Assessing Hospital Resource Utilization with Application to Imaging for Patients Diagnosed with Prostate Cancer
Resource utilization measures are typically modeled by relying on clinical characteristics. However, in some settings, those clinical markers are not available, and hospitals are unable to explore potential inefficiencies or resource misutilization. We propose a novel approach to exploring misutiliz...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-01-01
|
| Series: | Healthcare |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-9032/10/2/248 |
| _version_ | 1797479749221613568 |
|---|---|
| author | Yazmine Lunn Rudra Patel Timothy S. Sokphat Laura Bourn Khalil Fields Anna Fitzgerald Vandana Sundaresan Greeshma Thomas Michael Korvink Laura H. Gunn |
| author_facet | Yazmine Lunn Rudra Patel Timothy S. Sokphat Laura Bourn Khalil Fields Anna Fitzgerald Vandana Sundaresan Greeshma Thomas Michael Korvink Laura H. Gunn |
| author_sort | Yazmine Lunn |
| collection | DOAJ |
| description | Resource utilization measures are typically modeled by relying on clinical characteristics. However, in some settings, those clinical markers are not available, and hospitals are unable to explore potential inefficiencies or resource misutilization. We propose a novel approach to exploring misutilization that solely relies on administrative data in the form of patient characteristics and competing resource utilization, with the latter being a novel addition. We demonstrate this approach in a 2019 patient cohort diagnosed with prostate cancer (<i>n</i> = 51,111) across 1056 U.S. healthcare facilities using Premier, Inc.’s (Charlotte, NC, USA) all payor databases. A multivariate logistic regression model was fitted using administrative information and competing resources utilization. A decision curve analysis informed by industry average standards of utilization allows for a definition of misutilization with regards to these industry standards. Odds ratios were extracted at the patient level to demonstrate differences in misutilization by patient characteristics, such as race; Black individuals experienced higher under-utilization compared to White individuals (<i>p</i> < 0.0001). Volume-adjusted Poisson rate regression models allow for the identification and ranking of facilities with large departures in utilization. The proposed approach is scalable and easily generalizable to other diseases and resources and can be complemented with clinical information from electronic health record information, when available. |
| first_indexed | 2024-03-09T21:50:16Z |
| format | Article |
| id | doaj.art-d1381dfdf9ab45d6bdb9003a29ab6356 |
| institution | Directory Open Access Journal |
| issn | 2227-9032 |
| language | English |
| last_indexed | 2024-03-09T21:50:16Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Healthcare |
| spelling | doaj.art-d1381dfdf9ab45d6bdb9003a29ab63562023-11-23T20:08:50ZengMDPI AGHealthcare2227-90322022-01-0110224810.3390/healthcare10020248Assessing Hospital Resource Utilization with Application to Imaging for Patients Diagnosed with Prostate CancerYazmine Lunn0Rudra Patel1Timothy S. Sokphat2Laura Bourn3Khalil Fields4Anna Fitzgerald5Vandana Sundaresan6Greeshma Thomas7Michael Korvink8Laura H. Gunn9School of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USASchool of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USASchool of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USASchool of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USASchool of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USASchool of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USASchool of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USADepartment of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USAITS Data Science, Premier, Inc., Charlotte, NC 28277, USASchool of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USAResource utilization measures are typically modeled by relying on clinical characteristics. However, in some settings, those clinical markers are not available, and hospitals are unable to explore potential inefficiencies or resource misutilization. We propose a novel approach to exploring misutilization that solely relies on administrative data in the form of patient characteristics and competing resource utilization, with the latter being a novel addition. We demonstrate this approach in a 2019 patient cohort diagnosed with prostate cancer (<i>n</i> = 51,111) across 1056 U.S. healthcare facilities using Premier, Inc.’s (Charlotte, NC, USA) all payor databases. A multivariate logistic regression model was fitted using administrative information and competing resources utilization. A decision curve analysis informed by industry average standards of utilization allows for a definition of misutilization with regards to these industry standards. Odds ratios were extracted at the patient level to demonstrate differences in misutilization by patient characteristics, such as race; Black individuals experienced higher under-utilization compared to White individuals (<i>p</i> < 0.0001). Volume-adjusted Poisson rate regression models allow for the identification and ranking of facilities with large departures in utilization. The proposed approach is scalable and easily generalizable to other diseases and resources and can be complemented with clinical information from electronic health record information, when available.https://www.mdpi.com/2227-9032/10/2/248resource utilizationmisutilizationmedical imagingprostate cancerrisk adjustment |
| spellingShingle | Yazmine Lunn Rudra Patel Timothy S. Sokphat Laura Bourn Khalil Fields Anna Fitzgerald Vandana Sundaresan Greeshma Thomas Michael Korvink Laura H. Gunn Assessing Hospital Resource Utilization with Application to Imaging for Patients Diagnosed with Prostate Cancer Healthcare resource utilization misutilization medical imaging prostate cancer risk adjustment |
| title | Assessing Hospital Resource Utilization with Application to Imaging for Patients Diagnosed with Prostate Cancer |
| title_full | Assessing Hospital Resource Utilization with Application to Imaging for Patients Diagnosed with Prostate Cancer |
| title_fullStr | Assessing Hospital Resource Utilization with Application to Imaging for Patients Diagnosed with Prostate Cancer |
| title_full_unstemmed | Assessing Hospital Resource Utilization with Application to Imaging for Patients Diagnosed with Prostate Cancer |
| title_short | Assessing Hospital Resource Utilization with Application to Imaging for Patients Diagnosed with Prostate Cancer |
| title_sort | assessing hospital resource utilization with application to imaging for patients diagnosed with prostate cancer |
| topic | resource utilization misutilization medical imaging prostate cancer risk adjustment |
| url | https://www.mdpi.com/2227-9032/10/2/248 |
| work_keys_str_mv | AT yazminelunn assessinghospitalresourceutilizationwithapplicationtoimagingforpatientsdiagnosedwithprostatecancer AT rudrapatel assessinghospitalresourceutilizationwithapplicationtoimagingforpatientsdiagnosedwithprostatecancer AT timothyssokphat assessinghospitalresourceutilizationwithapplicationtoimagingforpatientsdiagnosedwithprostatecancer AT laurabourn assessinghospitalresourceutilizationwithapplicationtoimagingforpatientsdiagnosedwithprostatecancer AT khalilfields assessinghospitalresourceutilizationwithapplicationtoimagingforpatientsdiagnosedwithprostatecancer AT annafitzgerald assessinghospitalresourceutilizationwithapplicationtoimagingforpatientsdiagnosedwithprostatecancer AT vandanasundaresan assessinghospitalresourceutilizationwithapplicationtoimagingforpatientsdiagnosedwithprostatecancer AT greeshmathomas assessinghospitalresourceutilizationwithapplicationtoimagingforpatientsdiagnosedwithprostatecancer AT michaelkorvink assessinghospitalresourceutilizationwithapplicationtoimagingforpatientsdiagnosedwithprostatecancer AT laurahgunn assessinghospitalresourceutilizationwithapplicationtoimagingforpatientsdiagnosedwithprostatecancer |