Use of self-reporting outcomes to inform patient care.

2014 ◽  
Vol 32 (30_suppl) ◽  
pp. 176-176
Author(s):  
Brandon Bosch ◽  
Diane Denny ◽  
Maurie Markman
Keyword(s):  
Patient Care ◽  
Real Time ◽  
Treatment Plan ◽  
Symptom Burden ◽  
Assessment Instrument ◽  
Free Text ◽  
Data Set ◽  
Symptom Inventory ◽  
Starting Point ◽  
E Mail

176 Background: Cancer Treatment Centers of America, Inc (CTCA) is a national network of hospitals that specialize in the treatment of patients fighting complex or advanced-stage cancer. The Symptom Inventory Tool (SIT) is an assessment tool that captures the patients’ perceived symptom burden for real-time clinical intervention, from the point of no intervention (baseline) and every 21 days or greater. The SIT is comprised of 27 questions utilizing the MD Anderson Symptom Inventory tool, a validated assessment instrument with eight questions added and a free text box by CTCA. The SIT became an integral part of patient care at CTCA beginning in 2012. Methods: Non-clinical stakeholders administer the SIT via an electronic tablet. Upon completion of the assessment, a trending graph known as Symptoms-at-a-Glance (SAG) report is auto populated and available to clinicians in the EHR or may be printed at the point of care. The SAG provides run graphs for each symptom including arrows identifying clinically relevant changes in score. An accompanying e-mail notification system was created for physicians to review specific symptoms of interest at a threshold of their choosing, and refer patients to other specialties deemed integral for the patient’s treatment plan. Results: The SIT assessment is utilized by the nurse as a starting point from which they can initiate a more pointed conversation with the patient including the need for appropriate intervention including follow-up with the oncologist and/or referral to a member of the extended integrative care team. The percentage of new and returning patients completing an assessment is at 94.94% and 84.81%, respectively, for patients (1/1/14-6/9/14) across CTCA suggesting this process is useful for both patient and clinicians. Patients comment that the time for self-reflection is a healthy exercise enabled by the user-friendly tablet. Clinicians value both the ease of administration/use as well as the ability to create a large data set for quality improvement. Conclusions: With a majority of new and returning patients participating in the SIT, the SAG report fully implemented into the EHR along with the use of an e-mail functionality, clinicians and physicians can now better manage symptom burden real time

Use of an automated notification tool to drive real-time patient symptom intervention.

2016 ◽  
Vol 34 (7_suppl) ◽  
pp. 160-160
Author(s):  
Scott Hartman ◽  
Brandon Bosch ◽  
Diane Denny ◽  
Maurie Markman
Keyword(s):  
Real Time ◽  
Assessment Tool ◽  
Assessment Instrument ◽  
Free Text ◽  
Team Members ◽  
National Network ◽  
Symptom Inventory ◽  
Support Team ◽  
E Mail

160 Background: Cancer Treatment Centers of America, Inc. (CTCA) is a national network of hospitals that specialize in the treatment of patients fighting complex or advanced-stage cancer. The Symptom Inventory Tool (SIT) is an assessment tool that captures the patients’ perceived symptom burden for real-time clinical intervention, from baseline and every 21 days thereafter. The SIT is comprised of questions utilizing the M.D. Anderson Symptom Inventory tool, a validated assessment instrument with questions added and a free text box by CTCA. Methods: An e-mail notification system associated with the SIT was established to allow efficient communication with specialists and support team members who would not traditionally see the patient without such a trigger signifying a need. While the SIT report is housed within the EHR, an automated e-mail profile may be established for each clinician and or team, tailored to the clinical specialty, based on symptom(s) of interest. Patients completing the SIT and scoring a particular symptom(s) at or above a threshold will “trigger” notification of that their score along with information allowing follow-up. Notifications can be set at 15 minute intervals, hourly, daily, etc. Results: 31 users/groups, representing a wide variety of disciplines and multiple care teams, currently utilize the SIT e-mail functionality including: Pain, Distress, Mind Body Medicine, Survivorship, Physical Therapy, and Sleep. The content of the e-mail consists of the patient name, medical record number, and (self-defined) symptom scores of interest. These same patients triggering a notification may be readily tracked for follow-up by the support team throughout their course of treatment or seen only once depending upon patient preference and identified need. Conclusions: The e-mail notification process has promoted communication with specialists and other support team members outside of the core team, cognizant of their different communication needs. Moreover, it allows for effective alignment of resources based on clinician expertise.

Program development through compilation of patient self-reported symptom burden.

2014 ◽  
Vol 32 (30_suppl) ◽  
pp. 78-78
Author(s):  
Diane Denny ◽  
Brandon Bosch ◽  
Kayla Alston ◽  
Maurie Markman
Keyword(s):  
Program Development ◽  
Assessment Tool ◽  
Symptom Burden ◽  
Clinical Intervention ◽  
Assessment Instrument ◽  
Free Text ◽  
Cancer Type ◽  
National Network ◽  
Symptom Inventory ◽  
Md Anderson

78 Background: Cancer Treatment Centers of America, (CTCA) is a national network of five hospitals that specialize in the treatment of patients fighting complex or advanced-stage cancer. The Symptom Inventory Tool (SIT) is an assessment tool that captures the patients’ perceived symptom burden for real time clinical intervention and provides longitudinal data to demonstrate how effectively we meet our patient’s needs, from the point of no intervention (baseline) and every 21 days or greater. The SIT is comprised of 27 questions utilizing the MD Anderson Symptom Inventory tool, a validated assessment instrument with 8 questions added and a free text box by CTCA. The SIT became an integral part of patient care at CTCA in September 2012. Methods: A multidisciplinary team convened to evaluate how best to deliver the SIT data to facility leadership to assist with program development. The data needed to perform each calculation was obtained using analytical software that interfaces the database, electronic health record, and cancer registry. A Quality Research Associate prepares the operational summary providing a monthly update for the leadership at each facility with data included for the previous month, cumulatively for the facility, and cumulatively for the network. Results: The summary includes mean time to complete an assessment, assessments by timeframe (i.e. baseline, 2nd, 3rd assessments, etc.), gender and age percentages, and patients categorized by cancer type. The top three average scoring symptoms and interference issues by baseline, 2nd, and 3rd assessment are highlighted along with the top areas of improvement and diminishment in score defined by a change of 2 or more points reflecting clinical relevance. The top areas scored at 8 or greater that improved and the top areas where patients continued to score at 8 or greater on return are presented to focus upon the most severe needs. Graphs and tables are accompanied by explanation. Conclusions: In addition to consistency in presentation of the data across centers, the SIT operational summary provides visibility and insight on key emerging trends. Meaningful discussion of programmatic opportunities for focus on the most problematic and severe symptom by patient group has occurred.

Engaging patients with their self-reported symptom outcomes trended data.

2016 ◽  
Vol 34 (7_suppl) ◽  
pp. 69-69
Author(s):  
Scott Hartman ◽  
Diane Denny ◽  
Carmon Greene ◽  
Morgan Hannaford ◽  
Maurie Markman
Keyword(s):  
Real Time ◽  
Assessment Tool ◽  
Graphical Representation ◽  
Wide Spectrum ◽  
Care Physician ◽  
Interdisciplinary Teams ◽  
Care Team ◽  
Assessment Instrument ◽  
Free Text ◽  
Symptom Inventory

69 Background: Cancer Treatment Centers of America, Inc. (CTCA) is a national network of hospitals that specialize in the treatment of patients fighting complex or advanced-stage cancer. The Symptom Inventory Tool (SIT) is an assessment tool that captures the patients’ perceived symptom burden for real-time clinical intervention. Patients take a baseline SIT assessment at new patient intake and are eligible to take the SIT every 21 days. The SIT is comprised of the M.D. Anderson Symptom Inventory tool, a validated assessment instrument, along with additional questions and a free text box that were created by CTCA. The SIT became an integral part of patient care at CTCA beginning in 2012. Recognizing the value of the SIT data in real time patient intervention, a project was undertaken to engage the patient with his/her results and facilitate dialogue with his/her care team. Methods: Upon completing the SIT, patients were provided with their Symptoms-At-a-Glance (SAG) report, which is a graphical representation of trended outcomes of their SIT data, along with education on how to interpret the document. Patients were encouraged to review the SAG with their care team as a communication facilitation tool promoting open dialog on those symptoms identified as the most severe and or frequent. Pre and post evaluations of the process were completed via a brief questionnaire for patients and staff to evaluate efficacy of the exchange. Results: A total of 272 patients completed the SIT during the initial 30 days. 80.5% of patients utilized the SAG report during their Medical Oncology appointments and/or took their report with them for subsequent reference. Utilization of the SAG report by interdisciplinary teams for patient intervention showed an increase of 103%. Patients responded favorably to the project and reported that the SAG is a valuable tool which will be shared with their primary care physician and used to update family members. Conclusions: The project was successful in creating improved integration of the SIT outcomes and driving more focused and complete discussions between patients and their providers on a wide spectrum of quality of life issues.

Evaluation of self-reported symptoms and interference issues in prostate cancer patients.

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 283-283
Author(s):  
Mahdi Taha
Keyword(s):  
Prostate Cancer ◽  
Sexual Dysfunction ◽  
Cancer Patients ◽  
Large Body ◽  
Symptom Burden ◽  
The United States ◽  
Assessment Instrument ◽  
Cancer Center ◽  
Free Text ◽  
Symptom Inventory

283 Background: Prostate cancer is a leading cause of global morbidity and mortality and in the next few years is expected to be the leading cause of death among men in the United States. Both the disease and its treatments produce a variety of symptoms that impact prostate cancer outcomes, of which the more common symptoms are in relation to sexual dysfunction. A large body of literature has established that systematic patient reporting of symptoms during routine oncology care leads to clinical benefits. At our comprehensive community cancer center we evaluate patients’ reported symptoms using the Symptom Inventory Tool (SIT), an assessment tool that captures the patients' perceived symptom burden for real-time clinical intervention taken at the point of no intervention and every ≥ 21 days thereafter. Methods: The 27-question SIT is comprised of the M.D. Anderson Symptom Inventory Tool (MDASI), a validated assessment instrument, with 8 supplementary questions and a free-text box added by Cancer Treatment Centers of America. Symptoms are rated “at the worst” on a numeric scale ranging from 0 to 10, as experienced by pts in the past 24 hours. The SIT became an integral part of patient care at CTCA beginning in 2012. Results: Over a 45 month period (9/1/2012 to 05/31/2016), prostate cancer pts at CTCA completed the SIT at intake and again ≥ 21 days after. A total of 2,937 assessments were analyzed. The assessments consisted of 1,065 completed at baseline, 1,065 completed at the 2nd follow up (FU), and 807 completed at 3rd FU or greater. Further analysis of baseline SIT identified the pts who rated the above symptoms as “very burdensome” with a score of ≥ 5. 2nd SIT results from these PC patients revealed that those with a heavier symptoms burden at baseline would be more likely to experience a significant decrease in their symptoms burden than the average PC patient population. Conclusions: The SIT was successful in identifying symptoms burden and interference with life issues in prostate cancer patients. Sexual dysfunction and disturbed sleep were the most common reported symptoms. Early identification of patients with heavy symptom-burden allowed immediate intervention and improvement in approximately a one-fourth to two-thirds of patients.

A description of the free text word choices physicians use to describe prognosis in over 50,000 electronic treatment plans.

2018 ◽  
Vol 36 (30_suppl) ◽  
pp. 219-219
Author(s):  
Lalan S. Wilfong ◽  
Mark Ferencik ◽  
Marcus A. Neubauer
Keyword(s):  
Treatment Plan ◽  
Management Plan ◽  
Response To Therapy ◽  
Care Plan ◽  
Current Status ◽  
Free Text ◽  
Institute Of Medicine ◽  
Word Count ◽  
Data Set ◽  
Treatment Plans

219 Background: Fourteen practices within the US Oncology Network are participating in the Center for Medicare and Medicaid Innovation’s (CMMI) Oncology Care Model. To meet the requirement of documenting a care plan that contains the 13 components in the Institute of Medicine Care Management Plan, an electronic treatment plan was developed which incorporates core elements from our EMR, IKnowMed, supplemented by additional physician documentation. Physicians must document in their own words the prognosis section of the care plan. Methods: To better understand the word choices physicians use for prognosis, we evaluated the word choices used in over 50,000 treatment plans. Using an excel based word count macro, all contents of the free text entry “prognosis” field were sorted based on frequency of the same answer and were then ranked from most common use to least common. A word count method was applied to determine and rank the most commonly used words across all answers. The “current status of disease” field in the treatment plan was used to divide the prognosis answers into those that mentioned “Metastatic” and “Not Metastatic” so that prognosis wording trends could be compared using pivot tables and data filters. Results: 70% of prognosis word choices were single words: “excellent, good, fair, poor, or guarded” were the most common. 20% of phrases were multi-word that appeared repeatedly such as “will depend on the response to therapy.” Only 10% of answers were uniquely worded per treatment plan and felt to be personal to the patient’s situation. Additionally, the number of words did not differ between metastatic and non-metastatic disease. Conclusions: To our knowledge, this is the largest cohort of treatment plans where the word choices used by physicians are described to document prognosis to patients. The results indicate that single words or short phrases are commonly used to describe prognosis when the treatment plan is shared with patients. The data set has high potential for further study to better understand the role and impact of written treatment plans (including downstream events) to help physicians refine this documentation for better patient understanding of this important topic.

Addressing patient needs through compilation of self-reported verbatim comments.

2016 ◽  
Vol 34 (7_suppl) ◽  
pp. 111-111
Author(s):  
Scott Hartman ◽  
Diane Denny ◽  
Sarah Hizon ◽  
Danielle Kendrick ◽  
Maurie Markman
Keyword(s):  
Symptom Burden ◽  
Free Text ◽  
Patient Needs ◽  
Dual Processes ◽  
Text Data ◽  
National Network ◽  
Symptom Inventory ◽  
Advanced Stage Cancer ◽  
Multi Disciplinary Team

111 Background: Cancer Treatment Centers of America, Inc. (CTCA) is a national network of five hospitals that specialize in the treatment of patients fighting complex or advanced-stage cancer. The Symptom Inventory Tool (SIT) is an assessment that captures the patients’ perceived symptom burden, from baseline and every 21 days thereafter. The SIT is comprised of questions utilizing the M.D. Anderson Symptom Inventory tool, with eight questions and a free text box added by CTCA. Patient comments are provided in approximately 5% of all assessments (representing 3,700 comments) since initiation of the SIT. Methods: Patients answer the question, “Is there anything else that you would like to tell us or are there additional concerns you would like addressed?” within a free text field. In addition to availability to the care team to address any identified urgent need, each comment is classified into 15 defined categories to allow trending. The report is disseminated monthly to a multi-disciplinary team for follow-up on service delivery and consideration in program development. Results: The table represents the top five patient comment categories along with “other”. In addition, a sample of last quarter's data revealed that 84% of comments required immediate follow-up that may have otherwise been missed without text data mining. Conclusions: Verbatim comments are of significant value and can be best managed via dual processes to ensure timely follow-up and to support programmatic alignment, continuously analyzing data for areas of improvement. [Table: see text]

Analysis of Demand in The First Visit To The Mental Health Unit

2016 ◽  
Vol 33 (S1) ◽  
pp. S451-S451
Author(s):  
B. Mata Saenz ◽  
E. Lopez Lavela ◽  
T. Rodríguez Cano ◽  
L. Beato Fernández
Keyword(s):  
Treatment Plan ◽  
Demographic Data ◽  
High Rate ◽  
Record System ◽  
Data Set ◽  
Referral Criteria ◽  
Starting Point ◽  
Competing Interest ◽  
Image Position ◽  
Mental Care

IntroductionThe first visit is crucial, since it is where a treatment plan is selected and the decision to refer or not the patient to a specialized unit is made. Mental care could be improved through the centralization of demand and the identification of patients’ and psychiatrists’ expectations.ObjectivesAnalyzing patients’ and psychiatrists’ demands and expectations in the first visit to use them as a starting point for the planning and coordination of treatment actions.AimsTo design a record system of the Minimum Basic Data Set of the Centralized Department of our Unit.MethodsThis is an epidemiological, observational, prospective study of patients referred to our department. Following variables were collected:– referral origin;– reason;– demographic data;– diagnosis impression;– destination of referral.The Statistical Package for Social Science version 19.0 was used to analyze the data.ResultsTable 1.ConclusionsThe data obtained are consistent with those reported in the literature for this population. The high rate of wrong referrals reveals the necessity of improving coordination and establishing specific referral criteria. Some initiatives have been designed and will be prospectively evaluated in the future.Table 1Disclosure of interestThe authors have not supplied their declaration of competing interest.

scholarly journals Predicting Intentions of Pedestrians from 2D Skeletal Pose Sequences with a Representation-Focused Multi-Branch Deep Learning Network

Algorithms ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 331
Author(s):  
Joseph Gesnouin ◽  
Steve Pechberti ◽  
Guillaume Bresson ◽  
Bogdan Stanciulescu ◽  
Fabien Moutarde
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Autonomous Driving ◽  
Urban Traffic ◽  
Data Set ◽  
Learning Network ◽  
Starting Point ◽  
Good Starting Point ◽  
Deep Learning Network ◽  
Pedestrian Crossing

Understanding the behaviors and intentions of humans is still one of the main challenges for vehicle autonomy. More specifically, inferring the intentions and actions of vulnerable actors, namely pedestrians, in complex situations such as urban traffic scenes remains a difficult task and a blocking point towards more automated vehicles. Answering the question “Is the pedestrian going to cross?” is a good starting point in order to advance in the quest to the fifth level of autonomous driving. In this paper, we address the problem of real-time discrete intention prediction of pedestrians in urban traffic environments by linking the dynamics of a pedestrian’s skeleton to an intention. Hence, we propose SPI-Net (Skeleton-based Pedestrian Intention network): a representation-focused multi-branch network combining features from 2D pedestrian body poses for the prediction of pedestrians’ discrete intentions. Experimental results show that SPI-Net achieved 94.4% accuracy in pedestrian crossing prediction on the JAAD data set while being efficient for real-time scenarios since SPI-Net can reach around one inference every 0.25 ms on one GPU (i.e., RTX 2080ti), or every 0.67 ms on one CPU (i.e., Intel Core i7 8700K).

Efficacy of screening and treatment of breast cancer patients reporting high level of distress.

2015 ◽  
Vol 33 (28_suppl) ◽  
pp. 101-101
Author(s):  
Ryan West ◽  
John W Thomas ◽  
Elaine Smith ◽  
Navneet Dhillon ◽  
Haritha Pabbathi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Health Care Providers ◽  
Assessment Instrument ◽  
Initial Assessment ◽  
Free Text ◽  
Care Providers ◽  
Breast Cancer Patients ◽  
Integrative Oncology ◽  
Symptom Inventory

101 Background: Cancer patients (pts) are burdened by symptoms related to the disease itself or to the toxicities of treatment. The ASCO clinical oncology guideline adaptation recommends all health care providers routinely screen for the presence of emotional distress and specifically symptoms of anxiety from the point of diagnosis onward [Andersen BL, 2014].At Cancer Treatment Centers of America (CTCA) we perform screening assessments using a Symptom Inventory Tool (SIT) composed of 27 questions. Pts with moderate and severe levels of anxiety are evaluated by the Integrative Resource Assessment Program (IRAP) and subsequently referred to integrative oncology consultation. Methods: The SIT is an assessment tool that captures pts’ perceived symptom burden for real-time clinical intervention, taken at the point of no intervention (baseline) and every 21 days or greater. The SIT is comprised of 27 questions utilizing the M.D. Anderson Symptom Inventory tool (MDASI) and validated assessment instrument with 8 questions and a free text box added by CTCA. Symptoms were rated “at the worst” on an 11-point numeric scale ranging from 0 (“no present”) to 10 (“as bad as you can imagine”) in the previous 24 hours. Results: Between 9/1/2014 and 2/27/2015, 842 pts with multiple types of cancer were screened for distress and 435 (51.6%) scored 5 or greater, of which 212 completed a second screening assessment.58 breast cancer pts provided SIT distress scores at baseline and then again at least 23 days after the initial assessment. The average reduction in the distress scores for breast cancer patients was 2 (1st SIT mean = 6.2, 2ndSIT mean = 4.2) with 40 pts (69%) reporting a decrease, 7 pts (12%) having no change, and 11 pts (19%) reporting an increase in distress. The 4 interventions most frequently referred and completed by the pts were mind body therapy (100%), rehabilitation (66%), acupuncture (50%), and massage therapy (45%). Conclusions: Distress is a relevant symptom reported by cancer pts. This study demonstrates that early intervention in breast cancer pts using integrative oncology approaches will reduce the distress in 69% of cases.

A Real Time Control Architecture for Continuously Managing Patients in a Care Unit

1995 ◽  
Vol 34 (05) ◽  
pp. 475-488
Author(s):  
B. Seroussi ◽  
J. F. Boisvieux ◽  
V. Morice
Keyword(s):  
Real Time ◽  
Linear Time ◽  
Treatment Plan ◽  
Control Architecture ◽  
Real Time Control ◽  
Time Representation ◽  
Time Control ◽  
Continuous Support ◽  
Definition Of ◽  
Computerized System

Abstract:The monitoring and treatment of patients in a care unit is a complex task in which even the most experienced clinicians can make errors. A hemato-oncology department in which patients undergo chemotherapy asked for a computerized system able to provide intelligent and continuous support in this task. One issue in building such a system is the definition of a control architecture able to manage, in real time, a treatment plan containing prescriptions and protocols in which temporal constraints are expressed in various ways, that is, which supervises the treatment, including controlling the timely execution of prescriptions and suggesting modifications to the plan according to the patient’s evolving condition. The system to solve these issues, called SEPIA, has to manage the dynamic, processes involved in patient care. Its role is to generate, in real time, commands for the patient’s care (execution of tests, administration of drugs) from a plan, and to monitor the patient’s state so that it may propose actions updating the plan. The necessity of an explicit time representation is shown. We propose using a linear time structure towards the past, with precise and absolute dates, open towards the future, and with imprecise and relative dates. Temporal relative scales are introduced to facilitate knowledge representation and access.

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