The purpose of this paper is to determine which psychometric instruments have been used to identify risk factors to predict hospitalizations in patients with chronic obstructive pulmonary disease (COPD).
An integrative literature review was conducted on published studies carried out in the United States (US) and internationally, measuring risk factors related to hospital admission and readmission for COPD from 2002 to 2015. An extensive search was done using electronic databases PubMed, CINAHL, MEDLINE, and Google Scholar to find studies published in English, adults 18 years and older. Systematic manual searches produced additional empirical studies.
Of the 29 studies screened from electronic data bases the literature search (n = 6) and systematic manual searches (n = 9) met the criteria. The outcome yielded (n = 15) articles that met the criteria, reflecting heterogeneity in types of measurements involving clinical data, psychosocial, and socioeconomic variables in the final data set.
This integrative review found a multitude of psychometric instruments for assessing risk factors for COPD admission, which highlights the need for a comprehensive and concise instrument to identify patients at risk for future hospital admissions in the acute care setting. Due to a limited number of studies examining risk factors related to COPD admission, the literature search span was conducted from 2002 to 2015.
Keywords: COPD; Admission; Risk Assessment; St. George’s Respiratory Questionnaire; Quality of Life
When a patients with COPD comes to the emergency department (ED) for treatment, a tenuous balance exists in deciding, in less critical exacerbations of COPD (ECOPD), whether or not to admit the patient? Starting 2015 new regulations stipulating what is paid from healthcare funds has increased the need for better predictors for hospitalization . Medicare and Medicaid Services define a hospital readmission as an admission within 30 days for the same diagnosis . Based on new regulations by the Centers for Medicare and Medicaid, (section 3025 of the Affordable Care Act, section 1886q) individuals who are readmitted to the hospital for an acute exacerbated COPD, the hospital will not be paid or not paid in full for that hospitalization . Medicaid and Medicare are government-sponsored healthcare programs in the United States (US) with stipulations on payment which includes who is covered and how much will be paid for in health services . Adding to this dilemma, published studies on measurements to identify risk factors related to hospitalization for individuals with COPD, reveal there is no consensus on what measurement instruments best predict hospitalization [3-6].
The Study Design
The aim of this integrative review of the literature is to present findings from studies using instruments to determine risk factors predicting hospitalization among patients with COPD. COPD is a disease with worse implications among individuals of urban, low socioeconomic status. These vulnerable individuals are more likely to have high risk factors with frequent hospitalization or readmission for the same previous diagnosis of COPD [4, 7, 8]. Risk factors can be measured and can predict the likelihood of patients with COPD being hospitalized or readmitted (either of these being the result) for treatment of their COPD. For this integrative review a theoretical definition of risk factors for hospitalization of patients with COPD will include identified variables that are related to physical, functional, psychological, and socioeconomic status. An operational definition of risk factors for hospitalization for patients with COPD having dyspnea and hypoxia, can be obtained by collecting data using scales that determine most causative risk factors related to patients with COPD hospitalizations.
Due to a limited number of studies examining psychometric measures of risk factors related to COPD admission, the literature search span was conducted from 2002 to 2015. Two search strategies were conducted to identify articles describing instruments that measure risk factors for hospital admission and readmission to the hospital for COPD or exacerbated COPD treatment. Inclusion criteria: human, English, adults 18 year of age and older, risk factors for COPD admission. Exclusion criteria: studies that used an intervention and those using a machine-learning method such as Random Forest (due to lack of external cross-validation). The first search from 2002 to 2014 used MEDLINE, CINAHL, PubMed and the Cochrane Library. The search terms used for each database included MEDLINE: confounding variables (epidemiology), pulmonary disease, chronic obstructive, risk assessment, hospitalization, inpatients; patient discharge; risk factors; epidemiologic measurements; CINAHL: research instruments, pulmonary disease, chronic obstructive independent variable, risk assessment, hospitalization, inpatients, patient discharge education; PubMed: hospital predictors, chronic pulmonary disease, COPD, hospitalization, unplanned readmission, risk of admission, readmission; MeSH terms: hospitals; hospital; predictors; pulmonary disease, chronic obstructive, and the Cochrane Library: risk factors; predictors; chronic obstructive pulmonary disease; hospitalization; instruments to measure. MEDLINE: risk assessment, pulmonary disease, chronic obstructive produced 716 articles. CINAHL: risk assessment, pulmonary disease, chronic obstructive found 144 articles. PubMed: pulmonary disease, chronic obstructive MeSH and risk factors MeSH found 23 articles. From these searches, a total of 883 articles, 6 articles were obtained that met the inclusion criteria for adults 18 years and older, having COPD, male or female, and studies published in the US or other countries available in the English language.
A second search strategy was conducted using the same inclusion criteria to increase the number of studies measuring risk factors; hospital admission and readmission to the hospital for COPD treatment using MEDLINE, CINAHL, PubMed, Cochrane, and Google Scholar. Google Scholar searched with phrase: “COPD predictive instrument for hospital admission” and the phrase “St. George’s Respiratory Questionnaire to measure risk factor COPD and hospitalization” between 2002 to 2015 articles. A total of 13,283 articles were obtained and screened. Articles were selected if they met the inclusion criteria for adults 18 years and older, having COPD, male or female, hospital admission for COPD, risk factors predictive of hospital admission, and studies published in the US or other countries available in the English language. Sixty-seven pages were screened and 8 articles were obtained from hand searches of the retrieved Google references. In addition, one article met criteria from MEDLINE.
In total, 15 studies were included from the search strategy that met the inclusion criteria. The select sample of studies were from the following countries: Canada, India, Portugal, Scotland, Singapore, Spain, United Kingdom (UK), and the United States (US). Type of studies included: prospective (n =11), case control (n =1), observation (n =1), longitudinal (n = 1), and historical cohort (n=1). Quality appraisal used The Center for Evidence-Based Medicine Levels of Evidence to evaluate and rate the level of evidence for each study . Table 1.
Note. Body mass index (BMI), air flow obstruction, dyspnea (score from the modified Medical Research Council (MRC), and exercise capacity (distance walked in 6 minutes (BODE index), Global Initiative for Chronic Obstructive Lung Disease (GOLD), Glascow Coma Scale (GCS), Charlson Comorbidity Index (CCI), evaluation of COPD longitudinally to identify predictive surrogate endpoints (ECLIPSE), St. George’s Respiratory Questionnaire (SGRQ), Graffar Scale (socioeconomic score), Hospital Anxiety and Depression Scale (HADS), Carstairs index (socioeconomic deprivation), enhancing recovery in coronary heart disease (ENRICHD) social support inventory (ESSI), State-trait anxiety inventory (STAIS/ T), shortness of breath questionnaire (SOBQ), Beck-Depression Inventory, Anthoisen criteria determining severity of COPD, Seattle Obstructive Lung Disease Questionnaire (SOLDQ), Airway questionnaire 20 (AQ20), Cognitive Status Pfeiffer Questionnaire, Katz Activities of Daily Living Scale, Yesavage Scale (short version to evaluate the presence of depression), Canadian Triage and Acuity Scale (CTAS).
Levels of Evidence (Oxford Centre for Evidence-based Medicine – Levels of Evidence, March 2009) 
Of the fifteen studies included in the integrative review, numerous instruments were identified as measuring for risk factors predictive for hospital admission or readmission of COPD, exacerbated COPD, or patients with acute exacerbated COPD. Deciphering the validity and reliability of the instruments used to measure risk factors for COPD admission was as multifaceted problem given the different types that existed across studies. Specific reports of reliability and validity are typically not reported but we assume that these attributes are subsumed within the statistical tests conducted; especially for reliability. As a result reliability and validity are reported together. Statistical analysis of measurements used in the studies were done in order to determine risk factors, which focused on the predictive capacity of variables related to hospitalization for exacerbated COPD. In other words, all of these studies examined the predictive validity of exacerbated COPD hospitalizations using multiple variables.
Reliability is necessary for validity to be established [17,18]. However, the nature of COPD progression makes it difficult for reliability to be independently established. The study conducted by Vidal et al. had the highest statistic value predictive for COPD hospitalization amid the studies included in the review . The accuracy in the model to measure to predictive risk factors for hospitalization among patients with COPD was reported as being the area under the curve (AUC) 0.89. An outcome such as this, would indicate a clinical classification of the measurement tool as ‘good’ in predicting an admission for COPD . One study in the review reported being the first to use measurements to determine risk factors in their country, consequently stability of these measures has not been established . Multiple studies demonstrated the correlation between episodes of exacerbated COPD and accelerated disease progression, which in turn increase the incidence of repeated future hospital admissions, and mortality [11, 13]. As COPD patients experience exacerbations, deterioration impacts their quality of life, which is additionally challenged by those who have a low socioeconomic status, lack of social support, smoking, body mass index (BMI) being abnormally high or low, including the implications of experiencing anxiety, and depression .
Across studies multiple complexities and diverse models were used to measure risk factors. The BODE Index: BMI, degree of airway obstruction measured by forced expiration in one sec (FEV1), dyspnea (modified Medical Research Council questionnaire (mMRC), and exercise capacity measured by a 6-minute walk (6MWD), is a multidimensional score of COPD disease severity. Using the BODE index and other select clinical variables included, revealed a significant effect on predicting the number of COPD hospital admissions (95% Confidence Interval, 1.15 to 1.25; < 0.001) . Despite the BODE Index being valuable to clinicians because it is evaluates major indicators for hospital admission, many times the 6MWD it is not a useful instrument in the acute care setting.
In contrast, Coventry et al. from the United Kingdom measured variables with five different instruments to examine potential risk factors for COPD admission: baseline clinical data, St. George’s Questionnaire (SGRQ), Hospital Anxiety and Depression Scale (HADS), Charleston Comorbidity Index (CCI), Carstairs index (socioeconomic deprivation), and Enhancing Recovery in Coronary Heart Disease (ENRICHD) that included a social support inventory . Utilizing numerous tools was a common finding in all the studies. Expecting health care professionals to complete numerous scales is unrealistic, in order to determine COPD risk factors for hospitalization. The dilemma of finding a valid and reliable tool to measure risk prediction for COPD hospital admission is compounded by the regulation set by Medicare and Medicaid (2014) readmission penalty regarding reimbursement . Such a regulation indiscriminately imposes a judgment, presuming a lack of quality care and services among hospitals and the health care professionals .
There was limited reporting in the studies about their feasibility, but all had strengths in measuring risk factors. Table 2. Some of the specific strengths of the studies relied on the combination of instruments used and the inclusion of clinical, functional status, socioeconomic, and psychosocial components. Additionally, limitations of the integrative review was the heterogeneity of the different instruments used to capture the most predictive risk factors
Table 2. Constructs/instruments used in each study to determine risk factors for COPD admission. Report on validity and reliability of instruments with supporting citation.
Based on the initial literature results of 14,166 articles, 15 articles were selected that ranged in statistical rigor for determining risk factors most predictive of hospitalization for COPD or acute exacerbation of ECOPD. In addition, the studies clearly represent the global health crisis that COPD poses to patients diagnosed with this disease and the health care system that cares for them. One of the limitations of this study was that out of the articles measuring risk factors for exacerbated COPD hospital admission, most were from studies conducted outside of the US (80%). This is a limitation since other countries differ in health care practices and resources from the US. In addition, there was no consistency in the clinical data collected and the instruments used. The strengths of the studies revealed the correlation of past hospitalizations, low FEV1, measuring socioeconomic, and psychological aspects of anxiety and depression impacting the QOL of COPD patients.
Among these publications no theoretical frameworks were included, which could be the result of the studies being heavily influenced by physicians, who take more of a non-theoretical physiological approach to research. Random Forest (RF) was utilized in several studies found in the search but were not included because it employs an machine learning method where fit is almost always obtained irrespective of the clinical reliability and validity of the model [5, 21]. Other researchers conducted retrospective studies that did not meet the inclusion criteria. One such study was the Medicare Provider Analysis and Review (MEDPAR) files during the years 2006 and 2010 that included: California, Illinois, Florida, New York, Ohio, Pennsylvania, and Texas to detect risk factors for COPD hospital admission. Their findings revealed increasing use of hospitalization and common prevalent risk factors being congestive heart failure (CHF), patients who were indigent, sicker, lack of support, and low education level contributing to the vulnerability of this population .
COPD is a serious global health issue with a dynamic relationship involving patients’ socioeconomic status, self-rated quality of life, disease severity, comorbid factors, and geographic location. Due to the intricate problem of COPD and the fragile equilibrium of risk factors that predispose patients to being admitted to the hospital; finding one measurement instrument to identify the key potential risk factors is a daunting feat to accomplish. Access to valid and reliable instruments to measure risk factors employed by those health care professionals entrusted with the care of patients with COPD, needs to embody gestalt clinical assessment skills and follow an empirically sound predictive model [14, 18, 22].
The time is now, to create a comprehensive, efficient, and effective psychometric instrument that can measure risk factors in real-time to address this vulnerable COPD population [4, 15, 22, 23]. Use of the Socio-Ecological Model would provide a framework of four essential domains to be measured: individual (clinical, psychosocial, and socioeconomic factors); relationships (family, significant others); community setting (environment); and society (economic and social policies) [24, 25].
Research to establish statistically sound evidence of a new prediction model will bridge the gap in evidence-based practice for these patients. Therefore an instrument created with the Socio-Ecological Model and a baseline of common risk factors could be customized to meet the unique needs of populations in their geographic locations and susceptible attributes. Such an instrument could then be generalizable on a national and potentially international level. A COPD risk factor instrument, that could be used in the ED or when hospitalized patients have stabilized, would have the potential to improve outcomes, as well as conserving health care resources [10,23,24,26,27].
The authors would like to thank Lisa Kerr, PhD, and Kitty Serling, MLS for their guidance and support.
This research received no funding to write this paper and there are no conflicts of interest.