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Eur J Cardiovasc Nurs. Author manuscript; available in PMC 2019 April 01.
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Published in final edited form as:
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Eur J Cardiovasc Nurs. 2019 April ; 18(4): 325–331. doi:10.1177/1474515119825704.
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Measuring Health Status and Symptom Burden using a web
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based mHealth Application in Patients with Heart Failure
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Dawon Baik, PhD, RN,
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Columbia University School of Nursing, 630 West 168 Street; Mail Code 6, New York, New York
10032
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Meghan Reading, PhD, MPH, RN,
Weill Cornell Medicine, Department of Healthcare Policy & Research, 425 East 61st Street, Suite
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301, New York, NY 10065
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Haomiao Jia, PhD,
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Columbia University School of Nursing, 630 West 168th Street; Mail Code 6, New York, NY 10032
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Lisa V. Grossman, and
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Columbia University, Department of Biomedical Informatics, 622 W. 168th St, PH-20, New York,
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NY 10032
Ruth Masterson Creber, PhD, MSc, RN
Weill Cornell Medicine, Department of Healthcare Policy & Research, 425 East 61st Street, Suite
301, New York, NY 10065
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Abstract
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Background: Symptoms of heart failure (HF) markedly impair a patient’s health status. The aim
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of this study was to identify predictors of health status in a sample of racially and ethnically
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diverse patients with HF using a web-based mobile health (mHealth) application, mi.Symptoms.
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Methods: We conducted a cross-sectional study at an urban academic medical center. Patients
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with HF self-reported symptoms using validated symptom instruments (e.g. Patient-Reported
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Outcome Measurement Information System) via the mHealth application, mi.Symptoms. The
primary study outcome was health status, measured with the Kansas City Cardiomyopathy
Questionnaire Clinical Summary Score. Data were analyzed using descriptive statistics and
multiple linear regression.
Results: The mean age of the sample (n=168) was 58.7 (±12.5) years, 37% were female, 36%
were Black, 36% identified as Hispanic/Latino, 48% were classified as NYHA class III, and 44%
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reported not having enough income to make ends meet. Predictors of better health status in HF
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included higher physical function (β = 0.89, p = 0.001) and ability to participate in social roles and
activities (β = 0.58, p = 0.002), and predictors of poorer health status were NYHA Class IV (β = −
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Corresponding Author: Dawon Baik, Columbia University, School of Nursing, 560 W 168th St, New York, NY 10032, 212 305
7404, [email protected].
Declaration of Conflicting Interests
Authors declare that there is no conflict of interest.
Baik et al. Page 2
11.68, p = 0.006) and dyspnea (β = − 0.77, p < 0.001). The predictors accounted for 73% of the
variance in health status.
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Conclusion: Patient-centered interventions should focus on modifiable risk factors that reduce
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dyspnea, improve functional status, and enhance engagement in social roles to improve the health
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status of patients with HF.
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Keywords
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heart failure; mobile health; symptoms; social participation; physical function; health status
Introduction
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Heart failure (HF) is a significant global health problem and is the fastest growing
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cardiovascular disease affecting approximately 26 million people worldwide. HF is
characterized by chronic and progressive symptoms that worsen over the course of the
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disease. Escalating HF symptoms and acute decompensation limit physical and social
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activities of daily living and increase the risk of hospitalizations.
HF treatments represent
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1−2% of the total healthcare expenditures in Europe and North America, and have an
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estimated cost of over $39 billion annually in the U.S. In addition, HF is the most common
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cause for hospital admission and readmission, and the most expensive of all Medicare
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diagnoses in the U.S.
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Patients with HF have markedly worse self-reported health status, defined as exacerbated
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symptoms, limited physical and social function, and lower level of quality of life,
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compared to those with other chronic diseases.
Health status reflects the multidimensional
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health conditions in HF patients’ daily lives. Specifically, the health status of patients with
HF is impaired by physical (dyspnea, fatigue, pain, sleep) and psychological symptoms
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(anxiety, depression, anger).
Previous studies have identified the New York Heart
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Association (NYHA) class, age, gender, race, and financial status as factors influencing
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health status in patients with HF.
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It is crucial to monitor and manage symptoms of HF to improve health status and decrease
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the risk of acute exacerbations and rehospitalizations. Nevertheless, patients with HF
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15–17
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struggle with self-care management
and symptom perception. Thus, mobile Health
(mHealth) technology (e.g., smartphones, tablet computers) can be used at the point of need
to facilitate the ability of HF patients to recognize their own symptoms, connect the
symptoms to HF disease and communicate them with their healthcare providers. In
particular, mHealth applications have been used with increasing frequency to quantify a
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patient’s symptoms in the outpatient environment. Data collected via mHealth applications
in the patient’s home can be integrated into a patient’s health profile and used by healthcare
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providers to provide insights into their health status between clinic visits. Leveraging the
potential of mHealth technology, we developed a mHealth application, mi.Symptoms to
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facilitate the reporting of patient symptoms. As part of this study, we identified patient
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reported symptoms and the health status of patients with HF collected using the
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mi.Symptoms.
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Eur J Cardiovasc Nurs. Author manuscript; available in PMC 2019 April 01.
Baik et al. Page 3
Most previous studies that evaluate predictors of health status in HF have primarily included
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samples that have been predominantly Caucasian.
Less is known about predictors of
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health status in racially and ethnically diverse patient populations. Furthermore, few studies
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have used a mHealth application to identify and report physical and psychological symptoms
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of HF and their associations with health status. mHealth applications can play an important
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role in helping patients with HF and healthcare providers discuss symptoms using a single,
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integrated mobile system, thereby enabling shared decision-making about medical plans and
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treatments. Accordingly, the aim of this study was to identify predictors of health status in a
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racially and ethnically diverse, urban sample of English and Spanish-speaking HF patients,
using the mHealth web-application, mi.Symptoms.
Methods
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Study Design and Participants
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We conducted a cross-sectional study to examine symptoms and predictors of health status
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of patients with HF using the mHealth application, mi.Symptoms. We recruited patients with
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HF from a cardiac inpatient unit and an ambulatory cardiac clinic at an urban academic
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medical center in New York from October 2016 to January 2017. Eligible patients were
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identified using electronic health records. Patients were included if they met the following
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criteria: (1) diagnosed with HF confirmed by clinical exam, echocardiographic evidence, or
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a cardiologist, (2) willing and able to provide informed consent, (3) literate in English or
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Spanish, and (4) age 21 years or older. Patients were excluded if they had been diagnosed
with dementia, active psychosis, or isolation precautions. All participants provided written
informed consent in English or Spanish and were given $35 as a token of appreciation for
their time. Participants reported their symptom experience using the mi.Symptoms
application developed by the research team to allow patients to report and communicate their
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symptoms with their healthcare providers. Participants used the mi.Symptoms application on
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an iPad and completed demographic survey questionnaires and perceived health status using
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the Qualtrics survey software. A more detailed description of the development and usability
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test of mi.Symptoms application can be found elsewhere.
This study was approved by
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the Institutional Review Board of the Columbia University Medical Center.
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Measurements
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Sociodemographic questionnaire—The sociodemographic questionnaire collected
information on age, gender, race, ethnicity, marital status, financial status, education, health
literacy, participation in self-care management, type of heart failure, NYHA class, and total
medications. Health literacy was measured using the Brief Health Literacy Screener that
consists of 3 items with a Likert scale to assess the ability to understand health information
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and services needed to make medical decisions. Patient activation was measured with the
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Patient Activation Measure-13.
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Heart Failure Somatic Perception Scale—The Heart Failure Somatic Perception Scale
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(HFSPS) is an 18-item measure of HF-specific physical symptoms with total scores that
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range from 0 to 90 (Cronbach’s alpha: 0.90).
The HFSPS has five response options
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ranging from zero (I did not have the symptom) to five (extremely bothersome) with higher
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Baik et al. Page 4
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scores indicating higher symptom burden. The HFSPS includes a 6-item Dyspnea subscale
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with total scores that range from 0 to 30 (Cronbach’s alpha: 0.89).
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Patient Reported Outcomes Measurement Information System—To measure non
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cardiac symptoms, including psychological symptoms, we used the Patient-Reported
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Outcome Measurement Information System (PROMIS®) short-form questionnaires : Pain
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Interference v1.0, Fatigue v1.0, Sleep Disturbance v1.0, Depression v1.0, Anxiety
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v1.0, Emotional Distress-Anger v1.1, Physical Function v2.0, Applied Cognition
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Abilities v2.0, and Ability to Participate in Social Roles and Activities v2.0.
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The
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PROMIS short forms each have four or five questions. Response options range from one to
five. This measure uses a response pattern scoring that examines responses to each item for
each participant. The response scores of each item are summed for the total raw score by
adjusting for missing data. The raw scores are rescaled using the T-score to calculate a
standardized score with a mean of 50 and a standard deviation of 10 for the general
population in the U.S. The standardized T-score represents the final score for each patient. A
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higher PROMIS T-score indicates more of the concept being measured. A higher PROMIS
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score represents greater pain, greater fatigue, greater depression, greater anxiety, greater
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emotional distress-anger, better physical function, better cognition ability and better
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participation in social roles and activities. We chose the PROMIS measure because it is not
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disease specific, thus assessing psychological symptoms that are common across multiple
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health conditions. In addition, all of the PROMIS questionnaires are freely available and
have Spanish versions with comprehensive linguistic validation.
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Kansas City Cardiomyopathy Questionnaire Clinical Summary Score—The
primary outcome of this study is health status, which was measured with the 23-item Kansas
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City Cardiomyopathy Questionnaire Clinical Summary Score (KCCQ). Health status is a
composite outcome that consists of five domains including physical function, symptoms
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(frequency, severity, and recent change over time), social function, self-efficacy, and quality
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of life of patients with HF. The KCCQ is a reliable and valid measure with a Likert scale
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and five to seven response options. The scales are ranged from 0 to 100 with higher scores
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indicating fewer symptoms, better function and greater quality of life. Cronbach’s alpha of
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the KCCQ scale in this study was 0.94.
Data analysis
Statistical analyses were conducted using the STATA version 13 (Stata Corporation Inc.,
College Station, TX, USA). Descriptive statistics including mean, standard deviation,
frequency, and percentages were employed to characterize the participants of this study.
Multiple linear regression analysis was used to identify predictors of health status in patients
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with HF. A p-value of 0.05 represented the threshold for determining statistical significance.
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Results
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Sociodemographic Characteristics of Study Participants
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Table 1 illustrates the sociodemographic characteristics of all participants in this study. The
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sample (n=168) had a mean age of 58.7 (±12.5) years, 37% of participants were female, and
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36% were Black. Overall 36% of participants identified as Hispanic/Latino and 20%
completed the study in Spanish. More than a third of the participants were married (38%),
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nearly half (44%) reported not having enough income to make ends meet, and most patients
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(47%) graduated from college. More than half of the participants (52%) had the ability to
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understand health information and services and 71% engaged in activities for self-care
symptom management. Most patients (69%) had HF with reduced ejection fraction, 48%
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were classified as NYHA class III, and 65% had a left ventricular ejection fraction of less
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than 40%. The average number of medications taken per participant was 13 (±5.2).
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Table 2 shows the descriptive characteristics of HF patient-reported physical and
psychological symptoms including the PROMIS® measure. In addition, the mean of the
total score for the HFSPS was 42.9 (±21.4) and the mean of the HFSPS Dyspnea subscale
was 16.0 (±9.8). The mean of KCCQ Health Status scores was 49.3 (±27.2). All
measurements used in this study had excellent or good internal consistency with Cronbach’s
alpha ranging from 0.87 to 0.95.
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Patient-Reported Factors Associated with Health Status
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In bivariate analyses, multiple patient-reported factors, including demographic
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characteristics (race, ethnicity, financial status, NYHA class), physical symptoms (physical
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function, dyspnea, pain, fatigue, sleep), psychological symptoms (anxiety, depression,
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anger), physical function, cognition abilities, and the ability to participate in social roles and
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activities were significantly associated with health status (p 50% 49 (30.4)
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40–50% 8 (5.0)
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