Computational health economics for identification of unprofitable health care enrollees.

Rose, Sherri; Bergquist, Savannah L; Layton, Timothy J

Rose, Sherri; Bergquist, Savannah L; Layton, Timothy J.

Affiliation

Rose S; Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA, 02115, USA.
Bergquist SL; Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA, 02115, USA.
Layton TJ; Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA, 02115, USA.

Biostatistics ; 18(4): 682-694, 2017 Oct 01.

Article in En | MEDLINE | ID: mdl-28369273

Subject(s)

Drug Prescriptions/economics; Formularies as Topic/standards; Health Insurance Exchanges/economics; Insurance, Pharmaceutical Services/economics; Machine Learning; Algorithms; Humans

Key words

Classification and prediction; Ensembles; Machine learning; Statistical methods in health economics; Variable selection

Fulltext

Add to My VHL

XML

PubMed Links

Search on Google

Full text: 1 Database: MEDLINE Main subject: Drug Prescriptions / Health Insurance Exchanges / Machine Learning / Formularies as Topic / Insurance, Pharmaceutical Services Type of study: Diagnostic_studies / Health_economic_evaluation / Prognostic_studies Limits: Humans Language: En Journal: Biostatistics Year: 2017 Type: Article Affiliation country: United States

Fulltext

Add to My VHL

XML

PubMed Links

Search on Google