Implementation of a Real-Time Documentation Assistance Tool: Automated Diagnosis (AutoDx).

BACKGROUND: Clinical documentation improvement programs are utilized by most health care systems to enhance provider documentation. Suggestions are sent to providers in a variety of ways, and are commonly referred to as coding queries. Responding to these coding queries can require significant provider time and do not often align with workflows. To enhance provider documentation in a more consistent manner without creating undue burden, alternative strategies are required. OBJECTIVES: The aim of this study is to evaluate the impact of a real-time documentation assistance tool, named AutoDx, on the volume of coding queries and encounter-level outcome metrics, including case-mix index (CMI). METHODS: The AutoDx tool was developed utilizing tools existing within the electronic health record, and is based on the generation of messages when clinical conditions are met. These messages appear within provider notes and required little to no interaction. Initial diagnoses included in the tool were electrolyte deficiencies, obesity, and malnutrition. The tool was piloted in a cohort of Hospital Medicine providers, then expanded to the Neuro Intensive Care Unit (NICU), with addition diagnoses being added. RESULTS: The initial Hospital Medicine implementation evaluation included 590 encounters pre- and 531 post-implementation. The volume of coding queries decreased 57% (p < 0.0001) for the targeted diagnoses compared with 6% (p = 0.77) in other high-volume diagnoses. In the NICU cohort, 829 encounters pre-implementation were compared with 680 post. The proportion of AutoDx coding queries compared with all other coding queries decreased from 54.9 to 37.1% (p < 0.0001). During the same period, CMI demonstrated a significant increase post-implementation (4.00 vs. 4.55, p = 0.02). CONCLUSION: The real-time documentation assistance tool led to a significant decrease in coding queries for targeted diagnoses in two unique provider cohorts. This improvement was also associated with a significant increase in CMI during the implementation time period.

Impact of the COVID-19 Public Health Crisis and a Structured COVID Unit on Physician Behaviors in Code Status Ordering.

Purpose: Code status orders are standard practice impacting end-of-life care for individuals. This study reviews the impact of a COVID unit on physician behaviors towards goal-concordant end-of-life care at an urban academic tertiary-care hospital. Methods: We conducted a retrospective cohort study of code status ordering on adult inpatients comparing the pre-pandemic period to patients who tested positive, negative and were not tested during the pandemic from January 1, 2019, to December 31, 2020. Results: We analyzed 59,471 unique patient encounters (n = 35,317 pre-pandemic and n = 24,154 during). 1,631 cases of COVID-19 were seen. The rate of code status orders among all inpatients increased from 22% pre-pandemic to 29% during the pandemic (P < .001). Code status orders increased for both patients who were COVID-negative (32% P < .001) and COVID-positive (65% P < .001). Being in a cohorted COVID unit increased code status ordering by an odds of 4.79 (P < .001). Compared to the pre-pandemic cohort, the COVID-positive cohort is less female (50% to 56% P < .001), more Black (66% to 61% P < .001), more Hispanic (6.5% to 5%) and less white (26% to 30% P < .001). Compared to Black patients, white patients had lower odds (.86) of code status ordering (P < .001). Other race/ethnicity categories were not significant. Conclusions: Code status ordering remains low. Compared to pre-pandemic rates, the frequency of orders placed significantly increased for all patients during the pandemic. The largest increase occurred in patients with COVID-19. This increase likely occurred due to protocols in the COVID unit and disease uncertainty.

Attitudes and Behaviors with Diabetes Technology Use in the Hospital: Multicenter Survey Study in the United States.

Objective: To assess the attitudes, behaviors, and barriers with diabetes technology use in the general medicine hospital wards. Research Design and Methods: The authors developed a nonincentivized web-based anonymous survey that captured demographic and practice data regarding continuous subcutaneous insulin infusion (CSII) and continuous glucose monitor (CGM) use in the hospital. Setting: Four large hospital systems in the United States. Results: Among 128 survey respondents, 76%, 10%, and 6% were hospitalists, advanced practice providers, and primary care physicians, respectively. The majority of respondents rated the treatment of inpatient hyperglycemia (96%) and the continuation of CSII during the hospital stay (93%) "important." While most respondents (64%) acknowledged knowing the existence of their institution's policies for CSII use, only 84% of those respondents felt somewhat to very familiar with the policy. The most common barrier to CSII use in the inpatient setting was lack of practitioner (70%) and nursing (67%) knowledge of using the device. With regard to CGM use in the hospital, a minority (28%) of respondents were aware of their institution's CGM policies. Less than half of the providers, 43.8%, stated that, when admitting a patient, they reviewed CGM data to guide insulin dosing. Conclusions: In this US multicenter survey, we found that most inpatient practitioners valued glycemic control, but many were not familiar with institutional policies, had lack of knowledge with CSII, and were not reviewing CGM data.

Fast track dialysis: Improving emergency department and hospital throughput for patients requiring hemodialysis.

OBJECTIVE: To describe the impact of a novel communication and triage pathway called fast track dialysis (FTD) on the length of stay (LOS), resource utilization, and charges for unscheduled hemodialysis for end stage renal disease (ESRD) patients presenting to the emergency department (ED). METHODS: Prospective and retrospective cohorts of ESRD patients meeting requirements of routine or urgent hemodialysis at a tertiary academic hospital from September 25th, 2016 to September 25th, 2018 in 1 year cohorts. Two sample t-tests were used to compare most outcomes of the cohorts with a Mann-Whitney U test used for skewed data. Nephrology group outcomes were analyzed by two-way ANOVA and Kruskal-Wallis and chi-square tests. RESULTS: There were 98 encounters in the historical cohort and 143 encounters in the fast track dialysis cohort. FTD had significantly lowered median ED LOS (4.05 h, vs 5.3 h, p < 0.001), median hospital LOS (12.8 h vs 27 h, p < 0.001), time to hemodialysis (4.78 h vs 7.29 h, p < 0.001), and median hospital charges ($26,040 vs $30,747, p < 0.016). The FTD cohort had increased 30 day ED return for each encounter compared to the historical cohort (1.85 visits vs 0.73 visits, p < 0.001), however no significant increase in 1 year ED visits (6.52 visits vs 5.80, p = 0.4589) or 1 year readmissions (5.89 readmissions vs 4.81 readmissions, p = 0.3584). Most nephrology groups had significantly lower time to hemodialysis order placement and time to start hemodialysis. CONCLUSION: A multidisciplinary approach with key stakeholders using a standard pathway can lead to improved efficiency in throughput, reduced charges, and hospital resource utilization for patients needing urgent or routine hemodialysis. A study with a dedicated geographic observation unit for protocolized short stay patients including conditions ranging from low risk chest pain to transient ischemic events that incorporates FTD patients under this protocol should be considered.

Incorporating Continuity in a 7-On 7-Off Hospitalist Model and the Correlation With Patient Handoffs and Length of Stay.

Little research in hospital medicine examines the effects of hospitalist continuity on patient outcomes. This study implemented a novel staffing model with approximately half of rounding teams starting their 7-day workweek on Monday and the others on Friday. Teams admitted their own patients on their first 4 days with additional nighttime admissions handed off to those teams. No admissions were given to teams on their last 3 days. Length of stay was significantly reduced from 6.34 days in 2015 to 5.7 days in 2016 (P < .002) with a significant decrease in handoffs. There was an increase in odds ratio of death (1.37, SE = .128) with each additional hospitalist involved in a patient's care while adjusting for year and number of patient diagnoses (P < .001). There was no statistical difference in charges, 30-day readmissions, or mortality between years.