants completed measures assessing their early-life adversity and current depression/anxiety symptoms. At two months postpartum, mothers reported on their infant's temperament and participated in a parent-child interaction task designed to assess maternal sensitivity/responsiveness. RESULTS AND CONCLUSIONS: Maternal adverse childhood experiences indirectly predicted poor self-regulation during early infancy via prenatal internalizing symptoms. Maternal sensitivity/responsiveness was also found to moderate the association between maternal adverse childhood experiences and certain aspects of infant regulatory capacity and positive affectivity at two months. This research has implications for mental health screening procedures during pregnancy and the development of early intervention programs.

Using machine learning to understand age and gender classification based on infant temperament.

Age and gender differences are prominent in the temperament literature, with the former particularly salient in infancy and the latter noted as early as the first year of life. This study represents a meta-analysis utilizing Infant Behavior Questionnaire-Revised (IBQ-R) data collected across multiple laboratories (N = 4438) to overcome limitations of smaller samples in elucidating links among temperament, age, and gender in early childhood. Algorithmic modeling techniques were leveraged to discern the extent to which the 14 IBQ-R subscale scores accurately classified participating children as boys (n = 2,298) and girls (n = 2,093), and into three age groups: youngest (< 24 weeks; n = 1,102), mid-range (24 to 48 weeks; n = 2,557), and oldest (> 48 weeks; n = 779). Additionally, simultaneous classification into age and gender categories was performed, providing an opportunity to consider the extent to which gender differences in temperament are informed by infant age. Results indicated that overall age group classification was more accurate than child gender models, suggesting that age-related changes are more salient than gender differences in early childhood with respect to temperament attributes. However, gender-based classification was superior in the oldest age group, suggesting temperament differences between boys and girls are accentuated with development. Fear emerged as the subscale contributing to accurate classifications most notably overall. This study leads infancy research and meta-analytic investigations more broadly in a new direction as a methodological demonstration, and also provides most optimal comparative data for the IBQ-R based on the largest and most representative dataset to date.

Pregnancy and postpartum antidepressant use moderates the effects of sleep on depression.

This study examined the course of antidepressant use, sleep quality, and depression severity from pregnancy through 6-month postpartum in women with and without a depressive disorder during pregnancy. Women (N = 215) were interviewed during pregnancy, 1- and 6-month postpartum. Mixed linear models were used to examine the longitudinal course and inter-relationships for the time-varying variables of antidepressant use, subjective sleep quality, and depression severity. Pregnant women with a depressive disorder who did not use antidepressants had more variable depression severity over time with improvements in depression severity by 6-month postpartum. In contrast, the depression severity of their medicated counterparts remained stable and high throughout. Pregnant women without a depressive disorder had worse sleep quality when using antidepressants compared with when they were not. Antidepressant use significantly strengthened the magnitude of the effect of sleep quality on depression severity in women with a depressive disorder during pregnancy. When prenatally depressed women use antidepressants, their sleep disturbance is more highly linked to depression severity than when they do not. Furthermore, antidepressants are not adequately treating the sleep disturbance of these women or their remitted counterparts, leaving both groups vulnerable to significant negative mental and physical health outcomes.

Assessing the reliability of self-reported weight for the management of heart failure: application of fraud detection methods to a randomised trial of telemonitoring.

BACKGROUND: Since clinical management of heart failure relies on weights that are self-reported by the patient, errors in reporting will negatively impact the ability of health care professionals to offer timely and effective preventive care. Errors might often result from rounding, or more generally from individual preferences for numbers ending in certain digits, such as 0 or 5. We apply fraud detection methods to assess preferences for numbers ending in these digits in order to inform medical decision making. METHODS: The Telemonitoring to Improve Heart Failure Outcomes trial tested an approach to telemonitoring that used existing technology; intervention patients (n = 826) were asked to measure their weight daily using a digital scale and to relay measurements using their telephone keypads. First, we estimated the number of weights subject to end-digit preference by dividing the weights by five and comparing the resultant distribution with the uniform distribution. Then, we assessed the characteristics of patients reporting an excess number of weights ending in 0 or 5, adjusting for chance reporting of these values. RESULTS: Of the 114,867 weight readings reported during the trial, 18.6% were affected by end-digit preference, and the likelihood of these errors occurring increased with the number of days that had elapsed since trial enrolment (odds ratio per day: 1.002, p < 0.001). At least 105 patients demonstrated end-digit preference (14.9% of those who submitted data); although statistical significance was limited, a pattern emerged that, compared with other patients, they tended to be younger, male, high school graduates and on more medications. Patients with end-digit preference reported greater variability in weight, and they generated an average 2.9 alerts to the telemonitoring system over the six-month trial period (95% CI, 2.3 to 3.5), compared with 2.3 for other patients (95% CI, 2.2 to 2.5). CONCLUSIONS: As well as overshadowing clinically meaningful changes in weight, end-digit preference can lead to false alerts to telemonitoring systems, which may be associated with unnecessary treatment and alert fatigue. In this trial, end-digit preference was common and became increasingly so over time. By applying fraud detection methods to electronic medical data, it is possible to produce clinically significant information that can inform the design of initiatives to improve the accuracy of reporting. TRIAL REGISTRATION: ClinicalTrials.gov registration number NCT00303212 March 2006.

Do Non-Clinical Factors Improve Prediction of Readmission Risk?: Results From the Tele-HF Study.

OBJECTIVES: This study sought to determine whether a model that included self-reported socioeconomic, health status, and psychosocial characteristics obtained from patients recently discharged from hospitalizations for heart failure substantially improved 30-day readmission risk prediction compared with a model that incorporated only clinical and demographic factors. BACKGROUND: Existing readmission risk models have poor discrimination and it is unknown whether they would be markedly improved by the inclusion of patient-reported information. METHODS: As part of the Tele-HF (Telemonitoring to Improve Heart Failure Outcomes) trial, we conducted medical record abstraction and telephone interviews in a sample of 1,004 patients recently hospitalized for heart failure to obtain clinical, functional, and psychosocial information within 2 weeks of discharge. Candidate risk factors included 110 variables divided into 2 groups: demographic and clinical variables generally available from the medical record; and socioeconomic, health status, adherence, and psychosocial variables from patient interview. RESULTS: The 30-day readmission rate was 17.1%. Using the 3-level risk score derived from the restricted medical record variables, patients with a score of 0 (no risk factors) had a readmission rate of 10.9% (95% confidence interval [CI]: 8.2% to 14.2%), and patients with a score of 2 (all risk factors) had a readmission rate of 32.1% (95% CI: 22.4% to 43.2%), a C-statistic of 0.62. Using the 5-level risk score derived from all variables, patients with a score of 0 (no risk factors) had a readmission rate of 9.6% (95% CI: 6.1% to 14.2%), and patients with a score of 4 (all risk factors) had a readmission rate of 55.0% (95% CI: 31.5% to 76.9%), a C-statistic of 0.65. CONCLUSIONS: Self-reported socioeconomic, health status, adherence, and psychosocial variables are not dominant factors in predicting readmission risk for patients with heart failure. Patient-reported information improved model discrimination and extended the predicted ranges of readmission rates, but the model performance remained poor. (Telemonitoring to Improve Heart Failure Outcomes [Tele-HF]; NCT00303212).

An administrative claims measure suitable for profiling hospital performance based on 30-day all-cause readmission rates among patients with acute myocardial infarction.

BACKGROUND: National attention has increasingly focused on readmission as a target for quality improvement. We present the development and validation of a model approved by the National Quality Forum and used by the Centers for Medicare & Medicaid Services for hospital-level public reporting of risk-standardized readmission rates for patients discharged from the hospital after an acute myocardial infarction. METHODS AND RESULTS: We developed a hierarchical logistic regression model to calculate hospital risk-standardized 30-day all-cause readmission rates for patients hospitalized with acute myocardial infarction. The model was derived using Medicare claims data for a 2006 cohort and validated using claims and medical record data. The unadjusted readmission rate was 18.9%. The final model included 31 variables and had discrimination ranging from 8% observed 30-day readmission rate in the lowest predictive decile to 32% in the highest decile and a C statistic of 0.63. The 25th and 75th percentiles of the risk-standardized readmission rates across 3890 hospitals were 18.6% and 19.1%, with fifth and 95th percentiles of 18.0% and 19.9%, respectively. The odds of all-cause readmission for a hospital 1 SD above average were 1.35 times that of a hospital 1 SD below average. Hospital-level adjusted readmission rates developed using the claims model were similar to rates produced for the same cohort using a medical record model (correlation, 0.98; median difference, 0.02 percentage points). CONCLUSIONS: This claims-based model of hospital risk-standardized readmission rates for patients with acute myocardial infarction produces estimates that are excellent surrogates for those produced from a medical record model.

Variation in recovery: Role of gender on outcomes of young AMI patients (VIRGO) study design.

BACKGROUND: Among individuals with ischemic heart disease, young women with an acute myocardial infarction (AMI) represent an extreme phenotype associated with an excess mortality risk. Although women younger than 55 years of age account for less than 5% of hospitalized AMI events, almost 16 000 deaths are reported annually in this group, making heart disease a leading killer of young women. Despite a higher risk of mortality compared with similarly aged men, young women have been the subject of few studies. METHODS AND RESULTS: Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients (VIRGO) is a large, observational study of the presentation, treatment, and outcomes of young women and men with AMI. VIRGO will enroll 2000 women, 18 to 55 years of age, with AMI and a comparison cohort of 1000 men with AMI from more than 100 participating hospitals. The aims of the study are to determine sex differences in the distribution and prognostic importance of biological, demographic, clinical, and psychosocial risk factors; to determine whether there are sex differences in the quality of care received by young AMI patients; and to determine how these factors contribute to sex differences in outcomes (including mortality, hospitalization, and health status). Blood serum and DNA for consenting participants will be stored for future studies. CONCLUSIONS: VIRGO will seek to identify novel and prognostic factors that contribute to outcomes in this young AMI population. Results from the study will be used to develop clinically useful risk-stratification models for young AMI patients, explain sex differences in outcomes, and identify targets for intervention.

Telemonitoring in patients with heart failure.

BACKGROUND: Small studies suggest that telemonitoring may improve heart-failure outcomes, but its effect in a large trial has not been established. METHODS: We randomly assigned 1653 patients who had recently been hospitalized for heart failure to undergo either telemonitoring (826 patients) or usual care (827 patients). Telemonitoring was accomplished by means of a telephone-based interactive voice-response system that collected daily information about symptoms and weight that was reviewed by the patients' clinicians. The primary end point was readmission for any reason or death from any cause within 180 days after enrollment. Secondary end points included hospitalization for heart failure, number of days in the hospital, and number of hospitalizations. RESULTS: The median age of the patients was 61 years; 42.0% were female, and 39.0% were black. The telemonitoring group and the usual-care group did not differ significantly with respect to the primary end point, which occurred in 52.3% and 51.5% of patients, respectively (difference, 0.8 percentage points; 95% confidence interval [CI], -4.0 to 5.6; P=0.75 by the chi-square test). Readmission for any reason occurred in 49.3% of patients in the telemonitoring group and 47.4% of patients in the usual-care group (difference, 1.9 percentage points; 95% CI, -3.0 to 6.7; P=0.45 by the chi-square test). Death occurred in 11.1% of the telemonitoring group and 11.4% of the usual care group (difference, -0.2 percentage points; 95% CI, -3.3 to 2.8; P=0.88 by the chi-square test). There were no significant differences between the two groups with respect to the secondary end points or the time to the primary end point or its components. No adverse events were reported. CONCLUSIONS: Among patients recently hospitalized for heart failure, telemonitoring did not improve outcomes. The results indicate the importance of a thorough, independent evaluation of disease-management strategies before their adoption. (Funded by the National Heart, Lung, and Blood Institute; ClinicalTrials.gov number, NCT00303212.).

An administrative claims measure suitable for profiling hospital performance on the basis of 30-day all-cause readmission rates among patients with heart failure.

BACKGROUND: Readmission soon after hospital discharge is an expensive and often preventable event for patients with heart failure. We present a model approved by the National Quality Forum for the purpose of public reporting of hospital-level readmission rates by the Centers for Medicare & Medicaid Services. METHODS AND RESULTS: We developed a hierarchical logistic regression model to calculate hospital risk-standardized 30-day all-cause readmission rates for patients hospitalized with heart failure. The model was derived with the use of Medicare claims data for a 2004 cohort and validated with the use of claims and medical record data. The unadjusted readmission rate was 23.6%. The final model included 37 variables, had discrimination ranging from 15% observed 30-day readmission rate in the lowest predictive decile to 37% in the upper decile, and had a c statistic of 0.60. The 25th and 75th percentiles of the risk-standardized readmission rates across 4669 hospitals were 23.1% and 24.0%, with 5th and 95th percentiles of 22.2% and 25.1%, respectively. The odds of all-cause readmission for a hospital 1 standard deviation above average was 1.30 times that of a hospital 1 standard deviation below average. State-level adjusted readmission rates developed with the use of the claims model are similar to rates produced for the same cohort with the use of a medical record model (correlation, 0.97; median difference, 0.06 percentage points). CONCLUSIONS: This claims-based model of hospital risk-standardized readmission rates for heart failure patients produces estimates that may serve as surrogates for those derived from a medical record model.

Telemonitoring for patients with chronic heart failure: a systematic review.

BACKGROUND: Telemonitoring, the use of communication technology to remotely monitor health status, is an appealing strategy for improving disease management. METHODS AND RESULTS: We searched Medline databases, bibliographies, and spoke with experts to review the evidence on telemonitoring in heart failure patients. Interventions included: telephone-based symptom monitoring (n = 5), automated monitoring of signs and symptoms (n = 1), and automated physiologic monitoring (n = 1). Two studies directly compared effectiveness of 2 or more forms of telemonitoring. Study quality and intervention type varied considerably. Six studies suggested reduction in all-cause and heart failure hospitalizations (14% to 55% and 29% to 43%, respectively) or mortality (40% to 56%) with telemonitoring. Of the 3 negative studies, 2 enrolled low-risk patients and patients with access to high quality care, whereas 1 enrolled a very high-risk Hispanic population. Studies comparing forms of telemonitoring demonstrated similar effectiveness. However, intervention costs were higher with more complex programs (8383 dollars per patient per year) versus less complex programs (1695 dollars per patient per year). CONCLUSION: The evidence base for telemonitoring in heart failure is currently quite limited. Based on the available data, telemonitoring may be an effective strategy for disease management in high-risk heart failure patients.

Strategies for reducing the door-to-balloon time in acute myocardial infarction.

BACKGROUND: Prompt reperfusion treatment is essential for patients who have myocardial infarction with ST-segment elevation. Guidelines recommend that the interval between arrival at the hospital and intracoronary balloon inflation (door-to-balloon time) during primary percutaneous coronary intervention should be 90 minutes or less. However, few hospitals meet this objective. We sought to identify hospital strategies that were significantly associated with a faster door-to-balloon time. METHODS: We surveyed 365 hospitals to determine whether each of 28 specific strategies was in use. We used hierarchical generalized linear models and data on patients from the Centers for Medicare and Medicaid Services to determine the association between hospital strategies and the door-to-balloon time. RESULTS: In multivariate analysis, six strategies were significantly associated with a faster door-to-balloon time. These strategies included having emergency medicine physicians activate the catheterization laboratory (mean reduction in door-to-balloon time, 8.2 minutes), having a single call to a central page operator activate the laboratory (13.8 minutes), having the emergency department activate the catheterization laboratory while the patient is en route to the hospital (15.4 minutes), expecting staff to arrive in the catheterization laboratory within 20 minutes after being paged (vs. >30 minutes) (19.3 minutes), having an attending cardiologist always on site (14.6 minutes), and having staff in the emergency department and the catheterization laboratory use real-time data feedback (8.6 minutes). Despite the effectiveness of these strategies, only a minority of hospitals surveyed were using them. CONCLUSIONS: Several specific hospital strategies are associated with a significant reduction in the door-to-balloon time in the management of myocardial infarction with ST-segment elevation.

Health related quality of life after mitral valve repairs and replacements.

BACKGROUND: The decision to replace or repair mitral valves is often a difficult decision, and outcomes from the patients' perspective should guide decision-making. We investigated whether the change in health related quality of life (HRQOL) after mitral valve surgery is different after valve repairs compared with replacements. METHODS: We prospectively studied 25 patients with mitral valve replacement and 45 patients with valve repairs performed in 1998-99. We measured HRQOL at baseline and at 18 months using the Medical Outcomes Trust Short Form 36-item Health Survey (SF-36) questionnaire. We compared mean HRQOL scores of the groups with age-adjusted U.S. population scores. We used analysis of covariance to determine a change in HRQOL within groups (repair or replacement) and if the change in HRQOL was different between the groups. RESULTS: We found few differences between the groups, with more men and simultaneous coronary artery bypass graft surgery in the valve repair group and more prior operation in the valve replacement group. HRQOL improved after surgery in most domains, and was comparable to age-adjusted U.S. norms in the valve repair group. In the multivariable analysis, mitral valve repair recipients reported higher social functioning compared with patients who received valve replacement (p = 0.04). We did not find other statistically significant differences. However, the adjusted improvements in the component scales of physical functioning (PCS) and mental functioning (MCS) were substantial in the valve repair group (mean changes: PCS = 6.8, p = 0.003; MCS = 8.1, p = 0.014) and less pronounced in the replacement group (mean changes: PCS = 3.6, p = 0.09; MCS = 4.3, fsp = 0.16). CONCLUSIONS: While many considerations influence the decision to repair or replace mitral valves, these findings suggest that repair may be better from the health status perspective. Further studies are necessary to validate this finding.

An administrative claims model suitable for profiling hospital performance based on 30-day mortality rates among patients with heart failure.

BACKGROUND: A model using administrative claims data that is suitable for profiling hospital performance for heart failure would be useful in quality assessment and improvement efforts. METHODS AND RESULTS: We developed a hierarchical regression model using Medicare claims data from 1998 that produces hospital risk-standardized 30-day mortality rates. We validated the model by comparing state-level standardized estimates with state-level standardized estimates calculated from a medical record model. To determine the stability of the model over time, we used annual Medicare cohorts discharged in 1999-2001. The final model included 24 variables and had an area under the receiver operating characteristic curve of 0.70. In the derivation set from 1998, the 25th and 75th percentiles of the risk-standardized mortality rates across hospitals were 11.6% and 12.8%, respectively. The 95th percentile was 14.2%, and the 5th percentile was 10.5%. In the validation samples, the 5th and 95th percentiles of risk-standardized mortality rates across states were 9.9% and 13.9%, respectively. Correlation between risk-standardized state mortality rates from claims data and rates derived from medical record data was 0.95 (SE=0.015). The slope of the weighted regression line from the 2 data sources was 0.76 (SE=0.04) with intercept of 0.03 (SE=0.004). The median difference between the claims-based state risk-standardized estimates and the chart-based rates was <0.001 (25th percentile=-0.003; 75th percentile=0.002). The performance of the model was stable over time. CONCLUSIONS: This administrative claims-based model produces estimates of risk-standardized state mortality that are very good surrogates for estimates derived from a medical record model.

An administrative claims model suitable for profiling hospital performance based on 30-day mortality rates among patients with an acute myocardial infarction.

BACKGROUND: A model using administrative claims data that is suitable for profiling hospital performance for acute myocardial infarction would be useful in quality assessment and improvement efforts. We sought to develop a hierarchical regression model using Medicare claims data that produces hospital risk-standardized 30-day mortality rates and to validate the hospital estimates against those derived from a medical record model. METHODS AND RESULTS: For hospital estimates derived from claims data, we developed a derivation model using 140,120 cases discharged from 4664 hospitals in 1998. For the comparison of models from claims data and medical record data, we used the Cooperative Cardiovascular Project database. To determine the stability of the model over time, we used annual Medicare cohorts discharged in 1995, 1997, and 1999-2001. The final model included 27 variables and had an area under the receiver operating characteristic curve of 0.71. In a comparison of the risk-standardized hospital mortality rates from the claims model with those of the medical record model, the correlation coefficient was 0.90 (SE=0.003). The slope of the weighted regression line was 0.95 (SE=0.007), and the intercept was 0.008 (SE=0.001), both indicating strong agreement of the hospital estimates between the 2 data sources. The median difference between the claims-based hospital risk-standardized mortality rates and the chart-based rates was <0.001 (25th and 75th percentiles, -0.003 and 0.003). The performance of the model was stable over time. CONCLUSIONS: This administrative claims-based model for profiling hospitals performs consistently over several years and produces estimates of risk-standardized mortality that are good surrogates for estimates from a medical record model.

Achieving rapid door-to-balloon times: how top hospitals improve complex clinical systems.

BACKGROUND: Fewer than half of patients with ST-elevation acute myocardial infarction (STEMI) are treated within guideline-recommended door-to-balloon times; however, little information is available about the approaches used by hospitals that have been successful in improving door-to-balloon times to meet guidelines. We sought to characterize experiences of hospitals with outstanding improvement in door-to-balloon time during 1999-2002. METHODS AND RESULTS: We performed a qualitative study using in-depth interviews (n=122) with clinical and administrative staff at 11 hospitals that were participating with the National Registry of Myocardial Infarction and had median door-to-balloon times of < or =90 minutes during 2001-2002, representing substantial improvement since 1999. Data were organized with the use of NUD-IST 4 (Sage Publications Software) and were analyzed by the constant comparative method of qualitative data analysis. Eight themes characterized hospitals' experiences: commitment to an explicit goal to improve door-to-balloon time motivated by internal and external pressures; senior management support; innovative protocols; flexibility in refining standardized protocols; uncompromising individual clinical leaders; collaborative teams; data feedback to monitor progress and identify problems and successes; and an organizational culture that fostered resilience to challenges or setbacks in improvement efforts. CONCLUSIONS: Several themes characterized the experiences of hospitals that had achieved notable improvements in their door-to-balloon times. By distilling the complex and diverse experiences of organizational change into its essential components, this study provides a foundation for future efforts to elevate clinical performance in the hospital setting.

A randomized outpatient trial of a decision-support information technology tool.

BACKGROUND: Decision-support information technology is often adopted to improve clinical decision making, but it is rarely rigorously evaluated. Congress mandated the evaluation of Problem-Knowledge Couplers (PKC Corp, Burlington, Vt), a decision-support tool proposed for the Department of Defense's new health information network. METHODS: This was a patient-level randomized trial conducted at 2 military practices. A total of 936 patients were allocated to the intervention group and 966 to usual care. Couplers were applied before routine ambulatory clinic visits. The primary outcome was quality of care, which was assessed based on the total percentage of any of 24 health care quality process measures (opportunities to provide evidence-based care) that were fulfilled. Secondary outcomes included medical resources consumed within 60 days of enrollment and patient and provider satisfaction. RESULTS: There were 4639 health care opportunities (2374 in the Coupler group and 2265 in the usual-care group), with no difference in the proportion of opportunities fulfilled (33.9% vs 30.7%; P = .12). Although there was a modest improvement in performance on screening/preventive measures, it was offset by poorer performance on some measures of acute care. Coupler patients used more laboratory and pharmacy resources than usual-care patients (logarithmic mean difference, 71 dollars). No difference in patient satisfaction was observed between groups, and provider satisfaction was mixed. CONCLUSION: This study provides no strong evidence to support the utility of this decision-support tool, but it demonstrates the value of rigorous evaluation of decision-support information technology.

Achieving door-to-balloon times that meet quality guidelines: how do successful hospitals do it?

OBJECTIVES: We sought to recommend an approach for minimizing preventable delays in door-to-balloon time on the basis of experiences in top-performing hospitals nationally. BACKGROUND: Prompt percutaneous coronary intervention (PCI) for patients with ST-segment elevation myocardial infarction (STEMI) significantly reduces mortality and morbidity; however, door-to-balloon times often exceed the 90-min guideline set forth by the American College of Cardiology (ACC) and the American Heart Association (AHA). METHODS: We conducted a qualitative study using in-depth interviews (n = 122) of hospital staff at hospitals (n = 11) selected as top performers based on data from the National Registry of Myocardial Infarction from January 2001 to December 2002. We used the constant comparative method of qualitative data analysis to synthesize best practices across the hospitals. RESULTS: Top performers were those with median door-to-balloon times of < or =90 min for their most recent 50 PCI cases through December 2002 and the greatest improvement in median door-to-balloon times during the preceding four-year period 1999 to 2002. Several critical innovations are described, including use of pre-hospital electrocardiograms (ECGs) to activate the catheterization laboratory, allowing emergency physicians to activate the catheterization laboratory, and substantial interdisciplinary collaboration throughout the process. In the ideal approach, door-to-balloon time is 60 min for patients transported by paramedics with a pre-hospital ECG and 80 min for patients who arrive without paramedic transport and a pre-hospital ECG. CONCLUSIONS: Hospitals can achieve the recommended ACC/AHA guidelines for door-to-balloon time with specific process design efforts. However, the recommended best practices involve extensive interdisciplinary collaboration and will likely require explicit strategies for overcoming barriers to organizational change.