- Email: [email protected]
Using Referral Data Analysis to Drive Quality Improvement (QI)
Abstracts / Biol Blood Marrow Transplant 23 (2017) S18–S391
based on our optimized schedule (middle), and the actual utilization after implementation for July to September 2016 (right). The post-implementation average utilization is 80.7%. In addition, the hospital increases its daily capacity by 30% with no weekend overtime. Discussion: We will expand to improve clinical efficiency for other BMT patients. As the clinical team is expanding their service, the system process maps will be updated accordingly. Schedules and resources will be optimized efficiently for the new site. Clinical data, treatment history, and attributes associated with demographics and risk factors are currently analyzed. Machine learning will be performed to uncover characteristics to be incorporated into the global system for optimizing LOS and reducing readmission. Utilization and outcome data will be collected to monitor clinical service performance and potential overall impacts.
473 Using Referral Data Analysis to Drive Quality Improvement (QI) Richard Lex 1, Jose Carlos Cruz 2. 1 Blood and Marrow Transplant Program, Methodist Hospital, San Antonio, TX; 2 Adult Blood and Marrow Transplant, Texas Transplant Institute, San Antonio, TX Our transplant program serves a large geographic and varied community of patients and physicians in South Texas. Before 2015, we had no central data capture of patient referrals. We had anecdotal understanding of referral patterns, but no big data analysis of patient demographics useful in understanding dynamics within our markets and opportunities to improve patient care. We identified opportunities to enhance patient access, physician relationships, and survival outcomes through analysis of referral patterns. We built an internal database, using an Excel platform, capable of interacting with existing transplant logs and databases. We aligned Core-based Statistical Area (CBSA) mapping with our key market areas and constructed a zip code database to drive data pivots linked with patient and physician demographics, by city, within targeted markets. Key data points include: referral/consult dates, disease, transplant continuum status, transplant date, and payer mix. Today, our referral database pivots data to support program operations and quality. We track patient and disease patterns to identify trends within our local and outreach markets, providing data for strategic planning. Recognizing a downward trend in our door times we identified obstacles effecting patient access and time to transplantation. This year we are implementing processes to improve door times, particularly for outreach patients, Spanish speaking patients, and patient/families needing housing support. To analyze transplant survival outcomes, we track patient and disease migration trends, enabling us to recognize patterns that are market and payer mix specific. Trends are reported and analyzed in our quarterly committees to guide our QI and program development strategy.
474 Using Mobile Applications to Enhance Patient Safety in HSCT Deborah Liney, Roger Richard. Dana Farber Cancer Institute, Boston, MA Stem cell transplantation has evolved over the last 20 years leading to conditioning regimens and GVHD prophylaxis tailored to each graft and recipient profile, to create the optimum
S341
therapy and reduce treatment related mortality. One consequence of personalized medicine is a larger body of standard of care regimens and clinical research protocols. Our transplant program currently has 34 standard-of-care regimens in addition to 4 transplant protocols and 9 ancillary protocols for the treatment of GVHD, KIR typing and posttransplant immunotherapy. Many of these standard regimens are constructed using the same conditioning drugs with variations on the frequency of administration or associated GVHD prophylaxis. Selection and administration of the correct plan is imperative to patient care and safety. In a large academic HSCT program, such as ours, patients are treated by residents, house staff, fellows, PA, hospitalists, and nocturnists as well as attending physicians. Ensuring that staff are aware of the nuances of each regimen is challenging. Errors such as random dose adjustment and GVHD prophylaxis drug omission have occurred. While the schemas for all plans are listed on an internal website, accessing the information through this avenue is cumbersome and requires the practitioner to toggle back and forth between screens and programs. This is further complicated if the patient / clinician meeting takes place where there is no available bedside computer access. To help eliminate these issues and create an additional layer of patient safety, a mobile application was developed. The App (DFCI HSCT) enables practitioners to have access to the treatment plan administration instructions and protocol eligibility checklists at their fingertips since all staff members carry smart phones. Access to the DFCI HSCT App is by permission only. The app is password protected and all cell phones used for hospital business are encrypted. The treatment plan links mirror the website specificity, giving the schema, dosing and concurrent medications or hydration instructions for the conditioning regimens, GVHD prophylaxis, and GCSF timing. In addition, the app provides tools such as an ideal body weight calculator and an email link to quality assurance for questions. Security and access issues were vetted through the institution’s IT and Legal departments to ensure compliance. Since no patient personal health information is accessed or saved to the app, HIPPA concerns are avoided. Document management requirements must still be considered to ensure that only approved plans or protocols are accessed and that intellectual property is protected. Having this application available to all staff will enhance patient safety by providing an easy method for accessing treatment procedures.
based on our optimized schedule (middle), and the actual utilization after implementation for July to September 2016 (right). The post-implementation average utilization is 80.7%. In addition, the hospital increases its daily capacity by 30% with no weekend overtime. Discussion: We will expand to improve clinical efficiency for other BMT patients. As the clinical team is expanding their service, the system process maps will be updated accordingly. Schedules and resources will be optimized efficiently for the new site. Clinical data, treatment history, and attributes associated with demographics and risk factors are currently analyzed. Machine learning will be performed to uncover characteristics to be incorporated into the global system for optimizing LOS and reducing readmission. Utilization and outcome data will be collected to monitor clinical service performance and potential overall impacts.
473 Using Referral Data Analysis to Drive Quality Improvement (QI) Richard Lex 1, Jose Carlos Cruz 2. 1 Blood and Marrow Transplant Program, Methodist Hospital, San Antonio, TX; 2 Adult Blood and Marrow Transplant, Texas Transplant Institute, San Antonio, TX Our transplant program serves a large geographic and varied community of patients and physicians in South Texas. Before 2015, we had no central data capture of patient referrals. We had anecdotal understanding of referral patterns, but no big data analysis of patient demographics useful in understanding dynamics within our markets and opportunities to improve patient care. We identified opportunities to enhance patient access, physician relationships, and survival outcomes through analysis of referral patterns. We built an internal database, using an Excel platform, capable of interacting with existing transplant logs and databases. We aligned Core-based Statistical Area (CBSA) mapping with our key market areas and constructed a zip code database to drive data pivots linked with patient and physician demographics, by city, within targeted markets. Key data points include: referral/consult dates, disease, transplant continuum status, transplant date, and payer mix. Today, our referral database pivots data to support program operations and quality. We track patient and disease patterns to identify trends within our local and outreach markets, providing data for strategic planning. Recognizing a downward trend in our door times we identified obstacles effecting patient access and time to transplantation. This year we are implementing processes to improve door times, particularly for outreach patients, Spanish speaking patients, and patient/families needing housing support. To analyze transplant survival outcomes, we track patient and disease migration trends, enabling us to recognize patterns that are market and payer mix specific. Trends are reported and analyzed in our quarterly committees to guide our QI and program development strategy.
474 Using Mobile Applications to Enhance Patient Safety in HSCT Deborah Liney, Roger Richard. Dana Farber Cancer Institute, Boston, MA Stem cell transplantation has evolved over the last 20 years leading to conditioning regimens and GVHD prophylaxis tailored to each graft and recipient profile, to create the optimum
S341
therapy and reduce treatment related mortality. One consequence of personalized medicine is a larger body of standard of care regimens and clinical research protocols. Our transplant program currently has 34 standard-of-care regimens in addition to 4 transplant protocols and 9 ancillary protocols for the treatment of GVHD, KIR typing and posttransplant immunotherapy. Many of these standard regimens are constructed using the same conditioning drugs with variations on the frequency of administration or associated GVHD prophylaxis. Selection and administration of the correct plan is imperative to patient care and safety. In a large academic HSCT program, such as ours, patients are treated by residents, house staff, fellows, PA, hospitalists, and nocturnists as well as attending physicians. Ensuring that staff are aware of the nuances of each regimen is challenging. Errors such as random dose adjustment and GVHD prophylaxis drug omission have occurred. While the schemas for all plans are listed on an internal website, accessing the information through this avenue is cumbersome and requires the practitioner to toggle back and forth between screens and programs. This is further complicated if the patient / clinician meeting takes place where there is no available bedside computer access. To help eliminate these issues and create an additional layer of patient safety, a mobile application was developed. The App (DFCI HSCT) enables practitioners to have access to the treatment plan administration instructions and protocol eligibility checklists at their fingertips since all staff members carry smart phones. Access to the DFCI HSCT App is by permission only. The app is password protected and all cell phones used for hospital business are encrypted. The treatment plan links mirror the website specificity, giving the schema, dosing and concurrent medications or hydration instructions for the conditioning regimens, GVHD prophylaxis, and GCSF timing. In addition, the app provides tools such as an ideal body weight calculator and an email link to quality assurance for questions. Security and access issues were vetted through the institution’s IT and Legal departments to ensure compliance. Since no patient personal health information is accessed or saved to the app, HIPPA concerns are avoided. Document management requirements must still be considered to ensure that only approved plans or protocols are accessed and that intellectual property is protected. Having this application available to all staff will enhance patient safety by providing an easy method for accessing treatment procedures.