Dee W. Ford

Frequency, cost, and risk factors of readmissions among severe sepsis survivors.

Objective:To determine the frequency, mortality, cost, and risk factors associated with readmission after index hospitalization with severe sepsis. Design:Observational cohort study of Healthcare Cost and Utilization Project data. Setting:All nonfederal hospitals in three U.S. states. Patients:Severe sepsis survivors (n = 43,452) in the first two quarters of 2011. InterventionsNone. Measurements and Main Results:We measured readmission rates and the associated cost and mortality of readmissions in severe sepsis survivors. We used multivariable logistic regression to identify patient and hospitalization characteristics associated with readmission. Of 43,452 sepsis survivors, 26% required readmission within 30 days and 48% within 180 days. The cumulative mortality rate of sepsis survivors attributed to readmissions was 8%, and the estimated cost was over

FACTORS ASSOCIATED WITH ILLNESS PERCEPTION AMONG CRITICALLY ILL PATIENTS AND SURROGATES

1.1 billion. Among survivors, 25% required multiple readmissions within 180 days and accounted for 77% of all readmissions. Age younger than 80 years (odds ratio, 1.14; 95% CI, 1.08–1.21), black race (odds ratio, 1.18; 95% CI, 1.10–1.26), and Medicare or Medicaid payor status (odds ratio, 1.21; 95% CI, 1.13–1.30; odds ratio, 1.34; 95% CI, 1.23–1.46, respectively) were associated with greater odds of 30-day readmission while female gender was associated with reduced odds (odds ratio, 0.92; 95% CI, 0.87–0.96). Comorbidities including malignancy (odds ratio, 1.34; 95% CI, 1.24–1.45), collagen vascular disease (odds ratio, 1.30; 95% CI, 1.15–1.46), chronic kidney disease (odds ratio, 1.24; 95% CI, 1.18–1.31), liver disease (odds ratio, 1.22; 95% CI, 1.11–1.34), congestive heart failure (odds ratio, 1.14; 95% CI, 1.08–1.19), lung disease (odds ratio, 1.12; 95% CI, 1.06–1.18), and diabetes (odds ratio, 1.12; 95% CI, 1.07–1.17) were associated with greater odds of 30-day readmission. Index hospitalization characteristics including longer length of stay, discharge to a care facility, higher hospital annual severe sepsis case volume, and higher hospital sepsis mortality rate were also positively associated with readmission rates. Conclusion:The 30-day and 180-day readmissions are common in sepsis survivors with significant resultant cost and mortality. Patient sociodemographics and comorbidities as well as index hospitalization characteristics are associated with 30-day readmission rates.

Population-based study of the risk of in-hospital death after traumatic brain injury: the role of sepsis.

BACKGROUND We investigated illness perceptions among critically ill patients or their surrogates in a university medical ICU using a prospective survey. We hypothesized that these would vary by demographic, personal, and clinical measures. METHODS Patients (n = 23) or their surrogates (n = 77) were recruited. The Illness Perception Questionnaire-Revised (IPQ-R) measured six domains of illness perception: timeline-acute/chronic, consequences, emotional impact, personal control, treatment efficacy, and illness comprehension. Multiple variable linear regression models were developed with IPQ-R scores as the outcomes. RESULTS African Americans tended to perceive the illness as less enduring and reported more confidence in treatment efficacy (P < .01 for each). They also tended to report the illness as less serious, having less emotional impact, and having greater personal control (P = .0002 for each). Conversely, African Americans reported lower illness comprehension (P = .002). Faith/religion was associated with positive illness perceptions, including less concern regarding consequences (P = .02), less emotional impact (P = .03), and more confidence in treatment efficacy (P < .01). Lower patient quality of life (QOL) precritical illness was associated with negative perceptions, including greater concern about illness duration and consequences as well as perception of less personal control and less confidence in treatment efficacy (P < .01 for each). These variables were independently associated with illness perceptions after controlling for race, faith/religion, and survival to hospital discharge, whereas clinical measures were not. CONCLUSIONS Illness perceptions among critically ill patients and surrogates are influenced by patient/surrogate factors, including race, faith, and precritical illness QOL, rather than clinical measures. Clinicians should recognize the variability in illness perceptions and the possible implications for patient/surrogate communication.

A Severe Sepsis Mortality Prediction Model and Score for Use With Administrative Data.

BACKGROUND Traumatic brain injury (TBI) accounts for the largest proportion of injury-related deaths and disability in the United States. The proportion of TBI-related deaths that occur after admission in a hospital remains high despite improvement in medical technology. We provide findings on the risk factors of in-hospital death and demonstrate the risk associated with sepsis occurring in the hospital environment. METHODS Population-based retrospective cohort study of 41,395 patients with TBI from all nonfederal hospitals in South Carolina, 1998 to 2009. TBI was ascertained by International Classification of Diseases-9th Rev.-Clinical Modification codes of 800 to 801, 803 to 804, 850 to 854, and 959.01. Observation was censored at the 120th day. Days elapsing from the date of injury to date of death established the survival time (T). Cox regression was used to examine the risk of death, whereas Kaplan-Meier survival curves compared survival probabilities across time. RESULTS Sepsis was independently associated with risk of in-hospital death with hazard ratio of 1.34 (p < 0.001). Severity of TBI was the strongest risk factor with hazard ratio of 4.97 (p < 0.001). Nearly 90% of patients with sepsis were identified with one of the nosocomial etiologies included in the analyses compared with 7% of patients without sepsis (p < 0.001). The survival probabilities were significantly lower for persons with sepsis compared with those without (log-rank test p < 0.001). CONCLUSION Sepsis occurring in the hospital environment and associated with nosocomial etiologies is a strong risk factor for in-hospital death after TBI. Reducing the risk of infections and subsequent sepsis through adherence with infection control measures is a critical step to reduce in-hospital deaths among patients with TBI.

Therapeutic Alliance between the Caregivers of Critical Illness Survivors and Intensive Care Unit Clinicians.

Objective:Administrative data are used for research, quality improvement, and health policy in severe sepsis. However, there is not a sepsis-specific tool applicable to administrative data with which to adjust for illness severity. Our objective was to develop, internally validate, and externally validate a severe sepsis mortality prediction model and associated mortality prediction score. Design:Retrospective cohort study using 2012 administrative data from five U.S. states. Three cohorts of patients with severe sepsis were created: 1) International Classification of Diseases, 9th Revision, Clinical Modification codes for severe sepsis/septic shock, 2) Martin approach, and 3) Angus approach. The model was developed and internally validated in International Classification of Diseases, 9th Revision, Clinical Modification, cohort and externally validated in other cohorts. Integer point values for each predictor variable were generated to create a sepsis severity score. Setting:Acute care, nonfederal hospitals in New York, Maryland, Florida, Michigan, and Washington. Subjects:Patients in one of three severe sepsis cohorts: 1) explicitly coded (n = 108,448), 2) Martin cohort (n = 139,094), and 3) Angus cohort (n = 523,637) Interventions:None. Measurements and Main Results:Maximum likelihood estimation logistic regression to develop a predictive model for in-hospital mortality. Model calibration and discrimination assessed via Hosmer-Lemeshow goodness-of-fit and C-statistics, respectively. Primary cohort subset into risk deciles and observed versus predicted mortality plotted. Goodness-of-fit demonstrated p value of more than 0.05 for each cohort demonstrating sound calibration. C-statistic ranged from low of 0.709 (sepsis severity score) to high of 0.838 (Angus cohort), suggesting good to excellent model discrimination. Comparison of observed versus expected mortality was robust although accuracy decreased in highest risk decile. Conclusions:Our sepsis severity model and score is a tool that provides reliable risk adjustment for administrative data.

A mixed methods descriptive investigation of readiness to change in rural hospitals participating in a tele-critical care intervention

RATIONALE Therapeutic alliance is a novel measure of the multifaceted caregiver-clinician relationship and a promising intervention target for improving patient-centered outcomes. However, therapeutic alliance has not been studied in an intensive care unit (ICU) setting. OBJECTIVES To explore the relationships among caregiver-reported therapeutic alliance and psychological distress as well as patient, caregiver, and ICU clinician factors. METHODS In this cross-sectional study, we enrolled consecutive patient caregivers of mechanically ventilated patients discharged from all ICUs at Duke University and the Medical University of South Carolina Hospitals between December 2013 and August 2014. MEASUREMENTS AND MAIN RESULTS Caregivers completed an in-person, hospital-based interview that included measures of therapeutic alliance with the ICU physicians (Human Connection Scale) as well as patient centeredness of care; symptoms of depression, anxiety, and post-traumatic stress; decisional conflict; and quality of communication. We performed a multivariate regression to characterize associations between Human Connection Scale scores and key variables. A total of 56 caregivers were included in these exploratory analyses. Patients were largely disabled (47%) and Medicare insured (53%). Caregivers were highly educated and generally had high therapeutic alliance (median, 55; interquartile range, 48-58) with the ICU clinicians. Therapeutic alliance was strongly correlated with patient centeredness (r = 0.78) and poorly correlated with psychological distress (r < 0.2). Stepwise multivariate modeling revealed that higher therapeutic alliance was associated with fewer baseline patient comorbidities as well as caregiver report of greater trust in the ICU team, better quality of communication, and less decisional conflict (all P < 0.012). CONCLUSIONS Therapeutic alliance encompasses measures of trust, communication, and cooperation, which are intuitive to forming a good working relationship. Therapeutic alliance among ICU caregivers is strongly associated with both modifiable and nonmodifiable factors. Our exploratory study highlights new intervention targets that may inform strategies for improving the quality of the caregiver-clinician interaction.

Multiple in-hospital resuscitation efforts in the elderly.

BackgroundTelemedicine technology can improve care to patients in rural and medically underserved communities yet adoption has been slow. The objective of this study was to study organizational readiness to participate in an academic-community hospital partnership including clinician education and telemedicine outreach focused on sepsis and trauma care in underserved, rural hospitals.MethodsThis is a multi-method, observational case study. Participants included staff from 4 participating rural South Carolina hospitals. Using a readiness-for-change model, we evaluated 5 general domains and the related factors or topics of organizational context via key informant interviews (n=23) with hospital leadership and staff, compared these to data from hospital staff surveys (n=86) and triangulated data with investigators’ observational reports. Survey items were grouped into 4 categories (based on content and fit with conceptual model) and scored, allowing regression analyses for inferential comparisons to assess factors related to receptivity toward the telemedicine innovation.ResultsGeneral agreement existed on the need for the intervention and feasibility of implementation. Previous experience with a telemedicine program appeared pivotal to enthusiasm. Perception of need, task demands and resource need explained nearly 50% of variation in receptivity. Little correlation emerged with hospital or ED leadership culture and support. However qualitative data and investigator observations about communication and differing support among disciplines and between staff and leadership could be important to actual implementation.ConclusionsA mixed methods approach proved useful in assessing organizational readiness for change in small organizations. Further research on variable operational definitions, potential influential factors, appropriate and feasible methods and valid instruments for such research are needed.

Prospective Impact of Illness Uncertainty on Outcomes in Chronic Lung Disease

Objectives:The objective of this study was to determine the characteristics and survival rates of patients receiving cardiopulmonary resuscitation more than once during a single hospitalization. Design:We analyzed inpatient Medicare data from 1992 to 2005 identifying beneficiaries 65 years old and older who underwent cardiopulmonary resuscitation more than once during the same hospitalization. Measurements:We examined patient and hospital characteristics, survival to hospital discharge, factors associated with survival to discharge, median survival, and discharge disposition. Results:We analyzed data from 421,394 patients who underwent cardiopulmonary resuscitation during the study period. Four lakh thirteen thousand four hundred three patients received cardiopulmonary resuscitation once during a hospitalization and survival was 17.7% with median survival after discharge being 20.6 months. There were 7,991 patients who received cardiopulmonary resuscitation more than once during the same hospitalization; 8.8% survived the efforts, and median survival after leaving the hospital was 10.5 months. Patients who received more than one episode of cardiopulmonary resuscitation during a hospitalization were significantly less likely to go home after discharge. Greater age, black race, higher burden of chronic illness, and receiving cardiopulmonary resuscitation in a larger or metropolitan hospital were associated with lower survival among patients receiving cardiopulmonary resuscitation more than once. Conclusions:Undergoing multiple cardiopulmonary resuscitation events during a hospitalization is associated with substantially reduced short- and long-term survival compared with patients who undergo cardiopulmonary resuscitation once. This information may be useful to clinicians when discussing end-of-life care with patients and families of patients who have experienced return of spontaneous circulation following in-hospital cardiopulmonary resuscitation but remain at risk for recurrent cardiac arrest.

Coping as a Multifaceted Construct: Associations With Psychological Outcomes Among Family Members of Mechanical Ventilation Survivors.

OBJECTIVE To determine which aspect of illness uncertainty (i.e., ambiguity or complexity) has a stronger association with psychological and clinical outcomes over a 2-year period among individuals with a genetic subtype of chronic obstructive pulmonary disease (COPD). Ambiguity reflects uncertainty about physical cues and symptoms, and complexity reflects uncertainty about treatment and the medical system. METHOD Four-hundred and 7 individuals with alpha-1 antitrypsin deficiency-associated COPD completed questionnaires at baseline, 1- and 2-year follow-up. Uncertainty was measured using the Mishel Uncertainty in Illness Scale. Outcomes were measured using the Hospital Anxiety and Depression Scale, St. Georges Respiratory Questionnaire, and MMRC Dyspnea Scale. Ambiguity and complexity were examined as predictors of depressive symptoms, anxiety, quality of life, and breathlessness using linear mixed models adjusting for demographic and health characteristics. RESULTS Ambiguity was associated with more depressive symptoms (b = 0.09, SE = 0.02, p < .001) and anxiety (b = 0.13, SE = 0.02, p < .001), worse quality of life (b = 0.57, SE = 0.10, p < .001), and more breathlessness (b = 0.02, SE = 0.006, p < .001). Complexity did not have an independent effect on any outcome. Interactions between ambiguity and time since diagnosis were not statistically significant. CONCLUSIONS Ambiguity was prospectively associated with worse mood, quality of life, and breathlessness. Thus, ambiguity should be targeted in psychosocial interventions. Time since diagnosis did not affect the association between ambiguity and outcomes, suggesting that the impact of ambiguity is equally strong throughout the course of COPD.

The Social Environment and Illness Uncertainty in Chronic Obstructive Pulmonary Disease

Objectives: To develop and evaluate a preliminary multifaceted model for coping among family members of patients who survive mechanical ventilation. Design and Setting: In this multicenter cross-sectional survey, we interviewed family members of mechanically ventilated patients at the time of transfer from the ICU to the hospital ward. We constructed a theoretic model of coping that included characteristics attributable to family members, family-clinician rapport, and patients. We then explored relationships between coping factors and symptoms of psychological distress (anxiety, depression, and posttraumatic stress). Subjects: Fifty-six family members of survivors of mechanical ventilation. Measurements and Main Results: Psychological distress measured by the Hospital Anxiety and Depression Scale and Posttraumatic Stress Scale. Optimism measured using the Life Orientation Test scale, resiliency by Conner-Davidson Resilience Scale, and social support using the Patient Reported Outcomes Measurement Information System inventory. Family members had moderate levels of psychological distress with median total Hospital Anxiety and Depression Scale equal to 14 (interquartile range, 5–20) and Posttraumatic Stress Scale equal to 22 (interquartile range, 15–31). Among family member characteristics, greater optimism (p = 0.001, Hospital Anxiety and Depression Scale; p = 0.010, Posttraumatic Stress Scale), resilience (p = 0.012, Hospital Anxiety and Depression Scale), and social support (p = 0.013, Hospital Anxiety and Depression Scale) were protective against psychological distress. On the contrary, characteristics of family-clinician rapport such as communication quality and presence of conflict did not have any associations with psychological distress. Conclusion: To our knowledge, this is the first study to explore coping as a multifaceted construct and its relationship with family psychological outcomes among survivors of mechanical ventilation. We found certain family characteristics of coping such as optimism, resilience, and social support to be associated with less psychological distress. Further research is warranted to identify potentially modifiable aspects of coping that might guide future interventions.