Using a pathways process to ensure measurable evidence-based standardized care in a large cancer network.

2012 ◽  
Vol 30 (34_suppl) ◽  
pp. 252-252
Author(s):  
Peter G. Ellis ◽  
Kathleen Lokay
Keyword(s):  
Clinical Trials ◽  
Personalized Medicine ◽  
Clinical Pathways ◽  
Daily Practice ◽  
Evidence Based ◽  
Efficient Treatment ◽  
Treatment Regimens ◽  
Physician Decision Making ◽  
Daily Schedule ◽  
The Individual

252 Background: UPMC CancerCenter includes 40 sites of services in a 100 mile radius in Western Pennsylvania. Consistency and quality of care are critical to such a diverse network. In addition, the UPMC mission includes accrual to clinical trials. To meet these challenges, UPMC developed the Via Oncology Pathways. The program has served UPMC well for over seven years to date and is now a key foundation for UPMC’s overall healthcare reform strategy for quality and accountable care. Methods: Treatment algorithms were developed for 90% of cancer types by establishing committees of academic and community specialists. These committees interpret the literature and define the most efficacious, least toxic, and economically efficient treatment regimens appropriate for highly specific disease presentations (e.g., node +, er-, her2 +, PS 0-1). Clinical trials are also imbedded into the algorithms. Quarterly, these algorithms are reviewed by the committees to assess relevance, review network feedback, add newly available trials and address emerging data. Equally important to clinical content is its presentation to the practicing physician in a manner that allows real time usage and adds value to physician workflow. This is accomplished with a web portal that presents the individual pathways status through the physician’s daily schedule. Results: Over 120 oncologists at UPMC use Via Oncology Pathways in their daily practice. In 2011, UPMC physicians confirmed a pathways status for 94% of their patient visits (195,000) and achieved an On Pathway rate of 82% for their 18,000 treatment decisions. The database also includes patient presentations, reasons for going off pathway and reasons for not accruing to clinical trial. Lower hospitalization rates and mandated adoption of personalized medicine were also observed. Conclusions: When appropriately developed and implemented, clinical pathways are a solution to improving the quality and cost effectiveness of cancer care by enhancing physician decision-making, standardizing care and ensuring access to evidence-based personalized medicine. We continue to expand the scope of our pathways to include diagnostic studies, surveillance protocols and end of life prompts.

Use of radiation pathways to drive standardization of evidence-based care across a large network.

2013 ◽  
Vol 31 (31_suppl) ◽  
pp. 27-27
Author(s):  
Kathleen Lokay
Keyword(s):  
Radiation Treatment ◽  
Clinical Pathways ◽  
Daily Practice ◽  
Surgical Oncology ◽  
Treatment Decisions ◽  
Large Network ◽  
Multiple Cancer ◽  
Daily Schedule ◽  
The Individual ◽  
Evidence Based Care

27 Background: UPMC CancerCenter includes 37 academic and community based sites in western Pennsylvania. Consistency and quality of care are critical to such a diverse network. To meet these challenges, UPMC developed clinical pathways for medical and radiation oncology, now marketed as Via Pathways. The program has served UPMC well for over eight years and is now a key foundation for UPMC’s overall healthcare reform strategy for accountable care. Methods: Radiation treatment algorithms for 90% of cancers were developed by committees of academic and community radiation, surgical, and medical oncologists, with current representation from multiple cancer centers across the country. The committees meet semi-annually to interpret the literature and define the most efficacious and least toxic treatments for highly specific disease presentations (e.g., oropharynx, Stage III-IV, primary chemoradiation). Guidance for contouring, planning and delivery are provided along with applicable citations. Clinical trials open at UPMC sites are also imbedded into the algorithms. Converting these algorithms into measureable decision support is accomplished with a web portal that presents the individual pathways status through the physician’s daily schedule. Results: Thirty-one (31) radiation oncologists at UPMC use Via Pathways in their daily practice. For the 12 months ended May 31, 2013, UPMC physicians confirmed a pathways status for 98% of their patient visits (n=9,400) and achieved an On Pathway rate of 95% for their 5,575 treatment decisions. All off pathway treatment decisions were approved prior to treatment by a designated peer review radiation oncologist within UPMC. Reasons for going off pathway were recorded as well as what alternative approach to care was chosen. Conclusions: When appropriately developed and implemented, clinical pathways are a solution to standardizing care across multiple sites and physicians with the potential to improve the quality and cost effectiveness of cancer care. We continue to expand the scope of Via Pathways to include additional cancer types, surveillance protocols, and end of life prompts as well as surgical oncology pathways.

scholarly journals Learning to Personalize Medicine from Aggregate Data

2020 ◽  
Author(s):  
Rich Colbaugh ◽  
Kristin Glass
Keyword(s):  
Clinical Trials ◽  
Personalized Medicine ◽  
Prediction Models ◽  
Predictive Analytics ◽  
Learning Algorithm ◽  
Individual Characteristics ◽  
Training Data ◽  
Experimental Therapy ◽  
Individual Level ◽  
The Individual

AbstractThere is great interest in personalized medicine, in which treatment is tailored to the individual characteristics of patients. Achieving the objectives of precision healthcare will require clinically-grounded, evidence-based approaches, which in turn demands rigorous, scalable predictive analytics. Standard strategies for deriving prediction models for medicine involve acquiring ‘training’ data for large numbers of patients, labeling each patient according to the outcome of interest, and then using the labeled examples to learn to predict the outcome for new patients. Unfortunately, labeling individuals is time-consuming and expertise-intensive in medical applications and thus represents a major impediment to practical personalized medicine. We overcome this obstacle with a novel machine learning algorithm that enables individual-level prediction models to be induced from aggregate-level labeled data, which is readily-available in many health domains. The utility of the proposed learning methodology is demonstrated by: i.) leveraging US county-level mental health statistics to create a screening tool which detects individuals suffering from depression based upon their Twitter activity; ii.) designing a decision-support system that exploits aggregate clinical trials data on multiple sclerosis (MS) treatment to predict which therapy would work best for the presenting patient; iii.) employing group-level clinical trials data to induce a model able to find those MS patients likely to be helped by an experimental therapy.

A clinical pathways project to promote evidence-based medicine in a large community oncology practice

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 6597-6597
Author(s):  
M. A. Neubauer
Keyword(s):  
Colon Cancer ◽  
Clinical Trials ◽  
Evidence Based Medicine ◽  
Clinical Pathways ◽  
Small Cell ◽  
Evidence Based ◽  
Small Cell Lung ◽  
Treatment Data ◽  
Oncology Practice ◽  
Based Medicine

6597 Background: Medical oncology therapy tends to vary widely due to a large number of drug choices and a wide array of reference sources for decision-making. It is assumed that this high variability reduces quality and efficient delivery of cancer care. We developed clinical pathways for common cancers in which we, after extensive review of seminal literature, distilled a succinct list of evidence- based regimens. We then instructed all physicians at KCCC (26 medical oncologists) to adhere to these pathways or write an exception to the pathway. Exceptions were reviewed by a practice peer-review committee before treatment was initiated. Methods: Included in this analysis is KCCC practice data on treatment choices for ALL patients who were started on treatment or had a change in treatment for breast cancer, non-small cell lung cancer, or colon cancer. All treatments required entry of patient information and staging information on a web-based pathway tool followed by selection of a pathway choice. If a physician preferred “off-pathway” treatment for his/her patient, then an exception sheet with an explanation for off-pathway therapy was submitted and reviewed before treatment. Data was collected from January 1, 2006 through October 31, 2006. The study endpoints were pathway adherence, pathway exception rate, and frequency of accrual to clinical trials. Results: Over a 10 month time period, there were 764, 624, and 326 patients treated for breast, non-small cell lung, and colon cancer, respectively. On-pathway treatment rates were 92.5%, 93.4% and 88.3%. Conversely, exceptions were utilized 7.5%, 6.6% and 11.7% of the time. Rate of accrual to clinical trials was 6.8%, 13.0% and 7.7% for breast, non-small cell lung and colon cancer. Conclusions: Strategies to support and enforce evidence-based medicine in a community based oncology practice can be successful in standardizing care, improving efficiencies, promoting clinical trial enrollment, and developing a practice profile. This pathway project is now being implemented throughout most of the US Oncology network. No significant financial relationships to disclose.

scholarly journals Personalized Medicine Based on Nasal Epithelial Cells: Comparative Studies with Rectal Biopsies and Intestinal Organoids

2021 ◽  
Vol 11 (5) ◽  
pp. 421
Author(s):  
Iris A. L. Silva ◽  
Violeta Railean ◽  
Aires Duarte ◽  
Margarida D. Amaral
Keyword(s):  
Clinical Trials ◽  
Personalized Medicine ◽  
Unmet Need ◽  
Rare Mutations ◽  
Intestinal Organoids ◽  
Bona Fide ◽  
The Individual ◽  
Rectal Biopsies ◽  
Effective Drugs ◽  
Cftr Modulators

As highly effective CFTR modulator therapies (HEMT) emerge, there is an unmet need to find effective drugs for people with CF (PwCF) with ultra-rare mutations who are too few for classical clinical trials and for whom there are no drug discovery programs. Therefore, biomarkers reliably predicting the benefit from CFTR modulator therapies are essential to find effective drugs for PwCF through personalized approaches termed theranostics. Here, we assess CFTR basal function and the individual responses to CFTR modulators in primary human nasal epithelial (pHNE) cells from PwCF carrying rare mutations and compare these measurements with those in native rectal biopsies and intestinal organoids, respectively, in the same individual. The basal function in pHNEs shows good correlation with CFTR basal function in rectal biopsies. In parallel, CFTR rescue in pHNEs by CFTR modulators correlates to that in intestinal organoids. Altogether, results show that pHNEs are a bona fide theranostic model to assess CFTR rescue by CFTR modulator drugs, in particular for PwCF and rare mutations.

scholarly journals Digital Technology in Somatic and Gene Therapy Trials of Pediatric Patients With Ocular Diseases: Protocol for a Scoping Review (Preprint)

2018 ◽  
Author(s):  
Edward Meinert ◽  
Abrar Alturkistani ◽  
Tasnime Osama ◽  
Celine-Lea Halioua-Haubold ◽  
Josip Car ◽  
...  
Keyword(s):  
Gene Therapy ◽  
Clinical Trials ◽  
Personalized Medicine ◽  
Pediatric Patients ◽  
Pediatric Ophthalmology ◽  
Ocular Diseases ◽  
Cell Therapies ◽  
Gene Therapies ◽  
Therapeutic Tools ◽  
The Individual

BACKGROUND Pharmacogenomics suggests that diseases with similar symptomatic presentations often have varying genetic causes, affecting an individual patient’s response to a specific therapeutic strategy. Gene therapies and somatic cell therapies offer unique therapeutic pathways for ocular diseases and often depend on increased understanding of the genotype-phenotype relationship in disease presentation and progression. While demand for personalized medicine is increasing and the required molecular tools are available, its adoption within pediatric ophthalmology remains to be maximized in the postgenomic era. OBJECTIVE The objective of our study was to address the individual hurdles encountered in the field of genomic-related clinical trials and facilitate the uptake of personalized medicine, we propose to conduct a review that will examine and identify the digital technologies used to facilitate data analysis in somatic and gene therapy trials in pediatric patients with ocular diseases. METHODS This paper aims to present an outline for Healthcare Information Technology and Information and Communication Technology resources used in somatic and gene therapy clinical trials in children with ocular diseases. This review will enable authors to identify challenges and provide recommendations, facilitating the uptake of genetic and somatic therapies as therapeutic tools in pediatric ophthalmology. The review will also determine whether conducting a systematic review will be beneficial. RESULTS Database searches will be initiated in September 2018. We expect to complete the review in December 2019. CONCLUSIONS Based on review findings, the authors will summarize methods used for facilitating IT integration in personalized medicine. Additionally, it will identify further research gaps and determine whether conducting further reviews will be beneficial. INTERNATIONAL REGISTERED REPOR PRR1-10.2196/10705

Evidence-based Practice regarding knowledge, attitude and perceived barriers of Mangalore Physical Therapists: A Survey

2020 ◽  
Vol 11 (4) ◽  
pp. 7056-7063
Author(s):  
Vineel P ◽  
Gopala Krishna Alaparthi ◽  
Kalyana Chakravarthy Bairapareddy ◽  
Sampath Kumar Amaravadi
Keyword(s):  
Response Rate ◽  
Evidence Based Practice ◽  
Physical Therapists ◽  
Medical Profession ◽  
Demographic Data ◽  
Perceived Barriers ◽  
Hard Copy ◽  
Evidence Based ◽  
Research Committee ◽  
The Individual

  Evidence-based Practice is defined as usage of current best evidence which is conscientious, explicit and judicious in deciding on the care of the individual. It is one of the vital decision-making processes in the medical profession. Though India is renowned as a center for medical education, there is scarcity regarding the literature on evidence-based practice. The survey aims to identify the prevalence of evidence-based practice among the physical therapists of Mangalore. The study protocol submitted to scientific research committee and Ethical institutional committee, K.M.C. Mangalore Manipal University. On approval, the questionnaire had been distributed among the physical therapists of Mangalore through mails and in the written form. The questionnaire consists of questions divided into eight sections: 1) consent form 2) current practice status; 3) demographic data; 4) behavior; 5) previous knowledge of E.B.P. resources; 6) skills and available resources; 7) Opinions regarding E.B.P.; 8)Perceived barriers regarding E.B.P. The emails were sent through Google forms to all the physical therapists, and hard copies were distributed among the selected physical therapists. The response rate for the emails was 13.1%. The response collected through hard copies was 178, whereas total hard copies distributed was 320, the participants rejected some due to lack of interest. In total, including emails and hard copy questionnaire 205 was the response rate in which all were practicing physical therapy as their primary profession. The findings of the study will pave the way to identify the status of evidence-based practice as well as help in designing promotional programmers for evidence-based practice.

Indacaterol in the Treatment of Chronic Obstructive Pulmonary Disease: From Clinical Trials to Daily Practice

2014 ◽  
Vol 9 (2) ◽  
pp. 96-101
Author(s):  
Cristoforo Incorvaia ◽  
Erminia Ridolo ◽  
Edoardo Riario-Sforza ◽  
Marcello Montagni ◽  
Gian Riario-Sforza
Keyword(s):  
Chronic Obstructive Pulmonary Disease ◽  
Clinical Trials ◽  
Pulmonary Disease ◽  
Daily Practice ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease

In silico modeling of cellular probabilistic nanoparticle radiosensitization in head and neck cancers

Nanomedicine ◽  
2020 ◽  
Vol 15 (29) ◽  
pp. 2837-2850
Author(s):  
Myxuan Huynh ◽  
Ivan Kempson ◽  
Eva Bezak ◽  
Wendy Phillips
Keyword(s):  
Head And Neck ◽  
Patient Outcomes ◽  
Head And Neck Cancers ◽  
New Approach ◽  
Treatment Regimens ◽  
Therapeutic Benefits ◽  
In Silico Modeling ◽  
The Individual ◽  
Dose Deposition ◽  
Therapy Treatment

Background: The use of gold nanoparticles (AuNPs) as radiosensitizers may offer a new approach in the treatment of head and neck cancers; minimizing treatment-associated toxicities and improving patient outcomes. AuNPs promote localized dose deposition; permitting improved local control and/or dose reduction. Aim: This work aimed to address the theoretical optimization of radiation doses, fractionation and nanoparticle injection schedules to maximize therapeutic benefits. Materials & methods: Probabilistic nanoparticle sensitization factors were incorporated into the individual cell-based HYP-RT computer model of tumor growth and radiotherapy. Results: Total dose outcomes across all radiation therapy treatment regimens were found to be significantly reduced with the presence of AuNPs, with bi-weekly injections showing the most decrease. Conclusion: Outcomes suggest the need for regular AuNP administration to permit effective radiosensitization.

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