Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Interprofessional communication with hospitalist and consultant physicians in general internal medicine : a qualitative study

This study helps to improve our understanding of the collaborative environment in GIM, comparing the communication styles and strategies of hospitalist and consultant physicians, as well as the experiences of providers working with them. The implications of this research are globally important for understanding how to create opportunities for physicians and their colleagues to meaningfully and consistently participate in interprofessional communication which has been shown to improve patient, provider, and organizational outcomes

The [Hi]story Lives On: Using OER and Renewable Assignments to Engage Students

Dr. Leslie Lindenauer is Professor of History and Non-Western Cultures at Western Connecticut State University, and Director of the Center for Excellence in Learning and Teaching. Before entering academe, Dr. Lindenauer worked as a museum educator and administrator. Aura Lippincott is Instructional Designer at Western Connecticut State University where she works with faculty across the campus to design engaging and effective courses. As part of the design process she encourages faculty to consider open resources in the selection and design of learning materialsThe presenters redesigned an undergraduate history course to utilize an open history text, and a three-part renewable assignment that approaches topics in American history through storytelling. The presenters will discuss the open-pedagogy approach and will share sample student work, early impressions of student success, and the impacts on student learning

The Early Effects of Medicare's Mandatory Hospital Pay‐for‐Performance Program

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110552/1/hesr12206-sup-0001-AuthorMatrix.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110552/2/hesr12206.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110552/3/hesr12206-sup-0002-DataS1.pd

Pelvic Exenterative Therapy and Recurrent Pelvic Carcinoma1

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135384/1/ijgo00332.pd

Do Hospitals Alter Patient Care Effort Allocations under Pay-for-Performance?

To determine whether hospitals increase efforts on easy tasks relative to difficult tasks to improve scores under pay-for-performance (P4P) incentives.The Centers for Medicare and Medicaid Services Hospital Compare data from Fiscal Years 2003 through 2005 and 2003 American Hospital Association Annual Survey data.We classified measures of process compliance targeted by the Premier Hospital Quality Incentive Demonstration as easy or difficult to improve based on whether they introduce additional per-patient costs. We compared process compliance on easy and difficult tasks at hospitals eligible for P4P bonus payments relative to hospitals engaged in public reporting using random effects regression models.P4P hospitals did not preferentially increase efforts for easy tasks in patients with heart failure or pneumonia, but they did exhibit modestly greater effort on easy tasks for heart attack admissions. There is no systematic evidence that effort was allocated toward easier processes of care and away from more difficult tasks.Despite perverse P4P incentives to change allocation of efforts across tasks to maximize performance scores at lowest cost, we find little evidence that hospitals respond to P4P incentives as hypothesized. Alternative incentive structures may motivate greater response by targeted hospitals.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79380/1/j.1475-6773.2010.01192.x.pd

Guidelines for pre-operative cardiac risk assessment and perioperative cardiac management in non-cardiac surgery : the Task Force for Preoperative Cardiac Risk Assessment and Perioperative Cardiac Management in Non-cardiac Surgery of the European Society of Cardiology (ESC) and endorsed by the European Society of Anaesthesiology (ESA)

Non-cardiac surgery; Pre-operative cardiac risk assessment; Pre-operative cardiac testing; Pre-operative coronary artery revascularization; Perioperative cardiac management; Renal disease; Pulmonary disease; Neurological disease; Anaesthesiology; Post-operative cardiac surveillanc

The association between prior statin usage and long-term outcomes after critical care admission

Background: Statins may have immunomodulatory effects that benefit critically ill patients. Therefore we retrospectively examined the association between survival and the prescription of statins prior to admission to an intensive care unit (ICU), or high dependency unit (HDU), as a result of major elective surgery, or as an emergency with a presumed diagnosis of sepsis. Methods: We retrospectively studied critical care patients (ICU or HDU) from a tertiary referral UK teaching hospital. Nottingham University Hospitals has over 2200 beds, of which 39 are critical care beds. Over a five-year period (2000–2005) 414 patients were identified with a presumed diagnosis of sepsis, and 672 patients were identified with a planned ICU/HDU admission following elective major surgery. Patients prescribed statins prior to hospital admission were compared with those who were not. Demographics, past medical history, drug history, and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores were examined. Univariate and multivariate analyses were applied using the primary endpoint of survival at five years after admission. Results: Patients prescribed statins prior to critical care admission were, on average, older, with higher initial APACHE II scores and more pre-existing comorbidities. Statins were almost invariably stopped following admission to critical care. Statin usage was not associated with significantly altered survival during hospital admission, or at five years, for either patients with sepsis (9% v 15%, P=0.121; 73% v 84%, P=0.503 respectively), or post-operative patients (55% v 58%, P=0.762; 57% v 63%, P=0.390). Conclusions: Prior statin usage was not associated with improved or worsening outcomes in patients admitted to critical care after elective surgical cases or with a presumed diagnosis of sepsis

Canine Aortofemoral Bypass: a New Technique for the Evaluation of Prosthetic Implants

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67957/2/10.1177_000331977402500901.pd