Identifying Potentially Avoidable Hospitalizations in Medicare Patients With Prostate Cancer: A Retrospective Analysis

Autor: William H. Smith, Kavita V. Dharmarajan, Anish B. Parikh, Ronald D. Ennis, Mark Liu, Luis Isola, Mark Sanderson
Rok vydání: 2019
Předmět:
Zdroj: Journal of Oncology Practice. 15:e187-e194
ISSN: 1935-469X
1554-7477
DOI: 10.1200/jop.18.00560
Popis: PURPOSE: If identifiable, potentially avoidable hospitalizations (PAHs) can serve as an important target for cost containment efforts in oncology. METHODS: PAHs among a cohort of Medicare patients with prostate cancer were identified using a two-stage consensus-driven review process. In stage 1, two clinicians independently evaluated admissions records using a case review form, which we modified from a previous study to assess for PAHs. In stage 2, any admissions that the reviewers disagreed on or were unsure of were re-examined in a larger group of clinicians to yield a consensus determination regarding avoidability. Univariable and multivariable regression analyses were performed to identify factors predictive of PAH. RESULTS: There were 160 admissions among this cohort of 210 patients from January 2012 to June 2015, of which 99 were evaluable. Consensus-driven clinical review yielded an overall PAH rate of 28.3%. Factors associated with increased PAH risk were admission for symptoms related to cancer (odds ratio [OR], 7.33; P < .001), presence of a social contributor to admission (OR, 4.40; P = .014), and history of alcohol or drug abuse (OR, 4.93; P = .025). Admission for a noncancer condition was associated with decreased PAH risk (OR, 0.32; P = .011). On multivariable analysis, presence of a social contributor to admission (OR, 9.35; P = .002) and admission as a result of a noncancer condition (OR, 0.16; P = .038) remained predictive of PAH risk. CONCLUSION: A significant proportion of hospitalizations among patients with prostate cancer are potentially avoidable. Understanding factors predictive of risk for PAH can help inform programs aimed at avoiding such admissions to improve overall care quality and value.
Databáze: OpenAIRE