Dave Collingridge

The quality of qualitative research.

In general, an appreciation of the standards of qualitative research and the types of qualitative data analyses available to researchers have not kept pace with the growing presence of qualitative studies in medical science. To help rectify this problem, the authors clarify qualitative research reliability, validity, sampling, and generalizability. They also provide 3 major theoretical frameworks for data collection and analysis that investigators may consider adopting. These 3 approaches are ethnography, existential phenomenology, and grounded theory. For each, the basic steps of data collection and analysis involved are presented, along with real-life examples of how they can contribute to improving medical care. (Am J Med Qual 2008;23:389-395)

A Primer on Quantitized Data Analysis and Permutation Testing

Quantitization refers to transforming qualitative data into numerical format. Approaches to quantitization include dichotomizing qualitative themes and counting qualitative codes. Statistical analysis of themes and code counts has the potential to produce valuable information for mixed methods researchers. Examples of quantitized statistical analysis are presented along with ways in which the results can provide useful insights. With regard to analyzing code counts, due to limitations associated with traditional parametric and nonparametric tests of significance, permutation testing is offered as a rigorous alternative. A detailed example of permutation testing using readily available resampling software is provided.

Spirometric reference values for Malagasy adults aged 18–73 years

The American Thoracic Society (ATS) and European Respiratory Society (ERS) recommend that spirometry prediction equations be derived from samples of similar race/ethnicity. Malagasy prediction equations do not exist. The objectives of this study were to establish prediction equations for healthy Malagasy adults, and then compare Malagasy measurements with published prediction equations. We enrolled 2491 healthy Malagasy subjects aged 18–73 years (1428 males) from June 2006 to April 2008. The subjects attempted to meet the ATS/ERS 2005 guidelines when performing forced expiratory spirograms. We compared Malagasy measurements of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC with predictions from the European Community for Steel and Coal (ECSC), the third National Health and Nutrition Examination Survey (NHANES III) and the ERS Global Lung Function Initiative (GLI) 2012 study. A linear model for the entire population, using age and height as independent variables, best predicted all spirometry parameters for sea level and highland subjects. FEV1, FVC and FEV1/FVC were most accurately predicted by NHANES III African-American male and female, and by GLI 2012 black male and black and South East Asian female equations. ECSC-predicted FEV1, FVC and FEV1/FVC were poorly matched to Malagasy measurements. We provide the first spirometry reference equations for a healthy adult Malagasy population, and the first comparison of Malagasy population measurements with ECSC, NHANES III and GLI 2012 prediction equations. Malagasy linear regression predicts spirometry, as do NHANES III and GLI 2012 black and South East Asian equations http://ow.ly/DvUQv

Comparison of NHANES III and ERS/GLI 12 for airway obstruction classification and severity

The diagnosis and severity categorisation of obstructive lung disease is determined using reference values. The American Thoracic Society/European Respiratory Society in 2005 recommended the National Health and Nutrition Examination Survey (NHANES) III spirometry prediction equations for patients in USA aged 8–80 years. The Global Lung Initiative 2012 (GLI 12) provided spirometry prediction equations for patients aged 3–95 years. Comparison of the NHANES III and GLI 12 prediction equations for diagnosing and categorising airway obstruction in patients in USA has not been made. We aimed to quantify the differences between NHANES III and GLI 12 predicted values in Caucasians aged 18–95 years, using both mathematical simulation and clinical data. We compared predicted forced expiratory volume in 1 s (FEV1) and lower limit of normal (LLN) FEV1/forced vital capacity (FVC) % for NHANES III and GLI 12 prediction equations by applying both a simulation model and clinical spirometry data to quantify differences in the diagnosis and categorisation of airway obstruction. Mathematical simulation revealed significant similarities and differences between prediction equations for both LLN FEV1/FVC % and predicted FEV1. There are significant differences when using GLI 12 and NHANES III to diagnose airway obstruction and severity in Caucasian patients aged 18–95 years. Similarities and differences exist between NHANES III and GLI 12 for some age and height combinations. The differences in LLN FEV1/FVC % and predicted FEV1 are most prominent in older taller/shorter individuals. The magnitude of the differences can be large and may result in differences in clinical management. Significant differences exist between NHANES III and GLI 12 prediction equations for some age and height combinations http://ow.ly/4mWTZ8

Impact of pharmacy services on cystic fibrosis medication adherence

The purpose of this study is to characterize the impact of pharmacy services on medication adherence and hospitalizations for pediatric cystic fibrosis (CF) patients.

Validation of the Intermountain patient perception of quality (PPQ) survey among survivors of an intensive care unit admission: a retrospective validation study

BackgroundPatients’ perceptions of the quality of their hospitalization have become important to the American healthcare system. Standard surveys of perceived quality of healthcare do not focus on the Intensive Care Unit (ICU) portion of the stay. Our objective was to evaluate the construct validity and internal consistency of the Intermountain Patient Perception of Quality (PPQ) survey among patients discharged from the ICU.MethodsWe analyzed prospectively collected results from the ICU PPQ survey of all inpatients at Intermountain Medical Center whose hospitalization included an ICU stay. We employed principal components analysis to determine the constructs present in the PPQ survey, and Cronbach’s alpha to evaluate the internal consistency (reliability) of the items representing each construct.ResultsWe identified 5,680 patients who had completed the PPQ survey. There were three basic domains measured: nursing care, physician care, and overall perception of quality. Most of the variability was explained with the first two principal components. Constructs did not vary by type of respondent.ConclusionsThe Intermountain ICU PPQ survey demonstrated excellent construct validity across three distinct constructs. This, in addition to its previously established content validity, suggests the utility of the PPQ survey as an assay of the perceived quality of the ICU experience.

The Laboratory-Based Intermountain Validated Exacerbation (LIVE) Score Identifies Chronic Obstructive Pulmonary Disease Patients at High Mortality Risk

Background: Identifying COPD patients at high risk for mortality or healthcare utilization remains a challenge. A robust system for identifying high-risk COPD patients using Electronic Health Record (EHR) data would empower targeting interventions aimed at ensuring guideline compliance and multimorbidity management. The purpose of this study was to empirically derive, validate, and characterize subgroups of COPD patients based on routinely collected clinical data widely available within the EHR. Methods: Cluster analysis was used in 5,006 patients with COPD at Intermountain to identify clusters based on a large collection of clinical variables. Recursive Partitioning (RP) was then used to determine a preferred tree that assigned patients to clusters based on a parsimonious variable subset. The mortality, COPD exacerbations, and comorbidity profile of the identified groups were examined. The findings were validated in an independent Intermountain cohort and in external cohorts from the United States Veterans Affairs (VA) and University of Chicago Medicine systems. Measurements and Main Results: The RP algorithm identified five LIVE Scores based on laboratory values: albumin, creatinine, chloride, potassium, and hemoglobin. The groups were characterized by increasing risk of mortality. The lowest risk, LIVE Score 5 had 8% 4-year mortality vs. 56% in the highest risk LIVE Score 1 (p < 0.001). These findings were validated in the VA cohort (n = 83,134), an expanded Intermountain cohort (n = 48,871) and in the University of Chicago system (n = 3,236). Higher mortality groups also had higher COPD exacerbation rates and comorbidity rates. Conclusions: In large clinical datasets across different organizations, the LIVE Score utilizes existing laboratory data for COPD patients, and may be used to stratify risk for mortality and COPD exacerbations.

Stability of Frequency of Severe Chronic Obstructive Pulmonary Disease Exacerbations and Health Care Utilization in Clinical Populations

Rationale: Although chronic obstructive pulmonary disease (COPD) exacerbation frequency is stable in research cohorts, whether severe COPD exacerbation frequency can be used to identify patients at high risk for future severe COPD exacerbations and/or mortality is unknown. Methods: Severe COPD exacerbation frequency stability was determined in 3 distinct clinical cohorts. A total of 17,450 patients with COPD in Intermountain Healthcare were categorized based on the number of severe COPD exacerbations per year. We determined whether exacerbation frequency was stable and whether it predicted mortality. These findings were validated in 83,134 patients from the U.S. Veterans Affairs (VA) nationwide health care system and 3326 patients from the University of Chicago Medicine health system. Results: In the Intermountain Healthcare cohort, the majority (84%, 14,706 patients) had no exacerbations in 2009 and were likely to remain non-exacerbators with a significantly lower 6-year mortality compared with frequent exacerbators (2 or more exacerbations per year) (25% versus 57%, p<0.001). Similar findings were noted in the VA health system and the University of Chicago Medicine health system. Non-exacerbators were likely to remain non-exacerbators with the lowest overall mortality. In all cohorts, frequent exacerbator was not a stable phenotype until patients had at least 2 consecutive years of frequent exacerbations. COPD exacerbation frequency predicted any cause mortality. Conclusions: In clinical datasets across different organizations, severe COPD exacerbation frequency was stable after at least 2 consecutive years of frequent exacerbations. Thus, severe COPD exacerbation frequency identifies patients across a health care system at high risk for future COPD-related health care utilization and overall mortality.