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Original Investigation |

Hospitalization and Death Associated With Potentially Inappropriate Medication Prescriptions Among Elderly Nursing Home Residents FREE

Denys T. Lau, PhD; Judith D. Kasper, PhD; D. E. B. Potter, MS; Alan Lyles, ScD, RPh; Richard G. Bennett, MD
[+] Author Affiliations

Author Affiliations: Buehler Center on Aging, Feinberg School of Medicine, Northwestern University, Chicago, Ill (Dr Lau); Department of Health Policy and Management, Bloomberg School of Public Health (Dr Kasper), and Division of Geriatric Medicine and Gerontology, School of Medicine (Dr Bennett), The Johns Hopkins University, Baltimore, Md; Center for Financing, Access, and Cost Trends, Agency for Healthcare Research and Quality, Rockville, Md (Ms Potter); and School of Government and Public Administration, University of Baltimore (Dr Lyles).


Arch Intern Med. 2005;165(1):68-74. doi:10.1001/archinte.165.1.68.
Text Size: A A A
Published online

Background  This study examines the association of potentially inappropriate medication prescribing (PIRx) with hospitalization and death among elderly long-stay nursing home residents.

Methods  We defined PIRx using the combined version of the Beers criteria. Data were from the 1996 Medical Expenditure Panel Survey Nursing Home Component. The study sample included 3372 residents, 65 years and older, who had nursing home stays of 3 consecutive months or longer in 1996. We performed multivariate logistic regression analyses of longitudinal data using generalized estimating equations.

Results  Residents who received any PIRx had greater odds (odds ratio [OR], 1.27; P = .002) of being hospitalized in the following month than those receiving no PIRx. Residents with PIRx exposure for 2 consecutive months were at increased risk (OR, 1.27; P = .004) of hospitalization, as were those receiving PIRx in the second month only (OR, 1.80; P = .001), compared with those receiving no PIRx. Residents who received PIRx were at greater risk of death (OR, 1.28; P = .01) that month or the next. Residents with intermittent PIRx exposures were at greater odds of death (OR, 1.89; P<.001), compared with those with no PIRx exposure.

Conclusions  The association of PIRx with subsequent adverse outcomes (hospitalization and death) provides new evidence of the importance of improving prescribing practices in the nursing home setting.

Potentially inappropriate prescribing of medications (PIRx) occurs in hospitals,1,2 emergency departments,3 and ambulatory settings.4 Patients 65 years and older are at significant risk of PIRx, owing to polypharmacy for multiple conditions,5 and of resulting adverse drug events ranging from minor symptoms to serious adverse effects, including sedation and life-threatening arrhythmia.6 Although a linkage between PIRx and subsequent major health events, eg, falls with injuries, hospitalization, and death, has been suggested,7 few studies have examined these types of relationships. Perhaps the most cited criteria for PIRx to elderly patients are those developed by Beers and colleagues8 for nursing home (NH) residents in 1991 and updated for community-dwelling elderly patients in 1997.9 One study using the Beers criteria found that elderly patients in an urban academic emergency department with prior PIRx exposure had worse physical functioning and greater pain during a 4-month period after the emergency department visit; however, no association was found between PIRx and death or return visits to the emergency department.3 A study using a different standard for PIRx (a medication appropriateness index) found that patients with PIRx exposure had more subsequent hospitalizations and emergency visits; however, the study was limited by a small sample size.10

A positive relationship between PIRx and increased cost of pharmaceutical services, but not between PIRx and mortality, has been documented among elderly residents in a long-term care residential setting.11 In a previous study, we used the 1991 and 1997 Beers criteria and reported that at least 50% of all elderly NH residents with stays of 3 consecutive months or longer received a PIRx during the year.12 By types of PIRx exposure, 40% of all NH residents had inappropriate drug choice, 11% had excess dosage, and 13% had drug-disease interaction.12 Among residents with PIRx exposure, more than 1 in 3 received PIRx for almost their entire NH stay.

The present study investigates the association of PIRx with hospitalization and death among elderly residents with NH stays of at least 3 consecutive months. We examined (1) whether hospitalizations and death were more likely to occur among residents who had PIRx exposures, and (2) whether the odds of hospitalization and death differed by patterns of previous PIRx exposure. The goal of this study was to provide empirical evidence of the association between PIRx as defined by the Beers criteria and health consequences (hospitalization and death) among NH residents, thereby underscoring the importance of improving prescribing practices in this setting.

DATA AND STUDY SAMPLE

We obtained the approval of the institutional review board at the Bloomberg School of Public Health at The Johns Hopkins University, Baltimore, Md, for this project. Data were from the 1996 Medical Expenditure Panel Survey Nursing Home Component (MEPS NHC), a nationally representative survey of NHs and residents. The MEPS NHC was designed to provide national estimates of use and expenditures for NH residents, including persons who were residents on January 1, 1996, and persons who were admitted to NHs during the year.13

The MEPS NHC data were collected by trained personnel from NH records for a 1-year period. Prescribed medicine data for residents were obtained from medication administration records and medical charts. For each sampled resident, drug data were obtained on a monthly basis as long as the resident was in an NH.13 Drug information, such as name, form, strength, dosage, and frequency of administration, was recorded. To facilitate data collection, a computerized look-up directory of more than 2000 commonly prescribed medications was available to data collection personnel. Drug names or characteristics not found in the directory were keyed in and stored for use in subsequent data collection.13

The current study is restricted to residents 65 years and older who were in an NH for at least 3 consecutive months during 1996. The minimum NH stay of 3 consecutive months was chosen before data analysis to focus on long-stay residents. We excluded a small number of additional cases of patients who were comatose (n = 20), were missing all drug data (n = 5), received no drugs (n = 4), or were in NHs that specialized in treatment of human immunodeficiency virus/AIDS or in other specialty NHs (n = 13). The final study sample included 3372 persons, representing 1.6 million long-stay elderly NH residents.

VARIABLES
PIRx Measures

The Beers criteria define the following 3 types of PIRx for elderly patients: (1) inappropriate drug choice, ie, medications that generally should be avoided; (2) excess dosage, ie, medications at a dose or duration of therapy that should not be exceeded; and (3) drug-disease interaction, ie, medications that should be avoided for patients with specific comorbid conditions.10,11

To construct monthly indicators of PIRx exposure, we screened drug data for each resident. Residents were considered to have PIRx exposure if any of the following occurred: (1) drug names matched the definition of inappropriate drug choice; (2) drug names, strengths, and dosages matched the definition of excess dosage; or (3) drug names and active diagnoses matched the definition of drug-disease interaction.

Hospitalizations and Death

Dates of inpatient hospital stays for residents and dates of death were obtained for the entire year from NH records. Binary measures of both outcomes were constructed for each month of NH residence.

Resident and Facility Characteristics

Resident characteristics were those reported as of January 1, 1996, for current residents and at admission for all others. Age, sex, race (white and other subjects including Hispanic subjects vs African American subjects), marital status, living offspring, education, and poverty status were constructed on the basis of data from NH records and community next of kin. Poverty level was constructed from gross annual household income using poverty thresholds published by the US Census Bureau.14 Admission before 1996 identifies persons who were admitted to an NH before January 1, 1996.13

Resident health status data collected in the MEPS NHC paralleled data obtained in the federally mandated NH resident assessment instrument (the minimum data set). Mental health status was constructed from items on active diagnosis and categorized as (1) any dementia, including Alzheimer disease; (2) other mental disorders only, such as anxiety disorder, depression, and schizophrenia; and (3) no mental disorders. Functional health status was defined as the number of activities of daily living for which a resident required supervision or assistance.14 Behavior problems included being verbally and physically abusive, resisting care, and being disruptive. Communication problems were present if a resident was not able to understand others or to be understood by others.15

Facility characteristics were linked to each resident. If residents were in a single NH during the year (about 90% of the residents), facility characteristics reflected that NH. If residents were in more than 1 NH, facility characteristics were those associated with the stay of 3 months or longer. If a resident had more than 1 NH stay exceeding 3 months, we selected the first stay if no PIRx occurred; otherwise, we selected the stay with the PIRx.

Facility type was defined as being hospital based, with multiple levels of care (including those facilities with continuing care retirement communities and personal care units), or as having NH beds only. Certification status included Medicare skilled-nursing facilities, and/or Medicaid nursing facilities. Accreditation status indicated accreditation by the Joint Commission on Accreditation of Healthcare Organizations.16 The ratio of registered nurses to residents (hereafter referred to as the nurse-resident ratio) included only full-time employees, and not part-time or pooled staff. Consultant pharmacists and mental health care providers, defined as psychiatrists and psychologists, were considered present if they were in NHs at least once a week. We selected the following 4 technological services: ventilator care, intravenous therapy, dialysis, and tube feeding. The percentage of residents vaccinated for influenza was estimated by the nursing facility respondent. Census region and metropolitan statistical area were defined using criteria from the US Census Bureau.14 Two county-level characteristics were obtained from the 1998 Area Resource File17: NH bed availability and annual income per capita. The former was defined by the number of empty NH beds per 1000 population 75 years and older; smaller values indicated fewer NH beds available.18

STATISTICAL ANALYSIS

We performed all descriptive and regression analyses using weighted data and SUDAAN statistical software to account for the complex sampling design of the MEPS NHC.19 We also used the generalized estimating equation method to account for the intercorrelation among repeated measures (eg, monthly drug data for each resident).20

Separate multivariate regression analyses were performed to examine the association between (1) PIRx and hospitalization and (2) PIRx and death. For hospitalization, the probability of hospitalization in any given month was regressed as a function of PIRx exposure in the preceding month or 2 consecutive months, controlling for other resident or facility characteristics. (If hospitalization and PIRx exposure occurred in the same month, it could not be determined whether PIRx preceded or followed hospitalization, because PIRx dates reflected month but not day of administration.) For mortality, the probability of death in any given month was regressed as a function of PIRx exposure before the date of death (same month, preceding month, or preceding 2 months).

Resident and facility characteristics that might have confounded the relationships between PIRx and hospitalization and between PIRx and death were included on the basis of their correlations into the final multivariate models (P≤.05 in univariate regressions) with PIRx exposure and hospitalization or death.21 Selected patient characteristics—age, sex, race, and NH admission before 1996—were kept in the multivariate models regardless of their statistical significance.

SAMPLE DESCRIPTION

Almost half of long-stay NH residents were 85 years and older, and most were female, white, and admitted before 1996 (Table 1). More than half had dementia or other mental disorders and more than 3 limitations in activities of daily living. Most of the residents were in nonaccredited NHs and in urban areas. One quarter were in NHs with nurse-resident ratios of less than 1:20; close to one third of NHs had ratios of 1:10 or greater.

Table Graphic Jump LocationTable 1. Resident and Facility Characteristics of Long-Stay Nursing Home Residents*

One half of residents had 1 or more PIRx exposures during the year. Therapuetic classes most frequently involved in PIRx included narcotics, antihistamines with strong anticholinergic effects, sedatives/hypnotics, gastrointestinal/antispasmodic agents, antidepressants, platelet inhibitors, and iron supplements.12 About one third of residents were hospitalized at least once during the year, and almost 1 in 5 died.

IMPACT OF PIRx
Univariate Analyses

The risk of hospitalization was almost 30% higher among residents who received PIRx in the preceding month, and 33% higher among residents who received PIRx for 2 consecutive months, compared with residents with no PIRx exposure (Table 2). Risk of hospitalization was greatest (78%) for residents who received PIRx in the previous month but not for the previous 2 months.

Table Graphic Jump LocationTable 2. Exposure Patterns of PIRx and Association With Hospitalization and Death*

The odds of death in any month were 21% higher among residents who had PIRx exposure during the month of death or the preceding month, compared with those with no PIRx exposure. Risk of death was greater (87%) for residents with intermittent PIRx exposure, relative to those receiving no PIRx, but was not elevated for those receiving PIRx in consecutive months.

Factors correlated with PIRx included race, Medicaid coverage, mental and functional status, communication problems, Joint Commission on Accreditation of Healthcare Organizations accreditation status of the facility, nurse-resident ratio, census region, metropolitan statistical area, and county-level annual income per capita (Table 3). Race, mental status, nurse-resident ratio, and census region were associated with PIRx exposure and hospitalization (Table 4). Medicaid coverage, functional status, and communication problems were correlated with PIRx exposure and death.

Table Graphic Jump LocationTable 3. Univariate Relationships of PIRx With Resident and Facility Characteristics*
Table Graphic Jump LocationTable 4. Univariate Relationships of Resident and Facility Characteristics With Hospitalization and Death*
Multivariate Analyses

Based on Tables 3 and 4, multivariate models with hospitalization as the outcome controlled for age, sex, race, admission before 1996, mental status, nurse-resident ratio, and census region. Multivariate models with death as the outcome controlled for age, sex, race, Medicaid coverage, admission before 1996, functional status, and communication problems.

The risk of hospitalization in a given month for residents with PIRx exposure in the preceding month remained significantly elevated (27%) compared with those with no PIRx exposure (Table 5). Residents who had PIRx exposure for 2 consecutive months also had a 27% greater risk of hospitalization in the following month. During 2 months, residents with PIRx exposure only in the second month had an 80% greater risk of hospitalization in the month after the PIRx exposure, compared with those with no PIRx exposure.

Table Graphic Jump LocationTable 5. Multivariate Models of Association Between Exposure to PIRx and Hospitalization and Death*

The odds of death in any month remained significantly elevated (28%) for residents with PIRx exposure in the preceding month, compared with those with no PIRx exposure. Residents with intermittent PIRx exposure during 2 months had almost a 90% increased risk of death compared with those with no PIRx, but odds of death were no different for those with PIRx in all months vs none.

Concerns about ensuring standards of care and patient safety have received renewed attention.7,22,23 We previously reported that at least 50% of all elderly NH residents with a stay of 3 consecutive months or longer received at least 1 PIRx, and that 1 in 3 had a PIRx exposure for almost every month of their stay.12 The most common PIRx’s (propoxyphene, diphenhydramine, hydroxyzine, oxybutynin chloride, amitriptyline hydrochloride, cyproheptadine hydrochloride, iron supplement, and ranitidine),12 although not generally considered to have extremely dangerous adverse effects, are viewed as inappropriate because of their relative lack of efficacy compared with alternative agents and/or their potential for adverse events among older patients. Using longitudinal data, the current study found an association between inappropriate medication prescribing and subsequent hospitalization and death, controlling for a number of resident and facility characteristics.

Risks of adverse outcomes increased in the month after PIRx exposure, but this study did not find a consistent dosage (or duration) effect of PIRx exposure on hospitalization or death. This finding was counterintuitive, because we expected that longer exposures would elevate the odds of subsequent hospitalization or death. However, although our methods identified duration of PIRx exposure across months, severity of exposure could not be assessed. For example, differences in severity between a 2-month exposure to a low-severity PIRx (eg, a low-dose sedative antihistamine) and a 1-month exposure to a high-severity PIRx (eg, high dose of propoxyphene) were not taken into consideration. In addition, duration of exposure was based on a monthly indicator that does not take into account frequency of exposures within a month.

Residents with intermittent PIRx exposures during consecutive months also had a higher risk of death compared with those with no PIRx exposure. Greater medical attention may be needed to monitor residents whose drug regimens fluctuate.

Caution should be used in interpreting results that indicate associations between previous PIRx exposure and hospitalization or death. Although these associations are drawn from longitudinal data analysis, relationships cannot be assumed to be causal. The time lapse between PIRx exposure in 1 month and hospitalization or death in the following month could have been several weeks if the PIRx occurred at the beginning of 1 month and the adverse event at the end of the next, with the opportunity for other intervening events to occur.

Although the number of medications was associated with PIRx exposure,12 the variable was not included in this analysis. Conceptually, we hypothesize that the pathway by which polypharmacy would exert an effect on adverse outcomes (hospitalization or death) would be through increasing the likelihood of having PIRx exposures. In addition, number of medications taken could be viewed as an indicator of illness severity or a measure of quality of prescribing practices. The number of medications alone is difficult to interpret as a quality-of-care indicator. Someone receiving few medications may be well treated or undertreated, just as someone receiving many medications may be well treated or overmedicated. The Beers criteria provide a more direct measure of quality of prescribing. Although number of medications could be used as an indicator of illness severity, measures of mental health status and functioning were used for this purpose and are measures of illness severity not confounded by prescribing patterns.

This study analyzed hospitalizations for all causes (admitting diagnoses were not available). It is unclear whether admitting diagnoses accurately reflect adverse drug events. The PIRx exposures can be broad and subtle, making them difficult to diagnose. For example, hospitalizations owing to congestive heart failure might result from treatment with an anticholinergic, leading to dry mouth and excess fluid intake, or an admission for aspiration pneumonia might result from oversedation with a narcotic.

This study also assumed that the drug information collected from the medication administration records and medical charts of each resident accurately reflects the drugs administered and consumed. Data quality could vary depending on how accurately NHs kept their records. This method of data collection, however, is commonly used in national surveys of NH residents and has proved reliable and valid.

Although 23% of NH residents in the study sample had at least 1 month of missing drug data, 93% of these cases had drug data available for more than half of the months of their NH stay. Because 85% of residents had stays of at least 6 months, even in cases where drug data were missing for 1 month, data were available for 5 other time points. A separate analysis of residents with missing drug data found that these residents were similar on most characteristics to residents with no missing drug data.24 Reasons for missing drug data included refusals by facilities to provide information and inability to locate medical charts. Because PIRx was assumed not to have occurred in a month with missing data, any bias would be against the hypothesis of a relationship between PIRx and adverse outcomes.

Finally, although this analysis used longitudinal data to investigate the relationship of PIRx to adverse health outcomes for NH residents, clinical and prospective studies are needed to clarify a causal pathway and to address other pharmaceutical issues, such as the effects of severity of PIRx exposure. Because the Beers criteria are based on expert opinion and are not evidence based, the PIRx identified on the list have been subject to disagreement.25 This reflects the complexity of prescribing for elderly patients in general and underscores the need for further research to contribute to the evolving knowledge of prescribing criteria in the treatment of elderly patients. By doing so, prescribing criteria, such as those of Beers et al,9 will garner greater acceptance from the health care provider community, facilitate the education process for improving prescribing behaviors for the elderly population, and allow for these criteria to have greater applicability with respect to regulatory review and compliance.

Correspondence: Denys T. Lau, PhD, Buehler Center on Aging, Feinberg School of Medicine, Northwestern University, 740 N Lake Shore Dr, Suite 601, Chicago, IL 60611 (d-lau@northwestern.edu).

Accepted for Publication: June 29, 2004.

Financial Disclosure: None.

Funding/Support: This study was supported by intramural funds from the Agency for Healthcare Research and Quality (AHRQ), Rockville, Md.

Disclaimer: The opinions expressed are those of the authors. No official endorsement by the Department of Health and Human Services or the AHRQ is intended or should be inferred.

Previous Presentation: This study was previously presented in part at the Annual Research Meeting of Academy Health; June 23, 2002; Washington, DC.

Acknowledgment: We thank the following individuals for their helpful comments on earlier drafts of this report: Crystal Simpson, MD, of the School of Medicine and Francesca Dominici, PhD, Lynda Burton, PhD, and Emily Agree, PhD, of the Bloomberg School of Public Health, The Johns Hopkins University, Baltimore, Md; and William Spector, PhD, John Moeller, PhD, Joel Cohen, PhD, Steven Cohen, PhD, and Tom Shaffer, MHS, of the AHRQ. We also thank Kathy McMillan, Devi Katikineni, MS, and Zhengyi Fang, MS, of Social Scientific Systems, Inc, Silver Spring, Md, for their data-processing support.

Bates  DWCullen  DJLaird  N  et al. ADE Prevention Study Group, Incidence of adverse drug events and potential adverse drug event: implications for prevention. JAMA 1995;27429- 34
PubMed Link to Article
Leape  LLBates  DWCullen  DJ  et al. ADE Prevention Study Group, Systems analysis of adverse drug events. JAMA 1995;27435- 43
PubMed Link to Article
Chin  MHWang  LCJin  L  et al.  Appropriateness of medication selection for older persons in an urban academic emergency department. Acad Emerg Med 1999;61232- 1242
PubMed Link to Article
Aparasu  RRFliginger  SE Inappropriate medication prescribing for the elderly by office-based physicians. Ann Pharmacother 1997;31823- 829
PubMed
Tamblyn  R Medication use in seniors: challenges and solutions. Therapie 1996;51269- 282
PubMed
Nash  DBKoenig  JBChatterton  ML Why the Elderly Need Individualized Pharmaceutical Care.  Philadelphia, Pa Office of Health Policy and Clinical Outcomes, Thomas Jefferson University April2000;
Kohn  LCorrigan  JDonaldson  M To Err Is Human: Building a Safer Health System.  Washington, DC Institute of Medicine, National Academy Press1999;
Beers  MHOuslander  JGRollingher  IReuben  DBBrooks  JBeck  JC Explicit criteria for determining inappropriate medication use in nursing home residents: UCLA Division of Geriatric Medicine. Arch Intern Med 1991;1511825- 1832
PubMed Link to Article
Beers  MH Explicit criteria for determining potentially inappropriate medication use by the elderly: an update. Arch Intern Med 1997;1571531- 1536
PubMed Link to Article
Schmader  KEHanlon  JTLandsman  PBSamsa  GPLewis  IKWeinberger  M Inappropriate prescribing and health outcomes in elderly veteran outpatients. Ann Pharmacother 1997;31529- 533
PubMed
Gupta  SRappaport  HMBennett  LT Inappropriate drug prescribing and related outcomes for elderly Medicaid beneficiaries residing in nursing homes. Clin Ther 1996;18183- 196
PubMed Link to Article
Lau  DTKasper  JDPotter  DEBLyles  A Potentially inappropriate medication prescriptions among geriatric nursing home residents: their scope and associated resident and facility characteristics. Health Serv Res 2004;391257- 1276
PubMed Link to Article
Potter  DEB Design and Methods of the 1996 Medical Expenditure Panel Survey Nursing Home Component.  Rockville, Md Agency for Healthcare Research and Quality1998;
Rhoades  JSommers  J Expenses and Sources of Payment for Nursing Home Residents, 1996.  Rockville, Md Agency for Healthcare Research and Quality2000;
Krauss  NAAltman  BM Characteristics of Nursing Home Residents, 1996.  Rockville, Md Agency for Healthcare Research and Quality 1998
Rhoades  JPotter  DKrauss  N Nursing Homes: Structure and Selected Characteristics, 1996.  Rockville, Md Agency for Healthcare Research and Quality1998;
 Area Resource File System.  Rockville, Md Office of Research and Planning, Bureau of Health Professions, Health Resources and Services Administration, US Dept of Health and Human Services1998;
Cohen  JWSpector  WD The effect of Medicaid reimbursement on quality of care in nursing homes. J Health Econ 1996;1523- 48
PubMed Link to Article
Shah  BBarnwell  BBieler  G SUDAAN User’s Manual: Software for the Statistical Analysis of Correlated Data.  Research Triangle Park, NC Research Triangle Institute1995;
Diggle  PJLiang  KYZeger  SL Analysis of Longitudinal Data.  New York, NY Oxford University Press Inc1999;
Hosmer  DWJLemeshow  S Applied Logistic Regression.  New York, NY John Wiley & Sons Inc1989;
 Crossing the Quality Chasm: A New Health System for the 21st Century.  Washington, DC Institute of Medicine, National Academy Press2001;
Wunderlich  GSKohler  PO Improving the Quality of Long-term Care.  Washington, DC Institute of Medicine, National Academy Press2001;
Potter  DEBLau  DDominici  F Characteristics of nursing home residents with item non-response in their prescribed medicine data: analyzing the 1996 Medical Expenditure Panel Survey Nursing Home Component.  Proceedings of the 2002 Joint Statistical Meetings, American Statistical Association August 13, 2002 New York, NY
Zhan  CSangl  JBierman  AS  et al.  Potentially inappropriate medication use in the community-dwelling elderly: findings from the 1996 Medical Expenditure Panel Survey. JAMA 2001;2862823- 2829
PubMed Link to Article

Figures

Tables

Table Graphic Jump LocationTable 1. Resident and Facility Characteristics of Long-Stay Nursing Home Residents*
Table Graphic Jump LocationTable 2. Exposure Patterns of PIRx and Association With Hospitalization and Death*
Table Graphic Jump LocationTable 3. Univariate Relationships of PIRx With Resident and Facility Characteristics*
Table Graphic Jump LocationTable 4. Univariate Relationships of Resident and Facility Characteristics With Hospitalization and Death*
Table Graphic Jump LocationTable 5. Multivariate Models of Association Between Exposure to PIRx and Hospitalization and Death*

References

Bates  DWCullen  DJLaird  N  et al. ADE Prevention Study Group, Incidence of adverse drug events and potential adverse drug event: implications for prevention. JAMA 1995;27429- 34
PubMed Link to Article
Leape  LLBates  DWCullen  DJ  et al. ADE Prevention Study Group, Systems analysis of adverse drug events. JAMA 1995;27435- 43
PubMed Link to Article
Chin  MHWang  LCJin  L  et al.  Appropriateness of medication selection for older persons in an urban academic emergency department. Acad Emerg Med 1999;61232- 1242
PubMed Link to Article
Aparasu  RRFliginger  SE Inappropriate medication prescribing for the elderly by office-based physicians. Ann Pharmacother 1997;31823- 829
PubMed
Tamblyn  R Medication use in seniors: challenges and solutions. Therapie 1996;51269- 282
PubMed
Nash  DBKoenig  JBChatterton  ML Why the Elderly Need Individualized Pharmaceutical Care.  Philadelphia, Pa Office of Health Policy and Clinical Outcomes, Thomas Jefferson University April2000;
Kohn  LCorrigan  JDonaldson  M To Err Is Human: Building a Safer Health System.  Washington, DC Institute of Medicine, National Academy Press1999;
Beers  MHOuslander  JGRollingher  IReuben  DBBrooks  JBeck  JC Explicit criteria for determining inappropriate medication use in nursing home residents: UCLA Division of Geriatric Medicine. Arch Intern Med 1991;1511825- 1832
PubMed Link to Article
Beers  MH Explicit criteria for determining potentially inappropriate medication use by the elderly: an update. Arch Intern Med 1997;1571531- 1536
PubMed Link to Article
Schmader  KEHanlon  JTLandsman  PBSamsa  GPLewis  IKWeinberger  M Inappropriate prescribing and health outcomes in elderly veteran outpatients. Ann Pharmacother 1997;31529- 533
PubMed
Gupta  SRappaport  HMBennett  LT Inappropriate drug prescribing and related outcomes for elderly Medicaid beneficiaries residing in nursing homes. Clin Ther 1996;18183- 196
PubMed Link to Article
Lau  DTKasper  JDPotter  DEBLyles  A Potentially inappropriate medication prescriptions among geriatric nursing home residents: their scope and associated resident and facility characteristics. Health Serv Res 2004;391257- 1276
PubMed Link to Article
Potter  DEB Design and Methods of the 1996 Medical Expenditure Panel Survey Nursing Home Component.  Rockville, Md Agency for Healthcare Research and Quality1998;
Rhoades  JSommers  J Expenses and Sources of Payment for Nursing Home Residents, 1996.  Rockville, Md Agency for Healthcare Research and Quality2000;
Krauss  NAAltman  BM Characteristics of Nursing Home Residents, 1996.  Rockville, Md Agency for Healthcare Research and Quality 1998
Rhoades  JPotter  DKrauss  N Nursing Homes: Structure and Selected Characteristics, 1996.  Rockville, Md Agency for Healthcare Research and Quality1998;
 Area Resource File System.  Rockville, Md Office of Research and Planning, Bureau of Health Professions, Health Resources and Services Administration, US Dept of Health and Human Services1998;
Cohen  JWSpector  WD The effect of Medicaid reimbursement on quality of care in nursing homes. J Health Econ 1996;1523- 48
PubMed Link to Article
Shah  BBarnwell  BBieler  G SUDAAN User’s Manual: Software for the Statistical Analysis of Correlated Data.  Research Triangle Park, NC Research Triangle Institute1995;
Diggle  PJLiang  KYZeger  SL Analysis of Longitudinal Data.  New York, NY Oxford University Press Inc1999;
Hosmer  DWJLemeshow  S Applied Logistic Regression.  New York, NY John Wiley & Sons Inc1989;
 Crossing the Quality Chasm: A New Health System for the 21st Century.  Washington, DC Institute of Medicine, National Academy Press2001;
Wunderlich  GSKohler  PO Improving the Quality of Long-term Care.  Washington, DC Institute of Medicine, National Academy Press2001;
Potter  DEBLau  DDominici  F Characteristics of nursing home residents with item non-response in their prescribed medicine data: analyzing the 1996 Medical Expenditure Panel Survey Nursing Home Component.  Proceedings of the 2002 Joint Statistical Meetings, American Statistical Association August 13, 2002 New York, NY
Zhan  CSangl  JBierman  AS  et al.  Potentially inappropriate medication use in the community-dwelling elderly: findings from the 1996 Medical Expenditure Panel Survey. JAMA 2001;2862823- 2829
PubMed Link to Article

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