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.
Background: During the COVID-19 pandemic, prioritization of care and utilization of scarce resources are daily considerations in healthcare systems that have never experienced these issues before. Elective surgical cases have been largely postponed, and surgery departments are struggling to correctly and equitably determine which cases need to proceed. A resource to objectively prioritize and track time sensitive cases would be useful as an adjunct to clinical decision-making. Methods: A multidisciplinary working group at Emory Healthcare developed and implemented an adjudication tool for the prioritization of time sensitive surgeries. The variables identified by the team to form the construct focused on the patient’s survivability according to actuarial data, potential impact on function with delay in care, and high-level biology of disease. Implementation of the prioritization was accomplished with a database design to streamline needed communication between surgeons and surgical adjudicators. All patients who underwent time sensitive surgery between 4/10/20 and 6/15/20 across 5 campuses were included. Results: The primary outcomes of interest were calculated patient prioritization score and number of days until operation. 1767 cases were adjudicated during the specified time period. The distribution of prioritization scores was normal, such that real-time adjustment of the empiric algorithm was not required. On retrospective review, as the patient prioritization score increased, the number of days to the operating room decreased. This confirmed the functionality of the tool and provided a framework for organization across multiple campuses. Conclusions: We developed an in-house adjudication tool to aid in the prioritization of a large cohort of canceled and time sensitive surgeries. The tool is relatively simple in its design, reproducible, and data driven which allows for an objective adjunct to clinical decision-making. The database design was instrumental in communication optimization during this chaotic period for patients and surgeons.
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.
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 system (CDSS) which presents physicians with evidence-based discharge criteria that can be effectively applied 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.
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 KruskaleWallis 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 oncommon Laboratory tests and Patient demographicswhen 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.
Hospital readmission rates have assumed a central position in the discussion of critical health care quality metrics for American hospitals. This primarily was triggered by the passage of the Patient Protection and Affordable Care Act in October 2010.1 Contained within this piece of legislation is §3025, the Hospital Readmissions Reduction Program. Under this provision, hospitals with a high rate of 30-day readmissions for Medicare patients with pneumonia, myocardial infarction, or congestive heart failure will be penalized with decreased Medicare payments for all Medicare discharges. The Affordable Care Act was challenged for being unconstitutional, but in the summer of 2012, the Supreme Court upheld the law and shortly thereafter the Centers for Medicare & Medicaid Services announced the prospective penalties for hospitals with excess 30-day readmissions that would be in effect in October 2012.2 The scheduled penalties escalate in future years and will apply to broader classes of conditions including patients undergoing surgical procedures.
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 following General Surgery procedures.
Study Design: Using standard National Surgical Quality Improvement Project (NSQIP) 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 utilized to identify risk factors associated with 30-day readmission.
Results: 1442 General Surgery patients were reviewed. 163 (11.3%) were readmitted within 30 days of discharge. The most common reasons for readmission were gastrointestinal complaint/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 (OR 4.20, 95% CI 2.89–6.13).
Conclusions: Risk factors for readmission after General Surgery procedures are multi-factorial; however, postoperative complications appear to drive readmissions in surgical patients. Taking appropriate steps to minimize postoperative complications will decrease postoperative readmissions.
Resolution of Type-2 diabetes mellitus (DM) after weight loss surgery is well documented, but the mechanism is elusive. We evaluated the glucose-insulin metabolism of patients undergoing a Roux-en-Y gastric bypass (RYGB) using the intravenous glucose tolerance test (IVGTT) and compared it with patients who underwent laparoscopic adjustable gastric band (AB) placement. Thirty-one female patients (age range, 20 to 50 years; body mass index, 47.2 kg/m2) underwent RYGB. Nine female patients underwent AB placement and served as control subjects. All patients underwent IVGTT at baseline and 1 month and 6 months after surgery. Thirteen patients undergoing RYGB and one patient undergoing AB exhibited impaired glucose tolerance defined by the American Diabetes Association. By 6 months post surgery, diabetes was resolved in all but one patient undergoing RYGB and none of the patients undergoing AB. Patients with diabetes undergoing demonstrated increased insulin secretion and β-cell responsiveness 1 month after surgery and continued this trend up to 6 months, whereas none of the patients undergoing AB had changes in β-cell function. Both patients undergoing RYGB and those undergoing AB demonstrated significant weight loss (34.6 and 35.0 kg/m2, respectively) and improved insulin sensitivity at 6 months. RYGB ameliorates DM resolution in two phases: 1) early augmentation of beta cell function at 1 month; and 2) attenuation of peripheral insulin resistance at 6 months. Patients undergoing AB only exhibited reduction in peripheral insulin resistance at 6 months but no changes in insulin secretion.
As COVID-19 infections soar worldwide, surgical teams must quickly adapt to care for the COVID-19-positive patient in the operating room (OR). This challenge comes in the face of constant change in data and conditions, reliable evidence yet to emerge, shortages of personal protective equipment (PPE), uncertainty due to lack of testing equipment and capacity, and unprecedented strain on caregivers, hospital systems, and resources.
Background: Numerous recent reports describe the performance of laparoscopic procedures through a single incision. Although the feasibility of this approach for a variety of procedures is currently being established, little data are available regarding safety.
Case Report: A 65-year-old female patient who was transferred from an outside institution had undergone a single incision laparoscopic cholecystectomy that resulted in biliary tract and vascular injuries.
Methods: The patient was transferred with a known bile duct injury on the first postoperative day following single incision laparoscopic cholecystectomy. Review of her magnetic resonance imaging and percutaneous transhepatic cholangiogram studies showed a Bismuth type 3 bile duct injury. Hepatic angiogram demonstrated an occlusion of the right hepatic artery with collateralization from the left hepatic artery. She was initially managed conservatively with a right-sided external biliary drain, followed 6 weeks later by a Hepp-Couinaud procedure to reconstruct the biliary tract.
Conclusion: As new techniques evolve, it is imperative that safety, or potential side effects, or both safety and side effects, be monitored, because no learning curve is established for these new techniques. In these initial stages, surgeons should have a low threshold to add additional ports when necessary to ensure that procedures are completed safely.