Incidence, Prediction, and Causes of Unplanned 30-Day Hospital Admission After Ambulatory Procedures

Anesthesia and Analgesia - Tập 131 Số 2 - Trang 497-507 - 2020
Bijan Teja1, Dana Raub1,2, Sabine Friedrich1,2, Paul Rostin1,2, Maria D. Patrocínio1, Jeffrey C Schneider3, Changyu Shen4, Gabriel A. Brat5, Timothy T. Houle2, Robert W. Yeh6,4, Matthias Eikermann1,7
1Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
2Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
3Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, Massachusetts
4Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology
5Department of Surgery
6Cardiology Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
7Klinik für Anästhesiologie und Intensivmedizin, Universitätsklinikum Essen, Essen, Germany

Tóm tắt

BACKGROUND: Unanticipated hospital admission is regarded as a measure of adverse perioperative patient care. However, previously published studies for risk prediction after ambulatory procedures are sparse compared to those examining readmission after inpatient surgery. We aimed to evaluate the incidence and reasons for unplanned admission after ambulatory surgery and develop a prediction tool for preoperative risk assessment. METHODS: This retrospective cohort study included adult patients undergoing ambulatory, noncardiac procedures under anesthesia care at 2 tertiary care centers in Massachusetts, United States, between 2007 and 2017 as well as all hospitals and ambulatory surgery centers in New York State, United States, in 2014. The primary outcome was unplanned hospital admission within 30 days after discharge. We created a prediction tool (the PREdicting admission after Outpatient Procedures [PREOP] score) using stepwise backward regression analysis to predict unplanned hospital admission, based on criteria used by the Centers for Medicare & Medicaid Services, within 30 days after surgery in the Massachusetts hospital network registry. Model predictors included patient demographics, comorbidities, and procedural factors. We validated the score externally in the New York state registry. Reasons for unplanned admission were assessed. RESULTS: A total of 170,983 patients were included in the Massachusetts hospital network registry and 1,232,788 in the New York state registry. Among those, the observed rate of unplanned admission was 2.0% (3504) and 1.7% (20,622), respectively. The prediction model showed good discrimination in the training set with C-statistic of 0.77 (95% confidence interval [CI], 0.77–0.78) and satisfactory discrimination in the validation set with C-statistic of 0.71 (95% CI, 0.70–0.71). The risk of unplanned admission varied widely from 0.4% (95% CI, 0.3–0.4) among patients whose calculated PREOP scores were in the first percentile to 21.3% (95% CI, 20.0–22.5) among patients whose scores were in the 99th percentile. Predictions were well calibrated with an overall ratio of observed-to-expected events of 99.97% (95% CI, 96.3–103.6) in the training and 92.6% (95% CI, 88.8–96.4) in the external validation set. Unplanned admissions were most often related to malignancy, nonsurgical site infections, and surgical complications. CONCLUSIONS: We present an instrument for prediction of unplanned 30-day admission after ambulatory procedures under anesthesia care validated in a statewide cohort comprising academic and nonacademic hospitals as well as ambulatory surgery centers. The instrument may be useful in identifying patients at high risk for 30-day unplanned hospital admission and may be used for benchmarking hospitals, ambulatory surgery centers, and practitioners.

Từ khóa


Tài liệu tham khảo

Blakey, 2017, What is the experience of being readmitted to hospital for people 65 years and over? A review of the literature., Contemp Nurse, 53, 698, 10.1080/10376178.2018.1439395

Donaghy, 2018, Unplanned early hospital readmission among critical care survivors: a mixed methods study of patients and carers., BMJ Qual Saf, 27, 915, 10.1136/bmjqs-2017-007513

McCarty, 2005, Optimizing outcomes in bariatric surgery: outpatient laparoscopic gastric bypass., Ann Surg, 242, 494, 10.1097/01.sla.0000183354.66073.4c

Twersky, 1997, What happens after discharge? Return hospital visits after ambulatory surgery., Anesth Analg, 84, 319, 10.1213/00000539-199702000-00014

Fortier, 1998, Unanticipated admission after ambulatory surgery—a prospective study., Can J Anaesth, 45, 612, 10.1007/BF03012088

Elsamadicy, 2018, Drivers and risk factors of unplanned 30-day readmission following spinal cord stimulator implantation., Neuromodulation, 21, 87, 10.1111/ner.12689

Bhattacharyya, 2014, Unplanned revisits and readmissions after ambulatory sinonasal surgery., Laryngoscope, 124, 1983, 10.1002/lary.24584

Mioton, 2014, Predictors of readmission after outpatient plastic surgery., Plast Reconstr Surg, 133, 173, 10.1097/01.prs.0000436833.11442.8d

Fleisher, 2004, Inpatient hospital admission and death after outpatient surgery in elderly patients: importance of patient and system characteristics and location of care., Arch Surg, 139, 67, 10.1001/archsurg.139.1.67

Shin, 2017, Development and validation of a Score for Preoperative Prediction of Obstructive Sleep Apnea (SPOSA) and its perioperative outcomes., BMC Anesthesiol, 17, 71, 10.1186/s12871-017-0361-z

1988, Prediction of the first variceal hemorrhage in patients with cirrhosis of the liver and esophageal varices. A prospective multicenter study., N Engl J Med, 319, 983, 10.1056/NEJM198810133191505

Longstreth, 1983, Prediction of awakening after out-of-hospital cardiac arrest., N Engl J Med, 308, 1378, 10.1056/NEJM198306093082302

Picard, 1984, Cross-validation of regression models., J Am Stat Assoc, 79, 575, 10.1080/01621459.1984.10478083

Brier, 1950, Verification of forecasts expressed in terms of probability., Mon Weather Rev, 78, 1, 10.1175/1520-0493(1950)078<0001:VOFEIT>2.0.CO;2

DeLong, 1988, Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach., Biometrics, 44, 837, 10.2307/2531595

Dalton, 2011, Development and validation of a risk quantification index for 30-day postoperative mortality and morbidity in noncardiac surgical patients., Anesthesiology, 114, 1336, 10.1097/ALN.0b013e318219d5f9

Shinall, 2020, Association of preoperative patient frailty and operative stress with postoperative mortality., JAMA Surg, 155, e194620, 10.1001/jamasurg.2019.4620

Donato, 2017, Unplanned readmission in outpatient hand surgery: an analysis of 23,613 patients in the NSQIP data set., Eplasty, 17, e36

Zuckerman, 2016, Readmissions, observation, and the hospital readmissions reduction program., N Engl J Med, 374, 1543, 10.1056/NEJMsa1513024

Hall, 2017, Ambulatory surgery data from hospitals and ambulatory surgery centers: United States, 2010., Natl Health Stat Report, 1

McPhee, 2013, Risk prediction of 30-day readmission after infrainguinal bypass for critical limb ischemia., J Vasc Surg, 57, 1481, 10.1016/j.jvs.2012.11.074

Merkow, 2015, Underlying reasons associated with hospital readmission following surgery in the United States., JAMA, 313, 483, 10.1001/jama.2014.18614

Graham, 2018, Preventability of early versus late hospital readmissions in a national cohort of general medicine patients., Ann Intern Med, 168, 766, 10.7326/M17-1724

Doran, 2012, Questionable safety of thyroid surgery with same day discharge., Ann R Coll Surg Engl, 94, 543, 10.1308/003588412X13373405384576

Kansagara, 2011, Risk prediction models for hospital readmission: a systematic review., JAMA, 306, 1688, 10.1001/jama.2011.1515

Lucas, 2013, Assessing readmission after general, vascular, and thoracic surgery using ACS-NSQIP., Ann Surg, 258, 430, 10.1097/SLA.0b013e3182a18fcc

Baltodano, 2016, A validated, risk assessment tool for predicting readmission after open ventral hernia repair., Hernia, 20, 119, 10.1007/s10029-015-1413-2

Lukannek, 2019, The development and validation of the Score for the Prediction of Postoperative Respiratory Complications (SPORC-2) to predict the requirement for early postoperative tracheal re-intubation: a hospital registry study., Anaesthesia, 74, 1165, 10.1111/anae.14742

Brueckmann, 2013, Development and validation of a score for prediction of postoperative respiratory complications., Anesthesiology, 118, 1276, 10.1097/ALN.0b013e318293065c

2017, Federal Register., 82, 19796

McAlister, 2004, Multidisciplinary strategies for the management of heart failure patients at high risk for admission: a systematic review of randomized trials., J Am Coll Cardiol, 44, 810

Bourbeau, 2003, Reduction of hospital utilization in patients with chronic obstructive pulmonary disease: a disease-specific self-management intervention., Arch Intern Med, 163, 585, 10.1001/archinte.163.5.585

Jack, 2011, Perioperative exercise training in elderly subjects., Best Pract Res Clin Anaesthesiol, 25, 461, 10.1016/j.bpa.2011.07.003

Friedman, 2004, Ambulatory surgery adult patient selection criteria— a survey of Canadian anesthesiologists., Can J Anesth, 51, 437, 10.1007/BF03018305