Objectives: An increasing number of children are living with complex chronic diseases (CCDs) due to medical advances. Despite a need for code status discussions (CSDs), there is great variability in the frequency and documentation of such conversations. The objective was to identify gaps in the documentation of CSDs within the electronic health record (EHR), focusing on patients with CCDs.
Methods: This was a retrospective review of all patients admitted from the emergency department of a tertiary care children's hospital in 2016. An EHR query using the Apache Hadoop cluster and manual review identified documentation of CSDs, including (1) code status orders, (2) advance directives, and (3) CSDs in provider notes. Patient complexity was stratified using the Pediatric Medical Complexity Algorithm 3.0. Comparative analysis was performed using chi-square, Kruskal–Wallis tests and multivariable logistic regression.
Results: There were 12,648 unique patients of whom 4157 (32.9%) had CCD. Only 209 (1.7%) patients had a code status documented, of whom 200 (95.7%) had CCD. Of 528 (4.2%) patients =18 years of age, 428 (81.1%) had CCD and only 65 (12.3%) had CSDs. Palliative care consultation increased odds of CSDs (OR: 21.4, 95% CI: 13.8–33.2, p < 0.0001), whereas African American race decreased odds of CSDs (OR: 0.42, 95% CI: 0.27–0.64, p < 0.0001).
Conclusions: Among admitted pediatric patients, most do not have documentation of CSDs, including those with CCD and patients =18 years of age. Improvements in both frequency and consistency of CSD documentation are needed to inform the family-centered care of patients living with CCDs.
Access to data on quality metrics can better equip palliative care social workers to identify and address gaps in patient care, establish standards and accountability for social work functions on the interdisciplinary team, and evaluate the impact of interventions. The objective of this demonstration project was to create and pilot a data collection format in the patient electronic medical record (Epic) for documentation of social work metrics at each inpatient consultation, and to build corresponding pilot reports relevant to quality improvement goals. The successful implementation and initial pilot reports were reviewed for the feasibility of longer-term applications.
Opportunities for expanding advance care planning (ACP) throughout the health-care system make it critical that primary care (PC) providers have a basic understanding of how the electronic health record (EHR) can aid promoting ACP discussions and documentation. This article will offer PC providers 5 useful tips for implementing ACP in outpatient settings utilizing the EHR.
BACKGROUND: Advanced care planning through Physician Order For Life-Sustaining Therapies (POLST) has been encouraged by professional societies. But these documents may be overlooked or ignored during hospitalization and "full-code" orders written as a default, putting patients at risk for unwanted resuscitation. After 2 instances of unwanted resuscitation in which limited support POLSTs were ignored, a series of improvements were implemented. This study measured the effectiveness of those steps in reducing POLST code status discrepancy.
METHODS: Pre-post implementation chart review of randomly chosen medical admissions to determine the rate of discordance between POLST orders (when present) and admission code status orders. Physician Order For Life-Sustaining Therapies were classified as either "full" or "limited" based on orders for life-sustaining therapies on the form. Chi-square tests or Fisher exact tests were performed on binary data to identify statistically significant differences at the 95% confidence level between pre- and postimplementation admissions.
RESULTS: In all, 444 preimplementation and 448 postimplementation admissions were evaluated. Discrepant code status orders for those with limited POLST fell from 10 (22.7%) of 44 preimplementation to 3 (4.6%) of 65 after implementation, P = .006. The number of documented code status discussions in admission notes increased from 19.6% to 63.6% (P < .001). The median age of all POLST in the chart was 1.2 years.
CONCLUSIONS: Among those patients with limited POLST orders, discrepant full-code orders increase the potential for unwanted resuscitation. Multistep improvements including documentation templates improved the process of verifying end-of-life wishes and increased meaningful code status discussions. The rate of discrepant orders fell in response to process improvements.
BACKGROUND: Electronic care coordination systems, known as the Key Information Summary (KIS) in Scotland, enable the creation of shared electronic records available across healthcare settings. A KIS provides clinicians with essential information to guide decision making for people likely to need emergency or out-of-hours care.
AIM: To estimate the proportion of people with an advanced progressive illness with a KIS by the time of death, to examine when planning information is documented, and suggest improvements for electronic care coordination systems.
DESIGN AND SETTING: This was a mixed-methods study involving 18 diverse general practices in Scotland.
METHOD: Retrospective review of medical records of patients who died in 2017, and semi-structured interviews with healthcare professionals were conducted.
RESULTS: Data on 1304 decedents were collected. Of those with an advanced progressive illness (79%, n = 1034), 69% (n = 712) had a KIS. These were started a median of 45 weeks before death. People with cancer were most likely to have a KIS (80%, n = 288), and those with organ failure least likely (47%, n = 125). Overall, 68% (n = 482) of KIS included resuscitation status and 55% (n = 390) preferred place of care. People with a KIS were more likely to die in the community compared to those without one (61% versus 30%). Most KIS were considered useful/highly useful. Up-to-date free-text information within the KIS was valued highly.
CONCLUSION: In Scotland, most people with an advanced progressive illness have an electronic care coordination record by the time of death. This is an achievement. To improve further, better informal carer information, regular updating, and a focus on generating a KIS for people with organ failure is warranted.
Le déploiement du Système d'Information et du Dossier Patient informatisé suscite craintes et interrogations au sein de l'Hôpital. Le rôle d'accompagnement du cadre de santé est alors essentiel. L'élaboration d'objectifs nécessite une stratégie qui repose sur différents leviers. La phase exploratoire a permis d'établir trois hypothèses répondant à : en quoi une stratégie dans l'accompagnement influence le déploiement du Dossier Patient informatisé ?
Une enquête basée sur une approche qualitative tend à les confirmer ou réfuter. L'étude repose sur l'analyse d'entretiens avec des cadres de santé. A l'issue, il s'avère que le diagnostic est une phase importante pour l'adaptation de l'accompagnement. La responsabilisation, l'implication des professionnels sont de véritables leviers. Cependant la finalité qui favorise l'adhésion n'est pas toujours celle autour de la prise en charge du patient mais plutôt la traçabilité et l'utilisation pratique. Deux autres leviers ont également été éclairés.
Advance care planning is a process that supports conversations about the values that matter most to patients and their family members. The documentation of advance directives and code status in a patient's electronic health record (EHR) is a critical step to ensure treatment preferences are honored in the medical care received. The current approach to advanced care planning documentation in electronic medical records often remains disparate within and across EHR systems. Without a standardized format for documentation or centralized location for documentation, advance directives and even code status content are often difficult to access within electronic medical records. This case report launched our palliative care team into partnership with the Information Technology team for implementation of a centralized, standardized, longitudinal, functional documentation of advance care planning and code status in the electronic medical record system.
Importance Earlier clinician-patient conversations about patients’ values, goals, and preferences in serious illness (ie, serious illness conversations) are associated with better outcomes but occur inconsistently in cancer care.
Objective To evaluate the efficacy of a communication quality-improvement intervention in improving the occurrence, timing, quality, and accessibility of documented serious illness conversations between oncology clinicians and patients with advanced cancer.
Design, Setting, Participants This cluster randomized clinical trial in outpatient oncology was conducted at the Dana-Farber Cancer Institute and included physicians, advanced-practice clinicians, and patients with cancer who were at high risk of death.
Main Outcomes and Measures The primary outcomes (goal-concordant care and peacefulness at the end of life) are published elsewhere. Secondary outcomes are reported herein, including (1) documentation of at least 1 serious illness conversation before death, (2) timing of the initial conversation before death, (3) quality of conversations, and (4) their accessibility in the electronic medical record (EMR).
Results We enrolled 91 clinicians (48 intervention, 43 control) and 278 patients (134 intervention, 144 control). Of enrolled patients, 58% died during the study (n=161); mean age was 62.3 years (95% CI, 58.9-65.6 years); 55% were women (n=88). These patients were cared for by 76 of the 91 enrolled clinicians (37 intervention, 39 control); years in practice, 11.5 (95% CI, 9.2-13.8); 57% female (n=43). Medical record review after patients’ death demonstrated that a significantly higher proportion of intervention patients had a documented discussion compared with controls (96% vs 79%, P = .005) and intervention conversations occurred a median of 2.4 months earlier (median, 143 days vs 71 days, P < .001). Conversation documentation for intervention patients was significantly more comprehensive and patient centered, with a greater focus on values or goals (89% vs 44%, P < .001), prognosis or illness understanding (91% vs 48%, P < .001), and life-sustaining treatment preferences (63% vs 32%, P = .004). Documentation about end-of-life care planning did not differ between arms (80% intervention vs 68% control, P = .08). Significantly more intervention patients had documentation that was accessible in the EMR (61% vs 11%, P < .001).
Conclusions and Relevance This communication quality-improvement intervention resulted in more, earlier, better, and more accessible serious illness conversations documented in the EMR. To our knowledge, this is the first such study to demonstrate improvement in all 4 of these outcomes.
Objectives: Globally, healthcare systems are using the Electronic Health Record (EHR) and elements of clinical decision support (CDS) to facilitate palliative care (PC). Examination of published results is needed to determine if the EHR is successfully supporting the multidisciplinary nature and complexity of PC by identifying applications, methodology, outcomes, and barriers of active incorporation of the EHR in PC clinical workflow.
Methods: A systematic review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The data sources PubMed, CINAL, EBSCOhost, and Academic Search Premier were used to identify literature published 1999 - 2017 of human subject peer-reviewed articles in English containing original research about the EHR and PC.
Results: The search returned 433 articles, 30 of which met inclusion criteria. Most studies were feasibility studies or retrospective cohort analyses; one study incorporated prospective longitudinal mixed methods. Twenty-three of 30 (77%) were published after 2014. The review identified five major areas in which the EHR is used to support PC. Studies focused on CDS to: identify individuals who could benefit from PC; electronic advanced care planning (ACP) documentation; patient-reported outcome measures (PROMs) such as rapid, real-time pain feedback; to augment EHR PC data capture capabilities; ,and to enhance interdisciplinary communication and care.
Discussion: Beginning in 2015, there was a proliferation of articles about PC and EHRs, suggesting increasing incorporation of and research about the EHR with PC. This review indicates the EHR is underutilized for PC CDS, facilitating PROMs, and capturing ACPs.
Timely outreach to individuals in an advanced stage of illness offers opportunities to exercise decision control over health care. Predictive models built using Electronic health record (EHR) data are being explored as a way to anticipate such need with enough lead time for patient engagement. Prior studies have focused on hospitalized patients, who typically have more data available for predicting care needs. It is unclear if prediction driven outreach is feasible in the primary care setting. In this study, we apply predictive modeling to the primary care population of a large, regional health system and systematically examine the impact of technical choices, such as requiring a minimum number of health care encounters (data density requirements) and aggregating diagnosis codes using Clinical Classifications Software (CCS) groupings to reduce dimensionality, on model performance in terms of discrimination and positive predictive value. We assembled a cohort of 349,667 primary care patients between 65 and 90 years of age who sought care from Sutter Health between July 1, 2011 and June 30, 2014, of whom 2.1% died during the study period. EHR data comprising demographics, encounters, orders, and diagnoses for each patient from a 12 month observation window prior to the point when a prediction is made were extracted. L1 regularized logistic regression and gradient boosted tree models were fit to training data and tuned by cross validation. Model performance in predicting one year mortality was assessed using held-out test patients. Our experiments systematically varied three factors: model type, diagnosis coding, and data density requirements. We found substantial, consistent benefit from using gradient boosting vs logistic regression (mean AUROC over all other technical choices of 84.8% vs 80.7% respectively). There was no benefit from aggregation of ICD codes into CCS code groups (mean AUROC over all other technical choices of 82.9% vs 82.6% respectively). Likewise increasing data density requirements did not affect discrimination (mean AUROC over other technical choices ranged from 82.5% to 83%). We also examine model performance as a function of lead time, which is the interval between death and when a prediction was made. In subgroup analysis by lead time, mean AUROC over all other choices ranged from 87.9% for patients who died within 0 to 3 months to 83.6% for those who died 9 to 12 months after prediction time.
The current study explored the perceptions of health care providers' use of electronic advance directive (AD) forms in the electronic health record (EHR). The Technology Acceptance Model (TAM) was used to guide the study. Of 165 surveys distributed, 151 participants (92%) responded. A moderately strong positive correlation was noted between perceived usefulness and actual system usage (r = 0.70, p < 0.0001). Perceived ease of use and actual system usage also had a moderately strong positive correlation (r = 0.70, p < 0.0001). In contrast, the strength of the relationship between behavioral intention to use and actual system usage was more modest (r = 0.22, p < 0.004). There was a statistically significant difference in actual system usage of electronic ADs across six departments ( 2 = 79.325, p < 0.001). The relationships among primary TAM constructs found in this research are largely consistent with previous TAM studies, with the exception of behavioral intention to use, which is slightly lower. These data suggest that health care providers' perceptions have great influence on the use of electronic ADs. [
CONTEXT: Opportunities for patients to receive unnecessary, costly and potentially harmful care near the end-of-life abound. Advance care planning (ACP) can help to make this vulnerable period better for patients, caregivers and providers.
OBJECTIVE: The objective of this study was to determine whether older age predicted the presence of certain forms of retrievable ACP documentation in the Electronic Health Record (EHR) in a large sample of hospice-referred patients.
METHODS: This was a retrospective analysis of medical-record data on 3,595 patients referred to hospice between January 1st, 2013 and December 31, 2015. EHR documentation of an ACP note in the problem list, presence of a scanned Advance Directive (AD), and the presence of a verified Do Not Resuscitate order (DNR) were the outcome measures. Logistic regression was used to assess the effect of age, education, race, gender, cancer diagnosis, dementia diagnosis, palliative encounter and death on the outcome variables.
RESULTS: Our results suggest that when we control for prognosis, patients over age 70 may experience gaps in ACP communication. We found that as patients age, the odds of having documentation of a conversation (OR=0.56; P <0.001) or scanned AD decreased (OR=0.63; P<0.001), while the odds of having a verified DNR increased (OR=1.42; P<0.001).
CONCLUSION: The results of this study may imply some degree of unilateral and physician-driven decision making for end-of-life care among older adults. Collaborative efforts between an interdisciplinary medical team should focus on developing policies to address this potential disparity between younger and older adults at the end-of-life.
BACKGROUND: Access to palliative care is a key quality metric which most healthcare organizations strive to improve. The primary challenges to increasing palliative care access are a combination of physicians over-estimating patient prognoses, and a shortage of palliative staff in general. This, in combination with treatment inertia can result in a mismatch between patient wishes, and their actual care towards the end of life.
METHODS: In this work, we address this problem, with Institutional Review Board approval, using machine learning and Electronic Health Record (EHR) data of patients. We train a Deep Neural Network model on the EHR data of patients from previous years, to predict mortality of patients within the next 3-12 month period. This prediction is used as a proxy decision for identifying patients who could benefit from palliative care.
RESULTS: The EHR data of all admitted patients are evaluated every night by this algorithm, and the palliative care team is automatically notified of the list of patients with a positive prediction. In addition, we present a novel technique for decision interpretation, using which we provide explanations for the model's predictions.
CONCLUSION: The automatic screening and notification saves the palliative care team the burden of time consuming chart reviews of all patients, and allows them to take a proactive approach in reaching out to such patients rather then relying on referrals from the treating physicians.
Documentation of code status and advance directives for end-of-life (EOL) care improves care and quality of life, decreases cost of care, and increases the likelihood of an experience desired by the patient and his/her family. However, the use of advance directives and code status remains low and only a few organizations maintain code status in electronic form. Members of the American Medical Informatics Association's Ethics Committee identified a need for a patient's EOL care wishes to be documented correctly and communicated easily through the electronic health record (EHR) using a minimum data set for the storage and exchange of code status information. After conducting an environmental scan that produced multiple resources, Ethics Committee members used multiple conference calls and a shared document to arrive at consensus on the proposed minimum data set. Ethics Committee members developed a minimum required data set with links to the HL7 C_CDA Advance Directives Module. Data categories include information on the organization obtaining the code status information, the patient, any supporting documentation, and finally the desired code status information including mandatory, optional, and conditional elements. The "minimum set of attributes" to exchange advance directive / code status data described in this manuscript enables communication of patient wishes across multiple providers and health care settings. The data elements described serve as a starting point for a dialog among informatics professionals, physicians experienced in EOL care, and EHR vendors, with the goal of developing standards for incorporating this functionality into the EHR systems.
Objectives: The demand for hospice has been increasing among patients with cancer. This study examined the current hospice referral scenario for terminally ill cancer patients and created a data form to collect hospice information and a modified health information exchange (HIE) form for a more efficient referral system for terminally ill cancer patients.
Methods: Surveys were conducted asking detailed information such as medical instruments and patient admission policies of hospices, and interviews were held to examine the current referral flow and any additional requirements. A task force team was organized to analyze the results of the interviews and surveys.
Results: Six hospices completed the survey, and 3 physicians, 2 nurses, and 2 hospital staff from a tertiary hospital were interviewed. Seven categories were defined as essential for establishing hospice data. Ten categories and 40 data items were newly suggested for the existing HIE document form. An implementation guide for the Consolidated Clinical Document Architecture developed by Health Level 7 (HL7 CCDA) was also proposed. It is an international standard for interoperability that provides a framework for the exchange, integration, sharing, and retrieval of electronic health information. Based on these changes, a hospice referral scenario for terminally ill cancer patients was designed.
Conclusions: Our findings show potential improvements that can be made to the current hospice referral system for terminally ill cancer patients. To make the referral system useful in practice, governmental efforts and investments are needed.
BACKGROUND: Palliative surgical procedures are frequently performed to reduce symptoms in patients with advanced cancer, but quality is difficult to measure.
OBJECTIVE: To determine whether natural language processing (NLP) of the electronic health record (EHR) can be used to (1) identify a population of cancer patients receiving palliative gastrostomy and (2) assess documentation of end-of-life process measures in the EHR.
DESIGN/SETTING: Retrospective cohort study of 302 adult cancer patients who received a gastrostomy tube at a single tertiary medical center.
MEASUREMENTS: Sensitivity and specificity of NLP compared to gold standard of manual chart abstraction in identifying a palliative indication for gastrostomy tube placement and documentation of goals of care discussions, code status determination, palliative care referral, and hospice assessment.
RESULTS: Among 302 cancer patients who underwent gastrostomy, 68 (22.5%) were classified by NLP as having a palliative indication for the procedure compared to 71 patients (23.5%) classified by human coders. Human chart abstraction took >2600 times longer than NLP (28 hours vs. 38 seconds). NLP identified the correct patients with 95.8% sensitivity and 97.4% specificity. NLP also identified end-of-life process measures with high sensitivity (85.7%-92.9%,) and specificity (96.7%-98.9%). In the two months leading up to palliative gastrostomy placement, 20.5% of patients had goals of care discussions documented. During the index hospitalization, 67.7% had goals of care discussions documented.
CONCLUSIONS: NLP offers opportunities to identify patients receiving palliative surgical procedures and can rapidly assess established end-of-life process measures with an accuracy approaching that of human coders.
OBJECTIVE: To develop a set of clinically relevant recommendations to improve the state of advance care planning (ACP) documentation in the electronic health record (EHR).
BACKGROUND: Advance care planning (ACP) is a key process that supports goal-concordant care. For preferences to be honored, clinicians must be able to reliably record, find, and use ACP documentation. However, there are no standards to guide ACP documentation in the electronic health record (EHR).
METHODS: We interviewed 21 key informants to understand the strengths and weaknesses of EHR documentation systems for ACP and identify best practices. We analyzed these interviews using a qualitative content analysis approach and subsequently developed a preliminary set of recommendations. These recommendations were vetted and refined in a second round of input from a national panel of content experts.
RESULTS: Informants identified six themes regarding current inadequacies in documentation and accessibility of ACP information and opportunities for improvement.
DISCUSSION: We offer a set of concise, clinically relevant recommendations, informed by expert opinion, to improve the state of ACP documentation in the EHR.
BACKGROUND: Documentation rates of advance directives (ADs) remain low. Using electronic medical records (EMRs) could help, but a synthesis of evidence is currently lacking.
OBJECTIVES: To evaluate the evidence for using EMRs in documenting ADs and its implications for overcoming challenges associated with their use.
DESIGN: Systematic review of articles in English, published from inception of databases to December 2017.
DATA SOURCES: PubMed, PsycINFO, EMBASE, and CINAHL. Methods/Measurements: Four databases were searched from inception to December 2017. Randomized and nonrandomized quantitative studies examining the effects of EMRs on creation, storage, or use of ADs were included. All featured an advance care planning process. Evidence was evaluated using the Cochrane Collaboration's risk assessment tool.
RESULTS: Fifteen studies were included: 1 randomized controlled trial, 1 randomized pilot, 4 pre-post studies, 4 cross-sectional studies, 1 retrospective cohort study, 1 historical control study, 1 retrospective observational study, 1 retrospective review, and 1 evaluation of an EMR feature. Seven studies showed that EMR-based reminders, AD templates, and decision aids can improve AD documentation rates. Three demonstrated that EMR search functions, decision aids, and automatic identification software can help identify patients who have or need ADs according to certain criteria. Five showed EMRs can create documentation challenges, including locating ADs, and making some patients more likely than others to have an AD. Most studies had an unclear or high risk of bias.
CONCLUSIONS: Limited evidence suggests EMRs could be used to help address AD documentation challenges but may also create additional problems. Stronger evidence is needed to more conclusively determine how EMR may assist in population approaches to improving AD documentation.
BACKGROUND: Strategies have been developed for use in primary care to identify patients at risk of declining health and dying, yet little is known about the perceptions of doing so or the broader implications and impacts.
AIM: To explore the acceptability and implications of using a primary care-based electronic medical record algorithm to help providers identify patients in their practice at risk of declining health and dying.
DESIGN AND SETTING: Qualitative descriptive study in Ontario and Nova Scotia, Canada.
METHOD: Six focus groups were conducted, supplemented by one-on-one interviews, with 29 healthcare providers, managers, and policymakers in primary care, palliative care, and geriatric care. Participants were purposively sampled to achieve maximal variation. Data were analysed using a constant comparative approach.
RESULTS: Six themes were prevalent across the dataset: early identification is aligned with the values, aims, and positioning of primary care; providers have concerns about what to do after identification; how we communicate about the end of life requires change; early identification and subsequent conversations require an integrated team approach; for patients, early identification will have implications beyond medical care; and a public health approach is needed to optimise early identification and its impact.
CONCLUSION: Stakeholders were much more concerned with how primary care providers would navigate the post-identification period than with early identification itself. Implications of early identification include the need for a team- based approach to identification and to engage broader communities to ensure people live and die well post-identification.
Background: recognising that a patient is nearing the end of life is essential, to enable professional carers to discuss prognosis and preferences for end of life care.
Objective: investigate whether an electronic frailty index (eFI) generated from routinely collected data, can be used to predict mortality at an individual level.
Design: historical prospective case control study.
Setting: UK primary care electronic health records.
Subjects: 13,149 individuals age 75 and over who died between 01/01/2015 and 01/01/2016, 1:1 matched by age and sex to individuals with no record of death in the same time period.
Methods: two subsamples were randomly selected to enable development and validation of the association between eFI 3 months prior to death and mortality. Receiver operator characteristic (ROC) analyses were used to examine diagnostic accuracy of eFI at 3 months prior to death.
Results: an eFI > 0.19 predicted mortality in the development sample at 75% sensitivity and 69% area under received operating curve (AUC). In the validation dataset this cut point gave 76% sensitivity, 53% specificity.
Conclusions: the eFI measured at a single time point has low predictive value for individual risk of death, even 3 months prior to death. Although the eFI is a strong predictor or mortality at a population level, its use for individuals is far less clear.