Risk Factors for Hospitalization of Home Hospice Enrollees Development and Validation of a Predictive Tool.

BACKGROUND: Over 10% of hospice patients experience at least 1 care transition 6 months prior to death. Transitions at the end of life, particularly from hospice to hospital, result in burdensome and fragmented care for patients and families. Little is known about factors that predict hospitalization in this population. OBJECTIVES: To develop and validate a model predictive of hospitalization after enrollment into home hospice using prehospice admission risk factors. DESIGN: Retrospective cohort study using Medicare fee-for-service claims. PARTICIPANTS: Patients enrolled into the Medicare hospice benefit were ≥18 years old in 2012. OUTCOME MEASURED: Hospitalization within 2 days from a hospice discharge. RESULTS: We developed a predictive model using 61 947 hospice enrollments, of which 3347 (5.4%) underwent a hospitalization. Seven variables were associated with hospitalization: age 18 to 55 years old (adjusted odds ratio [95% confidence interval]: 2.94 [2.41-3.59]), black race (2.13 [1.93-2.34]), east region (1.97 [1.73-2.24]), a noncancer diagnosis (1.32 [1.21-1.45]), 4 or more chronic conditions (8.11 [7.19-9.14]), 2 or more prior hospice enrollments (1.75 [1.35-2.26]), and enrollment in a not-for-profit hospice (2.01 [1.86-2.18]). A risk scoring tool ranging from 0 to 29 was developed, and a cutoff score of 18 identified hospitalized patients with a positive predictive value of 22%. CONCLUSIONS: Reasons for hospitalization among home hospice patients are complex. Patients who are younger, belong to a minority group, and have a greater number of chronic conditions are at increased odds of hospitalization. Our newly developed predictive tool identifies patients at risk for hospitalization and can serve as a benchmark for future model development.

Physician specialty and variations in adoption of electronic health records.

OBJECTIVE: Efforts to promote adoption of electronic health records (EHRs) have focused on primary care physicians, who are now expected to exchange data electronically with other providers, including specialists. However, the variation of EHR adoption among specialists is underexplored. METHODS: We conducted a retrospective cross-sectional study to determine the association between physician specialty and the prevalence of EHR adoption, and a retrospective serial cross-sectional study to determine the association of physician specialty and the rate of EHR adoption over time. We used the 2005-2009 National Ambulatory Medical Care Survey. We considered fourteen specialties, and four definitions of EHR adoption (any EHR, basic EHR, full EHR, and a novel definition of EHR sophistication). We used multivariable logistic regression, and adjusted for several covariates (geography, practice characteristics, revenue characteristics, physician degree). RESULTS: Physician specialty was significantly associated with EHR adoption, regardless of the EHR definition, after adjusting for covariates. Psychiatrists, dermatologists, pediatricians, ophthalmologists, and general surgeons were significantly less likely to adopt EHRs, compared to the reference group of family medicine/general practitioners. After adjustment for covariates, these specialties were 44-94% less likely to adopt EHRs than the reference group. EHR adoption increased in all specialties, by approximately 40% per year. The rate of EHR adoption over time did not significantly vary by specialty. CONCLUSIONS: Although EHR adoption is increasing in all specialties, adoption varies widely by specialty. In order to insure each individual's network of providers can electronically share data, widespread adoption of EHRs is needed across all specialties.

Anatomy reports on the internet: a web-based tool for student reports on cadaveric findings.

The difference between the idealization of anatomy atlases and the reality of human cadavers often frustrates gross anatomy students. To encourage students to celebrate rather than protest these differences, we describe a web site ARI (Anatomy Reports on the Internet) that allows students to document cadaveric findings online with photographs and text. We used several web languages for site construction, including mysql, php, html, and javascript. Faculty tools allow instructors to upload digital images of the structures, add relevant commentary, view and delete images, review submitted reports, and examine database statistics. Student tools allow dissection groups to choose and comment on images, enter and edit reports, and read reports submitted by other students. During the first two years of the site's use (2000-2001, 2002-2003), every dissection group at our institution submitted at least one report. Technical support requests were minimal.