Health Care Specialization and Asymmetric Competition:
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Health Care Specialization and Asymmetric Competition: The Dynamics of Surgery Center and Hospital Exit Michael G. Housman Health Care Management Department University of Pennsylvania, The Wharton School Health Care Specialization • Growth of specialized health care providers: – Specialty hospitals – Ambulatory surgery centers (ASCs) – Other services (e.g., cardiac catheterization, lithotripsy, radiation therapy, diagnostic imaging, etc.) • Shift to service line competition in health care – Hospitals pushed to peripheral role (Robinson, 1994) – Number of US hospitals has been steadily declining Specialty Hospitals vs. ASCs • Specialty hospitals under tremendous scrutiny – Congress enacted moratorium on new hospitals – Just over 100 specialty hospitals in the US • Much less attention being paid to ASCs – CMS proposed a major expansion to procedure list – Currently 6,091 ASCs operating in the US • Very little research on the impact of ASC entry – Decline in hospital outpatient volume (Plotzke, 2008) – Decline in hospital costs and revenues (Carey, 2009) Inpatient vs. Outpatient Surgery Figure 1: Inpatient vs. Outpatient Surgery Volume, 1981-2005 60 Procedures (millions) 50 40 All Outpatient Settings 30 20 10 Hospital Inpatient 0 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005* Source: Avalere Health analysis of Verispan’s Diagnostic Imaging Center Profiling Solution, 2004, and American Hospital Association Annual Survey data for community hospitals, 1981-2004. *2005 values are estimates. Outpatient Surgery Settings Figure 2: Percent of Outpatient Surgeries by Facility Type, 1981-2005 100% Physician Offices 80% 60% Freestanding Facilities 40% 20% Hospital-based Facilities 0% 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005* Source: Verispan’s Diagnostic Imaging Center Profiling Solution, 2004. *2005 values are estimates. Number of ASCs Figure 3: Number of Freestanding Ambulatory Care Surgery Centers (1996, 1998, and 2000 – 2005) 5,500 5,095 5,000 4,601 4,500 4,000 3,500 3,000 2,500 2,425 2,754 2,864 1998 2000 3,508 3,570 2001 2002 3,836 2,000 1,500 1,000 500 0 1996 Source: Verispan’s Diagnostic Imaging Center Profiling Solution 2003 2004 2005 Research Question • Outpatient surgery is a rapidly growing market – Number of ASCs has doubled in the past decade – Recent CMS expansion is likely to accelerate growth • Know little about ASC vs. hospital competition – Management theories on organizational niche – We apply theories to market for outpatient surgery • Research Question: How do ASCs influence market exit by hospitals and vice versa? Organizational Niche • Firms select an organizational niche within their market (Hannan & Freeman, 1977) • Entry/exit rates depend upon firm density within organizational niches (Baum & Singh, 1994) – Firms with overlapping niches elevate exit risks – Firms with non-overlapping niches lower exit risks – Tested among similar organizational forms • This competition is generally asymmetric – Firms i has a different impact on firm j than vice versa Asymmetric Competition • New forms benefit from existing organizations – Residual socio-political and cognitive legitimation – May learn from structures, strategies, and routines • ASCs have competitive advantage over hospitals – Cost advantage competing for patients – Ownership advantage competing for physicians • Hospitals may not benefit from competing ASCs – Implications for treatment of vulnerable populations – Cross-subsidization of less profitable service lines Hypotheses • Among similar organizational forms: – H1: High niche overlap leads to high exit rates – H2: High niche non-overlap leads to low exit rates • Among different organizational forms: – H3: High hospital niche overlap leads to low ASC exit rates – H4: High ASC niche overlap leads to high hospital exit rates Niche Overlap Density Niche Non-Overlap Density Competition from ASC ASC HOSP + – Exit by Presence of ASC ASC HOSP – Exit by HOSP + + HOSP – Study Site: Florida • Number of ASCs grew from 200 to 333 • Number of hospitals grew from 197 to 204 • Florida facilities report quarterly patient data – Complete census of surgical procedures (1997-2006) • CPTs coded by Clinical Classification Software – 244 procedures assigned to 15 surgical specialties • Calculate variables with a high level of precision – Quarterly procedure counts by facility and county – Use Florida licensure data to validate entry/exit dates Surgical Specialties 1. 2. 3. 4. 5. Nervous system Endocrine system Eye Ear Nose, mouth, and pharynx 6. Respiratory system 7. Cardiovascular system 8. Hemic and lymphatic system 9. Digestive system 10. Urinary system 11. Male genital organs 12. Female genital organs 13. Obstetrical procedures 14. Musculoskeletal system 15. Integumentary system 1997Q1 1997Q2 1997Q3 1997Q4 1998Q1 1998Q2 1998Q3 1998Q4 1999Q1 1999Q2 1999Q3 1999Q4 2000Q1 2000Q2 2000Q3 2000Q4 2001Q1 2001Q2 2001Q3 2001Q4 2002Q1 2002Q2 2002Q3 2002Q4 2003Q1 2003Q2 2003Q3 2003Q4 2004Q1 2004Q2 2004Q3 2004Q4 2005Q1 2005Q2 2005Q3 2005Q4 2006Q1 2006Q2 2006Q3 2006Q4 0 Number of Procedures 200000 400000 600000 800000 1.0e+06 Total Procedures Inpatient (HSP) Outpatient (ASC) Outpatient (HSP) 1997Q1 1997Q2 1997Q3 1997Q4 1998Q1 1998Q2 1998Q3 1998Q4 1999Q1 1999Q2 1999Q3 1999Q4 2000Q1 2000Q2 2000Q3 2000Q4 2001Q1 2001Q2 2001Q3 2001Q4 2002Q1 2002Q2 2002Q3 2002Q4 2003Q1 2003Q2 2003Q3 2003Q4 2004Q1 2004Q2 2004Q3 2004Q4 2005Q1 2005Q2 2005Q3 2005Q4 2006Q1 2006Q2 2006Q3 2006Q4 0 2 Number of Facilities 4 6 8 10 Number of ASC Openings & Closings (1997-2006) Openings Closings 1997Q1 1997Q2 1997Q3 1997Q4 1998Q1 1998Q2 1998Q3 1998Q4 1999Q1 1999Q2 1999Q3 1999Q4 2000Q1 2000Q2 2000Q3 2000Q4 2001Q1 2001Q2 2001Q3 2001Q4 2002Q1 2002Q2 2002Q3 2002Q4 2003Q1 2003Q2 2003Q3 2003Q4 2004Q1 2004Q2 2004Q3 2004Q4 2005Q1 2005Q2 2005Q3 2005Q4 2006Q1 2006Q2 2006Q3 2006Q4 0 Number of Facilities .5 1 1.5 2 Number of Hospital Openings & Closings (1997-2006) Openings Closings 1997Q1 1997Q2 1997Q3 1997Q4 1998Q1 1998Q2 1998Q3 1998Q4 1999Q1 1999Q2 1999Q3 1999Q4 2000Q1 2000Q2 2000Q3 2000Q4 2001Q1 2001Q2 2001Q3 2001Q4 2002Q1 2002Q2 2002Q3 2002Q4 2003Q1 2003Q2 2003Q3 2003Q4 2004Q1 2004Q2 2004Q3 2004Q4 2005Q1 2005Q2 2005Q3 2005Q4 2006Q1 2006Q2 2006Q3 2006Q4 0 200 400 600 Outpatient Volume for Facility Number 14960582 LASER & OUTPATIENT SURGERY CENTER 0 200 400 600 800 1997Q1 1997Q2 1997Q3 1997Q4 1998Q1 1998Q2 1998Q3 1998Q4 1999Q1 1999Q2 1999Q3 1999Q4 2000Q1 2000Q2 2000Q3 2000Q4 2001Q1 2001Q2 2001Q3 2001Q4 2002Q1 2002Q2 2002Q3 2002Q4 2003Q1 2003Q2 2003Q3 2003Q4 2004Q1 2004Q2 2004Q3 2004Q4 2005Q1 2005Q2 2005Q3 2005Q4 2006Q1 2006Q2 2006Q3 2006Q4 0 100200300400500 0 100200300400 Outpatient Volume for Facility Number 144 AYERS SURGERY CENTER 1997Q1 1997Q2 1997Q3 1997Q4 1998Q1 1998Q2 1998Q3 1998Q4 1999Q1 1999Q2 1999Q3 1999Q4 2000Q1 2000Q2 2000Q3 2000Q4 2001Q1 2001Q2 2001Q3 2001Q4 2002Q1 2002Q2 2002Q3 2002Q4 2003Q1 2003Q2 2003Q3 2003Q4 2004Q1 2004Q2 2004Q3 2004Q4 2005Q1 2005Q2 2005Q3 2005Q4 2006Q1 2006Q2 2006Q3 2006Q4 1997Q1 1997Q2 1997Q3 1997Q4 1998Q1 1998Q2 1998Q3 1998Q4 1999Q1 1999Q2 1999Q3 1999Q4 2000Q1 2000Q2 2000Q3 2000Q4 2001Q1 2001Q2 2001Q3 2001Q4 2002Q1 2002Q2 2002Q3 2002Q4 2003Q1 2003Q2 2003Q3 2003Q4 2004Q1 2004Q2 2004Q3 2004Q4 2005Q1 2005Q2 2005Q3 2005Q4 2006Q1 2006Q2 2006Q3 2006Q4 Outpatient Volume for Facility Number 252 SURGERY CENTER OF NORTH FLORIDA, INC. Outpatient Volume for Facility Number 14960375 NORTH FLORIDA ENDOSCOPY CENTER Outpatient Volume for Facility Number 14960402 ORTHOPAEDIC SURGERY CENTER 0 500100015002000 1997Q1 1997Q2 1997Q3 1997Q4 1998Q1 1998Q2 1998Q3 1998Q4 1999Q1 1999Q2 1999Q3 1999Q4 2000Q1 2000Q2 2000Q3 2000Q4 2001Q1 2001Q2 2001Q3 2001Q4 2002Q1 2002Q2 2002Q3 2002Q4 2003Q1 2003Q2 2003Q3 2003Q4 2004Q1 2004Q2 2004Q3 2004Q4 2005Q1 2005Q2 2005Q3 2005Q4 2006Q1 2006Q2 2006Q3 2006Q4 0 100200 300 400 Outpatient Volume for Facility Number 37 EYE SURGICENTER LLC 1997Q1 1997Q2 1997Q3 1997Q4 1998Q1 1998Q2 1998Q3 1998Q4 1999Q1 1999Q2 1999Q3 1999Q4 2000Q1 2000Q2 2000Q3 2000Q4 2001Q1 2001Q2 2001Q3 2001Q4 2002Q1 2002Q2 2002Q3 2002Q4 2003Q1 2003Q2 2003Q3 2003Q4 2004Q1 2004Q2 2004Q3 2004Q4 2005Q1 2005Q2 2005Q3 2005Q4 2006Q1 2006Q2 2006Q3 2006Q4 1997Q1 1997Q2 1997Q3 1997Q4 1998Q1 1998Q2 1998Q3 1998Q4 1999Q1 1999Q2 1999Q3 1999Q4 2000Q1 2000Q2 2000Q3 2000Q4 2001Q1 2001Q2 2001Q3 2001Q4 2002Q1 2002Q2 2002Q3 2002Q4 2003Q1 2003Q2 2003Q3 2003Q4 2004Q1 2004Q2 2004Q3 2004Q4 2005Q1 2005Q2 2005Q3 2005Q4 2006Q1 2006Q2 2006Q3 2006Q4 0 20 40 60 80 Outpatient Procedure Volume for ASCs in County 1 (ALACHUA) Outpatient Volume for Facility Number 183 NORTH FLORIDA SURGICAL PAVILION Markets and Specialty Participation • Defined markets using health service area (HSA) boundaries (Makuc et al. 1991) – Florida’s 67 counties assigned to 17 HSAs – Broke markets into “local” and “diffuse” areas • Developed definition of specialty participation for a related paper – Positive procedure volume for three quarters Niche Overlap and Non-Overlap • Niche overlap weights calculated for facilities i and j: wij = sij w ji = sij + si s ji s ji + s j • where sij and sji represent procedure volume in surgical specialties they share • Niche overlap and non-overlap density were calculated: overlap density i = n ∑w j =1 ji non − overlap densityi = n − n ∑w ji j =1 • where wij represents niche overlap weights and n represents the total number of facilities • Calculates the fractional number of overlapping facilities Controls • • • • • • • Facility age (in days) to test the “liability of newness” Facility size (number of ORs/beds) Ownership status (for-profit, non-profit*) Ownership type (corporation, government, other*) Ownership chain (dummy variable) Number of specialties that a facility serves Percent of procedures reimbursed by each payer – Categorized 16 payer codes as public, private, or other* • Size of market demand within a facility’s specialties – Quarterly procedure counts within specialties served by a facility * Denotes variables representing the omitted group in our analyses Physician Statistics • Facilities should exit when they are highly dependent upon their surgeons • Cross-tabulated facility and physician IDs to control for these relationships: – Number of surgeons operating within a facility – Average number of facilities these physicians utilize – “Kick butt ratio” represents physician/facility leverage: Percent of surgeries in facility i coming from physician j KBR = Percent of surgeries for physician j admitted to facility i – Included the average KBR across facility’s physicians Model Specification • Variables broken down in four models: 1. 2. 3. 4. • None Facility type (ASC vs. HOSP) Geographic location (local vs. diffuse) Facility type and geographic location Ran exit models for ASCs and hospitals – Estimated with Cox proportional hazard models – Validated results by running parametric models • Related study explores facility entry Exit Model (1) Pr(Exitit) = β0 + β1OverlapDensityijt + β2NonoverlapDensityijt + β3MarketDemandijt + β4FirmControlsit + β5PhysicianStatisticsit + εit where: • OverlapDensityjt represents niche overlap density • NonoverlapDensityjt represents niche non-overlap • MarketDemandjt represents quarterly procedure counts • FirmControlsit is a vector of facility-level controls • PhysicianStatisticsit is a vector of physician statistics ASC Results Category1 Facility Location Measure Model 1 Breakdown Model Statistics Diffuse Competition Local HOSP Diffuse 1 Model 4 Facility Location Facility Location 10100 10100 10100 10100 Subjects 406 406 406 406 Failures 51 51 51 51 -264.6984 -255.4791 -262.9857 -250.9986 39.51 57.95 42.94 66.91 Prob > Chi2 0.0005 0.0000 0.0008 0.0000 Generalized R2 0.0927 0.1330 0.1004 0.1519 Overlap 0.0186 0.163*** 0.0507 0.334*** Non-overlap -0.0299* -0.0764** -0.0186 -0.0597 Overlap 0.0215 0.121 Non-overlap -0.0333 -0.0746 Likelihood Ratio ASC Model 3 Observations Log Likelihood Local Model 2 Chi2 Overlap -0.00945 -0.19 Non-overlap 0.0159 0.0137 Overlap 0.0957 Non-overlap 0.00514 Model includes measures of market demand, physician supply, and market controls. Results not presented here. *** p<0.01, ** p<0.05, * p<0.1 Hospital Results Category1 Facility Location Measure Model 1 Breakdown Model Statistics Diffuse Competition Local HOSP Diffuse 1 Model 4 Facility Location Facility Location 7840 7840 7840 7840 Subjects 222 222 222 222 Failures 9 9 9 9 -29.9242 -27.3889 -25.8616 -22.9969 35.47 40.54 43.59 49.32 Prob > Chi2 0.0034 0.0028 0.0017 0.0038 Generalized R2 0.1477 0.1669 0.1783 0.1992 Overlap 0.203** 0.351** 0.151 0.399 Non-overlap -0.0746 -0.0114 0.0341 -0.165 Overlap 0.349** 0.700** Non-overlap -0.109 0.053 Likelihood Ratio ASC Model 3 Observations Log Likelihood Local Model 2 Chi2 Overlap 0.437** -0.0354 Non-overlap -0.387 0.645 Overlap 0.728* Non-overlap -1.519 Model includes measures of market demand, physician supply, and market controls. Results not presented here. *** p<0.01, ** p<0.05, * p<0.1 Predicted vs. Actual Coefficients Niche Non-Overlap Density Niche Overlap Density Competition with Predicted Coefficients ASC ASC HOSP + – Exit by Presence of ASC ASC + + HOSP Competition with ASC ASC – Presence of HOSP ASC +++ ASC Exit by Exit by HOSP 1 Actual – Exit by HOSP Actual Coefficients1 HOSP ++ ++ HOSP results emerge from model 2, which is broken down by facility type +++ p<0.01, ++ p<0.05, + p<0.1 -- HOSP Conclusions • Management theories hold true in this setting – Competition with similar forms has expected effect • Asymmetric competition between different forms – ASCs unaffected by the presence of nearby hospitals – Hospitals are hurt by competition with ASCs • Findings have major health care implications – Hospital closures may affect patient access to care • Future work should assess welfare implications – Test applicability to other specialized providers Acknowledgements • Thanks to the AcademyHealth Annual Research Meeting 2009 for the opportunity to present here today • Thanks to the state of Florida’s Agency for Health Care Administration (AHCA) for their research assistance • Thanks to the members of my dissertation committee (Mark Pauly, Lawton Burns, Guy David, Jitendra Singh, Lee Fleisher) for their valuable feedback • Thanks to the Agency for Healthcare Research & Quality (AHRQ) for their financial support of this research
