Health Status Assessment Completing the Clinical Database

doi:10.1046/j.1525-1497.1997.012004254.x

Cited by 8 publications

(1 citation statement)

References 21 publications

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“…These sources produce variable amounts of information about clinical outcomes and health care utilization, but generally lack the patient perspective. Mentions in clinical notes about health status tend to be ambiguous and non-standardized, such as “patient is doing well.”[27] There are several ways in which patient-reported outcome can be combined with other data sources to provide information about comparative effectiveness research. [28,29] The classical approach is to include patient-reported outcomes in clinical trials and observational studies or link them to administrative data.…”

Section: Just Add Patient-reported Outcomes?mentioning

confidence: 99%

Measure once, cut twice—adding patient-reported outcome measures to the electronic health record for comparative effectiveness research

Kharrazi

Boulware

et al. 2013

Journal of Clinical Epidemiology

169

105

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Objective This paper presents the current state of patient-reported outcome measures, and explains new opportunities for leveraging the recent adoption of electronic health records to expand the application of patient-reported outcomes in both clinical care and comparative effectiveness research. Study Design and Setting Historic developments of patient-reported outcome, electronic health record, and comparative effectiveness research are analyzed in two dimensions: patient-centeredness and digitization. We pose the question: “What needs to be standardized around the collection of patient-reported outcomes in electronic health records for comparative effectiveness research?” Results We identified three converging trends: the progression of patient-reported outcomes toward greater patient centeredness and electronic adaptation; the evolution of electronic health records into personalized and fully digitized solutions; the shift toward patient-oriented comparative effectiveness research. Related to this convergence, we propose an architecture for patient-reported outcome standardization that could serve as a first step toward a more comprehensive integration of patient-reported outcomes with electronic health record for both practice and research. Conclusion The science of patient-reported outcome measurement has matured sufficiently to be integrated routinely into electronic health records and other e-health solutions to collect data on an ongoing basis for clinical care and comparative effectiveness research. Further efforts and ideally coordinated efforts from various stakeholders are needed to refine the details of the proposed framework for standardization.

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Section: Just Add Patient-reported Outcomes?mentioning

confidence: 99%

Measure once, cut twice—adding patient-reported outcome measures to the electronic health record for comparative effectiveness research

Kharrazi

Boulware

et al. 2013

Journal of Clinical Epidemiology

169

105

View full text Add to dashboard Cite

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Self‐report quality of life as a predictor of hospitalization for patients with LV dysfunction: A life course approach¶

Stull

Clough

Dussen

2001

Research in Nursing & Health

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For this secondary data analysis of a large clinical drug study, researchers investigated the independent prognostic utility of self-report quality-of-life measures versus clinical measures for assessing patient risk for heart-failure-related hospitalization. The experience of heart failure varies over the life course; hence, four age groups were investigated. Quality-of-life measures, specifically health-related quality-of-life and psychosocial quality-of-life measures, were found to be independent and significant predictors of heart-failure-related hospitalizations, as compared to traditional clinical indicators. In addition, the psychosocial quality-of-life measure varied by age group in its importance as a predictor of hospitalization, suggesting differential relevance over the life course. Specifically, psychosocial quality of life was most strongly predictive of hospitalization for those ages 21-44, was less predictive for those ages 45-54, and was nonsignificant for those 55-64 years of age and those 65 and over. Including self-report quality-of-life measures provides a more complete picture of the factors associated with risk of hospitalization at different points in the life course for individuals with heart failure. These findings suggest that researchers and practitioners could use self-report quality-of-life measures as additional prognostic indicators of a patient's condition and risk for heart-failure-related hospitalization, especially for younger patients.

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Issues in the design of Internet-based systems for collecting patient-reported outcomes

Jones

Snyder

2007

Qual Life Res

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Health Status Assessment Completing the Clinical Database

Cited by 8 publications

References 21 publications

Measure once, cut twice—adding patient-reported outcome measures to the electronic health record for comparative effectiveness research

Measure once, cut twice—adding patient-reported outcome measures to the electronic health record for comparative effectiveness research

Self‐report quality of life as a predictor of hospitalization for patients with LV dysfunction: A life course approach¶

Issues in the design of Internet-based systems for collecting patient-reported outcomes

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