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Assessing the productivity of advanced practice providers using a time and motion study.

EXECUTIVE SUMMARY

The Resource-Based Relative Value Scale is widely used to measure healthcare provider productivity and to set payment standards. The scale, however, is limited in its assessment of pre- and postservice work and other potentially non-revenue-generating healthcare services, what we have termed service-valued activity (SVA). In an attempt to quantify SVA, we conducted a time and motion study of providers to assess their productivity in inpatient and outpatient settings.

Using the Standard Time and Motion Procedures checklist as a methodological guide, we provided personal digital assistants (PDAs) that were prepopulated with 2010 Current Procedural Terminology codes to 19 advanced practice providers (APPs). The APPs were instructed to identify their location and activity each time the PDA randomly alarmed. The providers collected data for 3 to 5 workdays, and those data were separated into revenue-generating services (RGSs) and SVAs. Multiple inpatient and outpatient departments were assessed. The inpatient APPs spent 61.6 percent of their time on RGSs and 35.1 percent on SVAs. Providers in the outpatient settings spent 59.0 percent of their time on RGSs and 38.2 percent on SVAs.

This time and motion study demonstrated an innovative method and tool for the quantification and analysis of time spent on revenue- and non-revenue-generating services provided by healthcare professionals. The new information derived from this study can be used to accurately document productivity, determine clinical practice patterns, and improve deployment strategies of healthcare providers.

INTRODUCTION

In 1989, the Physician Payment Review Commission (PPRC) drafted a report for the LI.S. Congress highlighting the need to reform the way in which the Centers for Medicare & Medicaid Services provides payments to physicians. The recommendations centered on the implementation of the Resource-Based Relative Value Scale (RBRVS) (PPRC, 1989). This scale assigns a relative value unit (RVU) to patient care services delivered by healthcare providers. Since the introduction of the scale, RVUs have become a primary method of payment and productivity assessment of health services in the United States (Bergman, 2003). Although it has been extensively studied and determined to be successful in setting payment standards (Bergman, 2003; Committee on Coding, 2008), the RBRVS system has encountered criticism and its application has demonstrated some limitations (Maloney, 1995; Zweifel and Tai-Seale, 2009; Martin et al., 2010; Eggleston, 2005).

In particular, the scale is limited in its assessment of preservice and postservice work and other potentially nonrevenue-generating healthcare services. Dunn, Hsiao, Ketcham, & Braun (1988) describe preservice and postservice as various fragmented, intermingled activities that take place in addition to the total work of a physician. According to Dunn et al. (1988), preservice activities include review of records and professional and family member communication, while postservice work includes documentation of service, observations, development of treatment plans with other professionals, and postprocedure communication with family members. Pre- and postservice activities have been referenced by lacobson et al. (2011) as an influencing factor in determining work intensity of physicians. They indicated that pre- and postservice activities, such as filling prescriptions, interacting with other providers and staff, reviewing records, and making appointments and referrals, are nonbillable actions that contribute to the overall work of physicians and should be taken into account when measuring work intensity. As primary investigators of pre- and postservice work, Dunn et al. identified similar nonbillable activities during the developmental stages of the RBRVS system. In the development of the RBRVS system, the researchers poorly estimated that the added values assigned to pre- and postservice activities were due to the extreme fragmentation and variability of those services. In fact, Dunn et al. alluded to the difficulty in estimating pre- and postservice activities for each service. For the purposes of this article, we refer to such pre- and postservices and other related activities as service-valued activity (SVA).

In an attempt to quantify SVA, we conducted a productivity assessment through a time and motion study of healthcare providers to identify time spent on revenue-generating services (RGSs) and SVAs in an inpatient and outpatient setting. A secondary outcome of the study was to identify the administrative and organizational impact of the time spent on SVAs by the providers. Ultimately, results of this study can be used to develop a supplemental model of productivity assessment that focuses on SVAs by assigning a unit of measure to complement the RBRVS system. This supplement should help payers to comprehensively measure the productivity of a healthcare provider in the delivery of services to patients. We submit that a comprehensive assessment of patient healthcare services should include an accurate measurement of both RGSs and SVAs.

METHODOLOGY

A time and motion study (Hendrich, Chow, Skierczynski, & Lu, 2008) of advanced practice providers (APPs) composed of physician assistants and nurse practitioners was conducted at Henry Ford Hospital in Detroit, Michigan. The hospital, part of the seven-hospital Henry Ford Health System (HFHS), is an inner-city tertiary academic medical center. HFHS also includes Henry Ford Medical Group, which employs approximately 1,200 physicians and 400 APPs in various medicine and surgical specialties. The time and motion study design was based on the Standard Time and Motion Procedures (STAMP) checklist (Zheng, Guo, & Hanauer, 2011). (1) The checklist used in this study outlines the multiple variables used in the various study settings, design, execution, and analysis. STAMP's 9 main categories of procedures--intervention, empirical setting, research design, task category, observer, subject, data recording, data analysis, and ancillary data--focus on subject identification, randomization, data collection, and data analysis. We used the STAMP checklist to capture and organize the data collection process.

The goals of this study were to assess the daily responsibilities of APPs and quantify the time spent on medical and surgical services delivered to patients; individual patients and their disease-specific conditions were not assessed. The APPs were chosen on the basis of well-established practice patterns indicating a high degree of exposure to the delivery of a variety of services, many of which could be considered SVAs (Nyberg, Keuter, Berg, Helton, & Johnston, 2010; Moote, Krsek, Kleinpell, & Todd, 2011), and represented multiple medical and surgical subspecialties and points of service (inpatient [IP] and outpatient [OP]). An assessment of emergency department (ED) and obstetric (OB) services was conducted to determine which were SVAs, and the findings were consistent with those seen in the inpatient and outpatient provider assessments (Figure 1). The ED and OB results are not presented in this article.

All study participants were provided handheld personal digital assistants (PDAs) that were prepopulated with evaluation and management and non-procedure-based healthcare service codes as defined by the American Medical Association's 2010 Current Procedural Terminology (CPT). The prepopulated codes were those commonly found in the specific points of service shown in Tables 1 and 2 and were preprogrammed to randomly alarm every 15 to 30 minutes. The providers were instructed to check off their location and main activity from among the PDA's coded services at the time the alarm sounded. The providers assumed the use of the PDAs from the beginning of their shift to the end of their workday. The PDAs were distributed to the selected APPs daily, and each provider collected data for 3 to 5 days. At any given time during the study, at least three providers were participating simultaneously. The data were then divided into RGSs and SVAs and aligned with the appropriate CPT codes (see Tables 1 and 2). We further defined SVAs as non-revenue-generating healthcare services delivered to patients that consume time, expense, and expertise but are not allocated an RVU equivalent.

The primary purpose of the study was to quantify the time spent by the providers on RGSs and SVAs. A secondary purpose was to identify the impact of SVAs on administrative and organizational processes, including assessing the variances of RGSs and SVAs between the points of service and within the individual inpatient and outpatient departments. Descriptive statistics and chi-square analysis were used for data analysis.

RESULTS

Nineteen APPs (13 nurse practitioners [NPs] and 6 physician assistants [PAs]) collected 44 days' worth of data for a total of 1,498 data points (Tables 1 and 2). Of the total data point occurrences, 60.3 percent (903) were RGSs, 36.7 percent (550) were SVAs, and 3 percent (45) accounted for personal time.

Inpatient Services

Inpatient services were represented by 5 NPs and 3 PAs from acute care/general surgery, transplant surgery, hematology/ oncology, and nephrology. Overall, the inpatient APPs spent 61.6 percent of their time on RGSs and 35.1 percent on SVAs (Figure 2). The two most common RGSs delivered by the providers were subsequent hospital care (CPT 99231-99233) and discharge management (CPT 99238-99239), accounting for 33.6 percent and 15.9 percent of their time, respectively, while admission history and physical (CPT 99221-99233) accounted for 4.12 percent of their time delivering RGSs. In contrast, the most common SVA identified was attending and participating in team conferences (CPT 99366-99368), occurring 15.6 percent of the time, whereas analysis of data (CPT 99090), telephone consultations (CPT 98966-98968), and special report (CPT 99080) accounted for 7.54 percent, 3.43 percent, and 3.29 percent of their time, respectively (Table 2). A statistically significant difference was found between inpatient time spent on RGSs and SVAs within the specific departments ([c.sup.2] = 27.610, p < .01) (see Figure 2).

Outpatient Services

Those performing outpatient services were represented by 8 NPs and 3 PAs from internal medicine, orthopedics, the pain clinic, and transplant services. In total, the outpatient providers spent 59.0 percent of their time on RGSs and 38.2 percent on SVAs (Figure 3). The two most common RGSs provided by the APPs were new office visits (CPT 99201-99201) and follow-up (CPT 99211-99215), accounting for 31.9 percent and 10.6 percent of their time, respectively. Documentation of visits and procedures accounted for 14.1 percent of the time spent on RGSs. The most common SVA identified was analysis of clinical data (CPT 99090), at 17.8 percent, followed by team conferences (CPT 99366) and telephone consults (CPT 99211-99215), at 4.29 percent and 4.03 percent of their time, respectively (see Table 1). The departmental variance between time spent on RGSs and SVAs was statistically significant ([c.sup.2] = 129.496, p < .001) in the outpatient setting. A further breakdown of the data into medical and surgical subspecialties revealed a wide range of individual provider time increments spent on RGSs (Figure 4).

DISCUSSION

A 2010 article by the University HealthSystem Consortium suggests that very few organizations provide well-defined productivity tools to PAs and NPs. The article recommends that health systems explore opportunities in productivity tracking and, in particular, monitor patient outcomes and financial outcomes related to the use of APPs. The present study attempted to develop a productivity tool that quantifies and tracks the comprehensive delivery of care services to patients. Dunn et al. (1988) suggest that to effectively measure work, time and motion studies may need to be conducted with the willing collaboration of healthcare practitioners. Our study specifically identified time increments spent delivering RGSs and SVAs performed by advanced practice providers in various work settings and departments, Jacobson et al. (2011) suggest that work intensity of physicians is highly influenced by pre- and postservice work, which could account for 20 to 47 percent of a clinician's total productivity and work intensity. Very little data can be found in the literature to effectively quantify time spent on pre- and postservice work activities and their impact on service delivery, workforce assessments, investment returns, and workforce utilization and deployment. Hooker (2010) believes that productivity measurement is critical to the growth and acceptance of PAs in the national workforce. Organizations and institutions contemplating an increase in the number and utilization of APPs will require tools for improved value assessment and quantification of services by these providers. The results from this study provide a benchmark for organizations seeking information on APP productivity as they shed light on return on investment (ROI) factors and the causes of SVA variance in medical and surgical subspecialties.

Impact on ROI

We found that the time spent on RGSs provided by APPs at our facility was between 60 and 65 percent and the time spent on SVAs was about 30 to 35 percent. In essence, two thirds of APP daily work was spent conducting services that have direct revenue-generating opportunities through RVU allocation, while one third of that time was spent on SVAs, most of which were either non-RVLI generating or difficult to quantify.

The implications of these finding are far reaching. The quantifiable financial ROI on the utilization of an APP is only about two thirds of the total productivity of that provider, which implies that about one third of the productivity of each provider is lost when productivity is considered on the basis of current reimbursement and practice standards. The findings also indicate that, using current RVLI standards, only 60 to 65 percent of the providers' productivity is accurately assessed, whereas 30 to 35 percent of the time spent on valuable patient care services is lost, missed, or poorly accounted for.

As indicated earlier, pre- and post-service activities were defined as valued services lumped into current reimbursement calculations. These services have evolved over the past 20 years to include additional technology-based services and increasingly complex communication strategies, such as online medicine and electronic health records, subsequently altering methods of care delivery. Newer tools for service delivery, such as electronic health records, while aimed at improving efficiency and care, require the healthcare provider to have advanced education and training with very little improvement in reimbursement.

Variance in Medicine and Surgical Subspecialties

The results indicate that a statistically significant variance exists when comparing APP productivity (RGSs vs. SVAs) in medicine and surgical subspecialties (see Figure 4). Medicine subspecialties were noted to have statistically significant differences in percentage of time spent on RGSs ([c.sup.2] = 13.382, p < .05) versus SVAs, while the surgical subspecialties did not demonstrate similar significance ([c.sup.2] = 5.925, p = .205). These findings suggest that a narrower variance of productivity and services delivered could be expected in medicine subspecialties than in surgical subspecialties when staffing the medicine services with a PA or an NP. In contrast to medicine services, APPs in surgical services, who demonstrate the cross-coverage competencies, might provide healthcare organizations an opportunity to explore innovative deployment and coverage strategies that yield maximum productivity without compromising quality and patient safety.

MODEL DEVELOPMENT

This time and motion study is a prelude to the development of a supplemental model of productivity assessment intended to complement the existing RBRVS system. This new model will capitalize on the work done by Hsiao, Braun, Kelly, & Becker (1988), by using the same principle behind the RBRVS equation to supplement time spent on SVAs (Ts) for time worked (Tw) and maintaining all other variables. The equation will create a unit of measure for SVA delivered to patients, which we term service value unit (SVU), whereby

SVU = [Ts * Cf] + [Pc * Cf] + [Mc/s],

where Ts = time spent on SVAs, Cf = conversion factor, Pc = practice cost, and Mc/s = malpractice cost per specialty. The combination of RVUs and SVUs might provide an improved method of quantifying the total amount of service delivered to patients (total productivity = RVU + SVU). The finding that 30-35 percent of time was spent on SVAs across the various points of service (see Figure 1) suggests that these services are of value to patient outcomes and can add financial value to health systems' downstream revenue opportunities. Thus, SVAs should not be discounted, as they will in turn become an addition to the existing RBRVS scale measure and not a replacement. The unit of measure of SVUs could provide a quantifiable measure that will comprehensively account for day-to-day preservice and postservice work that is underrepresented in current RVU calculations. A valuation of SVAs by healthcare organizations and health finance industries might help to bridge the gap between the value of total services delivered to patients and the value placed on services by the current RBRVS system (Kravet, Jones, Howell, & Wright, 2008).

LIMITATIONS

The sample size for this study was a limitation. Henry Ford Hospital, the largest hospital within HFHS, employs approximately 230 APPs. The sample size of 19 represents about 10 percent of the APPs within the hospital and less than 10 percent of the APPs within the system. Other limitations to this study were seen in the development and translation of the list of services or activity used to populate the PDAs. Despite significant effort to populate the PDAs with established explanations of services using CPT 2010, some study participants were not familiar with the terminologies, which led to misunderstanding and misinterpretation of how to input the time spent on specific activities.

Another limiting factor relates to the exclusion of patient- and disease-specific influences on the data. Certainly, RGSs and SVAs could be influenced by patients and their specific disease acuity levels; however, this study focused on generating standard work patterns across multiple disciplines purely on the basis of well-established services delivered using commonly accepted CPT codes. Finally, the definitions of revenue-generating and service-valued activities were based on HFHS definitions of services for which reimbursement was or was not received. Such variances in third-party payments could be unique to HFHS or the state of Michigan.

SUMMARY AND CONCLUSION

The time and motion studies performed with this small group of providers has laid the foundation for conducting more in-depth analysis of time spent on RGSs and, particularly, SVAs in healthcare systems. The results from this study indicate that the efficiency of APPs varies by practice style and setting, and organizations may benefit from understanding those variables and applying the principles of our findings to quality and productivity metrics. Quantifiable knowledge on time spent on SVAs or other health-related services is still widely unknown, and this study provides a pathway to identifying areas of organizational improvement. It also sets a premise for future research on the relationship between productivity of healthcare providers, including SVAs, and outcomes, such as patient satisfaction and ROI.

For more information about the concepts in this article, please contact Dr. Ogunfiditimi at folu@yahoo.com.

REFERENCES

Bergman, J. M. (2003). Resource-Based Relative Value Scale (RBRVS): A useful tool for practice analysis. Journal of Clinical Rheumatology, 9(5), 325-327.

Braun, P., Hsiao, W. C., Becket, E., & DeNicola, M. (1988). Evaluation and management services in the Resource-Based Relative Value Scale. Journal of the American Medical Association, 260(16), 2409-2417.

Burke, T. A., McKee, J. R., Wilson, H. C., Donohue, R. M., Batenhorst, A. S., & Pathak, D. S. (2000). A comparison of time-and-motion and self-reporting methods of work measurement. Journal of Nursing Administration, 30, 118-125.

Committee on Coding and Nomenclature Review. (2008). Application of the Resource-Based Relative Value Scale system to pediatrics. Pediatrics, 122(6), 1395-1400.

Dunn, D., Hsiao, W. C., Ketcham, T. R., & Braun, P. (1988). A method for estimating the pre service and post service work of physicians' services. Journal of the American Medical Association, 260(16), 2371-2378.

Eggleston, K. (2005). Multitasking and mixed systems for provider payment. Journal of Health Economics, 24(1), 211-223.

Finkler, S. A., Knickman, J. R., & Hendrickson, G. (1993). A comparison of work-sampling and time-and-motion techniques for studies in health service research. Health Services Research, 28(5), 577-597.

Hendrich, A., Chow, M., Skierczynski, B., & Lu, Z. (2008). A 36-hospital time and motion study: How do medical-surgical nurses spend their time? Permanente Journal, 12(3), 10.

Hooker, R. (2010). Physician assistants, economics, and workforce modeling. Journal of the American Academy of Physician Assistants, 23(7), 10.

Hsiao, W. C., Braun, P., Kelly, N. L., & Becker, E. R. (1988). Results, potential effects, and implementation issues of the Resource-Based Relative Value Scale. Journal of the American Medical Association, 260(16), 2429-2438.

Jacobson, C. J., Jr., Bolon, S., Elder, N., Schroer, B., Matthews, G., Szaflarski, J. P., ... Horner, R. D. (2011). Temporal and subjective work demands in office-based patient care: An exploration of the dimensions of physician work intensity. Medical Care, 49(1), 52-58.

Kravet, S., Jones, H., Howell, E., & Wright, S. M. (2008). Pilot study comparing patients' valuation of health-care services with Medicare's relative value units. Health Expectations, 11 (4), 391-399.

Maloney, J. V., Jr. (1995). A rational process for the reform of the physician payment system. Annals of Surgery, 222(2), 134-145.

Martin, J. D., Warble, P. B., Hupp, J. A., Mapes, J. E., Stanziale, S. E, Weiss, L. L., ... Hanson L. A. (2010). A real world analysis of payment per unit time in a Maryland Vascular Practice. Journal of Vascular Surgery, 52(4), 1094-1098.

Moote, M., Krsek, C., Kleinpell, R., & Todd, B. (2011). Physician assistant and nurse practitioner utilization in academic medical centers. American Journal of Medical Quality, 26(6), 452-460.

Nyberg, S. M., Keuter, K. R., Berg, G. M., HeRon, A. M., & Johnston, A. D. (2010). Acceptance of physician assistants and nurse practitioners in trauma centers. Journal of the American Academy of Physician Assistants, 23(1), 35-37, 41.

Physician Payment Review Commission (PPRC). (1989). Physician Payment Review Commission Annual Report to Congress. Retrieved from http://archive.org/details/ physicianpayment00phys

University HealthSystem Consortium. (2010). Cost reduction: Labor practices--Midlevel provider bench marking project. Midlevel Provider Field Brief, 1-4.

Zheng, K., Guo, M. H., & Hanauer, D. A. (2011). Using the time and motion method to study clinical work processes and workflow: Methodological inconsistencies and a call for standardized research. Journal of the American Medical Informatics Association, 18, 704-710.

Zweifel, P., & Tai-Seale, M. (2009). An economic analysis of payment for health care services: The United States and Switzerland compared. International Journal of Health Care Finance and Economics, 9(2), 197-210.

RELATED ARTICLE: Practitioner application.

Louis G. Rubino, PhD, FACHE, professor and director, Health Administration Program, California State University, Northridge, and governing board member, St. Francis Medical Center, Lynwood, California

Productivity measurement has not received the same emphasis in human services as it has in manufacturing and industrial practices. But with the overall decline in healthcare reimbursement comes the need to do more with less. A medical practice must monitor patient billable time to survive. Hospitals are challenged to become more efficient with the advent of bundled payments and value-based purchasing.

The authors of this article have tackled the issue of productivity by reporting on their time and motion study measuring service-valued activity (SVA) and revenue-generating service (RGS) in inpatient and outpatient departments. Though limited to one healthcare system and a relatively low number of advanced practice providers (APPs) and lacking specificity by disease, the study still provides an interesting comparative analysis of productivity and its impact on administrative and organizational processes.

Along with healthcare reform will come the increased use of APPs (McLaughlin, 2011). Methods to measure their productivity as it relates to billable services will be needed. This study provides evidence that approximately one third of the APPs' time in both settings is spent performing activities that do not directly generate revenue. We need to be aware of the challenges being faced by all healthcare providers to properly address the common obstacles to productivity.

As a medical center governing board member and chair of its Quality and Patient Safety Subcommittee, I have used leader rounding as an opportunity to talk to various staff members regarding their frustrations in attempting to provide services in the most efficient way possible. Recently, for example, I spoke with several physicians and APPs in various settings to determine what is causing the loss of productivity at the healthcare worksites today. The overwhelming response I received was that the use of information technology (IT) was an impediment.

IT has been heralded as the way in which we will become more efficient and safe. Yet, recent evidence (Kellerman & Jones, 2013) and my own primary research demonstrate that the full benefits of health IT have not been achieved. Providers tend to spend more time documenting patient care notes on an electronic device than they had in paper charts because they are uncomfortable with typing techniques. Often, records from previous visits, those located in disparate information systems, and new test results are not directly or immediately available. It is hoped that once individuals become proficient in working with electronic medical records, the collection of data improves, and electronic information systems are fully integrated, IT as a barrier to productivity will no longer be an issue.

In addition, new methods of delivering healthcare services need to be explored to increase efficiency. Some examples are the use of primary care multidisciplinary teams; a patient-centering approach, whereby a provider sees groups of patients at the same time; and medical homes. As we develop these new models, productivity needs to be considered and its measurements hardwired into the system.

Yet, with the attention placed on RGS, we must remember that improved efficiency should not sacrifice face time with the patient and family. Personal interaction increases quality of care and patient satisfaction but does not necessarily increase reimbursement. And, unfortunately, there is no billing modifier for empathy.

REFERENCES

Kellerman, A. L., & Jones, S. S. (2013). What it will take to achieve the as-yet-unfulfilled promises of health information technology. Health Affairs 32(1), 63-68.

McLauglin, D. B. (2011). Responding to healthcare reform: A strategy guide for healthcare leaders. Chicago, IL: Health Administration Press.

Folusho Ogunfiditimi, DM, PA-C, manager, Advanced Practice Providers; Lisa Tahis, CSSBB, project manager; Virginia J. Paige, ACHPN, NP-C, chair, Advanced Practice Provider Council; Janet F. Wyman, RN, ACNS-BC, past chair, Advanced Practice Provider Council; and Elissa Marlow, PA-C, Governance Committee chair, Advanced Practice Provider Council, Henry Ford Health System, Detroit, Michigan

NOTE

(1.) STAMP is composed of a list of suggested standardized procedures for use in time and motion studies. Prior to the development of the STAMP checklist, time and motion studies of clinical workflows were inconsistent, leading to variable results and challenges to the ability to reproduce methods (Finkler, Knickman, & Hendrickson, 1993; Burke et al., 2000). Zheng et al. (2011) conducted a meta-analysis to evaluate multiple time and motion studies and developed the STAMP checklist on the basis of common elements found in the multiple studies assessed. Please contact the corresponding author to request a copy of the STAMP list.

TABLE 1
Outpatient PDA Activity List Options Associated with CPT Codes and
Study Results

                                   Revenue-     Service-
                                  Generating     Valued
Outpatient Activities              Services    Activities

Outpatient visit                      x
Outpatient follow-up                  x
General documentation                 x
Procedure documentation               x
Procedure                             x
Other revenue-generating              x
activities
Analysis of clinical data                          x
Team conference                                    x
Telephone consultation--                           x
  patient follow-up
Special reports                                    x
Research visit documentation                       x
Student precepting                                 x
Collection of physiological                        x
  data
Other service-valued activities                    x
Cafeteria
Personal time
Other
Total occurrences

                                                  % of      No. of
Outpatient Activities             CPT 2010 Code   Time    Occurrences

Outpatient visit                   99201-99205    31.99       246
Outpatient follow-up               99211-99215    10.66        82
General documentation                  N/A         8.45        65
Procedure documentation             Based on       5.72        44
                                    procedure
                                      code
Procedure                           Based on       1.82        14
                                    procedure
                                      code
Other revenue-generating          99000-99002,     0.40         3
activities                        98960-98962,
                                  98966-98968,
                                   99002.99078
Analysis of clinical data             99090       17.82       137
Team conference                       99366        4.29        33
Telephone consultation--           99211-99215     4.03        31
  patient follow-up
Special reports                       99080        3.25        25
Research visit documentation           N/A         2.60        20
Student precepting                     N/A         2.47        19
Collection of physiological           99091        1.30        10
  data
Other service-valued activities   99401-99409,     2.47        19
                                  99381-99387,
                                      99024
Cafeteria                              N/A         1.30        10
Personal time                          N/A         0.91         7
Other                                  N/A         0.52         4
Total occurrences                                             769

TABLE 2
Inpatient PDA Activity List Options Associated with CPT Codes and
Study Results

                                   Revenue-     Service-
                                  Generating     Valued
Inpatient Activities               Services    Activities

Subsequent hospital care              x
Discharge management                  x
Admission history and                 x
  physical
Postoperative care                    x
Procedures                            x
Procedure documentation               x
Other revenue-generating              x
  activities
Team conferences                                   x
Analysis of clinical data                          x
Telephone consultation by                          x
  NPP
Special reports                                    x
Collection of physiological                        x
  data
Business meeting council or                        x
  committee
Other service-valued activities                    x
Cafeteria
Lunch meeting
Total occurrences

                                                  % of      No. of
Inpatient Activities              CPT 2010 Code   Time    Occurrences

Subsequent hospital care           99231-99233    33.61       245
Discharge management               99238-99239    15.91       116
Admission history and              99221-99223     4.12        30
  physical
Postoperative care                    99024        3.02        22
Procedures                          Based on       2.88        21
                                    procedure
                                      code
Procedure documentation             Based on       0.82         6
                                    procedure
                                      code
Other revenue-generating          99354-99357,     1.23         9
  activities                      99401-99409,
                                  99251-99255,
                                   99024.99234
Team conferences                      99366       15.64       114
Analysis of clinical data             99090        7.54        55
Telephone consultation by          98966-98968     3.43        25
  NPP
Special reports                       99080        3.29        24
Collection of physiological           99091        1.65        12
  data
Business meeting council or            N/A         0.96         7
  committee
Other service-valued activities   99002, 99082,    2.61        19
                                  98960-98962,
                                  99000-99002,
                                  99026-99027,
                                   99053.98969
Cafeteria                              N/A         3.02        22
Lunch meeting                          N/A         0.27         2
Total occurrences                                             729

Note: NPP = nonphysician provider.

FIGURE 2
Comparison of RGS to SVA for Inpatient Services

Special Reports                            3%
Telephone Consultation
  by APP                                   3%
Analysis of Clinical
  Data                                     9%
Team Conferences                          16%
Other                                      3%
Other Revenue-Generating
  Activities                               2%
Procedures                                 3%
Post-op Care                               3%
Admission History
  and Physical                             4%
Discharge Management                      16%
Subsequent Hospital
 Care                                     34%
Other Service-Valued
  Activities                               5%

Service Valued                         35.12%
Other                                   3.29%
Revenue Generating                     61.59%

Note: Table made from pie chart.

FIGURE 3
Comparison of RGS to SVA for Outpatient Services

Other Service-Valued Activities            9%
Special Reports                            3%
Telephone Consultation
  Patient Follow-Up                        4%
Team Conference                            4%
Analysis of Clinical Data                 18%
Other                                      3%
Other Revenue-Generating Activities        2%
Procedure Documentation                    6%
General Documentation                      8%
Outpatient Follow-up                      11%
Outpatient Visit                          32%

Service Valued                         38.23%
Other                                   2.73%
Revenue Generating                     59.04%

Note: Table made from pie chart.
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Article Details
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Author:Ogunfiditimi, Folusho; Takis, Lisa; Paige, Virginia J.; Wyman, Janet F.; Marlow, Elissa
Publication:Journal of Healthcare Management
Geographic Code:1USA
Date:May 1, 2013
Words:4910
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