2 results
5 Hospitalization Outcomes Following Neuropsychological Evaluation in a Traumatic Brain Injury Sample
- Charlotte A Payne, Timothy Chrusciel, David A. S. Kaufman
-
- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 117-118
-
- Article
-
- You have access Access
- Export citation
-
Objective:
Previous research has shown that positive outcomes are associated with receiving a neuropsychological evaluation (NPE). The current project examined hospitalization outcomes following an NPE in a sample of patients who had sustained a traumatic brain injury (TBI). Hospitalization rates were compared between the two years pre- and two years post-evaluation. The role that insurance status plays on these health outcomes was also examined. This project is part of a growing effort to evaluate outcomes of clinical neuropsychological services in order to better characterize the broad health impacts of NPEs.
Participants and Methods:Participants for the current study come from the Optum® de-identified Electronic Health Record dataset. The final sample included 245 patients who completed at least one NPE and were diagnosed with a TBI, according to ICD codes associated with their healthcare records. Patients were aged 21-87 (M = 51.55, SD = 16.74) with an average Charleston Comorbidity Index of 1.77 (SD = 2.41). The sample consisted of 124 females (50.6%), 121 males (49.4%). The majority of the sample identified as non-Hispanic white (N = 213; 86.9%), while 8.6% identified as another race or ethnicity. Regarding insurance, the most common insurance type was commercial (61.6%), followed by Medicare (13.5%), Medicaid (9.4%), and uninsured (6.5%). Those with unknown insurance status, race, or ethnicity were excluded from analyses of those variables.
Results:Hospitalization incidence for the sample was significantly lower in the two years following a NPE, X2(1, N = 245) = 26.98, p < .001, compared to the two years prior. The mean number of hospitalizations were also lower following a NPE (t(244) = 4.83, p < .001). Insurance status did not show a significant main effect or interaction on mean number of hospitalizations over time. Regarding demographic variables, there was no significant main effects of race/ethnicity group or interaction between race/ethnicity and hospitalization rate change over time. However, there was a significant interaction between hospitalization rate change over time and gender (F(242) = 4.74, p = 0.030). A significant decrease in hospitalizations over time was seen for males (p < .001), while females showed a trend-level decrease that approached significance (p = .06).
Conclusions:Consistent with previous research, significant reductions in hospitalization incidence and mean number of hospitalizations were seen following a NPE. This finding did not vary based on insurance status. However, hospitalization outcomes varied as a function of gender. These findings suggest that completing a NPE following a traumatic brain injury may contribute to improved hospitalization outcomes, but it does not appear that this benefit is seen equally for all patients. Insurance status may play a role in accessibility to care and hospitalization outcomes in this population, but that relationship is likely influenced by other factors, including racial identity, gender, and income. Future research is needed to investigate the extent that NPEs impact hospitalization rates in the broader context of insurance, demographic factors, and socioeconomic status.
Treatment-resistant and insufficiently treated depression and all-cause mortality following myocardial infarction
- Jeffrey F. Scherrer, Timothy Chrusciel, Lauren D. Garfield, Kenneth E. Freedland, Robert M. Carney, Paul J. Hauptman, Kathleen K. Bucholz, Richard Owen, Patrick J. Lustman
-
- Journal:
- The British Journal of Psychiatry / Volume 200 / Issue 2 / February 2012
- Published online by Cambridge University Press:
- 02 January 2018, pp. 137-142
- Print publication:
- February 2012
-
- Article
-
- You have access Access
- HTML
- Export citation
-
Background
Depression is a known risk factor for mortality after an acute myocardial infarction. Patients with treatment-responsive depression may have a better prognosis than those with treatment-resistant depression.
AimsWe sought to determine whether mortality following acute myocardial infarction was associated with treatment-resistant depression.
MethodFollow-up began after myocardial infarction and continued until death or censorship. Depression was counted as present if diagnosed any time during the study period. Treatment for depression was defined as receipt of 12 or more weeks of continuous antidepressant therapy at a therapeutic dose during follow-up. Treatment-resistant depression was defined as use of two or more antidepressants plus augmentation therapy, receipt of electroconvulsive therapy or use of monoamine oxidase inhibitors. Mean duration of follow-up was 39 months.
ResultsDuring follow-up of 4037 patients with major depressive disorder who had had a myocardial infarction, 6.9% of those with insufficiently treated depression, 2.4% of those with treated depression and 5.0% of those with treatment-resistant depression died. A multivariable survival model that adjusted for sociodemographics, anxiety disorders, beta-blocker use, mortality risk factors and health service utilisation indicated that compared with treated patients, insufficiently treated patients were 3.04 (95% CI 2.12–4.35) times more likely and patients with treatment-resistant depression were 1.71 (95% CI 1.05–2.79) times more likely to die.
ConclusionsAll-cause mortality following an acute myocardial infarction is greatest in patients with depression who are insufficiently treated and is a risk in patients with treatment-resistant depression. However, the risk of mortality associated with treatment-resistant depression is partly explained by comorbid disorders. Further studies are warranted to determine whether changes in depression independently predict all-cause mortality.