Informed consent in refractive surgery: in-person vs telemedicine approach.

Purpose:The aim of this study was to compare the quality of consent process in refractive surgery between patients who had a preoperative consent discussion with the surgeon using a telemedicine approach and those who had a face-to-face discussion. Methods:Patients treated between January and December 2017 (8,184 laser vision correction [LVC] and 3,754 refractive lens exchange [RLE] patients) that attended day 1 and 1-month postoperative visit were retrospectively reviewed. Preoperative consent preparation included a consultation with an optometrist, observation of an educational video, and written information. Patients then selected either a face-to-face appointment with their surgeon (in-clinic group) or a telemedicine appointment (remote group) for their consent discussion, according to their preference. Patient experience questionnaire and clinical data were included in a multivariate model to explore factors associated with consent quality. Results:Prior to surgery, 80.1% of LVC and 47.9% of RLE patients selected remote consent. Of all LVC patients, 97.5% of in-clinic and 98.3% of remote patients responded that they were adequately consented for surgery (P=0.04). Similar percentages in the RLE group were 97.6% for in-clinic and 97.9% for remote patients (P=0.47). In a multivariate model, the major predictor of patient's satisfaction with the consent process was postoperative satisfaction with visual acuity, responsible for 80.4% of variance explained by the model. Other significant contributors were postoperative visual phenomena and dry eyes, difficulty with night driving, close-up and distance vision, postoperative uncorrected distance visual acuity, change in corrected distance visual acuity, and satisfaction with the surgeon's approach. The type of consent (remote or in-clinic) had no impact on patient's perception of consent quality in the regression model. Conclusion:The majority of patients opted for telemedicine-assisted consent. Those who chose it were equally satisfied as those who had a face-to-face meeting with their surgeon. Dissatisfaction with surgical outcome was the major factor affecting patient's perception of consent quality, regardless of the method of their consent

Information Management for Tactical Decision-making in the Cardiac Care Process

Siirretty Doriast

Learning Tasks for Multitask Learning: Heterogenous Patient Populations in the ICU

Machine learning approaches have been effective in predicting adverse outcomes in different clinical settings. These models are often developed and evaluated on datasets with heterogeneous patient populations. However, good predictive performance on the aggregate population does not imply good performance for specific groups. In this work, we present a two-step framework to 1) learn relevant patient subgroups, and 2) predict an outcome for separate patient populations in a multi-task framework, where each population is a separate task. We demonstrate how to discover relevant groups in an unsupervised way with a sequence-to-sequence autoencoder. We show that using these groups in a multi-task framework leads to better predictive performance of in-hospital mortality both across groups and overall. We also highlight the need for more granular evaluation of performance when dealing with heterogeneous populations.Comment: KDD 201

Patient Acuity as a Predictor of Length of Hospital Stay and Discharge Disposition After Open Colorectal Surgery

Major areas of concern within the US healthcare system today include the quality and cost of healthcare. Open colorectal surgery patients have a higher prevalence of prolonged length of hospital stay (LOS) than most other types of surgery patients and are likely to be discharged to home care or other healthcare settings (DHCS), both of which contribute to increased costs. The ability to predict which patients are at risk for these outcomes early after open colorectal surgery could prompt nursing interventions aimed at improving quality of care and reducing healthcare costs. Radwin and Fawcett’s Refined Quality Health Outcomes Model served as the conceptual framework for this study. In this retrospective cross sectional study of adult open colorectal surgery patients (N=789), nursing documentation in the electronic health record (EHR) was reused to examine the relationships among patient acuity, LOS, and discharge disposition (DD). At the large Midwest healthcare system where this study took place, a patient acuity software system generated real-time patient acuity scores from discrete nursing assessment data fields in the EHR. This information was being used by unit nurse managers to guide nurse staffing decisions. Patient data were stratified by three discharge diagnostic-related groups (DRG) for colorectal surgeries, DRG 329, 330, and 331, to provide some control for comorbidities and post-operative complications. Multiple regression analysis for each DRG examined how patient acuity and select patient characteristics predicted prolonged LOS. Findings included that having a high patient acuity score on Day 2 or 3 after open colorectal surgery was a significant predictor of prolonged LOS for subjects in each DRG (DRG 329: B=1.985, p\u3c0.05; DRG 330: B=1.956, p\u3c0.01; DRG 331: B=0.967, p\u3c0.01). Logistic regression analysis results also indicated that high patient acuity scores on Day 2 or 3 after surgery significantly predicted DHCS for each DRG (DRG 329: OR=3.65, 95% CI [1.39, 9.59], p\u3c0.05; DRG 330: OR=2.86, 95% CI [1.58, 5.16], p\u3c0.01; DRG 331: OR=8.62, 95% CI [2.04, 39.48], p\u3c0.05). Implications for nursing include the need for further research to examine the use of patient acuity information to support evidence-based clinical decision making to improve healthcare quality and contain costs