Dataset Information

Confirmatory factor analysis of the pain care quality surveys (PainCQ©).

ABSTRACT:

Objective

To examine the reliability and validity and to decrease the battery of items in the Pain Care Quality (PainCQ(©) ) Surveys.

Data sources/study setting

Patient-reported data were collected prospectively from 337 hospitalized adult patients with pain on medical/surgical oncology units in four hospitals in three states.

Study design

This methodological study used a cross-sectional survey design. Each consenting patient completed two PainCQ(©) Surveys, the Brief Pain Inventory-Short Form, and demographic questions. Clinical data were extracted from the medical record.

Data collection/extraction methods

All data were double entered into a Microsoft Access database, cleaned, and then extracted into SPSS, AMOS, and Mplus for analysis.

Principal findings

Confirmatory factor analysis using Structural Equation Modeling supported the initial factor structure. Modification indices guided decisions that resulted in a superior, parsimonious model for the PainCQ-Interdisciplinary Care Survey (six items, two subscales) and the PainCQ-Nursing Care Survey (14 items, three subscales). Cronbach's alpha coefficients all exceeded .80.

Conclusions

Cumulative evidence supports the reliability and validity of the companion PainCQ(©) Surveys in hospitalized patients with pain in the oncology setting. The tools may be relevant in both clinical research and quality improvement. Future research is recommended in other populations, settings, and with more diverse groups.

SUBMITTER: Pett MA

PROVIDER: S-EPMC3681241 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Pett Marjorie A MA Beck Susan L SL Guo Jia-Wen JW Towsley Gail L GL Brant Jeannine M JM Lavoie Smith Ellen M EM Berry Patricia H PH Donaldson Gary W GW

Health services research 20121203 3

<h4>Objective</h4>To examine the reliability and validity and to decrease the battery of items in the Pain Care Quality (PainCQ(©) ) Surveys.<h4>Data sources/study setting</h4>Patient-reported data were collected prospectively from 337 hospitalized adult patients with pain on medical/surgical oncology units in four hospitals in three states.<h4>Study design</h4>This methodological study used a cross-sectional survey design. Each consenting patient completed two PainCQ(©) Surveys, the Brief Pain ...[more]

PMID: 23205503

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Project description:BackgroundEmerging data show that many low-income and middle-income country (LMIC) health systems struggle to consistently provide good-quality care. Although monitoring of inequalities in access to health services has been the focus of major international efforts, inequalities in health-care quality have not been systematically examined.MethodsUsing the most recent (2007-16) Demographic and Health Surveys and Multiple Indicator Cluster Surveys in 91 LMICs, we described antenatal care quality based on receipt of three essential services (blood pressure monitoring and urine and blood testing) among women who had at least one visit with a skilled antenatal-care provider. We compared quality across country income groups and quantified within-country wealth-related inequalities using the slope and relative indices of inequality. We summarised inequalities using random-effects meta-analyses and assessed the extent to which other geographical and sociodemographic factors could explain these inequalities.FindingsGlobally, 72·9% (95% CI 69·1-76·8) of women who used antenatal care reported blood pressure monitoring and urine and blood testing; this number ranged from 6·3% in Burundi to 100·0% in Belarus. Antenatal care quality lagged behind antenatal care coverage the most in low-income countries, where 86·6% (83·4-89·7) of women accessed care but only 53·8% (44·3-63·3) reported receiving the three services. Receipt of the three services was correlated with gross domestic product per capita and was 40 percentage points higher in upper-middle-income countries compared with low-income countries. Within countries, the wealthiest women were on average four times more likely to report good quality care than the poorest (relative index of inequality 4·01, 95% CI 3·90-4·13). Substantial inequality remained after adjustment for subnational region, urban residence, maternal age, education, and number of antenatal care visits (3·20, 3·11-3·30).InterpretationMany LMICs that have reached high levels of antenatal care coverage had much lower and inequitable levels of quality. Achieving ambitious maternal, newborn, and child health goals will require greater focus on the quality of health services and their equitable distribution. Equity in effective coverage should be used as the new metric to monitor progress towards universal health coverage.FundingBill & Melinda Gates Foundation.

Dataset Information

Confirmatory factor analysis of the pain care quality surveys (PainCQ©).

Objective

Data sources/study setting

Study design

Data collection/extraction methods

Principal findings

Conclusions

Publications

Confirmatory factor analysis of the pain care quality surveys (PainCQ©).

Similar Datasets

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