Two important review papers are out this week (state of the art) and deserve mention in the blog. They both dovetail nicely, and serve as bookends in our approach to readmission management.
Assessing discharge recidivism rates is dicey at best, and given the state of evidence, again, we are called upon to correct a systemic problem—one with multiple causes—with unsatisfactory tools. This frustrates not just hospitalists, but the health system at large given the uneven progress in improving this metric.
If we cannot predict who will return to the hospital, or choose proper interventions, performance ranking and penalties are premature. A recurring theme, the same concern exists with standardized mortality ratios (SMR). Moreover, if there is any doubt as to assessments in that realm, this citation is sobering. The horse has left the barn however; we are stuck, and resistance is futile.
Casting wide nets (“bundles of services”) is the best available salve to tackle the problem currently. Effective? Yes. Efficicent? No.
Hospitals will spend needlessly and target resources unproductively. If the benefits of reducing readmissions outweigh the lost opportunity cost of directing valued dollars elsewhere, the system wins. If not, the system loses. Knowing the arrival of new data will take time, establishing how hospitals should implement bundles, in what dose, and the components, is the next trying step.
The JAMA citation examined the performance of risk prediction models. Many were only slightly better than a coin toss: (c statistic ranges: 0.5-0.6). The money summary:
[…]Nevertheless, the poor discriminative ability of most of the administrative models we examined raises concerns about the ability to standardize risk across hospitals to fairly compare hospital performance. Until risk prediction and risk adjustment become more accurate, it seems inappropriate to compare hospitals in this way and reimburse (or penalize) them on the basis of risk-standardized readmission rates.[…]
[…]In summary, readmission risk prediction is a complex endeavor with many inherent limitations. Most models created to date, whether for hospital comparison or clinical purposes, have poor predictive ability. Although in certain settings such models may prove useful, better approaches are needed to assess hospital performance in discharging patients, as well as to identify patients at greater risk of avoidable readmission.
The Annals study looked at trials examining interventions to reduce admission rates. The investigators used the following taxonomy, and another summary statement follows:
“[…] Given the paucity of high-quality trials evaluating various interventions to reduce 30-day readmissions (for example, we found only 4 randomized, controlled trials enrolling >400 participants) and the impending hospital reimbursement penalty for excess rehospitalization, additional patient-centered outcomes research on remedies for avoidable rehospitalization and characteristics of successful implementation is clearly needed. Although rehospitalization represents a large burden to patients and the health care system, the current evidence base may not be adequate to facilitate change even for highly incentivized hospitals, and reconsideration of planned penalties may be reasonable.[…]”
Given difficulties with administrative data, and the intangibles contributing to readmission beyond the control of hospital personnel, I suspect institutions will take gratuitous hits. Only In hindsight, we will untangle the mess.
That is not to say low hanging fruit cant be harvested. It can. However, like diabetic control, the hospitals at a HbA1C readmit level of 9 need to activate—and quickly. However, once at 7.7 (equivalent readmit rate of ~17-18%, my dimension), where many hospitals hover, progressing further will be grueling. Regrettably, we do not have the means in the near to moderate term to collectively subordinate them. Only nameless or unmeasured variables prevail in that ambit.
Call back in five years. Sorry, that is all I can say.
UPDATE: Short, but on target commentary in this weeks JAMA (10-25-11) discussing access to hospital services and associated risk of readmission. Ironically, more home care, more affluence, etc., may increase the chance of readmission, whereas lower economic status may decrease it. The converse is also possible: less resources equal more ER presentations. Again, this is not easy to disentangle, mainly, goings on outside hospital walls and attribution of recurrent hospital stays.