Productivity growth, case mix and optimal size of hospitals. A 16-year study of the Norwegian hospital sector.

BACKGROUND AND OBJECTIVES: This paper analyses productivity growth in the Norwegian hospital sector over a period of 16 years, 1999-2014. This period was characterized by a large ownership reform with subsequent hospital reorganizations and mergers. We describe how technological change, technical productivity, scale efficiency and the estimated optimal size of hospitals have evolved during this period. MATERIAL AND METHODS: Hospital admissions were grouped into diagnosis-related groups using a fixed-grouper logic. Four composite outputs were defined and inputs were measured as operating costs. Productivity and efficiency were estimated with bootstrapped data envelopment analyses. RESULTS: Mean productivity increased by 24.6% points from 1999 to 2014, an average annual change of 1.5%. There was a substantial growth in productivity and hospital size following the ownership reform. After the reform (2003-2014), average annual growth was <0.5%. There was no evidence of technical change. Estimated optimal size was smaller than the actual size of most hospitals, yet scale efficiency was high even after hospital mergers. However, the later hospital mergers have not been followed by similar productivity growth as around time of the reform. CONCLUSIONS: This study addresses the issues of both cross-sectional and longitudinal comparability of case mix between hospitals, and thus provides a framework for future studies. The study adds to the discussion on optimal hospital size.

Do hospital mergers reduce costs?

Proponents of hospital consolidation claim that mergers lead to significant cost savings, but there is little systematic evidence backing these claims. For a large sample of hospital mergers between 2000 and 2010, I estimate difference-in-differences models that compare cost trends at acquired hospitals to cost trends at hospitals whose ownership did not change. I find evidence of economically and statistically significant cost reductions at acquired hospitals. On average, acquired hospitals realize cost savings between 4 and 7 percent in the years following the acquisition. These results are robust to a variety of different control strategies, and do not appear to be easily explained by post-merger changes in service and/or patient mix. I then explore several extensions of the results to examine (a) whether the acquiring hospital/system realizes cost savings post-merger and (b) if cost savings depend on the size of the acquirer and/or the geographic overlap of the merging hospitals.

Demographic factors and hospital size predict patient satisfaction variance--implications for hospital value-based purchasing.

BACKGROUND: Hospital Value-Based Purchasing (HVBP) incentivizes quality performance-based healthcare by linking payments directly to patient satisfaction scores obtained from Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) surveys. Lower HCAHPS scores appear to cluster in heterogeneous population-dense areas and could bias Centers for Medicare & Medicaid Services (CMS) reimbursement. OBJECTIVE: Assess nonrandom variation in patient satisfaction as determined by HCAHPS. DESIGN: Multivariate regression modeling was performed for individual dimensions of HCAHPS and aggregate scores. Standardized partial regression coefficients assessed strengths of predictors. Weighted Individual (hospital) Patient Satisfaction Adjusted Score (WIPSAS) utilized 4 highly predictive variables, and hospitals were reranked accordingly. SETTING: A total of 3907 HVBP-participating hospitals. PATIENTS: There were 934,800 patient surveys by the most conservative estimate. MEASUREMENTS: A total of 3144 county demographics (US Census) and HCAHPS surveys. RESULTS: Hospital size and primary language (non-English speaking) most strongly predicted unfavorable HCAHPS scores, whereas education and white ethnicity most strongly predicted favorable HCAHPS scores. The average adjusted patient satisfaction scores calculated by WIPSAS approximated the national average of HCAHPS scores. However, WIPSAS changed hospital rankings by variable amounts depending on the strength of the predictive variables in the hospitals' locations. Structural and demographic characteristics that predict lower scores were accounted for by WIPSAS that also improved rankings of many safety-net hospitals and academic medical centers in diverse areas. CONCLUSIONS: Demographic and structural factors (eg, hospital beds) predict patient satisfaction scores even after CMS adjustments. CMS should consider WIPSAS or a similar adjustment to account for the severity of patient satisfaction inequities that hospitals could strive to correct.

Medicare Charges and Payments for Cervical Spine Surgery: Association With Hospital Characteristics.

STUDY DESIGN: Retrospective analysis. OBJECTIVE: To determine the association of hospital and patient population characteristics with charges and payments for Medicare patients undergoing cervical spine surgery. SUMMARY OF BACKGROUND DATA: Third-party payers such as Medicare pay negotiated rates for health care services that represent a substantial savings from hospitals' list prices. Previous research has shown geographical variation in hospital charges. However, the association with other hospital and patient population characteristics is poorly understood. METHODS: We determined the association of hospital characteristics (hospital size, ownership, location, teaching status, procedure volume, and geographical region) and patient population characteristics (proportion female, nonwhite, or with ≥1 comorbid conditions) with excess charges (difference between hospital charges and payments) and cost-to-charge ratio (ratio of payments to hospital charges) for Medicare patients undergoing cervical spine fusion without complication (MS-DRG 473). Significance levels were set at a P value less than 0.05. RESULTS: The median excess charge was $59,799 (interquartile range, $41,668, $69,576) and cost-to-charge ratio was 25.8% (interquartile range, 20.4%, 32.7%). Higher excess charges were observed for urban hospitals (P = 0.003). There was an association between excess charges and procedure volume (P = 0.034) and proportion of patients with 1 or more comorbid conditions (P = 0.008). There were no differences based on hospital size, ownership, teaching status, geographical region, or proportion of female or nonwhite patients.Private hospitals had higher cost-to-charge ratios than government hospitals (P = 0.017). There was no association with hospital size, teaching status, geographical region, procedure volume, or proportion of patients who were female, nonwhite, or who had 1 or more comorbid conditions. CONCLUSION: The relationship between hospital charges and payments for cervical spine surgery without complication is associated with certain hospital and patient population characteristics. Further study is needed to determine whether these differences are associated with health outcomes. LEVEL OF EVIDENCE: 3.

The National Practice Benchmark for oncology, 2014 report on 2013 data.

The National Practice Benchmark (NPB) is a unique tool to measure oncology practices against others across the country in a way that allows meaningful comparisons despite differences in practice size or setting. In today's economic environment every oncology practice, regardless of business structure or affiliation, should be able to produce, monitor, and benchmark basic metrics to meet current business pressures for increased efficiency and efficacy of care. Although we recognize that the NPB survey results do not capture the experience of all oncology practices, practices that can and do participate demonstrate exceptional managerial capability, and this year those practices are recognized for their participation. In this report, we continue to emphasize the methodology introduced last year in which we reported medical revenue net of the cost of the drugs as net medical revenue for the hematology/oncology product line. The effect of this is to capture only the gross margin attributable to drugs as revenue. New this year, we introduce six measures of clinical data density and expand the radiation oncology benchmarks.

Incentive payments are not related to expected health gain in the pay for performance scheme for UK primary care: cross-sectional analysis.

BACKGROUND: The General Medical Services primary care contract for the United Kingdom financially rewards performance in 19 clinical areas, through the Quality and Outcomes Framework. Little is known about how best to determine the size of financial incentives in pay for performance schemes. Our aim was to test the hypothesis that performance indicators with larger population health benefits receive larger financial incentives. METHODS: We performed cross sectional analyses to quantify associations between the size of financial incentives and expected health gain in the 2004 and 2006 versions of the Quality and Outcomes Framework. We used non-parametric two-sided Spearman rank correlation tests. Health gain was measured in expected lives saved in one year and in quality adjusted life years. For each quality indicator in an average sized general practice we tested for associations first, between the marginal increase in payment and the health gain resulting from a one percent point improvement in performance and second, between total payment and the health gain at the performance threshold for maximum payment. RESULTS: Evidence for lives saved or quality adjusted life years gained was found for 28 indicators accounting for 41% of the total incentive payments. No statistically significant associations were found between the expected health gain and incentive gained from a marginal 1% increase in performance in either the 2004 or 2006 version of the Quality and Outcomes Framework. In addition no associations were found between the size of financial payment for achievement of an indicator and the expected health gain at the performance threshold for maximum payment measured in lives saved or quality adjusted life years. CONCLUSIONS: In this subgroup of indicators the financial incentives were not aligned to maximise health gain. This disconnection between incentive and expected health gain risks supporting clinical activities that are only marginally effective, at the expense of more effective activities receiving lower incentives. When designing pay for performance programmes decisions about the size of the financial incentive attached to an indicator should be informed by information on the health gain to be expected from that indicator.

Economies of scale and scope in the Danish hospital sector prior to radical restructuring plans.

OBJECTIVE: The Danish hospital sector faces a significant rebuilding program driven by recent regional reform and guidelines for acute admission hospitals. Within the next 5-10 years, the number of public hospitals offering acute admission will be reduced from 35 to approximately 20 larger hospitals. As the administrative data may be biased during the middle of a restructuring process our objective was to analyze whether the configuration of Danish public hospitals was subject to economies of scale and scope prior to the restructuring plans. METHODS: We estimated a quadratic cost function using panel data on the total costs for somatic treatment, casemix adjusted DRG-production values, and other cost drivers for the three years before the 2007 reforms. A short-run cost function was used to derive estimates of a long-run cost function by applying the envelope condition. Next, we estimated economies of scale and scope. RESULTS: We identified moderate-to-significant economies of scale and scope. This indicates that the Danish hospital sector was characterized by unexploited gains from consolidation. CONCLUSIONS: Our results suggest that the proposed plans have the potential to result in hospitals that are more efficient. However, post-restructuring studies elsewhere show that the strategy of horizontal integration has failed.

Physician patient-sharing networks and the cost and intensity of care in US hospitals.

BACKGROUND: There is substantial variation in the cost and intensity of care delivered by US hospitals. We assessed how the structure of patient-sharing networks of physicians affiliated with hospitals might contribute to this variation. METHODS: We constructed hospital-based professional networks based on patient-sharing ties among 61,461 physicians affiliated with 528 hospitals in 51 hospital referral regions in the US using Medicare data on clinical encounters during 2006. We estimated linear regression models to assess the relationship between measures of hospital network structure and hospital measures of spending and care intensity in the last 2 years of life. RESULTS: The typical physician in an average-sized urban hospital was connected to 187 other doctors for every 100 Medicare patients shared with other doctors. For the average-sized urban hospital an increase of 1 standard deviation (SD) in the median number of connections per physician was associated with a 17.8% increase in total spending, in addition to 17.4% more hospital days, and 23.8% more physician visits (all P<0.001). In addition, higher "centrality" of primary care providers within these hospital networks was associated with 14.7% fewer medical specialist visits (P<0.001) and lower spending on imaging and tests (-9.2% and -12.9% for 1 SD increase in centrality, P<0.001). CONCLUSIONS: Hospital-based physician network structure has a significant relationship with an institution's care patterns for their patients. Hospitals with doctors who have higher numbers of connections have higher costs and more intensive care, and hospitals with primary care-centered networks have lower costs and care intensity.

Medicare program; inpatient rehabilitation facility prospective payment system for federal fiscal year 2012; changes in size and square footage of inpatient rehabilitation units and inpatient psychiatric units. Final rule.

This final rule will implement section 3004 of the Affordable Care Act, which establishes a new quality reporting program that provides for a 2 percent reduction in the annual increase factor beginning in 2014 for failure to report quality data to the Secretary of Health and Human Services. This final rule will also update the prospective payment rates for inpatient rehabilitation facilities (IRFs) for Federal fiscal year (FY) 2012 (for discharges occurring on or after October 1, 2011 and on or before September 30, 2012) as required under section 1886(j)(3)(C) of the Social Security Act (the Act). Section 1886(j)(5) of the Act requires the Secretary to publish in the Federal Register on or before the August 1 that precedes the start of each FY the classification and weighting factors for the IRF prospective payment system (PPS) case-mix groups and a description of the methodology and data used in computing the prospective payment rates for that fiscal year. We are also consolidating, clarifying, and revising existing policies regarding IRF hospitals and IRF units of hospitals to eliminate unnecessary confusion and enhance consistency. Furthermore, in accordance with the general principles of the President's January 18, 2011 Executive Order entitled "Improving Regulation and Regulatory Review," we are amending existing regulatory provisions regarding ''new'' facilities and changes in the bed size and square footage of IRFs and inpatient psychiatric facilities (IPFs) to improve clarity and remove obsolete material.

The economics of robotic cystectomy: cost comparison of open versus robotic cystectomy.

OBJECTIVE: • To assess and compare the economic burden of open radical cystectomy (OC) vs robotic-assisted laparoscopic radical cystectomy (RC) with pelvic lymph node dissection and urinary diversion. PATIENTS AND METHODS: • A series of 103 and 83 consecutive patients undergoing OC and RC, respectively, were prospectively studied at a tertiary care institution from April 2002 to February 2009. • Data were collected on patient demographics, perioperative parameters and length of stay (LOS) in hospital. Cohorts were subdivided into ileal conduit (IC), continent cutaneous diversion (CCD) and orthotopic neobladder (ON) subgroups. • A linear cost model was created to simulate treatment with OC vs RC. Procedural costs were derived from the Medicare Resource Based Relative Value Scale. Materials costs were obtained from the respective suppliers. The indirect costs of complications were considered. • Sensitivity analyses were performed. RESULTS: • Despite a higher cost of materials, RC was less expensive than OC for IC and CCD, although the cost advantage deteriorated for ON. • The per-case costs of RC with IC, CCD and ON were $20,659, $22,102 and $22,685, respectively, compared to $25,505, $22,697 and $20,719 for their OC counterparts. • The largest cost driver in the study was LOS in hospital. • RC showed a shorter LOS compared to OC, although this effect was insufficient to offset the higher cost of robotic surgery. • Complications materially affected cost performance. CONCLUSIONS: • Despite a higher cost of materials, RC can be more cost efficient than OC as a treatment for bladder cancer at a high-volume, tertiary care referral centre, particularly with IC. • Complications significantly impact cost performance.