Abstract
Background and purpose
Shoulder arthroplasty is being performed in the United States with increasing frequency. We describe the medium-term findings from a large integrated healthcare system shoulder arthroplasty registry.
Patients and methods
Shoulder arthroplasty cases registered between January 2005 and June 2013 were included for analysis. The registry included patient characteristics, surgical information, implant data, attrition, and patient outcomes such as surgical site infections, venous thromboembolism, and revision procedures.
Results
During the study period, 6,336 primary cases were registered. Median follow-up time for all primaries was 3.3 years; 461 cases were lost to follow-up by ending of health plan membership. Primary cases were predominantly female (56%) and white (81%), with an average age of 70 years. The most common reason for surgery was osteoarthritis in 60% of cases, followed by acute fracture (17%) and rotator cuff tear arthropathy (15%). In elective shoulder arthroplasty procedures, 200 all-cause revisions (4%) were reported, with glenoid wear being the most common reason.
Interpretation
Most arthroplasties were elective procedures: over half performed for osteoarthritis. Glenoid wear was the most common reason for revision of primary shoulder arthroplasty in elective cases.
In the period 2000 through 2010, over 200,000 shoulder arthroplasties were performed in the USA for osteoarthritis (Trofa et al. 2014). With the increasing use of shoulder arthroplasty (SA) over the past decade (Kim et al. 2011) and projections that future growth rates of SA may exceed those of hip and knee arthroplasty (Day et al. 2010), the need to track the outcomes of SA is becoming increasingly important.
Arthroplasty registries provide an important mechanism for tracking surgical outcomes. In the fields of total hip arthroplasty and total knee arthroplasty, registries have demonstrated their importance in monitoring revisions, complications, and mortality, identifying outlier prostheses, and improving quality of care (Graves et al. 2004, Herberts and Malchau 2000, de Steiger et al. 2013, Paxton et al. 2010). SA registries have also provided critical information about demographics, survival, and outlier implants, though there have been considerably fewer publications from the younger national SA registries than from the more established hip and knee registries (Clitherow et al. 2014, Young et al. 2013, Rasmussen et al. 2012a, Rasmussen et al. 2014a and b, Fevang et al. 2009, Fevang et al. 2013). The lack of a national US registry emphasizes the need to use existing US registries to conduct international comparisons of SA patients, implants, surgical techniques, and outcomes. We present the medium-term findings of a large integrated healthcare system SA registry.
Material and methods
Data collection procedures and participants
Kaiser Permanente is a large integrated healthcare system based in California, USA. In 2001, Kaiser Permanente started a total joint replacement registry, focusing on a minimal dataset and revision surgery as the endpoint. Its success led to the formation of other registries, including the Kaiser Permanente Shoulder Arthroplasty Registry (KPSAR) (Paxton et al. 2012).
Starting in April 2010, surgeons have collected intraoperative information on paper forms to send to the registry. This information on paper is validated and supplemented with information from the institution’s electronic medical records (EMRs) using electronic algorithms and queries. Cases from January 2005 through March 2010 have been incorporated into the registry by retrospective review of EMR information.
Registry data components
Patient factors captured by the registry include age, sex, race, diagnosis, BMI, American Society of Anaesthesiologists’ (ASA) score, and medical comorbidities. Surgical factors recorded in the registry include the type of procedure performed (total shoulder arthroplasty (TSA), humeral head resurfacing (HHR), reverse total shoulder arthroplasty (RSA), hemiarthroplasty (HEMI)), implanted components, fixation, surgical approach, bone graft, subscapularis repair, anesthesia, blood loss, operative time, and length of stay. Surgeon characteristics captured include fellowship status and calculated annual case volume. Hospital annual volume is also included.
The registry captures a number of postoperative complications. Data on death (30- and 90-day mortality) are obtained from an administrative database that monitors the institution’s membership and information about use of the service. International Classification of Disease, Ninth Revision, Clinical Modification codes (ICD-9-CM) (Buck 2010) are used to identify suspected complications; all such cases are audited through chart review by clinical content experts to determine if they meet pre-established criteria. These outcomes include deep infection (following National Healthcare Safety Network/Centers for Disease Control guidelines (Horan et al. 2008) with extended surveillance time for the lifetime of the implant), deep vein thrombosis and pulmonary embolism (DVT/PE) monitored within 90 days of surgery (using the Agency for Healthcare Research and Quality Inpatient Quality Indicators Algorithm (Department of Health and Human Services 2007)), and implant revision. Revisions, defined here as any procedure after the registered index arthroplasty involving the addition, removal or replacement of at least 1 implanted component, are captured together with reasons for revision and validated by chart review. HHR procedures and reverse total shoulder procedures are distinguished from other procedures, and patients with a history of fracture are identified through details on the operative paper forms. Missing data concerning identification of the patient or surgeon, procedure type with laterality, and primary diagnosis are reviewed and coded using chart review methodology for comprehensive data and 100% capture.
Attrition of the cohort is monitored using the membership files of the integrated healthcare system that this registry covers. Biannual reports monitoring both termination of membership in the health plan and mortality in the enrolled cohort are obtained from the institution and integrated with the registry. For this study, attrition is defined as a patient ending his/her health plan membership or dying before the end of June 2013.
Study design
SA cases between January 2005 and June 2013 were included for analysis. This study examined primary procedures from 2 of 6 regions in the healthcare system (Southern California and Northern California) with a combined patient population of well over 7 million members (Kaiser Permanente 2014). The population covered by Kaiser Permanente has been shown to be representative (Karter et al. 2002, Khatod et al. 2008, Koebnick et al. 2012) of the 37 million inhabitants of the state of California (United States Census Bureau 2015). While 6 regions participated in the registry during the study period, the other 4 regions (Hawaii, Pacific Northwest, Mid-Atlantic, Colorado) each represent much smaller case volumes and also later entry into the registry. The final study sample includes data from 32 medical centers and 263 participating surgeons, all in California.
All biological glenoid resurfacing procedures were excluded from the study. Individuals with primary diagnoses of cancer and/or infection were also excluded. Patients who had surgery secondary to acute fracture were evaluated separately from those undergoing elective surgery, as it was felt that trauma patients may represent a different patient demographic.
For this study, we developed a hierarchy to apply to cases with more than 1 diagnosis listed for the index procedure, in order to identify the primary diagnosis (i.e. the principal reason to be reported). All index cases with multiple diagnoses were reviewed by a registry surgeon to ensure the clinical accuracy of the primary diagnosis hierarchy. In contrast, more than 1 reason for revision could be reported for study purposes (for example, rotator cuff tear and glenoid component loosening).
Ethics
Institutional review board approval was obtained prior to the inception of the registry (Kaiser Permanente Southern California Institutional Review Board, study 5527).
Results
Demographics
6,336 cases met the inclusion criteria (Table 1), comprising 2,179 HEMIs (34%), 191 HHRs (3%), 940 RSAs (15%), and 3,026 TSAs (48%). Female members comprised 56% of all cases, and the mean overall age was 70 years. HHR patients were younger on average (mean 59 years) whereas RSA patients were generally older (mean 75 years). Whites represented 81% of all cases. Mean BMI of all cases was 30. On average, cases had 3.3 years of follow-up. Overall, 461 cases (7%) were lost to follow-up before the end of the study period, due to termination of membership in the health plan. Of the 6,336 cases altogether, 5,291 (84%) were elective, made up of 1,218 HEMIs (23%), 191 HHRs (4%), 868 RSAs (16%), and 3,014 TSAs (57%). There were 1,045 acute fracture cases, which included 961 HEMIs (92%), 72 RSAs (7%), and 12 TSAs (1%).
Table 1.
Total sample n = 6,336 |
HEMI n = 2,179 |
HHR n = 191 |
RSA n = 940 |
TSA n = 3,026 |
Elective n = 5,291 |
Fracture n = 1,045 |
||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
n | (%) | n | (%) | n | (%) | n | (%) | n | (%) | n | (%) | n | (%) | |
Gender | ||||||||||||||
Missing | 29 | 0.5 | 3 | 0.1 | 0 | 0 | 6 | 0.6 | 20 | 0.7 | 28 | 0.5 | 1 | 0.1 |
Male | 2,747 | 43 | 817 | 38 | 115 | 60 | 302 | 32 | 1,513 | 50 | 2,498 | 47 | 249 | 24 |
Female | 3,560 | 56 | 1,359 | 62 | 76 | 40 | 632 | 67 | 1,493 | 49 | 2,765 | 52 | 795 | 76 |
Mean age (SD), years | 70 | 11 | 68 | 12 | 59 | 12 | 75 | 7.6 | 69 | 9.1 | 69 | 10 | 71 | 12 |
Race | ||||||||||||||
Asian/Pacific islander | 154 | 2.4 | 55 | 2.5 | 4 | 2.1 | 28 | 3.0 | 67 | 2.2 | 118 | 2.2 | 36 | 3.4 |
Black | 299 | 4.7 | 93 | 4.3 | 19 | 10 | 40 | 4.3 | 147 | 4.9 | 274 | 5.2 | 25 | 2.4 |
Native American | 16 | 0.3 | 10 | 0.5 | 0 | 0.0 | 1 | 0.1 | 5 | 0.2 | 10 | 0.2 | 6 | 0.6 |
Missing | 55 | 0.9 | 16 | 0.7 | 1 | 0.5 | 5 | 0.5 | 33 | 1.1 | 49 | 0.9 | 6 | 0.6 |
White | 5,154 | 81 | 1,753 | 81 | 147 | 77 | 737 | 78 | 2,517 | 83 | 4,321 | 82 | 833 | 80 |
Hispanic | 606 | 9.6 | 229 | 10.5 | 20 | 11 | 125 | 13 | 232 | 7.7 | 480 | 9.1 | 126 | 12 |
Other | 52 | 0.8 | 23 | 1.1 | 0 | 0 | 4 | 0.4 | 25 | 0.8 | 39 | 0.7 | 13 | 1.2 |
Mean BMI (SD) | 30 | 6.5 | 30 | 7.2 | 31 | 7.0 | 29 | 5.8 | 30 | 6.1 | 30 | 6.2 | 30 | 7.8 |
BMI category | ||||||||||||||
< 30 | 3,551 | 56 | 1,222 | 56 | 96 | 50 | 622 | 66 | 1,611 | 53 | 2,971 | 56 | 580 | 56 |
≥ 30 and < 35 | 1,485 | 23 | 479 | 22 | 50 | 26 | 189 | 20 | 767 | 25 | 1,254 | 24 | 231 | 22 |
≥ 35 | 1,208 | 19 | 441 | 20 | 45 | 24 | 120 | 13 | 602 | 20 | 990 | 19 | 218 | 21 |
Missing | 92 | 1.5 | 37 | 1.7 | 0 | 0.0 | 9 | 1.0 | 46 | 1.5 | 76 | 1.4 | 16 | 1.5 |
ASA category | ||||||||||||||
1 or 2 | 3,106 | 49 | 1,066 | 49 | 107 | 56 | 372 | 40 | 1,561 | 52 | 2,670 | 51 | 436 | 42 |
≥ 3 | 2,675 | 42 | 948 | 44 | 65 | 34 | 467 | 50 | 1,195 | 40 | 2,153 | 41 | 522 | 50 |
Missing | 555 | 8.8 | 165 | 7.6 | 19 | 10 | 101 | 11 | 270 | 8.9 | 468 | 8.9 | 87 | 8.3 |
Mean follow-up (SD), days | 1,196 | 838 | 1,398 | 846 | 1,348 | 789 | 856 | 708 | 1,147 | 832 | 1,187 | 839 | 1,245 | 833 |
Membership termination | ||||||||||||||
No termination | 5,875 | 93 | 1,974 | 91 | 165 | 86 | 899 | 96 | 2,837 | 94 | 4,927 | 93 | 948 | 91 |
Termination | 461 | 7.3 | 205 | 9.4 | 26 | 14 | 41 | 4.4 | 189 | 6.3 | 364 | 6.9 | 97 | 9.3 |
Primary diagnoses
The principal diagnosis was osteoarthritis in 60% of all cases, including 94% of TSAs (Table 2). Fracture was the principal diagnosis for 17% of all cases: 44% of HEMIs, 8% of RSAs, and 0.4% of TSAs. In 15% of all cases rotator cuff arthropathy (RCA) was the principal diagnosis, including 85% of RSAs, 13% of HHRs, and 6% of HEMIs. Overall, osteonecrosis applied to 2.6% of cases, with rheumatoid arthritis assigned to only 1.4% of cases.
Table 2.
Total sample n = 6,336 |
HEMI n = 2,179 |
HHR n = 191 |
RSA n = 940 |
TSA n = 3,026 |
||||||
---|---|---|---|---|---|---|---|---|---|---|
n | (%) | n | (%) | n | (%) | n | (%) | n | (%) | |
Osteoarthritis | 3790 | 60 | 818 | 38 | 130 | 68 | 6 | 0.6 | 2836 | 94 |
Proximal humerus fracture | 1045 | 17 | 961 | 44 | 0 | 0 | 72 | 7.7 | 12 | 0.4 |
Rotator cuff arthropathy | 949 | 15 | 129 | 5.9 | 25 | 13 | 795 | 85 | 0 | 0 |
Osteonecrosis – avascular necrosis | 167 | 2.6 | 91 | 4.2 | 21 | 11 | 3 | 0.3 | 52 | 1.7 |
Rheumatoid arthritis | 89 | 1.4 | 32 | 1.5 | 1 | 0.5 | 0 | 0.0 | 56 | 1.9 |
Failed ORIF | 73 | 1.2 | 45 | 2.1 | 2 | 1.1 | 17 | 1.8 | 9 | 0.3 |
Non-union | 49 | 0.8 | 32 | 1.5 | 0 | 0.0 | 12 | 1.3 | 5 | 0.2 |
Malunion | 48 | 0.8 | 25 | 1.2 | 2 | 1.1 | 9 | 1.0 | 12 | 0.4 |
Posttraumatic arthritis | 46 | 0.7 | 16 | 0.7 | 3 | 1.6 | 0 | 0.0 | 27 | 0.9 |
Rotator cuff tear | 34 | 0.5 | 10 | 0.5 | 1 | 0.5 | 23 | 2.5 | 0 | 0.0 |
Chronic dislocation | 22 | 0.4 | 15 | 0.7 | 3 | 1.6 | 3 | 0.3 | 1 | 0.0 |
Non-rheumatoid inflammatory arthritis | 16 | 0.3 | 5 | 0.2 | 1 | 0.5 | 0 | 0.0 | 10 | 0.3 |
Capsulorrhaphy arthropathy | 11 | 0.2 | 3 | 0.1 | 2 | 1.1 | 0 | 0.0 | 6 | 0.2 |
Other | 6 | 0.1 | 3 | 0.1 | 1 | 0.5 | 2 | 0.2 | 0 | 0.0 |
Outcomes
There were 200 all-cause revisions in the elective patient population (4%) (Table 3). The most common reason was glenoid arthritis wear in 53 cases (27%). Among the HEMI revisions, glenoid wear was a reason for revision in 52% of cases, and it was a reason for revision in 78% of HHR revisions. In the elective procedures (Table 4), there were 56 instances of deep infection (1.1%); these occurred more commonly among RSAs (2.4%). Similarly, there were 25 DVTs (0.5%) and 20 PEs (0.4%). The 90-day mortality rate in the elective patient population was 0.3%.
Table 3.
Total n = 200 |
HEMI n = 75 |
HHR n = 18 |
RSA n = 44 |
TSA n = 63 |
||
---|---|---|---|---|---|---|
n | (%) | n | n | n | n | |
Glenoid wear | 53 | 27 | 39 | 14 | 0 | 0 |
Deep infection | 40 | 20 | 6 | 1 | 15 | 18 |
Instability | 36 | 18 | 8 | 1 | 16 | 11 |
Rotator cuff tear | 33 | 17 | 10 | 1 | 0 | 22 |
Glenoid component failure | 26 | 13 | 0 | 0 | 6 | 20 |
Humeral component loosening | 12 | 6 | 9 | 0 | 1 | 2 |
Painful HEMI with cuff dysfunction | 11 | 6 | 11 | 0 | 0 | 0 |
Malposition | 11 | 6 | 4 | 1 | 1 | 5 |
Periprosthetic fracture | 3 | 2 | 1 | 0 | 1 | 1 |
Other | 9 | 5 | 1 | 1 | 5 | 2 |
Table 4.
Total n = 5,291 |
HEMI n = 1,218 |
HHR n = 191 |
RSA n = 868 |
TSA n = 3,014 |
||||||
---|---|---|---|---|---|---|---|---|---|---|
n | (%) | n | (%) | n | (%) | n | (%) | n | (%) | |
Deep infection | 56 | 1.1 | 13 | 1.1 | 1 | 0.5 | 21 | 2.4 | 21 | 0.7 |
DVT | 25 | 0.5 | 4 | 0.3 | 1 | 0.5 | 5 | 0.6 | 15 | 0.5 |
PE | 20 | 0.4 | 0 | 0.0 | 1 | 0.5 | 6 | 0.7 | 13 | 0.4 |
Revision for any reason | 200 | 3.8 | 75 | 6.2 | 18 | 9.4 | 44 | 5.1 | 63 | 2.1 |
Revision (aseptic) | 160 | 3.0 | 69 | 5.7 | 17 | 8.9 | 29 | 3.3 | 45 | 1.5 |
Death (30 days) | 9 | 0.2 | 1 | 0.1 | 0 | 0.0 | 2 | 0.2 | 6 | 0.2 |
Death (90 days) | 16 | 0.3 | 3 | 0.3 | 0 | 0.0 | 3 | 0.4 | 10 | 0.3 |
There were 31 all-cause revisions in fracture patients (Table 5), resulting in a revision rate of 3%. The most common reason for revision was deep infection (11 revisions), while instability was the second most common reason for revision in fracture patients. In acute fracture cases (Table 6), there were 15 instances of deep infection (1.4%) and all of these occurred in HEMI patients. There were 8 DVTs (0.8%), 6 of which occurred in HEMI patients (0.6%). The 90-day mortality rate was 1.6%.
Table 5.
Total n = 31 |
HEMI n = 30 |
RSA n = 1 |
|
---|---|---|---|
n | n | n | |
Deep infection | 11 | 11 | 0 |
Instability | 7 | 6 | 1 |
Glenoid wear | 5 | 5 | 0 |
Rotator cuff tear | 5 | 5 | 0 |
Humeral component loosening | 3 | 3 | 0 |
Other | 4 | 3 | 1 |
Table 6.
Total n = 1,045 |
HEMI n = 961 |
RSA n = 72 |
|||
---|---|---|---|---|---|
n | (%) | n | (%) | n | |
Deep infection | 15 | 1.4 | 15 | 1.6 | 0 |
DVT | 8 | 0.8 | 6 | 0.6 | 2 |
PE | 10 | 1.0 | 10 | 1.0 | 0 |
Revision for any reason | 31 | 3.0 | 30 | 3.1 | 1 |
Revision (aseptic) | 20 | 1.9 | 19 | 2.0 | 1 |
Death (30 days) | 11 | 1.1 | 10 | 1.0 | 1 |
Death (90 days) | 17 | 1.6 | 16 | 1.7 | 1 |
Discussion
To our knowledge, this study covering the Kaiser Permanente population residing in California is one of the largest ever to be published from a shoulder arthroplasty registry. Four-fifths of the patients who received SA were whites. In comparison, Jain et al. (2006) noted that roughly nine-tenths of patients undergoing SA in the USA from 1990 through 2000 were of white race. It is unknown whether our data represent improved access to SA by minority populations or whether this difference simply represents the diversity of our patient population in California. The average age of patients in our study is comparable to that in other studies examining the US population (Jain et al. 2006, Adams et al. 2006) and to those based on studies from other national shoulder replacement registries (Rasmussen et al. 2012a, Fevang et al. 2013, Young et al. 2013, Clitherow et al. 2014).
Similarly to other studies examining US based populations (Adams et al. 2006, Jain et al. 2006, Day et al. 2010, Kim et al. 2011), we found that the majority of patients undergoing SA are females (56%). However, this difference may be lessening with time. A study by Adams et al. (2006) examining the incidence of SA in Olmstead County, Minnesota between 1976 and 2000 contained over 65% female patients. Jain et al. (2006) reported on 12,758 patients from Nationwide Inpatient Sample databases from between 1990 and 2000. From 1990–1993, 66% of the patients were female, as compared to 63% from 1994–1997 and 57% from 1998–2000. It is interesting to note, however, that patient populations outside of the USA continue to show that a high percentage of female patients undergo shoulder replacement. In 2012, the Danish registry published its early findings and reported that 70% of primary SAs were performed on women (Rasmussen et al. 2012a), while a recent study from Norway found that 85% of patients undergoing RSA were female (Fevang et al. 2013).
Few studies have evaluated SA and obesity (Li et al. 2013, Griffin et al. 2014). In our cohort, 19% of the patients had a BMI of 35 or more. In their recent study, Griffin et al. (2014) noted that 7.5% of patients undergoing shoulder replacement in the USA are obese, with 1.8% being categorized as morbidly obese (BMI of 40 or over).
As with our findings, other reports from within the USA have shown osteoarthritis to be the most common reason for shoulder replacement (Adams et al. 2006, Jain et al. 2006, Kim et al. 2011). The percentage of cases with osteoarthritis as the primary diagnosis appears to be increasing. Jain et al. (2006) noted that osteoarthritis was the primary diagnosis in 57% of cases during the period 1990–1993, increasing to 71% during 1998–2000.
TSA was the most commonly performed procedure in our study. The procedures performed on 48% of the cases in the KPSAR were TSA, and osteoarthritis was the primary diagnosis in 94% of these cases. HEMI was performed in 34% of cases, with fracture being the most common reason in 44% of cases, followed by osteoarthritis in 38% of cases. Using the Nationwide Inpatient Sample, Kim et al. (2011) reported that osteoarthritis was the most common diagnosis for both HEMI (43% of cases) and TSA (77% of cases) between 1993 and 2008. During this period, Kim et al. also demonstrated that while the annual rate of HEMIs increased, the rate of TSAs increased at a much higher rate. However, it should be noted that due to the fact that TSA and RSA cannot be distinguished using ICD-9-CM codes, much of this increase in the incidence of TSAs was judged to be due to approval of the RSA by the United States Food and Drug Administration during the study period.
Interestingly, our registry showed much more frequent use of TSA than some registries have reported in the international literature, such as in Norway, where, after examining 1,825 SA patients, only 69 TSAs were performed (Fevang et al. 2009). Likewise, the Danish Shoulder Arthroplasty Registry reported that TSA was used in only 3% of the cases (Rasmussen et al. 2012a). It should be noted that the major indication for SA in the Danish registry was displaced proximal humerus fracture (54%), as compared to only 17% in the present study. These findings suggest that the indications for elective arthroplasty procedures differ in various parts of the world. This may lead to future collaboration to compare the use of SA globally.
Our all-cause revision rate for elective SA was 4%, with the most common reason for revision being glenoid wear following HEMI or HHR (27% of all revisions). Looking specifically at elective HEMI, the revision rate was 6% with glenoid wear as the reason for revision in 52% of cases, while the revision rate following TSA in particular was only 2%. Previous studies from the KPSAR have examined the effect of age on early to medium-term revision rates, and have found that patients less than 60 years of age receiving a HEMI had an almost 5 times higher risk of revision than those patients who received TSA (Dillon et al. 2013).
Our overall infection rate was 1.1% for elective cases and 1.4% for traumatic cases, though not all deep infections led to formal revisions. A recent study from our registry revealed that males have a more than 2.5 times greater risk of infection, and the risk of infection decreases 5% with every 1 year of additional age (Richards et al. 2014). We have also examined our rates of venous thromboembolism, with an early paper suggesting a trend of increased DVT/PE in patients undergoing arthroplasty for trauma (Navarro et al. 2013), a trend that appears to be supported by our most recent data.
The major strength of the present study is the quality of the data. The registry collects data from over 90% of surgeons in the health system, and participation is increasing at a steady rate every year. With a high rate of participation among many surgeons across several medical centers, our findings can be generalized to larger community-based populations more accurately than results from studies consisting of cases from few surgeons at a single institution.
All the data are actively monitored on a case-by-case basis and go through a systematic quality-control process each quarter to ensure that there is a high level of integrity of the data, and to reduce information bias. Quality-control processes include an integrated set of queries, programming, and chart review methodology to catch outliers, to validate data, and to capture missing values. To maintain clinical accuracy, registry surgeons lead efforts to develop and validate data-cleaning procedures. As the registry matures, we continually evaluate our collection methods in order to better refine our data. Chart review is performed, and a new diagnosis or reason for revision can be assigned if it more accurately reflects the data.
One weakness of the present study may be the lack of outcome scores. It should be noted that there is no consensus regarding the use of patient-reported outcomes in registries, as demonstrated in a recent review of the national shoulder replacement registries by Rasmussen et al. (2012b). All 7 registries used implant survival as the primary outcome, but only 5 used or plan to use outcome measures. Only the Swedish registry obtains baseline scores, and only at certain participating centers, with the UK also planning to obtain preoperative scores. (Starting in July 2010, the KPSAR began collecting VAS pain and VAS function scores preoperatively). Furthermore, even when the decision is made to obtain patient-reported outcomes, achieving adequate patient participation can be challenging (Polk et al. 2013, Fevang et al. 2013). The Danish registry recently noted that only 65% of patients initially returned their follow-up evaluations, with follow-up telephone calls or mailings being required to improve response rates (Polk et al. 2013).
Admittedly, using implant survival alone fails to capture patients with underperforming SAs who simply decline revision surgery. A recent study examining the outcomes of SA following proximal humerus non-unions noted that 12 patients out of 67 in the study underwent reoperation. However, 24 other patients had unsatisfactory outcomes but declined revision surgery. As a result, the authors advised that “caution should be exercised when using survivorship analysis as a prognostic indicator of outcome” (Duquin et al. 2012).
In summary, we have presented the current findings from the Kaiser Permanente Shoulder Arthroplasty Registry. We hope that with time, we will be able to better examine implant survivorship and factors influencing revision for individual reasons, such as glenoid component failure. Future directions include more specific examinations of unique patient populations, such as those undergoing SA for fracture or for elective purposes.
Acknowledgments
MD: conception of the study, interpretation of data, and manuscript preparation. CA: statistical analysis and manuscript preparation. MB: data processing and manuscript preparation. AS and EY: interpretation of data and manuscript preparation. EP: conception of the study and manuscript preparation. RN: conception of study and interpretation of data.
No competing interests declared.
References
- Adams JE, Sperling JW, Hoskin TL, Melton III LJ, Cofield RH. Shoulder arthroplasty in Olmsted County Minnesota, 1976–2000: A population-based study . J Shoulder Elbow Surg. 2006;15(1):50–5. doi: 10.1016/j.jse.2005.04.009. [DOI] [PubMed] [Google Scholar]
- Buck CJ. Professional Edition. Volumes 1, 2 and 3. Saunders Elsevier; Maryland Heights: 2010. 2010 ICD-9-CM for Hospitals. [Google Scholar]
- Clitherow HD, Frampton CM, Astley TM. Effect of glenoid cementation on total shoulder arthroplasty for degenerative arthritis of the shoulder: A review of the New Zealand National Joint Registry . J Shoulder Elbow Surg. 2014;23(6):775–81. doi: 10.1016/j.jse.2013.08.022. [DOI] [PubMed] [Google Scholar]
- Day JS, Lau E, Ong KL, Williams GR, Ramsey ML, Kurtz SM. Prevalence and projections of total shoulder and elbow arthroplasty in the United States to 2015 . J Shoulder Elbow Surg. 2010;19(8):1115–20. doi: 10.1016/j.jse.2010.02.009. [DOI] [PubMed] [Google Scholar]
- de Steiger RN, Miller LN, Davidson DC, Ryan P, Graves SE. Joint registry approach for identification of outlier prostheses . Acta Orthop. 2013;84(4):348–52. doi: 10.3109/17453674.2013.831320. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Department of Health and Human Services. Agency for Healthcare Research and Quality. 2007. “AHRQ Quality Indicators. Guide to Patient Safety Indicators.”. http://www.qualityindicators.ahrq.gov/downloads/modules/psi/v31/psi_guide_v31.pdf 2014 Accessed May 28.
- Dillon MT, Inacio MC, Burke MF, Navarro RA, Yian EH. Shoulder arthroplasty in patients 59 years of age and younger . J Shoulder Elbow Surg. 2013;22(10):1338–44. doi: 10.1016/j.jse.2013.01.029. [DOI] [PubMed] [Google Scholar]
- Duquin TR, Jacobson JA, Sanchez-Sotelo J, Sperling JW, Cofield RH. Unconstrained shoulder arthroplasty for treatment of proximal humerus nonunions . J Bone Joint Surg (Am) 2012;94(17):1610–7. doi: 10.2106/JBJS.J.01975. [DOI] [PubMed] [Google Scholar]
- Fevang BT, Lie SA, Havelin LI, Skredderstuen A, Furnes O. Risk factors for revision after shoulder arthroplasty: 1,825 shoulder arthroplasties from the Norwegian Arthroplasty Register . Acta Orthop. 2009;80(1):83–91. doi: 10.1080/17453670902805098. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Fevang BT, Lygre SH, Bertelsen G, Skredderstuen A, Havelin LI, Furnes O. Pain and function in eight hundred and fifty nine patients comparing shoulder hemiprostheses, resurfacing prostheses, reversed total and conventional total prostheses . Int Orthop. 2013;37(1):59–66. doi: 10.1007/s00264-012-1722-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Graves SE, Davidson D, Ingerson L, Ryan P, Griffith EC, McDermott BF, et al. The Australian Orthopaedic Association National Joint Replacement Registry . Med J Aust. 2004;180(S suppl):S31–4. doi: 10.5694/j.1326-5377.2004.tb05911.x. [DOI] [PubMed] [Google Scholar]
- Griffin JW, Novicoff WM, Browne JA, Brockmeier SF. Morbid obesity in total shoulder arthroplasty: risk, outcomes, and cost analysis . J Shoulder Elbow Surg. 2014;23(10):1444–8. doi: 10.1016/j.jse.2013.12.027. [DOI] [PubMed] [Google Scholar]
- Herberts P, Malchau H. Long-term registration has improved the quality of hip replacement: a review of the Swedish THR Register comparing 160,000 cases . Acta Orthop Scand. 2000;71(2):111–21. doi: 10.1080/000164700317413067. [DOI] [PubMed] [Google Scholar]
- Horan TC, Andrus M, Dudeck MA. CDC/NHSN surveillance definition of health care–associated infection and criteria for specific types of infections in the acute care setting . Am J Infect Control. 2008;36(5):309–32. doi: 10.1016/j.ajic.2008.03.002. [DOI] [PubMed] [Google Scholar]
- Jain NB, Higgins LD, Guller U, Pietrobon R, Katz JN. Trends in the epidemiology of total shoulder arthroplasty in the United States from 1990 . Arthritis Rheum. 2006;55(4):591–7. doi: 10.1002/art.22102. [DOI] [PubMed] [Google Scholar]
- Kaiser Permanente. “Share Our News, Views, and Moves.”. http://share.kaiserpermanente.org/article/fast-facts-about-kaiser-permanente/ 2014 Accessed June 11, 2014. [Google Scholar]
- Karter AJ, Ferrara A, Liu JY, Moffet HH, Ackerson LM, Selby JV. Ethnic disparities in diabetic complications in an insured population . JAMA. 2002;287(19):2519–27. doi: 10.1001/jama.287.19.2519. [DOI] [PubMed] [Google Scholar]
- Khatod M, Inacio M, Paxton EW, Bini SA, Namba RS, Burchette RJ, et al. Knee replacement: epidemiology, outcomes, and trends in Southern California: 17,080 replacements from 1995 . Acta Orthop. 2008;79(6):812–9. doi: 10.1080/17453670810016902. [DOI] [PubMed] [Google Scholar]
- Kim SH, Wise BL, Zhang Y, Szabo RM. Increasing incidence of shoulder arthroplasty in the United States . J Bone Joint Surg (Am) 2011;93(24):2249–54. doi: 10.2106/JBJS.J.01994. [DOI] [PubMed] [Google Scholar]
- Koebnick C, Langer-Gould AM, Gould MK, Chao CR, Iyer RL, Smith N, et al. Sociodemographic characteristics of members of a large, integraged health care system: comparison with US census bureau data . Perm J. 2012;16(3):37–41. doi: 10.7812/tpp/12-031. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Li X, Williams PN, Nguyen JT, Craig EV, Warren RF, Gulotta LV. Functional outcomes after total shoulder arthroplasty in obese patients. J Bone Joint Surg (Am) 2013;95(21):e160(1-8). doi: 10.2106/JBJS.L.01145. [DOI] [PubMed] [Google Scholar]
- Navarro RA, Inacio MC, Burke MF, Costouros JG, Yian EH. Risk of thromboembolism in shoulder arthroplasty: effect of implant type and traumatic indication . Clin Orthop Relat Res. 2013;471(5):1576–81. doi: 10.1007/s11999-013-2829-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Paxton EW, Namba RS, Maletis GB, Khatod M, Yue EJ, Davies M, et al. A prospective study of 80,000 total joint and 5000 anterior cruciate ligament reconstruction procedures in a community-based registry in the United States . J Bone Joint Surg (Am) 2010;92(Suppl 2):117–32. doi: 10.2106/JBJS.J.00807. [DOI] [PubMed] [Google Scholar]
- Paxton EW, Inacio MC, Kiley ML. The Kaiser Permanent implant registries: effect on patient safety, quality improvement, cost effectiveness, and research opportunities . Perm J. 2012;16(2):36–44. doi: 10.7812/tpp/12-008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Polk A, Rasmussen JV, Brorson S, Olsen BS. Reliability of patient-reported functional outcome in a joint replacement registry. A comparison of primary responders and non-responders in the Danish Shoulder Arthroplasty Registry . Acta Orthop. 2013;84(1):12–7. doi: 10.3109/17453674.2013.765622. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Rasmussen JV, Jakobsen J, Brorson S, Olsen BS. The Danish Arthroplasty Registry: clinical outcome and short-term survival of 2,137 primary shoulder replacements . Acta Orthop. 2012a;83(2):171–3. doi: 10.3109/17453674.2012.665327. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Rasmussen JV, Olsen BS, Fevang BT, Furnes O, Skytta ET, Rahme H, et al. A review of national shoulder and elbow replacement registries . J Shoulder Elbow Surg. 2012b;21(10):1328–35. doi: 10.1016/j.jse.2012.03.004. [DOI] [PubMed] [Google Scholar]
- Rasmussen JV, Polk A, Brorson S, Sorensen AK, Olsen BS. Patient-reported outcome and risk of revision after shoulder replacement for osteoarthritis 1,209 cases from the Danish Shoulder Arthroplasty Registry 2006 . Acta Orthop. 2014a;85(2):117–22. doi: 10.3109/17453674.2014.893497. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Rasmussen JV, Polk A, Sorensen AK, Olsen BS, Brorson S. Outcome, revision rate and indication for revision following resurfacing hemiarthroplasty for osteoarthritis of the shoulder: 837 operations reported to the Danish Shoulder Arthroplasty Registry . Bone Joint J. 2014b;96(4):519–25. doi: 10.1302/0301-620X.96B4.31850. [DOI] [PubMed] [Google Scholar]
- Richards J, Inacio MC, Beckett M, Navarro RA, Singh A, Dillon MT, et al. Patient and procedure-specific risk factors for deep infection after primary shoulder arthroplasty . Clin Orthop Relat Res. 2014;472(9):2809–15. doi: 10.1007/s11999-014-3696-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Trofa D, Rajaee SS, Smith EL. Nationwide trends in total shoulder arthroplasty and hemiarthroplasty for osteoarthritis . Am J Orthop. 2014;43(4):166–72. [PubMed] [Google Scholar]
- United States Census Bureau. “2010 Census Data”. http://www.census.gov/2010census/data/ 2015 Accessed January 5, 2015.
- Young SW, Zhu M, Walker CG, Poon PC. Comparison of functional outcomes of reverse shoulder arthroplasty with those of hemiarthroplasty in the treatment of cuff-tear arthropathy: a matched-pair analysis . J Bone Joint Surg (Am) 2013;95(10):910–5. doi: 10.2106/JBJS.L.00302. [DOI] [PubMed] [Google Scholar]