How Should Risk Adjustment Data Be Collected?
Risk adjustment has broad general application and is a key part of the Patient Protection and Affordable Care Act (ACA). Yet, little has been written on how data required to support risk adjustment should be collected. This paper offers analytical support for a distributed approach, in which insurer...
| Publicado en: | Inquiry (00469580) Vol. 49; no. 2; pp. 127 - 141 |
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| Autor principal: | |
| Formato: | research tables/charts Journal Article |
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Sage Publications Inc.
Summer2012
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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=78429787&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 78429787 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00469580 INQ jtl: Inquiry (00469580) issn: 00469580 maglogo: Y pubinfo: dt: Summer2012 vid: 49 iid: 2 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 78429787 104490502 104490502 10.5034/inquiryjrnl_49.02.08 78429787 ppf: 127 ppct: 14 formats: fmt: @attributes: type: P tig: atl: How Should Risk Adjustment Data Be Collected? aug: au: Kessler, Daniel P. affil: Professor, Law School and Graduate School of Business, senior fellow, Hoover Institution, Stanford University sug: subj: Theory Construction Risk Management Methods Patient Protection and Affordable Care Act Data Collection Methods Insurance Carriers Statistics and Numerical Data Decentralization Human Funding Source Billing and Claims Statistics and Numerical Data Data Analysis, Statistical Methods Calibration Database Construction Methods Selection Bias Linear Regression Comparative Studies Database Quality Privacy and Confidentiality Cost Savings Health Information Networks Validation Studies Audit ab: Risk adjustment has broad general application and is a key part of the Patient Protection and Affordable Care Act (ACA). Yet, little has been written on how data required to support risk adjustment should be collected. This paper offers analytical support for a distributed approach, in which insurers retain possession of claims but pass on summary statistics to the risk adjustment authority as needed. It shows that distributed approaches function as well as or better than centralized ones-where insurers submit raw claims data to the risk adjustment authority-in terms of the goals of risk adjustment. In particular, it shows how distributed data analysis can be used to calibrate risk adjustment models and calculate payments, both in theory and in practice-drawing on the experience of distributed models in other contexts. In addition, it explains how distributed methods support other goals of the ACA, and can support projects requiring data aggregation more generally. It concludes that states should seriously consider distributed methods to implement their risk adjustment programs. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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