Managing care, incentives, and information: an exploratory look inside the\" black box\" of hospital...

$: Managing care, incentives, and information: an exploratory look inside the\" black box\" of hospital efficiency$
Articles

Managing Care, Incentives, andInformation: An ExploratoryLook Inside the "Black Box"of Hospital EfficiencyDouglas Conrad, Thomas Wickizer, Charles Maynard, TheodoreKlastorin, Daniel Lessler, Austin Ross, Naomi Soderstrom, SeanSullivan,Jejfrey Alexander, and Karen Travis

Objective. We sought to estimate the impact of individual dimensions of hospitals'managed care strategies on the cost per hospital discharge.Study Setting/Data Sources. Thirty-seven member hospitals ofseven health systemsin the Pacific, Rocky Mountain, and Southwest regions of the United States werestudied.Study Design. Separate cross-sectional regression analyses of 21,135 inpatient dis-charges were performed in 1991 and 23,262 discharges in 1992. The multivariatemodel was estimated with hospital cost per discharge as the dependentvariable. Modelrobustness was checked by comparing regression results at the individual dischargelevel with those at the level of the hospital/clinical condition pair.Data Collection/Extraction Methods. Information on hospitals' managed carestrategies was provided by mail and phone survey of key informants in 1991 and1992. Other hospital characteristics were collected from AHA Annual Survey data, anddischarge data from hospital abstracting systems.Principal Findings. The pooled discharge analysis indicated three dimensions ofhospital managed care strategy that consistently related to lower costs per hospitaldischarge: the proportion of hospital revenues derived from per case or capitationpayment, the hospital's mechanisms for sharing information on resource consumptionwith clinicians, and the use of formalized, systematic care coordination mechanisms.Conclusions. Three strategies appear to hold promise for enhancing the efficiencyof inpatient resource use: (1) "fixed price" hospital payment incentives, (2) hospitalapproaches to sharing resource use information with clinicians, and (3) the applicationofformal care management mechanisms for specific clinical conditions.Key Words. Managed care, care management, payment incentives, scope of services,care coordination, resource use

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236 HSR: Health Services Research 31:3 (August 1996)

The health care system of the United States is undergoing major transfor-mation, both in its delivery and its financing structures. This fundamentalchange is being driven by a variety ofsocial and economic forces-the growingsensitivity to high and rising health care costs by organized purchasers, theneed to ensure better access to affordable care for the substantial uninsuredpopulation, and the results of a variety of "natural experiments" suggestingthat better models ofhealth care financing and delivery are available (Salmon1994; Miller and Luft 1993). The concept of "managed care" is central tothe system changes now under way, and there is some evidence that certainforms of managed care can reduce health care costs without compromisingthe quality of care (Manning, Leibowitz, Goldberg, et al. 1984; Ware, Brook,Rogers, et al. 1986).

Simultaneously, as the health system has evolved toward managed careand more integrated health delivery models, a substantial movement of pa-tients from hospitals into alternative, less resource-intensive settings has beentaking place (Anderson 1992). In fact, the hospital is now commonly referredto as a "cost center" from the perspective of those paying a fixed premiumor capitation in return for assurance of access to a comprehensive range ofhealth services. Rather than being revenue generators or "profit centers,"hospitals are now being challenged to define a new role for themselves withinintegrated health delivery and financing organizations-for example, withinthe "community care networks" that (as envisioned by the American HospitalAssociation's proposal for health care reform) will assume financial risk for

This study was supported by a grant from the Industry-University Cooperative Center for HealthManagement Research housed at Arizona State University, which is a venture of the Networkfor Health Care Management, the National Science Foundation, and a consortium ofuniversitiesand health systems.

Address correspondence and requests for reprints to Douglas A. Conrad, Ph.D., Professor ofHealth Services, Department of Health Services, Box 357660, University ofWashington, Seattle,WA 98195-7660. Thomas Wickizer, Ph.D. is Associate Professor, Department of Health Ser-vices, University of Washington; Charles Maynard, Ph.D. is Research Scientist, Departnentof Cardiology, University of Washington; Theodore Klastorin, Ph.D. is Professor, Departmentof Management Science, University of Washington; Daniel Lessler, M.D., M.H.A. is AssistantProfessor, Department of Health Services, University of Washington; Austin Ross, M.P.H. isProfessor, Department of Health Services, University of Washington; Naomi Soderstrom, Ph.D.is Assistant Professor, Department ofAccounting, University ofWashington; Sean Sullivan, Ph.D.is Assistant Professor, Department of Pharmacy and Department of Health Services, Universityof Washington; Jeffrey Alexander, Ph.D. is Professor in the Department of Health ServicesOrganization and Policy, University of Michigan; and Karen Travis is a Doctoral Student in theDepartment of Economics, University of Washington. This article, submitted to Health ServicesResearch on December 14, 1994, was revised and accepted for publication on November 28, 1995.

"Black Box" ofHospital Efficiency 237

delivering comprehensive health services to a defined population (AmericanHospital Association 1992).

The hospital's role within this new paradigm is to provide acute inpatientcare efficiently to those who require such services, add value through pread-mission and postdischarge services, and provide population-based healthpromotion. Hospitals are moving toward an increasingly important role indeveloping a "seamlessly integrated" continuum ofhealth care (Hurley 1993).Even in the current regime, evolving as it is to fixed per case prices, capitation,and declining hospital days per 1,000 population, expenditures on hospitalcare sfill account for roughly 40 percent of total health care expenditures(Burner, Waldo, and McKusick 1992), so hospitals will play a crucial rolein determining the efficiency of the integrated delivery system. In light ofthe central place of hospitals in the overall health care cost structure, it iscrucial that clinicians, organizational managers and leaders, and policymakersgain better knowledge and understanding of the cost-efficiency of alternativemethods for managing the care process within the hospital. Ironically, in lightof the centrality of hospital operations in designing and implementing moreeffective and efficient health services, there is a paucity of empirical literatureon this subject.

Previous research has generally focused on measuring differences inlength of stay and charges between patients covered by fee-for-service versusHMO health plans. While the specific findings of studies have differed, moststudies have consistently documented a "managed care effect," showing thatHMO patients, on average, consume fewer hospital resources (Johnson et al.1989; Miller and Luft 1994). The reduction in resource consumption amongHMO inpatients occurs because these patients have shorter lengths of stayand use fewer ancillary resources during any given stay, and because the rateof admission to hospitals is lower for HMO enrollees (Manning, Leibowitz,Goldberg, et al. 1984; Miller and Luft 1994).

Unfortunately, much less is known about the contribution of hospital-based structures and processes to these outcomes. Indeed, there are virtuallyno available empirical studies of the effects of product line management (or,more broadly, of organization-managerial structures to support cost-effectiveinpatient care) on the actual use ofhospital resources. As Greco and Eisenbergobserve (1993), most studies of physician practice guidelines have looked atchanges in physician practices, but not at outcomes. Recent work by Welchand colleagues, which compared the resource intensity of physicians' carepatterns for Medicare inpatient stays in Florida and Oregon, exemplifies thesort of work that is needed (Welch, Miller, and Welch 1994). The literature


on the effects of hospital-physician integration on hospital cost is also quitesparse (Alexander and Morrisey 1988).

The "missing links" in previous studies of the impact of managed careon hospital inpatient resource use are twofold:

* The research has generally lacked a comprehensive theoretical frame-work for conceptualizing and measuring the hospital's strategy ofmanaging the care process; and

* There is still a need for empirical studies using multivariate modelsto estimate the simultaneous impact on hospital cost of the multiplecomponents of the hospital's overall managed care strategy.

The study presented here aims to supply both of these missing links: (1)by presenting a conceptual framework for managing the care process of thehospital (its "managedness") and (2) by modeling the simultaneous impacts onhospital cost of the multiple dimensions that represent the hospital's strategyfor managing care.

CONCEPTUAL FRAMEWORK

Agency theory in economics and sociology provides the motivation for theframework of this study. As articulated by Kenneth Arrow (1986), and morerecently by Mooney and Ryan (1993), hospitals and physicians act as "agents"for their patients, who are the "principals" in the relationship. Agency theorysuggests that the key attributes defining the efficiency of exchange betweenthe parties are the organization of exchange, incentives, constraints, information,and available opportunities.

These key attributes of exchange suggest five dimensions that capturethe "managedness" of the patient care process internal to a given hospital:

* Organization of exchange. This is measured by the scope of "lowresource-intensity" and "high resource-intensity" services availablein the hospital; the presence of an array of preadmission and post-discharge "substitution possibilities" that enhance the efficiency ofinpatient care by providing alternatives to inpatient hospitalizationwithin an integrated continuum of care; and the extent of integra-tion of physicians within the management and organization of thehospital.

* Intensity of the incentives facing the hospital for constrainingresource use. This is measured by the use of capitation or per case

"Black Box" ofHospital Efficiency

payment to the hospital and maturity of managed care contracting,both of which encourage reductions in hospital cost.

* Constraints. Constraints are measured as the use of formal hospitalarrangements for organizing and coordinating the delivery of patientcare, which is expected to result in lower hospital costs per discharge.

* Information. This is measured as the depth and breadth of informa-tion exchange within the hospital regarding resource use, particularlywith physicians.

* Opportunities. Finally, market area factors extemal to the hospitaldetermine the opportunities available to physicians, hospitals, andpatients. In areas with a greater proportion of the population in healthmaintenance organizations (which are subject to fixed price capita-tion) and a larger number of active physicians, one would expect thepressure from those "competitive" factors to result in lower hospitalcosts. In contrast, controlling for total physician supply, an increasednumber of specialists may result in increased intensity and cost ofhospital care. Similarly, a larger number of hospital beds per capitaeffectively "loosens" the constraint offixed capacity, thus encouraginglonger lengths of stay and higher costs per discharge.

Thus, in examining the effect of managed care on hospital resourceuse, this study team is not addressing whether HMOs, PPOs, point-of-service(POS) options, and direct contracting per se are associated with reducedinpatient resource use. Instead, the analysis transcends this typical view of"managed care" by estimating how specific structures, incentives, and pro-cesses embodied in the management of care within the hospital, as well asexternal market factors, actually influence hospital resource consumption.This is the meaning of "managedness" in this study.

METHODS

DESIGN OVERVIEW

The hospitals participating in this study were drawn from seven participatinghealth systems (headquarters in parentheses) with complete data for analysisin fiscal years 1991 and 1992: Franciscan Hospitals of Washington (Tacoma,Washington); Intermountain Health Care (Salt Lake City, Utah); Samari-tan Health Services (Phoenix, Arizona); Sisters of Charity Western Region(Colorado Springs, Colorado); Sisters of Providence (Seattle, Washington);

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240 HSR: Health Services Research 31.3 (August 1996)

Tucson Medical Center (Tucson, Arizona), and Virginia Mason MedicalCenter (Seattle).

SAMPLING

The study hospitals are similar in bed size to the universe ofshort-term generalhospitals in the United States. The average number of staffed beds per studyhospital is 162, quite similar to the national average of 173 for all communityhospitals in 1991 (American Hospital Association 1993). The average ratioof interns and residents per bed is .02, well below the national average of.06 prevailing in 1991 (American Hospital Association 1993), reflecting theabsence of academic medical centers among the study hospitals. A largerproportion of study hospitals are in urban areas (72 percent in the studysample versus a national community hospital average in 1991 of 55 percent),primarily reflecting the concentration of many of the systems in large ormedium size metropolitan areas. Study hospitals are located in the states ofArizona, Colorado, Idaho, Oregon, Utah, Washington, and Wyoming.

The analysis concentrates on six important clinical conditions that arejudged to be amenable to formal care management, and that represent aspectrum of chronic and acute health problems and medical and surgicalprocedures: hip replacement, acute myocardial infarction (AMI), congestiveheart failure (CHF), stroke, chronic obstructive pulmonary disease (COPD),and pneumonia. AMI and CHF were included in the Medical OutcomesStudy (Greenfield, Nelson, Zubkoff, et al. 1992); stroke (Stern et al. 1989)has been the subject of inpatient resource use comparisons of fee-for-service(FFS) andHMO patients; and hip replacement problems should offer a usefulcontrast for surgical versus medical problems.

DATA COLLECTION

Uniform individual hospital discharge abstracts are the database used inthis study to characterize the content and economic outcomes of individualhospitalizations. Uniform hospital discharge abstract systems for the states ofColorado, Idaho, Oregon, and Washington, and for the systems ofIntermoun-tain Health Care, Samaritan, and Tucson Medical Center, are the source ofthis information.

Original hospital surveys also were conducted for the hospitals' 1991and 1992 fiscal years. These surveys supplied the data for measuring managedcare variables relating to hospital payment incentives, coordination and orga-nization of care delivery, information exchange, and hospital-physician inte-gration. In addition, the American Hospital Association 1991 Annual Survey


data were used to measure other baseline hospital characteristics not includedin the original hospital surveys: staffed hospital beds, teaching activity (internsand residents per bed), scope of services, and the hospital continuum ofcare(specifically, the preadmission and postdischarge "substitution possibilities"incorporated as one of the five dimensions of "managedness"). The mostrecent Area Resource File data from the Bureau of Health Professions (yearsare in parentheses) were used to measure hospital beds, total active physi-cians, and specialists per capita (all 1990 data) by county. The InterStudyCompetitive Edge data (1991 and 1992) were used to measure the number ofHMO enrollees per (multi-county) plan area, and since enrollment by countywas not available, plan area enrollment was allocated to county within eacharea in proportion to county population.' Thirty-seven study hospitals fromthe seven health systems provided complete data for all of their FY 1991and 1992 discharges for six clinical conditions: acute myocardial infarction(AMI), congestive heart failure (CHF), stroke, chronic obstructive pulmonarydisease (COPD), pneumonia, and hip replacement, and on the independentvariables included in the statistical analysis.

STATISTICAL METHODS

The principal method of data analysis is ordinary least squares (OLS) regres-sion,2 with cost per hospital stay as the outcome variable. Hospital costs perdischarge are calculated by multiplying total billed institutional charges perdischarge by the hospital's overall ratio of cost-to-charges.3 It is recognizedthat the cost:charge ratio method for measuring costs has several limitations:(1) the "step-down" allocation of overhead costs to hospital revenue centersmay not accurately represent "true" indirect costs; and (2) the order of allo-cation by overhead cost center may distort the results and is therefore subjectto gaming by hospitals attempting to maximize cost-based reimbursementper discharge. However, it was not feasible to collect original "micro cost"data in this study, nor was cost-based reimbursement sufficiently important in1991-1992 for there to exist much scope for gaming the step-down formula.In addition, the cost:charge method is unlikely to induce bias in the estimatedcoefficients of the managed care variables.

OLS regression equations are estimated for the dependent variable ofcost per discharge, transformed to its natural logarithm ("In cost") in order toreduce skewness and to produce more well-behaved and easily interpretedestimates. The regression analysis examines cost per individual hospital dis-charge (henceforth termed "individual discharge-level" analysis). Only theindividual discharge-level analysis is presented in this article, but regressions


also have been estimated at-the level of the hospital/condition pair (e.g.,Virginia Mason Medical Center treatment of inpatients with stroke) as a wayof validating the analysis.4 Separate regression equations are estimated for1991 and 1992. The regressions for each year and level of analysis have beenestimated two ways: (1) including all observations and (2) excluding outliers(defined as observations for which the natural logarithm of cost was either >or < 3 standard deviations from the sample mean). The analysis presentedhere focuses on the regressions including such outliers, since estimates werelittle changed.

Four categories of independent variable are used in the regressions:(1) hospital- and patient-level control variables, such as hospital bed size, caseseverity,5 and teaching status: basically, these are intended to adjust for hos-pital and patient characteristics that might otherwise confound one's ability toisolate the effects of "managedness"; (2) managed care variables, to capture thefive dimensions of "managedness" that are of primary interest in this study;(3) market area and regionalfactors (a regional dummy is specified to captureunmeasured differences in health care cost factors between the Northweststates-Washington, Oregon, Idaho, and Wyoming-and the Southwest states-Arizona, Colorado, and Utah-in our sample); and (4) hospital system-specificindicator (0,1) variables, to reflect fixed effects of the different hospital systemsthat otherwise are not measured by the other factors in the model. Since thehospital's managed care strategy at a given point in time might be a responseto high costs, the hospital is generally coded as having a particular managedcare strategy in year t (e.g., 1992) only if that strategy has been in place sinceat least year t - 1 (e.g., 1991). This mitigates the "endogeneity" problemone encounters in trying to distinguish between the effect of managed carestrategy on costs and the response of such strategy to those same costs.6

RESULTS

DESCRIPTIVE STATISTICS

Table 1 presents the individual discharge-level means and standard deviationsofthe hospital and patient characteristics and the managed care variables usedin the analysis. Based on the sample's average value of the area hospital wageindex (1.01 on a scale where the national average is 1.00), average labor inputprices for study hospitals seem to be representative of national levels. Onaverage, study hospitals offered three of the six possible services measuredin the "low intensity" service score, and three of the ten services of "high


resource intensity." The average age of patients treated in study hospitals forthe six clinical conditions was 66 in both years, and approximately half (46-48percent) of discharged study patients were women.

The sample averages of the managed care variables indicate the rel-atively nascent stage of "managedness" characteristic of study hospitals in1991-1992. As of 1992, 83 percent of the hospitals had been involved inmanaged care contracting for at least three years (indeed, roughly 87 per-cent had their own or a system-sponsored managed care plan), and theyoffered an average of slightly more than seven services (of 15 possible on thecontinuum of care scale) providing "substitution possibilities" both pre- andpost-hospital discharge. Nonetheless, study hospitals' financial incentives andsystematic care management processes were, for the most part, embryonic asofFY 1991-1992. For example, on average, only 43-45 percent of hospitals'revenues were based on per case or capitation payment (including Medicareprospective payment by DRGs, which accounts for 30-40 percent of mosthospitals' revenues on a per case basis). The share of revenues paid bycapitation averaged only 6 percent for study hospitals during this period.Only one in seven study hospitals had implemented systematic care coor-dination strategies for the specific clinical conditions as of 1991, althoughthe proportion rose to one in four as of 1992. Thirty-two percent of studyhospitals had salaried relationships with physicians providing patient care(not primarily in administrative roles), but the average number of salariedphysicians per hospital was only five or six; and 7-14 percent of the hospitalswere involved in exclusive contractual relationships with physicians for someof the clinical services related to the six conditions studied here. Fewer than30 percent of study hospitals had formal product line management in placefor one or more of the six clinical conditions.

REGRESSION RESULTS

The results in Table 2 can be used to estimate, at the individual dischargelevel, the average impact of "managedness" dimensions on hospital costsfor any of the six conditions for the 37 hospitals reporting complete data inboth 1991 and 1992.7 In drawing final conclusions, however, results fromthe hospital/condition-level analysis will be cross-referenced as a means ofvalidating the individual analysis. Since the data have been analyzed for twoyears, the estimates of impact are generally presented as ranges in the text thatfollows.8 Where the impact coefficient is statistically insignificant (p > .05,two-tailed test), this is noted in the presentation of results.

243


Table 1: Descriptive Statistics for Study Variables1991 Mean 1992 Mean

Variabk (Definition) Value (s.d.) Value (s.d.)Cost per stay (In) 8.262 (.804) 8.331 (.799)Staffed hospital beds 287.418 (143.662) 292.359 (136.610)Number of diagnoses 2.892 (1.301) 3.309 (1.157)Patient age 65.878 (19.676) 66.341 (19.486)Sex (% women) .458 (.498) .477 (.499)Low-intensity service score* 3.190 (1.259) 3.21 (1.22)High-intensity service scoret 3.401 (2.236) 3.52 (2.15)Interns and residents/staffed bed .036 (.077) .037 (.076)Proportion in urban area .729 (.445) .716 (.451)Hospital area wage index 1.01 (.08) 1.01 (.08)Continuum of care score* 7.39 (2.19) 7.55 (2.15)% of revenues capitated/per case 42.97 (10.53) 45.18 (15.07)(0,1) 3 yrs. managed care contracting .818 (.386) .833 (.373)(0,1) system/own managed care plan .747 (,435) .869 (.337)Condition-specific care coordination score .141 (.400) .320 (.620)Global care coordination score§ .134 (.269) .375 (.462)(0,1) Salaried physicians in clinical services .316 (.465) .417 (.493)

(condition-specific)(0,1) Physicians under exclusive contract

(condition-specific)(0,1) Low levels of resource reporting to

physicians (not specific to condition)(0,1) Variable for resource reporting specific

to condition

Global score for condition-specific resourcereportings

(0,1) Variable: condition-specific productline management

Number of hospital-salaried physicians(square root)

(0,1) HMO enrollees per capita in county

.066 (.249)

.354 (.478)

.245 (.430)

.284 (.344)

.264 (.441)

1.893 (2.028)

prop. med.: .060 (.238);prop. high: .557 (.497)

.135 (.342)

.279 (.448)

.505 (.500)

.555 (.428)

.350 (.477)

2.30 (2.42)

prop. med.: .101 (.302);

prop. high: .525 (.499)

Continued

'Black Box" ofHospital Efficiency

Table 1: Continued1991 Mean 1992 Mean

Variable (Definition) Value (s.d.) Value (s.d.)Hospital beds per capita in county .003 (.001) .003 (.001)

Total physicians per capita in county .002 (.001) .002 (.001)

Specialists per capita in county .001 (.000) .001 (.000)

*This score was computed as a count of the number of available services from the following listof facilities and services of lower resource intensity: emergency department, medical-surgicalICU, cardiac ICU, CT scanner, blood bank, and obstetrics provided through another facility.

tThis score was computed as a count of services from the following list of somewhat higherresource intensity: neonatal ICU, neonatal intermediate care, pediatric ICU, burn care, cardiaccatheterization laboratory, MRI, x-ray radiation therapy, trauma center (certified), bone marrowtransplant, own obstetrics service.

4:This score is a count of services available from the following list: adult day care, geriatricclinic, patient education, home health services, hospital-based outpatient center, freestandingoutpatient center, outpatient rehabilitation, organized social work services, outpatient socialwork, subacute rehabilitation, subacute chronic disease care, hospice, SNF services, Medicare-certified swing beds, and presence of separate long-term care, nursing home type, unit.

§This is the average of the condition-specific scores for each of the clinical conditions.

Patient, Hospital, and Market Area/Regional Effects on Cost

The number of diagnoses per individual discharge is significantly related tohigher cost per discharge in both years. Patient age also is positively associatedwith cost: a 10 percent increase in patient age is related to an increase in cost ofapproximately 1-2 percent. Holding constant the clinical condition and otherfactors, cost per discharge is roughly 5 percent lower for women (p < .10 in1991 only). Costs also vary substantially across conditions. Other factors heldconstant, for example, cost per discharge is roughly 14-16 percent higher forpneumonia patients than for those with CHF (the omitted category in theregression'.

Looking at hospital factors, the hospital wage index has the greatesteffect on cost: a difference in the direction of 10 percent higher hospital laborinput prices is associated with costs from roughly 26 to 32 percent higher.Patient and hospital characteristics overall account for almost 30 percent ofthe total variance in hospital costs per discharge in the study sample.

Hospital costs per discharge in 1991 are 9 percent lower in marketswith an intermediate level ofHMO enrollees per capita (relative to those inareas of relatively low HMO enrollment), and 20 percent lower in areas of

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'Black Box" ofHospital Efficiency 249

high HMO enrollment. The differences in cost by level ofHMO penetrationin 1992 are somewhat smaller and marginally significant (p < .10). A 10percent higher beds per capita ratio is associated with approximately 5 percenthigher costs per discharge (but only significant in 1992). A 10 percent risein physicians per capita relative to the mean is related to approximately a 4percent decline in costs per discharge. A rise of 10 percent in relative specialistsupply is associated with roughly a 7 percent increase in hospital cost perdischarge in 1991, but the impact is insignificant in 1992. The market areavariables as a whole account for a relatively small proportion of the variancein hospital cost per discharge-roughly 0.1 percent and 0.5 percent in 1-991 and1992, respectively. The proxy for Northwest states (region) accounts for about0.1 percent of the variance in costs. The coefficient of the Northwest regiondummy switches from -0.617 in 1991 to +0.322 in 1992 (both significant,p<.01).

'Managedness"Dimensions

Overall, controlling for hospital and patient characteristics and the hospitalsystem indicators, the managed care variables account for approximately 3percent of the variance in hospital costs per discharge in both years. Resultsfor specific dimensions of "managedness" in the individual-level analysesare summarized next, following the constructs identified in the conceptualframework.

Scope ofLow- andHigh-Intensity Services and Continuum ofCare. The costsof hospitals decline by approximately 2 percent with a 10 percent increase innumber of their low-intensity services, and by approximately 1 percent for anequivalent increase in the number of high-intensity services (significant onlyin 1992). Contrary to expectations, the index of breadth of the hospital's carecontinuum is positively related to cost (significant only in 1991), suggestingapproximately a 9 percent rise in hospital cost in 1991 for a 10 percent increasein the continuum measure.

Intensity of Incentives. Hospitals with a higher percentage of revenuesfrom managed care contracts paying on a capitation or per case basis havesignificantly lower costs per stay, other things equal. Costs per stay ofhospitalswhose share of revenues from per case or capitation contracts is 10 percentabove the sample average (43 percent in 1991, 45 percent in 1992) are roughly0.10 percent lower in 1991 and 0.01 percent lower in 1992. Hospitals withtheir own or a system-sponsored managed care plan experience significantlylower costs per hospitalization, but only in 1992. Other things equal, the


presence of one's "own plan" is related to approximately 35 percent and 22percent lower costs in 1991 and 1992, respectively.

Maturity of managed care contracting-defined as whether the hospitalhas been involved in managed care contracting for at least three years-isassociated with roughly 17 percent higher cost in 1992. The difference ismuch smaller and insignificant in 1991, however.

Coordination and Organization of Care Delivery. The use of formal casemanagement, critical nursing pathways, and/or physician clinical guidelines(varying from a score of 0 for none of these potentially complementaryapproaches to 3 if all have been adopted) is related to significantly lower costsper stay. The regression coefficient on condition-specific care coordination impliesthat adoption of one of these approaches for a particular clinical conditionlowers costs per stay by approximately 7-12 percent (using the 1991 and 1992estimates, respectively). Looking at the coefficient on global care coordination,hospitals adopting an average of one care coordination strategy per conditionhave costs from approximately 14 to 52 percent less than those without anyof these formal coordinative mechanisms.

On the other hand, product line management, measured by whether thehospital has implemented a formal clinical progran with budgeting, plan-ning, and/or staffing organized around that program or service line (definedaccording to the clinical category whose cost per discharge is being estimated),is not related to lower costs per stay. Indeed, the 1991 and 1992 resultsindicate that, on average, the adoption of product line management for agiven clinical category is associated with costs that are significantly higher-by8 to 14 percent.

Hospital-Physician IntegrationHospital-Employed Physician Relationships. Estimates from the multivari-

ate model imply that the number of hospital-employed physicians is relatedto lower hospital cost per discharge in 1991 (p < .05), but the coefficient ispositive and insignificant in 1992.

Salaried Relationships with Physicians in a Particular Clinical Category.Having salaried physicians on the clinical services related to a particularcondition (e.g., cardiologists are involved prominently in treating strokes)is associated with 6 percent higher costs in 1991, but insignificantly lowercosts in 1992.

Exclusive Contractual Relationships with Physicians. In the 1991 data thepresence of exclusive contractual relationships with physicians in a particularclinical service is related to higher costs, by approximately 12 percent per

"Black Box" ofHospital Efficieny 2

discharge. However, the same variable is not statistically significant in the1992 analyses.

Information Provision and ExchangeWritten Reports, in General, to Physicians on Resource Consumption. Hos-

pitals that provide written resource consumption reports to their physiciansin general, but not specific to any of the six conditions included in this study,have costs from 13 percent (1991) to roughly 42 percent (1992) lower thanthose that do not.

Resource Consumption Reports to Physicians for the Specific Condition. Thecosts per stay of hospitals providing reports to their physicians on resourceconsumption for the specific condition (e.g., stroke, hip replacement) areapproximately 12 percent (1991) to 27 percent (1992) lower than those thatdo not provide reports specific to that condition. Breadth of condition-specificresource reports-as measured by the proportion of the six conditions forwhich such reports are provided-is associated unexpectedly with significantlyhigher costs per discharge in 1991-a rise of about 20 percent in cost for a10 percent rise in the global score for condition-specific reporting, although thecorresponding effect for 1992 is much smaller and not statistically significant.

Condition-Specific Resource Reports Providing Physician Peer Comparisons.After controlling for other aspects of the hospital's approach to sharing infor-mation on resource use with physicians, the use of peer comparisons is notrelated to significant differences in hospital cost per discharge.

Hospital-System Indicator VariablesFive ofthe six dummy variables included to capture "system-level" differencesin cost not otherwise measured in the model are highly significant (p < .01)in 1991 (relative to the seventh system treated as the reference category).All but the coefficients for systems four and six are significant in 1992, also.The system variables jointly explain only 0.2 percent of the variance in costin 1992, but a much larger 1.1 percent in 1991. The relative size of thosecoefficients is not consistent for the two years.

DISCUSSION

This study provides relatively consistent support for the positive role of pro-spective payment and financial incentives and formalized, systematic carecoordination strategies in containing hospital costs per discharge. Both of

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these findings are consistent with the results of regression analysis (not shownhere) at the level of the hospital/condition pair. The evidence also indicatesthat structuring a broader scope of low-intensity services in the hospital willlower costs per discharge. However, a more well-developed continuum ofpre- and postdischarge possibilities per se does not seem to lead to lowerhospital costs, and this is a puzzle in light of the apparent efficiency gainsfrom a broader scope of low-intensity services, other things equal. Absentconsistent evidence that both the scope of services and breadth of the carecontinuum enhance efficiency, one must remain somewhat skeptical of theapparent cost reduction associated with increased scope.

Providing information on resource use in general to physicians andspecific to clinical conditions such as those in this study also appears tooffer relatively large and significant efficiency benefits to the hospital, but theparadox remains of higher costs in 1991 for hospitals with greater breadth ofresource use reporting across conditions. We place less emphasis on this para-dox in interpreting our findings, however, because the hospital/condition-level regression analysis suggests consistently (for 1991 and 1992 and forthe condition-specific dummy variable and global care coordination scores)that condition-specific resource reporting contributes to lower hospital costs.The evidence in this article is equivocal on the question of whether hospital-physician contractual relationships increase efficiency.

On balance, we conclude that what matters most in this exploratorystudy of hospital efficiency is the intensity ofpayment incentives, the application ofsystematic strategiesfor managing the clinicalprocess ofpatient care, and theprovisionto physicians of information on resource use. These aspects of "managedness"represent a radical departure in emphasis from the conventional use of theterm "managed care," which generally refers to a mix of constraints andincentives applied to the patient's choice of physician and the physician'schoice of diagnostic and treatment regimens for individual patients.

INCENTIVES

Clearly, per case and capitation payment incentives to hospitals do resultin cost savings per discharge, but-given the relatively low penetration ofcapitation contracts in our sample-it is not surprising that the size of thosecost effects is relatively small in this exploratory study. Structured phone inter-views with study hospital managers imply that these "at-risk" contracts haveacted as "triggers" for physicians to collaborate with hospitals in designingmore integrated health delivery models. For example, in one local marketwith a relatively high penetration of capitation payment to hospitals, a group


of cardiologists has taken the initiative to develop a stroke rehabilitation clinicto expedite discharge from the hospital and provide enhanced post-hospitalcare. Generally, before a hospital will enter into a capitation contract, it willcraft a collaborative arrangement with a physician organization to assumejoint financial risk. Interestingly, the maturity of the hospital's experiencewith managed care contracting does not seem to relate to lower costs, oncethe direct effects of factors such as the intensity of payment incentives, carecoordination, and resource use reporting to physicians are taken into account.

This study presents somewhat promising evidence on the cost effects ofa hospital's having its own or a system-sponsored managed care plan, withrelatively large diminution in cost in both years, associated with having one'sown plan. The observed "effect" of this variable is probably a proxy for otherunmeasured phenomena associated with the hospital's or system's decisionto implement its own managed care plan. For example, the managementincentives of the hospital that has its own plan are more aligned with thecost-reducing perspective of the payer. Moreover, the plan acts like a "bill-board," announcing to clinicians that the hospital's activity must increasinglybe attuned to minimizing cost and maximizing health status for the largestnumber of covered lives. Maturity of the hospital's managed care activityis positively related to the presence of the hospital's own plan, and thusunmeasured "learning curve" effects on hospital costs may be captured inour estimates of the hospital's own plan effect.

ORGANIZATION AND COORDINATIONOF CARE DELIVERY

By its very nature, a broad, exploratory study such as this one cannot providedefinitive answers regarding the relative cost-efficacy of different methodsof managing the care process. Surely, answers to those questions lie in thedetails ofhow such care process models are designed, implemented, and eval-uated over time. This study's structured telephone interviews with hospitalmanagers revealed that concepts such as case management, critical nursingpathways, and physician clinical guidelines were defined differently acrosshospitals. Thus, the investigators chose to evaluate the cumulative intensity of agiven hospital's formal care management, rather than the independent effectsof individual methods (e.g., critical paths versus physician guidelines).

Subject to that caveat, the multivariate estimates imply that both thespecific intensity of care management for a given clinical condition and itspervasiveness contribute to significant cost efficiencies in the hospital. Inter-views with hospital managers in late 1993 and early 1994 reveal that the use

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of internal utilization review, care management committees, and physicianguidelines is accelerating, and that the study hospitals are integrating theircost management activities within a broader continuous quality improvementstrategy. The finding that the average level of care management across con-ditions actually influences resource consumption for a particular condition,after controlling for care management of that condition itself, implies thatthere may be a kind of "organizational culture" that generally encourages moreefficient care processes via the broad adoption of case management, criticalnursing pathways, and physician clinical guidelines.

Previous conceptual work has generally suggested that administrativesupport structures will facilitate clinical integration, and there is a positivecorrelation in our sample between the level of care coordination and theadoption of one particular form of administrative support-product line man-agement. In light of the salutary evidence regarding the relationship of carecoordination to efficiency, the positive association between cost and the pres-ence of product line management is puzzling-particularly since the definitionof product line management in this study attempted to exclude "windowdressing," or purely marketing and promotional programs. A finding of noeffect would not have been as surprising, but it is not clearwhy hospitals wouldconsciously devise an administrative structure likely to increase costs-unlessthere is an offsetting health benefit. Yet, surely, product line management perse would have at most a distal impact on health outcome.

INFORMATION PROVISION AND EXCHANGE

For this particular sample of hospitals, substantial and statistically significantreductions in hospital cost per discharge are surprising, in light of Elden-burg's (1991) finding that peer comparisons were the only information vari-able associated with hospital charges per discharge. Perhaps the difference isattributable to the hierarchical way in which information sharing was mea-sured in this study or to the distinction between charges and costs as measuresof resource use.

Market Area/Regional Factors. Given the market conditions prevailingin this study, it appears that hospitals in areas with larger numbers of bedsdo apply somewhat more resources per case (although the difference wassignificant only in 1991), perhaps because inpatient capacity acts as lessof a constraint in those markets. Conversely, physicians in areas havinga larger total supply of physicians appear to use inpatient resources moreconservatively. This may be due to greater "competition" among physiciansfor access to hospital beds in such markets. This is also consistent with the


natural incentive of physicians to serve as "agents" for their patients, seekingto minimize total health cost per person, as suggested by Mark Pauly (1980). Incontrast to the impact of total physician supply on costs, there is a suggestionthat an increased supply of specialists per capita is associated with increasedhospital cost (significantly so in 1991).

Most studies (Miller and Luft 1993) have found a small, negative impactofHMOs on community-wide hospital cost, and our findings are consistentwith this general pattern. We have no ready explanation for why the 1991coefficients are highly significant while those for 1992 are only marginallysignificant (p < .10), and why the dummy for markets with intermediateHMO penetration is unexpectedly positive in that year.

It does appear that certain cost factors not direcdy captured in our modeldo differ systematically between the northwest and southwest states in oursample. However, we do not have a ready explanation for why the cost effectsof those factors differ for the two years.

Hospital-System Indicator Variables. The inclusion of dummy variablesfor identity of the system to which each hospital belongs represents an impor-tant feature of the empirical work in this article. The fact that those indicatorvariables, while generally significant, were not consistently ordered in sizeover the two study years suggests that these fixed effects may be reflectingother variables omitted from the model but correlated with system identity.

CONCLUSION

An exploratory study such as this one, based on two cross-sections ofinpatientdischarges in a purposive sample of hospitals, cannot offer the final wordon the cause-effect relationship between hospitals' "managedness" and theircosts per discharge. To do that would require (1) a substantially larger, randomsample of hospitals; (2) a dataset examining cost, "managedness," and marketfactors for several time periods; and (3) a deeper look into the details ofthe design, implementation, and evaluation of the particular care processmodels9 used in hospitals to manage the care of patients. In particular, itis acknowledged that the lack of consistency in the sign and significanceof the effects of certain variables for 1991 and 1992 probably reflects thelimitations ofknowledge regarding the true underlyingmodel ofcost behaviorand consequent misspecification of our empirical work.

While not definitive, we do believe that this study's findings suggestthat hospital efficiency can be promoted by at least three strategies related

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to managing the process of inpatient care: (1) developing payment arrange-ments under which the hospital assumes economic risk (e.g., capitation or percase/DRG); (2) intensifying the management of the care process for specifichealth problems-through case management, critical nursing pathways, andphysician clinical guidelines; and (3) providing systematic, regular informa-tion to physicians on resource consumption in the care of their patients.

As policymakers and health care executives consider the place of thehospital within the larger organizational context of future integrated healthsystems, they may wish to consider the specific findings of this study. Thepatterns of "managedness" and market area characteristics that seem to relatesignificantly to hospital cost per discharge can be useful guideposts for placesto look first in configuring the hospital's role witiin those integrated deliveryand financing systems.

NOTES

1. This procedure, while arguably the best one available to us, probably has theeffect of overstating the HMO:population ratio in areas of larger population, andthus it may lead to an underestimate (downward bias) of the absolute value of the(negative) coefficient measuringHMO penetration's hypothesized effect ofloweringhospital costs.

2. The residuals from both the 1991 and 1992 regressions are approximately normallydistributed and the null hypothesis ofno first-order autocorrelation in the residualscannot be rejected in the data, so the application ofOLS appears appropriate. TheDurbin-Watson small-sample statistic was used as a test for autocorrelation, andthe values of 1.90 and 1.85 for 1991 and 1992, respectively, were above the upperbound of 1.78-thus failing to reject the null, at least for a small-sample approxi-mation to this application (for five independent variables and 100 observations).SeeJohnston (1972, 251-53 and 430-31).

3. This information is based on Medicare Cost Report data for FY 1991 and 1992provided to us by Gerard Anderson of theJohns Hopkins University Center forHospital Finance and Management.

4. The latter analysis is referred to as the "hospital/condition-level" analysis. Thehospital/condition-level analysis was performed as a validation of the individ-ual discharge-level regressions. This seemed advisable for two reasons: (1) sincemanaged care strategies are adopted at the hospital/condition level, such an ana-lytic approach matches the unit of observation with the unit of the phenomenonunder study; (2) the use of hospital/condition pairs as the unit of observation(n = 201) and analysis will produce more conservative statistical significance testsof hypothesized managed care effects than the individual-level regressions. Thehospital/condition-level regression for each year was estimated in two steps. First,a regression was run at the individual discharge level, with In (cost) as the dependent


variable and the following regressors: patient age, sex, number of diagnoses, anddiagnoses-squared (measures of comorbidity), and a vector of 201 dummy (0,1)variables identifying uniquely each hospital/condition pair. Second, the coeffi-cients on each hospital/condition dummy variable were saved and used as theobservations (n = 201, given 37 hospitals and five or six conditions representedin each hospital) for a second regression, in which the dependent variable wasthe hospital/condition dummy variable coefficient from the first regression. Theregressors in the second equation were the set of control variables for hospitalcharacteristics, dummy variables to identify the clinical condition of each hos-pital/condition pair, and the managed care variables. Each observation in thesecond regression was weighted by the reciprocal of the standard error of the cor-responding hospital/condition dummy variable coefficient from the first equation(1/S.E.B).

5. For case severity, we have used two kinds of measures in our work. One is basedon a version of the 3M HCIS case severity scoring system, which uses secondarydiagnoses to classify discharges within DRG into four levels of ascending comor-bidity. The second method simply counts the number of secondary diagnosesand that number squared per discharge to derive a measure of comorbidity and,thus, one dimension of case "severity." Because the HCIS method uses proceduresperformed as part of the algorithm and we desired a baseline measure of initial, or"presenting" severity, we opted for the second method in this article.

6. Moreover, it should be noted that any "simultaneity bias" in our estimates due tothis potential endogeneity of cost and managed care strategy will be in a conser-vative direction. That is, one would expect high-cost hospitals to be more likely toadoptmanaged care strategies as ameans oftrying to lower costs; this would tend tobias ordinary least squares regression coefficients toward positive values-therebyworking against our alternative hypothesis that adoption of managed care tends tolower cost. We attempted to model the exogenous determinants of the dimensionsof hospital "managedness," but the number of study hospitals provided too fewdegrees of freedom for such an approach to yield sufficiently precise estimates foruse in two-stage least squares or instrumental variables.

7. The language in the text frequently refers to "impact" and the effect of "changesin" particular dependent variables; this is to avoid the continual use of unwieldyphrases like the "difference in" cost "related to" a given "difference in" a particularindependent variable.

8. Impact sizes for dummy (0,1) variables are measured directly from the Table 2regression coefficients as proportionate changes (in switching from the omittedcategory, value 0, to the included category, value 1). This interpretation is exactfor small changes (in the calculus, dln(y)/dy = l/y, so, by the chain rule, dln(y)/dx= (dy/y)/d4, where x "switches" from 0 to 1 for dummy variables. For continuousvariables and "small" (literally, approaching zero) changes in costs per discharge,the coefficient measures proportionate change in cost for a "one unit" change inx. For selected continuous variables of interest in this study, the "elasticities" arepresented as "E = (value)" directly next to the coefficient and its t-statistic. Theelasticity is calculated (by the preceding reasoning) as: = x's coefficient multiplied

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by its mean value. The "elasticities" are presented as the percentage change in costfor a 10 percent change in the continuous variable. Thus, they are actually .1 timesthe estimated elasticity.

9. BrentJames (1994) has suggested this more generic term for delineating the dif-ferent methodologies that providers might apply to managing the care processthrough clinical and administrative approaches.

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