Total hip arthroplasties (THAs) and total knee arthroplasties (TKAs) are successful procedures, and a large proportion of patients who elect to have these procedures are satisfied with their outcomes.1 As the patient population in the United States continues to age, the demand for TKA and THA can be expected to increase.2 Despite the typically successful outcomes of total joint arthroplasty (TJA) procedures, complications and read-missions after TKA and THA can be disastrous for the patient, the provider, and the entire health care system. Although medical diagnoses represent a large proportion of readmissions following TJA, the most common reasons for readmission within 30 days of surgery are typically procedure related, most notably infection and dislocation.3
The “July effect” refers to the assumed increased risk of complications during July, when medical school graduates within the United States transition to residency programs. The actual existence of a July effect is controversial in the literature, both in orthopedics as well as other medical specialties.4–19 Several studies have reported an increased risk of medical errors, patient morbidity, and patient mortality in the months of July and August when residents are transitioning into their new roles for the year.4,9,10,15,17,20,21
Although these findings do not point to causation, they do show that the beginning of the academic year for residents within academic institutions can be a burden to patient care.4,9,10,15,17,20,21 Conversely, several studies have reported no evidence of a July effect and that the time of the year does not affect patient care outcomes.6,7,12–14,22–24 There is limited evidence of increased surgical time, complications, and cost in teaching hospitals vs nonteaching hospitals,24–26 but the current authors are unaware of any prior studies examining the role of teaching hospital status and the July effect for TJA procedures.
In the current study, the authors sought to determine whether evidence exists for the presence of a July effect among TJA procedures. They hypothesized that 30-day readmission rates following primary and revision THA and TKA would be higher for procedures in July compared with other months of the year. The specific aims of the study were to (1) determine whether readmission rates for TKA and THA are higher in certain months of the year; (2) evaluate the added cost of readmissions in months that have higher readmission rates; and (3) evaluate the re-admission rates at teaching vs nonteaching hospitals to assess the presence of a July effect in both facilities.
Materials and Methods
To investigate whether evidence exists for a July effect among TJA procedures, the authors used a large nationwide administrative claims-based database. The Nationwide Readmission Database (NRD) is part of the Healthcare Costs and Utilization Project. The NRD is created using the State Inpatient Database, with data obtained from 22 states, representing 51.2% of the total US resident population and 49.3% of all US hospitalizations. Unweighted, the NRD contains data from approximately 15 million discharges from US health care institutions per year; weighted, this number is approximately 35 million.27
All index primary and revision arthroplasty procedures were identified using the 2013 and 2014 NRD databases during a 22-month period using International Classification of Diseases, 9th Revision procedure codes 81.51 (primary THA), 81.54 (primary TKA), 00.70 (revision THA, both components), 00.71 (revision THA, acetabular component), 00.72 (revision THA, femoral component), 00.73 (revision THA, head and liner), 81.53 (revision THA, not otherwise specified), 00.80 (revision TKA, all components), 00.81 (revision TKA, tibial component), 00.82 (revision TKA, femoral component), 00.84 (revision TKA, tibial insert), and 81.55 (revision TKA, not otherwise specified). Cases were excluded if length of stay or admission day was missing, if the patient was younger than 18 years, if the patient died on the index admission, or if the patient was discharged in December (because the NRD does not capture read-missions across calendar years).
Readmissions for any reason within 30 days were identified, and outcome data for the first readmission were merged back to the original NRD data set to allow for analysis of readmission data by the index admission discharge month. In addition to the presence or absence of readmission for each index procedure, outcome data included index and readmissions costs (calculated from charges using the NRD hospital cost-to-charge ratio file), index and readmission length of stay, and days to readmission. A working data set including only those cases with an index arthroplasty procedure (using the International Classification of Diseases, 9th Revision procedure codes listed above) was created from the full merged NRD data set.
Descriptive statistics were determined from the full data set. Patient sex, age, procedure type, index and readmission length of stay, overall hospital costs, primary payer type, and hospital type were determined. The groups were compared using the Student's t test for continuous, normally distributed variables, and the chi-square test for categorical variables.
A weighted bivariate logistic regression model was created using readmission as the dependent variable and discharge month as the predictor variable. The chi-square test was used to compare proportions across all months and, in the case of significant differences in proportions, was followed with an analysis of means for proportions to compare each month's specific readmission rate to the overall mean, with an alpha set to 0.05. Modeling was performed for all patients and then controlled for hospital type (teaching vs non-teaching), as well as procedure type (primary vs revision, and revision subtype).
Mean annualized cost of readmission for primary TKA and THA to the US health care system was determined by multiplying the mean readmission rate by the annualized incidence of primary hip and knee replacement, and then multiplying this number by the average cost for a single readmission as previously reported in the literature.28 This cost was then subtracted from the month-specific annualized readmission cost to determine the annualized additional (lower) cost due to excessive (reduced) readmission rates. Statistical analysis was performed using SAS and JMP Pro, version 14.1 (SAS Institute, Cary, North Carolina).
A total of 1,193,034 index primary (1,107,657) and revision (85,377) arthroplasty procedures were identified (Table 1). Among all procedure types, 46,674 (3.9%) 30-day readmissions were observed. Among all procedures, an index procedure associated with a discharge in July resulted in the highest monthly read-mission rate of the year (4.2%), which was significantly higher than the mean annual readmission rate (P<.0001; Figure 1). The weighted readmission frequency and rate by primary procedure type and month were determined. For primary THA, a total of 275,255 procedures had 10,668 total 30-day readmissions. The highest 30-day readmission months for primary THA were associated with an index procedure occurring in July (4.1%) and September (4.1%), but were not significantly higher than the mean annual readmission rate. For primary TKA there were a total of 832,402 procedures with 30,173 total 30-day readmissions. The highest 30-day re-admission months for primary TKA were associated with an index procedure occurring in July (3.9%) and August (3.9%), which were significantly higher than the mean annual readmission rate (P<.05).
Weighted Readmission Frequency and Rate by Month
Monthly readmission rates for all primary total hip and knee arthroplasty procedures from 2013 to 2014. Shaded area represents 95% confidence interval (CI). Horizontal line represents mean readmission rate. Red dots indicate a statistical outlier (alpha less than 0.05); green dots fall within the expected decision limits, and are not statistically different from the overall proportion.
The annualized monthly cost variation was also calculated for procedure type and month based on weighted readmission frequency and rate (Table 2). The annualized cost variation for each month was greatest in July for both THAs and TKAs. The annualized cost variation was $4,907,223.61 for THAs in July and $13,695,963.76 for TKAs in July. In July alone, this number equated to a total of $18,603,187.37 in additional costs.
Weighted Readmission Frequency and Rate by Procedure Type and Month, Along With Calculated Annualized Monthly Cost Variation
When controlling for teaching hospital status, the highest readmission rate occurred if the index procedure occurred at a teaching hospital in May (4.1%, P<.0001; Figure 2) and at a nonteaching hospital in July (4.5%, P<.0001; Figure 3).
Monthly readmission rates for all primary total hip and knee arthroplasty procedures performed at teaching institutions from 2013 to 2014. Shaded area represents 95% confidence interval (CI). Horizontal line represents mean readmission rate. Red dots indicate a statistical outlier (alpha less than 0.05); green dots fall within the expected decision limits, and are not statistically different from the overall proportion.
Monthly readmission rates for all primary total hip and knee arthroplasty procedures performed at nonteaching institutions from 2013 to 2014. Shaded area represents 95% confidence interval (CI). Horizontal line represents mean read-mission rate. Red dots indicate a statistical outlier (alpha less than 0.05); green dots fall within the expected decision limits, and are not statistically different from the overall proportion.
The July effect refers to the assumed increase in complication rates during July, when medical students are transitioning to residency programs within the United States and are assuming new roles and responsibilities as they advance in their training. The presence of the July effect across several subspecialties has been described, and its effects and existence have been debated.4–19 The current study is the first to provide evidence of a July effect for TKA and THA procedures, which equates to an estimated $18.6 million annually in additional cost to the health care system during July. Unique to this study is the finding that this effect seems to be predominantly driven by hospitals designated as nonteaching. Conversely, teaching institutions appear to have a statistically average readmission rate in July, which gradually decreases throughout the year and reaches its nadir in January, but then increases precipitously until it reaches its peak in May. This “May effect” has not previously been described.
The orthopedic and nonorthopedic literature demonstrate contradicting evidence regarding the July effect.6,12–17,21,23,24,26,29 A pediatric trainee study by Shah et al5 described an increase in reported medical errors in a teaching hospital during July, but no increase in adverse patient outcomes due to those errors. Similarly, Inaba et al10 showed an increase in reported errors at the beginning of the academic year, but they did not impact mortality.
The medical literature has shown increased mortality, fatal medication errors, longer length of stay, and increased costs in teaching hospitals in July.4,20,30 One study by Varma et al31 in the gynecologic literature examined 30-day readmission rates, similar to the current study, but did not find an increase in readmissions in July.
In the orthopedic literature, Bohl et al6 reviewed more than 21,000 THAs and TKAs using the National Surgical Quality Improvement Program (NSQIP) database and were unable to find evidence for a July effect. Unlike the data source used in the current study, the NSQIP does not provide institutional data or teaching hospital status, which could explain the discrepancy between their findings and the current findings. Conversely, Anderson et al,15 using the National Inpatient Sample, studied elderly patients with hip fractures and demonstrated a 12% greater relative risk of mortality among elderly patients with hip fractures in July and August.
Although several studies have debated the existence of a July effect among teaching hospitals, this is the first study to find a higher 30-day readmission rate at a nonteaching hospital if the index procedure occurred in July. Shah et al5 argued that teaching hospitals have an increase in reported medical errors in July, but an absence of increased adverse events due to hypervigilance of the staff to the new medical trainees. This may explain the protective effect seen in the current study among teaching hospitals that may be absent in July in nonteaching hospitals. Nonteaching hospitals experience work-force turnover during summer months, as do teaching institutions, because residents, fellows, and other professional graduates are transitioning to new roles and responsibilities.
Documentation provided by Healthcare Costs and Utilization Project defines a teaching hospital as one with one or more Accreditation Council for Graduate Medical Education (ACGME)–approved residency programs, one that is a member of the Council of Teaching Hospitals (COTH), or one that has a ratio of full-time equivalent interns and residents to beds of 0.25 or higher.27 With this limited definition, it is reasonable to assume that even nonteaching hospitals will accommodate a large number of new and transitioning residents and other trainees. Perhaps the lack of heightened awareness of “senior” staff over the trainees creates potential for increased errors in July.
Although a heightened awareness of the ancillary and senior staff in July helps to explain the lack of a July effect in teaching hospitals, it does not account for the increase in admissions given an index procedure occurring in May at these institutions. The authors hypothesize that there is a paradoxical decrease in vigilance at the end of the year with a concomitant decrease in resident attention to detail as other important deadlines approach and confidence in their training is at its peak. Upper-level residents in particular could be shifting their attention to board examinations, fellowship training, and job searches. In addition, there is the possibility of intensifying feelings of burnout for residents of all years as the academic year progresses. This hypothesis is further strengthened by the shape of the monthly readmission rates, which slowly decrease, reaching a nadir in January, and then increasing rapidly again over the following months as the academic year comes to an end.
There are notable limitations to this study. This study used administrative claims–based data that contains a large amount of retrospectively collected information dependent on the accuracy of coding. If coding is inaccurate, this would undermine the statistical analysis and conclusions of the study. Another limitation is that these data do not contain information related to resident involvement in each particular case. Because participation level will vary across institutions, attending physicians, residents, and cases, it is difficult to generalize the findings of this study to each individual teaching or non-teaching institution.
This study provides evidence that a July effect appears to exist for TJA procedures, particularly when the index procedure occurs at a nonteaching institution, resulting in a significant cost burden to the health care system. In addition, a separate but related May effect appears to exist at teaching institutions, a finding that has never been previously reported, to the authors' knowledge. Future research is needed to determine the causes of and possible solutions to these costly problems.
- Pollock M, Somerville L, Firth A, Lanting B. Outpatient total hip arthroplasty, total knee arthroplasty, and unicompartmental knee arthroplasty: a systematic review of the literature. JBJS Rev. 2016;4(12):01874474–201612000-00004. doi:10.2106/JBJS.RVW.16.00002 [CrossRef] PMID:28060788
- Kurtz S, Ong K, Lau E, Mowat F, Halpern M. Projections of primary and revision hip and knee arthroplasty in the United States from 2005 to 2030. J Bone Joint Surg Am. 2007;89(4):780–785. doi:10.2106/00004623-200704000-00012 [CrossRef] PMID:17403800
- Schairer WW, Vail TP, Bozic KJ. What are the rates and causes of hospital readmission after total knee arthroplasty?Clin Orthop Relat Res.2014;472(1):181–187. doi:10.1007/s11999-013-3030-7 [CrossRef] PMID:23645339
- Young JQ, Ranji SR, Wachter RM, Lee CM, Niehaus B, Auerbach AD. “July effect”: impact of the academic year-end changeover on patient outcomes. A systematic review. Ann Intern Med. 2011;155(5):309–315. doi:10.7326/0003-4819-155-5-201109060-00354 [CrossRef] PMID:21747093
- Shah AY, Abreo A, Akar-Ghibril N, Cady RF, Shah RK. Is the “July effect” real? Pediatric trainee reported medical errors and adverse events. Pediatr Qual Saf. 2017;2(2):e018. doi:10.1097/pq9.0000000000000018 [CrossRef] PMID:30229156
- Bohl DD, Fu MC, Golinvaux NS, Basques BA, Gruskay JA, Grauer JN. The “July effect” in primary total hip and knee arthroplasty: analysis of 21,434 cases from the ACS-NSQIP database. J Arthroplasty. 2014;29(7):1332–1338. doi:10.1016/j.arth.2014.02.008 [CrossRef] PMID:24631125
- Banco SP, Vaccaro AR, Blam O, et al. Spine infections: variations in incidence during the academic year. Spine. 2002;27(9):962–965. doi:10.1097/00007632-200205010-00016 [CrossRef] PMID:11979171
- Haller G, Myles PS, Taffé P, Perneger TV, Wu CL. Rate of undesirable events at beginning of academic year: retrospective cohort study. BMJ. 2009;339(Oct13 1):b3974. doi:10.1136/bmj.b3974 [CrossRef] PMID:19826176
- Englesbe MJ, Pelletier SJ, Magee JC, et al. Seasonal variation in surgical outcomes as measured by the American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP). Ann Surg. 2007;246(3):456–462. doi:10.1097/SLA.0b013e31814855f2 [CrossRef] PMID:17717449
- Inaba K, Recinos G, Teixeira PGR, et al. Complications and death at the start of the new academic year: is there a July phenomenon?J Trauma.2010;68(1):19–22. doi:10.1097/TA.0b013e3181b88dfe [CrossRef] PMID:20065752
- Ford AA, Bateman BT, Simpson LL, Ratan RB. Nationwide data confirms absence of ‘July phenomenon’ in obstetrics: it's safe to deliver in July. J Perinatol. 2007;27(2):73–76. doi:10.1038/sj.jp.7211635 [CrossRef] PMID:17262037
- Edelstein AI, Lovecchio FC, Saha S, Hsu WK, Kim JYS. Impact of resident involvement on orthopaedic surgery outcomes: an analysis of 30,628 patients from the American College of Surgeons National Surgical Quality Improvement Program Database. J Bone Joint Surg Am. 2014;96(15):e131. doi:10.2106/JBJS.M.00660 [CrossRef] PMID:25100784
- Haughom BD, Schairer WW, Hellman MD, Yi PH, Levine BR. Does resident involvement impact post-operative complications following primary total knee arthroplasty? An analysis of 24,529 cases. J Arthroplasty. 2014;29(7):1468–1472.e2. doi:10.1016/j.arth.2014.02.036 [CrossRef] PMID:24726182
- Cvetanovich GL, Schairer WW, Haughom BD, Nicholson GP, Romeo AA. Does resident involvement have an impact on postoperative complications after total shoulder arthroplasty? An analysis of 1382 cases. J Shoulder Elbow Surg. 2015;24(10):1567–1573. doi:10.1016/j.jse.2015.03.023 [CrossRef] PMID:25953488
- Anderson KL, Koval KJ, Spratt KF. Hip fracture outcome: is there a “July effect”?Am J Orthop (Belle Mead NJ).2009;38(12):606–611. PMID:20145785
- Bagsby DT, Loder RT, Myung K. Operative intervention of supracondylar humerus fractures more complicated in July: analysis of the July effect. J Pediatr Orthop. 2017;37(4):254–257. doi:10.1097/BPO.0000000000000618 [CrossRef] PMID:26280293
- Pugely AJ, Gao Y, Martin CT, Callagh JJ, Weinstein SL, Marsh JL. The effect of resident participation on short-term outcomes after orthopaedic surgery. Clin Orthop Relat Res. 2014;472(7):2290–2300. doi:10.1007/s11999-014-3567-0 [CrossRef] PMID:24658902
- Smith ER, Butler WE, Barker FG II, . Is there a “July phenomenon” in pediatric neurosurgery at teaching hospitals?J Neurosurg. 2006;105(3)(suppl):169–176. doi:10.3171/ped.2006.105.3.169 [CrossRef] PMID:16970228
- Alshekhlee A, Walbert T, DeGeorgia M, Preston DC, Furlan AJ. The impact of Accreditation Council for Graduate Medical Education duty hours, the July phenomenon, and hospital teaching status on stroke outcomes. J Stroke Cerebrovasc Dis. 2009;18(3):232–238. doi:10.1016/j.jstrokecerebrovasdis.2008.10.006 [CrossRef] PMID:19426896
- Phillips DP, Barker GEC. A July spike in fatal medication errors: a possible effect of new medical residents. J Gen Intern Med. 2010;25(8):774–779. doi:10.1007/s11606-010-1356-3 [CrossRef] PMID:20512532
- Schoenfeld AJ, Serrano JA, Waterman BR, Bader JO, Belmont PJ Jr, . The impact of resident involvement on post-operative morbidity and mortality following orthopaedic procedures: a study of 43,343 cases. Arch Orthop Trauma Surg. 2013;133(11):1483–1491. doi:10.1007/s00402-013-1841-3 [CrossRef] PMID:23995548
- Barry WA, Rosenthal GE. Is there a July phenomenon? The effect of July admission on intensive care mortality and length of stay in teaching hospitals. J Gen Intern Med. 2003;18(8):639–645. doi:10.1046/j.1525-1497.2003.20605.x [CrossRef] PMID:12911646
- Rao AJ, Bohl DD, Frank RM, Cvetanovich GL, Nicholson GP, Romeo AA. The “July effect” in total shoulder arthroplasty. J Shoulder Elbow Surg. 2017;26(3):e59–e64. doi:10.1016/j.jse.2016.09.043 [CrossRef] PMID:27914844
- Woolson ST, Kang MN. A comparison of the results of total hip and knee arthroplasty performed on a teaching service or a private practice service. J Bone Joint Surg Am. 2007;89(3):601–607. doi:10.2106/00004623-200703000-00017 [CrossRef] PMID:17332109
- Farnworth LR, Lemay DE, Wooldridge T, et al. A comparison of operative times in arthroscopic ACL reconstruction between orthopaedic faculty and residents: the financial impact of orthopaedic surgical training in the operating room. Iowa Orthop J. 2001;21:31–35. PMID:11813948
- Lavernia CJ, Sierra RJ, Hernandez RA. The cost of teaching total knee arthroplasty surgery to orthopaedic surgery residents. Clin Orthop Relat Res. 2000;380:99–107. doi:10.1097/00003086-200011000-00014 [CrossRef] PMID:11064979
- NRD Database Documentation. https://www.hcup-us.ahrq.gov/db/nation/nrd/nrddbdocumentation.jsp. Accessed November 29, 2018.
- Kurtz SM, Lau EC, Ong KL, Adler EM, Kolisek FR, Manley MT. Which clinical and patient factors influence the national economic burden of hospital readmissions after total joint arthroplasty?Clin Orthop Relat Res. 2017;475(12):2926–2937. doi:10.1007/s11999-017-5244-6 [CrossRef] PMID:28108823
- Tobert DG, Menendez ME, Ring DC, Chen NC. The “July effect” on shoulder arthroplasty: are complication rates higher at the beginning of the academic year?Arch Bone Joint Surg.2018;6(4):277–281. PMID:30175174
- Mims LD, Porter M, Simpson KN, Carek PJ. The “July effect”: a look at July medical admissions in teaching hospitals. J Am Board Fam Med. 2017;30(2):189–195. doi:10.3122/jabfm.2017.02.160214 [CrossRef] PMID:28379825
- Varma S, Mehta A, Hutfless S, Stone RL, Wethington SL, Fader AN. Is there evidence of a July effect among patients undergoing hysterectomy surgery?Am J Obstet Gynecol. 2018;219(2):176.e1–176.e9. doi:10.1016/j.ajog.2018.05.033 [CrossRef] PMID:29870735
Weighted Readmission Frequency and Rate by Month
Weighted Readmission Frequency and Rate by Procedure Type and Month, Along With Calculated Annualized Monthly Cost Variationa
|Month||Primary THA (n=275,255)||Primary TKA (n=832,402)||Combined Annualized Cost Variation|
|Frequency||%||THA Annualized Cost Variation||Frequency||%||TKA Annualized Cost Variation|