Santosh J. Agarwal, BPharm, MS
Covidien, Mansfield, MA
Gary V. Delhougne, JD, MHA
Covidien, Boulder, CO
Levi Citrin, JD
Numerof & Associates Inc., St. Louis, MO
Jill E. Sackman, DVM, PhD
Numerof & Associates Inc., St. Louis, MO
Anthony J. Senagore, MD, MS, MBA
Department of Surgery, Keck School of Medicine of University of Southern California, Los Angeles, CA


Purpose: Minimally invasive surgery is associated with improved clinical outcomes and reduced costs. We hypothesize that in patients with similar preoperative characteristics, hysterectomy, colectomy, and thoracic resection performed via minimally invasive surgery (MIS) approach would be associated with fewer complex Diagnosis Related Group (cDRG) assignments and subsequently result in reimbursement savings.

Methodology: Premier hospital database was used to examine inpatient discharges of open and MIS colectomy, hysterectomy and thoracic resection. Open and MIS groups were matched based on propensity score. Descriptive statistics and regression analysis were used to assess the impact of MIS on cDRG assignment. Potential reimbursement savings to the U.S. health care system, assuming a 10% increase in MIS utilization, was estimated using Medicare’s Fiscal Year (FY) 2013 national average reimbursement data and Premier’s procedure volume projections.

Results: Compared with open surgery, the MIS group had a statistically significantly lower percentage of cDRG assignment (colectomy, 57% vs. 71%; hysterectomy, 15% vs. 19%; thoracic resection, 62% vs. 70%; P<.001 for each). Open surgery, when compared to MIS, increased the odds of cDRG assignment by 67% (odds ratio [OR], 1.67; 95% confidence interval [CI], 1.62–1.71). We estimated that a 10% increase in MIS utilization would lead to annual payer reimbursement savings of about $24.4 million (colectomy, $17 million; hysterectomy, $5 million; thoracic resection, $2.4 million).

Conclusion: Health care reform laws and economic pressures are causing a shift in focus from volume-based to value-based care. MIS approaches reduce payer expense based on fewer expensive cDRG assignments. Further adoption of MIS may lead to improved outcomes and additional savings.


Adoption of minimally invasive surgery (MIS) has advanced rapidly in the past 2 decades. Minimally invasive procedures offer patients reduced pain and scarring, shorter hospitalization, and a quicker return to activities of daily living. Studies demonstrate that MIS is frequently associated with reduced rates of complications, mortality, and morbidity (Tiwari 2011, Bilimoria 2008, Delaney 2008, Kiran 2010, Varela 2008, Chalermchockchareonkit 2012, Cheng 2007, Cho 2011, Howington 2012, Murthy 2012, Sawada 2008, Villamizar 2009, Epstein 2013). The data also suggest that MIS is associated with cost benefits, likely due to reduced length of stay (LOS) and fewer complications (Varela 2008, Cho 2011, Swanson 2011, Casali 2009, Alkhamesi 2011, Eisenberg 2010, Jensen 2012, Senagore 2002, Noblett 2007, Vaid 2012, Bosio 2007, Barnett 2010, Bijen 2009, Lenihan 2004). The potential net result of replacing open procedures with MIS is that both the payer and the provider could see improved outcomes and a more favorable cost structure.

The comparison of several types of hysterectomy demonstrates the improved outcomes offered by laparoscopy (ACOG 2009, Sarmini 2005). Laparoscopic hysterectomy is associated with less postoperative pain, lower stress levels, and better cosmetic results than abdominal hysterectomy (Olsson 1996). In their 2005 meta-analysis of 27 randomized controlled trials comparing ­laparoscopic-assisted vaginal hysterectomy (LAVH), total laparoscopic hysterectomy (TLH), and abdominal hysterectomy for benign uterine disease, the Cochrane Collaboration found a significant advantage of laparoscopy over open procedures (Nieboer 2009). Laparoscopic hysterectomy led to fewer wounds or abdominal wall infections, less pain, less pyrexia, a smaller drop in hemoglobin, shorter hospitalization, and a faster return to work; though operative times were longer and urinary tract injuries were more common (Lenihan 2004, Nieboer 2009, Shen 2003, Hidlebaugh 1994, Epstein 2013).

Like laparoscopic procedures, ­video-assisted thoracoscopic procedures (VATS) have also developed rapidly in the past 2 decades. In fact, VATS has been widely adopted for use in simple thoracic operations, such as the treatment of pneumo­thorax and pleural effusion (Howington 2012). VATS wedge resection has also been established as a diagnostic tool for lung cancer staging (Sihoe 2004). VATS lobectomy for lung cancer has numerous reported benefits, including earlier chest tube removal, less postoperative pain, shorter hospitalization, less inflammation, and better long-term functional level (Murthy 2012, Sawada 2008, Kaseda 2002, Swanson 2002).

Similarly, meta-analyses and large randomized trials have demonstrated the safety and efficacy of laparoscopic colectomy as an alternative to open surgery in patients with conditions ranging from Crohn’s disease, diverticulitis, and ulcerative colitis (UC) to colon cancer (Nash 2010, Fullum 2010, Bonjer 2007). The Clinical Outcomes of Surgical Therapy study (COST Study Group 2004) involved 48 centers and 872 patients who under­went either open or laparoscopic-assisted colectomy. There was no difference in overall survival (86% for laparoscopic-assisted and 85% for open) at 3 years. The laparoscopic group demonstrated faster recovery with a shorter median hospital stay (5 vs 6 days) and lower use of postoperative narcotics.

Throughout the literature, MIS tends to be associated with lower hospital costs, shorter hospitalization, a quicker return to activities of daily living, and a faster return to work compared to open procedures (Varela 2008, Swanson 2011, Casali 2009, Alkhamesi 2011, Eisenberg 2010, Jensen 2012, Senagore 2002, Noblett 2007, Vaid 2012, Bosio 2007, Barnett 2010, Bijen 2009, Hidlebaugh 1994, Epstein 2013, Fullum 2010).

Most of the literature concerning MIS-associated cost benefits has focused on provider cost reduction. Few studies consider implications for payers utilizing a prospective payment program (Senagore 2005).

In the United States, inpatient procedures are reimbursed based on the Medicare Severity Diagnosis Related Groups (MS-DRG) system, which provides one single reimbursement for the entire inpatient hospitalization, accounting for diagnosis and procedures performed during the hospital stay. MS-DRGs provide higher reimbursement for procedures with complications and/or comorbidities (CC) and major complications and/or comorbidities (MCC). Patients with significant comorbidities prior to the surgery or who experience complications during or after the surgery (prior to discharge) are assigned a complex DRG (cDRG). Reduction in certain postoperative complications, such as surgical site infections, translates into a higher rate of assignment of DRGs without complications and/or comorbidities, provided patients have similar pre-existing comorbidities.

Payers generally reimburse the provider a set amount according to a predetermined fee schedule. Procedures assigned to a cDRG are reimbursed at a higher rate on average than those assigned to the corresponding noncomplex, or base, DRG. The implications of DRG assignment for the payer are important because cDRGs typically result in a substantially increased expense.

We hypothesize that when all pre-operative patient and provider characteristics are similar and the only difference is the surgical approach, MIS is associated with a lower rate of postoperative complications compared to open procedures. Postoperative complications are an important predictor of cDRG assignment and, thus, cost for payers.

Senagore (2005) evaluated this relationship for colectomy using data from a single institution. We conducted a retrospective cohort study using a large hospital database to demonstrate that among patients with similar preoperative characteristics but different surgical approaches (open vs a nonrobotic laparoscopic or MIS), MIS was associated with fewer cDRG assignments. Procedures such as colectomy, hysterectomy, and thoracic resection were selected because these are high-volume surgeries with a high percentage of open procedures and significant payment differentials between cDRGs and non-cDRGs.


Data Source

This study utilized the Premier hospital database, one of the largest administrative and resource utilization databases in the United States, covering approximately 20% of hospital discharges. The database contains more than 42 million discharges from more than 600 hospitals. Contributing hospitals send data on patient demographics; hospital, surgeon, and payer characteristics; and resource utilization, including diagnosis and procedures. Diagnoses and procedures are coded using the International Classification of Diseases, Ninth Revision Clinical Modification (ICD-9-CM) codes. All data undergo a quality-review process for validation.

Patients and Procedures

All surgical discharges for adult patients (age ≥18 years) between the years 2009 and 2011 with a primary surgical procedure of either open or laparoscopic colectomy, hysterectomy, or thoracic resection were included in this analysis. Relevant discharges were identified and selected using a combination of ICD-9-CM (Appendix Table 1), Current Procedural Terminology (CPT), and billing codes. The analysis excluded cases with missing data on cost or severity, with patients who were deceased at discharge, and where robotic surgical procedures were used.

The primary outcome of interest was complex MS-DRG (cDRG) code assignment (see Appendix Table 1). MS-DRG codes that ended with MCC or CC were classified as cDRG. MS-DRG was coded as a variable in the Premier hospital database.

The main independent (predictor) variable was open or laparoscopic surgery. Confounders were identified from variables available in the database and were similar to variables included in previous database studies (Delaney 2008, Swanson 2011). These included patient characteristics (age, gender, race, comorbidities), hospital characteristics (geographic location, teaching, urban, number of beds), payer, procedure characteristics (elective admission, procedure including subtype, procedural approach, principal diagnosis), and surgeon specialty.

Comorbidities selected were from the Charlson Comorbidity Index (CCI), which includes 17 conditions.Hypertension and obesity, two conditions not included in the CCI, were considered as relevant comorbidities and were included.


Descriptive analyses using a chi-square test were performed to analyze differences between open/laparoscopy and cDRG assignment rates for the three procedures.

To evaluate the impact of surgical approach on cDRG assignment, propensity score matching was conducted. Propensity score matching attempts to predict assignment to a particular group by accounting for a set of variables. We used propensity score matching to build a model of open/MIS group assignment controlling for patient, provider, and payer characteristics. The open and MIS groups were then matched 1:1 based on propensity score. The procedure type (hysterectomy, colectomy, thoracic resection) was chosen for exact matching, enabling a 50:50 split of open and laparoscopic procedures.

Descriptive characteristics (mean age, CCI, propensity score) were evaluated to assess the impact of matching. Thus, the propensity score matching process helped reduce the inherent systematic differences between the 2 groups.

Multivariate logistic regression was performed on the matched popu­lation to assess the impact of MIS on cDRG assignment. All the confounding factors used to create the propensity score were included in the multivariate regression to account for differences that may have remained postmatching. All statistical analyses were conducted using SAS 9.2.

Finally, we built a model to estimate the reimbursement impact on the U.S. health care system resulting from increased MIS utilization. We used projection weights provided by Premier to obtain national estimates of inpatient discharges. We projected the cost savings using Fiscal Year (FY) 2013 Medicare national average reimbursement rates (Appendix Table 2). A 10% increase in MIS utilization was considered an achievable yet conservative shift, considering regional variations and MIS adoption in general surgical procedures. Reimbursement rates for cDRG were based on the reimbursement rates for the corresponding MS-DRG with Complications and/or Comorbidities (CC). For hysterectomy, we averaged the base reimbursement for the non-cDRGs (735, 738, 741, and 743) and the cDRGs (734, 737, 740, and 742). Reimbursement was calculated by factoring in the annual number of projected inpatient procedures in the United States, prevailing and projected share of MIS, split of cDRG for open and MIS cases, and Medicare’s average national reimbursement rates for FY 2013.


During the study period, there were 292,443 hospital discharges with colectomy, hysterectomy, or thoracic resection surgery as the primary inpatient procedure. We excluded certain discharges (n=25,435) for the following reasons: involvement of patients under age 18 (n=1,324), patients being deceased in the hospital (n=3,103), lack of information on costs or severity (n=3), and the use of robot-assisted surgery (n=22,005). The three procedures accounted for 266,008 discharges (Table 1); among them, 37% of the colectomies, 23% of the hysterectomies, and 58% of the thoracic resections were performed using MIS. Raw cDRG assignment rates are presented in Table 1. For all three procedures, the MIS cohort had a lower percentage of discharges assigned to a cDRG.

TABLE 1  Description of discharges with open and MIS procedures (before matching)
Procedure Discharges (n) MIS (%) Open cases with cDRG (%) MIS cases with cDRG (%)
Colectomy 94,383 37 80 54
Hysterectomy 142,220 23 24 15
Thoracic resection 29,405 58 73 56

Logistic regression on the overall cohort before propensity matching highlighted that, after accounting for confounders, open surgery increased the odds of cDRG assignment by 74% (odds ratio [OR], 1.74; 95% confidence interval [CI], 1.70–1.78) compared with MIS. The factors used for matching and their odds ratios predicting the use of MIS surgery are presented in Appendix Table 3. Pre- and post-matching descriptive characteristics are given in Table 2.

TABLE 2  Pre- and post-matching descriptive characteristics
Pre-matching Post-matching
Open MIS P value Open MIS P value
n 181,901 84,107 67,532 67,532
Age, mean 54.6 55.4 <.001 55.1 55.1 .5368
Charlson Comorbidity Index, mean 1.49 1.48 .2952 1.50 1.48 .1447
Propensity score, mean 0.2408 0.4791 <.001 0.4146 0.4225 <.001

After adjusting for all confounders, the MIS cohort had a statistically significantly lower percentage of cDRG assignment. Across the three procedures, 48% of the open procedures were assigned to cDRG, compared with 39% of laparoscopic procedures (P<.001). Further, as presented in Table 3, colectomy MIS discharges were assigned to a cDRG less often than open (57% vs. 71%, respectively; relative reduction [RR], 20%), hysterectomy MIS discharges were assigned to a cDRG less often than open (15% vs. 19%; RR, 23%), and thoracic resection MIS discharges were assigned to a cDRG less often (62% vs. 70%; RR, 11%) than open.

TABLE 3 Post-matching cDRG assignment rates by procedure
Procedure Discharges (n) Open cases with cDRG (%) MIS cases with cDRG (%) P value
Colectomy 57,032 71 57 <.001
Hysterectomy 59,782 19 15 <.001
Thoracic 18,250 70 62 <.001

In the post-matching logistic regression model, again accounting for confounders, open surgery was associated with a 67% (OR, 1.67; 95% CI, 1.62–1.71) increased cDRG assignment rate compared to MIS.

The model we employed to estimate the reduction in payer reimbursement across the United States, assuming a 10% increase in MIS, is presented in Table 4. It should be acknowledged that not all patients are ideal candidates for under­going MIS. Patient factors such as comorbidities, physician skills, and hospital infrastructure could influence the access to MIS. The model was limited to hospital reimbursement for inpatient care, and does not include reimbursement associated with follow-up visits. In total, based on the Premier-provided projection weights, there were an estimated 224,592 colectomy, 279,748 hysterectomy, and 63,768 thoracic resection discharges, across the U.S. annually. Our model presents a conservative estimate of projected savings as the cDRG reimbursement was based on reimbursement for CC DRGs and a 10% increase in MIS share, which can be easily achieved given the regional variation and adoption of MIS in similar general surgeries. Our model projects $24.4 million in annual savings from reduction in payer reimbursement for colectomy ($17 million), hysterectomy ($5 million), and thoracic resection ($2.4 million).

TABLE 4 Estimated reduction in reimbursement from a 10% increase in MIS utilization
Estimated 2011 discharges 10% increase in MIS discharges Projected savings
MIS (%) Total reimbursement MIS (%) Total reimbursement
Colectomy 37 $2,921,587,369 47 $2,904,575,293 $17,012,076
Hysterectomy 23 $2,070,305,973 33 $2,065,321,210 $4,984,762
Thoracic 58 $858,915,011 68 $856,479,211 $2,435,800
Total $5,850,808,353 $5,826,375,714 $24,432,638


Our results considerably extend previous single-procedure, single-institution research (Senagore 2005) showing the association between MIS and lower cDRG assignment by analyzing data from a large national claims database and multiple procedures. To our knowledge, this is the first such national study performed. We risk-adjusted the data by propensity-matching the open and MIS cases based on patient characteristics including comorbidities, hospital characteristics, procedural characteristics, payer, and surgeon specialty. After accounting for a majority of confounders, we found an association between MIS and a lower rate of cDRG assignment for all three procedures analyzed. Although there might be other clinical reasons for why the MIS cohort was associated with fewer cDRG assignments, having accounted for the most common preoperative patient related clinical factors, we believe the difference in the rate of postoperative complications as a result of the surgical approach remains the principal reason for cDRG assignment.

The Center for Medicare and Medicaid Services’ (CMS) acute Inpatient Prospective Payment System (IPPS) is used to pay for inpatient stays under Medicare Part A. Each discharge is assigned a DRG, which has an associated payment weight based on average resources used. The more complex and resource-intensive the DRG, the higher the weight assigned. To determine reimbursement for a given discharge, Medicare uses a formula that multiplies the DRG’s relative weight by the base payment rate (in 2013, this was $5,774.25). Medicare further adjusts the reimbursement amount based on a number of largely nonclinical factors, including hospital location, teaching status, and percentage of low-income patients.

Appendix Table 2 presents the 2013 Medicare base reimbursement for the DRGs in this study. There is a significant difference in reimbursement between non-cDRG and cDRG discharges. In 2013, the base Medicare reimbursement for non-cDRG colectomy discharges was $9,447.25, while cDRG reimbursement was $14,857.72 to $30,371.98. Hysterectomy and thoracic resection show similar differences. With hundreds of thousands of procedures performed each year, reducing the number of cDRG assignments based on postoperative complications can result in significant cost savings from a payer perspective.

Our results suggest that MIS can help reduce overall U.S. health care system reimbursement costs. Our model conservatively estimates nearly $24.4 million in annual savings for a 10% increase in MIS utilization. MIS is also associated with fewer readmissions and faster recovery time, which could further add to the savings.

Administrative claims databases, such as Premier, allow for the study of large populations, but there are limitations. Patients were not randomized, so there is potential for selection bias.

Although we attempted to control for clinical severity, surgeons may have used additional clinical data available to select their approach. Also, based on data available, we could not identify and eliminate the MIS procedures that were converted to open procedures. There might be coding errors, documentation errors, and incomplete records. However, these errors should be distributed equally between the MIS and open groups. Factors such as surgeon training or other surgeon preferences could not be accounted for and might affect results.

Despite these limitations, this study presents the first national-level payer view of the potential association between MIS utilization and cDRG assignment. Collectively, this study, along with others demonstrating MIS’s superior outcomes, supports greater adoption of MIS for colectomy, hysterectomy, and thoracic procedures.

Further research, including a prospective cohort study, are required to definitively determine if MIS is the reason for the lower rate of cDRG assignment.


The U.S. health care industry is in the midst of a fundamental transformation, stemming largely from rising costs and inconsistent quality of care. Health care reform laws and economic pressures are causing a shift in focus from volume-based to value-based care.

Payers and providers continue to explore innovations that improve clinical outcomes and reduce costs, and MIS is one such innovation.

MIS approaches in colectomy, hysterectomy, and thoracic resection have demonstrated significant clinical benefits, including a reduction in both hospital cost per case and payer reimbursement expense based on fewer cDRG assignments. Further adoption of MIS may lead to improved outcomes and additional savings.


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Corresponding author

Santosh J. Agarwal, BPharm, MS
Phone: (508) 452-1610

Funding source: This research project was sponsored by Covidien, a global company that manufactures, distributes, and provides services for a diverse range of medical devices and supplies.

Disclosure statement: Santosh Agarwal and Gary Delhougne are employees of, and hold stock in, Covidien, a medical device and supplies manufacturer. Jill Sackman and Levi Citrin report being paid by Covidien to provide editorial services. Anthony Senagore reports no disclosures.


Appendix Table 1  ICD procedure and MS-DRG codes used to select discharges
Procedure MIS Open MS-DRG
ICD code ICD code Code Description cDRG assignment
Colectomy 17.31 45.71 329 Major Small and Large Bowel Procedures w MCC Yes
17.32 45.72 330 Major Small and Large Bowel Procedures w CC Yes
17.33 45.73 331 Major Small and Large Bowel Procedures w/o CC/MCC No
17.34 45.74
17.35 45.75
17.36 45.76
17.39 45.79
45.81 45.82
Hysterectomy 68.31 68.39 734 Pelvic Evisceration, Radical Hysterectomy and Radical Vulvectomy w CC/MCC Yes
68.41 68.49 735 Pelvic Evisceration, Radical Hysterectomy and Radical Vulvectomy w/o CC/MCC No
68.51 68.59 736 Uterine and Adnexa Procedures for Ovarian or Adnexal Malignancy w MCC Yes
68.61 68.69 737 Uterine and Adnexa Procedures for Ovarian or Adnexal Malignancy w CC Yes
738 Uterine and Adnexa Procedures for Ovarian or Adnexal Malignancy w/o CC/MCC No
739 Uterine, Adnexa Procedures for Nonovarian/Adnexal Malignancy w MCC Yes
740 Uterine, Adnexa Procedures for Nonovarian/Adnexal Malignancy w CC Yes
741 Uterine, Adnexa Procedures for Nonovarian/Adnexal Malignancy w/o CC/MCC No
742 Uterine and Adnexa Procedures for Nonmalignancy w CC/MCC Yes
743 Uterine and Adnexa Procedures for Nonmalignancy w/o CC/MCC No
Thoracic 32.20 32.29 163 Major Chest Procedures w MCC Yes
32.30 32.39 164 Major Chest Procedures w CC Yes
32.41 32.49 165 Major Chest Procedures w/o CC/MCC No
CC=complications and comorbidities, cDRG=complex Diagnosis Related Groups, ICD=International Classification of Diseases, MCC=major complications and comorbidities, MIS=minimally invasive surgery, MS-DRG=Medicare Severity Diagnosis Related Groups
  Appendix Table 2  Medicare national average reimbursement rates for FY 2013 by MS-DRG
MS-DRG Average payment
329: Major Small and Large Bowel Procedures w MCC $30,371.98
330: Major Small and Large Bowel Procedures w CC $14,857.72
331: Major Small and Large Bowel Procedures w/o CC/MCC $9,447.25
734: Pelvic Evisceration, Radical Hysterectomy and Radical Vulvectomy w CC/MCC $15,389.53
735: Pelvic Evisceration, Radical Hysterectomy and Radical Vulvectomy w/o CC/MCC $6,745.48
736: Uterine and Adnexa Procedures for Ovarian or Adnexal Malignancy w MCC $25,487.54
737: Uterine and Adnexa Procedures for Ovarian or Adnexal Malignancy w CC $11,576.79
738: Uterine and Adnexa Procedures for Ovarian or Adnexal Malignancy w/o CC/MCC $7,421.64
739: Uterine, Adnexa Procedures for Nonovarian/Adnexal Malignancy w MCC $19,181.48
740: Uterine, Adnexa Procedures for Nonovarian/Adnexal Malignancy w CC $9,058.64
741: Uterine, Adnexa Procedures for Nonovarian/Adnexal Malignancy w/o CC/MCC $6,639.81
742: Uterine and Adnexa Procedures for Nonmalignancy w CC/MCC $8,174.61
743: Uterine and Adnexa Procedures for Nonmalignancy w/o CC/MCC $5,573.88
163: Major Chest Procedures w MCC $29,560.12
164: Major Chest Procedures w CC $15,123.34
165: Major Chest Procedures w/o CC/MCC $10,348.61
Appendix Table 3  Predictors of minimally invasive surgery
Effect Odds Ratio 95% CI
Lower Upper
36–45 vs ≤35 years 0.88 0.85 0.92
46–55 vs ≤35 0.87 0.84 0.91
56–65 vs ≤35 0.80 0.76 0.83
66–75 vs ≤35 0.76 0.72 0.80
76–85 vs ≤35 0.71 0.67 0.76
85+ vs ≤35 0.67 0.62 0.73
Male vs female 0.96 0.94 0.98
Black vs white 0.80 0.77 0.82
Others vs white 0.86 0.84 0.88
Northeast vs South 1.13 1.10 1.16
Midwest vs South 0.83 0.80 0.85
West vs South 0.94 0.91 0.96
Urban vs rural 1.35 1.30 1.39
Teaching vs nonteaching 0.93 0.91 0.95
100–249 beds vs <100 beds 1.29 1.22 1.36
250–499 beds vs <100 beds 1.16 1.10 1.22
>500 beds vs <100 beds 1.32 1.25 1.40
Medicaid vs Medicare 0.86 0.82 0.90
Managed care vs Medicare 1.17 1.13 1.21
Uninsured vs Medicare 0.72 0.67 0.76
Others vs Medicare 0.97 0.91 1.04
Nonelective vs elective admission 0.43 0.41 0.44
Myocardial infarction 0.94 0.88 0.99
Congestive heart failure 0.83 0.78 0.88
Peripheral vascular disease 0.87 0.82 0.93
Cerebrovascular disease 0.94 0.86 1.03
Dementia 0.73 0.55 0.96
COPD 0.88 0.85 0.90
Rheumatic disease 0.97 0.90 1.04
Ulcers 0.92 0.82 1.05
Liver disease, mild 1.01 0.87 1.17
Liver disease, moderate/severe 0.85 0.66 1.09
Diabetes 0.94 0.91 0.97
Diabetes + sequelae 1.03 0.94 1.13
Chronic renal failure 0.84 0.79 0.89
Malignancy 0.82 0.76 0.88
Metastatic solid tumor 0.56 0.54 0.59
Paralysis 0.67 0.52 0.87
AIDS 0.70 0.47 1.04
Obesity 0.86 0.84 0.89
Hypertension 0.94 0.92 0.97
Others vs general surgeons 0.85 0.81 0.89
Colorectal surgeons vs general surgeons 1.73 1.67 1.81
Obstetrics and gynecology vs general surgeons 0.62 0.57 0.67
Thoracic surgeon vs general surgeons 1.09 1.03 1.16
Colectomy vs hysterectomy 2.36 2.08 2.68
Thoracic vs hysterectomy 3.68 3.34 4.06
Multiple segmental large bowel resection vs abdominal hysterectomy 1.16 0.93 1.46
Cecectomy vs abdominal hysterectomy 2.04 1.83 2.29
Right hemicolectomy vs abdominal hysterectomy 2.06 1.87 2.26
Transverse colon resection vs abdominal hysterectomy 1.19 1.05 1.34
Left hemicolectomy vs abdominal hysterectomy 1.23 1.12 1.36
Sigmoidectomy vs abdominal hysterectomy 1.71 1.56 1.87
Unspecified partial large intestine resection vs abdominal hysterectomy 0.80 0.72 0.90
Total intra-abdominal colectomy vs abdominal hysterectomy 0.00 0.00 0.00
Supracervical/subtotal hysterectomy vs abdominal hysterectomy 8.10 7.76 8.45
Vaginal hysterectomy vs abdominal hysterectomy 13.10 12.64 13.58
Radical hysterectomy vs abdominal hysterectomy 2.97 2.67 3.31
Wedge resection vs abdominal hysterectomy 6.46 6.09 6.86
Segmental resection vs abdominal hysterectomy 1.89 1.71 2.08
Lung lobectomy vs abdominal hysterectomy 0.00 0.00 0.00
Other diagnosis vs malignancy 0.55 0.51 0.60
Benign neoplasm of colon vs malignancy 1.93 1.78 2.10
IBD / diverticulitis vs malignancy 0.94 0.87 1.02
Benign fibroids vs malignancy 0.44 0.40 0.47
Endometriosis vs malignancy 0.68 0.62 0.74
Menstrual disorders vs malignancy 0.60 0.55 0.65
Genital prolapse vs malignancy 0.09 0.08 0.10
Secondary neoplasm of respiratory system vs malignancy 0.87 0.79 0.97
Pulmonary fibrosis vs malignancy 1.25 1.09 1.43
Pneumothorax vs malignancy 2.41 2.08 2.77

Managed Care’s Top Ten Articles of 2016

There’s a lot more going on in health care than mergers (Aetna-Humana, Anthem-Cigna) creating huge players. Hundreds of insurers operate in 50 different states. Self-insured employers, ACA public exchanges, Medicare Advantage, and Medicaid managed care plans crowd an increasingly complex market.

Major health care players are determined to make health information exchanges (HIEs) work. The push toward value-based payment alone almost guarantees that HIEs will be tweaked, poked, prodded, and overhauled until they deliver on their promise. The goal: straight talk from and among tech systems.

They bring a different mindset. They’re willing to work in teams and focus on the sort of evidence-based medicine that can guide health care’s transformation into a system based on value. One question: How well will this new generation of data-driven MDs deal with patients?

The surge of new MS treatments have been for the relapsing-remitting form of the disease. There’s hope for sufferers of a different form of MS. By homing in on CD20-positive B cells, ocrelizumab is able to knock them out and other aberrant B cells circulating in the bloodstream.

A flood of tests have insurers ramping up prior authorization and utilization review. Information overload is a problem. As doctors struggle to keep up, health plans need to get ahead of the development of the technology in order to successfully manage genetic testing appropriately.

Having the data is one thing. Knowing how to use it is another. Applying its computational power to the data, a company called RowdMap puts providers into high-, medium-, and low-value buckets compared with peers in their markets, using specific benchmarks to show why outliers differ from the norm.
Competition among manufacturers, industry consolidation, and capitalization on me-too drugs are cranking up generic and branded drug prices. This increase has compelled PBMs, health plan sponsors, and retail pharmacies to find novel ways to turn a profit, often at the expense of the consumer.
The development of recombinant DNA and other technologies has added a new dimension to care. These medications have revolutionized the treatment of rheumatoid arthritis and many of the other 80 or so autoimmune diseases. But they can be budget busters and have a tricky side effect profile.

Shelley Slade
Vogel, Slade & Goldstein

Hub programs have emerged as a profitable new line of business in the sales and distribution side of the pharmaceutical industry that has got more than its fair share of wheeling and dealing. But they spell trouble if they spark collusion, threaten patients, or waste federal dollars.

More companies are self-insuring—and it’s not just large employers that are striking out on their own. The percentage of employers who fully self-insure increased by 44% in 1999 to 63% in 2015. Self-insurance may give employers more control over benefit packages, and stop-loss protects them against uncapped liability.