Clinical and economic consequences of a reimbursement restriction of nebulised respiratory therapy in adults: direct comparison of randomise
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《英国医生杂志》
1 Brigham and Women's Hospital and Harvard Medical School, Division of Pharmacoepidemiology and Pharmacoeconomics, 1620 Tremont St (Suite 3030), Boston, MA 02120, USA, 2 Harvard School of Public Health, Boston, University of Victoria, Victoria, Canada, 3 University of British Columbia, Vancouver, Canada
Correspondence to: S Schneeweiss schneeweiss@post.harvard.edu
Abstract
Total expenditure on drugs in the United Kingdom (￡5.5bn; $10.1bn; 8bn) has grown by 30% over the past four years, 50% faster than other expenditure on health services.1 Spending in continental Europe and North America has escalated similarly.2 To contain costs, drug benefit programmes are introducing increasingly restrictive policies that are, however, intended to have no impact on access to effective care.3 4 Critics claim that restrictions cause patients to switch to less effective treatments, resulting in reduced compliance,5 6 more contacts with doctors and procedures, and more admissions to hospital.7 8
As drug cost containment policies evolve the need grows for direct, valid, and timely evidence of their benefits and risks.9 Only a few well designed observational evaluations have been undertaken—no randomised trials—of the clinical and economic consequences of restricting the reimbursement of drugs.10-14 One observational study15 16 that received publicity17 purported to show by comparing six health maintenance organisations that restrictions lead to more admissions to hospitals and doctors' services, thus increasing net costs. Seriously confounded by unmeasured characteristics of the health maintenance organisation and patient selection bias,18-20 the study was valuable mainly for highlighting the need for rigorous methods in this field. Randomised controlled trials provide the gold standard of evidence because they eliminate selection bias and baseline confounding if enough units are randomised.21 However, a major barrier to policy trials is the belief—which Chalmers called the biggest myth22—that randomisation is expensive. An opportunity to assess the feasibility of randomised evaluation of drug policy and to compare it with a well designed observational evaluation arose in British Columbia, when the provincial government's drug plan, Pharmacare, restricted reimbursement for nebulised respiratory drugs in 1999.
Current guidelines from the British Thoracic Society say that nebulised respiratory drugs are indicated for adult patients with a limited number of conditions, including chronic persistent asthma in elderly people, exacerbations of chronic obstructive pulmonary disease, palliative care, or specific infections.23 On the other hand, a Canadian asthma consensus conference found that "nebulised medication is rarely, if ever, indicated in the management of asthma in adults."24 Metered dose inhalers are more efficient than nebulisers at delivering drugs to the lungs, and drug costs are usually lower with inhalers. Many drug benefit plans therefore limit reimbursement of nebulised drugs.25 When such a policy was developed in British Columbia we persuaded Pharmacare to delay it for six months in a randomised control group of 10% of doctors and patients, which would cost Pharmacare no more than if the long delayed policy were further delayed by just 18 days (10% of six months).26
This enabled us to compare a cluster randomised evaluation with an observational time trend evaluation in the same target population.
Methods
The baseline distributions of age, sex, drug use, comorbidity score, and use of healthcare did not differ between the randomised groups (table 1; all P values > 0.1). The observational cohorts had slightly more women than the randomised groups (62% v 59%). Otherwise the observational cohorts were comparable to each other.
Table 1 Baseline characteristics of patients before randomisation (randomised analysis) or before cohort start (observational analysis) for the evaluation of the reimbursement restriction for nebulised respiratory drugs in British Columbia. Values are numbers (percentages) of patients unless otherwise indicated
Dropout of patients because of death or emigration during the trial period was comparable between intervention group (5%) and control group (8%). These dropout rates were comparable to dropout rates at six months in the observational and historical cohorts (6%, 7%, and 8%; table 2).
Table 2 Characteristics of patients six months after the start of the formulary restriction for nebulised respiratory drugs in British Columbia. Values are numbers (percentages) of patients unless otherwise indicated
After the policy was implemented the observational analysis indicated that significantly fewer patients used nebulised drugs only (7% v 14%, P < 0.001; table 2 and table 1, respectively) or nebulised in combination with inhaled drugs (21% v 46%, P < 0.001; table 2 and table 1, respectively) compared with levels of use before the policy. By contrast, more moderate reductions became obvious in the randomised analysis for nebulised drug use (6% v 11%, P < 0.01) or nebulised in combination with inhaled drug use (23% v 37%, P < 0.001, table 2). The historical control groups showed some seasonal variation, with higher use of respiratory drugs in the six months preceding 1 March compared with the subsequent six months (table 1 and table 2), underlining the importance of adjusting for seasonal effects in observational analyses (table 3).
Table 3 Randomised intention to treat analysis and observational repeated measures analysis of the same formulary restriction of nebulised respiratory drugs in adults
In the analysis of the observational cohorts we found that expenditure for nebulised drugs increased by about $C25 per patient month in the month preceding the new policy, followed by an equally lower use in the first month afterwards (see "difference" line in figure 2a). When we excluded these two months of stockpiling and transition the average economic effects in the observational analysis were savings of $C24 per patient month for nebulised drugs and an increase of $C3 per patient month for inhaler drugs (table 3).
Fig 2 Expenditure for nebulised respiratory drugs: a) observational analysis, b) randomised analysis. The vertical lines represent the policy change on 1 March 1999
In the analysis of the randomised groups the estimated savings were $C8 per patient month for nebulised drugs (non-significant, P = 0.24) and spending was $C1 per patient month higher for inhalers (fig 2b and table 3). These estimates are low because many control doctors did not exercise their right to an exemption. In the control group as a whole, prescribing of nebulised drug expenditure dropped about by 60% as much as in the intervention group. Under the reasonable assumption that "non-compliance" with the exemption (or crossover) by control doctors was unrelated to patients' characteristics, we corrected for this misclassification in a sensitivity analysis by using the method of Zelen (p 887).42 This corrected estimate of savings from the randomised analysis was then about $C21 per patient month, very close to the observational estimate.
Both study designs consistently showed no increase in contacts with doctors or admissions to hospital, including emergency admissions (table 3, fig 3).
Fig 3 Rates of contacts with doctors or emergency admissions to hospital in the observational analysis. The vertical lines represent the policy change on 1 March 1999
P values did not change for any of the analyses by more than 0.02 after additional adjustment for clustering of patients within doctors' practices.
Discussion
Audit Commission. Primary care prescribing: a bulletin for primary care trusts. London: Audit Commission, 2003.
Organisation for Economic Co-operation and Development. Health data 2001: a comparative analysis of 29 countries. Paris, OECD, 2001.
Abel-Smith B, Mossialos E. Cost containment and health care reform. A study of the European Union. Health Policy 1994;28: 89-132.
Ess S, Schneeweiss S, Szucs T. European healthcare policies for controlling drug expenditure. PharmacoEconomics 2003;21: 89-103.
McFadden ER: Improper patient techniques with metered dose inhalers: clinical consequences and solutions to misuse. J Allergy Clin Immunol 1995;96: 278-83.
Pounsford JC: Nebulizers for the elderly. Thorax 1997;52(suppl 2): S53-55.
Bourgault C, Elstein E, Le Lorier J, Suissa S. Reference-based pricing of prescription drugs: exploring the equivalence of angiotensin-converting-enzyme inhibitors. CMAJ 1999;161: 255-60.
Thomas M, Mann J. Increased thrombotic vascular events after change of statin. Lancet 1998;352: 1830-1.
Maclure M, Potashnik T. What is direct evidence-based policy making? Experience of the drug benefits program for seniors in British Columbia. Can J Public Policy/Can J Aging 1997;16(suppl): 132-46.
Reeder CE, Nelson AA. The differential impact of copayment on drug use in a Medicaid population. Inquiry 1985;22: 396-403.
Soumerai SB, Avorn J, Ross-Degnan D, Gortmaker S. Payment restrictions for prescription drugs in Medicaid: Effects on therapy, cost, and equity. New Engl J Med 1987;317: 550-6.
Motheral BR, Henderson R. The effect of a closed formulary on prescription drug use and costs. Inquiry 1999;36: 481-91.
Tamblyn R, Laprise R, Hanley JA, Abrahamowicz M, Scott S, Mayo N, et al. Adverse events associated with prescription drug cost-sharing among poor and elderly persons. JAMA 2001;285: 421-429.
Schneeweiss S, Walker AM, Glynn RJ, Maclure M, Dormuth C, Soumerai SB. Outcomes of reference pricing for angiotensin-converting enzyme inhibitors. New Engl J Med 2002;346: 822-9.
Horn SD, Sharkey PD, Tracy DM, Horn CE, James B, Goodwin F.Intended and unintended consequences of HMO cost-containment strategies: results from the managed care outcomes project. Am J Managed Care 1996;2: 253-64.
Horn SD, Sharkey PD, Phillips-Harris C. Formulary limitations and the elderly: results from the managed care outcomes project. Am J Managed Care 1998;4: 1105-13.
Barnett AA. HMO formularies lead to higher care costs. Lancet 1996;347: 894.
Soumerai SB, Ross-Degnan D. HMO formularies and care costs. Lancet 1996;347: 1264.
Fairman K, Teitelbaum F, Motheral B, Barrow SM, Thomas ME. Letter to the editor. Am J Managed Care 1996;2: 588-592;
Kravitz RL, Romano PS. Managed care cost containment and the law of unintended consequences. Am J Managed Care 1996;2: 323-324.
Cook TD, Campbell DT. Quasi-experimentation. Design and analysis issues for field studies. Boston: Houghton Mifflin, 1979.
Maclure M. Tom Chalmers 1917-95: part 2: the tribulations of a trialist. CMAJ 1996;155: 986-8.
Muers MF, Corris PA, eds. Nebuliser Project Group of the British Thoracic Society Standards of Care Committee. Current best practice for nebulizer treatment. Thorax 1997;52(suppl.2): S1-104.
Canadian Asthma Consensus Conference (CACC). Summary of recommendations. Can Respir J 1996;3: 89-100.
Muers MF. Overview of nebuliser treatment. Thorax 1997;52(suppl 2): S25-30.
Maclure M, Nakagawa R, Carleton BC. Applying research to the policy cycle: implementing and evaluating evidence-based drug policies in British Columbia. In: Clarke M, Fox DM, Langhorne P. Informing judgment: case studies of health policy and research in six countries. New York: Milbank Memorial Fund, 2001; 35-70.
Zelen M. A new design for randomized clinical trials. N Engl J Med 1979;300: 1242-5.
British Columbia Ministry of Health Services. Pharmacare trends 2000. Victoria BC, 2001.
Anderson GM, Kerluke KJ, Pulcins IR, Hertzman C, Barer ML. Trends and determinants of prescription drug expenditures in the elderly: data from the British Columbia Pharmacare program. Inquiry 1993;30: 199-207.
Williams JI, Young W. Inventory of studies on the accuracy of Canadian health administrative databases. Technical report. Toronto: Institute for Clinical Evaluative Sciences (ICES), 1996.
Daniel WW. Biostatistics: a foundation for analysis in health sciences. New York: Wiley, 1991.
Diehr P, Yanez D, Ash A, Hornbrook M, Lin DY. Methods for analyzing health care utilization and costs. Annu Rev Public Health 1999;20: 125-44.
Liang K-Y, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika 1986;73: 13-22.
Thompson SG, Barber JA. How should cost data in pragmatic randomised trials be analysed? BMJ 2000;320: 1197-200.
Barber JA, Thompson SG. Analysis of cost data in randomized trials: an application of the non-parametric bootstrap. Stat Med 2000;19: 3219-36.
Schneeweiss S, Maclure M, Soumerai SB, Walker AM, Glynn RJ. Quasi-experimental longitudinal designs to evaluate drug benefit policy changes with low policy compliance. J Clin Epidemiol 2002;55: 833-41.
Gillings D, Makuc D, Siegel E: Analysis of interrupted time series mortality trends: an example to evaluate regionalized perinatal care. Am J Public Health 1981;71: 38-46.
Veney JE, Kaluzny AD. Evaluation and decision making for health services. Part V: Trend analysis. 2nd ed. Ann Arbor, MI: Health Administration Press, 1991.
Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992;45: 613-9.
Glynn RJ, Buring JE: Ways of measuring rates of recurrent events. BMJ 1996;312: 364-7.
Akaike H. A new look at the statistical model identification. IEEE Transaction on Automatic Control 1974;19: 716-23.
Zelen M. Author's reply to compliance, bias, and power in clinical trials. Biometrics 1991;47: 778-9.
Goodman SN, Berlin JA. The use of predicted confidence intervals when planning experiments and the misuse of power when interpreting results. Ann Int Med 1994;121: 200-6.
Bowton DL, Goldsmith WM, Haponik EF: Substitution of metered-dose inhalers for hand-held nebulizers: success and cost-savings in a large, acute care hospital. Chest 1992;101: 305.
Jasper AC, Mohsenifar Z, Kahan S, Goldberg HS, Koerner SK. Cost-benefit comparison of aerosol bronchodilator delivery methods in hospitalized patients. Chest 1987;91: 614.
Chappell N, Maclure M, Brunt H, Hopkinson J, Mullett J, Thomson ME. Seniors' views of medication reimbursement policies: bridging research and policy at the point of policy impact. Can J Aging 1997; 114-31.(Sebastian Schneeweiss, as)
Correspondence to: S Schneeweiss schneeweiss@post.harvard.edu
Abstract
Total expenditure on drugs in the United Kingdom (￡5.5bn; $10.1bn; 8bn) has grown by 30% over the past four years, 50% faster than other expenditure on health services.1 Spending in continental Europe and North America has escalated similarly.2 To contain costs, drug benefit programmes are introducing increasingly restrictive policies that are, however, intended to have no impact on access to effective care.3 4 Critics claim that restrictions cause patients to switch to less effective treatments, resulting in reduced compliance,5 6 more contacts with doctors and procedures, and more admissions to hospital.7 8
As drug cost containment policies evolve the need grows for direct, valid, and timely evidence of their benefits and risks.9 Only a few well designed observational evaluations have been undertaken—no randomised trials—of the clinical and economic consequences of restricting the reimbursement of drugs.10-14 One observational study15 16 that received publicity17 purported to show by comparing six health maintenance organisations that restrictions lead to more admissions to hospitals and doctors' services, thus increasing net costs. Seriously confounded by unmeasured characteristics of the health maintenance organisation and patient selection bias,18-20 the study was valuable mainly for highlighting the need for rigorous methods in this field. Randomised controlled trials provide the gold standard of evidence because they eliminate selection bias and baseline confounding if enough units are randomised.21 However, a major barrier to policy trials is the belief—which Chalmers called the biggest myth22—that randomisation is expensive. An opportunity to assess the feasibility of randomised evaluation of drug policy and to compare it with a well designed observational evaluation arose in British Columbia, when the provincial government's drug plan, Pharmacare, restricted reimbursement for nebulised respiratory drugs in 1999.
Current guidelines from the British Thoracic Society say that nebulised respiratory drugs are indicated for adult patients with a limited number of conditions, including chronic persistent asthma in elderly people, exacerbations of chronic obstructive pulmonary disease, palliative care, or specific infections.23 On the other hand, a Canadian asthma consensus conference found that "nebulised medication is rarely, if ever, indicated in the management of asthma in adults."24 Metered dose inhalers are more efficient than nebulisers at delivering drugs to the lungs, and drug costs are usually lower with inhalers. Many drug benefit plans therefore limit reimbursement of nebulised drugs.25 When such a policy was developed in British Columbia we persuaded Pharmacare to delay it for six months in a randomised control group of 10% of doctors and patients, which would cost Pharmacare no more than if the long delayed policy were further delayed by just 18 days (10% of six months).26
This enabled us to compare a cluster randomised evaluation with an observational time trend evaluation in the same target population.
Methods
The baseline distributions of age, sex, drug use, comorbidity score, and use of healthcare did not differ between the randomised groups (table 1; all P values > 0.1). The observational cohorts had slightly more women than the randomised groups (62% v 59%). Otherwise the observational cohorts were comparable to each other.
Table 1 Baseline characteristics of patients before randomisation (randomised analysis) or before cohort start (observational analysis) for the evaluation of the reimbursement restriction for nebulised respiratory drugs in British Columbia. Values are numbers (percentages) of patients unless otherwise indicated
Dropout of patients because of death or emigration during the trial period was comparable between intervention group (5%) and control group (8%). These dropout rates were comparable to dropout rates at six months in the observational and historical cohorts (6%, 7%, and 8%; table 2).
Table 2 Characteristics of patients six months after the start of the formulary restriction for nebulised respiratory drugs in British Columbia. Values are numbers (percentages) of patients unless otherwise indicated
After the policy was implemented the observational analysis indicated that significantly fewer patients used nebulised drugs only (7% v 14%, P < 0.001; table 2 and table 1, respectively) or nebulised in combination with inhaled drugs (21% v 46%, P < 0.001; table 2 and table 1, respectively) compared with levels of use before the policy. By contrast, more moderate reductions became obvious in the randomised analysis for nebulised drug use (6% v 11%, P < 0.01) or nebulised in combination with inhaled drug use (23% v 37%, P < 0.001, table 2). The historical control groups showed some seasonal variation, with higher use of respiratory drugs in the six months preceding 1 March compared with the subsequent six months (table 1 and table 2), underlining the importance of adjusting for seasonal effects in observational analyses (table 3).
Table 3 Randomised intention to treat analysis and observational repeated measures analysis of the same formulary restriction of nebulised respiratory drugs in adults
In the analysis of the observational cohorts we found that expenditure for nebulised drugs increased by about $C25 per patient month in the month preceding the new policy, followed by an equally lower use in the first month afterwards (see "difference" line in figure 2a). When we excluded these two months of stockpiling and transition the average economic effects in the observational analysis were savings of $C24 per patient month for nebulised drugs and an increase of $C3 per patient month for inhaler drugs (table 3).
Fig 2 Expenditure for nebulised respiratory drugs: a) observational analysis, b) randomised analysis. The vertical lines represent the policy change on 1 March 1999
In the analysis of the randomised groups the estimated savings were $C8 per patient month for nebulised drugs (non-significant, P = 0.24) and spending was $C1 per patient month higher for inhalers (fig 2b and table 3). These estimates are low because many control doctors did not exercise their right to an exemption. In the control group as a whole, prescribing of nebulised drug expenditure dropped about by 60% as much as in the intervention group. Under the reasonable assumption that "non-compliance" with the exemption (or crossover) by control doctors was unrelated to patients' characteristics, we corrected for this misclassification in a sensitivity analysis by using the method of Zelen (p 887).42 This corrected estimate of savings from the randomised analysis was then about $C21 per patient month, very close to the observational estimate.
Both study designs consistently showed no increase in contacts with doctors or admissions to hospital, including emergency admissions (table 3, fig 3).
Fig 3 Rates of contacts with doctors or emergency admissions to hospital in the observational analysis. The vertical lines represent the policy change on 1 March 1999
P values did not change for any of the analyses by more than 0.02 after additional adjustment for clustering of patients within doctors' practices.
Discussion
Audit Commission. Primary care prescribing: a bulletin for primary care trusts. London: Audit Commission, 2003.
Organisation for Economic Co-operation and Development. Health data 2001: a comparative analysis of 29 countries. Paris, OECD, 2001.
Abel-Smith B, Mossialos E. Cost containment and health care reform. A study of the European Union. Health Policy 1994;28: 89-132.
Ess S, Schneeweiss S, Szucs T. European healthcare policies for controlling drug expenditure. PharmacoEconomics 2003;21: 89-103.
McFadden ER: Improper patient techniques with metered dose inhalers: clinical consequences and solutions to misuse. J Allergy Clin Immunol 1995;96: 278-83.
Pounsford JC: Nebulizers for the elderly. Thorax 1997;52(suppl 2): S53-55.
Bourgault C, Elstein E, Le Lorier J, Suissa S. Reference-based pricing of prescription drugs: exploring the equivalence of angiotensin-converting-enzyme inhibitors. CMAJ 1999;161: 255-60.
Thomas M, Mann J. Increased thrombotic vascular events after change of statin. Lancet 1998;352: 1830-1.
Maclure M, Potashnik T. What is direct evidence-based policy making? Experience of the drug benefits program for seniors in British Columbia. Can J Public Policy/Can J Aging 1997;16(suppl): 132-46.
Reeder CE, Nelson AA. The differential impact of copayment on drug use in a Medicaid population. Inquiry 1985;22: 396-403.
Soumerai SB, Avorn J, Ross-Degnan D, Gortmaker S. Payment restrictions for prescription drugs in Medicaid: Effects on therapy, cost, and equity. New Engl J Med 1987;317: 550-6.
Motheral BR, Henderson R. The effect of a closed formulary on prescription drug use and costs. Inquiry 1999;36: 481-91.
Tamblyn R, Laprise R, Hanley JA, Abrahamowicz M, Scott S, Mayo N, et al. Adverse events associated with prescription drug cost-sharing among poor and elderly persons. JAMA 2001;285: 421-429.
Schneeweiss S, Walker AM, Glynn RJ, Maclure M, Dormuth C, Soumerai SB. Outcomes of reference pricing for angiotensin-converting enzyme inhibitors. New Engl J Med 2002;346: 822-9.
Horn SD, Sharkey PD, Tracy DM, Horn CE, James B, Goodwin F.Intended and unintended consequences of HMO cost-containment strategies: results from the managed care outcomes project. Am J Managed Care 1996;2: 253-64.
Horn SD, Sharkey PD, Phillips-Harris C. Formulary limitations and the elderly: results from the managed care outcomes project. Am J Managed Care 1998;4: 1105-13.
Barnett AA. HMO formularies lead to higher care costs. Lancet 1996;347: 894.
Soumerai SB, Ross-Degnan D. HMO formularies and care costs. Lancet 1996;347: 1264.
Fairman K, Teitelbaum F, Motheral B, Barrow SM, Thomas ME. Letter to the editor. Am J Managed Care 1996;2: 588-592;
Kravitz RL, Romano PS. Managed care cost containment and the law of unintended consequences. Am J Managed Care 1996;2: 323-324.
Cook TD, Campbell DT. Quasi-experimentation. Design and analysis issues for field studies. Boston: Houghton Mifflin, 1979.
Maclure M. Tom Chalmers 1917-95: part 2: the tribulations of a trialist. CMAJ 1996;155: 986-8.
Muers MF, Corris PA, eds. Nebuliser Project Group of the British Thoracic Society Standards of Care Committee. Current best practice for nebulizer treatment. Thorax 1997;52(suppl.2): S1-104.
Canadian Asthma Consensus Conference (CACC). Summary of recommendations. Can Respir J 1996;3: 89-100.
Muers MF. Overview of nebuliser treatment. Thorax 1997;52(suppl 2): S25-30.
Maclure M, Nakagawa R, Carleton BC. Applying research to the policy cycle: implementing and evaluating evidence-based drug policies in British Columbia. In: Clarke M, Fox DM, Langhorne P. Informing judgment: case studies of health policy and research in six countries. New York: Milbank Memorial Fund, 2001; 35-70.
Zelen M. A new design for randomized clinical trials. N Engl J Med 1979;300: 1242-5.
British Columbia Ministry of Health Services. Pharmacare trends 2000. Victoria BC, 2001.
Anderson GM, Kerluke KJ, Pulcins IR, Hertzman C, Barer ML. Trends and determinants of prescription drug expenditures in the elderly: data from the British Columbia Pharmacare program. Inquiry 1993;30: 199-207.
Williams JI, Young W. Inventory of studies on the accuracy of Canadian health administrative databases. Technical report. Toronto: Institute for Clinical Evaluative Sciences (ICES), 1996.
Daniel WW. Biostatistics: a foundation for analysis in health sciences. New York: Wiley, 1991.
Diehr P, Yanez D, Ash A, Hornbrook M, Lin DY. Methods for analyzing health care utilization and costs. Annu Rev Public Health 1999;20: 125-44.
Liang K-Y, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika 1986;73: 13-22.
Thompson SG, Barber JA. How should cost data in pragmatic randomised trials be analysed? BMJ 2000;320: 1197-200.
Barber JA, Thompson SG. Analysis of cost data in randomized trials: an application of the non-parametric bootstrap. Stat Med 2000;19: 3219-36.
Schneeweiss S, Maclure M, Soumerai SB, Walker AM, Glynn RJ. Quasi-experimental longitudinal designs to evaluate drug benefit policy changes with low policy compliance. J Clin Epidemiol 2002;55: 833-41.
Gillings D, Makuc D, Siegel E: Analysis of interrupted time series mortality trends: an example to evaluate regionalized perinatal care. Am J Public Health 1981;71: 38-46.
Veney JE, Kaluzny AD. Evaluation and decision making for health services. Part V: Trend analysis. 2nd ed. Ann Arbor, MI: Health Administration Press, 1991.
Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992;45: 613-9.
Glynn RJ, Buring JE: Ways of measuring rates of recurrent events. BMJ 1996;312: 364-7.
Akaike H. A new look at the statistical model identification. IEEE Transaction on Automatic Control 1974;19: 716-23.
Zelen M. Author's reply to compliance, bias, and power in clinical trials. Biometrics 1991;47: 778-9.
Goodman SN, Berlin JA. The use of predicted confidence intervals when planning experiments and the misuse of power when interpreting results. Ann Int Med 1994;121: 200-6.
Bowton DL, Goldsmith WM, Haponik EF: Substitution of metered-dose inhalers for hand-held nebulizers: success and cost-savings in a large, acute care hospital. Chest 1992;101: 305.
Jasper AC, Mohsenifar Z, Kahan S, Goldberg HS, Koerner SK. Cost-benefit comparison of aerosol bronchodilator delivery methods in hospitalized patients. Chest 1987;91: 614.
Chappell N, Maclure M, Brunt H, Hopkinson J, Mullett J, Thomson ME. Seniors' views of medication reimbursement policies: bridging research and policy at the point of policy impact. Can J Aging 1997; 114-31.(Sebastian Schneeweiss, as)