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Primary Care: Developing An Efficiency Decision Guide (work in progress) AHRQ ANNUAL CONFERNECE (September 28, 2010) A Report from SNOCAP-USA Contract Number: HHSA290200710008 (July 2009 through December 2010) Dr. Michael Harrison: Task Order Officer . University of Colorado
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Primary Care: Developing An Efficiency Decision Guide(work in progress)AHRQ ANNUAL CONFERNECE (September 28, 2010)A Report from SNOCAP-USAContract Number: HHSA290200710008 (July 2009 through December 2010)Dr. Michael Harrison: Task Order Officer
University of Colorado School of Medicine Colorado Health Outcomes Program (COHO) I have no financial relationships to disclose and I will not discuss off label use and/or investigational use in my presentation Disclosure Information:Presenter: David R. West, PhD
Session Objective • To provide participants with information regarding current gaps in evidence for process improvement in primary care and the insights gained, to date, through research into the major contributors to primary care practice efficiency.
Exploring Ways to Improve Efficiency in Primary CareSNOCAP-USA Team: AHRQ Task Order • Kathy James, PhD • Betsy Vance, MPH • Steven Ross, MD • Tiffany Radcliff, PhD • David R. West, PhD (Task Order Leader) • Acknowledgement: Thanks to MGMA
Specific Aims • Review, Summarize and understand the current literature regarding efficiency in primary care • Understand how primary care practices think about and implement efficiency measures, and factors associated with efficiency/inefficiency in these practices (in depth in Colorado, and phone interviews) • Develop and test an “efficiency” decision-guide for use in primary care practice
Literature Scan Defining Inefficiency Waste: 1) Brent James’ definition of inefficiency waste as “using more inputs than is necessary to produce a unit of care to benefit patients, and has strong linkages to the design of care systems”(James and Bayley 2006), and 2) Litvak’s definition of inefficiency waste as variation and lack of standardization of processes in the practice setting, including clinical variation (i.e., variation in the care provided), flow variation (i.e., variation in the demand for healthcare), and professional variation (i.e., variation amongst providers(Litvak, Buerhaus, et al. 2005).
Factors [Reported to be] Associated with Inefficiency Waste in Primary Care: • Practice processes, including improved practice work flow, patient flow, and physical configuration, • Electronic modes of communication amongst practice personnel and with patients, • Improved coding to increase reimbursement, • Computerized physician order entry (CPOE), • The use of the EHR as a tool to address nearly all of the above listed factors, and • Practice size and complexity
Tools and Measures for Addressing Inefficiency Waste: • Moving historically from continuous quality improvement (CQI) and total quality management (TQM), to Six Sigma and Lean; these techniques have applicability (and a track record) for use in measuring inefficiency waste and tracking the improvement of practice/clinic/organization operations in primary care settings.
Secondary Data from MGMA “Cost Survey” • Information provided by hundreds of practices that responded to the annual survey from MGMA – slightly under 300 defined as primary care (FM/GIM) – not solo, and not multi-specialty • Includes data elements such as: • Fiscal year revenue • Costs (fixed and variable – e.g., labor, lease, supplies) • Inputs (including types of labor and capital), and • Outputs (productivity measures - relative value units, visits per year).
Preliminary Econometric Models and ResultsEconometric Analyses and Results Preliminary multiple regression analyses predict efficiency (RVUs and Net Operating cost) outcomes using other practice characteristics as the independent variables • Rural location of practices was associated with lower operating costs • Average costs per billing provider and total number of physician FTE’s were directly related to both higher operating costs and RVU’s • Non-physician providers, when included in practices, had some association with higher practice RVU’s
DEA Analysis (input-oriented, variable returns to scale (VRS) ) • DEA model input-oriented, variable returns to scale (VRS) – provides an “efficiency” score to divide “efficient from inefficient practices” using numerous variables. Used to select practices for follow-up study • Sample size for the DEA was 283 practices • DEA identified 19 of the 117 practices as “efficient”
Primary Data Collection • Colorado Practices • MGMA Practices
Practice Engagement Questions Adoption: 1) when did the topic of redesign initially arise? 2) key people inside and outside the clinic responsible for adoption? 3) technical and administrative challenges (including costs of lost productivity and opportunity costs) faced in adoption? Current use: 1) how redesign is currently integrated into clinical practice? 2) frequency of use? 3) variability of use among providers?
Practice Engagement Questions Perceived/Realized benefits of current use: 1) organizational costs and benefits? 2) improvements in the quality of care? 3) improvements in the safety of care? 4) improvements in the efficiency of care? 5)changes in culture? Future of redesign: What additional functions/data sources could provide additional practice value in the future?
FINDINGS • Understanding of Processes that Surround the Patient Visit • Pre-Visit Processes • During Visit Processes • Post-Visit Processes • A Desire for Self- Assessment and Improvement • There are Barriers to Achieving Efficiencies in Primary Care Practices
PRE VISIT PROCESSES Appointments/Scheduling • Problems • Maximizing capacity • Dealing with patient “no shows” • Solutions • Mixture of Open access and traditional scheduling processes • Remedial Actions/patient consequences
PRE VISIT PROCESSES Telephone • Patient phone calls are common struggle: • Volume of phone calls some clinics receive can cause an inability of staff that handles phone calls (generally the front desk) • Patients may not be able to get through and/or experience long hold times • Solutions Include: • Call Centers • Electronic call systems
PRE VISIT PROCESSES Insurance Eligibility Verification • A critically important but time consuming process with various processes for: • Medicaid and CHP+ • Medicare • Private Insurance • Solutions include electronic and automated verification systems
VISIT PROCESSES Patient flow during a visit • Observed Problems with layout • Opportunities for bottlenecks – particularly check in and check out • Lack of standardization of exam room layout and patient flow to and from exam room • Solutions • Standardization of Exam room layout and inventory control • Use of “PODS” for streamlining flow and removing bottlenecks (in larger sites)
VISIT PROCESSES Hierarchy/Staffing/Team Concept • Problems with: • Defining roles/standardizing roles and responsibilities, maximizing staff capabilities, and off-loading tasks from clinicians • Physician “buy-in” to delegation of tasks • Communication
VISIT PROCESSES Solutions: • Primary Health Care Team models • Communication tools and huddles to inform team/work together more effectively • Improve Patient Experience and Practice Productivity with Group Visits • Concerns about patient buy in • Lack of information/uncertainty about insurance reimbursement
POST VISIT/IN BETWEEN VISITS • Medication Refills • Coding and Billing • Diagnostic Test • Ordering • Tracking • Incorporation into care plans • Communicating to patient
SOME IMPORTANT LESSONS The competing demands for time and resources within practices must be taken into account when developing a strategy to improve efficiency. Both practice leaders and staff must learn to collaborate and co-evolve together to assure an understanding of the models/processes of care to be implemented, and to assure buy-in to the model.
The comprehensive change of process in practice can be daunting and expensive. However, meaningful change can occur by identifying everyday problems and by implementing common sense solutions. Solutions implemented can evolve over time, as needed.
NEXT STEPS • Draft the Decision Guide • Pilot Test the Decision Guide • Final Deliverable to AHRQ