Pre-Operative Predictors for Discharge to Post-Acute Care Facilities After Total Knee Arthroplasty.

BACKGROUND: Joint replacement surgery is in increasing demand and is the most common inpatient surgery for Medicare beneficiaries. The venue for post-operative rehabilitation, including early outpatient therapy after surgery, influences recovery and quality of life. As part of a comprehensive total joint program at Kaiser Permanente Colorado, we developed and validated a predictive model to anticipate and plan the disposition for rehabilitation of our patients after total knee arthroplasty (TKA). METHODS: We analyzed data for TKA patients who completed a pre-operative Total Knee Risk Assessment in 2017 (the model development cohort) or during the first 6 months of 2018 (the model validation cohort). The Total Knee Risk Assessment, which is used to guide disposition for rehabilitation, included questions in mobility, social, and environment domains. Multivariable logistic regression was used to predict discharge to post-acute care facilities (PACFs) (ie, skilled nursing facilities or acute rehabilitation centers). RESULTS: Data for a total of 1481 and 631 patients who underwent TKA were analyzed in the development and validation cohorts, respectively. Ninety-three patients (6.3%) in the development cohort and 22 patients (3.5%) in the validation cohort were discharged to PACFs. Eight risk factors for discharge to PACFs were included in the final multivariable model. Patients with a diagnosis of neurological disorder and with a mobility/balance issue had the greatest chance of discharge to PACFs. CONCLUSION: This validated predictive model for discharge disposition following TKA may be used as a tool in shared decision-making and discharge planning for patients undergoing TKA.

Development and Validation of a Model for Predicting Rehabilitation Care Location Among Patients Discharged Home After Total Knee Arthroplasty.

BACKGROUND: Demand for joint replacement is increasing, with many patients receiving postsurgical physical therapy (PT) in non-inpatient settings. Clinicians need a reliable tool to guide decisions about the appropriate PT setting for patients discharged home after surgery. We developed and validated a model to predict PT location for patients in our health system discharged home after total knee arthroplasty. METHODS: We analyzed data for patients who completed a preoperative total knee risk assessment in 2017 (model development cohort) or during the first 6 months of 2018 (model validation cohort). The initial total knee risk assessment, to guide rehabilitation disposition, included 28 variables in mobility, social, and environment domains, and on patient demographics and comorbidities. Multivariable logistic regression was used to identify factors that best predict discharge to home health service (HHS) vs home with outpatient PT. Model performance was assessed by standard criteria. RESULTS: The development cohort included 259 patients (19%) discharged to HHS and 1129 patients (81%) discharged to home with outpatient PT. The validation cohort included 609 patients, with 91 (15%) discharged to HHS. The final model included age, gender, motivation for outpatient PT, and reliable transportation. Patients without motivation for outpatient PT had the highest probability of discharge to HHS, followed by those without reliable transportation. Model performance was excellent in the development and validation cohort, with c-statistics of 0.91 and 0.86, respectively. CONCLUSION: We developed and validated a predictive model for total knee arthroplasty PT discharge location. This model includes 4 variables with accurate prediction to guide patient-clinician preoperative decision making.

Use of Internet Search Data to Monitor Rotavirus Vaccine Impact in the United States, United Kingdom, and Mexico.

BACKGROUND: Previous studies have found a strong correlation between internet search and public health surveillance data. Less is known about how search data respond to public health interventions, such as vaccination, and the consistency of responses in different countries. In this study, we aimed to study the correlation between internet searches for "rotavirus" and rotavirus disease activity in the United States, United Kingdom, and Mexico before and after introduction of rotavirus vaccine. METHODS: We compared time series of internet searches for "rotavirus" from Google Trends with rotavirus laboratory reports from the United States and United Kingdom and with hospitalizations for acute gastroenteritis in the United States and Mexico. Using time and location parameters, Google quantifies an internet query share (IQS) to measure the relative search volume for specific terms. We analyzed the correlation between IQS and laboratory and hospitalization data before and after national vaccine introductions. RESULTS: There was a strong positive correlation between the rotavirus IQS and laboratory reports in the United States (R2 = 0.79) and United Kingdom (R2 = 0.60) and between the rotavirus IQS and acute gastroenteritis hospitalizations in the United States (R2 = 0.87) and Mexico (R2 = 0.69) (P < .0001 for all correlations). The correlations were stronger in the prevaccine period than in the postvaccine period. After vaccine introduction, the mean rotavirus IQS decreased by 40% (95% confidence interval [CI], 25%-55%) in the United States and by 70% (95% CI, 55%-86%) in Mexico. In the United Kingdom, there was a loss of seasonal variation after vaccine introduction. CONCLUSIONS: Rotavirus internet search data trends mirrored national rotavirus laboratory trends in the United States and United Kingdom and gastroenteritis-hospitalization data in the United States and Mexico; lower correlations were found after rotavirus vaccine introduction.

Trends in lower respiratory tract infection hospitalizations among American Indian/Alaska Native children and the general US child population.

OBJECTIVE: To describe trends in the rate of hospitalization for lower respiratory tract infection (LRTI) among American Indian/Alaska Native (AI/AN) children and the general US population of children aged <5 years. STUDY DESIGN: This was a retrospective analysis of trends and hospitalization rates for LRTI-associated hospitalizations in 1998-2008 among AI/AN children aged <5 years using the Indian Health Service direct/contract inpatient data, and also among the general population of US children aged <5 years using the Nationwide Inpatient Sample. RESULTS: The 2006-2008 LRTI-associated hospitalization rate for AI/AN children aged <5 years (21.8 per 1000/year) was 32% lower than the 1998-1999 rate, and 1.6-fold higher than the general US children rate (13.8 per 1000/year; 95% CI, 12.8-14.8). Higher rates were seen in AI/AN children aged <5 years in the Alaska and the Southwest regions of the United States (41.2 and 28.0 per 1000/year, respectively). In infants, these rates were 136.4 and 82.4 per 1000/year, respectively, exceeding the rate in the general US infant population (37.1 per 1000/year; 95% CI, 34.3-40.0). The greatest disparity in the LRTI-associated hospitalization rate between AI/AN infants and the general US infant population was seen for pneumonia, with a 3-fold higher rate in AI/AN infants (36.2 per 1000/year vs 12.7 per 1000/year; 95% CI, 11.8-13.6). CONCLUSION: The LRTI-associated hospitalization rate is higher in AI/AN children, particularly infants from Alaska and the American Southwest, compared with the general US child population. Closing this gap will require addressing housing and sanitation inequities and ensuring high immunization rates and access to care.

Pertussis-associated hospitalizations in American Indian and Alaska Native infants.

OBJECTIVE: To investigate the burden of pertussis in American Indian and Alaska Native (AI/AN) infants. STUDY DESIGN: AI/AN pertussis-associated hospitalizations between 1980 and 2004 were evaluated using Indian Health Service (IHS)/tribal inpatient data, which include all reported hospitalizations within the IHS/tribal health care system. RESULTS: Between 1980 and 2004, 483 pertussis-associated hospitalizations in AI/AN infants were documented; 88% of cases involved infants age < 6 months. For this entire period, the average annual hospitalization rate was 132.7 per 100,000 AI/AN infants (95% confidence interval [CI] = 121.3 to 145.2), and 234.5 per 100,000 AI/AN infants age < 6 months (95% CI = 213.1 to 258.1). Between 2000 and 2004, the annual hospitalization rate was 100.5 per 100,000 AI/AN infants (95% CI = 81.6 to 123.7), which exceeds the estimated 2003 pertussis hospitalization rate of 67.7 per 100,000 in the general US infant population (95% CI = 61.9 to 73.5). The highest pertussis hospitalization rates in 2000 to 2004 were in AI/AN infants in the Alaska and Southwestern IHS regions of the United States. CONCLUSIONS: The burden of pertussis in AI/AN infants is high, particularly so in infants age < 6 months in the Alaska and the Southwestern IHS regions of the United States. Ensuring implementation of vaccination strategies to reduce the incidence of pertussis in AI/AN, infants, adolescents, and adults alike is warranted to reduce the burden of pertussis in AI/AN infants.