Archive for December, 2019

It only took 15 months and 3 revisions, but the paper

Papadopoulos, A and Roland B. Stark (2019). “Does Home Health Care increase the probability of 30-day hospital re-admissions? Interpreting coefficient sign reversals, or their absence, in binary logistic regression analysis”.

has now been accepted for publication in The American Statistician

…and is now (Dec 17, 2019) on-line at https://doi.org/10.1080/00031305.2019.1704873

The paper is very light on technical stuff, but heavy on concepts. The abstract reads : Data for 30-day readmission rates in American hospitals often show that patients that receive Home Health Care (HHC) have a higher probability of being readmitted to hospital than those that did not receive such services, but it is expected that when control variables are included in a regression we will obtain a “sign reversal” of the treatment effect. We map the real-world situation to the binary logistic regression model, and we construct a counterfactual probability metric that leads to necessary and sufficient conditions for the sign reversal to occur, conditions that show that logistic regression is an appropriate tool for this research purpose. This metric also permits us to obtain evidence related to the criteria used to assign HHC treatment. We examine seven data samples from different USA hospitals for the period 2011-2017. We find that in all cases the provision of HHC increased the probability of readmission of the treated patients. This casts doubt on the appropriateness of the 30-day readmission rate as an indicator of hospital performance and a criterion for hospital reimbursement, as it is currently used for Medicare patients.

The main contributions of the paper can be distilled down to the following two: first, we show how the familiar binary logistic regression model can be reliably used to glean information as to whether assignment of Home Health Care (HHC) treatment, to patients that are discharged form the hospital, depends positively on the seriousness of their health status, or not (in which case we would have statistical evidence that administrators go for an “easy win” by assigning HHC to less needy patients).

Second, we provide the theoretical framework to explain an ongoing “puzzle” in Healthcare, that HHC appears to increase the probability of hospital readmissions, even after risk-adjustment: in other words, we explain why the statement “Home Health Care is beneficial to the health of patients and it increases their probability of hospital readmission” is not a contradiction in terms.