Development of an algorithm to identify fall-related injuries and costs in Medicare data

Kim, Sung-Bou; Zingmond, David S.; Keeler, Emmett B.; Jennings, Lee A.; Wenger, Neil S.; Reuben, David B.; Ganz, David A.

doi:10.1186/s40621-015-0066-z

Cited by 38 publications

(52 citation statements)

References 20 publications

(53 reference statements)

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“…21 We started with the hospital admission claims and determined a patient had experienced a fall if the admitting or primary diagnosis code fields, or primary external cause code field reported an accidental fall (ICD9-CM external cause codes E880-E888, excluding E887), following an algorithm developed by Kim et al for identifying fall-related injuries in Medicare inpatient claims data. 22 In the years of our data, reporting of external cause codes is high, at about 90 percent for all injury cases (Appendix S1). We linked these claims to MDS assessments using beneficiary identifiers and then applied criteria for each MDS fall-related item to identify an appropriate denominator for reporting ( Figure 1).…”

Section: Identification Of Falls For Mds Reportingmentioning

confidence: 92%

Assessment of nursing home reporting of major injury falls for quality measurement on nursing home compare

Sanghavi

Pan

Caudry

2019

Health Services Research

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Objective To assess the accuracy of nursing home self‐report of major injury falls on the Minimum Data Set (MDS). Data Sources MDS assessments and Medicare claims, 2011‐2015. Study Design/Methods We linked inpatient claims for major injury falls with MDS assessments. The proportion of claims‐identified falls reported for each fall‐related MDS item was calculated. Using multilevel modeling, we assessed patient and nursing home characteristics that may be predictive of poor reporting. We created a claims‐based major injury fall rate for each nursing home and estimated its correlation with Nursing Home Compare (NHC) measures. Principal Findings We identified 150,828 major injury falls in claims that occurred during nursing home residency. For the MDS item used by NHC, only 57.5 percent were reported. Reporting was higher for long‐stay (62.9 percent) than short‐stay (47.2 percent), and for white (59.0 percent) than nonwhite residents (46.4 percent). Adjusting for facility‐level race differences, reporting was lower for nonwhite people than white people; holding constant patient race, having larger proportions of nonwhite people in a nursing home was associated with lower reporting. The correlation between fall rates based on claims vs the MDS was 0.22. Conclusions The nursing home‐reported data used for the NHC falls measure may be highly inaccurate.

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Section: Identification Of Falls For Mds Reportingmentioning

confidence: 92%

Assessment of nursing home reporting of major injury falls for quality measurement on nursing home compare

Sanghavi

Pan

Caudry

2019

Health Services Research

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“… FRIs identified using the adapted UCLA/RAND algorithm (Ganz et al. ; Kim et al ) in which serious FRIs are identified using inpatient (hospital and SNF) ICD‐9 primary diagnoses and external cause of injury codes and outpatient diagnoses and procedural codes. Models were estimated using OLS (expenditure change scores) or logistic regression (persistently high expenditures, controlling for preindex expenditures) with robust standard errors. …”

Section: Resultsmentioning

confidence: 99%

“…; Hoffman et al ; Kim et al. ) refines commonly used FRI identification approaches. Although it is potentially an improvement over prior approaches because it uses a more sensitive and specific approach involving inpatient and outpatient diagnoses/procedures, it needs to be further evaluated.…”

Section: Resultsmentioning

confidence: 99%

The Costs of Fall‐Related Injuries among Older Adults: Annual Per‐Faller, Service Component, and Patient Out‐of‐Pocket Costs

Hoffman

Hays

Shapiro

et al. 2016

Health Services Research

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Objective To estimate expenditures for fall‐related injuries (FRIs) among older Medicare beneficiaries. Data Sources The 2007–2009 Medicare claims and 2008 Health and Retirement Study (HRS) data for 5,497 (228 FRI and 5,269 non‐FRI) beneficiaries. Study Design FRIs were indicated by inpatient/outpatient ICD‐9 diagnostic codes for fractures, trauma, dislocations, and by e‐codes. A pre‐post comparison group design was used to estimate the differential change in pre‐post expenditures for the FRI relative to the non‐FRI cohort (FRI expenditures). Out‐of‐pocket (OOP) costs, service category total annual FRI‐related Medicare expenditures, expenditures related to the type of initial FRI treatment (inpatient, ED, outpatient), and the risk of persistently high expenditures (4th quartile for each post‐FRI quarter) were estimated. Principal Findings Estimated FRI expenditures were $9,389 (95 percent CI: $5,969–$12,808). Inpatient, physician/outpatient, skilled nursing facility, and home health comprised 31, 18, 39, and 12 percent of the total. OOP costs were $1,363.0 (95 percent CI: $889‐$1,837). Expenditures for FRIs initially treated in inpatient/ED/outpatient settings were $21,424/$6,142/$8,622. The FRI cohort had a 64 percent increased risk of persistently high expenditures. Total Medicare expenditures were $13 billion (95 percent CI: $9–$18 billion). Conclusions FRIs are associated with substantial, persistent Medicare expenditures. Cost‐effectiveness of multifactorial falls prevention programs should be assessed using these expenditure estimates.

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“…We examined several published diagnosis code-based definitions of falls 16,17 and selected the approach used by Bohl et al 17 Falls were identified by both ICD-9 codes associated with injuries commonly sustained during fall (800–848, 850–854, and 920–924) or e-codes identifying a fall mechanism (E880, E881, E884, E885, or E888). We chose this broad definition to intentionally bias the study towards the null hypothesis: by selecting a coding-based definition which casts a wide net, additional cases identified via chief complaint data were unlikely to have been picked up by more specific definitions.…”

Section: Methodsmentioning

confidence: 99%

“…In prior studies, diagnosis codes, such as the ICD-9 codes and the injury subcodes, have been used as an identifier of falls in large datasets. 16,17 While this is a standard procedure for many conditions within health services research, it may miss many patients in the ED, where visits for falls may result in other diagnosis codes reflecting the injury sustained such as fractures, contusions, etc. without mention of the mechanism of injury.…”

Section: Introductionmentioning

confidence: 99%

Using Chief Complaint in Addition to Diagnosis Codes to Identify Falls in the Emergency Department

Patterson

Smith

Repplinger

et al. 2017

J American Geriatrics Society

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Objectives We compared incidence of falls in an emergency department (ED) cohort using a traditional ICD-9 code-based scheme and an expanded definition that included chief complaint information. We further examined the clinical characteristics of those visits “missed” in the ICD-9-based scheme. Design Retrospective Electronic Record Review Setting Academic medical center ED Participants All ED visits of individuals aged 65 and older between 1/1/2013 and 9/30/2015. Measurements Two fall definitions were applied (both individually and in unison) to the cohort: an ICD-9-based definition, and a chief complaint definition. Admission and 30-day mortality rates (per encounter) were measured for each definition. Results 23,880 older adult visits occurred during the study period. Using the most inclusive definition (either ICD-9 code or chief complaint indicating a fall) 4,363 visits (18%) were fall related. Among these visits, 3,506 (80%) met the ICD-9 definition for a fall related visit, while 2,664 (61%) met the chief complaint definition. Among visits meeting the chief complaint definition, 857 (19.6%) were missed when applying the ICD-9 definition alone. Encounters missed by the ICD-9 definition had a lower admission rate (42.9%, 95% CI 39.7–46.3) than those identified (54.4%, 95% CI 52.7–56.0). Conclusion Identifying ED fall patients based on diagnosis codes underestimates the true burden of disease. Patients missed by the code-based definition were less likely to have been admitted than those captured. These findings call attention to the value of using chief complaint information to identify fall patients in the ED setting, whether it be for research, clinical care, or policy reasons.

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Development of an algorithm to identify fall-related injuries and costs in Medicare data

Cited by 38 publications

References 20 publications

Assessment of nursing home reporting of major injury falls for quality measurement on nursing home compare

Assessment of nursing home reporting of major injury falls for quality measurement on nursing home compare

The Costs of Fall‐Related Injuries among Older Adults: Annual Per‐Faller, Service Component, and Patient Out‐of‐Pocket Costs

Using Chief Complaint in Addition to Diagnosis Codes to Identify Falls in the Emergency Department

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