Domain

Analytic Methods

Type

Protocol

Theme

effectiveness; population

Start Date

7-6-2014 10:25 AM

End Date

7-6-2014 11:45 AM

Structured Abstract

Introduction: Research in a fragmented healthcare system can be challenging when one seeks to follow patients within a care episode. Cancer treatment can continue for months or years and a care trajectory may reflect many physician and patient decisions. Patients may seek evaluations or specialty care at more than one medical center, either through referrals or provider “shopping”. Claims data can track where patients are seen, but lack clinical detail. Linking routine data systems with clinical registry data offers one way to gain a more complete picture of the patient journey through a cancer care episode. However, valid analytical approaches to evaluating care trajectories must account for the dynamic nature of the EHR population, longitudinality of the data, and careful classification of cancer-related encounters. This study aims to better understand treatment location decisions among women with breast cancer who are seen at more than one healthcare facility, and highlights challenges associated with analyzing linked routine data sources.

Background: The OncoShare database combines clinical detail from the California Cancer Registry with EHR data from two large healthcare facilities in the same catchment area—a multisite community practice and an academic medical center—for all women treated for breast cancer from 2000-2012. A total of 11,716 women received diagnostic services or treatment related to their breast cancer from either of the two medical centers, 16% of whom received treatment at both institutions during the follow-up time. Preliminary cross-sectional analyses reveal that these women had comparable prognostic factors, but far more diagnostic and treatment interventions than those treated at only one facility. Accounting for the longitudinality of the EHR data reveals that the complexity of the patient journey and length of the care episode may account for some of the apparent differences in service utilization.

Findings: We review analytical strategies, descriptive statistics and results from longitudinal modeling to characterize treatment trajectories and define predictors of treatment facility decisions. We present key findings on identifiable predictors of facility decisions, especially as they relate to women who are seen at both facilities.

Lessons Learned: Linking EHR data from multiple neighboring healthcare systems can provide a rich source of information on patient journeys through cancer care episodes, but careful consideration of the complexity of the treatment process is necessary to make valid inferences about treatment trajectories. Longitudinal electronic medical records offer a rich source of data to begin to identify predictors of patient decisions.

Conclusion: If properly analyzed as a timeline, and with careful characterization of diagnostic tests, surgical interventions, and type and frequency of physician encounters, the “journeys” of women through their breast cancer episode may inform specific aspects of the complex patient decision process.

Acknowledgements

This work is supported by a grant from the Richard & Susan Levy Family Trust.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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Jun 7th, 10:25 AM Jun 7th, 11:45 AM

Linked electronic medical records to better understand cancer patient journeys within and between two care delivery systems

Introduction: Research in a fragmented healthcare system can be challenging when one seeks to follow patients within a care episode. Cancer treatment can continue for months or years and a care trajectory may reflect many physician and patient decisions. Patients may seek evaluations or specialty care at more than one medical center, either through referrals or provider “shopping”. Claims data can track where patients are seen, but lack clinical detail. Linking routine data systems with clinical registry data offers one way to gain a more complete picture of the patient journey through a cancer care episode. However, valid analytical approaches to evaluating care trajectories must account for the dynamic nature of the EHR population, longitudinality of the data, and careful classification of cancer-related encounters. This study aims to better understand treatment location decisions among women with breast cancer who are seen at more than one healthcare facility, and highlights challenges associated with analyzing linked routine data sources.

Background: The OncoShare database combines clinical detail from the California Cancer Registry with EHR data from two large healthcare facilities in the same catchment area—a multisite community practice and an academic medical center—for all women treated for breast cancer from 2000-2012. A total of 11,716 women received diagnostic services or treatment related to their breast cancer from either of the two medical centers, 16% of whom received treatment at both institutions during the follow-up time. Preliminary cross-sectional analyses reveal that these women had comparable prognostic factors, but far more diagnostic and treatment interventions than those treated at only one facility. Accounting for the longitudinality of the EHR data reveals that the complexity of the patient journey and length of the care episode may account for some of the apparent differences in service utilization.

Findings: We review analytical strategies, descriptive statistics and results from longitudinal modeling to characterize treatment trajectories and define predictors of treatment facility decisions. We present key findings on identifiable predictors of facility decisions, especially as they relate to women who are seen at both facilities.

Lessons Learned: Linking EHR data from multiple neighboring healthcare systems can provide a rich source of information on patient journeys through cancer care episodes, but careful consideration of the complexity of the treatment process is necessary to make valid inferences about treatment trajectories. Longitudinal electronic medical records offer a rich source of data to begin to identify predictors of patient decisions.

Conclusion: If properly analyzed as a timeline, and with careful characterization of diagnostic tests, surgical interventions, and type and frequency of physician encounters, the “journeys” of women through their breast cancer episode may inform specific aspects of the complex patient decision process.