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The American Journal of Managed Care June 2019
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Association of Decision Support for Hospital Discharge Disposition With Outcomes
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Association of Decision Support for Hospital Discharge Disposition With Outcomes

Winthrop F. Whitcomb, MD; Joseph E. Lucas, PhD; Rachel Tornheim, MBA; Jennifer L. Chiu, MPH; and Peter Hayward, PhD
The use of clinical decision support for hospital discharge disposition was associated with a reduction in spending and readmissions without negatively affecting emergency department use.
Tested Versus Untested

The second analysis consisted of tested versus untested cases. Tested cases received the CDS tool, whereas untested cases did not receive the CDS tool. This was an ITT analysis, examining outcomes independent of whether the CDS tool recommendation was followed. This analysis reflects the expectation that the decision of discharge disposition is based on a merging of clinical expertise and the CDS tool recommendation, with responsibility for the final decision resting with the discharge planning team and patient/caregiver.

We acknowledge that in actual use, providers may not apply the CDS tool to all patients, nor do we expect that everyone in the population will receive the test. Therefore, we used a propensity model to estimate the ATT, or the effect of the test on the outcome of those who received it.

Federal common rule28 provides an exemption from institutional review board requirements when the purpose is to study, evaluate, or otherwise examine a public benefit or a service program—in this case, CMS’ BPCI program. The contractor signed a data use agreement stating that all data were securely and solely used for the purposes of this study.

RESULTS

In general, compared with patients found to be discordant, those who were concordant were about 1 year younger, had shorter lengths of stay, were less likely to be women, were less likely to be dual enrolled, and had lower rates of major complications. Concordant patients were also less likely to be sent to home health agencies and postacute facilities and were more likely to go home (Table 1). Adjustment for differences in concordant versus discordant patients using IPW resulted in the 2 groups being similar in all categories (eAppendix Table 1A [eAppendix available at ajmc.com]).

There were 148,385 patients in the sample in total. Of the 15,887 who received CDS, 10,218 were CDS concordant and 5669 were CDS discordant. Of the latter group, 2066 were discharged to a less intense level of care than what the CDS proposed and 3603 were discharged to a more intense level of care (Figure 1).

Episode spending was $860 less (95% CI, $162-$1558; P = .016), 90-day readmissions were lower (adjusted odds ratio [OR], 0.920; 95% CI, 0.850-0.995; P = .038), and ED use was unchanged (adjusted OR, 0.990; 95% CI, 0.882-1.110; P = .858) for concordant compared with discordant cases (Figure 2). A post hoc analysis, controlling for the hospital as a main effect, showed episode spending to be $934 less (95% CI, $247-$1621; P = .008), 90-day readmissions lower (adjusted OR, 0.916; 95% CI, 0.846-0.992; P = .031), and ED use unchanged (adjusted OR, 0.997; 95% CI, 0.887-1.120; P = .957) for concordant versus discordant cases.

More Intense and Less Intense Levels of Care

When concordant cases were compared with discordant cases discharged to more intense levels of care, concordance was associated with decreased spending ($4802; 95% CI, $3896-$5709; P <.001), decreased readmission rates (adjusted OR, 0.834; 95% CI, 0.757-0.920; P <.001), and unchanged ED use (adjusted OR, 0.956; 95% CI, 0.832-1.096; P = .517). Results of the adjusted analysis of concordant versus discordant cases discharged to less intense care suggest that concordance was more expensive ($6417; 95% CI, $5551-$7283; P <.001), with no changes in readmission rates (adjusted OR, 1.086; 95% CI, 0.951-1.240; P = .222) or ED use (adjusted OR, 1.086; 95% CI, 0.893-1.319; P = .410) (Figure 3).

Disposition to Home, Home Health Agency, and Postacute Facility

Recommended rates for disposition to home, home health agency, and postacute facility were 41.5%, 29.6%, and 28.9%, respectively, whereas actual disposition rates among the tested population were 40.8%, 20.6%, and 38.7% (Table 2). Compared with actual, the CDS tool recommended fewer patients be sent to a postacute facility and more patients be sent to a home health agency than was observed. Approximately the same proportion of patients were sent home (40.8%) as were recommended (41.5%). Conversely, more patients received a recommendation to go to a home health agency (29.6%) than was observed (20.6%), and fewer received a postacute facility recommendation (28.9%) than was observed (38.7%). The overall rate of concordance with the CDS recommendation was 64%. Table 2 shows the numbers of patients for each combination of disposition and recommendation.

Tested Versus Untested Populations and Outcomes

Overall, there was no difference in age between the tested and untested populations. However, the tested were less likely to be white, were more likely to be female, had longer lengths of stay, and had higher rates of dual enrollment. See eAppendix Table 1B for the rate of testing split across a selection of demographic variables.

The IPW-adjusted ITT analysis showed decreased spending among those tested, but it was not statistically significant ($221 savings; 95% CI, –$115 to $557; P = .198). There was also no difference among those tested in ED use (adjusted OR, 0.959; 95% CI, 0.908-1.012; P = .128) or readmission rates (adjusted OR, 1.004; 95% CI, 0.966-1.043; P = .840) (see the eAppendix Figure).


 
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