Alexis B. Guzman

Using Time-Driven Activity-Based Costing to Identify Value Improvement Opportunities in Healthcare

EXECUTIVE SUMMARY As healthcare providers cope with pricing pressures and increased accountability for performance, they should be rededicating themselves to improving the value they deliver to their patients: better outcomes and lower costs. Time‐driven activity‐based costing offers the potential for clinicians to redesign their care processes toward that end. This costing approach, however, is new to healthcare and has not yet been systematically implemented and evaluated. This article describes early time‐driven activity‐based costing work at several leading healthcare organizations in the United States and Europe. It identifies the opportunities they found to improve value for patients and demonstrates how this costing method can serve as the foundation for new bundled payment reimbursement approaches.

Using Quality Improvement Methods and Time-Driven Activity-Based Costing to Improve Value-Based Cancer Care Delivery at a Cancer Genetics Clinic

PURPOSE To meet increasing demand for cancer genetic testing and improve value-based cancer care delivery, National Cancer Centre Singapore restructured the Cancer Genetics Service in 2014. Care delivery processes were redesigned. We sought to improve access by increasing the clinic capacity of the Cancer Genetics Service by 100% within 1 year without increasing direct personnel costs. METHODS Process mapping and plan-do-study-act (PDSA) cycles were used in a quality improvement project for the Cancer Genetics Service clinic. The impact of interventions was evaluated by tracking the weekly number of patient consultations and access times for appointments between April 2014 and May 2015. The cost impact of implemented process changes was calculated using the time-driven activity-based costing method. RESULTS Our study completed two PDSA cycles. An important outcome was achieved after the first cycle: The inclusion of a genetic counselor increased clinic capacity by 350%. The number of patients seen per week increased from two in April 2014 (range, zero to four patients) to seven in November 2014 (range, four to 10 patients). Our second PDSA cycle showed that manual preappointment reminder calls reduced the variation in the nonattendance rate and contributed to a further increase in patients seen per week to 10 in May 2015 (range, seven to 13 patients). There was a concomitant decrease in costs of the patient care cycle by 18% after both PDSA cycles. CONCLUSION This study shows how quality improvement methods can be combined with time-driven activity-based costing to increase value. In this paper, we demonstrate how we improved access while reducing costs of care delivery.

Value based care and bundled payments: Anesthesia care costs for outpatient oncology surgery using time-driven activity-based costing

BACKGROUND With the movement towards bundled payments, stakeholders should know the true cost of the care they deliver. Time-driven activity-based costing (TDABC) can be used to estimate costs for each episode of care. In this analysis, TDABC is used to both estimate the costs of anesthesia care and identify the primary drivers of those costs of 11 common oncologic outpatient surgical procedures. METHODS Personnel cost were calculated by determining the hourly cost of each provider and the associated process time of the 11 surgical procedures. Using the anesthesia record, drugs, supplies and equipment costs were identified and calculated. The current staffing model was used to determine baseline personnel costs for each procedure. Using the costs identified through TDABC analysis, the effect of different staffing ratios on anesthesia costs could be predicted. RESULTS Costs for each of the procedures were determined. Process time and costs are linearly related. Personnel represented 79% of overall cost while drugs, supplies and equipment represented the remaining 21%. Changing staffing ratios shows potential savings between 13% and 28% across the 11 procedures. CONCLUSIONS TDABC can be used to estimate the costs of anesthesia care. This costing information is critical to assessing the anesthesiology component in a bundled payment. It can also be used to identify areas of cost savings and model costs of anesthesia care. CRNA to anesthesiologist staffing ratios profoundly influence the cost of care. This methodology could be applied to other medical specialties to help determine costs in the setting of bundled payments.

Development and Feasibility of Bundled Payments for the Multidisciplinary Treatment of Head and Neck Cancer: A Pilot Program

PURPOSE Despite growing interest in bundled payments to reduce the costs of care, this payment method remains largely untested in cancer. This 3-year pilot tested the feasibility of a 1-year bundled payment for the multidisciplinary treatment of head and neck cancers. METHODS Four prospective treatment-based bundles were developed for patients with selected head and neck cancers. These risk-adjusted bundles covered 1 year of care that began with primary cancer treatment. Manual processes were developed for patient identification, enrollment, billing, and payment. Patients were prospectively identified and enrolled, and bundled payments were made at treatment start. Operational metrics tracked incremental effort for pilot processes and average payment cycle time compared with fee-for-service (FFS) payments. RESULTS This pilot confirmed the feasibility of a 1-year prospective bundled payment for head and neck cancers. Between November 2014 and October 2016, 88 patients were enrolled successfully with prospective bundled payments. Through September 2017, 94% of patients completed the pilot with 6% still enrolled. Manual pilot processes required more effort than anticipated; claims processing was the most time-consuming activity. The production of a bundle bill took an additional 15 minutes versus FFS billing. The average payment cycle time was 37 days (range, 15 to 141 days) compared with a 15-day average under FFS. CONCLUSION Prospective bundled payments were successfully implemented in this pilot. Additional pilots should study this payment method in higher-volume cancers. Robust systems are needed to automate patient identification, enrollment, billing, and payment along with policies that reduce administrative burden and allow for the introduction of novel cancer therapies.

Assessing the cost of cancer care delivery using a time-driven, activity-based costing software.

25 Background: Poor costing systems and measurement have led to cross-subsidies and cost-shifting in health care. A large academic cancer center has adopted Robert Kaplans bottom-up cost accounting methodology called time-driven, activity-based costing (TDABC). TDABC in health care has been proven to be an effective cost accounting tool to measure and improve care delivery by standardizing and creating transparency around patient care processes. The project aims to process map and identify event triggers associated with each process map, use a software applications to compute the costs and resource capacities. METHODS Information technology and financial subject-matter experts integrated clinical, resource, and financial data from the institutions enterprise information warehouse, general ledger, resource and asset management systems into the software application. Clinical business managers, nurse managers and other clinical content experts helped identify patient-level care processes. RESULTS The institution deployed a project team to integrate data from the institutions enterprise information warehouse and aid in the process mapping across three multidisciplinary care centers. The team was able to successfully cost both direct and overhead costs associated with 69 head and neck, 18 endocrine, and 15-20 proton therapy patient-level processes over 7 different business department within 7 months. The resource capacity analysis was the most difficult to analyze due of the lack of transparency around resources clinical, administrative, and research responsibilities. Dashboards are currently being developed to help assess changes in patient care processes, cost or resource utilization. CONCLUSIONS This methodology can be used across all health care organizations in all countries to analyze the true cost of care delivery.

Measuring value in bundled payments for head and neck cancer.

11 Background: Value, defined as outcomes relative to costs, cannot be improved without rigorous long-term measurement. To assess value within a bundled payment pilot for head and neck cancer, we aim to generate timely, patient-centered outcomes and robust, near-real time financial tracking (Porter and Teisberg, Redefining health care. Creating value-based competition on results; Harvard Business School Press, 2006). METHODS Clinical and quality experts created an outcome measure set for head and neck cancer, using a three-tiered outcomes hierarchy from Michael Porter of Harvard Business School as a framework. Process measures were identified to evaluate compliance with standards of care. Data sources were verified and patient-reported outcomes were collected via a patient portal. A REDCap database was created to aggregate all longitudinal outcomes. The project managers and financial leaders identified key financial metrics to be tracked for enrolled patients. Outcomes and financial data were built into a dashboard to deliver timely, actionable information on value. Patients will be tracked for 2 years post-treatment completion. RESULTS 22 outcome measures and 6 process measures are being collected for all enrolled patients. Financial indicators, such as cumulative costs and fee-for-service payment vs. bundled payment, are being tracked for each patient. Currently, most outcomes and financial data are extracted manually. Implementation of a new electronic health record (EHR) should alleviate much of this administrative burden (Table). CONCLUSIONS The project demonstrates the feasibility of value measurement for bundled payment. With provider and patient input, the outcome measures direct attention to what is important to patients and is actionable by clinicians. Additionally, near real-time financial tracking offers insights into the financial implications of this alternative payment model for cancer care. With automation via the EHR, this value measurement methodology can be scaled for other disease sites and additional payers. [Table: see text].

Proof-of-concept: A working demonstration of real-time patient tracking using time-driven activity-based costing.

28 Background: Historically, hospital costs are based on a cost-to-charge ratio. The current cost system determines when a charge is filed and a bill is created, which can be days following the patient visit. This time lag between the patient visit and the billed charges can be problematic. In preparation for episode-based payments, it is essential to know the true cost of care at the time of delivery. To accomplish this goal, the University of Texas MD Anderson Cancer Center (MDACC) leveraged existing time-driven activity-based costing (TDABC) process maps to track the true costs of the patient care cycle. METHODS The first steps were to understand the patient care cycle through process mapping. Next, data sources were identified to capture patient volumes. Process maps were adjusted to capture the data sources and provide a more accurate cost. Trigger logic models were created to link data sources and the TDABC process maps to the true cost for each patient appointment. Lastly, we developed a SAS software program to compute the real-time TDABC costs for 50 patients in the Head & Neck Center. RESULTS Our existing data sources capture information relevant to TDABC on a regular basis. Patient appointment data provided the patient visit, and billing and time data provided approximations of the amount of time spent in the encounter and the number of resources involved in the patient visit. Out of 219 process maps, 148 (70%) were matched to existing patient appointment and charge data using the trigger logic. This allowed us to track 4,980 patient appointments for 50 patients in fifteen minutes. CONCLUSIONS As data are collected throughout the institution, it is realized that multiple data sources are needed to reconcile the patients experience and to match the TDABC process maps to existing data sources. Since our data sources are updated daily and are based on a patients date of service, we can capture our costs of delivering care close to real-time. This process is continually refined as additional data sources are made available and as process maps are developed in other parts of MDACC.

A patient-centered outcome measurement approach for bundled payments in cancer care.

266 Background: The project aims are to: 1) apply a patient-centered approach to evaluate quality of care in a bundled payment pilot for head & neck cancer; and, 2) measure quality at the condition-level; and, 3) incorporate patient-reported outcomes (PRO) in routine quality assessments. A three-tiered outcomes hierarchy developed by Michael Porter of Harvard Business School is used to define outcome measures, to be used for quality improvement and reporting during the pilot. Porters model evaluates outcomes over the full cycle of care, examining: (1) health status achieved/retained; (2) recovery process; and, (3) health sustainability. [Porter, M.E. (2010). What is value in health care? N Engl J Med, 363(26), 2477-2481. doi: 10.1056/NEJMp1011024.] Methods: An 11-member team of clinical, quality, data, and IT experts identified measure concepts, developed measure specifications, and implemented reporting. The project lead interviewed clinical experts to gain consensus around a focused set of measures and benchmarks. Measures were evaluated for importance to patients using feedback from patient focus groups. The team defined the measure specifications (numerator, denominator, etc.), selected a validated PRO instrument, and developed the work flow and tools for data collection and reporting. Process maps were created for training and reference purposes, and clinic staff trained. Testing was completed prior to implementation, with periodic process checks and additional staff training, as needed. RESULTS Measure development and implementation were completed using a streamlined approach over a 6-month period and required 12 team meetings before implementation. The project leveraged existing data streams, where possible, and IT development focused on quick-turnaround solutions. CONCLUSIONS The project demonstrated that patient-centered outcomes measures can be developed and implemented in a compressed time frame. With provider and patient input, the measures focused on outcomes that are important to patients and actionable by clinicians. This created a scalable framework to be implemented in other disease sites and integrated into our EHR.