- Email: [email protected]
Readmissions after hospital care for meningitis in the United States
ARTICLE IN PRESS American Journal of Infection Control 000 (2019) 1−7
Contents lists available at ScienceDirect
American Journal of Infection Control journal homepage: www.ajicjournal.org
Major Article
Readmissions after hospital care for meningitis in the United States Darcy E. Ellis MPH a,b,*, Theoklis Zaoutis MD, MSCE a,b,c, Dylan P. Thibault MS d,e, James A.G. Crispo PhD d,e, Danielle S. Abraham PhD, MPH a,d,e, Allison W. Willis MD, MSCI a,b,d,e a
Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA c Division of Infectious Diseases, The Children’s Hospital of Philadelphia, Philadelphia, PA d Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA e Translational Center of Excellence for Neuroepidemiology and Neurological Outcomes Research, Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA b
Key Words: Outcomes Hospitalization Population-based
Background: Our objectives were to (1) characterize patient and clinical characteristics of adults hospitalized with meningitis; (2) describe meningitis hospitalization outcomes, including 30- and 90-day readmissions; and (3) determine whether clinical, patient, or index hospitalization characteristics are associated with readmission and readmission outcomes. Methods: This retrospective study of the 2014 National Readmissions Database extracted data on hospitalized adults with a principal diagnosis of meningitis and examined hospitalization outcomes using descriptive statistics. Logistic regression models were built to determine whether characteristics were associated with 30- or 90-day readmissions. Results: For the 30-day readmission analyses, 18,883 adults qualified. Meningitis hospitalizations commonly involved adults 25 to 54 years of age who were insured by private carriers. The readmission rates were 7.0% at 30 days and 11.4% at 90 days. Readmission was associated with greater comorbidity burden (2 conditions: adjusted odds ratio [AOR] = 1.60, range 1.24-2.08; 3 conditions: AOR = 1.92, range 1.43-2.58; 4+ conditions: AOR = 2.68, range 2.04-3.51 vs 0 or 1 condition), public insurance (Medicare: AOR = 1.85, range 1.30-2.62; Medicaid: AOR = 1.48, range 1.16-1.90 vs private insurance), and medical error (AOR = 1.43, range 1.07-1.91). Readmissions were most often for meningitis, septicemia, or medical complications. Conclusions: Readmission after hospitalization for meningitis is associated with both fixed and modifiable factors. More research is needed to determine which post-meningitis readmissions are preventable. © 2019 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
INTRODUCTION Meningitis is a central nervous system disorder usually caused by viral, bacterial, or fungal infection.1 Previous research on *Address correspondence to Darcy E. Ellis, MPH, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Blockley Hall, Room 110, 423 Guardian Dr, Philadelphia, PA 19104. E-mail address: [email protected] (D.E. Ellis). Funding/support: This work was supported by the Departments of Neurology and of Biostatistics Epidemiology and Informatics at the University of Pennsylvania and by the National Institute of Neurological Disorders and Stroke and the National Institutes of Health (grant number NIH F31 NS103445 01A1). Conflicts of interest: None to report. A.W. and D.T. contributed to the study design. A.W. served as study investigator. A. W. and D.T. acquired the study data. D.E. and A.W. provided data analysis. D.E., A.W., J. C., D.A., and T.Z. participated in manuscript preparation. All authors contributed to the interpretation of the data and to the critical review and revision of the manuscript. All authors approved the final draft of the manuscript for submission.
meningitis outcomes has focused on clinical sequelae,2-7 and several studies have examined mortality outcomes in meningitis2-4,6,8-11; however, there are limited data on other hospitalization outcomes such as cost, length of stay, discharge disposition, and readmissions. No study has explicitly examined factors associated with meningitis readmissions. This gap in the literature is concerning, given that hospitalization data are increasingly being interpreted as indicators of care quality and used to guide reimbursement strategies in the United States.12 In this study, we examined meningitis hospitalization outcomes in the United States using a national, all-payer dataset. Our study objectives were to (1) characterize patient and clinical characteristics of adults hospitalized with meningitis; (2) describe meningitis hospitalization outcomes, including 30- and 90-day readmissions; and (3) determine whether clinical, patient, or index hospitalization characteristics are associated with readmission and readmission outcomes.
https://doi.org/10.1016/j.ajic.2019.10.025 0196-6553/© 2019 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
ARTICLE IN PRESS 2
D.E. Ellis et al. / American Journal of Infection Control 00 (2019) 1−7
METHODS
Outcomes
Approvals and research protections
Our primary outcomes were (1) index hospitalization disposition, and (2) 30-day and 90-day readmissions. Secondary outcomes included (1) readmission discharge disposition, (2) length of stay, and (3) reason for readmission. Disposition in the NRD was categorized as routine discharge to home, discharge to post-acute care (skilled nursing facility or inpatient rehabilitation), or discharge to home with home health care. The reason for readmission was identified using the principle diagnosis on the readmission record and classified using the HCUP Clinical Classification Software, which groups individual ICD-9 codes into clinically similar groups.14 Thirty-day readmissions were defined as all-cause, non-elective readmission within 30 days of the index meningitis hospitalization discharge date. Individuals who died during the index admission were excluded from all analyses. We also excluded persons with an index hospitalization discharge occurring less than 30 days before December 31, 2014, as the NRD does not allow researchers to track readmissions between calendar years. For instances with more than one readmission, we extracted data from only the first readmission. As a secondary analysis, we examined 90-day readmissions, adjusting the study sample accordingly.
The University of Pennsylvania Human Protection Research Organization approved an exemption for the use of Health Care Utilization Project data for research analyses and publication. Data source and study population We used the 2014 National Readmissions Database (NRD), a database developed for the Healthcare Cost and Utilization Project (HCUP), for our hospitalization and readmissions analyses. The NRD contains data sampled from approximately 50% of hospitalizations in the United States and can be weighted to produce national estimates of hospitalizations and associated outcomes.13 The NRD contains clinical (ICD-9-CM diagnosis and procedure codes and comorbid disease indicators) and nonclinical (patient demographics, costs, hospital characteristics) variables.13 Patient identification numbers (created solely for the dataset) allow researchers to track an individual across all hospitalizations during a given year. The NRD is the only national source of readmissions data; however, the NRD does not have race data or hospital identifiers that would allow researchers to perform hierarchical analyses (such as those that examine hospital volume or hospital-level effects on outcomes).13 We sampled NRD discharges of adults hospitalized with a principal discharge diagnosis of meningitis, as identified by ICD-9 diagnosis codes that have been grouped by the HCUP into clinically meaningful categories.14 The HCUP Clinical Classification Software classifies individual ICD-9 codes into clinically similar groups.14 We excluded individuals with missing values for any of the variables needed to accomplish the study objectives (ie, patient and hospital descriptors, clinical and outcome variables). We also excluded individuals who had hospitalizations that disqualified them from readmission analyses: those not residing in the state in which they were initially hospitalized (because we would not have been able to observe local readmissions) and those who died before the 30- or 90-day observation window ended. Patient, clinical, and hospital characteristics Several variables were extracted or derived from NRD data to be used in descriptive analyses. We extracted sociodemographic information, including age, sex, expected payer (uninsured, private insurance, Medicare, Medicaid), and socioeconomic status (indicated by median postal code income quartile), from the initial hospitalization record. Hospital characteristics of interest included hospital bed size (small, medium, large), teaching-population density (metropolitan teaching, metropolitan non-teaching, non-metropolitan/rural), and type of hospital (government, private not-for-profit, private for-profit). The HCUP Clinical Classification Software was used to identify preexisting comorbid conditions and to calculate an Elixhauser Comorbidity Index score at the time of initial hospitalization.15 The Elixhauser Comorbidity Index score was examined as a categorical variable (0-1, 2, 3, or 4+ conditions). Mechanical ventilation, seizure, and use of continuous electroencephalography (cEEG) were selected a priori as indicators of a complicated index hospitalization for meningitis; indicator variables for these conditions were created using standard ICD-9 procedure codes. We also extracted data on medical care−related adverse events due to “drugs, medicinal and biological substances causing adverse effects in therapeutic use” (E codes E9300-E9499) and “misadventures to patients during surgical and medical care” (E codes E8700-E8799).
Statistical analysis Survey weights were applied to the 2014 NRD to produce national estimates of inpatient care and outcomes for meningitis in the United States. Sociodemographic, clinical, and hospital characteristics associated with inpatient care for meningitis were analyzed using descriptive statistics. Weighted, unconditional logistic regression models were built to examine the associations among sociodemographic, clinical, hospital, and index hospitalization characteristics and adjusted odds of 30- and 90-day readmissions. We produced rank order lists of the 10 most common reasons for readmissions. Statistical analyses were performed using SAS 9.4 (SAS Institute; Cary, NC). RESULTS Study sample characteristics Applying NRD sample weights, we identified 18,883 adults hospitalized for clinical meningitis in the United States who qualified for 30-day readmission analyses. As shown in Table 1, persons 25 to 54 years of age accounted for 58.9% of adult meningitis hospitalizations in our sample. Females were more common in our sample (55.5% vs 44.5% male). Thirteen percent (n = 2,476) of adults hospitalized with meningitis were uninsured, and the remainder received benefits from Medicare (17.6%), Medicaid (19.0%), or private insurers (50.3%). Care for meningitis occurred most frequently at large (57.5%), private notfor-profit (74.3%), and metropolitan teaching hospitals (64.8%). As shown in Table 2, most individuals hospitalized for meningitis were otherwise healthy. Fifty-three percent (n = 10,022) had no or 1 Elixhauser condition. The most frequently identified chronic conditions were hypertension (31.0%), fluid and electrolyte disorders (28.5%), obesity (12.1%), chronic pulmonary disease (12.0%), uncomplicated diabetes (11.7%), depression (11.2%), and deficiency anemias (11.0%). Index admission outcomes As shown in Table 3, the majority of patients (51.1%) were discharged between 3 and 6 days after admission, and 81.4% of discharges after the index admission were routine discharges to home. Notably, 10.8% (n = 2,037) of meningitis patients had a medical error code recorded during the index admission, 3.2% (n = 612) had medical care errors, and 7.9% (n = 1,482) had documented injuries from medical drugs. Mechanical
ARTICLE IN PRESS D.E. Ellis et al. / American Journal of Infection Control 00 (2019) 1−7 Table 1 Index characteristics of meningitis patients eligible for 30- and 90-day readmission analyses (2014 National Readmissions Database)
Characteristics Age (y) 18-24 25-34 35-44 45-54 55-64 65-74 75-84 85+ Sex Male Female Primary payer Medicare Medicaid Private insurance Other Zip Code income quartile $1-$37,999 $38,000-$47,999 $48,000-$63,999 $64,000+ Control/ownership of hospital Government, nonfederal Private, not-for-profit Private, for-profit Hospital bed size Small Medium Large Teaching status Metropolitan non-teaching Metropolitan teaching Non-metropolitan
Eligible for 30-day readmission analyses n (%)
Table 2 Index clinical characteristics of meningitis patients eligible for 30- and 90-day readmission analyses (2014 National Readmissions Database)
Eligible for 90-day readmission analyses n (%) Clinical characteristics
2,663 (14.1) 4,385 (23.2) 3,532 (18.7) 3,219 (17.0) 2,469 (13.1) 1,489 (7.9) 826 (4.4) 301 (1.6)
2,196 (14.1) 3,605 (23.1) 2,904 (18.6) 2,705 (17.3) 2,035 (13.0) 1,247 (8.0) 687 (4.4) 236 (1.5)
8,401 (44.5) 10,482 (55.5)
6,963 (44.6) 8,651 (55.4)
3,331 (17.6) 3,579 (19.0) 9,498 (50.3) 2,476 (13.1)
2,757 (17.7) 2,936 (18.8) 7,837 (50.2) 2,085 (13.4)
4,660 (24.7) 5,070 (26.8) 4,728 (25.0) 4,426 (23.4)
3,942 (25.2) 4,213 (27.0) 3,880 (24.8) 3,580 (22.9)
2,563 (13.6) 14,025 (74.3) 2,296 (12.2)
2,143 (13.7) 11,594 (74.2) 1,878 (12.0)
2,883 (15.3) 5,141 (27.2) 10,860 (57.5)
2,340 (15.0) 4,185 (26.8) 9,090 (58.2)
5,349 (28.3) 12,228 (64.8) 1,307 (6.9)
4,369 (28.0) 10,166 (65.1) 1,080 (6.9)
ventilation, seizure, and cEEG use were uncommon, documented in 3.0%, 6.1%, and 0.3% cases, respectively, of hospitalizations. 30-Day readmission The all-cause 30-day non-elective readmission rate among meningitis inpatients was 7.0%. As shown in Table 4, the readmission rate was lowest among individuals ages 18 to 24 (4.1%) and highest among individuals ages 85 and older (13.2%). Readmission did not vary by sex. Medicare and Medicaid program participants and individuals from the lowest income neighborhoods had higher than average 30-day readmission rates (13.2%, 8.3%, and 8.4%, respectively). The readmission rates of persons requiring advanced post-acute care—inpatient postacute care or home health care—were nearly twice the average (14.9% and 12.5%, respectively). Readmission rates increased with comorbidity burden, from 4.0% (n = 397) among persons with 0 or 1 comorbid condition to 15.2% (n = 471) among those with 4 or more comorbid conditions. Readmission rates also increased with increasing index length of stay (Table 4). Eleven percent of persons with an adverse event documented during their index admission were readmitted, compared to 6.6% of those without adverse event codes. Logistic regression models that included variables for patient, clinical, and hospital characteristics found that public insurance program participation (Medicare adjusted odds ratio [AOR] = 1.85, 95% CI, 1.30-2.62; Medicaid AOR = 1.48, 95% CI, 1.16-1.90 vs private insurance) and Elixhauser scores of 4 or more (AOR = 2.68; 95% CI, 2.043.51), 3 (AOR = 1.92; 95% CI, 1.43-2.58), or 2 (AOR = 1.60; 95% CI, 1.242.08) were associated with greater odds of readmission. Discharge to
3
Elixhauser Comorbidity Index score 0-1 condition 2 conditions 3 conditions 4+ conditions Chronic conditions AIDS Alcohol abuse Deficiency anemias Rheumatoid arthritis/collagen vascular diseases Chronic blood loss anemia Congestive heart failure Chronic pulmonary disease Coagulopathy Depression Diabetes, uncomplicated Diabetes, complicated Drug abuse Hypertension Hypothyroidism Liver disease Lymphoma Fluid and electrolyte disorders Metastatic cancer Neurological disorders Obesity Paralysis Peptic ulcer disease excluding bleeding Peripheral vascular disorders Psychoses Pulmonary circulation disorders Renal failure Solid tumor without metastasis Valvular disease Weight loss
Eligible for 30-day readmission analyses n (%)
Eligible for 90-day readmission analyses n (%)
10,022 (53.1) 3,327 (17.6) 2,425 (12.8) 3,109 (16.5)
8,307 (53.2) 2,723 (17.4) 1,991 (12.7) 2,595 (16.6)
101 (0.5) 477 (2.5) 2,082 (11.0) 606 (3.2)
74 (0.5) 400 (2.6) 1,769 (11.3) 511 (3.3)
71 (0.4) 383 (2.0) 2,274 (12.0) 835 (4.4) 2,114 (11.2) 2,206 (11.7) 416 (2.2) 1,018 (5.4) 5,862 (31.0) 1,522 (8.1) 416 (2.2) 167 (0.9) 5,383 (28.5) 163 (0.9) 84 (0.4) 2,289 (12.1) 316 (1.7) —*
56 (0.4) 342 (2.2) 1,895 (12.1) 679 (4.3) 1,704 (10.9) 1,816 (11.6) 365 (2.3) 851 (5.4) 4,846 (31.0) 1,267 (8.1) 345 (2.2) 131 (0.8) 4,461 (28.6) 130 (0.8) 70 (0.4) 1,872 (12) 276 (1.8) —*
335 (1.8) 750 (4.0) 152 (0.8) 773 (4.1) 162 (0.9) 339 (1.8) 415 (2.2)
280 (1.8) 612 (3.9) 121 (0.8) 655 (4.2) 108 (0.7) 270 (1.7) 363 (2.3)
*The Healthcare Cost and Utilization Project data use agreement prevents printing cells with n < 10.
Table 3 Outcomes associated with meningitis patients eligible for 30- and 90-day readmission analyses (2014 National Readmissions Database)
Outcomes Length of stay (d) 2 3-6 >7 Disposition after index admission Routine to home Transfer to short-term hospital or other facility Home health care Other Complications E code during index admission (any) E codes for medical errors/CCS 2616 E codes for drug errors/CCS 2617 Specific complications Mechanical ventilation Seizure Continuous electroencephalography
Eligible for 30-day readmission analyses n (%)
Eligible for 90-day readmission analyses n (%)
5,636 (29.8) 9,654 (51.1) 3,594 (19)
4,604 (29.5) 7,989 (51.2) 3,022 (19.4)
15,379 (81.4) 1,435 (7.6)
12,708 (81.4) 1,184 (7.6)
1,806 (9.6) 262 (1.4)
1,498 (9.6) 224 (1.4)
2,037 (10.8) 612 (3.2) 1,482 (7.9)
1,678 (10.7) 504 (3.2) 1,219 (7.8)
570 (3.0) 1,157 (6.1) 64 (0.3)
497 (3.2) 978 (6.3) 54 (0.3)
4
Table 4 Factors associated with 30- and 90-day non-elective readmissions after hospitalization for meningitis (2014 National Readmissions Database)* 30-day non-elective readmission
Characteristics
Percent readmitted (overall = 11.4%)
Adjusted odds ratio of readmission (95% CI)
4.1 5.4 5.8 7.5 9.1 11.7 12.1 13.2
Ref. 1.28 (0.86-1.89) 1.20 (0.81-1.78) 1.28 (0.87-1.89) 1.25 (0.81-1.93) 0.94 (0.57-1.56) 0.84 (0.49-1.43) 0.81 (0.40-1.65)
2,196 3,605 2,904 2,705 2,035 1,247 687 236
127 241 264 306 272 251 135 58
5.8 6.7 9.1 11.3 13.3 20.1 19.7 24.4
Ref. 1.07 (0.74-1.55) 1.26 (0.89-1.79) 1.29 (0.90-1.84) 1.12 (0.74-1.7) 0.95 (0.60-1.49) 0.75 (0.46-1.23) 0.89 (0.47-1.7)
599 735
7.1 7.0
Ref. 0.99 (0.81-1.22)
6,963 8,651
767 886
11.0 10.2
Ref. 0.93 (0.77-1.12)
3,331 3,579 9,498 2,476
441 298 459 136
13.2 8.3 4.8 5.5
1.85 (1.30-2.62)** 1.48 (1.16-1.90)** REF 1.06 (0.74-1.50)
2,757 2,936 7,837 2,085
613 349 521 170
22.2 11.9 6.7 8.1
2.09 (1.53-2.86)** 1.50 (1.20-1.88)** REF 1.10 (0.80-1.51)
4,660 5,070 4,728 4,426
394 385 288 268
8.4 7.6 6.1 6.1
1.20 (0.91-1.59) 1.19 (0.92-1.54) 1.00 (0.75-1.32) Ref.
3,942 4,213 3,880 3,580
529 440 385 300
13.4 10.4 9.9 8.4
1.48 (1.15-1.90)** 1.22 (0.95-1.57) 1.22 (0.93-1.61) Ref.
15,379 1,435 1,806 262
847 (5.5) 214 (14.9) 226 (12.5) 47 (17.9)
5.5 14.9 12.5 17.9
Ref. 1.44 (1.06-1.95)** 1.64 (1.26-2.13)** 3.09 (1.82-5.24)**
12,708 1,184 1,498 224
1,029 308 267 49
8.1 26.0 17.9 21.8
Ref. 1.59 (1.20-2.12)** 1.50 (1.16-1.95)** 2.58 (1.51-4.4)**
10,022 3,327 2,425 3,109
397 236 230 471
4.0 7.1 9.5 15.2
Ref. 1.60 (1.24-2.08)** 1.92 (1.43-2.58)** 2.68 (2.04-3.51)**
8,307 2,723 1,991 2,595
431 246 322 654
5.2 9.0 16.2 25.2
Ref. 1.51 (1.17-1.96)** 2.55 (1.94-3.35)** 3.55 (2.76-4.58)**
5,636 9,654 3,594
294 574 466
5.2 5.9 13.0
Ref. 0.92 (0.71-1.18) 1.30 (0.93-1.80)
4,604 7,989 3,022
320 719 614
7.0 9.0 20.3
Ref. 1.00 (0.78-1.27) 1.34 (0.99-1.82)
5,349 12,228 1,307
323 922 88
6.0 7.5 6.7
0.86 (0.70-1.05) Ref. 0.85 (0.55-1.31)
4,369 10,166 1,080
426 1,131 96
9.7 11.1 8.9
0.96 (0.80-1.16) Ref. 0.70 (0.46-1.06)
16,846 2,037
1,105 228
6.6 11.2
Ref. 1.43 (1.07-1.91)**
13,936 1,678
1,380 273
9.9 16.3
Ref. 1.33 (1.02-1.74)**
18,272 612
1,258 76
6.9 12.4
Ref. 1.61 (0.94-2.74)
15,110 504
1,566 87
10.4 17.3
Ref. 1.47 (0.91-2.40)
Percent readmitted (overall = 7.0%)
2,663 4,385 3,532 3,219 2,469 1,489 826 301
110 237 206 241 225 174 100 40
8,401 10,482
(continued on next page)
ARTICLE IN PRESS
Adjusted odds ratio of readmission (95% CI)
Number readmitted (N = 1,653)
Number readmitted (N =1,334)
D.E. Ellis et al. / American Journal of Infection Control 00 (2019) 1−7
Age (y) 18-24 25-34 35-44 45-54 55-64 65-74 75-84 85+ Sex Male Female Payer Medicare Medicaid Private Other Zip Code income quartile $1-$37,999 $38,000-$47,999 $48,000-$63,999 $64,000+ Index stay disposition Home Inpatient post-acute care Home health care Other/unknown Elixhauser Comorbidity Index score 0-1 condition 2 conditions 3 conditions 4+ conditions Length of index stay (d) <3 3-6 >6 Teaching status Metropolitan non-teaching Metropolitan teaching Non-metropolitan Any E code during index admission Absent Present E codes for medical care E8700-E8799/CCS 2616 Absent Present
90-day non-elective readmission Total population (index admissions) (N = 15,614)
Total population (index admissions) (N = 18,883)
ARTICLE IN PRESS 5
an inpatient facility (AOR = 1.44; 95% CI, 1.06-1.95) or home health care (AOR = 1.64; 95% CI, 1.26-2.13) or documentation of an adverse event (AOR = 1.43; 95% CI, 1.07-1.91) were also positively associated with readmission. Patient descriptors, hospital characteristics, and diagnoses indicating more severe clinical courses were not significantly associated with readmission in our adjusted models.
0.79 (0.49-1.29) 0.68 (0.24-1.93) 1.37 (1.06-1.79)**
Ref. 1.28 (0.97-1.70)
Adjusted odds ratio of readmission (95% CI)
D.E. Ellis et al. / American Journal of Infection Control 00 (2019) 1−7
*Adjusted for sex, Elixhauser Comorbidity Index score, index disposition, length of stay, insurance, Zip Code income quartile, and readmission hospital teaching status. y The Healthcare Cost and Utilization Project data use agreement prevents printing cells with n < 10. **Indicates p < 0.05 statistical significance.
20.1 —y 24.7 100 —y 242 497 54 978 55 —y 168 570 64 1,157
9.7 —y 14.5
0.59 (0.33-1.06) 0.35 (0.09-1.44) 1.22 (0.89-1.66)
10.1 16.3 1,454 199 14,395 1,219 1,173 161
E codes for adverse effects of medical drugs E9300-E9499/CCS 2617 Absent Present Specific complications (yes vs no) Mechanical ventilation Continuous electroencephalography Seizure
17,401 1,482
6.7 10.8
Ref. 1.30 (0.97-1.74)
Percent readmitted (overall = 11.4%) Number readmitted (N = 1,653) Total population (index admissions) (N = 15,614) Adjusted odds ratio of readmission (95% CI) Percent readmitted (overall = 7.0%) Number readmitted (N =1,334) Characteristics
Table 4 (Continued)
Total population (index admissions) (N = 18,883)
30-day non-elective readmission
90-day non-elective readmission
90-Day readmission The study sample eligible for 90-day readmissions had sociodemographic, clinical, and hospital characteristics that were nearly identical to those described for the 30-day sample above (Table 1). The 90-day unplanned readmission rate was 11.4% (n = 1,653), among 15,614 eligible patients. As shown in Table 4, 64.2% (n = 444) of persons readmitted within 90 days after discharge for meningitis were ages 65 and above. Public insurance (Medicare or Medicaid), residence in a neighborhood with median income less than $37,999, non-routine discharge, documentation of a medical error, increasing Elixhauser comorbidity scores, and documentation of seizure were all associated with increased odds of readmission within 90 day (Table 4). Readmission diagnoses Table 5 displays the top 10 primary readmission diagnoses for both 30- and 90-day readmission analyses. The reasons for readmission were diverse, with no clinical condition observed more frequently than 11.6%. Readmissions were most often for meningitis (11.6% of readmissions at 30 days and 10.3% of readmissions at 90 days), followed by septicemia. DISCUSSION The results from this national analysis increase our understanding of adult meningitis in the United States by providing key data on patient characteristics, clinical, and hospitalization outcomes, including readmissions. Comorbid disease burden and experiencing a medical adverse event were positively associated with readmission. Readmissions were most often for infection or complications of initial care. We found national 30- and 90-day readmission rates of 7.0% and 11.4%, respectively, among adults receiving inpatient meningitis care. A HCUP statistical brief reported a 30-day all-cause readmission rate after meningitis hospitalization of 7.8% in 2010.16 A study conducted using the Premier Healthcare Database (PHD) spanning the years 2011 through 2014 found the 30-day all-cause readmission rate for meningitis or encephalitis to be 3.2%.17 To understand how our estimates differ from these, it must be understood that these other studies used different study populations, readmission definitions, and time frames. The HCUP study included adults and children, whereas the PHD study estimates were for infants and children only. We have produced estimates for adults, filling a gap in the literature. With respect to readmission definitions, the HCUP study, like our study, captured all readmissions within the same state. However, the PHD study included only readmissions to the same index hospital, which would result in lower estimates. Our analysis was conducted for 2014, whereas the HCUP and PHD estimates were obtained from 2010 and 2011-2014, respectively. Although the incidence of bacterial meningitis has declined since 1997 due to vaccination,8 it is unclear if this would impact readmissions in any way. Overall 30-day readmissions also have been decreasing with time.18 Consequently, a future trend analysis should be conducted exploring whether there have been any changes in readmission rates for meningitis. Our data suggest that 30-day readmission rates for meningitis (7.0%) are lower than those estimated for more prevalent infectious diseases, including septicemia (2014 rate = 18.9%), urinary tract infections (2014 rate = 15.7%), and pneumonia (2014 rate = 15.5%).19
ARTICLE IN PRESS D.E. Ellis et al. / American Journal of Infection Control 00 (2019) 1−7
6
Table 5 Clinical conditions associated with 30- and 90-day unplanned readmissions (2014 National Readmissions Database) 30-Day readmission analyses
90-Day readmission analyses
Rank
Condition
n (%)
Condition
n (%)
1
Meningitis (except that caused by tuberculosis or sexually transmitted disease) Septicemia (except in labor) Complications of surgical procedures or medical care Headache, including migraine
154 (11.6)
Meningitis (except that caused by tuberculosis or sexually transmitted disease) Septicemia (except in labor) Headache, including migraine
170 (10.3)
Complications of surgical procedures or medical care Epilepsy, convulsions Other nervous system disorders
88 (5.3)
Complication of device, implant or graft Encephalitis (except that caused by tuberculosis or sexually transmitted disease) Acute cerebrovascular disease Pneumonia (except that caused by tuberculosis or sexually transmitted disease)
51 (3.1) 49 (3.0)
2 3 4 5 6
107 (8.0) 90 (6.7) 89 (6.7) 61 (4.6) 57 (4.3)
7 8
Other nervous system disorders Encephalitis (except that caused by tuberculosis or sexually transmitted disease) Epilepsy, convulsions Complication of device, implant or graft
9 10
Acute cerebrovascular disease Acute and unspecified renal failure
33 (2.5) 30 (2.2)
Total
46 (3.5) 34 (2.6)
1,334 (1,334/18,884 = 7.1% readmission rate)
Readmission rates for meningitis in our study were also lower than the overall rate of 30-day all-cause readmissions in 2014 (14.0%).19 Factors related to 30- or 90-day readmission in fully adjusted regression models included comorbid disease burden, initial discharge location, and adverse events. Comorbidities are often incorporated into predictive models of hospital readmission.20 In prior studies of meningitis, age was found to be a prognostic factor for adverse clinical outcomes,2,3,9,10,21 and comorbidities increase with age.22 Additionally, meningitis is particularly challenging to manage in older adults with other chronic conditions.21 In our sample, readmission rates were highest among older adults; however, age was not associated with readmission in the adjusted analyses. These findings suggest that premorbid health state may be a more important driver of readmissions than age. Surprisingly, those with an index stay discharge to home health care had significantly higher odds of readmission compared to those discharged home or to inpatient post-acute care. Home health care aims to reduce the risk of readmissions; however, the success of this goal is partially dependent on adequate communication between home health care providers and physicians.23 The needs of sicker patients discharged to home health care after hospitalization for meningitis may be insufficiently met. Further study is needed to determine which patients would more adequately benefit from inpatient post-acute care. In the 30-day readmission analysis, 10.8% of patients experienced an adverse event. Despite adjusting for covariates, adverse events during the index hospitalization significantly increased the odds for both 30- and 90-day readmissions. Also, complications of surgical procedures or medical care were the third and fourth most common reasons for readmission in this study. Medical errors are particularly common in critical care settings, with one prospective cohort study finding a 1-year incidence of 20.2%.24 We could not determine with certainty whether patients were admitted to an intensive care unit in this dataset; however, meningitis patients, particularly bacterial meningitis patients, are likely to be critically ill and receive higher level inpatient care. Diagnostic procedures for meningitis also carry established risks. Headache is a common complication of lumbar puncture and was a common reason for readmission.25-27 Brain herniation and local tissue injury are also possible after lumbar puncture.28 Neuroimaging carries a risk of allergic or toxic reaction to intravenous contrast agents. Antibiotics necessary to treat meningitis may cause liver or kidney injury or allergic reactions. Clinical
134 (8.1) 99 (6.0)
67 (4.0) 65 (3.9)
49 (3.0) 34 (2.1) 1,653 (1,653/15,615 = 10.6% readmission rate)
monitoring of a meningitis patient requires regular blood sampling. Patient, provider, clinical treatment, environmental, and organizational factors (such as provider experience, medications administered, or patient-to-nurse ratio) can lead to medication errors or procedure complications.11 We were unable to examine these factors with this dataset, but future analyses using data containing these variables may identify intervenable processes associated with readmission or unfavorable clinical outcomes. Alternatively, given the low absolute number of readmissions due to complications of medical care, our estimates of medical error−related readmissions may be within the acceptable range for care of a condition that requires invasive diagnostic tests and multiple drug exposures. Although meningitis can be severe, our analysis suggests that readmissions may not be dependent on index disease severity, as marked by cEEG monitoring, ventilation, or seizure, but instead on medical care− related factors such as medical procedures, devices, medications, and secondary infections. The only indicator of a complicated index hospitalization that was significantly associated with readmission was seizure, at 90 days. This supports the policy of using readmission rates to measure and compare hospital quality within and between hospitals, because readmission rates do not seem to reflect disease severity or diagnosis in this case. Datasets that support hierarchical analyses (nesting of patients within individual hospitals) are needed to confirm and explore this finding further. However, given the association between comorbidities and readmission, as well as insurance type and readmission, it is important that any comparisons be case-mix adjusted. Meningitis was the most common documented reason for readmission in this national sample. Other infections ranking in the top 10 for either the 30-day or 90-day readmissions included septicemia, encephalitis, and pneumonia. With this dataset, we cannot determine if infections are a consequence of a new primary infection (hospitalor community-acquired) or recurrent infection. Recurrent bacterial meningitis is known to occur in about 5%-6% of adults.28 In our study, the proportion of readmissions with recurrent meningitis at 30 days was 11.6%. Baseline health status, particularly the presence of immunocompromising comorbid diseases, is likely an important contributor to post-discharge infection risk. Ensuring appropriate empiric and final antibiotic prescribing may also reduce such readmissions.29 Because our national dataset did not include laboratory or imaging data, we were unable to corroborate meningitis etiologies (bacterial, viral, fungal) or extent of disease (meningitis, meningoencephalitis,
ARTICLE IN PRESS D.E. Ellis et al. / American Journal of Infection Control 00 (2019) 1−7
encephalitis). Consequently, we did not stratify our results by meningitis type. Repeat infections may be preventable, underscoring the importance of further study of infection-related readmissions. CONCLUSIONS In this study, we leveraged nationally representative data on inpatient care to produce, as far as we know, the first national-level data on short-term hospitalization outcomes among adults with meningitis in the United States. Our overall findings suggest that readmissions may not be dependent on index disease severity but rather on patient baseline health state and medical care−related factors. Yet, it is important to emphasize the limitations of our study. Data that are generated for billing or documentation of care or services, as found in billing claims or medical records, are subject to coding error or bias. Administrative datasets such as the NRD may not provide clinical details on disease severity or physical function, or may contain these data in an incomplete or biased fashion. All retrospective studies are subject to these limitations, and methods to increase data comprehensiveness (eg, patient registries, academic center based studies) directly oppose approaches to produce national estimates or improve external validity. Also, we present the most recent data, which could represent a decline in readmissions in response to changes in clinical guidelines for meningitis prevention and treatment or to readmission reduction strategies and penalties. Future trend analyses will allow stakeholders to place our findings in the appropriate historical context and guide the development of interventions targeting medical care, social support, or patient predisposing factors. In spite of these limitations, these data will likely become the benchmark for future public health or health service research evaluations of hospitalization outcomes for meningitis in the adult population. Acknowledgments Ms. Lia Weil assisted with background literature searches. Mr. Derrick Tam assisted with background literature search and manuscript formatting. References 1. Zueter AM, Zaiter A. Infectious meningitis. Clin Microbiol Newsl 2015;37:43-51. 2. van de Beek D, de Gans J, Spanjaard L, Weisfelt M, Reitsma JB, Vermeulen M. Clinical features and prognostic factors in adults with bacterial meningitis. N Engl J Med 2004;351:1849-59. 3. Weisfelt M, van de Beek D, Spanjaard L, Reitsma JB, de Gans J. Communityacquired bacterial meningitis in older people. J Am Geriatr Soc 2006;54:1500-7. 4. Wang AY, Machicado JD, Khoury NT, Wootton SH, Salazar L, Hasbun R. Community-acquired meningitis in older adults: clinical features, etiology, and prognostic factors. J Am Geriatr Soc 2014;62:2064-70. 5. van de Beek D, Schmand B, de Gans J, Weisfelt M, Vaessen H, Dankert J, et al. Cognitive impairment in adults with good recovery after bacterial meningitis. J Infect Dis 2002;186:1047-52. 6. Aronin SI, Peduzzi P, Quagliarello VJ. Community-acquired bacterial meningitis: risk stratification for adverse clinical outcome and effect of antibiotic timing. Ann Intern Med 1998;129:862-9.
7
dos JP, et al. Pneumo7. Auburtin M, Porcher R, Bruneel F, Scanvic A, Trouillet JL, Be coccal meningitis in the intensive care unit: prognostic factors of clinical outcome in a series of 80 cases. Am J Respir Crit Care Med 2002;165:713-7. 8. Castelblanco RL, Lee M, Hasbun R. Epidemiology of bacterial meningitis in the USA from 1997 to 2010: a population-based observational study. Lancet Infect Dis 2014;14:813-9. 9. Durand ML, Calderwood SB, Weber DJ, Miller SI, Southwick FS, Caviness VS Jr, et al. Acute bacterial meningitis in adults. A review of 493 episodes. N Engl J Med 1993;328:21-8. 10. Sigurdardottir B, Bjornsson OM, Jonsdottir KE, Erlendsdottir H, Gudmundsson S. Acute bacterial meningitis in adults. A 20-year overview. Arch Intern Med 1997;157:425-30. 11. Hasbun R, Rosenthal N, Balada-Llasat JM, Chung J, Duff S, Bozzette S, et al. Epidemiology of meningitis and encephalitis in the United States, 2011-2014. Clin Infect Dis 2017;65:359-63. 12. U.S. Centers for Medicare & Medicaid Services. Hospital Readmissions Reduction Program (HRRP). Available from: https://www.cms.gov/medicare/medicare-feefor-service-payment/acuteinpatientpps/readmissions-reduction-program.html. Accessed November 7, 2019. 13. Healthcare Cost and Utilization Project (HCUP). NRD overview. Available from: www.hcup-us.ahrq.gov/nrdoverview.jsp. Accessed November 7, 2019. 14. Healthcare Cost and Utilization Project (HCUP). HCUP Clinical Classification Software (CCS) for ICD-9-CM. Available from: http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp. Accessed November 7, 2019. 15. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care 1998;36:8-27. 16. Elixhauser A, Steiner C. Readmissions to U.S. hospitals by diagnosis, 2010: statistical brief #153. Healthcare Cost and Utilization Project (HCUP) statistical briefs. Rockville (MD): Agency for Healthcare Research and Quality; 2006. 17. Hasbun R, Wootton SH, Rosenthal N, Balada-Llasat JM, Chung J, Duff S, et al. Epidemiology of meningitis and encephalitis in infants and children in the United States, 2011-2014. Pediatr Infect Dis J 2019;38:37-41. 18. Fingar K, Washington R. Trends in hospital readmissions for four high-volume conditions, 2009-2013: statistical brief #196. Healthcare Cost and Utilization Project (HCUP) statistical briefs. Rockville (MD): Agency for Healthcare Research and Quality; 2006. 19. Fingar KR, Barrett ML, Jiang HJ. A comparison of all-cause 7-day and 30-day readmissions, 2014: statistical brief #230. Healthcare Cost and Utilization Project (HCUP) statistical briefs. Rockville (MD): Agency for Healthcare Research and Quality; 2006. 20. Kansagara D, Englander H, Salanitro A, Kagen D, Theobald C, Freeman M, et al. Risk prediction models for hospital readmission: a systematic review. JAMA 2011;306: 1688-98. 21. Domingo P, Pomar V, de Benito N, Coll P. The spectrum of acute bacterial meningitis in elderly patients. BMC Infect Dis 2013;13:108. 22. Ashman JJ, Beresovsky V. Multiple chronic conditions among US adults who visited physician offices: data from the National Ambulatory Medical Care Survey, 2009. Prev Chronic Dis 2013;10:E64. 23. Pesko MF, Gerber LM, Peng TR, Press MJ. Home health care: nurse-physician communication, patient severity, and hospital readmission. Health Serv Res 2018;53: 1008-24. 24. Rothschild JM, Landrigan CP, Cronin JW, Kaushal R, Lockley SW, Burdick E, et al. The Critical Care Safety Study: the incidence and nature of adverse events and serious medical errors in intensive care. Crit Care Med 2005;33:1694-700. 25. Ahmed SV, Jayawarna C, Jude E. Post lumbar puncture headache: diagnosis and management. Postgrad Med J 2006;82:713-6. 26. Leibold RA, Yealy DM, Coppola M, Cantees KK. Post-dural-puncture headache: characteristics, management, and prevention. Ann Emerg Med 1993;22:1863-70. 27. Kuntz KM, Kokmen E, Stevens JC, Miller P, Offord KP, Ho MM. Post-lumbar puncture headaches: experience in 501 consecutive procedures. Neurology 1992;42: 1884-7. 28. Tebruegge M, Curtis N. Epidemiology, etiology, pathogenesis, and diagnosis of recurrent bacterial meningitis. Clin Microbiol Rev 2008;21:519-37. 29. Tunkel AR, Hartman BJ, Kaplan SL, Kaufman BA, Roos KL, Scheld WM, et al. Practice guidelines for the management of bacterial meningitis. Clin Infect Dis Epub 2004;39:1267-84.
Contents lists available at ScienceDirect
American Journal of Infection Control journal homepage: www.ajicjournal.org
Major Article
Readmissions after hospital care for meningitis in the United States Darcy E. Ellis MPH a,b,*, Theoklis Zaoutis MD, MSCE a,b,c, Dylan P. Thibault MS d,e, James A.G. Crispo PhD d,e, Danielle S. Abraham PhD, MPH a,d,e, Allison W. Willis MD, MSCI a,b,d,e a
Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA c Division of Infectious Diseases, The Children’s Hospital of Philadelphia, Philadelphia, PA d Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA e Translational Center of Excellence for Neuroepidemiology and Neurological Outcomes Research, Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA b
Key Words: Outcomes Hospitalization Population-based
Background: Our objectives were to (1) characterize patient and clinical characteristics of adults hospitalized with meningitis; (2) describe meningitis hospitalization outcomes, including 30- and 90-day readmissions; and (3) determine whether clinical, patient, or index hospitalization characteristics are associated with readmission and readmission outcomes. Methods: This retrospective study of the 2014 National Readmissions Database extracted data on hospitalized adults with a principal diagnosis of meningitis and examined hospitalization outcomes using descriptive statistics. Logistic regression models were built to determine whether characteristics were associated with 30- or 90-day readmissions. Results: For the 30-day readmission analyses, 18,883 adults qualified. Meningitis hospitalizations commonly involved adults 25 to 54 years of age who were insured by private carriers. The readmission rates were 7.0% at 30 days and 11.4% at 90 days. Readmission was associated with greater comorbidity burden (2 conditions: adjusted odds ratio [AOR] = 1.60, range 1.24-2.08; 3 conditions: AOR = 1.92, range 1.43-2.58; 4+ conditions: AOR = 2.68, range 2.04-3.51 vs 0 or 1 condition), public insurance (Medicare: AOR = 1.85, range 1.30-2.62; Medicaid: AOR = 1.48, range 1.16-1.90 vs private insurance), and medical error (AOR = 1.43, range 1.07-1.91). Readmissions were most often for meningitis, septicemia, or medical complications. Conclusions: Readmission after hospitalization for meningitis is associated with both fixed and modifiable factors. More research is needed to determine which post-meningitis readmissions are preventable. © 2019 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
INTRODUCTION Meningitis is a central nervous system disorder usually caused by viral, bacterial, or fungal infection.1 Previous research on *Address correspondence to Darcy E. Ellis, MPH, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Blockley Hall, Room 110, 423 Guardian Dr, Philadelphia, PA 19104. E-mail address: [email protected] (D.E. Ellis). Funding/support: This work was supported by the Departments of Neurology and of Biostatistics Epidemiology and Informatics at the University of Pennsylvania and by the National Institute of Neurological Disorders and Stroke and the National Institutes of Health (grant number NIH F31 NS103445 01A1). Conflicts of interest: None to report. A.W. and D.T. contributed to the study design. A.W. served as study investigator. A. W. and D.T. acquired the study data. D.E. and A.W. provided data analysis. D.E., A.W., J. C., D.A., and T.Z. participated in manuscript preparation. All authors contributed to the interpretation of the data and to the critical review and revision of the manuscript. All authors approved the final draft of the manuscript for submission.
meningitis outcomes has focused on clinical sequelae,2-7 and several studies have examined mortality outcomes in meningitis2-4,6,8-11; however, there are limited data on other hospitalization outcomes such as cost, length of stay, discharge disposition, and readmissions. No study has explicitly examined factors associated with meningitis readmissions. This gap in the literature is concerning, given that hospitalization data are increasingly being interpreted as indicators of care quality and used to guide reimbursement strategies in the United States.12 In this study, we examined meningitis hospitalization outcomes in the United States using a national, all-payer dataset. Our study objectives were to (1) characterize patient and clinical characteristics of adults hospitalized with meningitis; (2) describe meningitis hospitalization outcomes, including 30- and 90-day readmissions; and (3) determine whether clinical, patient, or index hospitalization characteristics are associated with readmission and readmission outcomes.
https://doi.org/10.1016/j.ajic.2019.10.025 0196-6553/© 2019 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
ARTICLE IN PRESS 2
D.E. Ellis et al. / American Journal of Infection Control 00 (2019) 1−7
METHODS
Outcomes
Approvals and research protections
Our primary outcomes were (1) index hospitalization disposition, and (2) 30-day and 90-day readmissions. Secondary outcomes included (1) readmission discharge disposition, (2) length of stay, and (3) reason for readmission. Disposition in the NRD was categorized as routine discharge to home, discharge to post-acute care (skilled nursing facility or inpatient rehabilitation), or discharge to home with home health care. The reason for readmission was identified using the principle diagnosis on the readmission record and classified using the HCUP Clinical Classification Software, which groups individual ICD-9 codes into clinically similar groups.14 Thirty-day readmissions were defined as all-cause, non-elective readmission within 30 days of the index meningitis hospitalization discharge date. Individuals who died during the index admission were excluded from all analyses. We also excluded persons with an index hospitalization discharge occurring less than 30 days before December 31, 2014, as the NRD does not allow researchers to track readmissions between calendar years. For instances with more than one readmission, we extracted data from only the first readmission. As a secondary analysis, we examined 90-day readmissions, adjusting the study sample accordingly.
The University of Pennsylvania Human Protection Research Organization approved an exemption for the use of Health Care Utilization Project data for research analyses and publication. Data source and study population We used the 2014 National Readmissions Database (NRD), a database developed for the Healthcare Cost and Utilization Project (HCUP), for our hospitalization and readmissions analyses. The NRD contains data sampled from approximately 50% of hospitalizations in the United States and can be weighted to produce national estimates of hospitalizations and associated outcomes.13 The NRD contains clinical (ICD-9-CM diagnosis and procedure codes and comorbid disease indicators) and nonclinical (patient demographics, costs, hospital characteristics) variables.13 Patient identification numbers (created solely for the dataset) allow researchers to track an individual across all hospitalizations during a given year. The NRD is the only national source of readmissions data; however, the NRD does not have race data or hospital identifiers that would allow researchers to perform hierarchical analyses (such as those that examine hospital volume or hospital-level effects on outcomes).13 We sampled NRD discharges of adults hospitalized with a principal discharge diagnosis of meningitis, as identified by ICD-9 diagnosis codes that have been grouped by the HCUP into clinically meaningful categories.14 The HCUP Clinical Classification Software classifies individual ICD-9 codes into clinically similar groups.14 We excluded individuals with missing values for any of the variables needed to accomplish the study objectives (ie, patient and hospital descriptors, clinical and outcome variables). We also excluded individuals who had hospitalizations that disqualified them from readmission analyses: those not residing in the state in which they were initially hospitalized (because we would not have been able to observe local readmissions) and those who died before the 30- or 90-day observation window ended. Patient, clinical, and hospital characteristics Several variables were extracted or derived from NRD data to be used in descriptive analyses. We extracted sociodemographic information, including age, sex, expected payer (uninsured, private insurance, Medicare, Medicaid), and socioeconomic status (indicated by median postal code income quartile), from the initial hospitalization record. Hospital characteristics of interest included hospital bed size (small, medium, large), teaching-population density (metropolitan teaching, metropolitan non-teaching, non-metropolitan/rural), and type of hospital (government, private not-for-profit, private for-profit). The HCUP Clinical Classification Software was used to identify preexisting comorbid conditions and to calculate an Elixhauser Comorbidity Index score at the time of initial hospitalization.15 The Elixhauser Comorbidity Index score was examined as a categorical variable (0-1, 2, 3, or 4+ conditions). Mechanical ventilation, seizure, and use of continuous electroencephalography (cEEG) were selected a priori as indicators of a complicated index hospitalization for meningitis; indicator variables for these conditions were created using standard ICD-9 procedure codes. We also extracted data on medical care−related adverse events due to “drugs, medicinal and biological substances causing adverse effects in therapeutic use” (E codes E9300-E9499) and “misadventures to patients during surgical and medical care” (E codes E8700-E8799).
Statistical analysis Survey weights were applied to the 2014 NRD to produce national estimates of inpatient care and outcomes for meningitis in the United States. Sociodemographic, clinical, and hospital characteristics associated with inpatient care for meningitis were analyzed using descriptive statistics. Weighted, unconditional logistic regression models were built to examine the associations among sociodemographic, clinical, hospital, and index hospitalization characteristics and adjusted odds of 30- and 90-day readmissions. We produced rank order lists of the 10 most common reasons for readmissions. Statistical analyses were performed using SAS 9.4 (SAS Institute; Cary, NC). RESULTS Study sample characteristics Applying NRD sample weights, we identified 18,883 adults hospitalized for clinical meningitis in the United States who qualified for 30-day readmission analyses. As shown in Table 1, persons 25 to 54 years of age accounted for 58.9% of adult meningitis hospitalizations in our sample. Females were more common in our sample (55.5% vs 44.5% male). Thirteen percent (n = 2,476) of adults hospitalized with meningitis were uninsured, and the remainder received benefits from Medicare (17.6%), Medicaid (19.0%), or private insurers (50.3%). Care for meningitis occurred most frequently at large (57.5%), private notfor-profit (74.3%), and metropolitan teaching hospitals (64.8%). As shown in Table 2, most individuals hospitalized for meningitis were otherwise healthy. Fifty-three percent (n = 10,022) had no or 1 Elixhauser condition. The most frequently identified chronic conditions were hypertension (31.0%), fluid and electrolyte disorders (28.5%), obesity (12.1%), chronic pulmonary disease (12.0%), uncomplicated diabetes (11.7%), depression (11.2%), and deficiency anemias (11.0%). Index admission outcomes As shown in Table 3, the majority of patients (51.1%) were discharged between 3 and 6 days after admission, and 81.4% of discharges after the index admission were routine discharges to home. Notably, 10.8% (n = 2,037) of meningitis patients had a medical error code recorded during the index admission, 3.2% (n = 612) had medical care errors, and 7.9% (n = 1,482) had documented injuries from medical drugs. Mechanical
ARTICLE IN PRESS D.E. Ellis et al. / American Journal of Infection Control 00 (2019) 1−7 Table 1 Index characteristics of meningitis patients eligible for 30- and 90-day readmission analyses (2014 National Readmissions Database)
Characteristics Age (y) 18-24 25-34 35-44 45-54 55-64 65-74 75-84 85+ Sex Male Female Primary payer Medicare Medicaid Private insurance Other Zip Code income quartile $1-$37,999 $38,000-$47,999 $48,000-$63,999 $64,000+ Control/ownership of hospital Government, nonfederal Private, not-for-profit Private, for-profit Hospital bed size Small Medium Large Teaching status Metropolitan non-teaching Metropolitan teaching Non-metropolitan
Eligible for 30-day readmission analyses n (%)
Table 2 Index clinical characteristics of meningitis patients eligible for 30- and 90-day readmission analyses (2014 National Readmissions Database)
Eligible for 90-day readmission analyses n (%) Clinical characteristics
2,663 (14.1) 4,385 (23.2) 3,532 (18.7) 3,219 (17.0) 2,469 (13.1) 1,489 (7.9) 826 (4.4) 301 (1.6)
2,196 (14.1) 3,605 (23.1) 2,904 (18.6) 2,705 (17.3) 2,035 (13.0) 1,247 (8.0) 687 (4.4) 236 (1.5)
8,401 (44.5) 10,482 (55.5)
6,963 (44.6) 8,651 (55.4)
3,331 (17.6) 3,579 (19.0) 9,498 (50.3) 2,476 (13.1)
2,757 (17.7) 2,936 (18.8) 7,837 (50.2) 2,085 (13.4)
4,660 (24.7) 5,070 (26.8) 4,728 (25.0) 4,426 (23.4)
3,942 (25.2) 4,213 (27.0) 3,880 (24.8) 3,580 (22.9)
2,563 (13.6) 14,025 (74.3) 2,296 (12.2)
2,143 (13.7) 11,594 (74.2) 1,878 (12.0)
2,883 (15.3) 5,141 (27.2) 10,860 (57.5)
2,340 (15.0) 4,185 (26.8) 9,090 (58.2)
5,349 (28.3) 12,228 (64.8) 1,307 (6.9)
4,369 (28.0) 10,166 (65.1) 1,080 (6.9)
ventilation, seizure, and cEEG use were uncommon, documented in 3.0%, 6.1%, and 0.3% cases, respectively, of hospitalizations. 30-Day readmission The all-cause 30-day non-elective readmission rate among meningitis inpatients was 7.0%. As shown in Table 4, the readmission rate was lowest among individuals ages 18 to 24 (4.1%) and highest among individuals ages 85 and older (13.2%). Readmission did not vary by sex. Medicare and Medicaid program participants and individuals from the lowest income neighborhoods had higher than average 30-day readmission rates (13.2%, 8.3%, and 8.4%, respectively). The readmission rates of persons requiring advanced post-acute care—inpatient postacute care or home health care—were nearly twice the average (14.9% and 12.5%, respectively). Readmission rates increased with comorbidity burden, from 4.0% (n = 397) among persons with 0 or 1 comorbid condition to 15.2% (n = 471) among those with 4 or more comorbid conditions. Readmission rates also increased with increasing index length of stay (Table 4). Eleven percent of persons with an adverse event documented during their index admission were readmitted, compared to 6.6% of those without adverse event codes. Logistic regression models that included variables for patient, clinical, and hospital characteristics found that public insurance program participation (Medicare adjusted odds ratio [AOR] = 1.85, 95% CI, 1.30-2.62; Medicaid AOR = 1.48, 95% CI, 1.16-1.90 vs private insurance) and Elixhauser scores of 4 or more (AOR = 2.68; 95% CI, 2.043.51), 3 (AOR = 1.92; 95% CI, 1.43-2.58), or 2 (AOR = 1.60; 95% CI, 1.242.08) were associated with greater odds of readmission. Discharge to
3
Elixhauser Comorbidity Index score 0-1 condition 2 conditions 3 conditions 4+ conditions Chronic conditions AIDS Alcohol abuse Deficiency anemias Rheumatoid arthritis/collagen vascular diseases Chronic blood loss anemia Congestive heart failure Chronic pulmonary disease Coagulopathy Depression Diabetes, uncomplicated Diabetes, complicated Drug abuse Hypertension Hypothyroidism Liver disease Lymphoma Fluid and electrolyte disorders Metastatic cancer Neurological disorders Obesity Paralysis Peptic ulcer disease excluding bleeding Peripheral vascular disorders Psychoses Pulmonary circulation disorders Renal failure Solid tumor without metastasis Valvular disease Weight loss
Eligible for 30-day readmission analyses n (%)
Eligible for 90-day readmission analyses n (%)
10,022 (53.1) 3,327 (17.6) 2,425 (12.8) 3,109 (16.5)
8,307 (53.2) 2,723 (17.4) 1,991 (12.7) 2,595 (16.6)
101 (0.5) 477 (2.5) 2,082 (11.0) 606 (3.2)
74 (0.5) 400 (2.6) 1,769 (11.3) 511 (3.3)
71 (0.4) 383 (2.0) 2,274 (12.0) 835 (4.4) 2,114 (11.2) 2,206 (11.7) 416 (2.2) 1,018 (5.4) 5,862 (31.0) 1,522 (8.1) 416 (2.2) 167 (0.9) 5,383 (28.5) 163 (0.9) 84 (0.4) 2,289 (12.1) 316 (1.7) —*
56 (0.4) 342 (2.2) 1,895 (12.1) 679 (4.3) 1,704 (10.9) 1,816 (11.6) 365 (2.3) 851 (5.4) 4,846 (31.0) 1,267 (8.1) 345 (2.2) 131 (0.8) 4,461 (28.6) 130 (0.8) 70 (0.4) 1,872 (12) 276 (1.8) —*
335 (1.8) 750 (4.0) 152 (0.8) 773 (4.1) 162 (0.9) 339 (1.8) 415 (2.2)
280 (1.8) 612 (3.9) 121 (0.8) 655 (4.2) 108 (0.7) 270 (1.7) 363 (2.3)
*The Healthcare Cost and Utilization Project data use agreement prevents printing cells with n < 10.
Table 3 Outcomes associated with meningitis patients eligible for 30- and 90-day readmission analyses (2014 National Readmissions Database)
Outcomes Length of stay (d) 2 3-6 >7 Disposition after index admission Routine to home Transfer to short-term hospital or other facility Home health care Other Complications E code during index admission (any) E codes for medical errors/CCS 2616 E codes for drug errors/CCS 2617 Specific complications Mechanical ventilation Seizure Continuous electroencephalography
Eligible for 30-day readmission analyses n (%)
Eligible for 90-day readmission analyses n (%)
5,636 (29.8) 9,654 (51.1) 3,594 (19)
4,604 (29.5) 7,989 (51.2) 3,022 (19.4)
15,379 (81.4) 1,435 (7.6)
12,708 (81.4) 1,184 (7.6)
1,806 (9.6) 262 (1.4)
1,498 (9.6) 224 (1.4)
2,037 (10.8) 612 (3.2) 1,482 (7.9)
1,678 (10.7) 504 (3.2) 1,219 (7.8)
570 (3.0) 1,157 (6.1) 64 (0.3)
497 (3.2) 978 (6.3) 54 (0.3)
4
Table 4 Factors associated with 30- and 90-day non-elective readmissions after hospitalization for meningitis (2014 National Readmissions Database)* 30-day non-elective readmission
Characteristics
Percent readmitted (overall = 11.4%)
Adjusted odds ratio of readmission (95% CI)
4.1 5.4 5.8 7.5 9.1 11.7 12.1 13.2
Ref. 1.28 (0.86-1.89) 1.20 (0.81-1.78) 1.28 (0.87-1.89) 1.25 (0.81-1.93) 0.94 (0.57-1.56) 0.84 (0.49-1.43) 0.81 (0.40-1.65)
2,196 3,605 2,904 2,705 2,035 1,247 687 236
127 241 264 306 272 251 135 58
5.8 6.7 9.1 11.3 13.3 20.1 19.7 24.4
Ref. 1.07 (0.74-1.55) 1.26 (0.89-1.79) 1.29 (0.90-1.84) 1.12 (0.74-1.7) 0.95 (0.60-1.49) 0.75 (0.46-1.23) 0.89 (0.47-1.7)
599 735
7.1 7.0
Ref. 0.99 (0.81-1.22)
6,963 8,651
767 886
11.0 10.2
Ref. 0.93 (0.77-1.12)
3,331 3,579 9,498 2,476
441 298 459 136
13.2 8.3 4.8 5.5
1.85 (1.30-2.62)** 1.48 (1.16-1.90)** REF 1.06 (0.74-1.50)
2,757 2,936 7,837 2,085
613 349 521 170
22.2 11.9 6.7 8.1
2.09 (1.53-2.86)** 1.50 (1.20-1.88)** REF 1.10 (0.80-1.51)
4,660 5,070 4,728 4,426
394 385 288 268
8.4 7.6 6.1 6.1
1.20 (0.91-1.59) 1.19 (0.92-1.54) 1.00 (0.75-1.32) Ref.
3,942 4,213 3,880 3,580
529 440 385 300
13.4 10.4 9.9 8.4
1.48 (1.15-1.90)** 1.22 (0.95-1.57) 1.22 (0.93-1.61) Ref.
15,379 1,435 1,806 262
847 (5.5) 214 (14.9) 226 (12.5) 47 (17.9)
5.5 14.9 12.5 17.9
Ref. 1.44 (1.06-1.95)** 1.64 (1.26-2.13)** 3.09 (1.82-5.24)**
12,708 1,184 1,498 224
1,029 308 267 49
8.1 26.0 17.9 21.8
Ref. 1.59 (1.20-2.12)** 1.50 (1.16-1.95)** 2.58 (1.51-4.4)**
10,022 3,327 2,425 3,109
397 236 230 471
4.0 7.1 9.5 15.2
Ref. 1.60 (1.24-2.08)** 1.92 (1.43-2.58)** 2.68 (2.04-3.51)**
8,307 2,723 1,991 2,595
431 246 322 654
5.2 9.0 16.2 25.2
Ref. 1.51 (1.17-1.96)** 2.55 (1.94-3.35)** 3.55 (2.76-4.58)**
5,636 9,654 3,594
294 574 466
5.2 5.9 13.0
Ref. 0.92 (0.71-1.18) 1.30 (0.93-1.80)
4,604 7,989 3,022
320 719 614
7.0 9.0 20.3
Ref. 1.00 (0.78-1.27) 1.34 (0.99-1.82)
5,349 12,228 1,307
323 922 88
6.0 7.5 6.7
0.86 (0.70-1.05) Ref. 0.85 (0.55-1.31)
4,369 10,166 1,080
426 1,131 96
9.7 11.1 8.9
0.96 (0.80-1.16) Ref. 0.70 (0.46-1.06)
16,846 2,037
1,105 228
6.6 11.2
Ref. 1.43 (1.07-1.91)**
13,936 1,678
1,380 273
9.9 16.3
Ref. 1.33 (1.02-1.74)**
18,272 612
1,258 76
6.9 12.4
Ref. 1.61 (0.94-2.74)
15,110 504
1,566 87
10.4 17.3
Ref. 1.47 (0.91-2.40)
Percent readmitted (overall = 7.0%)
2,663 4,385 3,532 3,219 2,469 1,489 826 301
110 237 206 241 225 174 100 40
8,401 10,482
(continued on next page)
ARTICLE IN PRESS
Adjusted odds ratio of readmission (95% CI)
Number readmitted (N = 1,653)
Number readmitted (N =1,334)
D.E. Ellis et al. / American Journal of Infection Control 00 (2019) 1−7
Age (y) 18-24 25-34 35-44 45-54 55-64 65-74 75-84 85+ Sex Male Female Payer Medicare Medicaid Private Other Zip Code income quartile $1-$37,999 $38,000-$47,999 $48,000-$63,999 $64,000+ Index stay disposition Home Inpatient post-acute care Home health care Other/unknown Elixhauser Comorbidity Index score 0-1 condition 2 conditions 3 conditions 4+ conditions Length of index stay (d) <3 3-6 >6 Teaching status Metropolitan non-teaching Metropolitan teaching Non-metropolitan Any E code during index admission Absent Present E codes for medical care E8700-E8799/CCS 2616 Absent Present
90-day non-elective readmission Total population (index admissions) (N = 15,614)
Total population (index admissions) (N = 18,883)
ARTICLE IN PRESS 5
an inpatient facility (AOR = 1.44; 95% CI, 1.06-1.95) or home health care (AOR = 1.64; 95% CI, 1.26-2.13) or documentation of an adverse event (AOR = 1.43; 95% CI, 1.07-1.91) were also positively associated with readmission. Patient descriptors, hospital characteristics, and diagnoses indicating more severe clinical courses were not significantly associated with readmission in our adjusted models.
0.79 (0.49-1.29) 0.68 (0.24-1.93) 1.37 (1.06-1.79)**
Ref. 1.28 (0.97-1.70)
Adjusted odds ratio of readmission (95% CI)
D.E. Ellis et al. / American Journal of Infection Control 00 (2019) 1−7
*Adjusted for sex, Elixhauser Comorbidity Index score, index disposition, length of stay, insurance, Zip Code income quartile, and readmission hospital teaching status. y The Healthcare Cost and Utilization Project data use agreement prevents printing cells with n < 10. **Indicates p < 0.05 statistical significance.
20.1 —y 24.7 100 —y 242 497 54 978 55 —y 168 570 64 1,157
9.7 —y 14.5
0.59 (0.33-1.06) 0.35 (0.09-1.44) 1.22 (0.89-1.66)
10.1 16.3 1,454 199 14,395 1,219 1,173 161
E codes for adverse effects of medical drugs E9300-E9499/CCS 2617 Absent Present Specific complications (yes vs no) Mechanical ventilation Continuous electroencephalography Seizure
17,401 1,482
6.7 10.8
Ref. 1.30 (0.97-1.74)
Percent readmitted (overall = 11.4%) Number readmitted (N = 1,653) Total population (index admissions) (N = 15,614) Adjusted odds ratio of readmission (95% CI) Percent readmitted (overall = 7.0%) Number readmitted (N =1,334) Characteristics
Table 4 (Continued)
Total population (index admissions) (N = 18,883)
30-day non-elective readmission
90-day non-elective readmission
90-Day readmission The study sample eligible for 90-day readmissions had sociodemographic, clinical, and hospital characteristics that were nearly identical to those described for the 30-day sample above (Table 1). The 90-day unplanned readmission rate was 11.4% (n = 1,653), among 15,614 eligible patients. As shown in Table 4, 64.2% (n = 444) of persons readmitted within 90 days after discharge for meningitis were ages 65 and above. Public insurance (Medicare or Medicaid), residence in a neighborhood with median income less than $37,999, non-routine discharge, documentation of a medical error, increasing Elixhauser comorbidity scores, and documentation of seizure were all associated with increased odds of readmission within 90 day (Table 4). Readmission diagnoses Table 5 displays the top 10 primary readmission diagnoses for both 30- and 90-day readmission analyses. The reasons for readmission were diverse, with no clinical condition observed more frequently than 11.6%. Readmissions were most often for meningitis (11.6% of readmissions at 30 days and 10.3% of readmissions at 90 days), followed by septicemia. DISCUSSION The results from this national analysis increase our understanding of adult meningitis in the United States by providing key data on patient characteristics, clinical, and hospitalization outcomes, including readmissions. Comorbid disease burden and experiencing a medical adverse event were positively associated with readmission. Readmissions were most often for infection or complications of initial care. We found national 30- and 90-day readmission rates of 7.0% and 11.4%, respectively, among adults receiving inpatient meningitis care. A HCUP statistical brief reported a 30-day all-cause readmission rate after meningitis hospitalization of 7.8% in 2010.16 A study conducted using the Premier Healthcare Database (PHD) spanning the years 2011 through 2014 found the 30-day all-cause readmission rate for meningitis or encephalitis to be 3.2%.17 To understand how our estimates differ from these, it must be understood that these other studies used different study populations, readmission definitions, and time frames. The HCUP study included adults and children, whereas the PHD study estimates were for infants and children only. We have produced estimates for adults, filling a gap in the literature. With respect to readmission definitions, the HCUP study, like our study, captured all readmissions within the same state. However, the PHD study included only readmissions to the same index hospital, which would result in lower estimates. Our analysis was conducted for 2014, whereas the HCUP and PHD estimates were obtained from 2010 and 2011-2014, respectively. Although the incidence of bacterial meningitis has declined since 1997 due to vaccination,8 it is unclear if this would impact readmissions in any way. Overall 30-day readmissions also have been decreasing with time.18 Consequently, a future trend analysis should be conducted exploring whether there have been any changes in readmission rates for meningitis. Our data suggest that 30-day readmission rates for meningitis (7.0%) are lower than those estimated for more prevalent infectious diseases, including septicemia (2014 rate = 18.9%), urinary tract infections (2014 rate = 15.7%), and pneumonia (2014 rate = 15.5%).19
ARTICLE IN PRESS D.E. Ellis et al. / American Journal of Infection Control 00 (2019) 1−7
6
Table 5 Clinical conditions associated with 30- and 90-day unplanned readmissions (2014 National Readmissions Database) 30-Day readmission analyses
90-Day readmission analyses
Rank
Condition
n (%)
Condition
n (%)
1
Meningitis (except that caused by tuberculosis or sexually transmitted disease) Septicemia (except in labor) Complications of surgical procedures or medical care Headache, including migraine
154 (11.6)
Meningitis (except that caused by tuberculosis or sexually transmitted disease) Septicemia (except in labor) Headache, including migraine
170 (10.3)
Complications of surgical procedures or medical care Epilepsy, convulsions Other nervous system disorders
88 (5.3)
Complication of device, implant or graft Encephalitis (except that caused by tuberculosis or sexually transmitted disease) Acute cerebrovascular disease Pneumonia (except that caused by tuberculosis or sexually transmitted disease)
51 (3.1) 49 (3.0)
2 3 4 5 6
107 (8.0) 90 (6.7) 89 (6.7) 61 (4.6) 57 (4.3)
7 8
Other nervous system disorders Encephalitis (except that caused by tuberculosis or sexually transmitted disease) Epilepsy, convulsions Complication of device, implant or graft
9 10
Acute cerebrovascular disease Acute and unspecified renal failure
33 (2.5) 30 (2.2)
Total
46 (3.5) 34 (2.6)
1,334 (1,334/18,884 = 7.1% readmission rate)
Readmission rates for meningitis in our study were also lower than the overall rate of 30-day all-cause readmissions in 2014 (14.0%).19 Factors related to 30- or 90-day readmission in fully adjusted regression models included comorbid disease burden, initial discharge location, and adverse events. Comorbidities are often incorporated into predictive models of hospital readmission.20 In prior studies of meningitis, age was found to be a prognostic factor for adverse clinical outcomes,2,3,9,10,21 and comorbidities increase with age.22 Additionally, meningitis is particularly challenging to manage in older adults with other chronic conditions.21 In our sample, readmission rates were highest among older adults; however, age was not associated with readmission in the adjusted analyses. These findings suggest that premorbid health state may be a more important driver of readmissions than age. Surprisingly, those with an index stay discharge to home health care had significantly higher odds of readmission compared to those discharged home or to inpatient post-acute care. Home health care aims to reduce the risk of readmissions; however, the success of this goal is partially dependent on adequate communication between home health care providers and physicians.23 The needs of sicker patients discharged to home health care after hospitalization for meningitis may be insufficiently met. Further study is needed to determine which patients would more adequately benefit from inpatient post-acute care. In the 30-day readmission analysis, 10.8% of patients experienced an adverse event. Despite adjusting for covariates, adverse events during the index hospitalization significantly increased the odds for both 30- and 90-day readmissions. Also, complications of surgical procedures or medical care were the third and fourth most common reasons for readmission in this study. Medical errors are particularly common in critical care settings, with one prospective cohort study finding a 1-year incidence of 20.2%.24 We could not determine with certainty whether patients were admitted to an intensive care unit in this dataset; however, meningitis patients, particularly bacterial meningitis patients, are likely to be critically ill and receive higher level inpatient care. Diagnostic procedures for meningitis also carry established risks. Headache is a common complication of lumbar puncture and was a common reason for readmission.25-27 Brain herniation and local tissue injury are also possible after lumbar puncture.28 Neuroimaging carries a risk of allergic or toxic reaction to intravenous contrast agents. Antibiotics necessary to treat meningitis may cause liver or kidney injury or allergic reactions. Clinical
134 (8.1) 99 (6.0)
67 (4.0) 65 (3.9)
49 (3.0) 34 (2.1) 1,653 (1,653/15,615 = 10.6% readmission rate)
monitoring of a meningitis patient requires regular blood sampling. Patient, provider, clinical treatment, environmental, and organizational factors (such as provider experience, medications administered, or patient-to-nurse ratio) can lead to medication errors or procedure complications.11 We were unable to examine these factors with this dataset, but future analyses using data containing these variables may identify intervenable processes associated with readmission or unfavorable clinical outcomes. Alternatively, given the low absolute number of readmissions due to complications of medical care, our estimates of medical error−related readmissions may be within the acceptable range for care of a condition that requires invasive diagnostic tests and multiple drug exposures. Although meningitis can be severe, our analysis suggests that readmissions may not be dependent on index disease severity, as marked by cEEG monitoring, ventilation, or seizure, but instead on medical care− related factors such as medical procedures, devices, medications, and secondary infections. The only indicator of a complicated index hospitalization that was significantly associated with readmission was seizure, at 90 days. This supports the policy of using readmission rates to measure and compare hospital quality within and between hospitals, because readmission rates do not seem to reflect disease severity or diagnosis in this case. Datasets that support hierarchical analyses (nesting of patients within individual hospitals) are needed to confirm and explore this finding further. However, given the association between comorbidities and readmission, as well as insurance type and readmission, it is important that any comparisons be case-mix adjusted. Meningitis was the most common documented reason for readmission in this national sample. Other infections ranking in the top 10 for either the 30-day or 90-day readmissions included septicemia, encephalitis, and pneumonia. With this dataset, we cannot determine if infections are a consequence of a new primary infection (hospitalor community-acquired) or recurrent infection. Recurrent bacterial meningitis is known to occur in about 5%-6% of adults.28 In our study, the proportion of readmissions with recurrent meningitis at 30 days was 11.6%. Baseline health status, particularly the presence of immunocompromising comorbid diseases, is likely an important contributor to post-discharge infection risk. Ensuring appropriate empiric and final antibiotic prescribing may also reduce such readmissions.29 Because our national dataset did not include laboratory or imaging data, we were unable to corroborate meningitis etiologies (bacterial, viral, fungal) or extent of disease (meningitis, meningoencephalitis,
ARTICLE IN PRESS D.E. Ellis et al. / American Journal of Infection Control 00 (2019) 1−7
encephalitis). Consequently, we did not stratify our results by meningitis type. Repeat infections may be preventable, underscoring the importance of further study of infection-related readmissions. CONCLUSIONS In this study, we leveraged nationally representative data on inpatient care to produce, as far as we know, the first national-level data on short-term hospitalization outcomes among adults with meningitis in the United States. Our overall findings suggest that readmissions may not be dependent on index disease severity but rather on patient baseline health state and medical care−related factors. Yet, it is important to emphasize the limitations of our study. Data that are generated for billing or documentation of care or services, as found in billing claims or medical records, are subject to coding error or bias. Administrative datasets such as the NRD may not provide clinical details on disease severity or physical function, or may contain these data in an incomplete or biased fashion. All retrospective studies are subject to these limitations, and methods to increase data comprehensiveness (eg, patient registries, academic center based studies) directly oppose approaches to produce national estimates or improve external validity. Also, we present the most recent data, which could represent a decline in readmissions in response to changes in clinical guidelines for meningitis prevention and treatment or to readmission reduction strategies and penalties. Future trend analyses will allow stakeholders to place our findings in the appropriate historical context and guide the development of interventions targeting medical care, social support, or patient predisposing factors. In spite of these limitations, these data will likely become the benchmark for future public health or health service research evaluations of hospitalization outcomes for meningitis in the adult population. Acknowledgments Ms. Lia Weil assisted with background literature searches. Mr. Derrick Tam assisted with background literature search and manuscript formatting. References 1. Zueter AM, Zaiter A. Infectious meningitis. Clin Microbiol Newsl 2015;37:43-51. 2. van de Beek D, de Gans J, Spanjaard L, Weisfelt M, Reitsma JB, Vermeulen M. Clinical features and prognostic factors in adults with bacterial meningitis. N Engl J Med 2004;351:1849-59. 3. Weisfelt M, van de Beek D, Spanjaard L, Reitsma JB, de Gans J. Communityacquired bacterial meningitis in older people. J Am Geriatr Soc 2006;54:1500-7. 4. Wang AY, Machicado JD, Khoury NT, Wootton SH, Salazar L, Hasbun R. Community-acquired meningitis in older adults: clinical features, etiology, and prognostic factors. J Am Geriatr Soc 2014;62:2064-70. 5. van de Beek D, Schmand B, de Gans J, Weisfelt M, Vaessen H, Dankert J, et al. Cognitive impairment in adults with good recovery after bacterial meningitis. J Infect Dis 2002;186:1047-52. 6. Aronin SI, Peduzzi P, Quagliarello VJ. Community-acquired bacterial meningitis: risk stratification for adverse clinical outcome and effect of antibiotic timing. Ann Intern Med 1998;129:862-9.
7
dos JP, et al. Pneumo7. Auburtin M, Porcher R, Bruneel F, Scanvic A, Trouillet JL, Be coccal meningitis in the intensive care unit: prognostic factors of clinical outcome in a series of 80 cases. Am J Respir Crit Care Med 2002;165:713-7. 8. Castelblanco RL, Lee M, Hasbun R. Epidemiology of bacterial meningitis in the USA from 1997 to 2010: a population-based observational study. Lancet Infect Dis 2014;14:813-9. 9. Durand ML, Calderwood SB, Weber DJ, Miller SI, Southwick FS, Caviness VS Jr, et al. Acute bacterial meningitis in adults. A review of 493 episodes. N Engl J Med 1993;328:21-8. 10. Sigurdardottir B, Bjornsson OM, Jonsdottir KE, Erlendsdottir H, Gudmundsson S. Acute bacterial meningitis in adults. A 20-year overview. Arch Intern Med 1997;157:425-30. 11. Hasbun R, Rosenthal N, Balada-Llasat JM, Chung J, Duff S, Bozzette S, et al. Epidemiology of meningitis and encephalitis in the United States, 2011-2014. Clin Infect Dis 2017;65:359-63. 12. U.S. Centers for Medicare & Medicaid Services. Hospital Readmissions Reduction Program (HRRP). Available from: https://www.cms.gov/medicare/medicare-feefor-service-payment/acuteinpatientpps/readmissions-reduction-program.html. Accessed November 7, 2019. 13. Healthcare Cost and Utilization Project (HCUP). NRD overview. Available from: www.hcup-us.ahrq.gov/nrdoverview.jsp. Accessed November 7, 2019. 14. Healthcare Cost and Utilization Project (HCUP). HCUP Clinical Classification Software (CCS) for ICD-9-CM. Available from: http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp. Accessed November 7, 2019. 15. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care 1998;36:8-27. 16. Elixhauser A, Steiner C. Readmissions to U.S. hospitals by diagnosis, 2010: statistical brief #153. Healthcare Cost and Utilization Project (HCUP) statistical briefs. Rockville (MD): Agency for Healthcare Research and Quality; 2006. 17. Hasbun R, Wootton SH, Rosenthal N, Balada-Llasat JM, Chung J, Duff S, et al. Epidemiology of meningitis and encephalitis in infants and children in the United States, 2011-2014. Pediatr Infect Dis J 2019;38:37-41. 18. Fingar K, Washington R. Trends in hospital readmissions for four high-volume conditions, 2009-2013: statistical brief #196. Healthcare Cost and Utilization Project (HCUP) statistical briefs. Rockville (MD): Agency for Healthcare Research and Quality; 2006. 19. Fingar KR, Barrett ML, Jiang HJ. A comparison of all-cause 7-day and 30-day readmissions, 2014: statistical brief #230. Healthcare Cost and Utilization Project (HCUP) statistical briefs. Rockville (MD): Agency for Healthcare Research and Quality; 2006. 20. Kansagara D, Englander H, Salanitro A, Kagen D, Theobald C, Freeman M, et al. Risk prediction models for hospital readmission: a systematic review. JAMA 2011;306: 1688-98. 21. Domingo P, Pomar V, de Benito N, Coll P. The spectrum of acute bacterial meningitis in elderly patients. BMC Infect Dis 2013;13:108. 22. Ashman JJ, Beresovsky V. Multiple chronic conditions among US adults who visited physician offices: data from the National Ambulatory Medical Care Survey, 2009. Prev Chronic Dis 2013;10:E64. 23. Pesko MF, Gerber LM, Peng TR, Press MJ. Home health care: nurse-physician communication, patient severity, and hospital readmission. Health Serv Res 2018;53: 1008-24. 24. Rothschild JM, Landrigan CP, Cronin JW, Kaushal R, Lockley SW, Burdick E, et al. The Critical Care Safety Study: the incidence and nature of adverse events and serious medical errors in intensive care. Crit Care Med 2005;33:1694-700. 25. Ahmed SV, Jayawarna C, Jude E. Post lumbar puncture headache: diagnosis and management. Postgrad Med J 2006;82:713-6. 26. Leibold RA, Yealy DM, Coppola M, Cantees KK. Post-dural-puncture headache: characteristics, management, and prevention. Ann Emerg Med 1993;22:1863-70. 27. Kuntz KM, Kokmen E, Stevens JC, Miller P, Offord KP, Ho MM. Post-lumbar puncture headaches: experience in 501 consecutive procedures. Neurology 1992;42: 1884-7. 28. Tebruegge M, Curtis N. Epidemiology, etiology, pathogenesis, and diagnosis of recurrent bacterial meningitis. Clin Microbiol Rev 2008;21:519-37. 29. Tunkel AR, Hartman BJ, Kaplan SL, Kaufman BA, Roos KL, Scheld WM, et al. Practice guidelines for the management of bacterial meningitis. Clin Infect Dis Epub 2004;39:1267-84.