Healthcare-Associated Infections and Length of Hospital Stay in the Medicare Population

Increased length of stay following total joint arthroplasty based on insurance type

BACKGROUND

Increased length of stay after total joint arthroplasty has been shown to be a risk factor for peri-operative complications. The purpose of this study was to determine if Medicaid insurance would be a risk factor for increased length of stay after total joint arthroplasty.

METHODS

We retrospectively reviewed a single surgeon's practice of 428 total hip and total knee arthroplasties who had insurance status of Medicaid, Medicare, Private or none. After exclusion criteria there were 400 patients. Patients with insurance status of Medicaid, Medicare or Private were then compared based on length of stay ≤ 2 days and length of stay > 2 days and then further analyzed using demographic, operative data, and total length of stay.

RESULTS

Medicaid patients had an increased length of stay compared to patients with Medicare or Private insurance [1.98 days versus 1.73 days, p = .037, 95% confidence intervals (1.78-2.18) and (1.61-1.85), respectively]. The greatest predictor of a less than two-night stay post-operatively was private insurance status (p = 0.001). Medicaid patients had a higher incidence of prescribed narcotic use pre-operatively (p = 0.013). Although not significant, a trend was noted in the Medicaid population with higher incidence of smoking (p = 0.094) and illicit drug abuse (p = 0.099) pre-operatively in this sample subset.

CONCLUSIONS

Patients with Medicaid insurance undergoing total joint arthroplasty have increased length of stay compared to patients with Medicare or Private insurance and have higher incidence of pre-operative narcotic use.

Use of Lean Healthcare to Improve Hospital Throughput and Reduce LOS

Supplemental Digital Content is available in the text.

Improving the discharge process is an area of focus throughout healthcare organizations. Capacity constraints, efficiency improvement, patient safety, and quality care are driving forces for many discharge process workgroups.

Impact of healthcare-associated infection on length of stay

BACKGROUND

Increased length of stay (LOS) for patients is an important measure of the burden of healthcare-associated infection (HAI).

AIM

To estimate the excess LOS attributable to HAI.

METHODS

This was a one-year prospective incidence study of HAI observed in one teaching hospital and one general hospital in NHS Scotland as part of the Evaluation of Cost of Nosocomial Infection (ECONI) study. All adult inpatients with an overnight stay were included. HAI was diagnosed using European Centres for Disease Prevention and Control definitions. A multi-state model was used to account for the time-varying nature of HAI and the competing risks of death and discharge.

FINDINGS

The excess LOS attributable to HAI was 7.8 days (95% confidence interval (CI): 5.7-9.9). Median LOS for HAI patients was 30 days and for non-HAI patients was 3 days. Using a simple comparison of duration of hospital stay for HAI cases and non-cases would overestimate the excess LOS by 3.5 times (27 days compared with 7.8 days). The greatest impact on LOS was due to pneumonia (16.3 days; 95% CI: 7.5-25.2), bloodstream infections (11.4 days; 5.8-17.0) and surgical site infection (SSI) (9.8 days; 4.5-15.0). It is estimated that 58,000 bed-days are occupied due to HAI annually.

CONCLUSION

A reduction of 10% in HAI incidence could make 5800 bed-days available. These could be used to treat 1706 elective patients in Scotland annually and help reduce the number of patients awaiting planned treatment. This study has important implications for investment decisions in infection prevention and control interventions locally, nationally, and internationally.

A Simplified Cost-Utility Analysis of Inpatient Flap Monitoring after Microsurgical Breast Reconstruction and Implications for Hospital Length of Stay

BACKGROUND

The number of free flap take-backs and successful salvages following microsurgical breast reconstruction decreases as time from surgery increases. As a result, the cost of extended inpatient monitoring to achieve a successful flap salvage rises rapidly with each postoperative day. This study introduces a simplified cost-utility model of inpatient flap monitoring and identifies when cost-utility exceeds the thresholds established for other medical treatments.

METHODS

A retrospective review of a prospectively maintained database was performed of patients who underwent microsurgical breast reconstruction to identify flap take-back and salvage rates by postoperative day. The number of patients and flaps that needed to be kept on an inpatient basis each day for monitoring to salvage a single failing flap was determined. Quality-of-life measures and incremental cost-effectiveness ratios for inpatient flap monitoring following microsurgical breast reconstruction were calculated and plotted against a $100,000/quality-adjusted life-year threshold.

RESULTS

A total of 1813 patients (2847 flaps) were included. Overall flap take-back and salvage rates were 2.4 percent and 52.3 percent, respectively. Of the flaps taken back, the daily take-back and salvage rates were 56.8 and 60.0 percent (postoperative day 0 to 1), 13.6 and 83.3 percent (postoperative day 2), 11.4 and 40.0 percent (postoperative day 3), 9.1 and 25.0 percent (postoperative day 4), and 9.1 and 0.0 percent (>postoperative day 4), respectively. To salvage a single failing flap each day, the number of flaps that needed to be monitored were 121 (postoperative day 0 to 1), 363 (postoperative day 2), 907 (postoperative day 3), 1813 (postoperative day 4), and innumerable for days beyond postoperative day 4. The incremental cost-effectiveness ratio of inpatient flap monitoring begins to exceed a willingness-to-pay threshold of $100,000/quality-adjusted life-year by postoperative day 2.

CONCLUSION

The health care cost associated with inpatient flap monitoring following microsurgical breast reconstruction begins to rise rapidly after postoperative day 2.

Estimating excess length of stay due to healthcare-associated infections: a systematic review and meta-analysis of statistical methodology

BACKGROUND

Healthcare-associated infection (HCAI) affects millions of patients worldwide. HCAI is associated with increased healthcare costs, owing primarily to increased hospital length of stay (LOS) but calculating these costs is complicated due to time-dependent bias. Accurate estimation of excess LOS due to HCAI is essential to ensure that we invest in cost-effective infection prevention and control (IPC) measures.

AIM

To identify and review the main statistical methods that have been employed to estimate differential LOS between patients with, and without, HCAI; to highlight and discuss potential biases of all statistical approaches.

METHODS

A systematic review from 1997 to April 2017 was conducted in PubMed, CINAHL, ProQuest and EconLit databases. Studies were quality-assessed using an adapted Newcastle-Ottawa Scale (NOS). Methods were categorized as time-fixed or time-varying, with the former exhibiting time-dependent bias. Two examples of meta-analysis were used to illustrate how estimates of excess LOS differ between different studies.

FINDINGS

Ninety-two studies with estimates on excess LOS were identified. The majority of articles employed time-fixed methods (75%). Studies using time-varying methods are of higher quality according to NOS. Studies using time-fixed methods overestimate additional LOS attributable to HCAI. Undertaking meta-analysis is challenging due to a variety of study designs and reporting styles. Study differences are further magnified by heterogeneous populations, case definitions, causative organisms, and susceptibilities.

CONCLUSION

Methodologies have evolved over the last 20 years but there is still a significant body of evidence reliant upon time-fixed methods. Robust estimates are required to inform investment in cost-effective IPC interventions.

The impact of HIV diagnosis on length of hospital stay in New York City, NY, USA

While hospitalizations among people living with human immunodeficiency virus (PLWH) have been elevated in the past compared to their uninfected counterparts, the introduction of antiretroviral therapy (ART) has resulted in great strides in controlling symptomatic infection. However, research largely overlooks important differences among HIV-infected individuals, primarily PLWH who are symptomatic versus those who are asymptomatic. We conducted a retrospective study assessing the length of hospital stay among 717,237 admissions from three hospitals in the New York City area. Using zero-truncated negative binomial regression we documented trends in length of hospital stay among individuals who are HIV positive (with symptoms versus those without symptoms) compared to HIV-negative patients over nine consecutive years, from 2006 to 2014. Approximately 0.85% of the admissions were infected with asymptomatic HIV (n = 6,131), while 1.43% of admissions were infected with symptomatic HIV (n = 10,271). The length of stay (LOS) among symptomatic HIV-infected admissions was 32.0% (95% CI: 29.7%-34.2%) longer than LOS in the general admissions. The mean LOS dropped about 1.5% (95% CI: 1.5%-1.6%) per year in the study sample. The LOS in inpatients with asymptomatic HIV had the same LOS as the general inpatient population. Our findings highlight the need for comprehensive strategies to reduce length of hospitalization among HIV-infected individuals.

Are medical outliers associated with worse patient outcomes? A retrospective study within a regional NHS hospital using routine data

OBJECTIVE

To explore the quality and safety of patients' healthcare provision by identifying whether being a medical outlier is associated with worse patient outcomes. A medical outlier is a hospital inpatient who is classified as a medical patient for an episode within a spell of care and has at least one non-medical ward placement within that spell.

DATA SOURCES

Secondary data from the Patient Administration System of a district general hospital were provided for the financial years 2013/2014-2015/2016. The data included 71 038 medical patient spells for the 3-year period.

STUDY DESIGN

This research was based on a retrospective, cross-sectional observational study design. Multivariate logistic regression and zero-truncated negative binomial regression were used to explore patient outcomes (in-hospital mortality, 30-day mortality, readmissions and length of stay (LOS)) while adjusting for several confounding factors.

PRINCIPAL FINDINGS

Univariate analysis indicated that an outlying medical in-hospital patient has higher odds for readmission, double the odds of staying longer in the hospital but no significant difference in the odds of in-hospital and 30-day mortality. Multivariable analysis indicates that being a medical outlier does not affect mortality outcomes or readmission, but it does prolong LOS in the hospital.

CONCLUSIONS

After adjusting for other factors, medical outliers are associated with an increased LOS while mortality or readmissions are not worse than patients treated in appropriate specialty wards. This is in line with existing but limited literature that such patients experience worse patient outcomes. Hospitals may need to revisit their policies regarding outlying patients as increased LOS is associated with an increased likelihood of harm events, worse quality of care and increased healthcare costs.

Barriers in Transitioning Patients With Severe Obesity From Hospitals to Nursing Homes

This cross-sectional, descriptive study explored perspectives of discharge planners regarding transitions of hospitalized patients who are severely obese seeking discharge to a nursing home. Attention has been focused on care transitions regarding high hospital readmission rates, yet specific needs of patients who are severely obese have been largely overlooked. Ninety-seven (response rate 39.8%) discharge planners returned surveys addressing frequency of, and issues encountered when, arranging placements. Community and hospital characteristics were also collected. One third of the respondents from Pennsylvania and Arkansas reported inability to transfer patients; barriers included reimbursement, staffing, and equipment. Respondents perceiving nursing homes to have equipment concerns were nearly 7 times more likely to report patient size as a barrier ( p = .001). Given increasing obesity rates, health care delivery systems must be prepared to provide necessary resources and all levels of care, including transitions for hospitalized patients who are severely obese needing nursing home care post-discharge.

Percutaneous freezing of sensory nerves prior to total knee arthroplasty

BACKGROUND

Total knee arthroplasty (TKA) is a common procedure resulting in significant post-operative pain. Percutaneous cryoneurolysis targeting the infrapatellar branch of the saphenous nerve and anterior femoral cutaneous nerve could relieve post-operative knee pain by temporarily blocking sensory nerve conduction.

METHODS

A retrospective chart review of 100 patients who underwent TKA was conducted to assess the value of adding perioperative cryoneurolysis to a multimodal pain management program. The treatment group consisted of the first 50 patients consecutively treated after the practice introduced perioperative (five days prior to surgery) cryoneurolysis as part of its standard pain management protocol. The control group consisted of the 50 patients treated before cryoneurolysis was introduced. Outcomes included hospital length of stay (LOS), post-operative opioid requirements, and patient-reported outcomes of pain and function.

RESULTS

A significantly lower proportion of patients in the treatment group had a LOS of ≥2days compared with the control group (6% vs. 67%, p<0.0001) and required 45% less opioids during the first 12weeks after surgery. The treatment group reported a statistically significant reduction in symptoms at the six- and 12-week follow-up compared with the control group and within-group significant reductions in pain intensity and pain interference at two- and six-week follow-up, respectively.

CONCLUSIONS

Perioperative cryoneurolysis in combination with multimodal pain management may significantly improve outcomes in patients undergoing TKA. Promising results from this preliminary retrospective study warrant further investigation of this novel treatment in prospective, randomized trials.

LEVEL OF EVIDENCE

III.

Do Serially Recorded Prognostic Scores Predict Outcome Better Than One-Time Recorded Score on Admission? A Prospective Study in Adult Intensive Care Patients

OBJECTIVES

The prognosticating ability of one-time recorded Acute Physiology and Chronic Health Evaluation (APACHE) IV score was compared with serially recorded Mortality Prediction Model (MPM) II scores.

DESIGN AND METHODS

A prospective observational study was conducted for a period of 6 months. Acute Physiology and Chronic Health Evaluation IV score was recorded during the first day on intensive care unit (ICU) admission. Mortality Prediction Model II was recorded on admission, 24, 48, and 72 hours. Predicted mortality was compared with observed mortality. The systems were calibrated and tested for discriminant functions.

RESULTS

One hundred and fifty patients were studied. The observed mortality was 21.3%. The mean predicted hospital mortality by APACHE IV was 20.6%. The mean predicted hospital mortality rate by serial MPM II measurements was 27.7%, 24.3%, 25.5%, and 25.8%. The area under the receiver-operating characteristic curve was 0.87 for APACHE IV and 0.82, 0.84, 0.85, and 0.89 for MPM II series. Both systems calibrated well with similar degree of goodness of fit.

CONCLUSION

Acute Physiology and Chronic Health Evaluation IV on admission predicted hospital mortality better than serially recorded MPM, which overestimated mortality. Also, APACHE IV had a slightly better discrimination compared to MPM II on admission. One-time recording of APACHE IV on admission may be sufficient for prognostication of ICU patients rather than serial MPM scores.

Impact of Hospital Population Case-Mix, Including Poverty, on Hospital All-Cause and Infection-Related 30-Day Readmission Rates

BACKGROUND

Reducing hospital readmissions, including preventable healthcare-associated infections, is a national priority. The proportion of readmissions due to infections is not well-understood. Better understanding of hospital risk factors for readmissions and infection-related readmissions may help optimize interventions to prevent readmissions.

METHODS

Retrospective cohort study of California acute care hospitals and their patient populations discharged between 2009 and 2011. Demographics, comorbidities, and socioeconomic status were entered into a hierarchical generalized linear mixed model predicting all-cause and infection-related readmissions. Crude verses adjusted hospital rankings were compared using Cohen's kappa.

RESULTS

We assessed 30-day readmission rates from 323 hospitals, accounting for 213 879 194 post-discharge person-days of follow-up. Infection-related readmissions represented 28% of all readmissions and were associated with discharging a high proportion of patients to skilled nursing facilities. Hospitals serving populations with high proportions of males, comorbidities, prolonged length of stay, and populations living in a federal poverty area, had higher all-cause and infection-related readmission rates. Academic hospitals had higher all-cause and infection-related readmission rates (odds ratio 1.24 and 1.15, respectively). When comparing adjusted vs crude hospital rankings for infection-related readmission rates, adjustment revealed 31% of hospitals changed performance category for infection-related readmissions.

CONCLUSIONS

Infection-related readmissions accounted for nearly 30% of all-cause readmissions. High hospital infection-related readmissions were associated with serving a high proportion of patients with comorbidities, long lengths of stay, discharge to skilled nursing facility, and those living in federal poverty areas. Preventability of these infections needs to be assessed.

The Timed Up and Go Test does not predict length of stay on an acute geriatric ward

This study aimed to determine whether the admission Timed Up and Go Test (TUG) predicted the length of stay of patients in an acute geriatric ward. Consecutive patients were quasi-randomly allocated to either a model development sample or a model validation sample. Multivariate Cox proportional hazards regression was used to model length of stay. Variables considered for inclusion in the development model were risk factors for length of stay reported in the literature and univariate predictors from our dataset (p < 0.05). Variables selected for use in the development sample were then tested in the validation sample. Of 2463 patients of mean age 82.1 years, 932 (37.8%) were able to complete the TUG. Despite a significant, though weak, relationship between the length of stay and the TUG time (Spearman coefficient 0.18, p < 0.001), no time clearly identified patients with longer length of stay. Patients unable to complete the TUG had a median length of stay of 11 days (IQR 7 to 18), 40% longer than those able to complete the TUG (median 8 days, IQR 8 to 12, p < 0.001). Other significant (p < 0.05) predictors of length of stay in both samples were number of active medical diagnoses, referral from the emergency department, in-patient fall, and diagnosis of ulcer or infection. The admission TUG time should not be used to screen for patients likely to have longer lengths of stay. The value of the TUG lies in determining the patient's ability to complete it, rather than the time taken.