Are Older Women More Likely to Get Inappropriate Drugs? Arlene S. Bierman, MD, MS Ontario Women’s...

Are Older Women More Likely to Get Are Older Women More Likely to Get Inappropriate Drugs?Inappropriate Drugs?

Arlene S. Bierman, MD, MSArlene S. Bierman, MD, MSOntario Women’s Health Council Chair in Women’s HealthOntario Women’s Health Council Chair in Women’s Health

Centre for Research in Inner City HealthCentre for Research in Inner City HealthSt. Michael’s HospitalSt. Michael’s Hospital

June 28, 2005June 28, 2005

Potentially Inappropriate Prescribing in the Elderly (PIPE) Potentially Inappropriate Prescribing in the Elderly (PIPE) StudyStudy– Mary Jo V. Pugh PhD, RN Mary Jo V. Pugh PhD, RN 5,65,6

– B. Graeme Fincke, MD B. Graeme Fincke, MD 1,21,2

– Amy Rosen, PhD Amy Rosen, PhD 1,21,2

– Fran Cunningham, PharmD Fran Cunningham, PharmD 44

– Bei-Hung Chang, ScD Bei-Hung Chang, ScD 1,21,2

– Megan Amuan MPH Megan Amuan MPH 11

– Muriel Burke, PharmD Muriel Burke, PharmD 44

– Irfan Dalla Irfan Dalla 33

– Dan Berlowitz, MD, MPH Dan Berlowitz, MD, MPH 1,21,2

11Center for Health Quality, Outcomes and Economic Research, Bedford VA; Center for Health Quality, Outcomes and Economic Research, Bedford VA; 2 2 Boston University School of Public Health; Boston University School of Public Health; 3 3 University of Toronto; University of Toronto; 4 4 Pharmacy Benefits Management Strategic Healthcare Group, Hines VA and University Pharmacy Benefits Management Strategic Healthcare Group, Hines VA and University of Chicago, Illinois of Chicago, Illinois55 Veterans Evidence-based Research, Dissemination, and Implementation Center, Veterans Evidence-based Research, Dissemination, and Implementation Center, 66 South Texas Healthcare System, Audie L. Murphy Division, San Antonio, Texas; South Texas Healthcare System, Audie L. Murphy Division, San Antonio, Texas; University of Texas Health Science Center at San Antonio University of Texas Health Science Center at San Antonio

Inappropriate Prescribing in the ElderlyInappropriate Prescribing in the Elderly

Prescribing of drugs for which potential harms Prescribing of drugs for which potential harms outweigh potential benefits is a major patient safety outweigh potential benefits is a major patient safety concern in the elderly.concern in the elderly.

Inappropriate prescribing increases risk for falls, hip Inappropriate prescribing increases risk for falls, hip fractures, cognitive impairment, diminished fractures, cognitive impairment, diminished independence, and death. independence, and death.

Studies consistently find that 20-27% of older Studies consistently find that 20-27% of older Americans receive drugs identified as inappropriate, Americans receive drugs identified as inappropriate, with little to no improvement in nearly two decades.with little to no improvement in nearly two decades.

Gender Differences in Potentially Gender Differences in Potentially Inappropriate PrescribingInappropriate Prescribing

Prior studies of community-dwelling elders have Prior studies of community-dwelling elders have suggested that older women were more likely to receive suggested that older women were more likely to receive potentially inappropriate drugs than men. potentially inappropriate drugs than men.

No prior study has examined whether gender differences No prior study has examined whether gender differences in potentially appropriate use of these drugs could explain in potentially appropriate use of these drugs could explain this or the factors associated with gender differences this or the factors associated with gender differences inappropriate prescribing.inappropriate prescribing.

Examination of the patterns and correlates of these Examination of the patterns and correlates of these gender differences can provide evidence to develop and gender differences can provide evidence to develop and implement effective quality improvement interventions. implement effective quality improvement interventions.

Study ObjectivesStudy Objectives

To assess gender differences in rates of To assess gender differences in rates of inappropriate prescribing inappropriate prescribing

To assess whether gender differences are To assess whether gender differences are explained by gender differences in potentially explained by gender differences in potentially appropriate indications for these drugs.appropriate indications for these drugs.

To examine gender differences in the To examine gender differences in the correlates of inappropriate drug use.correlates of inappropriate drug use.

Methods:Methods:Data SourcesData Sources

Multiple Linked US Veterans Administration Multiple Linked US Veterans Administration (VA) Data Sets(VA) Data Sets– Administrative Data: DemographicsAdministrative Data: Demographics– Inpatient Records: Diagnoses and UtilizationInpatient Records: Diagnoses and Utilization– Outpatient Records: Diagnoses and UtilizationOutpatient Records: Diagnoses and Utilization– National Ambulatory Pharmacy Data: Drugs, Dose, National Ambulatory Pharmacy Data: Drugs, Dose,

Duration Duration – Veterans Health Survey: Race/EthnicityVeterans Health Survey: Race/Ethnicity

Study PopulationStudy Population

Cohort IdentificationCohort Identification At least one outpatient visit in Fiscal Year (FY)1999 and At least one outpatient visit in Fiscal Year (FY)1999 and

FY 2000FY 2000 >> 65 years of age October 1, 1999 65 years of age October 1, 1999

Potentially Inappropriate Prescribing: Potentially Inappropriate Prescribing: Beers CriteriaBeers Criteria

Potentially Inappropriate Prescribing in the Elderly Potentially Inappropriate Prescribing in the Elderly (Beers, 1991,1997 update 2003).(Beers, 1991,1997 update 2003).– Explicit criteria, expert consensus panelExplicit criteria, expert consensus panel– 33 drugs considered inappropriate regardless of diagnosis 33 drugs considered inappropriate regardless of diagnosis

(disease-independent) (disease-independent) – dose limitations dose limitations – drug-drug/drug-disease interactions drug-drug/drug-disease interactions

Controversial because clinicians argued that some drugs Controversial because clinicians argued that some drugs may be appropriate for specific patients in certain may be appropriate for specific patients in certain circumstancescircumstances

Outcome Variable:Outcome Variable:Diagnosis-Adjusted Inappropriate PrescribingDiagnosis-Adjusted Inappropriate Prescribing

AHRQ (US Agency for Healthcare and Quality) AHRQ (US Agency for Healthcare and Quality) expert consensus panel expert consensus panel

- Grouped 33 Beers disease-independent - Grouped 33 Beers disease-independent drugs into 3 categories using modified Delphi drugs into 3 categories using modified Delphi process;process;

Always-avoidAlways-avoid : 11 drugs: 11 drugsRarely-appropriateRarely-appropriate : 8 drugs: 8 drugsSome-indicationsSome-indications: 14 drugs: 14 drugs

Diagnosis-adjusted PIPE: Algorithms develop using Diagnosis-adjusted PIPE: Algorithms develop using ICD-9 codes and pharmacy data to adjust for ICD-9 codes and pharmacy data to adjust for potentially appropriate use.potentially appropriate use.

Covariates:Covariates:Patient CharacteristicsPatient Characteristics

DemographicsDemographics

- - Age, sex, race/ethnicityAge, sex, race/ethnicity

-- 1999 large Health Survey of Veterans provided missing race data1999 large Health Survey of Veterans provided missing race data Physical and Psychiatric ComorbidityPhysical and Psychiatric Comorbidity

- - Disease burden assessment by Selim’s physical and psychiatric Disease burden assessment by Selim’s physical and psychiatric Comorbidity IndexComorbidity Index

-- Assessed comorbidity status for 3 years (FY98-00) Assessed comorbidity status for 3 years (FY98-00)• # psychiatric diagnoses# psychiatric diagnoses• # physical diagnoses# physical diagnoses

Number of unique medications (FY 00)Number of unique medications (FY 00)

Covariates Covariates Characteristics of Care Characteristics of Care

Type of Care Received Type of Care Received (FY 99) (FY 99)

– Number of Primary Care VisitsNumber of Primary Care Visits– Number of Different Specialty ClinicsNumber of Different Specialty Clinics– Geriatric Care Geriatric Care – Long-term Care, Medical or Psychiatric HospitalizationsLong-term Care, Medical or Psychiatric Hospitalizations

Outpatient visits used to assess continuity of careOutpatient visits used to assess continuity of care

number of outpatient visits in primary care (FY 99) number of outpatient visits in primary care (FY 99) Total number of outpatient visitsTotal number of outpatient visits

Method - AnalysisMethod - Analysis We determined the prevalence of any use of potentially We determined the prevalence of any use of potentially

inappropriate drugs among men and women. Then, we used the inappropriate drugs among men and women. Then, we used the VA PIPE study algorithms to examine the proportion of this use VA PIPE study algorithms to examine the proportion of this use that may have been appropriate and whether the proportion that that may have been appropriate and whether the proportion that remained inappropriate differed by gender.remained inappropriate differed by gender.

Using logistic regression we determined the unadjusted and Using logistic regression we determined the unadjusted and adjusted odds ratios of women receiving diagnosis-adjusted adjusted odds ratios of women receiving diagnosis-adjusted inappropriate drugs compared to men both for individual agents inappropriate drugs compared to men both for individual agents and by drug category (always avoid, rarely appropriate, and rare and by drug category (always avoid, rarely appropriate, and rare indication).indication). Patient and care characteristics were included as Patient and care characteristics were included as covariates.covariates.

Logistic regressions stratified by gender were conducted to Logistic regressions stratified by gender were conducted to examine gender differences in factors associated with receipt of examine gender differences in factors associated with receipt of inappropriate medications.inappropriate medications.

Gender Differences in Use of Inappropriate DrugsGender Differences in Use of Inappropriate Drugs

ParameterParameter

Male (%)Male (%)

(N=946,641)(N=946,641)

Female (%)Female (%)

(N=19,115)(N=19,115)

OR OR

(F vs.M)(F vs.M)

Always avoidAlways avoid 0.90.9 1.71.7 1.951.95

Rarely appropriateRarely appropriate 10.510.5 12.412.4 1.311.31

Some indicationSome indication 18.118.1 22.622.6 1.441.44

At least one drugAt least one drug 25.725.7 31.031.0 1.451.45

All comparisons are significant with P< 0.0001All comparisons are significant with P< 0.0001

Gender Differences Proportion Gender Differences Proportion Inappropriate – Some IndicationInappropriate – Some Indication

DrugDrugProportion Inappropriate After Adjusting for Proportion Inappropriate After Adjusting for

Diagnosis/Duration of UseDiagnosis/Duration of Use (%) (%)MaleMale FemaleFemale

AmitriptylineAmitriptyline 75.075.0 76.176.1

Doxepin Doxepin 81.681.6 80.280.2

Oxybutynin Oxybutynin 74.874.8 52.652.6

Chlorpheniramine Chlorpheniramine 92.192.1 93.193.1

DiphenhydramineDiphenhydramine 94.294.2 95.095.0

Odds of Receiving Inappropriate Drugs:Odds of Receiving Inappropriate Drugs:Diagnosis AdjustedDiagnosis Adjusted

1.31.2

2.0

1.7

1.31.2

1.31.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

Any InappropriateDrug

Always Avoid Rare Indication Some Indicaton

Unadjusted

Adjusted*

OR

(F

vs.

M)

OR

(F

vs.

M)

*Adjusted for demographics, comorbidities, unique meds & characteristics of care*Adjusted for demographics, comorbidities, unique meds & characteristics of care

Gender Differences in Diagnosis-Adjusted Gender Differences in Diagnosis-Adjusted Use of Individual Agents: Always AvoidUse of Individual Agents: Always Avoid

DrugDrug

UnadjustedUnadjusted Adjusted*Adjusted*

OROR 95% CI95% CI OROR 95% CI95% CI

MeperidineMeperidine 1.71.7 1.2-2.51.2-2.5 1.51.5 1.1-2.21.1-2.2

Belladonna Belladonna AlkaloidsAlkaloids

2.62.6 1.3-5.31.3-5.3 2.22.2 1.1-4.41.1-4.4

DicyclomineDicyclomine 2.12.1 1.8-2.51.8-2.5 1.81.8 1.6-2.11.6-2.1

HyoscyamineHyoscyamine 2.52.5 2.0-3.22.0-3.2 2.52.5 1.9-3.11.9-3.1

PropanthelinePropantheline 3.23.2 2.1-4.72.1-4.7 2.72.7 1.8-4.01.8-4.0


Gender Differences in Diagnosis-Adjusted Gender Differences in Diagnosis-Adjusted Use of Individual Agents: Rare IndicationUse of Individual Agents: Rare Indication

DrugDrug



DiazepamDiazepam 1.21.2 1.1-1.41.1-1.4 1.01.0 0.9-1.10.9-1.1

PropoxyphenePropoxyphene 1.31.3 1.3-1.41.3-1.4 1.21.2 1.1-1.31.1-1.3

CyclobenzaprineCyclobenzaprine 1.41.4 1.2-1.51.2-1.5 1.41.4 1.3-1.61.3-1.6

MethocarbamolMethocarbamol 1.21.2 1.1-1.31.1-1.3 1.21.2 1.1-1.31.1-1.3

*Adjusted for demographics, comorbidities, unique meds & characteristics of care *Adjusted for demographics, comorbidities, unique meds & characteristics of care

Gender Differences in Diagnosis-Adjusted Gender Differences in Diagnosis-Adjusted Use of Individual Agents: Some IndicationUse of Individual Agents: Some Indication

DrugDrugUnadjustedUnadjusted Adjusted*Adjusted*


AmitriptylineAmitriptyline 1.41.4 1.3-1.51.3-1.5 1.31.3 1.2-1.41.2-1.4

Doxepin Doxepin 1.21.2 1.0-1.41.0-1.4 1.01.0 0.8-1.10.8-1.1

Disopyramide Disopyramide 4.04.0 1.6-9.91.6-9.9 3.03.0 1.2-7.41.2-7.4

Oxybutynin Oxybutynin 2.02.0 1.9-2.21.9-2.2 1.81.8 1.6-1.91.6-1.9

Chlorpheniramine Chlorpheniramine 1.41.4 1.3-1.51.3-1.5 1.31.3 1.2-1.41.2-1.4

DiphenhydramineDiphenhydramine

1.51.5 1.4-1.61.4-1.6 1.41.4 1.3-1.51.3-1.5

PromethazinePromethazine 1.71.7 1.3-2.11.3-2.1 1.41.4 1.1-1.71.1-1.7*Adjusted for demographics, comorbidities, unique meds & characteristics of care*Adjusted for demographics, comorbidities, unique meds & characteristics of care

Drugs less likely to be received by Drugs less likely to be received by women – Some Indicationwomen – Some Indication

DrugsDrugs



IndomethacinIndomethacin 0.60.6 0.5-0.70.5-0.7 0.60.6 0.5-0.70.5-0.7

Dipyridamole Dipyridamole 0.80.8 0.6-1.00.6-1.0 0.70.7 0.5-0.80.5-0.8

CyproheptadineCyproheptadine 0.60.6 0.5-0.90.5-0.9 0.50.5 0.4-0.60.4-0.6


Correlates of Inappropriate PrescribingCorrelates of Inappropriate Prescribing

ParameterParameter

Male (N=834,251)Male (N=834,251) Female (N=15,903)Female (N=15,903)

OROR P-valueP-value OROR P-ValueP-Value

HispanicHispanic 1.081.08 <0.00<0.00 1.361.36 0.030.03

1 mental health 1 mental health diagnosisdiagnosis

1.321.32 <0.00<0.00 0.990.99 0.880.88

2 or more mental 2 or more mental health diagnosishealth diagnosis

1.611.61 <0.00<0.00 1.081.08 0.200.20

Number of Number of medicationsmedications

1.171.17 <0.00<0.00 1.181.18 <0.00<0.00

Geriatric visitGeriatric visit 0.650.65 <0.00<0.00 0.640.64 <0.00<0.00

Age, continuity of care, long-term care, medical or psychiatric hospitalizations included Age, continuity of care, long-term care, medical or psychiatric hospitalizations included in model.in model.

Conclusions

Older women were more likely to receive inappropriate Older women were more likely to receive inappropriate medications than older men, even after accounting for a medications than older men, even after accounting for a liberal set of indications.liberal set of indications.

Analgesic, psychotropic, and anticholinergic Analgesic, psychotropic, and anticholinergic medications that should be avoided contribute to higher medications that should be avoided contribute to higher rates of inappropriate drug use among older women.rates of inappropriate drug use among older women.

Psychiatric comorbidity is a predictor of inappropriate Psychiatric comorbidity is a predictor of inappropriate drug use in men but not in women.drug use in men but not in women.

Conclusions

Receipt of geriatric care was equally protective for Receipt of geriatric care was equally protective for men and women, though only a small proportion of men and women, though only a small proportion of the sample received this care. the sample received this care.

Men and women did not differ in proportion of drugs Men and women did not differ in proportion of drugs that were inappropriate, inappropriate dosing, or that were inappropriate, inappropriate dosing, or duration.duration.

Limitations

While some use is classified as potentially appropriate While some use is classified as potentially appropriate often safer or more effective options exist.often safer or more effective options exist.

Data may not capture all drugs received by the cohort, Data may not capture all drugs received by the cohort, as those who have other drug coverage may have as those who have other drug coverage may have received medications outside the VA.received medications outside the VA.

VA population may limit generalizability. VA population may limit generalizability. A recent update of the Beers criteria added additional A recent update of the Beers criteria added additional

medications to the list of disease-independent drugs.medications to the list of disease-independent drugs.

ImplicationsImplications Because of these differences studies on inappropriate Because of these differences studies on inappropriate

prescribing should examine gender differences when prescribing should examine gender differences when possible.possible.

Efforts to improve the quality of medication Efforts to improve the quality of medication management in the elderly should address gender management in the elderly should address gender differences in prescribing patterns.differences in prescribing patterns.

Improved access to geriatric care may decrease rates Improved access to geriatric care may decrease rates of inappropriate prescribing.of inappropriate prescribing.

Are Older Women More Likely to Get Inappropriate Drugs? Arlene S. Bierman, MD, MS Ontario Women’s...

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