Appointment Pathways: Yield Management via Cause-and-Effect Modeling in the Outpatient Setting at Mayo Clinic.
Patients have multiple outpatient appointments for various reasons. Analyzing patients' related appointments provides insight into referral patterns, leading to recommendations for ideal care and more efficient planning. We model these appointments with causal graphs via Judea Pearl's causal graph a...
| Publicado en: | Journal of Ambulatory Care Management Vol. 46; no. 4; pp. 298 - 306 |
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| Autores principales: | , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Lippincott Williams & Wilkins
Oct-Dec2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=172389882&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 172389882 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01489917 0NV jtl: Journal of Ambulatory Care Management issn: 01489917 maglogo: N pubinfo: dt: Oct-Dec2023 vid: 46 iid: 4 pid: 5086 pub: Lippincott Williams & Wilkins place: Baltimore, Maryland artinfo: ui: 172389882 172389882 172389882 10.1097/JAC.0000000000000473 172389882 ppf: 298 ppct: 8 formats: tig: atl: Appointment Pathways: Yield Management via Cause-and-Effect Modeling in the Outpatient Setting at Mayo Clinic. aug: au: Keister, Adrian C. Munden, Derek R. Bailey, Brian S. affil: Reporting and Analytics, Enterprise Office of Access Management, Mayo Clinic, Rochester, Minnesota sug: subj: Appointments and Schedules Outpatient Service Decision Making Referral and Consultation Human Graphical User Interface Brainstorming Causal Attribution Data Analysis Software Algorithms Causality Leaders Personnel Staffing and Scheduling Health Care Delivery, Integrated Computer Hardware ab: Patients have multiple outpatient appointments for various reasons. Analyzing patients' related appointments provides insight into referral patterns, leading to recommendations for ideal care and more efficient planning. We model these appointments with causal graphs via Judea Pearl's causal graph approach. Once we define the causal relationships in the appointment data, we leverage a graph database and visualization software to investigate valuable patterns and relationships in patient care over time. The Pathways tool allows yield management at specialty, provider, or appointment levels. Leaders use this tool to anticipate a patient's downstream appointments; the tool provides insights into staffing and the impact of growing demand. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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