Methods

The National Heart, Lung, and Blood Institute-sponsored Family Cardiac Caregiver Investigation To Evaluate Outcomes (FIT-O) study was a prospective study designed to evaluate the patterns of caregiving among cardiac patients and its association with the clinical outcomes of patients hospitalized with CVD. Consecutive patients admitted to the CVD service line at Columbia University Medical Center/New York Presbyterian Hospital (CUMC/NYPH) from November 2009 to June 2010 were asked to complete a standardized questionnaire regarding caregiving (93% enrollment rate). Medical cardiovascular service patients (n = 3,188) who had 1-year follow-up data by June 2011 were included in the primary analysis. The baseline characteristics and patterns of caregiving in this population have been previously published. In brief, the hospital admission logs were reviewed daily to identify patients admitted to the CVD service, and trained bilingual research staff systematically distributed surveys in English and Spanish to potential participants to assess whether they had had a caregiver within the past year and had plans for a caregiver after discharge. The patients were excluded from survey administration if they were unable to read or understand English or Spanish, lived in a full-time nursing facility, had a mental status that precluded participation, or refused participation. The hospital logs were checked weekly to detect any uncollected surveys. If uncollected surveys were detected, the research staff attempted to contact the patient before discharge, or, in the event this was not feasible, the survey was mailed with a prestamped return envelope for the patient to complete and return. The institutional review board of CUMC approved the study.

The definition of caregiving was adapted from the report of the National Alliance of Caregiving and American Association of Retired People (AARP). The methods for standardized assessment of caregiving were described in our previous work. A caregiver was defined as a paid professional (e.g., nurse/home aide) or an informal (nonpaid) person who assists the patient with medical and/or preventive care. Data on having a caregiver in the previous year and plans for having a caregiver after discharge were evaluated and found to be similar; therefore, the former was used. Patients who reported having both paid and informal caregivers (n = 120) were categorized as having a paid caregiver.

The extent of caregiving provided to each participant who reported having a caregiver was systematically assessed according to the specific tasks the caregiver performed. The tasks were defined using the basic activities of daily living (e.g., assistance with dressing, bathing) and instrumental activities of daily living (e.g., assistance with meal preparation, transportation). The extent of caregiving provided was categorized as extensive (i.e., patient had a paid caregiver or an informal caregiver who provided assistance with the basic activities of daily living only or the basic activities of daily living plus instrumental activities of daily living) or nonextensive (informal caregiver provided assistance with instrumental activities of daily living or less, or the patient had no caregiver).

The baseline characteristics, medical history, admission diagnoses, and prescription medications were documented by standardized electronic chart review. The patient medical records were accessed using a secure and comprehensive electronic clinical information system at CUMC/NYPH. The admission diagnosis (CVD vs non-CVD) was determined from the International Classification of Disease, 9th Revision (ICD-9), billing code for admission or primary diagnosis and were validated in a substudy by an independent physician reviewer unaware of the ICD-9 billing code and caregiver status (n = 50; κ = 0.99). All research staff members were Health Insurance Portability and Accountability Act trained and certified in the use of this clinical information system. Current and previous medical conditions, including diabetes mellitus, renal disease, myocardial infarction, peripheral vascular disease, heart failure, and chronic obstructive pulmonary disease, were determined using the ICD-9 billing codes and physician or nurse practitioner notes. The medical history information was collected by a trained nurse research assistant and was available for 99% of this population. The number of different prescribed medications and names and/or types of medications were obtained from the discharge summary notes and supplemented by the ambulatory electronic records, if needed.

The primary outcome was all-cause rehospitalization or death within 1 year, and the secondary outcomes were CVD rehospitalization and all-cause mortality, assessed individually. The methods used to collect the outcomes data were similar to those previously tested in other studies of hospitalized patients with CVD. Rehospitalization was systematically obtained from the CUMC/NYPH electronic clinical information system, which is updated daily. The patients’ admitting date, admitting diagnosis, and primary diagnoses for each hospitalization and rehospitalization were recorded. The readmission type was classified (CVD vs non-CVD) using the ICD-9 billing codes. To supplement the outcomes data obtained from the CUMC/NYPH electronic medical records, all patients were systematically interviewed by mail or telephone 1 year after the index hospitalization that corresponded with their baseline survey interview date and queried regarding rehospitalization in the previous year (80% response rate). Rehospitalization was defined as rehospitalization at CUMC/NYPH or elsewhere for CVD or other reasons. The analyses using this definition were similar to the analysis limited to readmission to CUMC/NYPH only. Vital status was obtained from the clinical information system, which was updated monthly with National Death Index data.

The Ghali co-morbidity index was calculated for all patients using the medical history data obtained through systematic electronic record review. The Ghali co-morbidity index was developed by assigning study-specific data-derived weights to the original, widely used Charlson co-morbidity variables. Condition- and study-specific co-morbidity weights have been shown to be better predictors of adverse outcomes than the standard scores used to summarize co-morbidity. The Ghali co-morbidity index has been shown to be superior to the Charlson index for the prediction of in-hospital mortality among cardiac patients. The weighted conditions used to calculate the Ghali co-morbidity index were myocardial infarction, heart failure, peripheral vascular disease, and moderate or severe renal disease. The total score range was 0 to 11, with patients scoring 0 at the lowest risk. For the present analysis, the Ghali co-morbidity index was dichotomized at >1 versus 1 based on research indicating scores >1 are consistent with significant co-morbidities. In a subset of participants with data available to calculate both scores, the Ghali co-morbidity index correlated significantly with the New York State Department of Health risk scores for percutaneous coronary intervention (n = 613; p <0.001).

The surveys were created and processed using the intelligent character recognition software EzDataPro32, version 8.0.7 (Creative ICR, Beaverton, Oregon) and ImageFomula, version Dr-2,580C (Canon US, New York, New York). The data were double checked for errors and stored in a Microsoft Access database (Microsoft, Redmond, Washington). Descriptive data are presented as frequencies and percentages. Caregiving was categorized as having paid, informal, or any (either paid or informal) caregivers. Chi-square tests were used to determine the association between caregiving and the baseline characteristics of the hospitalized patients with CVD using a Bonferroni correction for multiple comparisons (p <0.017). The independent association between caregiving and clinical outcomes was evaluated using logistic regression analysis adjusted for confounders. A stratified analysis by baseline admission type (current or previous heart failure vs no history of heart failure) was also conducted.

To evaluate the potential role of exposure selection bias, propensity score weights were calculated, and a propensity score-weighted logistic model was fitted. The model covariates included demographic variables (age, gender, race/ethnicity, health insurance), Ghali co-morbidity index, and co-morbid conditions not accounted for by the Ghali co-morbidity index but associated with death or rehospitalization at 1 year (diabetes mellitus, chronic obstructive pulmonary disease, number of prescription medications at discharge, and history of hypertension). Analyses were conducted using SAS software, version 9.2 (SAS Institute, Cary, North Carolina). Statistical significance for the logistic regression models was set at p <0.05.

Results

Of 3,188 consecutively admitted cardiology patients enrolled in the present study, 1,206 (38%) reported having any type of caregiver, and 789 (25%) had an informal caregiver only. A summary of the prevalence of the demographic factors and co-morbidities according to paid, informal, or no caregiver status is presented in Table 1 . Patients without a caregiver had substantially fewer co-morbid conditions.

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