Hearing Loss and the Healthcare system - jhsph.edu · Reed et al. (2018) JAGS (in press); Reed et al. 2018 (in -prep) Note: Logistic regression model for odds of less than optimal

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Hearing Loss and the Healthcare system

Nicholas S. Reed, AuD

Assistant Professor │ Dept. OtolaryngologyCore Faculty │ Cochlear Center for Hearing and Public Health

Johns Hopkins UniversityBaltimore, Maryland

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Prevalence of Hearing Loss in the United States, 2001-2008

Hearing loss defined as a better-ear PTA of 0.5-4kHz tones > 25 dB

Lin et al., Arch Int Med. 2011

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Hearing Loss and Health Aging

Lin JAMA 2014

Maintaining Physical Mobility & Activity

Cognitive Vitality & Avoiding Dementia

Avoiding Injury

Health ResourceUtilization

Keeping Socially Engaged & Active

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Hearing Loss & Hearing Aid UsePrevalence in the U.S. 1999-2006

Chien, W. Arch Int Med. 2012

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Hearing Loss: Primer

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“You should go to the pharmacy before you get to your house.”


“You should go to the pharmacy before you get to your house.”

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Patient-Provider Communication

Shukla et al. 2018 AM J Med Qual; IOM 2001; Cohen et al. (2017) JAGS; Cudmore et al (2017) JAMA-OTO

IOM 2001: Patient-provider care is cornerstone of patient-centeredcare “…care that is respectful of and responsive to individual patient

preferences, needs, and value”

Only 23.9% (16/67) of patient-provider communication papersinvolving older adults included any mention of hearing loss Of those 16, only 4 included hearing loss in analyses

Systematic review of inpatient patient-provider communication 13/13 studies that included hearing loss found it associated with

poorer patient-provider communication

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Patient-Provider Communication

Shukla et al. 2018 (under review); IOM 2001

Patient-provider communication impacts healthcare metrics quality of care time to diagnosis length of stay treatment adherence satisfaction with care

Hearing Loss

Healthcare metrics?

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Objectives of Talk

Part 1; Secondary Analyses Hearing Loss and satisfaction: Cross sectional analyses The impact of hearing loss on health care cost and utilization

measures

Part 2; Primary Data Development and feasibility investigation of a systematic strategy to

address hearing loss in the inpatient setting

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Secondary AnalysisSatisfaction - Methods

Reed et al. (2018) JAGS (in press); Reed et al. 2018 (in-prep)

Data Sources:

Medicare Current Beneficiaries Survey 2015 Sample weighted national sample of 12311 US Medicare

Beneficiaries Interview conducted survey (8% respond by proxy)

Atherosclerosis Risk in Communities Study Objective audiometry pilot offered to ~300 persons Washington County, MD site

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Exposure: Hearing Loss

Medicare Current Beneficiary Survey No trouble hearing A little trouble hearing A lot of trouble hearing If applicable: w/ hearing aid

Atherosclerosis Risk in Communities Objective pure-tone audiometry Conducted in sound booth with calibrated equipment Pure-tone average (speech frequency sounds) Defined according to W.H.O criteria

Functional Hearing Loss

Objective Hearing Loss

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Outcome: Self-report satisfaction

Medicare Current Beneficiaries Survey: “Please tell me how satisfied you have been with the following:

The overall quality of the health care [you have] received [overthe past year/since (reference date)].”

Very Satisfied, Satisfied, Dissatisfied, Very Dissatisfied

Atherosclerosis Risk in Communities: “Overall, how satisfied are you with the quality of care you

received from your healthcare providers over the past 12months?”

Very Dissatisfied, Somewhat Dissatisfied, Somewhat Satisfied,Very Satisfied

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Outcome: Self-report satisfaction

Medicare Current Beneficiaries Survey: “Please tell me how satisfied you have been with the following:

The overall quality of the health care [you have] received [overthe past year/since (reference date)].”

Very Satisfied, Satisfied, Dissatisfied, Very Dissatisfied

Atherosclerosis Risk in Communities: “Overall, how satisfied are you with the quality of care you

received from your healthcare providers over the past 12months?”

Very Dissatisfied, Somewhat Dissatisfied, Somewhat Satisfied,Very Satisfied

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Secondary AnalysisOdds Dissatisfaction With Care


Note: Logistic Regression model includes age, sex, race, income, education level, general health, functional limitations, and martial status; Sensitivity Analyses using ordinal logistic and excluding disabled led to similar results

Self-Report Difficulty Hearing

Total N(unweighted)

Total N(weighted)

Dissatisfied with Care

Odds Ratio [95% CI] P-Value

No Trouble Hearing 5915 26.1 million 3.10% REF

A little Trouble Hearing 4667 19.3 million 4.64% 1.47

[1.06-2.03] 0.021

A Lot of Trouble Hearing

865 3.2 million 6.52% 1.74[1.15-2.62] 0.009

Total 11447 48.6 Million 3.94% - -

Medicare Current Beneficiaries Survey:

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Secondary AnalysisOdds Dissatisfaction With Care


Note: Logistic regression model for odds of less than optimal satisfaction and hearing loss adjusted for age, sex, global cognitivescore, comorbidity count (diabetes, hypertension, myocardial infarction, asthma, cancer, stroke, and hospital stay).

Atherosclerosis Risk in Communities:

75-year-old participant: Every 10 dB increase in

HL, odds of < satisfiedincreased .94 (95%CI:0.74-1.20).

85-year-old participant: Every 10 dB increase in

HL, odds of < satisfiedincreased 1.33 (95%CI:0.96-1.83).

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Objectives of Talk

Part 1; Secondary Analyses Hearing Loss and satisfaction: A cross sectional analysis The impact of hearing loss on health care cost and utilization

measures



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Secondary AnalysisCost/Utilization - Methods

Reed et al. (2018) JAMA-OTO

Data Source:

OptumLabs® Data Warehouse (Jan 1, 2000 to Dec 31, 2014)

125 million de-identified data claims from across US

Private and Medicare Advantage

Physician, hospital, prescription claims information

Socioeconomic and satisfaction measures (survey)

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Outcome Variables:

1. Medical Costs Total

Health plan paid Out of Pocket Isolated to hearing loss

2. Number inpatient hospitalizations3. Total days hospitalized4. Number of readmissions with 30-days of discharge5. Number Emergency Department Visits6. Number of days with at least one outpatient visit

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Exposure Variable:

Evidence of Hearing Loss from ICD codes ≥ 50 years No hearing aid usage evidence from ICD codes No hearing loss ICD code two years prior to index date Included

ICD codes for hearing loss and/or sensorineural hearingloss

Excluded ICD hearing codes such as sudden, hyperacusis, neural,

conductive, central, etc. Persons with same year code related to ear disease such as

otorrhea, otalgia

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Sample:

Propensity matched (1:1) to those with evident hearing loss to thosewithout any evidence of hearing loss (at any point)

Matching variables Insurance type Demographic (Age, Sex, Education, Income) Census geographic region Education level Charlson comorbidty index Number of office visits, inpatient stays, ED visits Dementia, depression, stroke, cancer (breast, prostate, renal

cell, colorectal) Baseline medical costs

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Secondary AnalysisCost/Utilization - Results


Baseline Characteristics:

2-year 5-year 10-year

Hearing loss No hearing loss Hearing loss No hearing loss Hearing loss No hearing loss

(n=77,207) (n=77,207) (n=22,426) (n=22,426) (n=2,364) (n=2,364)Demographics

Age, mean (sd) 63.80 (9.74) 63.79 (9.70) 61.71 (9.22) 61.70 (9.20) 61.03 (9.30) 61.05 (9.28)Female, N (%) 37,309 (48.3) 37,155 (48.1) 10,792 (48.1) 10,671 (47.6) 1,150 (48.6) 1,130 (47.8)Race, N (%)

Asian 1,707 (2.2) 1,626 (2.1) 385 (1.7) 352 (1.6) 39 (1.6) 34 (1.4)Black 4,367 (5.7) 4,420 (5.7) 1,312 (5.9) 1,373 (6.1) 144 (6.1) 162 (6.9)Hispanic 3,933 (5.1) 4,039 (5.2) 1,061 (4.7) 1,050 (4.7) 89 (3.8) 95 (4.0)Unknown 20,428 (26.5) 20,452 (26.5) 6,282 (28.0) 6,389 (28.5) 605 (25.6) 642 (27.2)White 46,772 (60.6) 46,670 (60.4) 13,386 (59.7) 13,262 (59.1) 1,487 (62.9) 1,431 (60.5)

Region, N (%)Midwest 21,896 (28.4) 21,951 (28.4) 6,903 (30.8) 6,796 (30.3) 861 (36.4) 830 (35.1)Northeast 14,536 (18.8) 14,323 (18.6) 3,966 (17.7) 3,906 (17.4) 418 (17.7) 436 (18.4)South 31,820 (41.2) 31, 929 (41.4) 9,205 (41.0) 9,329 (41.6) 882 (37.3) 899 (38.0)West 8,955 (11.6) 9,004 (11.7) 2,352 (10.5) 2,395 (10.7) 203 (8.6) 199 (8.4)

Net worth, N (%)Unknown 22,874 (29.6) 22,951 (29.7) 6,978 (31.1) 7,137 (31.8) 673 (28.5) 718 (30.4)<$25,000 2,771 (3.6) 2,707 (3.5) 729 (3.3) 682 (3.0) 80 (3.4) 77 (3.3)$24,000-$149,000 7,610 (9.9) 7,447 (9.6) 2,038 (9.1) 1,998 (8.9) 206 (8.7) 185 (7.8)$150,000-$249,000 7,678 (9.9) 7,815 (10.1) 2,047 (9.1) 2,043 (9.1) 195 (8.2) 193 (8.2)$250,000-$499,000 16,404 (21.2) 16,564 (21.5) 4,745 (21.2) 4,738 (21.1) 558 (23.6) 560 (23.7)$500k+ 19,870 (25.7) 19,723 (25.5) 5,889 (26.3) 5,828 (26.0) 652 (27.6) 631 (26.7)

Education, N (%)Less than 12th grade 231 (0.3) 219 (0.3) 39 (0.2) 37 (0.2) ** **High School diploma 14,647 (19.0) 14,568 (18.9) 3,937 (17.6) 3,890 (17.3) 380 (16.1) 386 (16.3)Less than bachelor’s degree 31,981 (41.4) 32,166 (41.7) 9,139 (40.8) 9,072 (40.5) 992 (42.0) 965 (40.8)Bachelor’s degree or more 12,068 (15.6) 11,886 (15.4) 3,621 (16.1) 3,594 (16.0) 444 (18.8) 430 (18.2)Unknown 18,280 (23.7) 18,368 (23.8) 5,690 (25.4) 5,833 (26.0) <546 <585

Medicare, N (%) 24,028 (31.1) 24,028 (31.1) 6,025 (26.9) 6,025 (26.9) 755 (31.9) 755 (31.9)Baseline Utilization

Inpatient stays, mean (sd) 0.14 (0.47) 0.14 (0.43) 0.12 (0.42) 0.12 (0.39) 0.10 (0.34) 0.10 (0.33)Total inpatient days, mean (sd) 0.79 (4.94) 0.82 (4.30) 0.61 (3.31) 0.64 (3.22) 0.54 (2.49) 0.54 (2.36)Outpatient encounters, mean (sd)

18.73 (18.18) 18.63 (17.84) 17.17 (16.07) 17.13 (15.67) 15.55 (14.35) 14.91 (13.33)

ER visits, mean (sd) 0.32 (0.77) 0.32 (0.75) 0.27 (0.69) 0.27 (0.66) 0.24 (0.59) 0.22 (0.54)Medical costs, mean (sd) $8,311.24

($20,645.18)$8,479.90

($19,165.55$7,418.90

($17,586.02)$7,536.63

($15,933.56)$6,365.09

($14,413.20)$6,272.95

($11,928.82)Baseline Comorbidities

Charlson Comorbidity Index, mean (sd) 1.12 (1.71) 1.12 (1.68) 0.89 (1.48) 0.90 (1.47) 0.69 (1.24) 0.68 (1.20)

Acute Myocardial Infarction, N (%)324 (0.4) 301 (0.4) 87 (0.4) 76 (0.3) 13 (0.5) 14 (0.6)

Depression, N (%) 8,358 (10.8) 8,325 (10.8) 2,147 (9.6) 2,109 (9.4) 201 (8.5) 192 (8.1)Dementia, N (%) 2,104 (2.7) 2,189 (2.8) 381 (1.7) 411 (1.8) 14 (0.6) 18 (0.8)Stroke, N (%) 1,963 (2.5) 1,953 (2.5) 466 (2.1) 437 (1.9) 35 (1.5) 30 (1.3)Mild Cognitive Impairment, N (%)

107 (0.1) 113 (0.1) ** ** ** **

Coronary Artery Disease, N (%) 8,744 (11.3) 8,850 (11.5) 2,119 (9.4) 2,195 (9.8) 208 (8.8) 224 (9.5)

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Post-Match, Unadjusted Health Service Costs and Utilization, HearingLoss vs. No Hearing Loss

2-year 5-year 10-yearHearing

LossNo hearing

loss Hearing Loss No hearing loss Hearing Loss No hearing

loss(n=77,207) (n=77,207) (n=22,426) (n=22,426) (n=2,364) (n=2,364)

Healthcare Outcome Measure

Medical costs, mean (sd) $18,744.36 ($40,628.30)

$14,892.70 ($32,038.23)

$41,386.64 ($64,387.99)

$30,239.23 ($49,259.55)

$70,631.60 ($84,918.08)

$48,198.08 ($60,954.44)

Non-hearing loss Medical Costs, mean (sd)

$18,362.40 ($40,613.22)

$14,892.70 ($32,038.23)

$40,916.95 ($64,371.86)

$30,239.23 ($49,259.55)

$70,075.82 ($84,894.26)

$48,198.08 ($60,954.44)

Inpatient stays, mean (sd) 0.28 (0.78) 0.24 (0.69) 0.62 (1.34) 0.48 (1.08) 1.24 (2.05) 0.86 (1.60)

Inpatient days, mean (sd) 1.57 (6.78) 1.31 (5.43) 3.25 (9.83) 2.50 (8.25) 6.56 (14.81) 4.46 (10.88)

Outpatient visit days, mean (sd)

40.18 (36.49)

32.72 (35.18) 90.76 (72.64) 68.62

(62.21)168.05

($123.25)115.85 (95.37)

Non-hearing loss office visit days, mean (sd)

39.62 (36.17)

32.47 (35.00) 89.69 (71.99) 68.10

(61.76)166.00

(121.14)115.13 (94.79)

ER visits, mean (sd) 0.64 (1.37) 0.52 (1.30) 1.39 (2.85) 1.10 (2.14) 2.61 (3.61) 1.81 (2.77)

30 Day Readmission, N (%) 1,542 (2.0) 1,198 (1.6) 829 (3.7) 646 (2.9) 164 (6.9) 114 (4.8)

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Difference in Unadjusted Mean Patient Paid, Plan Paid, and Total Costs,Hearing Loss vs. No Hearing Loss

Hearing lossassociated witha 46.5%increase inhealthcarecosts over a 10-year period

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Secondary AnalysisResults


Unadjusted Difference in 30-day Readmissions for Subjects withUncorrected Hearing Loss vs. No Hearing Loss

Hearing lossassociated witha 44% increasein risk of 30-dayreadmissionsover 10-years

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Secondary AnalysisConclusion


Hearing loss is associated with increase healthcare expenditures andresource utilization over a 10-year period.

Hearing Loss is associated with higher odds of dissatisfaction withmedical care.

Patient-Provider communication as a mechanism?

Limitations: Claims data has inherent limitations

Exposure capture (those with means to access healthcare) Hearing loss individuals in non-hearing loss group No indirect costs (hearing aids?) Residual unmeasured confounding (despite matching)

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Objectives of Talk

Part 1; Secondary Analyses The impact of hearing loss on health care cost and utilization

measures Hearing Loss and satisfaction: A cross sectional analysis



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Screening and InterventionBackground

Reed et al. (2018) In-Progress

Development and feasibility investigation of a systematic strategy toaddress hearing loss in the inpatient setting

No universal program to identify and intervene on hearing loss inadults in the hospital system

Many calls for adult hearing screening but most have ignored basicprinciples of implementation science

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Screening and InterventionBackground

Pronovost, Berenholtz, & Needham et al. (2008) JAMA; Reed et al. (2018) In-Progress

Implementation Science: Translating evidence into sustainable practice

Current state of hearing screenings for adults:

Run by foreign units (audiology) Single person screening all

Generally from outside Purpose is generally for referral for formal hearing care

Indirect implications Use specialized equipment

Training, time Label patient (puts responsibility on patient) Lack training programs Lack of “buy-in”

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ENHANCEBackground


ENgaging Healthcare to Address Communication Environments

Imbedded within current workflow Universal training end education sessions

Improve fidelity and “buy-in” Purpose is to improve patient-provider communication

Direct implications for staff Onus of communication placed on staff/providers Self-report hearing loss

Minimizes training, time

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ENHANCEBackground


No Hearing Loss

Mild Hearing Loss

Admission:Screen for hearing

loss using self-report as part of

common procedures ≥Moderate

Hearing Loss

No Intervention

Communication Signage

Signage + Amplifier

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ENHANCEBackground


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ENHANCEBackground


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ENHANCE3-month feasibility


From Jan –Mar 2018: Feasibility Trial

Med A and Med B at Bayview Hospital (Community Hospital)

Engage (prior):

1 meeting with Armstrong Institute 2 meetings with ADA compliance office 3 meetings with Aesthetics Committee 3 meetings with Bayview Med A+B administration 5 meetings with Med A +B clinical nurse specialists, charge nurses

Champion: Clinical nurse specialist 6 lunch and learn events with staff (3 each Med A and B)

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Educate:

6 lunch and learn prior to kick off Materials were printed and distributed to all staff and providers 8 lunch and learn during program (~15-20 minutes)

4 in 2nd week 4 in 4th week

16 check-in huddles (~1-2 minutes) 4 in 1st week 4 in 3rd week 4 in 6th week 4 in 8th week

Amounts to 8 formal education opportunities per shift over period

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Evaluate : Patient perspective

502 screenings captured (77.9% of all admitted per charge nursenumber reports)

41 indicated form not completed (15 unresponsive patient, 14 refusals,12 time constraints)

543/644 for 84.3% capture rate

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Evaluate : Patient perspective

Of 502 screened, 60.9% (306) completed discharge form

Screened No HL(n=264)

Mild HL(n=157)

≥ Moderate HL (n=81)

Overall(n=502)

Age, mean (sd) 64.03 years (±7.87)

72.87 years (±7.52)

81.23 years (±6.71)

67.34 years (±4.35)

Device Distributed 0/264 (0%) 7/157 (04.4%) 75/81 (91.4%) 82/502 (16.3%)Discharge Completed 121/264

(45.8%)114/157 (72.6%)

71/81 (87.6%) 306 (60.9%)

Previous communication troubles?Never 23 (19.0%) 17 (14.9%) 3 (04.2%) 43 (14.1%)

Sometimes 71 (58.6%) 42 (36.8%) 11 (15.5%) 124 (40.5%)Most of the time 21(17.3%) 46 (40.4%) 41 (57.7%) 108 (35.3%)

Always 6 (04.9%) 9 (07.9%) 16 (22.5%) 31 (10.1%)Hearing an issue previously in communication?

No 116 (95.8%) 82 (71.9%) 19 (26.8%) 217 (70.9%)Yes 5 (04.1%) 32 (28.1%) 52 (73.2%) 89 (29.7%)

Improved communication during current stay?No difference 21 (17.4%) 3 (02.6%) 4 (05.6%) 28 (09.2%)

Slight Improvement 36 (29.8%) 21 (18.4%) 9 (12.7%) 66 (21.6%)Improved A little 46 (38.0%) 58 (50.9%) 17 (23.9%) 121 (39.5%)

Improved A lot 18 (14.9%) 32 (28.1%) 41 (57.7%) 91 (23.7%)Satisfied with communication during current stay?

Not Satisfied 11 (9.09%) 5 (04.4%) 1 (01.4%) 17 (5.6%)Somewhat Satisfied 12 (9.92%) 13 (11.4%) 4 (05.6%) 29 (9.5%)

Mostly Satisfied 18 (14.9%) 15 (13.2%) 7 (09.9%) 40 (13.1%)Completely Satisfied 80 (66.1%) 81 (71.1%) 59 (83.1%) 220 (71.9%)

See communication program used in other healthcare settings?No 21 (17.4%) 6 (05.3%) 1 (01.4%) 28 (09.2%)

Yes 92 (76.0%) 103 (90.4%) 67 (94.4%) 262 (85.6%)Yes, with changes 8 (06.6%) 5 (04.4%) 3 (04.2%) 16 (5.2%)

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Evaluate : Provider/Staff Perspective

“Best intervention ever! I normally have a loud voice and some peoplestill can't hear me, but once they put the headphones on, then they canhear. It's nice not loosing your voice :)”

“Such a wonderful program for patients. This has come in handy andpatients truly benefit from this. This has made my job much easier! Thankyou!“

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Evaluate : Provider/Staff Perspective

18 completed surveyN

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Strongly Agree0 0 10 6 3 7 3 6 0 8 8

Agree0 1 8 9 10 9 11 11 2 7 9

Neutral3 13 0 2 5 2 3 1 2 3 1

Disagree 8 4 0 1 0 0 1 0 13 0 0

Strongly Disagree 7 0 0 0 0 0 0 0 1 0 0

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ENHANCEImplications


Universal Adult Hearing Screening: Move towards acceptance Educating the rest of the medical community Future for objective measures

Professionals in the context of OTC: Raise awareness Potential for knowledge disbursement Establishing a hearing care ecosystem

HCAHPS (the Hospital Consumer Assessment of Healthcare Providersand Systems: Medicare reimbursement Hospital Incentive

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ENHANCEFuture


Fall 2018: Redesign of materials Integrate demographic variables to calculate hearing loss Webinar training video with quiz

Spring 2018: Mass. General (Boston, MA): (2 floors, pre and post) nurse feedback,

length of stay, HCAHPS Bayview Surgical Units: Process evaluation of new materials and

webinar looking at compliance and retention of knowledge

Summer/Fall 2019: Johns Hopkins East Baltimore: cluster trial, length of stay

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Special Thanks

Frank Lin, MD PhDJennifer Deal, PhDAmber Willink, PhDJosh Betz, PhDEmily Boss, MDEsther Oh, MD, PhDMegru Liao, MFAEmily Pedersen, MPH

Charlotte Yeh, MD (AARP)Aylin Altan, PhD (OptumLabs)Kevin Frick, AuD, PhD (MEEI, Harvard)

NIH Kl2 – ICTR (Johns Hopkins)Cochlear, Inc (Sydney, Australia)

Thanks.

[email protected]

@NickSReed

https://www.jhucochlearcenter.org/

Documents

Hearing Loss and the Healthcare system - jhsph.edu · Reed et al. (2018) JAGS (in press); Reed et al. 2018 (in -prep) Note: Logistic regression model for odds of less than optimal