Only 33.5% of patients with ACP documentation somewhere in the EHR had an SD. Standardizing the location of these documents should become a priority to improve care. Actions are needed to eliminate disparities.

Older adults are at greater risk of developing conditions that affect health outcomes, quality of life, and costs of care. Screening for geriatric conditions such as memory loss, fall risk, and depression may contribute to the prevention of adverse physical and mental comorbidities, unnecessary hospitalizations, and premature nursing home admissions. Because screening is not consistently performed in primary care settings, a shared medical appointment (SMA) program was developed to fill this gap in care. The goals of the program were to improve early identification of at-risk individuals and ensure appropriate follow-up for memory loss, fall risk, and depression; facilitate discussion about prevention, diagnosis, and treatment of these conditions; implement strategies to reduce risks for these conditions; and increase access to screening and expand preventive health services for older adults. Between August 2011 and May 2013, 136 individuals aged 60 and older participated in the program. Three case studies highlighting the psychosocial and physiological findings of participation in the program are presented. Preliminary data suggest that SMAs are an effective model of regularly screening at-risk older adults that augments primary care practice by facilitating early detection and referral for syndromes that may otherwise be missed or delayed.

Background/Aims: Advanced Care planning is becoming a major public health concern. The ambulatory care setting is a new frontier for delivery of palliative care services. Understanding patients' preferences and documenting them in an accessible location can facilitate honoring patients' wishes. However, physicians document Advanced Health Care Directives (AHCD) in various locations within EpicCare EHR, including progress notes, scanned documents, and the problem list. The aim of the study is to identify the locations of AHCD decision documentations in the EHR. Methods: Extensive search of AHCD terms in EPIC EHR, e.g., Physician Orders for Life-Sustaining Treatments (POLST), living will, and power of attorney, using 10 years of EHR data (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) (45,240/76,887) were >= 65 at the time of their first AHCD documentation. About 57% (44,067/76,887) were female. About 90% (5,689/6,347) of patients who died had their first AHCD decision documented within 5 years of their death. Documentation was updated nearing death -90% (3,594/3,989) of patients who died and had more than one documented decision had their last decision documented within a year of death. Discussion: Most AHCD decisions are in progress notes in the EHR which can be difficult to access for busy physicians. Physicians' effort to elicit patient preferences for AHCD and subsequent decisions may be wasted if these decisions cannot be readily found in the EHR in actionable formats. Scanned documents containing signatures of the patient, surrogate, and if applicable, the physician, may be more actionable than text in progress notes without proper signatures and flagging. Standardizing the location of these important decisions needs to become a priority. , using an electronic medical record with an online patient access feature, which includes: appointment requests, results review, medication list, refill request, problem list, care instructions, and email communication with their healthcare providers. We collected administrative data for health plan utilization documented in the EMR for patients 12 months before and after the activation of their online access and for a matched cohort of patients without online access. The analytic data set included those with and without online access matched on propensity scores within a 5% range based on age, gender, and co-morbidity within baseline visit and year strata. Results: The propensity matched cohorts (N = 51,535; in each cohort) contained 54.2% females, an average age of 43.7 years, 6.9% were less than age 20, 36.2% ages 20-39, 43.3% ages 40-59, and 13.7% ages 60 and over. Eighty-six percent of the cohort had none of four chronic illnesses, 7.4% with asthma, 5.7% with diabetes, 1.5% with coronary artery disease, and 1% with