Showing papers by "Kevin J. O'Leary published in 2018"

Hospitalized Patients’ Knowledge of Care: a Systematic Review

Abstract: Patients’ comprehension of their medical conditions is fundamental to patient-centered care. Hospitalizations present opportunities to educate patients but also challenges to patient comprehension given the complexity and rapid pace of clinical care. We conducted a systematic review of the literature to characterize the current state of inpatients’ knowledge of their hospitalization, assess the methods used to determine patient comprehension, and appraise the effects of interventions on improving knowledge. We searched MEDLINE, EMBASE, and the Cochrane Library for articles published from January 1, 1995 through December 11, 2017. Eligible studies included patients under inpatient or observation status on internal medicine, family medicine, or neurology services. We extracted study characteristics (author, year, country, study design, sample size, patient characteristics, methods, intervention, primary endpoints, results) in a standardized fashion. The quality of observational studies was assessed using the NIH Quality Assessment Tool for Observation Cohort and Cross-Sectional Studies and the quality of interventional studies was assessed using adapted EPOC criteria from the Cochrane Collaboration. Twenty-eight studies met the criteria for inclusion, including 17 observational studies and 11 interventional studies. Patient knowledge of all aspects of their hospitalization was poor and patients often overestimated their knowledge. Older patients and those with lower education levels were more likely to have poorer knowledge. Intervention methods varied, but generally showed improvements in patient knowledge. Few interventional studies assessed the effect on health behaviors or outcomes and those that did were often underpowered. Clinicians should be aware that comprehension is often poor among hospitalized patients, especially in those with lower education and advanced age. Our results are limited by overall poor quality of interventional studies. Future research should use objective, standardized measures of patient comprehension and interventions should be multifaceted in approach, focusing on knowledge improvement while also addressing other factors influencing outcomes.

Validation of data from electronic data warehouse in diabetic ketoacidosis: Caution is needed

Abstract: Aims This study validated enterprise data warehouse (EDW) data for a cohort of hospitalized patients with a primary diagnosis of diabetic ketoacidosis (DKA). Methods 247 patients with 319 admissions for DKA (ICD-9 code 250.12, 250.13, or 250.xx with biochemical criteria for DKA) were admitted to Northwestern Memorial Hospital from 1/1/2010 to 9/1/2013. Validation was performed by electronic medical record (EMR) review of 10% of admissions (N = 32). Classification of diabetes type (Type 1 vs. Type 2) and DKA clinical status were compared between the EMR review and EDW data. Results Key findings included incorrect classification of diabetes type in 5 of 32 (16%) admissions and indeterminable classification in 5 admissions. DKA was not present, based on the review, in 11 of 32 (34%) admissions. DKA was not present, based on biochemical criteria, in 15 of 32 (47%) admissions. Conclusions This study found that EDW data have substantial errors. Some discrepancies can be addressed by refining the EDW query code, while others, related to diabetes classification and DKA diagnosis, cannot be corrected without improving clinical coding accuracy, consistency of medical record documentation, or EMR design. These results support the need for comprehensive validation of data for complex clinical populations obtained through data repositories such as the EDW.

Interventions for Frequently Hospitalized Patients and Their Effect on Outcomes: A Systematic Review.

Abstract: BACKGROUND: A small subset of patients account for a substantial proportion of hospital readmissions. Programs to reduce utilization among this subset of frequently hospitalized patients have the potential to improve health and reduce unnecessary spending. PURPOSE: To conduct a systematic review of interventions targeting frequently hospitalized patients. DATA SOURCES: PubMed MEDLINE; Embase (embase.com); and Cochrane Central Register of Controlled Trials, January 1, 1980 to January 1, 2018. STUDY SELECTION: Four physicians screened 4762 titles and abstracts for inclusion. Authors reviewed 116 full-text studies and included 9 meeting criteria. DATA EXTRACTION: Study characteristics, outcomes, and details regarding interventions were extracted. Risk of bias was assessed by the Downs and Black Scale. DATA SYNTHESIS: Out of the nine included studies, three were randomized controlled trials, three were controlled retrospective cohort studies, and three were uncontrolled pre-post studies. Inclusion criteria, interventions used, and outcomes assessed varied across studies. While all nine studies demonstrated reduced utilization, studies with lower risk of bias generally found similar reductions in utilization between intervention and control groups. Interventions commonly consisted of interdisciplinary teams interacting with patients across health care settings. CONCLUSIONS: Interventions targeting high need, high-cost patients are heterogeneous, with many studies observing a regression to the mean. More rigorous studies, using multifaceted interventions which can adapt to patients’ unique needs should be conducted to assess the effect on outcomes relevant to both providers and patients.

Collaboration, Interruptions and Changeover Times: Workflow Model and Empirical Study of Hospitalist Charting

Abstract: Collaboration is important in services, but may lead to interruptions. Professionals exercise discretion on whether to preempt individual tasks to switch to collaborative tasks. Task switching can introduce setup times, often mental and unobservable, when resuming the preempted task and thus can increase workload.We analyze and quantify how collaboration, through interruptions and setup times, affects workload. We introduce an episodal workflow model that captures the interruption dynamics — each switch and the episode of work it preempts — present in settings where collaboration and multitasking is paramount. We then deploy the model in a field study of hospital medicine physicians — “hospitalists.” A hospitalist’s patient-care routine includes visiting patients and consulting with other caregivers to guide patient diagnosis and treatment.A rigorous empirical analysis is presented using a dataset assembled from direct observation of physician activity and pager-log data. We estimate that a hospitalist incurs a total setup time of 5min per patient per day, which represents a significant 20% of the workload: caring for 14 patients per day, a hospitalist spends more than one hour each day on setups. Switches causally lead to longer documentation time in general but the magnitude of the effect depends on the trigger: when the switch is triggered by the hospitalist the setup time is smaller.