The authors (1) compare visit length across four categories of skilled nursing home health visits which reflect recent changes in home health casemix-AIDS-related, hospice/terminal (HT), intravenous (IV) therapy, and maternal and child health (MCH)-with general adult medical/surgical (MS) visits and (2) identify factors influencing visit length.Methods.
The study sites were 12 nonproprietary Massachusetts home health agencies (HHAs). Staff nurses collected data concurrently on a sample of visits they provided between December 1, 1992 and November 30, 1993. The visits were stratified by agency, time of year, and visit category. The authors used analysis of variance to test for significant differences across visit categories in Home Length of Visit (the number of minutes between when the nurse entered and left the home) (HLOV). The authors used multivariate regression analysis to develop models identifying determinants of HLOV and adjusted R2 to measure the explanatory power of partial models.Results.
In univariate analysis, the categories differed significantly from each other in length (P < 0.0001). HT visits were the longest (median visit length = 60, 80, and 59 minutes for HT Only visits, visits in both the HT and AIDS categories (HT/AIDS), and HT/IV visits, respectively). MS visits were the shortest (median = 30 minutes). The remaining categories were intermediate in length (medians = 37 to 50 minutes). Almost half the variability in HLOV was explained by the full multivariate regression model, which includes all independent variables (adjusted R2 = .4486; P < 0.0001). Visit characteristics alone in a partial model explained 18% of the variability in HLOV. Three other variable sub-groups-agency, client characteristics, and nursing workload-each explained about 15% of the variability in HLOV. Nursing activities performed during the visit explained 11%; several of these related to teaching, education, or assessment.Conclusions.
Accurate reimbursement reflecting casemix differences is important to protect the teaching, education, and assessment functions of nurses; measure nurse productivity and allocate caseloads; maintain access to services for clients with greater needs; and avoid creating economic disincentives to the agencies that serve them. Payers formulating prospective payment systems can adjust per visit reimbursement rates to reflect differences in visit length by category and incorporate functional limitations, clinical instability, and case coordination as classification variables. Developers of home health casemix systems can use factor analysis to improve the robustness of multivariate models and include nursing workload in predicting visit length. Home health agencies measuring productivity and caseload across complex client populations can classify visits into three groups-MS; HT; and AIDS, IV, and MCH-or use the regression results to develop more refined predictors of visit length and nursing caseload.