The Multi-Morbidity Index: A Tool for Assessing the Prognosis of Patients from
            History of Illness

Alemi, Farrokh; Levy, Cari; Kheirbek, Raya

doi:10.13063/2327-9214.1235

Cited by 16 publications

(15 citation statements)

References 46 publications

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“…Naïve Bayes is similar to linear logistic regression, 20 as it assumes independence and allows no interaction among diagnostic codes. Despite this false assumption of independence, in large sparse data, such as the data in this study, naïve Bayes has been relatively accurate in predicting patient outcomes 21‐23 …”

Section: Methodsmentioning

confidence: 89%

Relative accuracy of social and medical determinants of suicide in electronic health records

Alemi

Avramovic

Renshaw

et al. 2020

Health Services Research

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Objective: This paper compares the accuracy of predicting suicide from Social Determinants of Health (SDoH) or history of illness. Population Studied: 5 313 965 Veterans who at least had two primary care visits between 2008 and 2016. Study Design: The dependent variable was suicide or intentional self-injury. The independent variables were 10 495 International Classification of Disease (ICD) Version 9 codes, age, and gender. The ICD codes included 40 V-codes used for measuring SDoH, such as family disruption, family history of substance abuse, lack of education, legal impediments, social isolation, unemployment, and homelessness. The sample was randomly divided into training (90 percent) and validation (10 percent) sets. Area under the receiver operating characteristic (AROC) was used to measure accuracy of predictions in the validation set. Principal Findings: Separate analyses were done for inpatient and outpatient codes; the results were similar. In the hospitalized group, the mean age was 67.2 years, and 92.1 percent were male. The mean number of medical diagnostic codes during the study period was 37; and 12.9 percent had at least one SDoH V-code. At least one episode of suicide or intentional self-injury occurred in 1.89 percent of cases. SDoH V-codes, on average, elevated the risk of suicide or intentional self-injury by 24-fold (ranging from 4to 86-fold). An index of 40 SDoH codes predicted suicide or intentional self-injury with an AROC of 0.64. An index of 10 445 medical diagnoses, without SDoH V-codes, had AROC of 0.77. The combined SDoH and medical diagnoses codes also had AROC of 0.77. Conclusion: In predicting suicide or intentional self-harm, SDoH V-codes add negligible information beyond what is already available in medical diagnosis codes. Implications for Practice: Policies that affect SDoH (eg, housing policies, resilience training) may not have an impact on suicide rates, if they do not change the underlying medical causes of SDoH. K E Y W O R D S high dimensional data, hierarchical modeling, mental health, naive Bayes, observational data/ quasi-experiments, self-harm, social determinants of health, stressful life events, suicide, VA health care system This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Methodsmentioning

confidence: 89%

Relative accuracy of social and medical determinants of suicide in electronic health records

Alemi

Avramovic

Renshaw

et al. 2020

Health Services Research

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“…Palliative care is a multidisciplinary intervention that focuses on optimizing quality of life for patients and families affected by serious illness, independent of prognosis. 30,31 It is related to but distinct from hospice care, which in the United States is restricted to patients with a maximum expected prognosis of 6 months. However, when asked to describe eligibility and appropriateness criteria for palliative care, cardiology, and hospitalist, providers used the terms “hospice” and “palliative care” interchangeably unless prompted for clarification.…”

Section: Discussionmentioning

confidence: 99%

Impact of Hospice and Palliative Care Service Utilization on All-Cause 30-Day Readmission Rate for Older Adults Hospitalized with Heart Failure

Kheirbek

Alemi

Wojtusiak

et al. 2019

Am J Hosp Palliat Care

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Background: Acute decompensated heart failure (HF) is the leading cause for hospital readmission. Large-scale sustainable interventions to reduce readmission rate have not been fully explored or proven effective. Objective: We studied the impact of hospice and palliative care service utilization on 30-day all-cause hospital readmissions for patients with HF. Methods and Results: Data were retrieved from the Department of Veterans Affairs Corporate Data Warehouse. The study included 238 116 HF admissions with primary diagnosis of HF belonging to 130 812 patients. Among these patients, 2592 had hospice and palliative care utilizations and 68 245 patients did not. Rehospitalization was calculated within 30 days of index hospitalization. Propensity scores were used to match hospice and nonhospice patients on demographics, Charlson comorbidity categories, and 30-day survival. In the matched group, logistic regression was used to estimate effects of hospice on readmission, controlling for any covariates that had failed to balance. The average age of the matched patients was 74 years old, 14% were African American, 75% Caucasian, 2% Asian, and 17% female. After propensity matching, the odds ratio for readmission was 1.29. The 95% confidence interval for the odds was 1.13 to 1.48, suggesting that veterans receiving services have a higher chance of readmission. Conclusion: In a large cohort study of older US Veterans, utilization of hospice and palliative care services was associated with a higher 30-day all-cause readmission rate among hospitalized patients with HF. Further prospective studies should be conducted to confirm results and test generalizability outside the Veterans Affairs system of care.

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“…Future work will include calculation of a multimorbidity index to measure the impact of medical history on emergence of diabetes. 37 …”

Section: Cohort Descriptionmentioning

confidence: 99%

US veterans administration diabetes risk (VADR) national cohort: cohort profile

et al. 2020

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PurposeThe veterans administration diabetes risk (VADR) cohort facilitates studies on temporal and geographic patterns of pre-diabetes and diabetes, as well as targeted studies of their predictors. The cohort provides an infrastructure for examination of novel individual and community-level risk factors for diabetes and their consequences among veterans. This cohort also establishes a baseline against which to assess the impact of national or regional strategies to prevent diabetes in veterans.ParticipantsThe VADR cohort includes all 6 082 018 veterans in the USA enrolled in the veteran administration (VA) for primary care who were diabetes-free as of 1 January 2008 and who had at least two diabetes-free visits to a VA primary care service at least 30 days apart within any 5-year period since 1 January 2003, or veterans subsequently enrolled and were diabetes-free at cohort entry through 31 December 2016. Cohort subjects were followed from the date of cohort entry until censure defined as date of incident diabetes, loss to follow-up of 2 years, death or until 31 December 2018.Findings to dateThe incidence rate of type 2 diabetes in this cohort of over 6 million veterans followed for a median of 5.5 years (over 35 million person-years (PY)) was 26 per 1000 PY. During the study period, 8.5% of the cohort were lost to follow-up and 17.7% died. Many demographic, comorbidity and other clinical variables were more prevalent among patients with incident diabetes.Future plansThis cohort will be used to study community-level risk factors for diabetes, such as attributes of the food environment and neighbourhood socioeconomic status via geospatial linkage to residence address information.

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The Multi-Morbidity Index: A Tool for Assessing the Prognosis of Patients from History of Illness

Cited by 16 publications

References 46 publications

Relative accuracy of social and medical determinants of suicide in electronic health records

Relative accuracy of social and medical determinants of suicide in electronic health records

Impact of Hospice and Palliative Care Service Utilization on All-Cause 30-Day Readmission Rate for Older Adults Hospitalized with Heart Failure

US veterans administration diabetes risk (VADR) national cohort: cohort profile

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