Dataset Information

Electronic Health Record Mortality Prediction Model for Targeted Palliative Care Among Hospitalized Medical Patients: a Pilot Quasi-experimental Study.

ABSTRACT: BACKGROUND:Development of electronic health record (EHR) prediction models to improve palliative care delivery is on the rise, yet the clinical impact of such models has not been evaluated. OBJECTIVE:To assess the clinical impact of triggering palliative care using an EHR prediction model. DESIGN:Pilot prospective before-after study on the general medical wards at an urban academic medical center. PARTICIPANTS:Adults with a predicted probability of 6-month mortality of ??0.3. INTERVENTION:Triggered (with opt-out) palliative care consult on hospital day 2. MAIN MEASURES:Frequencies of consults, advance care planning (ACP) documentation, home palliative care and hospice referrals, code status changes, and pre-consult length of stay (LOS). KEY RESULTS:The control and intervention periods included 8 weeks each and 138 admissions and 134 admissions, respectively. Characteristics between the groups were similar, with a mean (standard deviation) risk of 6-month mortality of 0.5 (0.2). Seventy-seven (57%) triggered consults were accepted by the primary team and 8 consults were requested per usual care during the intervention period. Compared to historical controls, consultation increased by 74% (22 [16%] vs 85 [63%], P?

SUBMITTER: Courtright KR

PROVIDER: S-EPMC6712114 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Electronic Health Record Mortality Prediction Model for Targeted Palliative Care Among Hospitalized Medical Patients: a Pilot Quasi-experimental Study.

Courtright Katherine R KR Chivers Corey C Becker Michael M Regli Susan H SH Pepper Linnea C LC Draugelis Michael E ME O'Connor Nina R NR

Journal of general internal medicine 20190716 9

<h4>Background</h4>Development of electronic health record (EHR) prediction models to improve palliative care delivery is on the rise, yet the clinical impact of such models has not been evaluated.<h4>Objective</h4>To assess the clinical impact of triggering palliative care using an EHR prediction model.<h4>Design</h4>Pilot prospective before-after study on the general medical wards at an urban academic medical center.<h4>Participants</h4>Adults with a predicted probability of 6-month mortality ...[more]

PMID: 31313110

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Project description:BackgroundPatients in intensive care units (ICUs) often require quality palliative care for relief from various types of suffering. To achieve quality palliative care, specific goals need to be identified, measured, and reported. The present study aimed to develop quality indicators (QIs) for palliative care in ICUs, based on a systematic review and modified Delphi method, and test their feasibility by reviewing electronic medical record (EMR) data.MethodsThe current study was performed in two phases: the development of QIs using the modified Delphi method, and pilot-testing the quality of palliative care in ICUs based on EMR review. The pilot test included 262 patients admitted to the general or emergency ICU at a university hospital from January 1, 2019, to June 30, 2019.ResultsA 28-item QI set for palliative care in ICUs was developed based on the consensus of 16 experts. The Delphi process resulted in low measurability ratings for two items: "Assessment of the patient's psychological distress" and "Assessment of the patient's spiritual and cultural practices." However, these items were determined to be important for quality care from the perspective of holistic assessment of distress and were adopted in the final version of the QI set. While the pilot test results indicated the feasibility of the developed QIs, they suggested that the frequency of care performance varied, and certain aspects of palliative care in ICUs needed to be improved, namely (1) regular pain assessment, (2) identification of the patient's advance directive and advance care planning for treatment, (3) conducting an interdisciplinary family conference on palliative care, and (4) assessment of psychological distress of family members.ConclusionsThe QI set, developed using the modified Delphi method and tested using EMR data, provided a tool for assessing the quality of palliative care in ICUs. In the two ICUs considered in this study, aspects of the palliative care process with a low performance frequency were identified, and further national surveys were recommended. It is necessary to conduct ongoing surveys at more facilities to improve the quality of palliative care in ICUs.

Project description:Background/aimCost-efficient methods are essential for successful participant recruitment in clinical trials. Patient portal messages are an emerging means of recruiting potentially eligible patients into trials. We assessed the response rate and complaint rate from direct-to-patient, targeted recruitment through patient portals of an electronic medical record for a clinical trial, and compared response rates by differences in message content.MethodsThe Study to Understand Fall Reduction and Vitamin D in You (STURDY) trial is a National Institutes of Health-sponsored, community-based study of vitamin D supplementation for fall prevention in older adults conducted at Johns Hopkins. Potential participants were identified using the Epic electronic medical record at the Johns Hopkins Health System based on age (≥70 years), ZIP code (30-mile radius of study site), and prior activation of a patient portal account. We prepared a shorter message and a longer message. Both had basic information about study participation, but the longer message also contained information about the significance of the study and a personal invitation from the STURDY principal investigator. The Hopkins Institutional Review Board did not require prior consent from the patient or their providers. We calculated the response rate and tracked the number of complaints and requests for removal from future messages. We also determined response rate according to message content.ResultsOf the 5.5 million individuals receiving care at the Johns Hopkins Health System, a sample of 6896 met our inclusion criteria and were sent one patient portal recruitment message between 6 April 2017 and 3 August 2017. Assessment of enrollment by this method ended on 1 December 2017. There were 116 patients who expressed interest in the study (response rate: 1.7%). Twelve (0.2%) recipients were randomized. There were two complaints (0.03%) and one request to unsubscribe from future recruitment messages (0.01%). Response rate was higher with the longer message than the shorter message (2.1% vs 1.2%; p = 0.005).ConclusionPatient portal messages inviting seniors to participate in a randomized controlled trial resulted in a response rate similar to commercial email marketing and resulted in very few complaints or opt-out requests. Furthermore, a longer message with more content enhanced response rate. Recruitment through patient portals might be an effective strategy to enroll trial participants.

Dataset Information

Electronic Health Record Mortality Prediction Model for Targeted Palliative Care Among Hospitalized Medical Patients: a Pilot Quasi-experimental Study.

Publications

Electronic Health Record Mortality Prediction Model for Targeted Palliative Care Among Hospitalized Medical Patients: a Pilot Quasi-experimental Study.

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