Effects of patients' hospital discharge preferences on uptake of clinical decision support.

The Centers for Medicare and Medicaid Services identified unplanned hospital readmissions as a critical healthcare quality and cost problem. Improvements in hospital discharge decision-making and post-discharge care are needed to address the problem. Utilization of clinical decision support (CDS) can improve discharge decision-making but little is known about the empirical significance of two opposing problems that can occur: (1) negligible uptake of CDS by providers or (2) over-reliance on CDS and underuse of other information. This paper reports an experiment where, in addition to electronic medical records (EMR), clinical decision-makers are provided subjective reports by standardized patients, or CDS information, or both. Subjective information, reports of being eager or reluctant for discharge, was obtained during examinations of standardized patients, who are regularly employed in medical education, and in our experiment had been given scripts for the experimental treatments. The CDS tool presents discharge recommendations obtained from econometric analysis of data from de-identified EMR of hospital patients. 38 clinical decision-makers in the experiment, who were third and fourth year medical students, discharged eight simulated patient encounters with an average length of stay 8.1 in the CDS supported group and 8.8 days in the control group. When the recommendation was "Discharge," CDS uptake of "Discharge" recommendation was 20% higher for eager than reluctant patients. Compared to discharge decisions in the absence of patient reports: (i) odds of discharging reluctant standardized patients were 67% lower in the CDS-assisted group and 40% lower in the control (no-CDS) group; whereas (ii) odds of discharging eager standardized patients were 75% higher in the control group and similar in CDS-assisted group. These findings indicate that participants were neither ignoring nor over-relying on CDS.

Patient selection in the presence of regulatory oversight based on healthcare report cards of providers: the case of organ transplantation.

Many healthcare report cards provide information to consumers but do not represent a constraint on the behavior of healthcare providers. This is not the case with the report cards utilized in kidney transplantation. These report cards became more salient and binding, with additional oversight, in 2007 under the Centers for Medicare and Medicaid Services Conditions of Participation. This research investigates whether the additional oversight based on report card outcomes influences patient selection via waiting-list registrations at transplant centers that meet regulatory standards. Using data from a national registry of kidney transplant candidates from 2003 through 2010, we apply a before-and-after estimation strategy that isolates the impact of a binding report card. A sorting equilibrium model is employed to account for center-level heterogeneity and the presence of congestion/agglomeration effects and the results are compared to a conditional logit specification. Our results indicate that patient waiting-list registrations change in response to the quality information similarly on average if there is additional regulation or not. We also find evidence of congestion effects when spatial choice sets are smaller: new patient registrations are less likely to occur at a center with a long waiting list when fewer options are available.

Can we increase organ donation by reducing the disincentives? An experimental analysis.

Our research utilizes the experimental economics laboratory to investigate the impact that reducing disincentives has on organ donation. The experiment consists of four treatments across different levels of donation related costs, which reflect the disincentives associated with being an organ donor. Our experimental results indicate that sizable increases in the organ donation rate are achievable if we reduce the level of disincentives present. The largest observed donation rates arise when a financial return is offered for being an organ donor, which is prohibited under the National Organ Transplant Act (NOTA), but nearly 80% of the gains observed under the positive financial incentives can be achieved if all of the disincentives are eliminated.

Discharge decision-making after complex surgery: Surgeon behaviors compared to predictive modeling to reduce surgical readmissions.

BACKGROUND: Little is known about how information available at discharge affects decision-making and its effect on readmission. We sought to define the association between information used for discharge and patients' subsequent risk of readmission. METHODS: 2009-2014 patients from a tertiary academic medical center's surgical services were analyzed using a time-to-event model to identify criteria that statistically explained the timing of discharges. The data were subsequently used to develop a time-varying prediction model of unplanned hospital readmissions. These models were validated and statistically compared. RESULTS: The predictive discharge and readmission regression models were generated from a database of 20,970 patients totaling 115,976 patient-days with 1,565 readmissions (7.5%). 22 daily clinical measures were significant in both regression models. Both models demonstrated good discrimination (C statistic = 0.8 for all models). Comparison of discharge behaviors versus the predictive readmission model suggested important discordance with certain clinical measures (e.g., demographics, laboratory values) not being accounted for to optimize discharges. CONCLUSIONS: Decision-support tools for discharge may utilize variables that are not routinely considered by healthcare providers. How providers will then respond to these atypical findings may affect implementation.

Higher Quality and Lower Cost from Improving Hospital Discharge Decision Making.

This paper reports research on improving decisions about hospital discharges - decisions that are now made by physicians based on mainly subjective evaluations of patients' discharge status. We report an experiment on uptake of our clinical decision support software (CDSS) which presents physicians with evidence-based discharge criteria that can be effectively utilized at the point of care where the discharge decision is made. One experimental treatment we report prompts physician attentiveness to the CDSS by replacing the default option of universal "opt in" to patient discharge with the alternative default option of "opt out" from the CDSS recommendations to discharge or not to discharge the patient on each day of hospital stay. We also report results from experimental treatments that implement the CDSS under varying conditions of time pressure on the subjects. The experiment was conducted using resident physicians and fourth-year medical students at a university medical school as subjects.

Incentivizing Cost-Effective Reductions in Hospital Readmission Rates.

The recent regulatory changes enacted by the Centers for Medicare and Medicaid Services (CMS) have identified hospital readmission rates as a critical healthcare quality metric. This research focuses on the utilization of pay-for-performance (P4P) mechanisms to cost effectively reduce hospital readmission rates and meet the regulatory standards set by CMS. Using the experimental economics laboratory we find that both of the P4P mechanisms researched, bonus and bundled payments, cost-effectively meet the performance criteria set forth by CMS. The bundled payment mechanism generates the largest reduction in patient length of stay (LOS) without altering the probability of readmission. Combined these results indicate that utilizing P4P mechanisms incentivizes cost effective reductions in hospital readmission rates.

The fishery performance indicators: a management tool for triple bottom line outcomes.

Pursuit of the triple bottom line of economic, community and ecological sustainability has increased the complexity of fishery management; fisheries assessments require new types of data and analysis to guide science-based policy in addition to traditional biological information and modeling. We introduce the Fishery Performance Indicators (FPIs), a broadly applicable and flexible tool for assessing performance in individual fisheries, and for establishing cross-sectional links between enabling conditions, management strategies and triple bottom line outcomes. Conceptually separating measures of performance, the FPIs use 68 individual outcome metrics--coded on a 1 to 5 scale based on expert assessment to facilitate application to data poor fisheries and sectors--that can be partitioned into sector-based or triple-bottom-line sustainability-based interpretative indicators. Variation among outcomes is explained with 54 similarly structured metrics of inputs, management approaches and enabling conditions. Using 61 initial fishery case studies drawn from industrial and developing countries around the world, we demonstrate the inferential importance of tracking economic and community outcomes, in addition to resource status.

Increasing organ donation via changes in the default choice or allocation rule.

This research utilizes a laboratory experiment to evaluate the effectiveness of alternative public policies targeted at increasing the rate of deceased donor organ donation. The experiment includes treatments across different default choices and organ allocation rules inspired by the donor registration systems applied in different countries. Our results indicate that the opt-out with priority rule system generates the largest increase in organ donation relative to an opt-in only program. However, sizeable gains are achievable using either a priority rule or opt-out program separately, with the opt-out rule generating approximately 80% of the benefits achieved under a priority rule program.

Assessing clinical discharge data preferences among practicing surgeons.

BACKGROUND: It is believed that many postoperative patient readmissions can be curbed via optimization of a patient's discharge from hospital, but little is known about how surgeons make the decision to discharge a patient. This study explored the criteria that surgeons preferentially value in their discharge decision-making process. MATERIALS AND METHODS: All surgical faculty and residents at a U.S. academic medical center were surveyed about the relative importance of specific criteria regularly used to make a discharge decision. Demographic and professional information was collected about each surgeon as well. A Kruskal-Wallis and Fisher's exact test were used to describe one-way analysis of variance between groupings of surgeons. Ordered logit regressions were used to analyze variations across multiple subgroups. Factor analysis was used to further characterize statistically relevant groupings of criteria. RESULTS: In total, 88 (49%) of the invited surgeons responded to the survey. Respondents reported statistically less reliance on common Laboratory tests and Patient demographics when making discharge decisions preferring Vital signs, Perioperative factors, and Functional criteria. Surgeon-specific factors that influenced discharge criteria preferences included years of clinical education and gender. Factor analysis further identified subtle variations in preferences for specific criteria groupings based on clinical education, gender, and race. CONCLUSIONS: Surgeons use a wide range of clinical data when making discharge decisions. Typical measures of patient condition also appear to be used heterogeneously with a preference for binary rather than continuous measures. Further understanding the nature of these preferences may suggest novel ways of presenting discharge-relevant information to clinical decision makers to optimize discharge outcomes.

Risk factors for 30-day hospital readmission among general surgery patients.

BACKGROUND: Hospital readmission within 30 days of an index hospitalization is receiving increased scrutiny as a marker of poor-quality patient care. This study identifies factors associated with 30-day readmission after general surgery procedures. STUDY DESIGN: Using standard National Surgical Quality Improvement Project protocol, preoperative, intraoperative, and postoperative outcomes were collected on patients undergoing inpatient general surgery procedures at a single academic center between 2009 and 2011. Data were merged with our institutional clinical data warehouse to identify unplanned 30-day readmissions. Demographics, comorbidities, type of procedure, postoperative complications, and ICD-9 coding data were reviewed for patients who were readmitted. Univariate and multivariate analysis was used to identify risk factors associated with 30-day readmission. RESULTS: One thousand four hundred and forty-two general surgery patients were reviewed. One hundred and sixty-three (11.3%) were readmitted within 30 days of discharge. The most common reasons for readmission were gastrointestinal problem/complication (27.6%), surgical infection (22.1%), and failure to thrive/malnutrition (10.4%). Comorbidities associated with risk of readmission included disseminated cancer, dyspnea, and preoperative open wound (p < 0.05 for all variables). Surgical procedures associated with higher rates of readmission included pancreatectomy, colectomy, and liver resection. Postoperative occurrences leading to increased risk of readmission were blood transfusion, postoperative pulmonary complication, wound complication, sepsis/shock, urinary tract infection, and vascular complications. Multivariable analysis demonstrates that the most significant independent risk factor for readmission is the occurrence of any postoperative complication (odds ratio = 4.20; 95% CI, 2.89-6.13). CONCLUSIONS: Risk factors for readmission after general surgery procedures are multifactorial, however, postoperative complications appear to drive readmissions in surgical patients. Taking appropriate steps to minimize postoperative complications will decrease postoperative readmissions.