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Rural Hospital Flexibility Program Tracking Project

Chapter 3E
Financial Condition of Critical Access Hospitals: 1996-2000

William N. Zelman, Ph.D., Scott R. Stewart, M.S.P.H., Kathleen Dalton, Ph.D., 
Stephanie Poley, B.A., Melissa Fruhbeis, M.S.P.H., Andrew E. Cameron, Ph.D.
Department of Health Policy and Administration and 
Cecil G. Sheps Center for Health Services Research
University of North Carolina at Chapel Hill

Executive Summary

Background and Sources

The objective of this chapter is to provide an overview of the financial condition of the facilities that became Critical Access Hospitals (CAHs) under the Rural Hospital Flexibility Program (Flex Program). First, we review CAH administrators' own estimates of their financial conditions and their expectations of the impact of converting to CAH-Medicare cost-based reimbursement. Then, using financial ratio analysis, we compare the financial positions of hospitals that have chosen to become CAHs to the positions of other groups of rural hospitals, over a five-year period.

Secondary data were obtained from a private firm (HCIA, Inc.) to create a set of standard financial ratios for rural hospitals for the period from 1996 to 2000. HCIA obtains these data from the Medicare cost reports on an accelerated basis. All but ten hospitals that had converted from Medicare's prospective payment system (PPS) to CAH status at the time of this study had not yet completed and filed cost reports on their first year of cost-based reimbursement. For the majority of converting hospitals in our sample, therefore, our ratio analyses look back over the periods leading up to their decision to participate in this program. For comparisons, we computed median values of key financial ratios for all hospitals converting to CAH status as of July 2001 and for rural hospitals that had not converted to CAH status. 

Findings

Responses to a telephone survey of CAH administrators confirm that the expected benefit from cost-based reimbursement was the chief reason that hospitals considered participating in the Flex Program. Substantial increases in Medicare payments were projected by financial feasibility studies that had been conducted by hospitals prior to making the decision to convert, and the amounts of projected increased revenue were frequently as great or greater than the administrators' estimates of their net operating losses in recent prior years.

Ratio analysis confirms that the hospitals that chose to convert were operating with lower margins than were other small rural hospitals. Measures of profitability for all three of our comparison groups decreased over the study period. There was little change in median measures of liquidity or of labor efficiency in these organizations over time, and little difference in these median indicators for CAH converters compared to those of other small, rural hospitals. CAHs that were former Primary Care Hospital/Medical Assistance Facility (PCH/MAF) (pilot) hospitals in the early demonstration states scored worse than CAHs, as a group, on nearly every financial indicator and in nearly every year of the study.

Small rural facilities tend to have older fixed assets than do larger rural facilities. The group of former PCH/MAF facilities, in particular, operated with older plant and equipment. The amount of long-term debt relative to other financing increased from 1996 to 1999 in both groups of small, rural hospitals, but it was still substantially below the relative debt levels of larger rural facilities. The median ratio of long-term debt to equity among CAHs grew substantially over the study period, and in 1999 was almost double that for other small, rural hospitals. The cash flow available to service that debt did not appear to increase proportionally. This raises some question about the ability of the smaller facilities, and CAH converters in particular, to raise funds for future plant modernization or replacement.

Introduction

Background

In an effort to support the rural safety net, the Rural Hospital Flexibility Program (Flex Program) was adopted by Congress as part of the Balanced Budget Act of 1997 (BBA). One part of the Flex Program is intended to help preserve the role of small rural hospitals as critical links in their communities' systems of care by allowing them to become Critical Access Hospitals (CAHs). In this respect, the program updates and expands earlier demonstration programs for limited-service hospitals in rural areas, which were called Primary Care Hospitals (PCHs) or Medical Assistance Facilities (MAFs).¹ 

A major advantage of CAH designation is eligibility for cost-based reimbursement for inpatient and outpatient services under Medicare, and in some states, under Medicaid as well. Cost-based reimbursement mitigates much of the risk that hospitals typically bear under the prevailing Medicare Prospective Payment System (PPS), which reimburses hospitals a predetermined rate for specific cases regardless of cost. While it also eliminates the opportunity to earn a surplus on care delivered to Medicare patients, this disadvantage is unlikely to affect a significant portion of very small, rural hospitals because so few of them have been able to earn a surplus on their combined inpatient and outpatient Medicare business.²

This Study

The financial condition of Critical Access Hospitals is an important gauge of their viability and, hence, the success of a major component of the Medicare Rural Hospital Flexibility Program. This chapter provides an analysis of the ongoing financial standing of hospitals that chose to participate in the Flex Program compared to those that did not. Any analysis of the impact of cost-based reimbursement, per se, is limited by the delay in hospital Medicare reporting, because a definitive analysis of the financial status of CAH hospitals pre- and post-conversion cannot be accomplished until we have more complete data through the years 2000 and 2001. The first analysis in this chapter summarizes what was reported as the expected reimbursement impact of conversion. The subsequent ratio analyses identify key differences in the baseline financial positions of converting hospitals as compared to other rural hospitals, and serve as valuable tools for preliminary program tracking.

The first component of this study relies on primary data collected from a telephone survey of 217 CAHs conducted by the University of Minnesota and described elsewhere in this report. We provide a summary of the responses of CAH administrators to a series of questions regarding the financial position of their institutions at the time that they made the decision to convert to CAH status, their projections for the reimbursement impact of conversion, and their estimates of the actual impact in the first two years.

The remainder of our study is a secondary data analysis of financial information obtained from HCIA, Inc.'s annual Comparative Performance of U.S. Hospitals. This is a proprietary database containing selected financial and operating statistics for hospitals over multiple years. HCIA's source for these statistics is the Medicare cost report. We examine trends in key financial ratios for hospitals that converted to CAH status and compare them to those of other rural hospitals, for the period 1996-1999.

Survey Responses from CAH Administrators

Respondents to the telephone survey conducted by the University of Minnesota were asked a series of questions to gain information about their use of financial projections in deciding whether to convert to CAH status, and the subsequent financial impact of this decision. Tables summarizing their responses to each question appear in Appendix A at the end of this chapter (Tables A1-A6), and are discussed below.

Use of Financial Feasibility Studies

Eighty-six percent of respondents (185 out of 215) reported that an estimate of the financial impact of conversion on the hospital's net income was completed before deciding to convert to a CAH (Table A1).³ Eighty-three percent of those who conducted studies held them to be extremely important factors in their decision to convert to a CAH (Table A2). 

Of the hospitals that conducted feasibility studies, 71 percent conducted one feasibility study and 24 percent conducted two (Table A3). External consultants prepared the feasibility studies in 30 percent of these hospitals and internal staff were responsible in 20 percent. Ten hospitals (5%) reported that their studies had been conducted by a state hospital or other state agency. The remaining 44 percent reported their studies to have been completed by other, unspecified parties (Table A4).

Estimated Financial Impact of Conversion on the Hospital's Net Income

Respondents were asked to list the projected financial impact of CAH conversion at three points in time: in the conversion year, one year after conversion and two years after conversion (Table A5). Not all respondents were able to provide these estimates. The median estimate for respondents in the conversion year (N=148) was an increase in Medicare payments of $193,500. Fifty percent of the estimates ranged between $100,000 and $300,000. Figure 1 shows the distribution of responses in the initial year of conversion.

Figure 1:  Reported Initial-Year Dollar Impact of Converting
to CAH Status, as Predicted from Financial Studies

Estimates of financial impact one and two years after conversion were similar, although the number of respondents decreased significantly with each iteration of the question. The median projected financial impact one year after conversion (N=119) was $250,000, with 50 percent of the estimates ranging from $165,000 to $400,000. The median projected impact two years after conversion (N=41) was also $250,000.

Net Income or Loss During The Year Prior to Conversion.

Finally, respondents were asked to report their hospital's net income or loss for the year prior to CAH conversion, providing context for the significance of their conversion projections. The median reported net income in the year prior to conversion (N=164) was -$200,000, but the range was very large, from a negative $1.5 million to positive $4 million. Fifty percent of those responding to this question reported net incomes between -$450,000 and +$1.5 million (Table A6). 

Secondary Data Analysis - The Financial Condition of CAH Converters and Other Rural Hospitals 

Analytic Framework: Financial Ratio Analysis

Our secondary data study uses ratio analysis to assess the financial condition of CAHs. Financial ratios allow the comparison of two line items or groups of line items from financial statements to be expressed as a single measure that permits comparisons between organizations of different sizes. For example, we understand that an organization with total margin of five percent is making more profit for each dollar of revenue than one with total margin of two percent, regardless of each hospital's size. Our ratio analysis compares the median values of key measures of profitability, liquidity, asset structure, and efficiency, as discussed below and defined in Table 1.

Consideration of several ratios jointly offers a more complete picture of a facility's overall financial condition. This study uses 12 financial ratios to describe six broad characteristics of overall financial health:

• Profitability: Total margin and return on equity are expressions of net income relative to total revenue and to total equity, respectively. They provide measures of a hospital's ability to generate new resources for renewal and expansion. 

• Liquidity: Days in accounts receivable is also known as the average collection period. Days cash on hand is the number of days of expenses that the hospital can currently cover with its available cash. Together, these ratios provide an indication of the hospital's liquidity.

• Fixed Asset Use: Age of plant is the average age of property, plant and equipment owned by the hospital. Fixed asset turnover provides an indication of the efficiency with which the hospital uses its fixed assets to generate revenues. 

• Capital Structure: Long-term debt to equity⁴ (net assets) and cash flow to total debt are measures of the burden of debt and the ability of a hospital to take on more debt. Cash flow is approximated by subtracting depreciation expense (which is a non-cash item) from net income for the period. The ratio measures the proportion of a hospital's long-term obligations that could be met with available cash generated from a year of operations. Hospitals with higher debt to equity ratios and lower cash flow may have difficulty paying off their debt and securing financing for renewal and expansion. 

Table 1:  Definition of Financial Ratios

• Pricing and Market Strength: The markup ratio can be an indication of the hospital's power to set prices. The deduction percentage measures the proportion of total patient charges that are given up as discounts and allowances. In less competitive environments where individual hospitals can still influence overall prices, these two measures together help to identify a hospital's market strength and its ability to shift the burden of uncompensated care to insured customers. In markets where hospitals must accept prevailing price structures, these measures may be more indicative of the hospital's ability to manage its costs within a competitive setting. 

• Workforce Efficiency: Net patient revenue per full-time equivalent (FTE) is somewhat analogous to fixed asset turnover in that it measures the efficiency of labor relative to revenue, after adjusting for regional differences in prevailing wage rates. FTEs per adjusted patient day is a common industry indicator that provides a view of labor efficiency from the perspective of care delivery rather than income generation. Adjusted patient days are traditionally derived by computing average inpatient revenue per inpatient day, then dividing outpatient revenues by this amount to derive an "outpatient equivalent day." Adjusted patient days equals total inpatient plus outpatient equivalent days.

Study Sample

The study population for the secondary data analysis is all Medicare participating hospitals located in non-metropolitan counties during the period from 1996 to 2000. Financial account balances and selected operating statistics were abstracted from a proprietary database, HCIA, Inc.'s annual Comparative Performance of U.S. Hospitals, which was built from Medicare cost reports filed by acute-care hospitals. HCIA's data set includes separate records for approximately 6,000 hospitals, by reporting year. The full rural sample used for this study included 8,914 observations from 2,520 unique hospitals located in non-metropolitan counties. 

The data reflect operations from hospital fiscal years ending between 1996 and 2000, comprising four complete study years (1996-1999) and one partial year (2000). Data were annualized for reports that covered periods less than one year. For a small number of hospitals, recent data were missing from the HCIA database but were available from cost reports and financial statements that the investigators had received directly from site-visited hospitals. Where possible, the missing observations were added to the study data set from these sources. Eight observations were created in the 2000 study year in this way. Notes to financial statements and HCIA documentation were consulted to ensure the comparability of new observations to the rest of the database. 

Each observation was assigned to the study year corresponding to the calendar year in which its fiscal period ended.⁵ Because of the timing of cost report filings, data for the year 2000 were available for an estimated 13 percent of rural hospitals. There could be as many as five observations from each hospital (one for each year in the study) and 12 ratios per observation. However, many of the smaller hospitals, including many of the former PCH/MAF facilities, were missing records for one or more years in period covered by the study.

All records with data sufficient to calculate a given ratio were included in the sample for that indicator. Hospitals with missing data for a specific variable that was needed to compute a ratio were omitted from the calculation of that indicator, on a case-by-case basis. Thus, the number of observations contributing to the median calculation within each year may vary by indicator.

Classification of Hospitals

For purposes of computing median ratios, hospitals were grouped into the following categories:

• CAH converters (all).

  • Former PCH/MAP facilities (sub-set from this group).

• Small rural hospitals, never converting to CAH.

• Other rural hospitals.

Hospitals were first classified according to whether or not they had ever converted to CAH status as of the time of the analysis, which was in July of 2001. We created a separate grouping for hospitals that had been PCH or MAF facilities prior to becoming a Critical Access Hospital, because these facilities had been receiving cost-based reimbursement from Medicare and Medicaid throughout the period covered by the data. However, the group identified as "CAH converters" includes both these former PCH/MAF hospitals, and hospitals that were paid under the Medicare PPS prior to becoming CAHs. A comparison of the reporting dates to the CAH conversion dates for the hospitals that were not former PCHs or MAFs identified only ten observations, all from the year 2000, for which the data were applicable to a post-conversion period. 

For rural hospitals that have not converted to CAH status, we created two comparison groups. "Small rural hospitals, never converting to CAH" includes all non-converting hospitals that are located in non-metropolitan counties, and that have annual net revenue up to $10 million generated from any source (including inpatient, outpatient or other, non-acute care). The remaining "other rural hospitals" category includes all rural hospitals with annual net revenue in excess of $10 million. 

The "small rural hospitals, never CAH" is a reasonable CAH comparison group in that it should reflect the finances of facilities that might be similar to CAHs in location and size. It is important to keep in mind, however, that although this group includes many facilities that are eligible to convert according to the provisions of the enabling legislation, it also includes facilities in states that have not opted to participate in the Flex Program, as well as hospitals that do not meet the federal or state-specific eligibility criteria.

Table 2 shows the count of facilities within each group for each year. The maximum number of observations used to compute a median value within each comparison group is presented, along with a unique count of rural hospitals included in the data set. The number of observations used for any given ratio within a year is sometimes smaller due to missing data; the results tables included in Appendix A and B at the end of this chapter, however, provide an "N" for each cell of the tables. 

Table 2:  Number of Hospitals in Analysis File, by Category and Year

Findings and Discussion

Most of our indicators of financial health were either stable or declining for all rural comparison groups, over the four years for which we had complete data (1996-1999). In some cases the data for the year 2000 indicate a change in trend, and often, an improvement. As we noted earlier, due to the relatively small proportion of hospitals reporting 2000 data, these measures should be interpreted with caution. Any conclusions regarding a change in trends from 1999 to 2000 would be premature. 

The remainder of this section presents results for each of our six dimensions of financial health. A summary of the median values for each ratio in 1999 (our last year of complete data) is provided in Table 3. Median values for all of the indicators, by hospital group and by study year, are provided at the end of this chapter in Appendix B as Tables B1-12. Results for each of the three main comparison groups are presented graphically as part of the discussion that follows. 

The median ratios for the former PCH/MAF group appear in Tables B1-12. Although we comment on these wherever they appear to follow a different pattern than those of the CAH group as a whole, we have excluded them from the graphs because of the small number of observations in the group in any single year.

Profitability (see Tables B1 and B2) 

• Total Margin = (revenue-expense)/revenue

• Return on equity = (revenue-expense)/equity

There was a pronounced downward trend in profitability over the 1996-1999 period, for all groups of rural hospitals. Small rural hospitals had substantially lower median margins and return on equity measures than larger rural hospitals in all years. Converting-CAH hospitals were in worse shape than non-converting small hospitals, in every year other than the last. In four of the five study years, over half of the CAHs were operating with either negative margins or negative return on equity, or both.

For all years except 1998, the median values for both profitability indicators for PCH/MAF hospitals were negative. They were also considerably below the medians for the group of converted CAH hospitals as a whole.

Liquidity (see Tables B3 and B4)

• Days in accounts receivable = net patient accounts/average daily revenue

• Days cash on hand = (cash + cash equivalents)/average daily expenses net of depreciation

Liquidity measures provide an indication of the extent to which the organization is able to meet its current obligations. Two measures are provided here - days in accounts receivable (where lower is better) and days of cash on hand (where higher is better). The receivables ratio appears to have increased somewhat over the study period for all rural groups. Liquidity measures provide one of the few areas where the converting CAHs appear to do as well or better than other small or larger rural hospitals - although it should be noted that, at less than 25 days of cash on hand in all years, cash positions appear to be extremely tight for all of these hospital groups. 

Through 1999 there was very little difference in the median values for cash on hand across rural hospital groups. The change seen in the cash indicator in the year 2000 is startling, but it may be the result of fewer observations in this reporting year. 

Fixed Asset Measures (see Tables B5 and B6)

• Age of plant = accumulated depreciation/annual depreciation expense

• Fixed asset turnover = total revenue / net book value of property

Our two fixed asset measures provide insight into the overall capacity of the organization to provide service with its buildings and equipment. Smaller rural facilities tend to be older. The median age of plant for both CAHs and other small rural hospitals (about 12 years) seems to remain about two years greater than it is for larger rural hospitals. The median age of plant among former PCH/MAF hospitals was considerably higher than that for CAHs as a group. Although the PCH/MAF age of plant measure declined steadily over the study period it was still about 15 years by 1999.

The average age of plant is not a measure that should show sudden variation over time in grouped data, or even in individual hospitals (except in years when a major plant renovation or replacement has occurred). A gradual downward trend indicates that investment is taking place; an upward trend may be cause for concern, as evidence that existing assets are not being maintained or updated. 

Older facilities may still appear be relatively efficient users of capital. Fixed asset turnover is a measure of revenue generated per dollar of depreciated asset value. If assets are old, they will be heavily depreciated and their net book value will be relatively low, yet revenues generated relative to the book value may still be quite high. If a hospital's old facilities prevent it from attracting sufficient business (resulting in low revenues), then both the age of plant and the asset turnover ratios will be low. Turnover can also be relatively low if a facility has new or high-priced assets, but fails to bring in additional revenue as a result of its investment. Both the CAHs and other small rural hospitals appear to have generated slightly greater revenues per dollar of asset value, than have the larger hospitals. 

Capital Structure (see Tables B7 and B8)

• Long term debt to equity = long term debt/equity

• Cash flow to total debt = ((revenue-expense) + annual depreciation)/long term debt

Capital structure ratios give an indication of both the amount of debt a health care organization has taken on and its ability to repay that debt. The long-term debt-to-equity ratio is a commonly used measure of financial leverage. Very low values as well as very high values can be cause for concern. Median long-term debt to equity for the group of larger rural facilities is consistently higher than it is for smaller facilities, but the relative debt loads appear to be higher among converting CAHs than among other small rural hospitals; in 1999 the median was almost twice as high (0.28 compared to 0.14). 

The cash flow to debt ratio is used as a measure of creditworthiness, and indirectly, therefore, of access to capital. For this ratio, higher is generally better, but the indicator declined for all of our rural hospital groups from 1996 to 1999. The median for CAH-converting hospitals was considerably lower than the median for other small hospitals in the years for which complete data were available. 

The capital structure ratios through 1999 indicate that the amount of debt in both CAHs and other small rural hospitals is increasing in proportion to other financing, while their cash flow relative to that debt is decreasing. Without an increase in cash flow it may be difficult for either of these groups to obtain the financing necessary to upgrade their aged plant and equipment. 

Pricing and Market Strength (see Tables B9 and B10)

• Market-up ratio = (total patient charges + non-operating revenues)/operating expenses

• Deduction ratio = (total patient charges - net patient revenue)/total patient charges

In general, mark-up ratios vary across hospitals according to their proportions of charge-based payers and to their individual needs to fund uncompensated care and/or to accumulate surplus. The deductions percent is closely allied with the mark-up ratio; where mark-up evaluates charges relative to costs, the deductions percent is actually the inverse of charges relative to expected collections. The mark-up ratio computed for this study, however, includes non-operating revenues as well as patient charges in its numerator. Consequently, it can fluctuate with changes in a facility's external grant or tax-funded support.

Both of these ratios are noticeably higher for larger rural hospitals than for either group of smaller hospitals. Median mark-up ratios remained relatively constant over the study period through 1999. There is virtually no difference between the median ratios of the small hospitals that converted to CAH status and those that did not; each had close to a 25 percent markup (that is, a ratio of 1.25) and 25 percent deductions percent in each of the four complete study years. This raises a question about the ability of either group to a) set prices at a level sufficient to accumulate any surplus, or alternatively b) in more competitive markets where prices may be assumed to be externally dictated, to reduce unit costs to a level consistent with prevailing prices that are imposed by third-party payers.

The deduction percent should be responsive to CAH conversion. We expect to see an immediate reduction in this measure among hospitals that have converted from PPS to cost-based reimbursement, in the first year of post-conversion data. The median deductions percent for former PCH/MAF hospitals (included in Table B-10)) ranged from 9 percent to 13 percent over the study period, which is very low for the hospital industry, even in a cost-based reimbursement setting. Throughout the study period, this group had virtually no markup - median values of their markup ratios were actually less than one in three out of the five study years, indicating that full charges were set below cost, in at least half of the observations in this group.

Workforce Efficiency (see Tables B11 and B12)

• FTEs per adjusted patient day

• Net patient revenue per FTE

The two workforce efficiency measures summarized here show only slight differences between CAHs and other small rural hospitals and little change over the study period.  They are virtually identical in their net patient revenue generated per FTE ($60,000-$64,000, depending on the year). But, CAH converters tended to have used from one-half to one additional FTE per adjusted patient day. 

When we look at the labor efficiency indicators for the former PCH/MAFs, however, they are considerably worse. In each of the study years except 2000, this group generated 15-20 percent less revenue per FTE. Their median FTE per adjusted day ranged from a high of 12.0 in 1998 to a low of 9.3 in 2000, well above the range for the other small rural hospital groups (between 5.7 and 7.0) and larger rural facilities (about 5, across all years). 

The number of FTEs per adjusted patient day is a standard efficiency indicator in the hospital industry, but it is subject to some measurement error because of the additional requirement to estimate adjusted patient days. Other conditions being similar (including service mix), lower FTEs per adjusted patient day is preferable to higher. Where the mix of services across groups of hospitals is not similar, and/or patient acuity is not similar, net patient revenue generated per FTE can be a more effective measure of efficiency. 

Conclusions

The Rural Hospital Flexibility Program was adopted by Congress to help preserve the role of small rural hospitals as critical links in their communities' systems of care. It accomplished this by allowing certain small, limited service facilities the option of becoming cost-based providers under Medicare, as Critical Access Hospitals. Hospitals that had found it difficult to provide care to Medicare beneficiaries at average costs that were at or below the Medicare's national payment rates could become exempt from the prospective payment systems for inpatient and hospital-based outpatient care. Many hospitals studied this option and concluded that it offered them the possibility of eliminating hundreds of thousands of dollars in Medicare losses. 

The data reflecting the experience of rural hospitals in the period 1996-2000 cannot be used to accurately determine the effects of conversion to cost-based reimbursement. They can, however, help us to assess the extent to which the Flex Program has been adopted by the set of at-risk hospitals for which it was intended. Looking retrospectively at the conditions of groups of rural hospitals allows us to identify differences and time trends during their pre-conversion periods, and establish a baseline for later pre/post conversion analyses. 

The trend for all rural hospitals in our study was toward decreased profitability, but our findings indicate that small rural hospitals as a group were in worse overall financial condition than larger rural hospitals, in any given year. This is particularly evident with respect to measures of profitability, capital structure, pricing and work force efficiency. When we compared CAHs with other small rural facilities, CAHs showed considerably lower levels of profitability. In four out of five study years, one or both profitability indicators were negative for CAHs, indicating that any projected increases in Medicare payments were very much needed. CAHs also scored somewhat worse on measures of debt capacity and labor efficiency. In many other indicators, however, their performance was not easily distinguishable from the performance of small hospitals that have not converted. 

The use of long-term debt relative to other financing increased more quickly in the group of converting hospitals than it did for other small rural hospitals, while their median cash flow to total debt ratio decreased more quickly. We do not yet have data regarding increased cash flow resulting from cost-based reimbursement. The projected benefits of conversion that were identified from the telephone survey, however, seem likely to be particularly important to the ability of this group to finance upgrades to their plant and equipment.

For almost all of our indicators, the medians reported for former PCH/MAF hospitals were worse than those for CAHs as a group. There are a number of possible explanations for this, the most likely of which may be that the pilot hospitals were chosen from among the most geographically and financially challenged group of rural facilities to begin with. The fact that they continue to perform so poorly, however, raises the concern that eliminating Medicare losses is not a sufficient intervention to overcome severe financial difficulties in our most rural communities. 

Appendix A: Responses for Selected Questions from
Survey of CAH Administrators

A1 
Did your hospital conduct a financial feasibility study to obtain an estimate of the impact of conversion to CAH status on your net income?

(missing:2)

A2
If a financial feasibility study was conducted, how important were the results of the study, to your decision to convert to a CAH?

(not applicable: 29)
(missing: 1)

A3
How many financial studies were completed?