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R ES E A R C H, Intervention and control this effect is easier to interpret than a com. 1 Main components of the, The intervention consisted of three major posite score. Medication Review Checklist, parts education academic detailing giving We constructed ordinal outcome meas. Each section contained a list of problems to ures for each of the targeted drugs The. prescribing information and feedback, consider and potential solutions to any scoring algorithm of a neutral score 0. medication risk assessment and completion problems. of a medication review checklist success 1 ie recommendation was fol. Awareness of number of drugs used lowed or failure 1 ie recommendation. The education component was conducted, Compliance issues was not followed was decided prior to the.
by a clinical pharmacist with experience in, conducting medication reviews for nursing Several specific drug categories intervention details available from the. benzodiazepines tricyclic authors on request The individual drug. home patients The pharmacist visited each, antidepressants selective serotonin scores were then added up to form a com. doctor twice and provided tailored educa reuptake inhibitors antipsychotics other. tion on how to conduct medication reviews posite score a six point ordinal outcome. sedatives hypnotics tranquilisers, with em phasis on benzodiazepines measure A nurse blinded to group alloca. antidepressants non steroidal anti, NSAIDs COX 2 inibitors and antihyperten inflammatory drugs cyclooxygenase 2 tion and the project manager independ. sives Sources of information on prescribing inhibitors other analgesics diuretics ently assessed the composite score At 12. were provided 10 11 including one page lam blockers blockers angiotensin month follow up a nurse and a doctor who. inated desk size sheets GPs also received converting enzyme inhibitors calcium were blinded to group allocation assessed. feedback on the number of targeted drugs channel blockers H2 antagonists proton the composite score independently Agree. used by their patients pump inhibitors prochlorperazine ment between the two assessors was 99. metoclopramide oral corticosteroids Self reported secondary outcome meas. Doctors received Practice Incentive Pay, sulfonylureas metformin other ures were the proportions of participants.
ments after completing 10 medication hypoglycaemics digoxin quinine. review checklists and were reimbursed for using benzodiazepines excluding benzodi. allopurinol over the counter or, their time with the pharmacist azepines used for epilepsy NSAIDs and. complementary medicines and warfarin, Intervention group participants com thiazide diuretics the proportion receiving a. Adverse drug reactions, pleted a Medication Risk Assessment12 medication review the proportion having. Recommendation section, while in the waiting room They handed the falls 14 15 and the participants quality of life. form to their doctor who then decided as assessed by the SF 12 version 2 stand. whether the patient would benefit from a ard form 16 and EQ 5D17 questionnaires. medication review The form contained 31 Participants were asked to bring to the. items assessing risk factors for medication phone all the medicines taken in the previ Statistical analyses. misadventure for example having three ous 7 days and to spell out the brand name Statistical analyses were conducted using. or more health problems using more than and other details of each medication All SAS version 8 02 SAS Institute Cary NC. four medicines and having possible side drugs were classified according to the Ana USA and SUDAAN version 9 0 Research. effects such as sleep deprivation Doctors tomical Therapeutic Chemical Classification Triangle Institute Research Triangle Park. completed a Medication Review Checklist 200113 by two raters who coded independ NC USA All analyses were adjusted for. for at risk participants Box 1 ently and discussed points of difference clustering at the practice level Polytomous. Control group participants also com until 100 agreement on drug use was logistic regression was used to calculate the. pleted a Medication Risk Assessment but reached The kappa statistic for agree odds ratios ORs of a person in the inter. the forms were collected by the researchers ment between coders adjusted for overall vention group having a better outcome for. rather than being handed to the GP Control prevalence of drug use and bias was 0 81 the composite score than a person in the. doctors received no intervention except for 95 CI 0 64 0 96 and the overall pro control group At 4 month follow up the. completing a clinical audit to encourage portion of agreement between raters on categories 0 and 1 were combined as. participation in the study which included drug use was 90 this was the only combination for which the. feedback on the number of medication As the prevalence of drug use is a crude proportional odds assumption was met at a. reviews and medication risk factors reflection of appropriate prescribing we four level ordinal scale 2 16 8 df 10. developed a composite score Simply P 0 08 At 12 month follow up no four. recording the prevalence of drug use does level category was found to meet the pro. Data collection and measurement not take into account other important issues portional odds assumption hence a three. Consenting participants were contacted by such as dose reductions Even small scale level category was chosen with the highest P. trained telephone interviewers at baseline on changes when added up can have a signifi value by combining 0 1 and 2 2. average 3 weeks after recruitment and at 4 cant effect on improving the use of medi 4 3 df 5 P 0 50 Logistic regression. and 12 month follow up to record informa cines In addition multiple testing can lead analysis was used for binary outcome vari. tion about medication reviews drug use to type 1 errors if all separate drug changes ables and linear regression analysis for qual. falls quality of life and socio demographic are included in the analyses The propor ity of life scores Crude and adjusted results. factors Participants unable to complete the tions of participants using specific medi for a priori potential confounders were cal. telephone interview were visited at home cines were also included in the analysis as culated. Copies of the laminated desk size sheets with information about the targeted drugs Medication Sample size calculation. Risk Assessment form Medication Review Checklist and prescribing feedback are available from The sample size was based on the propor. the authors on request tions of participants using benzodiazepines. 24 MJA Volume 187 Number 1 2 July 2007,R ES E A R C H.
NSAIDs and thiazide diuretics 18 The larg problems identified during the reviews and hypertensive patients and less likely to be. est sample size needed to detect a difference actions taken to solve those problems have seen in patients who have been using anti. on the three outcome measures was for been published elsewhere 20 hypertensive drugs without any problems. NSAIDs with 398 participants required for Characteristics of doctors in the two Moreover as specialists have a substantial. each group With a power of 0 8 0 05 groups were generally similar except that impact on prescribing there may be a need. an intra class correlation of 0 01 19 an seven doctors in the intervention group had to involve both GPs and specialists in efforts. expected maximum cluster size of 60 parti had over 20 years experience in general to improve prescribing behaviour 22. cipants per practice and an inflation factor practice compared with only two in the Compared with our study Zermansky et. of 1 59 because of clustering we needed to control group Participants in the interven al5 reported a large increase in medication. inflate the sample size this sample was tion and control groups were reasonably review rates over a 1 year period during. sufficient to detect a 10 reduction from similar at baseline details available from the their intervention in the United Kingdom. 25 to 15 in the proportion of partici authors on request except that the inter 97 of patients in the intervention group. pants using an NSAID Allowing for 10 vention group contained a higher propor had medication reviews compared with 44. loss to follow up over 4 months we esti tion of women 67 versus 51 We in the control group This difference may be. mated that about 440 participants per group adjusted for this in the analysis Participants attributable to several factors In the study. would be required in the intervention group had higher odds of by Zermansky et al a pharmacist conducted. having an improved composite score than medication reviews and review rates were. Ethical approval control group participants OR 1 86 95 determined from medical records whereas. CI 1 21 2 85 at 4 month follow up but we relied on self report Thus medication. Ethical approval was received from the Aus not at 12 month follow up Box 3 Partici. tralian National Department of Veterans reviews may have been under reported in. pants in the intervention group had lower our study. Affairs the University of Newcastle Human odds of using NSAIDs than control group. Research Ethics Committee and the Hunter The effect of our intervention on the. participants at 4 month follow up but not at number of falls was more visible after 12. Health Research Ethics Committee 12 months No significant changes were months than after 4 months It may be that. found for benzodiazepines or thiazide diu the higher number of reported falls over a. RESULTS retics at 4 and 12 month follow up 12 month period increased the power of the. At 4 month follow up crude ORs but study to detect a difference The interven. Twenty three of 195 doctors invited to par, not adjusted ORs showed significant differ tion itself may have had other effects as it. ticipate in our study agreed to do so a, ences between the groups in relation to the addressed issues besides drug use such as. response rate of 12 The flow of partici, proportion of people having falls Box 4 At compliance postural hypotension and doc. pants is summarised in Box 2 Twenty GPs, 12 month follow up intervention group tors awareness of falls eg as a risk factor on. from 16 practices took part Recruitment, participants had lower adjusted odds of the Medication Risk Assessment form.
took place in 2002 and 12 month follow,having a fall fall injury or fall requiring. up finished in January 2004 Participation Alternatively the apparent impact on falls. medical attention The intervention pro, rates were higher in the intervention group may have been due to a type 1 error or to. duced no significant difference in quality of, 2 2 18 P 0 16 Reasons for loss to loss of some patients to follow up A higher. life scores after adjustment for age sex and, follow up were similar between the two proportion of intervention group partici. baseline scores Box 5, groups There were no statistically signifi pants aged 85 years were lost to follow.
cant differences between participants lost to up which may partly explain the lower. follow up and those who remained in the DISCUSSION proportion of falls in the intervention group. study in relation to sex and occurrence of Our intervention which aimed to encourage at follow up Also there may have been self. previous falls by experimental group How medication review by GPs improved medi report bias with those in the intervention. ever a higher proportion of intervention cines use in the short term but not in the group being less likely to report falls how. group participants aged 85 years were lost longer term and the effects were modest ever previous research shows that partici. to follow up 2 8 93 P 0 03 Prescription of NSAIDs was the only drug pants in intervention groups are more likely. All doctors in the intervention group use measure to show a statistically signifi to report falls 14 Our results are supported. except one who dropped out had two aca cant change As in a similar Australian by other studies aimed at reducing falls. demic detailing visits The first visit took study 21 thiazide diuretic use did not through medication review However these. place before patient recruitment so that doc increase There was a reduction in falls in interventions also addressed fall risk factors. tors were aware of what to look for when the intervention group that was sustained other than drugs such as home modifica. identifying patients for medication review over a 12 month period This was not easily tion Dr Sue Carter Director of Strategic and. One doctor conducted reviews with all explained by changes in medication use and Clinical Service Planning Division of Popu. patients on the same day the Medication may be a chance finding but it raises the lation Health Planning and Performance. Risk Assessment was completed and so did possibility that the intervention had other Hunter New England Area Health Service. not actually see all the participants medica effects see below NSW personal communication or exer. tions ideally patients should have been The intervention may not have adequately cise 23 Meredith et al 24 who solely addressed. invited back for a separate consultation to addressed barriers to prescribing thiazides medication problems for older people found. show the doctor their medications Another There may be conceptual and behavioural no effect of their intervention on falls. doctor did not conduct any medication differences between adding and reducing There was an apparent tendency for qual. reviews arguing that all patients medica medications Changes in prescribing are ity of life scores to increase over time in. tions were checked routinely Drug related more likely to occur in newly diagnosed both groups but adjusted ORs showed the. MJA Volume 187 Number 1 2 July 2007 25,R ES E A R C H. 2 Flow of participants, 195 general practitioners from 86 practices invited to take part. 2 GPs ineligible moved out of area 4 refused, 3 reported not having enough older patients 1 on holidays. 2 involved in other studies at the time Reasons unknown. 23 GPs from 18 practices agreed to take part 1 dropped out prior to randomisation due to holidays. Randomised 22 GPs from 17 practices,CONTROL INTERVENTION. General practice General practice, Allocated to usual care 9 GPs from 7 practices Allocated to intervention 13 GPs from 10 practices.
GP non participation GP participation GP participation GP non participation. N 0 N 9 7 practices N 11 9 practices N 2,Patient recruitment Patient recruitment. Assessed for eligibility n 566 from 7 practices Assessed for eligibility n 544 from 9 practices. Ineligible Eligible Eligible Ineligible,N 11 N 555 N 539 N 5. Nursing home n 1 Nursing home n 1,Aged 65 years n 10 Aged 65 years n 4. Non participation Participated Participated Non participation. N 158 28 N 397 7 practices N 452 9 practices N 87 16. Refused n 89 Mean cluster size 57 Mean cluster size 50 Refused n 50. Other reasons n 69 Range 41 124 Range 5 132 Other reasons n 37. Lost to baseline Completed baseline survey Completed baseline survey Lost to baseline. N 20 N 352 N 397 N 25,Refused n 11 Refused n 12,Moved n 1 Moved n 1. Language barrier n 1 Reasons not completed N 25 Reasons not completed N 30 Language barrier n 2. Other reasons n 6 Non contact n 12 Non contact n 17 Other reasons n 10. Ineligible nursing home Unwell n 11 Unwell n 11,n 1 Holiday n 1 Holiday n 2.
4 MONTH FOLLOW UP, Lost to follow up Completed follow up Completed follow up Lost to follow up. N 13 survey analysed survey analysed N 23, Refused n 5 N 329 7 practices N 368 9 practices Refused n 10. Moved n 2 Mean cluster size 47 Mean cluster size 41 Moved n 2. Other reasons n 3 Range 27 102 Range 5 111 Other reasons n 8. Ineligible 3 deaths n 3 Ineligible 2 nursing home, Reasons not completed N 35 Reasons not completed N 36 and 1 death n 3. Non contact n 12 Non contact n 13,Unwell n 21 Unwell n 19. Holiday n 2 Holiday n 4,12 MONTH FOLLOW UP, Lost to follow up Completed follow up analysed Completed follow up analysed Lost to follow up.
N 34 N 309 7 practices N 350 9 practices N 31, Refused n 1 Mean cluster size 44 Mean cluster size 39 Refused n 4. Moved n 1 Range 25 92 Range 5 103 Other reasons n 22. Other reasons n 24 Ineligible 1 nursing,Ineligible 4 nursing home and 4 deaths n 5. home and 4 deaths n 8 Reasons not completed N 21 Reasons not completed N 23. Non contact n 12 Non contact n 9,Unwell n 7 Unwell n 10. Holiday n 2 Holiday n 3,26 MJA Volume 187 Number 1 2 July 2007. 3 Number of patients reporting having had a medication review since taking part in the study and drug use at baseline and at 4 and 12 month follow. up by experimental group logistic regression and comparison of composite scores at 4 and 12 month follow up by experimental group polytomous. logistic regression,Baseline 4 month follow up 12 month follow up.
n N n N COR 95 CI P AOR 95 CI P n N COR 95 CI P AOR 95 CI P. Medication review, Intervention group 55 396 14 101 368 28 5 55 2 88 10 68 0 001 7 95 3 50 18 30 0 001 74 350 21 4 33 2 20 8 52 0 001 6 10 3 35 11 11 0 001. Control group 56 341 16 21 329 6 1 1 18 309 6 1 1,Benzodiazepines. Intervention group 30 397 8 28 368 8 0 45 0 19 1 04 0 060 0 51 0 20 1 30 0 14 26 350 7 0 61 0 27 1 37 0 21 0 65 0 27 1 57 0 31. Control group 42 352 12 51 329 16 1 1 36 309 12 1 1. NSAIDs including COX 2 inhibitors, Intervention group 94 397 24 72 368 20 0 67 0 44 1 00 0 049 0 62 0 39 0 99 0 044 76 350 22 0 82 0 57 1 19 0 28 0 77 0 51 1 16 0 19. Control group 99 352 28 88 329 27 1 1 78 309 25 1 1. R ES E A R C H,Thiazide diuretics, Intervention group 75 397 19 65 368 18 0 75 0 49 1 16 0 18 0 70 0 48 1 01 0 06 66 350 19 0 86 0 55 1 34 0 47 0 85 0 53 1 38 0 50. Control group 70 352 20 73 329 22 1 1 66 309 21 1 1. 4 month follow up 12 month follow up,MJA Volume 187 Number 1 2 July 2007.
Composite score 2 1 0 1 2 3 2 1 0 1 2 3, Intervention group 0 37 10 215 58 98 27 18 5 0 0 41 12 192 55 95 27 22 6 0. Control group 7 2 56 17 158 48 98 30 10 3 0 5 2 42 14 149 48 104 34 9 3 0. AOR adjusted odds ratio COR crude odds ratio COX 2 inhibitors cyclooxygenase 2 inhibitors NSAIDs non steroidal anti inflammatory drugs Drug use in the past 7 days Adjusted for clustering general. practice Medication review in past 12 months Adjusted for general practice baseline medication review sex age use of four or more medicines SF 12 summary scores Adjusted for general practice sex age SF. 12 summary scores Intraclass correlation coefficient for NSAIDs was 0 0026 COR 2 04 95 CI 1 29 3 21 P 0 004 AOR 1 86 95 CI 1 21 2 85 P 0 0076 Adjusted for general practice sex age SF 12 summary. scores COR 1 37 95 CI 0 89 2 11 P 0 14 AOR 1 33 95 CI 0 83 2 14 P 0 22 Composite score 2 worst possible score 0 neutral 3 best possible score Data expressed as number of patients with. that score, 4 Comparison of falls at baseline and at 4 and 12 month follow up by experimental group logistic regression analysis. Baseline 4 month follow up 12 month follow up, Questions relating to falls n N n N COR 95 CI P AOR 95 CI P n N COR 95 CI P AOR 95 CI P. Have you slipped tripped or stumbled inside or outside your home in the last xi months definition a momentary loss of balance that does not include a fall. Intervention group 122 396 31 68 365 19 0 90 0 51 1 56 0 68 1 00 0 59 1 68 1 0 94 339 28 0 79 0 54 1 17 0 22 0 83 0 52 1 35 0 43. Control group 119 351 34 66 324 20 1 1 96 294 33 1 1. Have you had a fall inside or outside your home in the last xi months definition body comes to rest unintentionally on the floor ground no longer weight bearing does not include slips. trips or stumbles, Intervention group 86 396 22 46 366 13 0 76 0 60 0 96 0 02 0 90 0 69 1 18 0 43 70 350 20 0 57 0 40 0 81 0 0036 0 61 0 41 0 91 0 02. Control group 100 351 29 52 327 16 94 309 30 1 1, Have you been injured as a result of a fall in the last xi months definition body comes to rest unintentionally on the floor ground no longer weight bearing.
Intervention group 58 396 15 21 366 6 0 63 0 42 0 93 0 025 0 74 0 48 1 14 0 15 35 350 10 0 51 0 31 0 84 0 011 0 56 0 32 0 96 0 04. Control group 71 351 20 29 327 9 1 1 55 308 18 1 1. R ES E A R C H, Have you needed to seek medical attention eg doctor hospital for an injury from a fall trip or accident in the last xi months. Intervention group 43 396 11 15 366 4 0 62 0 37 1 06 0 08 0 67 0 38 1 18 0 15 22 350 6 0 45 0 31 0 65 0 0004 0 46 0 30 0 70 0 0014. Control group 54 351 15 21 327 6 1 1 40 308 13 1 1. Have you had any other injury from an accident at your home in the last xi months eg burns cuts bruises from gardening kitchen tasks broken furniture etc. MJA Volume 187 Number 1 2 July 2007, Intervention group 96 396 24 98 364 27 1 08 0 61 1 92 0 77 1 20 0 68 2 12 0 50 92 347 27 0 84 0 50 1 44 0 51 0 91 0 49 1 68 0 74. Control group 97 350 28 83 327 25 1 1 91 304 30 1 1. Have you felt faint weak or dizzy in the last month especially at first standing up in the morning. Intervention group 93 396 24 97 364 27 1 08 0 76 1 54 0 65 1 51 0 88 2 60 0 12 85 349 24 0 91 0 61 1 35 0 61 1 16 0 76 1 76 0 46. Control group 107 351 31 82 326 25 1 1 81 309 26 1 1. AOR adjusted odds ratio COR crude odds ratio Adjusted for clustering general practice Source of questions Mackenzie et al and Cohen et al Data expressed as number of participants answering yes. to question Adjusted for general practice baseline score sex age SF 12 summary score xi 3 for 4 month follow up xi 12 for baseline and 12 month follow up. R ES E A R C H,differences to be non significant Simi. regression coefficient MCS Mental Component Summary PCS Physical Component Summary VAS Visual Analog Scale Adjusted for clustering general practice Adjusted for general practice baseline score. larly a systematic review investigating the,Adjusted results. effects of pharmaceutical services on,quality of life25 concluded that what.
appeared to be a positive trend was non, 5 Mean and standard error SE for SF 1216 and EQ 5D17 summary scores at baseline and at 4 and 12 month follow up by experimental group. significant,0 15 0 008 0 02,Limitations,The doctors low response rate to the. 12 month follow up,invitation to participate in our study may. limit the generalisability of the findings,as it is likely that participating doctors. Crude results,were those with an interest in medicine.
related issues in elderly patients How,ever participating GPs demographic and. 0 89 0 01 0 018 0 012,practice characteristics were similar to. national data The low response rate was,in line with the rate for other high. intensity intervention studies 26 27 Patient,80 4 0 8 response rates were difficult to deter. mine as office staff did not always sys,tematically record information about.
non participants Reasons for loss to fol,low up were similar in both groups The. fact that participation rates were higher,in the intervention group raises questions. Adjusted results,about the effectiveness of blinding Fur. thermore improvements were found in,the control group as well suggesting a. 0 086 0 001 0 021,Hawthorne effect Our study was under.
0 087 0 59,powered to detect significant differences. for the proportions of benzodiazepines,NSAIDs and thiazide diuretics used. between study arms due to higher loss of,4 month follow up. participants to follow up than expected,Academic detailing took place before. Crude results,patient recruitment In addition the tele.
phone surveys occurred on average 3,weeks after participants signed the con. 0 86 0 01 0 028 0 015,sent form The data collected during the. telephone interviews may therefore not,truly represent baseline data but rather a. first point of time measurement It is,therefore possible that for some inter. vention group participants medicine use,had already improved by the time of.
collecting baseline information If this is,the case the true impact of improved. 0 83 0 02 365,0 78 0 02 327,prescribing observed in our study may. have been underestimated,Intervention group 389 54 13 0 4. 339 53 07 0 8,linear regression analysis,Our approach of recording the preva. lence of use of several targeted drugs was,a crude measure of appropriate prescrib.
Intervention group 389,Intervention group 389,Intervention group 395. ing For example it did not take into,account the indications for prescribing. EQ 5D index score,For all the outcome measures we,attempted to approximate participants. Control group,Control group,Control group,Control group. Quality of life,comorbidity profiles by controlling for.
quality of life which has been shown to,be correlated with physical and mental. health conditions 28,MJA Volume 187 Number 1 2 July 2007 29. R ES E A R C H, Self reporting of medicine use may lead to COMPETING INTERESTS 12 Pit S Byles J Prevalence of self reported risk. bias The reliability of self reporting was factors for medication misadventure among older. None identified,people in general practice J Eval Clin Pract 2007. validated by comparing self reports with In press, findings obtained from home visits and 13 WHO Collaborating Centre for Drug Statistics.
AUTHOR DETAILS, pharmaceutical claims data There was high Methodology Anatomical therapeutic chemical. agreement between self reported and actual Sabrina W Pit MSc PhD Research Fellow1 ATC classification index with defined daily doses. drug use 90 for home visits and 86 Julie E Byles BMed PhD Director2 DDDs Oslo WHO Collaborating Centre for. David A Henry MB ChB FRCP Professor of Drug Statistics Methodology 2001. for pharmaceutical claims data 7 The com, Clinical Pharmacology1 14 Mackenzie L Byles J D Este C Validation of self. posite score also showed high agreement Lucy Holt BPharm Clinical Pharmacist 3 reported fall events in intervention studies Clin. between self reported and actual drug use Vibeke Hansen BA Psych Hons Senior Rehabil 2006 20 331 339. obtained from home visits 0 87 95 Research Officer1 15 Cohen I Rogers P Burke V Beilin L Predictors of. CI 0 76 0 98 Deborah A Bowman BA Senior Research medication use compliance and symptoms of. hypotension in a community based sample of,Standardised instruments were used to Officer1. elderly men and women J Clin Pharm Ther 1998, measure falls and quality of life The only 1 School of Medical Practice and Public Health 23 423 432. measure that had not been validated in Faculty of Health University of Newcastle 16 Ware JE Turner Bowker DM Kosinski M Gandek. Newcastle NSW B SF 12v2 how to score version 2 of the SF 12. previous research was patient self report of, 2 Research Centre for Gender Health and Health Survey Lincoln QualityMetric Incorpo.
having a medication review This issue was,Ageing Faculty of Health University of rated 2002. addressed by carefully training the inter Newcastle Newcastle NSW 17 Tamim H McCusker J Dendukuri N Proxy. viewers and explaining to the participants 3 Mater Hospital Newcastle NSW reporting of quality of life using the EQ 5D Med. what was meant by a medication review in Correspondence Care 2002 40 1186 1195. our study sabrina pit newcastle edu au 18 Donner A Klar N Design and analysis of cluster. randomization trials in health research London,Arnold 2000. Conclusion 19 Underwood M Barnett A Hajioff S Cluster rand. REFERENCES, Systems for medication review have the omization a trap for the unwary Br J Gen Pract. 1 Roughead EE Barratt JD Gilbert AL Medication 1998 48 1089 1090. potential to reduce costs to the health care related problems commonly occurring in an Aus. 20 Pit S Byles J Cockburn J Medication review, system by improving the use of medicines tralian community setting Pharmacoepidemiol patient selection and general practitioner s report. and reducing adverse events such as falls It Drug Saf 2004 13 83 87. of drug related problems and actions taken in, appears that continued reinforcement of 2 Soumerai SB McLaughlin TJ Avorn J Improving elderly Australians J Am Geriatr Soc 2007 55.
drug prescribing in primary care a critical analysis 927 934. appropriate prescribing is required to sus of the experimental literature Milbank Q 1989. tain long term improvements 21 Bolton G Tipper S Tasker J Medication review. 67 268 317,by GPs reduces polypharmacy in the elderly a. Our results suggest that this type of inter 3 Grimshaw J Thomas R MacLennan G et al Quality Use of Medicines program Aust J Primary. vention could be routinely used in general Effectiveness and efficiency of guideline dissemi Health 2004 10 78 82. practice to improve use of medicines and that nation and implementation strategies Health. 22 Robertson J Fryer JL O Connell DL et al The,Technol Assess 2004 8 6 iii iv 1 72. it may help reduce falls among older people impact of specialists on prescribing by general. 4 Grimshaw JM Shirran L Thomas R et al Chang, without adversely affecting quality of life practitioners Med J Aust 2001 175 407 411. ing provider behavior an overview of systematic,23 Tinetti ME Baker DI McAvay G et al A multifac. reviews of interventions Med Care 2001 39 8,torial intervention to reduce the risk of falling.
Suppl 2 II2 II45, ACKNOWLEDGEMENTS among elderly people living in the community N. 5 Zermansky AG Petty DR Raynor DK et al Clini,Engl J Med 1994 331 821 827. Professor Jill Cockburn deceased is especially cal medication review by a pharmacist of patients. 24 Meredith S Feldman P Frey D et al Improving, acknowledged She conceived designed ana on repeat prescriptions in general practice a. medication use in newly admitted home health, lysed and interpreted the results of our study until randomised controlled trial Health Technol. care patients a randomized controlled trial J Am, October 2004 We thank all the GPs in particular Assess 2002 6 20 1 86.
Geriatr Soc 2002 50 1484 1491, Dr Parker Magin and Dr Peter Hopkins and their 6 Sellors J Kaczorowski J Sellors C et al A rand. 25 Pickard AS Johnson JA Farris KB The impact of, patients for participating Chris Bonner for advice omized controlled trial of a pharmacist consulta. pharmacist interventions on health related qual, and for providing the Therapeutic flags manual tion program for family physicians and their. ity of life Ann Pharmacother 1999 33 1167 1172, Professor Tony Smith for advice Professor Paul elderly patients CMAJ 2003 169 17 22. 26 Kable S An application of interactive computer, Glasziou for developing the grant the Royal Aus 7 Pit S Improving quality use of medicines for older.
programs to promote adherence to clinical prac, tralian College of General Practitioners for approv people in general practice PhD thesis New. tice guidelines for childhood asthma in general, ing parts of the research as a clinical audit and as a castle NSW University of Newcastle 2004. practice PhD thesis Newcastle NSW University, continuing professional development activity and 8 Henry D Lim LL Garcia Rodriguez LA et al. of Newcastle 2004, the National Prescribing Service for approving Variability in risk of gastrointestinal complications. 27 Reeve JF Peterson GM Rumble RH Jaffrey R, Practice Incentive Payments We also thank the with individual non steroidal anti inflammatory.
Programme to improve the use of drugs in older, advisory group members interviewers and statisti drugs results of a collaborative meta analysis. people and involve general practitioners in com, cians in particular Christophe Lecathelinais and BMJ 1996 312 1563 1566. munity education J Clin Pharm Ther 1999 24, Sara Wheeles The National Health and Medical 9 Scottish Intercollegiate Guidelines Network. Research Council provided funding and Sabrina Hypertension in older people A national clinical. 28 Pettit T Livingston G Manela M et al Validation. Pit received a University of Newcastle Postgradu guideline Edinburgh SIGN 2001. and normative data of health status measures in, ate Scholarship as a PhD student The funding 10 Australian medicines handbook Adelaide Aus. older people the Islington study Int J Geriatr, bodies had no input into the content or prepara tralian Medicines Handbook Pty Ltd 2002.
Psychiatry 2001 16 1061 1070, tion of this article 11 Bonner C Tett S Minck S Therapeutic flags. Australian Clinical Trials Registration Number Healthy prescribing for the elderly Brisbane Uni. 012605000264684 versity of Queensland 2001 Received 9 Sep 2006 accepted 30 Apr 2007.

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