Influencing outcomes with automated time zero for sepsis through statistical validation and process improvement.

BACKGROUND: Sepsis is a life threating complication of infection acquired by more than 1.5 million people in the United State annually. Each year, sepsis claims the lives of at least 250,000 people. Real-time, automated surveillance for sepsis among hospitalized patients is of critical importance, given that one in three people who die in hospitals have sepsis. The early identification and treatment of sepsis is associated with reduced mortality and costly intensive care bed days. The objective of this analysis was to improve the performance of an electronic medical record based sepsis algorithm (early identification) and improve evidence based bundle compliance (early intervention) with the addition of a real-time, automated time zero calculation. METHODS: Data from our enterprise-wide health information systems were landed in a data lake platform and was used to statistically validate existing sepsis algorithms. An additional algorithm calculating time zero was introduced and a post-hoc comparison of measures of test performance, alert timing, bundle compliance, ICU length of stay, and all-hospital mortality were performed. RESULTS: A total of 55,918 alerts for sepsis were generated over the one-year study period across 30 inpatient facilities. The addition of an automated time zero algorithm improved several key indicators including superior positive predictive value (37% to 52%), enhanced timing of the alert (79% occurred within six hours, 77% within the critical 180-minute SEP-1 window, 47% within an hour of time zero), a 14% increase in bundle compliance, a 10% reduction in ICU length of stay, and a decrease in mortality from sepsis. CONCLUSIONS: The addition of a real-time, automated sepsis time zero calculation improved the performance and timeliness of a predictive sepsis alert provided through a system developed mobile application for clinicians and administrators. KEYWORDS: Sepsis; validation studies; decision making; computer assisted.

Qualitative Descriptive Methods in Health Science Research.

OBJECTIVE: The purpose of this methodology paper is to describe an approach to qualitative design known as qualitative descriptive that is well suited to junior health sciences researchers because it can be used with a variety of theoretical approaches, sampling techniques, and data collection strategies. BACKGROUND: It is often difficult for junior qualitative researchers to pull together the tools and resources they need to embark on a high-quality qualitative research study and to manage the volumes of data they collect during qualitative studies. This paper seeks to pull together much needed resources and provide an overview of methods. METHODS: A step-by-step guide to planning a qualitative descriptive study and analyzing the data is provided, utilizing exemplars from the authors' research. RESULTS: This paper presents steps to conducting a qualitative descriptive study under the following headings: describing the qualitative descriptive approach, designing a qualitative descriptive study, steps to data analysis, and ensuring rigor of findings. CONCLUSIONS: The qualitative descriptive approach results in a summary in everyday, factual language that facilitates understanding of a selected phenomenon across disciplines of health science researchers.

Cost analysis of a home-based nurse care coordination program.

OBJECTIVES: To determine whether a home-based care coordination program focused on medication self-management would affect the cost of care to the Medicare program and whether the addition of technology, a medication-dispensing machine, would further reduce cost. DESIGN: Randomized, controlled, three-arm longitudinal study. SETTING: Participant homes in a large Midwestern urban area. PARTICIPANTS: Older adults identified as having difficulty managing their medications at discharge from Medicare Home Health Care (N = 414). INTERVENTION: A team consisting of advanced practice nurses (APNs) and registered nurses (RNs) coordinated care for two groups: home-based nurse care coordination (NCC) plus a pill organizer group and NCC plus a medication-dispensing machine group. MEASUREMENTS: To measure cost, participant claims data from 2005 to 2011 were retrieved from Medicare Part A and B Standard Analytical Files. RESULTS: Ordinary least squares regression with covariate adjustment was used to estimate monthly dollar savings. Total Medicare costs were $447 per month lower in the NCC plus pill organizer group (P = .11) than in a control group that received usual care. For participants in the study at least 3 months, total Medicare costs were $491 lower per month in the NCC plus pill organizer group (P = .06) than in the control group. The cost of the NCC plus pill organizer intervention was $151 per month, yielding a net savings of $296 per month or $3,552 per year. The cost of the NCC plus medication-dispensing machine intervention was $251 per month, and total Medicare costs were $409 higher per month than in the NCC plus pill organizer group. CONCLUSION: Nurse care coordination plus a pill organizer is a cost-effective intervention for frail elderly Medicare beneficiaries. The addition of the medication machine did not enhance the cost effectiveness of the intervention.