Abstract
Objective:
Administrative claims data are used to study the incidence and outcomes of dementia-related hallucinations, but the validity of International Classification of Diseases (ICD) codes for identifying dementia-related hallucinations is unknown.
Methods:
We analyzed Medicare-linked survey data from two nationally representative studies of U.S. older adults (the National Health and Aging Trends Study and the Health and Retirement Study) which contain validated cognitive assessments and a screening question for hallucinations. We identified older adults who had dementia or were permanent nursing home residents, and we combined this with questionnaire responses to define dementia-related hallucinations. Using Medicare claims data, we calculated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ICD codes for dementia-related hallucinations overall and within prespecified strata of age, neurologic comorbidity, and health care utilization.
Results:
We included 2,337 older adults with dementia in our cohort. Among 3,789 person-years of data, 1,249 (33.0%) had hallucations, and of these 286 had a qualifying ICD code for dementia-related hallucinations or psychosis (sensitivity 22.9%). Of 2,540 person-years of dementia without hallucinations, 284 had a diagnosis code for hallucinations (specificity 88.8%). PPV was 50.2%, and NPV was 70.1%. Sensitivity was greatest (57.0%) among those seeing a psychiatrist. Otherwise, there were no significant differences in sensitivity, specificity, PPV, or NPV by age, neurologic diagnosis, or neurologist care.
Conclusion:
Dementia-related hallucinations are poorly captured in administrative claims data, and estimates of their prevalence and outcomes using these data are likely to be biased.
Keywords: Medicare, dementia, hallucinations, validity, sensitivity, specificity
OBJECTIVE
Parkinson disease (PD) and Alzheimer disease (AD) currently affect over 6 million older adults in the U.S. (1,2), and one in five patients with AD and up to half of those with PD experience hallucinations and other symptoms of psychosis during their lifetime (3,4). Dementia-related hallucinations are a leading source of patient and caregiver distress and an independent risk factor for falls, hip fracture, nursing home placement, and death (5–8). Administrative claims data (e.g., Medicare) have been used to quantify this burden and measure the healthcare utilization patterns and health outcomes associated with hallucinations (9–14). However, the diagnosis codes used to identify dementia-related hallucinations and psychosis in administrative datasets have not been validated. Because International Classification of Diseases (ICD) codes were developed primarily for billing rather than clinical research use, they are prone to misclassification error. This is especially true of hallucinations, which are under-reported in clinical practice due to perceived stigma and embarrassment (15,16), and providers may code for the underlying cause of hallucinations (i.e., AD or PD) rather than the symptoms themselves. While the spontaneous reporting of hallucinations by patients and caregivers is a major limitation, systematic screening through the use of structured questionnaires improves their detection (17,18). In this study, we use screening cognitive and neuropsychiatric inventory data with linked Medicare claims from a nationally representative sample of older adults to determine the validity of ICD codes for dementia-related hallucinations in administrative claims data.
METHODS:
Standard Protocol Approvals, Registrations, and Patient Consents
This study was approved by the University of Pennsylvania Institutional Review Board. Informed consent was previously obtained at the time of study enrollment and was not separately required for this secondary analysis.
Study Overview and Data
We analyzed patient-reported outcomes and linked Medicare claims data from two longitudinal surveys of the older U.S. adult population: the National Health and Aging Trends Study (NHATS) and the Health and Retirement Study (HRS). We used validated assessments of cognitive status and proxy-informed hallucinations to define dementia-related hallucinations, and to determine the validity of ICD codes for dementia-related hallucinations, we compared these assessments to corresponding ICD-9 and ICD-10 codes in Medicare claims data.
NHATS is a nationally representative sample of Medicare beneficiaries aged 65 or older who have been surveyed annually since 2011, with replenishment of the sample in 2015 (19). The Health and Retirement Study (HRS) is a large, nationally representative longitudinal survey of U.S. adults over the age of 50 (20). It is the result of two surveys from 1992–1996, HRS and Asset and Health Dynamics among the Oldest Old (AHEAD), which were merged in 1998. Participants have been re-surveyed biennially, with replenishment in 1998, 2004, 2010, and 2016. For this study, we used data from NHATS 2011–2017 and HRS 1996–2016.
The Medicare program is the primary insurer for 97% of the U.S. population ages 65 and above. Medicare linkage is available for all NHATS participants and for the subset of HRS participants who are Medicare-eligible and consent to data linkage (>80%). We used the Master Beneficiary Summary File (MBSF) to obtain Medicare enrollment and eligibility information, the carrier file to obtain outpatient (Part B) diagnosis and provider codes, and Part D eligibility and claims files to obtain prescription drug information.
Inclusion and exclusion criteria
Study inclusion and exclusion criteria are summarized in Figure 1. We included all NHATS and HRS respondents who had data on the presence or absence of hallucinations, were linkable to Medicare, and had evidence of dementia or were permanent nursing home residents (as described below). We excluded individuals who had a claim for a primary psychotic disorder such as schizophrenia. For Medicare claims to be eligible for analysis, we required subjects to have complete (12 months) of Part A and B coverage. If the reason for incomplete coverage was that the subject died during the survey year, we used the previous year’s claims data for eligibility and analysis.
Figure 1:
Flowchart of eligibility criteria for Medicare-linked NHATS and HRS study participants
Definition of dementia-related hallucinations
The NHATS and HRS survey questionnaires include a number of screening items that assess cognitive function. These include questions about self-reported cognitive difficulties (e.g., trouble remembering appointments or handling finances), physician diagnoses of AD or related dementia, and in-person cognitive testing (e.g., orientation, delayed recall, clock drawing). NHATS and HRS have developed algorithms that combine individual survey items to predict the presence or absence of dementia. These algorithms have been validated against clinically diagnosed dementia in the Aging, Demographics, and Memory Study (21,22). NHATS classifies dementia status as “probable dementia”, “possible dementia”, or “no dementia”, and the HRS Langa-Weir classification system categorizes cognitive function as “dementia”, “cognitively impaired but not demented”, and “normal”. For this study, we defined dementia as a rating of “probable dementia” in NHATS or “dementia” in HRS, hereafter referred to collectively as dementia.
In both NHATS and HRS, if a study participant is unable to complete the cognitive assessment independently, a proxy (i.e., spouse, child, or caregiver) is allowed to assist, and several additional questions about cognitive function are asked (proxy cognitive questionnaire). One of these questions assesses for the presence of hallucinations: “In the last year, do you/does he or she ever see or hear things that are not there?” A trained rater incorporates both patient and proxy observations in recording a response to this question. We used an affirmative response on this item together with a validated dementia rating to identify dementia-related hallucinations.
Claims data were queried for each person in our cohort of NHATS and HRS respondents. Using the carrier file, we identified a claim for dementia-related hallucinations as occurring when an ICD-9 or ICD-10 code for hallucinations or psychosis (eTable in the Supplemental Digital Content) was coupled with an outpatient healthcare encounter led by a physician or advanced practice provider. We examined claims that occurred during the same calendar year as the NHATS or HRS survey visit (or in the year prior if death occurred during the survey year) in order to match the one-year lookback period of the hallucinations question. While we included permanent nursing home residents in our cohort, we limited eligible diagnosis codes to those that were registered in the outpatient setting and did not include inpatient or skilled nursing facility claims due to the high prevalence of delirium in this setting, which can cause transient hallucinations and psychosis outside the context of dementia-related psychosis.
Because NHATS and HRS are both longitudinal studies, subjects with dementia could complete multiple proxy cognitive questionnaires, and dementia-related hallucinations were treated as a time-varying outcome. For example, a subject with dementia may not have had hallucinations during one year but may subsequently have reported hallucinations in the following year. Medicare claims from the survey year were compared to the corresponding year’s questionnaire-based assessment of dementia-related hallucinations, and the statistical analysis accounted for repeated measures (see below). A schematic of the study design is found in the eFigure (Supplemental Digital Content).
Statistical Methods
Statistical analysis was performed using STATA/MP 16.1 (College Station, TX), and statistical significance was defined at the p<0.05 level. We combined NHATS and HRS data for analysis and compared the characteristics of individuals with and without dementia-related hallucinations using univariable generalized estimating equation (GEE) models with logit function and exchangeable correlation structure to account for intra-individual correlation across repeated survey measurements. We tabulated the number of subjects who had a corresponding ICD-9 or ICD-10 code and calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with exact (Clopper-Pearson) confidence intervals. We also explored the validity of ICD codes for dementia-related hallucinations within prespecified subpopulations defined by age; a diagnosis of PD or Lewy body disorder (LBD); encounters with a neurologist, psychiatrist, or geriatrician; and nursing home status. Because the sample was restricted to proxy cognitive questionnaire respondents, we did not apply NHATS and HRS sample weights to the analysis.
RESULTS:
We identified 650 NHATS participants and 1,687 HRS participants who met eligibility criteria (Figure 1) and contributed a combined 3,789 person-years of Medicare claims and survey response data to the analysis. The clinical, demographic, and health care utilization characteristics of older adults with and without hallucinations are presented in Table 1. Among 1,249 person-years with both dementia and hallucinations, 112 (9.0%) carried a concurrent diagnosis of PD or LBD, 254 (20.3%) had seen a neurologist within a given year, and 387 (30.3%) resided in an assisted living facility or nursing home.
Table 1:
Prevalence of dementia-related hallucinations and baseline characteristics, NHATS 2011–2017 and HRS 1996–2016
| No hallucinations | Hallucinations | Prevalence of hallucinations | P-value | |
|---|---|---|---|---|
| Total | 2,540 | 1,249 | 33.0% | |
| Age | 0.004 | |||
| <70 | 128 (5.0%) | 47 (3.8%) | 26.9% | |
| 70–74 | 227 (8.9%) | 89 (7.1%) | 28.2% | |
| 75–79 | 357 (14.1%) | 173 (13.9%) | 32.6% | |
| 80–84 | 483 (19.0%) | 227 (18.2%) | 32.0% | |
| 85–89 | 635 (25.0%) | 315 (25.2%) | 33.2% | |
| ≥90 | 710 (28.0%) | 39.8 (31.9%) | 35.9% | |
| Sex | <0.001 | |||
| Male | 918 (36.1%) | 338 (27.1%) | 26.9% | |
| Female | 1,622 (63.9%) | 911 (72.9%) | 36.0% | |
| Race | 0.035 | |||
| White | 1810 (71.3%) | 925 (74.1%) | 33.8% | |
| Black | 562 (22.1%) | 265 (21.2%) | 32.0% | |
| Other | 168 (6.6%) | 59 (4.7%) | 26.0% | |
| PD/DLB | 129 (5.1%) | 112 (9.0%) | 46.5% | <0.001 |
| Residential care/nursing home | 673 (26.5%) | 378 (30.3%) | 36.0% | 0.013 |
| Neurologist care | 483 (19.0%) | 254 (20.3%) | 34.5% | 0.40 |
| Psychiatrist care | 331 (13.0%) | 219 (17.5%) | 39.8% | <0.001 |
| Geriatrician care | 130 (5.1%) | 76 (6.1%) | 36.9% | 0.096 |
Note. Column percentages are indicated in parentheses in columns 2 and 3. P-values are for Wald chi-square tests with one degree of freedom obtained using univariable generalized estimation equation (GEE) models with logit model and exchangeable correlation structure comparing the odds of hallucinations associated with each independent variable.
Among 1,249 person-years of dementia-related hallucinations (defined using the gold standard of combined patient and proxy report), 286 had a qualifying ICD-9 or ICD-10 code for dementia-related hallucinations or psychosis (sensitivity 22.9%). By comparison, 284 of 2,540 person-years of dementia without hallucinations had a qualifying diagnosis code (specificity 88.8%). PPV was 50.2%, and NPV was 70.1%. Stratified measures of validity are presented in Table 2. Sensitivity was greatest (57.0%) among the subgroup of individuals who had seen a psychiatrist in a given year (n=550), but this was accompanied by a lower specificity (60.4%). Sensitivity, specificity, PPV, and NPV were similar when stratified by age, PD or DLB diagnosis, or neurologist care (Table 2).
Table 2:
Prevalence of ICD codes for dementia-related hallucinations stratified by patient subgroups, NHATS 2011–2016 and HRS 1996–2016
| Dementia-related hallucinations | Validity and predictive value (Clopper-Pearson 95% confidence intervals) | |||||||
|---|---|---|---|---|---|---|---|---|
| No | Yes | |||||||
| Medicare claim for hallucinations/psychosis | ||||||||
| Yes (n/N,%) | No (n/N,%) | Yes (n/N,%) | No (n/N,%) | Sensitivity | Specificity | PPV | NPV | |
| Total | 284/2540 (11.1%) | 2256/2540 (88.8%) | 286/1,249 (22.9%) | 963/1249 (77.1%) | 22.9% (20.1–25.3%) | 88.8% (87.5–90.0%) | 50.2% (46.0–54.4%) | 70.1% (68.5–71.7%) |
| Age | ||||||||
| <85 | 122/1,195 (10.2%) | 1073/1195 (89.8%) | 129/536 (24.1%) | 407/536 (75.9%) | 24.1% (20.1–27.9%) | 89.8% (87.9–91.4%) | 51.4% (45.0–57.7%) | 72.5% (70.1–74.8%) |
| ≥85 | 162/1,345 (12.0%) | 1183/1345 (88.0%) | 157/713 (22.0%) | 556/713 (78.0%) | 22.0% (19.0–25.2%) | 88.0% (56.1–89.6%) | 49.2% (43.6–54.8%) | 68.0% (65.8–70.2%) |
| PD/DLB | 25/129 (19.4%) | 104/129 (80.6%) | 32/112 (28.6%) | 80/112 (71.4%) | 28.6% (20.4–37.9%) | 80.6% (72.7–87.0%) | 56.1% (42.4–69.3%) | 56.5% (49.0–63.8%) |
| Neurologist care | 91/483 (18.8%) | 392/483 (81.2%) | 76/254 (29.9%) | 178/254 (70.0%) | 29.9% (24.4–36.0%) | 81.2% (77.4–84.6%) | 45.5% (37.8–53.3%) | 68.8% (64.8–72.6%) |
| Psychiatrist care | 131/331 (39.6%) | 200/331 (60.4%) | 125/219 (57.1%) | 94/219 (43.0%) | 57.0% (50.2–63.7%) | 60.4% (54.9–65.7%) | 48.8% (52.6–55.1%) | 68.0% (62.3–73.3%) |
| Geriatrician care | 30/130 (23.1%) | 100/130 (76.9%) | 26/76 (34.2%) | 50/76 (65.8%) | 34.2% (23.7–46.0%) | 76.9% (68.7–83.9%) | 46.4% (33.0–60.3%) | 66.7% (58.5–74.1%) |
| Residential care/nursing home | 115/673 (17.1%) | 558/673 (82.9%) | 116/378 (30.7%) | 271/378 (70.0%) | 30.7% (26.1–35.6%) | 82.9% (80.0–85.7%) | 50.2% (43.6–56.8%) | 68.1% (64.7–71.2%) |
CONCLUSIONS:
In this study, we examined the validity of ICD-9 and ICD-10 codes for identifying dementia-related hallucinations in administrative claims data using validated dementia assessments and combine patient- and caregiver-reported hallucinations in two nationally representative health surveys. We found that among older adults with dementia who had hallucinations within the previous year, only 22.9% had a corresponding diagnosis code in their Medicare claims, and the PPV of an ICD code for dementia-related hallucinations or psychosis was 50.2%. These findings indicate that dementia-related hallucinations are under-reported in administrative claims data, and that estimates of their prevalence and outcomes using these data are likely to be biased.
The underestimation of hallucinations in Medicare claims data is consistent with studies showing that patients and their caregivers are hesitant to report hallucinations to their healthcare providers due to perceived stigma and embarrassment (16). In the case of administrative claims data, it is likely that the underlying cause of dementia and hallucinations (e.g., LBD) is coded rather than the symptoms themselves, especially when the presence of hallucinations does not result in a change in treatment. NHATS and HRS have the advantage of systematically screening for hallucinations rather than relying on spontaneous self-reporting, which has been shown to improve the detection of hallucinations (17,18), and the prevalence of dementia-related hallucinations in our cohort is consistent with recent epidemiologic data. The accurate identification of dementia-related hallucinations has important implications for studies that use administrative claims data to assess their prevalence, risk factors, health care utilization, and treatment outcomes. Because our results show that approximately 3 out of every 4 patients with dementia-related hallucinations are not captured in administrative claims datasets, we believe that these data are insufficient for estimating the true burden of dementia-related hallucinations in the population, and studies that use Medicare data to examine risk factors for hallucinations and psychosis in older adults with dementia may therefore be limited by a large degree of misclassification (9–14).
While sensitivity and PPV were limited in our study, NPV was relatively high (88.8%). This suggests that the absence of a relevant diagnosis code could be used to identify hallucination-free dementia patients for research using administrative claims data. While specificity was generally good, there were a significant number of false positives (21.2%), and because the majority of individuals in the cohort did not have hallucinations, this limited PPV. However, some of the ICD codes that we used to identify dementia-related hallucinations refer generally to psychosis or other behavioral symptoms associated with dementia rather than hallucinations in particular (e.g., ICD-10-CM F03.91: Unspecified dementia with behavioral disturbance). Therefore, it is possible that some of these are not false positives and that the true specificity is higher than 88.8%. However, excluding these codes to improve specificity and PPV would result in the undercounting of even more subjects with dementia-related hallucinations, leading to even lower sensitivity and NPV.
Our study is unique in its use of a nationally representative population of older adults with administrative claims and patient-reported outcomes data, including validated dementia assessments and systematic screening for hallucinations across a one-year period, which accounts for the potentially waxing and waning nature of hallucinations. However, even with gold-standard population-based screening, it is possible that some hallucinations were missed, especially if caregivers are unaware of them or mistake them for confusion, agitation, or other symptoms. Our cohort of older adults with dementia had a relatively high prevalence of hallucinations (33%), but as PPV and NPV are dependent on disease prevalence within the population, these calculations would differ in a patient population with fewer hallucinations. Because hallucinations are time-varying and questionnaires were repeated yearly (in NHATS) or every other year (in HRS), we limited claims data to a one-year lookback period relative to the survey responses. A longer lookback period may have captured more claims-based diagnoses and improved sensitivity. However, this would lead to confusion regarding overlapping survey periods and double counting of ICD codes. Given the frequency of healthcare utilization associated with dementia-related hallucinations and psychosis, we suspect that even with a longer lookback period, the sensitivity of ICD codes for detecting dementia-related hallucinations remains limited. Finally, while we used the co-occurrence of dementia and hallucinations to define dementia-related hallucinations, it is possible that some hallucinations were not directly attributable to dementia but rather to other factors such as release hallucinations in the setting of vision loss due to age-related eye disease (also known as the Charles Bonnet syndrome [23]), which could have contributed to the under-ascertainment of hallucinations in Medicare claims. However, the presence of dementia theoretically precludes a diagnosis of Charles Bonnet syndrome (24).
In summary, hallucinations are common in older adults with dementia but are poorly captured in administrative claims data. Because patients and their caregivers may not spontaneously volunteer information about hallucinations, it is important for clinicians to proactively ask about them, and screening questionnaires are useful in both the clinical and research setting. Both hallucinations and their treatments have been associated with negative outcomes in administrative claims studies, but these may have been biased by the underascertainment of hallucinations, so further studies incorporating patient-reported outcomes are needed to dissect the relationship between hallucinations, antipsychotic medications, and health outcomes in older adults.
Supplementary Material
HIGHLIGHTS:
Question: Does Medicare data accurately identify older adults with dementia-related hallucinations?
Findings: Medicare data underestimates the burden of dementia-related hallucinations in the U.S. In a cross-sectional analysis of cognitive screening and Medicare claims data from 2,337 older adults in two nationally representative U.S. health surveys, dementia-related hallucinations were common, but less than one in four had an ICD code for hallucinations or psychosis in Medicare.
Meaning: Because 3 out of every 4 patients with dementia-related hallucinations are not captured in administrative claims datasets, studies that use these data to estimate the prevalence and outcomes of hallucinations are likely to be biased.
DISCLOSURES:
This work was supported by the Parkinson Study Group (Mentored Clinical Research Award to AGH), NIH/NINDS (R01 NS099129-04 to AWW), and Acadia Pharmaceuticals (investigator-initiated award to AWW and DW). The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. The authors report no conflicts of interest. Dr. Hamedani had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
The National Health and Aging Trends Study (NHATS) is sponsored by the National Institute on Aging (grant number NIA U01AG032947) through a cooperative agreement with the Johns Hopkins Bloomberg School of Public Health. The Health and Retirement Study (HRS) is supported by the National Institute on Aging, supplemented by the Social Security Agency, and operated from the Institute for Social Research (ISR) at the University of Michigan. This analysis uses data or information from the Harmonized HRS dataset and Codebook, Version B as of October 2018 developed by the Gateway to Global Aging Data. The development of the Harmonized HRS was funded by the National Institute on Aging (R01 AG030153, RC2 AG036619, 1R03AG043052). For more information, please refer to www.g2aging.org.
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DATA STATEMENT:
The data has not been previously presented orally or by poster at scientific meetings.
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