Physician Staffing for the VA Volume I (1991) / Chapter Skim
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4 - THE EMPIRICALLY BASED PHYSICIAN STAFFING MODELS
4 - THE EMPIRICALLY BASED PHYSICIAN STAFFING MODELS
Pages 41-150
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From page 41... ...
PCAs: inpatient care-medicine, surgery, psychiatry, neurology, rehabilitation medicine, and spinal cord injury; ambulatory care medicine, surgery, psychiatry, neurology, rehabilitation medicine, and other physician 41
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From page 42... ...
; total ambulatory care workload associated with the specialty; total long-term care workload associated with the specialty; the number of residents In that specialty at the VAMC, by postgraduate year; and other variables possibly associated with physician time devoted to patient care and resident education. There are separate facility-level IPFs for each of the following 11 specialty groups: medicine, surgery, psychiatry, neurology, rehabilitation medicine, anesthesiology, laboratory medicine, diagnostic radiology, nuclear medicine, radiation oncology, and spinal cord injury.
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From page 43... ...
VAMCs. The estimated PF and IPF models are used, alternatively, as the centerpieces of an algorithm to derive facility-specific physician requirements for two selected future years, 2000 and 2005.
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From page 44... ...
For simplicity, in the PF models discussed below, no distinction is made between PCAs or specialties, and the variables are not defined with the specificity required in later sections. Suppose the prior hypothesis is that the rate of production of patient care workload is positively related to the quantity of physician FTEE, and not related systematically to any other factor.
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From page 45... ...
. For models with more than one independentvariable, i.e., multivariate models, it is also required that there be no perfectly linear relationship between any two variables (in fact, among any subset of independent variables)
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From page 46... ...
and as these physician FTEE levels more closely approach the sample mean of Phys, the statistical reliability of this multiplier increases. Roughly speaking, the larger the t-statistic in absolute value, the greater the statistical strength of the estimated coefficient; the absolute-value proviso is required since t and the estimated coefficient take on the same sign, which can be negative.
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From page 47... ...
If the assumptions about ERROR hold, these residuals should have a random appearance, that is, no discernible patterns or trends. Of obvious importance is that Equation 4.1' can be used to derive physician requirements for patient care at a given VAMC.
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From page 48... ...
If, on the other hand, the estimate for Phys had been significant whereas the estimate for Phys2 had not been, the hypothesis of a linear relationship would have been sustained. The derivation of physician requirements from Equation 4.2 is illustrated by again setting W= 100 and solving the resulting quadratic relationship; the clinically relevant solution is Phys = 14.
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From page 49... ...
The committee emphasizes that this is merely an illustration with no policy implications intended or possible; how the actual effect of affiliation status on productivity and physician requirements can be inferred is discussed later in the chapter. The amount of physician FTEE required to meet workload at a VAMC now depends on whether it is affiliated.
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From page 50... ...
From Equation 4.5, the quantity of physician FTEE required for patient care and resident education at a VAMC for which W = 100 is equal to-0.84 + 0.09~100~= 8.16. An alternative hypothesis that as workload increases, physician FTEE requirements increase at an increasing rate is illustrated in Figure 4.6 and in the following hypothetical estimated equation: Phys = 1.34 +0.08 W + 0.0001 w2 _ (2.01)
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From page 51... ...
R2= 0.84 (4.8) This equation implies that in an affiliated VAMC the marginal effect of small changes in workload on physician requirements (for patient care and resident education)
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From page 52... ...
The decision to examine the PF first does not itself imply any committee preference between the two variants. Production Function A PF approach to determining VA physician requirements for patient care rests on the following related ideas.
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From page 53... ...
It can be shown that these assumptions, taken together, have troubling implications for the estimation of PFs of the type represented in Equations 4.1' through 4.4 by the traditional least-squares method.6 On the other hand, a VAMC is a public-sector organization charged with a multi-objective mission, but maximizing profits is not one of them. Rather, it is assumed that each VAMC attempts to meet its patient care mission in a way that balances several concerns: that eligible veterans are treated In a timely Specifically, without further assumptions, the coefficient estimates will be both biased and ~inefficient,- as will predictions of physician requirements.
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From page 54... ...
. Although a substantial part of this variability may be attributable to differences across VAMCs in the commitment to teaching and research (which affects the relative amount of staff physician time available for patient care)
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From page 55... ...
= the annual rate of production of workload in PCA j of VAMC i; {Staf~physij} = a set of variables, each of which takes the form Staf~physijk = the amount of FTEE allocated to direct patient care in PCA j of VAMC i for staff physicians based in cost center k, where each k corresponds to one of the 11 specialty groups examined here in detail; (ConPhysij} = a set of variables for physicians under contract to VAMC i, such that ConPhysijk = the contract physician FTEE from specialty k devoted to PCA j; {Resij) = a set of variables to account for the net productive contribution of residents, with each variable of the form Resay = the amount of postgraduate year y resident FTEE allocated to PCA j at VAMC i; C&A,j = for non-VA physicians who perform consulting and attending duties on a fee-for-visit basis, the amount of FTEE allocated to PCA j at VAMC i; WOC,j = for non-VA physicians who perform consulting and attending duties without (monetary)
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From page 56... ...
The IPF's underlying assumption is that the amount of physician FTEE from a given specialty required for patient care and resident education is a Action of the volume of patient care workload to be produced, the number of residents to be taught on the PCAs, and possibly other factors influencing the relationship between workload, resident education, and staff physician requirements. From a cause-and-effect standpoint, the basic behavioral assumption in the IPF variant (in contrast with the PF)
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From page 57... ...
(4.10) where StaffPhys,k = across all PCAs at VAMC i, the total amount of specialty k staff physician and contract physician FTEE devoted to patient care and resident education; {Wk} = a set of workload variables, each of the form Wick = the level of workload on PCA j of VAMC i associated with specialty k; {Rest} = a set of variables, each of the form Rest,, = the amount of postgraduate year y resident FTEE at VAMC i in specialty k; {NPPik} = a set of variables, each of the form NAP, = the amount of FTEE of nonphysician practitioner type m associated with the PCA-related activities of physicians in specialty k at VAMC i; what the PF and IPF have different underlying assumptions does not in any way constitute an empirical contradiction.
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From page 58... ...
Patient care and resident education typically dominate these activities. (Because the PCA-related part of research FTEE cannot be separated from total research FTEE in the current data systems and because most research occurs off the PCAs, research is excluded from the IPF equation; to derive total physician FTEE through an IPF (or a PF)
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From page 59... ...
Workload It is useful to consider, in turn, each of the three major type-of-care areas: inpatient care, ambulatory care, and long-term care. Patient Care For the PF variant, six PCAs, corresponding to the six major inpatient bed sections defined within the VA data systems, have been delineated: medicine, surgery, psychiatry, neurology, rehabilitation medicine, and spinal cord injury.
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From page 60... ...
Then, the following workload data are generated: the patient's first, five-day stay in medicine is assigned a DRG, and thus a medicine WWU score; the seven-day stay in surgery gets a DRG and a surgery WWU score; and the six-day transfer back to medicine is assigned a DRG and a medicine WWU score. The sum of the medicine WWU scores is assigned, for purposes here, to the inpatient medicine PCA and becomes part of this facility's cumulative medicine WWU total for the year.
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From page 61... ...
For a specialty such as medicine, which has its own inpatient PCA, inpatient WWU is equivalent simply to the sum of medicine WWU across all inpatient PCAs; this also applies, of course, to the IPF equations for surgery, psychiatry, neurology, and rehabilitation medicine. For a specialty such as nuclear medicine, which has no direct PCA identification, the PCA scope of the inpatient WWU variable must be defined.
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From page 62... ...
On the basis of the VA's own analyses of these data, four alternative ambulatory care workload measures were defined: · Clinic Stops/Year for ambulatory PCA j at VAMC i are computed as the direct sum of all recorded encounters at all clinic stops in that PCA domain during the year. (However, if a patient encounters any clinic stop more than once during a visit to the VAMC, only one encounter for that stop is recorded in the Staff Outpatient File.)
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From page 63... ...
Whenever any of these measures served as the workload index in a PF, a log transformation was applied in generating dependent-variable values, for reasons discussed above. Long-Term Care For patients admitted to an intermediate-care or nursing-home bed, sufficient information is recorded altogether in the VA Patient Treatment File, Extended Patient Treatment File, and Patient Assessment File to permit the calculation of three alternative workload measures: · Patients/Year for LTC PCA j (either intermediate care or nursing home)
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From page 64... ...
Computing StaffPhys,k for the IPF variant requires some additional steps. This facility- and specialty-specific variable is defined as the sum of staff physician and contract physician FTEE allocated to direct patient care, plus staff physician FTEE allocated to resident training.
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From page 65... ...
Consequently, it is implicitly assumed that, for each VA physician and PCA, the proportion of direct-care FTEE devoted to administration and leaves (and thus not to hands-on patient care) is the same at all FTEE levels.
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From page 66... ...
In the IPF, the sum of these variables across PCAs yields ConPhys,~, which becomes one component of the dependent variable in Equation 4.10. Resident FIEE To derive observations on Resin, the total FTEE of postgraduate year (PGY)
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From page 67... ...
The CDR data, however, do not break out resident FTEE by PGY. The response was to proceed as follows: For each specialty at the VAMC, CDR data were used to compute the fraction of resident FTEE allocated to inpatient care, ambulatory care, and long-term care.
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From page 68... ...
In the final months of the study, the committee did locate (non-CDR) data on annual capital equipment purchases by VAMCs; as discussed in the final section, these data can be transformed into a PCA-specific capital equipment index that may improve the overall performance of the empirically based staffing models.
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From page 69... ...
In most cases, such variables were not statistically significant; when they were, specialty panel members had difficulty assessing their clinical plausibility. Some members of the data and methodology panel contended also that models for determining future physician requirements should not have regional effects embedded in them.
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From page 70... ...
= ln[wjj + 1] = the natural logarithm of total WWUs, plus 1, produced in the inpatient medicine PCA during the fiscal year; = VA staff physician FTEE from the medicine service allocated to direct care in the inpatient medicine PCA; = variable testing for nonlinear relationship between VA staff internist FTEE and workload production-specifically, that there are diminishing marginal returns to increases in internist FTEE;
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From page 71... ...
; (MED_MD x FELLOWS) = interaction term for the joint influence of VA staff internists and fellows on the rate of workload production in this PCA; N = number of inpatient medicine PCAs (equivalent to the number of VA medicine services)
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From page 72... ...
A unit increase in psychiatrist FTEE devoted to direct care is expected to lead to a 0.163 unit increase in W Since the latter is a nonlinear (logarithmic)
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From page 73... ...
and squared terms of each type of physician specialist and resident was investigated; interaction terms involving all of these inputs in pairwise combinations were likewise tested; a number of variables not appearing in the final version, such as NURSE/MD and hospital groups other than HGROUP6, were also examined. In the end, the version of the inpatient medicine PCA appearing in Equation 4.11 represented in the committee's judgment, the best-fitting clinically plausible model.
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From page 74... ...
with R2 = 0.943 and N = 130 = total FTEE allocated to inpatient surgery PCA by VA staff physicians not medicine' surgery' psychiatry, neurology' or rehabilitation medicine cost centers; sample; moreover, multiple comparisons were undertaken using that sample. The resulting confidence statements should be regarded as ~nominal.
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From page 75... ...
HGROUP2 (MED_MD x OTHER_MD) 75 nursing-staff FTEE divided by total FTEE for physicians involved in handson delivery of care in the inpatient surgery PCA, defined to include intemists, surgeons, psychiatrists, neurologists, and rehabilitation medicine physicians (hereafter, this variable will be labeled more succinctly, "nursing-staff FTEE per total physician FTEE in this SCAT; total FTEE of residents PGY 2 and above allocated to this PCA; categorical variable assuming a value of 1 if facility is in RAM Group 2 (small general unaffiliated VAMC)
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From page 76... ...
with R2 = 0.874 and N = 141 W = ln[BDOCij + 1] = the natural logarithm of total bed-days of care, plus 1, produced in the inpatient psychiatry PCA during the fiscal year; HGROUP4 = categorical variable assuming a value of 1 if facility is in RAM Group 4 (mid-size general unaffiliated VAMC)
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From page 77... ...
with R2 = 0.674 and N = 79 VA staff physician FTEE from the rehabilitation medicine service allocated to direct care in the inpatient rehabilitation medicine PCA;
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From page 78... ...
(-4~319) with R2 = 0.915 and N = 21 where W = the natural logarithm of the sum of all medicine, surgery, psychiatry, neurology, and rehabilitation medicine WWUs, plus 1, generated in the SCI PCA; and SCI_MD = VA staff physician FTEE from the SCI service allocated to direct care in the SCI PCA.
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From page 79... ...
= natural logarithm of total CAPVVWUs, plus 1, produced in the ambulatory medicine PCA during the fiscal year. Recall that OTHER_MD is defined in Equation 4.12 as all physician FTEE assigned to direct care in the PCA exclusive of the direct-care FTEE of internists, surgeons, psychiatrists, neurologists, and rehabilitation medicine .
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From page 80... ...
Ambulatory Psychiatry (4.18) with R2 = 0.824 and N = 156 = categorical variable assuming a value of 1 if facility is in either RAM Group 3' 4, or 5.
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From page 81... ...
(6.733) Ambulatory Rehabilitation Medicine W = 11.892 + 1.390 RMS_MD + 0.003 SUPPORT/MD (6.376)
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From page 82... ...
= natural logarithm of total clinic stops, plus 1, produced in the ambulatory other physician services PCA during the fiscal year; and RAD_MD = VA staff physician FTEE from radiology allocated to direct-care activities in this PCA. The ambulatory other physician services PCA includes the emergency unit and admitting & screening, plus a number of miscellaneous clinic-stop sites.
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From page 83... ...
(3.754) with R2 = 0.803 and N = 129 where INT_MD = VA staff physician FTEE from intermediate medicine (i.e., recorded in the intermediate medicine cost center)
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From page 84... ...
, the WWU makeup of its inpatient workload variable, the CAPWWWU makeup of its ambulatory workload variable, and the RUGWWU makeup of its long-term care workload variable all had to be defined. How this was handled for laboratory medicine, diagnostic radiology, nuclear medicine, radiation oncology, and anesthesiology is indicated, in turn, in the estimated equations below.
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From page 85... ...
across all PCAs, plus total internist FTEE allocated to resident training across all PCAs, plus 1; MEDWWU = total medicine WWUs produced during the fiscal year in the inpatient PCAs of medicine, surgery, psychiatry, neurology, and rehabilitation medicine (divided by 10,000~; MEDCAPWWU = total CAPWWUs produced during the fiscal year in the ambulatory PCAs of medicine and other physician services (divided by 10,000~;
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From page 86... ...
From Equation 4.25 it can be inferred that inpatient, ambulatory care, and long-term care WWUs all influence the amount of internist FTEE required for direct care and resident education at the VAMC; internist requirements are positively related to the number of fellows; and the relationship between RAMgroup assignment and internist requirements is complex and depends, in particular, on the absolute level of MEDWWU. In Figure 4.13, the studentize`1 residuals from Equation 4.25 are shown.
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From page 87... ...
withR2= 0.887andN= 164 PSY_MD' = the natural logarithm of the sum of VA psychiatrist FTEE devoted to direct care (i.e., the sum of all PSY_MD variables) across all PCAs, plus total psychiatrist FTEE allocated to residency training, plus 1; PSYWWU = total psychiatry WWUs during the fiscal year across all inpatient PCAs (divided by 10,000~;
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From page 88... ...
-withR2 = 0.568andN= 89 NEU_MD' = natural logarithm of the sum of VA neurologist FTEE devoted to direct care (i.e., the sum of NEU_MD) across PCAs, plus total neurologist FTEE allocated to resident training, plus 1; NEUWWU = total neurology Owns produced during the fiscal year across the inpatient PCAs (divided by 10,000~; NEUCAPWVVU = total CAPWWUs produced during the fiscal year in the ambulatory neurology PCA (divided by 10,000~.
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From page 89... ...
across PCAs, plus total RMS FTEE allocated to resident training, plus 1; RMSWVVU = total RMSWWUs produced during the fiscal year across the inpatient PCAs; RMSCAPWWU = total CAPWWUs produced during fiscal year in the ambulatory rehabilitation medicine PCA; RMSRUGWWU = total rehabilitation medicine RUGWWUs produced during the fiscal year in the LTC PCAs of nursing home care and intermediate care; RESIDENTS = total FTEE of RMS residents PGY1-PGY3 at the VAMC; and FELLOWS = total FTEE of RMS residents PGY4 and above at the VAMC.
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From page 90... ...
(-2.629) with R2 = 0.808 and N = 21 where SCI_MD' = the natural logarithm of the total FTEE devoted by physicians in the SCI cost center to direct care and resident education in the SCI PCA, plus 1; and SCIWWU = the sum of all medicine, surgery, psychiatry, neurology, and rehabilitation medicine WWUs generated during the fiscal year in the SCI PCA.
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From page 91... ...
with R2 = 0.803 and N = 156 LAB_MD' = the natural logarithm of the sum of VA laboratory medicine physician FTEE devoted to direct care (i.e., the sum of LAB_MD) across all PCAs, plus total contract laboratory medicine FTEE at the VAMC, plus total VA laboratory medicine FTEE allocated to resident education, plus 1; LABWWU = total inpatient WWUs at the VAMC (divided by 10,000~; LAB CAPWWU = total CAPWWUs at the VAMC (divided by 10,000~; and RESIDENTS = total FTEE of laboratory medicine residents PGY1-PGY3 at the VAMC.
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From page 92... ...
with R2 = 0.804 and N = 164 RAD_MD' = the natural logarithm of the sum of VA diagnostic radiology physician FTEE devoted to direct care (i.e., the sum of RAD_MD) across all PCAs, plus total diagnostic radiology contract physician FTEE at the VAMC, plus total VA diagnostic radiology physician FTEE allocated to resident education, plus 1; RADWWU = the sum of all MEDWWU, SURWWU, and NEUWWU at the VAMC (divided by 10,000)
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From page 93... ...
across all PCAs, plus total nuclear medicine contract physician FTEE at the VAMC, plus total VA nuclear medicine physician FTEE allocated to resident education, plus 1; NMWWU = the sum of all MEDWWU, SURWWU, and NEUWWU at the VAMC (divided by 10,000~; NMRUGWVVU = total MEDRUGWWU at the VAMC (divided by 10,000~; RESIDENTS = total FTEE of nuclear medicine residents PGY1-PGY3 at the VAMC; and FELLOWS = total FTEE of nuclear medicine residents PGY4 and above at the VAMC.
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From page 94... ...
EBPSM APPLICATION 1: USING THE MODELS TO ASSESS PHYSICIAN STAFFING LEVELS AND WORKLOAD PRODUCTIVITY AT VAMCs Irrespective of the weight accorded empirically based models in the overall strategy for determining fixture physician requirements (see chapter 6) , the EBPSM can serve as an important mechanism for evaluating the relative performance of individual VAMCs (or groups of them)
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From page 95... ...
Using the IPF to Compare Predicted and Actual Physician FIEE Devoted to Direct Patient Care and Resident Education The policy question being examined here is as follows. In specialty k at VAMC i at some point in time, there will be some actual (recorded)
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From page 96... ...
In Tables 4.1 through 4.4, actual and predicted physician FTEE for direct patient care and resident education are compared for each of 11 specialties at the selected VAMCs. The choice of a 95 percent prediction interval, although common, is arbitrary; intervals can be calculated similarly for whatever confidence level the decision maker desires.
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From page 97... ...
If a certain specialty's FTEE variable does not merit inclusion in a given PCA's PF on statistical grounds, physician requirements in that specialty for that PCA will always be computed as 0, whatever the specialty's actual time and contributions to patient care. Also, because the dependent variable is workload and not physician FTEE, prediction intervals on FTEE requirements cannot be computed directly.
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From page 98... ...
Physician requirements cannot be derived by this PF-based technique for the specialties for which a PF could not be estimated: anesthesiology, laboratory medicine, diagnostic radiology, nuclear medicine, and radiation oncology. There is no separate table for SCI physicians because all of their direct patient care is assumed to occur in the SCI PCA.
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From page 99... ...
Using the PF to Compare Predicted and Actual Rates of Workload Productivity The estimated PF equations are naturally well suited for exalIiining an important question that bears on physician requirements. Specifically, for any PCA at any VAMC, how does its actual rate of workload production compare with the rate predicted by the appropriate PCA-specific PF?
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From page 100... ...
Using the IPF to Derive Future Physician Requirements for Direct Patient Care and Resident Education These analyses are summarized in Tables 4.16 through 4.19 for VAMCs I through IV, respectively, and show physician requirements for patient care and resident education in 11 specialties for FYs 2000 and 2005. Each FTEE calculation is expressed as a "prediction," accompanied by a 95 percent prediction interval.
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From page 101... ...
(This can be compared with the predicted and actual FTEE levels for FY 1989, which from Table 4.1 are 14.77 and 19.41, respectively.) The accompanying prediction-interval calculation for FY 2000 implies that the probability is 0.95 that a facility with VAMC I's attributes and facing the workload demands calculated above will be found to have an internist FTEE level for patient care and resident education between 7.70 and 36.98.
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From page 102... ...
Using the PF to Derive Future Physician Requirenents for Direct Patient Care These analyses are summarized in Tables 4.20 through 4.27. Each shows, for a given future year and VAMC, the projected FTEE required for direct patient care, by specialty, in each PCA.
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From page 103... ...
PROPOSALS FOR REFINING AND EXTENDING THE EBPSM In sum, the results reported in this chapter demonstrate that, with few exceptions, statistically strong and clinically meaningful models for determining physician requirements can be developed and estimated using currently available VA data. It must be acknowledged, however, that a recurring theme sounded by the committee's six specialty and two clinical program panels was that the data used in these models particularly physician FTEE data from the CDR were at risk of being skewed through various types of reporting errors.
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From page 104... ...
2. It is also not possible at present to distinguish physicians by subspecialty in the national CDR accounts; for example, the quantity of FTEE allocated by the cardiologist to the medicine inpatient PCA or by the neurosurgeon FTEE to the ambulatory surgery PCA are not available from these accounts at the moment.
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From page 105... ...
5. For each resident supported by the VA via salary or contract, a CDR worksheet is completed, but it allocates the resident's time only to the broad categories of Inpatient Medicine, Inpatient Surgery, Inpatient Psychiatry, and Outpatient Care.
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From page 106... ...
Moreover, the motivation and effort level of individual physicians may well be influenced by some of these VA system changes. The VA should investigate measurable factors that appear to account for differences in individual physician productivity, then use these factors in subsequent analyses that relate physician requirements, in part, to the predicted effort level per FTEE.
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From page 107... ...
1975. Physician Productivity and the Dema~ulfor Health Manpower.
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From page 108... ...
108 Ste~s, To O^11~, N., Id HoldeD, F
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From page 109... ...
Radiation Oncology 2 2 2 NOTE: VAMC I = mid-size affiliated. Includes all physician FTEE for direct care and resident education associated with the specialty's CDR cost center, across all patient care areas (and thus encompassing the emergency and admitting & screening areas of the other physician services PCA)
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From page 110... ...
"Includes all physician FTEE for direct care and resident education associated with the specialty's CDR cost center, across all patient care areas (and thus encompassing the emergency and admitting & screening areas of the other physician services PCA) ; excludes physicians in that specialty who are assigned to a CDR cost center other than the one normally associated with the specialty.
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From page 111... ...
"Includes all physician FTEE for direct care and resident education associated with the specialty's CDR cost center, across all patient care areas (and thus encompassing the emergency and admitting & screening areas of the other physician services PCA) ; excludes physicians in that specialty who are assigned to a CDR cost center other than the one normally associated with the specialty.
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From page 112... ...
(0.08, 1.36) Includes all physician FTEE for direct care and resident education associated with the specialty's CDR cost center, across all patient care areas (and thus encompassing the emergency and admiring & screening areas of the other physician services PCA)
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From page 113... ...
EMPIRICALLY BASED MODELS 113 TABLE 4.5 For Medicine, CDR-Based Actual Physician FTEE and PFDerived Projected FTEE for Direct Patient Care at VAMC II, FY 1989 Physician FTEE Statistics Patient Care Areas Actual Projected Inpatient Medicine 10.95 12.13 Surgery 3.52 3.94 Psychiatry 0.57 0.00 Neurology 0.28 0.40 Rehabilitation Medicine 0.06 0.06 Spinal Cord Injury 0.51 0.00 Ambulatory Medicine 8.05 12.28 Surgery 0.28 0.00 Psychiatry 0.23 0.00 Neurology 0.00 0.00 Rehabilitation Medicine 0.06 0.00 Other Physician Services 12.47 9.59 Long-Term Care Nursing Home 0.68 0.60 Intermediate Care 0.11 0.18 Total 37.77 39.18 NOTE: VAMC II = metro affiliated.
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From page 114... ...
114 PHYSICIAN STAFFING FOR mE VA TABLE 4.6 For Surgery, CDR-Based Actual Physician FTEE and PFDerived Projected FTEE for Direct Patient Care at VAMC II, FY 1989 Physician FTEE Statistics Patient Care Areas Actual Projected Inpatient Medicine 0.05 0.06 Surgery 8.04 8.99 Psychiatry 0.00 0.00 Neurology 0.00 0.00 Rehabilitation Medicine 0.03 0.00 Spinal Cord Injury 0.00 0.00 Ambulatory Medicine 0.19 0.00 Surgery 0.94 1.64 Psychiatry 0.00 0.00 Neurology 0.00 0.00 Rehabilitation Medicine 0.03 0.00 Other Physician Services 2.96 0.00 Long-Term Care Nursing Home 0.00 0.00 Intermediate Care 0.03 0.00 Total 12.27 10.69 NOTE: VAMC II = metro affiliated.
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From page 115... ...
EMPIRICALLY BASED MODELS 115 TABLE 4.7 For Psychiatry, CDR-Based Actual Physician FTEE and PFDerived Projected FTEE for Direct Patient Care at VAMC II, FY 1989 Physician FTEE Statistics Patient Care Areas Actual Projected Inpatient Medicine 0.27 0.30 Surgery 0.05 0.00 Psychiatry 7.43 9.04 Neurology 0.00 0.00 Rehabilitation Medicine 0.02 0.00 Spinal Cord Injury 0.02 0.00 Ambulatory Medicine 0.00 0.00 Surgery 0.00 0.00 Psychiatry 9.61 7.27 Neurology 0.00 0.00 Rehabilitation Medicine 0.00 0.00 Other Physician Services 0.00 0.00 Long-Term Care Nursing Home 0.00 0.00 Intermediate Care 0.00 0.00 Total 17.40 16.61 NOTE: VAMC II = metro affiliated.
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From page 116... ...
6 PHYSICIAN STAFFING FOR ~ VA TABLE 4.8 For Neurology, CDR-Based Actual Physician FTEE and PFDerived Projected FTEE for Direct Patient Care at VAMC II, FY 1989 Physician FTEE Statistics Patient Care Areas Actual Projected Inpatient Medicine 0.45 0.50 Surgery 0.10 0.00 Psychiatry 0.61 0.00 Neurology 0.76 1.08 Rehabilitation Medicine 0.33 0.00 Spinal Cord Injury 0.03 0.00 Ambulatory Medicine 0.00 0.00 Surgery 0.04 0.00 Psychiatry 0.27 0.00 Neurology 0.56 2.03 Rehabilitation Medicine 0.00 0.00 Other Physician Services 0.00 0.00 Long-Term Care Nursing Home 0.00 0.00 Intermediate Care 0.25 0.00 Total 3.40 3.61 NOTE: VAMC II = metro affiliated.
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From page 117... ...
EMPIRICA=Y BASED MODELS 117 Table 4.9 For Rehabilitation Medicine, CDR-Based Actual Physician FTEE and PF-Derived Projected FTEE for Direct Patient Care at VAMC II, FY 1989 Physician FTEE Statistics Patient Care Areas Actual Projected Inpatient Medicine 0.09 0 00 Surgery 0.10 0.00 Psychiatry 0.30 0.00 Neurology 0.08 0.00 Rehabilitation Medicine 0.36 0.37 Spinal Cord Injury 0.24 0.00 Ambulatory Medicine 0.00 0.00 Surgery 0.00 0.00 Psychiatry 0.00 0.00 Neurology 0.00 0.00 Rehabilitation Medicine 1.15 0.66 Other Physician Services 0.01 0.00 Long-Term Care Nursing Home 0.25 0.22 Intermediate Care 0.14 0.23 Total 2.72 1.48 NOISE: VAMC II = metro affiliated.
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From page 120... ...
. Workload expressed in Capitation Weighted Work Units (CAPWWUs)
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From page 121... ...
. Workload expressed in Capitation Weighted Work Units (CAPWWUs)
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From page 122... ...
. Workload expressed in Resource Utilization Group Weighted Work Units (RUGWWUs)
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From page 123... ...
. Workload expressed in Capitation Weighted Work Units (CAPWWUs)
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From page 127... ...
127 Cal D A: ._ _, Cal a: C)
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From page 128... ...
128 ~1 ~ a ~1 ~1 ~1 08 ~ ~1 C Z ~ ~' :_ ~: as co ~> c o 04 a, .
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From page 130... ...
130 o u os ~5 .
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From page 132... ...
132 a 0 oo4 .= c C~ c ._ D C 5o ._ C~ 0 C £ 9J · _ c = 0 ; ~C o c ·_ .
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From page 134... ...
134 o 2 al ·c o .= ~> CO .
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From page 136... ...
136 180 160 140 3: 1 20 0 100 ye o 3: 80 60 40 20 o PHYSICIAN STAFFING FOR THE VA .
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From page 137... ...
16 18 FIGURE 4.2 PF with Nonlinear Relationship between Workload and Physician FTEE
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From page 138... ...
· ~ .~' ·-~ ·~ · ' · e . Unaffiliated VAMC 1 1 1 1 1 1 1 1 4 6 8 10 12 Physician FTEE (Phys)
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From page 139... ...
1-' //~ 1 / . Unaffiliated VAMC O 1 1 1 1 1 1 1 1 _ 4 6 8 10 12 14 16 18 Physician FTEE (Phys)
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From page 140... ...
140 18 16 14 ~n s ~12 10 ce ._ ._ In s 8 4 2 o PHYSICIAN STAFFING FOR THE VA 1 .
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From page 141... ...
. O 1 1 1 1 1 1 1 20 40 60 1 140 160 180 FIGURE 4.6 IPF with Nonlinear Relationship between Physician FTEE and Workload
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From page 142... ...
FIGURE 4.7 IPF with Affiliation Status and Workload Having Distinct (Independent) Effects on Physician FTEE
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From page 143... ...
. Unaffiliated VAMC 1 1 1 1 1 1 1 1 20 40 60 80 100 120 140 160 180 Workload (W)
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From page 150... ...
150 : # # # # # # # ## # .# ~ ~## I #i.~# # ## # .lc # ' # # # # # - ', ~ '# *
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Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.