• criteria;
  • inappropriate prescribing;
  • prescribing omissions;
  • screening tool;
  • screening tool of older person's potentially inappropriate prescriptions;
  • screening tool to alert doctors to the right treatment


  1. Top of page
  2. Summary
  3. What is Known and Objective
  4. Methods
  5. Results and Discussion
  6. What is New and Conclusion
  7. Funding
  8. References

What is known and Objective

Potentially inappropriate prescribing (PIP) has significant clinical, humanistic and economic impacts. Identifying PIP in older adults may reduce their burden of adverse drug events. Tools with explicit criteria are being developed to screen for PIP in this population. These tools vary in their ability to identify PIP in specific care settings and jurisdictions due to such factors as local prescribing practices and formularies. One promising set of screening tools are the STOPP (Screening Tool of Older Person's potentially inappropriate Prescriptions) and START (Screening Tool of Alert doctors to the Right Treatment) criteria. We conducted a systematic review of research studies that describe the application of the STOPP/START criteria and examined the evidence of the impact of STOPP/START on clinical, humanistic and economic outcomes in older adults.


We performed a systematic review of studies from relevant biomedical databases and grey literature sources published from January 2007 to January 2012. We searched citation and reference lists and contacted content experts to identify additional studies. Two authors independently selected studies using a predefined protocol. We did not restrict selection to particular study designs; however, non-English studies were excluded during the selection process. Independent extraction of articles by two authors used predefined data fields. For randomized controlled trials and observational studies comparing STOPP/START to other explicit criteria, we assessed risk of bias using an adapted tool.

Results and Discussion

We included 13 studies: a single randomized controlled trial and 12 observational studies. We performed a descriptive analysis as heterogeneity of study populations, interventions and study design precluded meta-analysis. All observational studies reported the prevalence of PIP; however, the application of the criteria was not consistent across all studies. Seven of the observational studies compared STOPP/START with other explicit criteria. The STOPP/START criteria were reported to be more sensitive than the more-frequently-cited Beers criteria in six studies, but less sensitive than a set of criteria developed in Australia. The STOPP criteria identified more medications associated with adverse drug events than the 2002 version of the Beers criteria. Patients with PIP, as identified by STOPP, had an 85% increased risk of adverse drug events in one study (OR = 1·85, 95% CI: 1·51–2·26; P < 0·001). There was limited evidence that the application of STOPP/START criteria optimized prescribing. Research involving the application of STOPP/START on the impact on the quality of life was not found. The direct costs of PIP were documented in three studies from Ireland, but more extensive analyses on the economic impact or studies from other jurisdictions were not found.

What is new and Conclusion

The STOPP/START criteria have been used to review the medication profiles of community-dwelling, acute care and long-term care older patients in Europe, Asia and North America. Observational studies have reported the prevalence and predictors of PIP. The STOPP/START criteria appear to be more sensitive than the 2002 version of the Beers criteria. Limited evidence was found related to the clinical and economic impact of the STOPP/START criteria.

What is Known and Objective

  1. Top of page
  2. Summary
  3. What is Known and Objective
  4. Methods
  5. Results and Discussion
  6. What is New and Conclusion
  7. Funding
  8. References

The health care of older adults presents significant challenges to patients, caregivers, healthcare providers and healthcare systems. Many factors contribute to this challenge, including (i) the increasing size of the demographic[1, 2]; (ii) the biological process of ageing, which may lead to increased sensitivity to drug effects due to changes in body composition (e.g. altered distribution volumes and altered permeability of the blood–brain barrier), reduced ability to eliminate drugs (e.g. changes in liver metabolism and renal capacity), malnutrition and cachexia[3, 4]; (iii) the increased potential for and impact of comorbidities, multiple conditions and polypharmacy[5]; and (iv) limited availability and access to appropriate evidence regarding drug effectiveness and safety in older and frail patients (i.e. studies have not been carried out, not synthesized or not in the public domain).[6-8]

Older adults exert a significant demand, due to disease burden on healthcare resources.[9-11] Potentially inappropriate prescribing (PIP) is reported to be highly prevalent in this age group and has been associated with adverse drug events (ADEs) leading to hospitalization and death.[12] In the United States, from 2007 to 2009, ADEs were responsible for approximately 100 000 emergency hospitalizations of adults 65 years and older.[13] In Canada, the cost of ADE-related emergency department visits and subsequent hospitalizations for adults aged 66 and older was estimated to be $35·7 million per year in 2007.[14]

Inappropriate prescribing occurs when the risks associated with prescribing a medication outweigh the potential benefit of the medication in a particular patient. Various measures of PIP have been developed. For example, PIP may occur when medications are prescribed: (i) with no clear evidence-based indication; (ii) in higher doses or for a longer period than necessary; (iii) in combination with other drugs from the same drug class; (iv) in combination with other drugs that may lead to drug–drug or drug–illness interactions; (v) for patients who are susceptible to certain ADEs, for example, benzodiazepines in patients with a history of falls; and (vi) instead of a more cost-effective medication that is equally or more therapeutically effective.[15]

Potentially inappropriate prescribing may also occur when a patient does not receive a medication indicated for the treatment or prevention of a disease or condition.[16] This may occur due to ageism, economic concerns, fear of adverse events or lack of prescribing knowledge.[4, 17, 18]

Early detection of PIP may prevent ADEs and improve geriatric care.[6, 19] PIP prevalence can often prove to be a useful indicator of prescribing quality.[7] In addition, evidence indicates that discontinuing inappropriate medications may improve subjective quality of life in older adults.[20]

In 1991, Mark Beers and colleagues created a list of drugs that were considered to be inappropriate for use in older adults in long-term care facilities.[21] The Beers criteria have been revised and updated on a number of occasions since their development, with the most recent iteration being published in 2012.[22-24] Although considered a cornerstone to the optimization of pharmaceutical care in older adults in the United States,[25] older versions have been criticized for their (i) limited transferability/applicability outside of the United States; (ii) failure to address a number of common PIPs (e.g. drug–drug and drug–disease interactions); (iii) failure to include criteria relating to potential underprescribing; and (iv) lack of user-friendly organization (e.g. by physiological systems).[15, 26, 27] As a result, at least 13 other explicit screening tools have been developed, many of which are specific to the country for which they were developed.[28-37] Many different clinicians including pharmacists, geriatricians, nurse practitioners, internists and researchers have used these different sets of explicit criteria to assess PIP across different healthcare settings and jurisdictions.[19, 27-41] The 2012 iteration of the Beers criteria has addressed some, but not all of the criticisms listed above.[24]

STOPP (Screening Tool of Older Person's potentially inappropriate Prescriptions) and START (Screening Tool to Alert doctors to the Right Treatment) are evidence-based sets of criteria, which were developed in Ireland using a modified Delphi process that involved 18 experts in geriatric pharmacotherapy from across the United Kingdom and Ireland.[42, 43] STOPP consists of 65 criteria that help researchers and healthcare personnel systematically identify potentially inappropriate medications (PIMs). START, consisting of 22 criteria, identifies potential prescribing omissions (PPOs).

The STOPP and START criteria may offer advantages over the Beers criteria and other screening tools. The criteria are organized according to the physiological systems to which each relate, thereby enhancing their useability.[42, 43] In addition, rather than listing specific medications, which make transferability to different countries with different formularies more difficult, STOPP and START criteria refer to classes of medications. To date, the STOPP/START criteria have been used by a variety of researchers across a number of healthcare settings in a number of different jurisdictions in Europe,[44-46] Taiwan[47] and the United States.[48]

There is a demonstrated research momentum towards the STOPP/START criteria, especially in the European Union. Our initial search on this subject found 17 records published in 2007–2009, 16 published in 2010, and 44 in 2011. In 2010, Levy and colleagues indicated that the STOPP/START criteria may be a good choice as an universal explicit criteria.[41] In 2012, a group of researchers and clinicians chose the STOPP/START criteria as the ‘most appropriate’ choice for evaluating the prescribing of patients with multiple chronic conditions in Spain.[49] These tools have been proposed as the most appropriate for assessing PIP in the Netherlands.[50] The European Union Geriatric Medicine Society (EUGMS) have also recently announced their support for the STOPP/START criteria.[51]

To our knowledge, no systematic review of the application and impact of STOPP/START has been undertaken. Although there is research establishing a relationship between PIP identified by STOPP/START criteria and other screening tools and adverse drug reactions, hospitalization rates and increased health services costs, this research is still in its infancy, and further study is needed to establish the full extent and true impact of this relationship.[37, 52]

This review informs researchers, clinicians and policy makers about the quality and extent of evidence relating to the STOPP/START criteria. Specifically, it provides an overview of studies documenting STOPP- and START-identified PIP prevalence and outcomes in different healthcare settings and jurisdictions. In addition, with the development of electronic health records, administrative databases and computer-assisted order entry, integration of a reliable and validated set of criteria into these systems offers the potential for optimization of care with reasonable and sustainable expense and effort. Therefore, a systematic review of this nature is of particular value at this time.

Our objective was to conduct a systematic review of research studies to describe the application of STOPP/START criteria and to examine the evidence of the impact of STOPP/START on clinical, humanistic and economic outcomes in older adults.


  1. Top of page
  2. Summary
  3. What is Known and Objective
  4. Methods
  5. Results and Discussion
  6. What is New and Conclusion
  7. Funding
  8. References

Identification of studies

Methods of the search strategy and inclusion criteria were specified in advance and documented in a protocol, which is available upon request. The methods of analyses were not predetermined due to the anticipated heterogeneity of the results.

Randomized trials and non-randomized study designs investigating the impact and application of the STOPP/START criteria in adults aged 65 years and older were included. No language or publication restrictions were used in the original search; however, non-English studies and unpublished data were not included in the synthesis. Studies were eligible if published or accepted for publication between January 2007 and January 2012; studies only published as abstracts were excluded. The eligibility criteria allowed access to all studies dated from the development of the criteria through to January 2012. Studies that used modified or a truncated list of STOPP/START criteria were considered for inclusion.

Data from studies that involved the application of STOPP/START to measure the prevalence of intervene in, or report predictors of, PIP were included. Indicators of the clinical and humanistic impact of the use of STOPP/START criteria on the patient and healthcare system (ADEs, physician visits, emergency department visits, hospitalization and quality of life) were developed by consensus and included in the protocol. Data demonstrating the economic impact of STOPP/START on PIP in older patients were also included.

Biomedical databases and grey literature sources were systematically searched for published studies, prepublication presentations and abstracts. Keywords ‘STOPP and START’, ‘STOPP Criteria’ and ‘START Criteria’ with the limit ‘Aged 65+ years’ (January 2007 to January 2012) were applied to Cochrane Library, Database of Abstracts of Reviews of Effectiveness (DARE), PubMed, EMBASE, CINAHL, ISI Web of Science, International Pharmaceutical Abstracts, Google Scholar, TRIP Database,, metaRegister of Controlled Trials (mRCT), ProQuest Dissertation and Theses Database, and Index to Theses in Great Britain and Ireland. References from all included studies and systematic reviews of explicit criteria, which included STOPP/START, were searched. Citing articles, as identified by ISI Web of Science and Google Scholar, were examined. Experts in the field and authors of prepublication presentations, abstracts and registered clinical trials were contacted to identify studies that were in the process of publication. Authors of articles not available in English were contacted to see whether English translations were available. The search was conducted in December 2011 and was followed with RSS feeds from MEDLINE (PubMed) and EMBASE until January 2012 by one author (BHT).

A title and abstract review of studies was performed independently in an unblinded standardized manner by two authors (DOS & BHT). Letters to the editor, commentaries and review articles were excluded. The full text of potentially relevant studies not eliminated by title and abstract was reviewed independently by both reviewers. Consensus was easily reached in the selection of included studies, and the two authors independently agreed to choose 13 of 77 citations.

Data extraction

A data extraction form was designed using Google Docs software (form available on request). The form was pilot-tested on two included studies and revised. Two authors independently performed the data extraction (DOS & BHT). One author checked extracted data for agreement (BHT). There were no disagreements in data extraction, beyond clarification of definitions and criteria.

Information extracted included the following: (i) study design including methods and units of randomization, prospective vs. retrospective, characteristics of control group, data sources and time period; (ii) intervention details such as the professional designation of the health professional involved, criteria applied and a brief description; (iii) description of the location and setting, numbers and characteristics of participants including age, sex and numbers of medications prescribed; (iv) type of outcome measures reported; (v) results and key conclusions by the authors; and (vi) sources of funding.

Risk of bias assessment

Two authors (DOS, RC) independently assessed the risk of bias in eight of the included articles – the randomized controlled trial (RCT) and observational studies that involved a comparison with another criteria.[17, 46, 52-57] The assessment was made using a modified quality assessment scale initially designed for studies of prognostic factors (QUIPS)[58] and was based on six domains: study participation, data collection, application of the STOPP/START criteria, outcome measurement, study confounding, and statistical analysis and presentation. Each domain contained a checklist of three to nine components, which were used to render a score of low, moderate or high risk of bias for the entire domain. After independent review, both authors met to reconcile discrepancies in scoring each domain. Prior to discussion, reviewers initially agreed on 23 of 49 domain ratings (48%); 94% of domains were rated no more than one category apart with discrepancies commonly due to differing opinions on the potential severity of the possible bias. Consensus was easily reached in all assessments.

We did not assess the risk of bias of cross-sectional studies that described the prevalence of PIPs using the STOPP/START criteria.

Heterogeneity of study populations, interventions and study design precluded meta-analysis. Descriptive analysis was performed. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) has been used in reporting this review.[59]

Results and Discussion

  1. Top of page
  2. Summary
  3. What is Known and Objective
  4. Methods
  5. Results and Discussion
  6. What is New and Conclusion
  7. Funding
  8. References

Search results

A search of relevant biomedical databases provided a total of 133 records: other sources including Google Scholar identified 31 records. Duplicates and records that did not meet the inclusion criteria were removed, leaving a total of 13 records: 12 observational studies[17, 42, 44, 46, 52, 54, 55, 57] and a RCT.[55] (Fig. 1)


Figure 1. Flow diagram.

Download figure to PowerPoint

Study characteristics

Clinicians and researchers from the Republic of Ireland and Northern Ireland, including members of the original development team of the criteria, published eight of the included studies.[17, 42-44, 52, 54, 55, 57] Gallagher was the lead author in both the only international comparative study examining PIP across six European jurisdictions[46] and the only RCT[55] that examined the effect that the application of the STOPP/START criteria could have on prescribing appropriateness and patient-related outcomes. Five other studies used the STOPP and/or the START criteria to evaluate PIP in older adults in Spain[53, 56], the United States[48] and Taiwan.[47] Retrospective data were used in five of the observational studies.[44, 47, 48, 53, 60]

This review includes the application of STOPP/START to the health records of approximately 344 957 adults, all aged 65 years and older. (Table 1) The exact number of patients included is impossible to determine due to potential for crossover between the older patients included in the Cork-based hospital or long-term care studies and the database study.[17, 42, 44, 46, 52, 54, 55, 57] The majority of participants were from the Northern Ireland and the Republic of Ireland (99·5%), reflecting both the large size of the study performed on the pharmacy database[44] and the smaller sizes of the other studies with non-Irish participants.[46-48, 53, 56, 60] The mean age of participants ranged from 74·9[57] to 86·9 years[60]; however, some studies did not report mean age.[44, 46, 54, 55] The majority of participants were female (from 53%[55] to 80%[56, 60]), except in two studies performed in veterans’ hospitals in Taiwan and the United States where 26%[47] and 1%[48] of the study population were female, respectively. The mean number of medications prescribed per participant ranged from 5[57] to 12·9[48] in ten studies.[17, 42, 47, 48, 52, 54-56, 60]

Table 1. Characteristics of studies included in systematic review of STOPP/START criteria
SourceStudy designCriteria appliedCriteria applied byCompared criteriaPopulationCountryData source#AgeSexMean no. Rx/Patient
  1. STOPP, screening tool of older person's prescriptions; START, screening tool to alert doctors to right treatment. Rx prescriptions.

Barry et al. (2007)[42]Observational – prospectiveFull STARTPhysicianNoneCommunity-dwelling patients being admitted to acute careIrelandElectronic database and paper-based medical records600Mean (range): 77·9 ± 6·856% FemaleMean: 5·4
Gallagher & O'Mahony (2008)[54]Observational – prospectiveFull STOPPPhysicianBeers (2002)[23]Community-dwelling patients being admitted to acute careIrelandMedical records from community healthcare and acute care facility715Median (range): 77 (65–94)54% FemaleMean (range): 6·2 (0–21)
Ryan et al. (2009)[57]Observational – cross-sectionalFull STOPP and full STARTResearch pharmacistBeers (2002)[23]Community-dwelling patientsIrelandElectronic and paper-based medical records1329Mean: 74·9 ± 6·4 (65–97)61% FemaleMean (range): 5·0 (1–19)
Pyszka et al. (2010)[48]Observational – cohortModified STOPP Full STARTClinical PharmacistNoneCommunity-dwelling patients being admitted to acute care and discharged back to community careUnited StatesElectronic medical records111Mean: 78·4 ± 5·4 (70+)1% FemaleMean: 12·9 (on Admission); 14·2 (discharge); 14·1 (Follow-up)
Conejos et al. (2010)[53]Observational – prospective (hospital geriatric clinic) and cross-sectional (community-dwelling and long-term care)Modified STOPP Modified STARTIndependent observerBeers (2002)[23]Community-dwelling, hospital geriatric clinic, and long-term care patientsSpainElectronic medical records and pharmacy claims database150Mean: 81·6 ± 6·3 (69+)62% FemaleNot reported
Cahir et al. (2010)[44]Observational – cross-sectionalPartial STOPPDatabaseNoneCommunity-dwelling patientsIrelandElectronic pharmacy claims database338801Not reported (70+)57% FemaleNot reported
Liu et al. (2011)[47]Observational – cross-sectionalFull STOPP and full STARTPhysicianNoneAcute care patients at dischargeTaiwanMedical records from an acute care facility520Mean: 79·2 ± 6·7 (65+)26% Female6·6 ± 3·2
Gallagher et al. (2011)[55]RCTFull STOPP and full STARTPhysicianMedication Appropriateness Index and Assessment of Underutilization indexCommunity-dwelling patients being admitted to acute care and dischargedIrelandPatient or caregiver, community care and hospital medical records382Median (range), control 77 (65+); intervention 74·5 (65+)53% FemaleControl: 8·0, intervention: 7·4
Gallagher et al. (2011)[46]Observational – prospectiveFull STOPP and full STARTConsultants and senor residents in the field of geriatric medicineBeers (2002)[23]Community-dwelling patients admitted to multiple acute care facilities in 6 different countriesSwitzerland, Ireland, Spain, Belgium, Italy, Czech RepublicPatient or caregiver, community care and hospital medical records900Median (range): 82 (65+)61% FemaleNot reported
Byrne et al. (2011)[17]Observational – cross-sectionalFull STOPPResearch pharmacistBeers (2002)[23]Long-term-care-dwelling patients in multiple facilitiesIrelandElectronic database and paper-based medical records630Mean (range): 83·4 ± 7·1 (65–99)75% Female7·8
García-Gollarte et al. (2011)[56]Observational – cross-sectionalFull STOPP and full STARTPhysician with experience in the care of older personsAustralian (Basger et al.)[28]Community-dwelling, hospital or long-term care patients being admitted to multiple long-term care facilitiesSpainElectronic medical records100Mean (range): 84·7 ± 7·5 (65+)80% Female6·5 ± 2·9
Hamilton et al. (2011)[52]Observational – prospectiveFull STOPPNot specifiedBeers (2002)[23]Community-dwelling, hospital or long-term care patients being admitted to acute care facilityIrelandPatient or caregiver, community care and hospital medical records600Range: 65+60% Female7·5
Parsons et al. (2012)[60]Observational – cross-sectionalPartial STOPPDatabaseNoneLong-term-care patients living with dementia in multiple facilitiesBritainMedication Administration Records119Mean (range): 86·9 ± 6·7 (69–106)80% Female8 ± 3·4

The majority of participants in the included studies were community dwelling (99·5%), who were assessed in either the primary care setting (community dwelling)[44, 53, 57] or while transitioning to a secondary care setting[42, 46, 48, 52, 54, 55, 57]; 0·5% of participants were divided between secondary care[47, 53] and long-term care[17, 53, 56, 60] (570 and 799 patients, respectively).

Five of the studies, including the RCT, applied the full STOPP and START criteria to participant's medication profiles,[46, 47, 55-57] three studies applied the STOPP criteria,[17, 52, 54] and one study applied the START criteria.[42] Four research teams used modified versions of the criteria.[44, 48, 53, 60] Pyszka and colleagues noted that ‘Medications without an appropriate diagnosis were the most common type of STOPP criteria that was identified’,[48] although this is not one of the original STOPP criteria.[43] Conejos and colleagues[53] used the Spanish version of the criteria in their study.[61] Two of the studies applied a shortened/condensed version of the STOPP criteria to electronic databases without diagnoses or laboratory data being available.[44, 60] The criteria selected for use in these studies were chosen ‘on a consensus basis by an expert panel of five members in geriatric pharmacotherapy, clinical pharmacology, pharmacoepidemiology and academic general practice’.[44] Cahir states that their research team applied 30 of the STOPP criteria.[44] Parsons states that their team used 31 STOPP criteria based on the list developed by Cahir and colleagues.[60]

Prevalence of potentially inappropriate prescribing

The observational studies reported the prevalence of PIP.[17, 42, 44, 46-48, 52-54, 56, 57, 60] The prevalence of patients with at least one instance of PIP identified by the STOPP criteria ranged from 21·4%[57] to 79%[56]; however, interpretation of this range should be made with caution due to the heterogeneity in both sample population and study design between the different studies.

The observational studies also outlined the most commonly encountered instances of prescribing potentially inappropriate medications[17, 42, 44, 46-48, 52-54, 56, 57, 60]: (i) PPI for peptic ulcer disease at full therapeutic dosage for > 8 weeks[17, 44, 46, 52, 56, 57, 60]; (ii) long-term (i.e. >1 month), long-acting benzodiazepines and benzodiazepines with long-acting metabolites[17, 44, 46, 47, 52-54, 56, 57]; and (iii) long-term (i.e. >1 month) neuroleptics as long-term hypnotics.[46, 47, 56, 60]

The START criteria identified at least one instance of PPO in 22·7%[57] to 74%[56] of patients. Seven studies outlined frequently encountered PPO instances[42, 46-48, 53, 56, 57]: (i) calcium and vitamin D supplement in patients with known osteoporosis[46, 48, 56, 57]; (ii) statin therapy in patients with documented history of coronary, cerebral or peripheral vascular disease, where the patients' functional status remains independent for activities of daily living and life expectancy more than 5 years[42, 46, 48, 53, 56, 57]; and (iii) statin therapy in diabetes mellitus if fasting serum cholesterol >5·0 mm or additional cardiovascular risk factor(s) present.[46, 47, 53]

Several authors reported the percentage or number of criteria that were useful in identifying PIPs in their study populations.[17, 46, 53, 54, 56, 57, 60] For example, Gallagher and colleagues found that 86·1% of the STOPP and 100% of the START criteria were used in the identification of PIP in their study population.[46] Overall, in those studies using full, unmodified criteria,[17, 46, 54, 56, 57] 43·1%[57] to 86·1%[46] of the 65 STOPP (median 56·9%) and 68·2%[57] to 100%[46] (median 88·7%) of the 22 START criteria were used in the identification of PIPs.

Application of STOPP/START

There were few challenges to applying either STOPP or START criteria documented in the thirteen studies. Five studies reported the need to consult multiple sources of medical history documentation to apply the criteria, including electronic and paper sources of information and direct contact with patients, caregivers and healthcare professionals.[42, 53-55, 57] Specifically, authors listed the following sources of medical history documentation: referral letters from general practitioners, patients' own medications lists, pharmacy records, hospital admission records, chart reviews, telephone consultation with general practitioners and dispensing pharmacists, patient and/or caregiver interviews, prescription claims databases and electronic medical records.[42, 53-55, 57] One researcher noted that the inadequate documentation in patients' charts of the rationale for prescribing or not prescribing medications made the application of the criteria difficult.[48]

One researcher noted that there was ‘a short but significant learning curve with the criteria’[57], which may lead to higher application times until familiarity develops. Not all studies reported the training or background of the individuals applying the criteria (see Table 1). There was also little or no information available regarding the impact of the professional role, beliefs, intentions or goals of the researcher on the application of the criteria.

Seven of the studies applied the criteria at a time when the patient was transitioning from one care setting to another.[42, 46, 48, 52, 54-56] As patients are often under stress with regard to their health when in the emergency department or when moving from one healthcare setting to another, it may be difficult to obtain an accurate medication history. In addition, the healthcare system may not facilitate accurate and timely medication reconciliation during care setting transitions.

Four studies reported the time taken to apply the STOPP and/or START criteria once the data were collected or extracted.[42, 55-57] An average of 3 min was taken to apply the START criteria in one study,[42] and 3–4·5 min was taken to apply both criteria.[55-57]

Predictors of potentially inappropriate prescribing

Predictors of PIP were reported in nine studies.[17, 42, 44, 46, 47, 52, 54, 57, 60] Age 75 years and older[44, 47] or 85 years and older[42], female sex[42, 44, 54] and polypharmacy (multiple medications)[46, 47, 54] were all reported to be associated with increased odds of PIP. However, in one study, after adjusting for polypharmacy, the direction of the association between PIP and female gender and age was reversed.[44] Additionally, in one study, after adjusting for age, sex, comorbidity, chronic cognitive impairment, baseline activities of daily living function and number of medications, the likelihood of an ADE increased for each STOPP PIP instance.[52] Correlations were also observed between the number of medications prescribed,[17, 57, 60] increasing comorbidity as measured by the Charlson Comorbidity Index[57] and the identification of PIP by the STOPP criteria. Age 85 years and older, female sex, increasing comorbidity (Charlson Comorbidity Index greater than or equal to 2) and polypharmacy (10 or greater prescriptions) were also reported to be significantly associated with higher PPO (identified by START).[46] Heterogeneity in the break points used when converting continuous variables (age, polypharmacy (number of medications) and comorbidity (vs. multiple morbidity) into categorical variables make comparison of predictors of PIP and PPO difficult.

Comparator explicit criteria

Six studies compared the applicability and sensitivity of STOPP and the 2002 version of the Beers criteria.[17, 46, 52-54, 57] One study[56] compared STOPP/START criteria to a set of Australian criteria.[28] All studies that compared the STOPP and Beers criteria found that STOPP was more sensitive than Beers.[17, 46, 52-54, 57] In all of these studies, the Beers criteria were used as the standard PIP screening tools in older adults. The Beers criteria do not contain criteria for evaluating potential PPOs; however, a comparison between START and the Australian criteria developed by Basger and colleagues[28] provided a comparator for PPO detection. Results from this study show that the Basger's criteria appear to exhibit an increased sensitivity for PPO in older adults in long-term care.[56]

Clinical and humanistic outcomes

In a RCT, carried out by Gallagher and colleagues, it was reported that the application of the STOPP/START criteria in the form of an intervention, whereby a clinician recommends changes to the clinical team looking after the patient, significantly improved prescribing appropriateness. This was assessed by the Medication Appropriateness Index (absolute risk reduction of 35·7%) and the Assessment of Underutilization index (absolute risk reduction 21·2%).[55] This improvement was sustained over a 6-month follow-up period. The prevalence of falls and all-cause mortality was lower in the intervention group, but differences were not statistically significant (5·8% of the intervention group and 8·4% of the control group had at least one fall, = 0·332; 5·3% of the intervention group and 7·3% of the control group died, = 0·414). There was also a trend towards a lower frequency of primary care visits during the follow-up period in the STOPP/START group (= 0·063).

Two studies attempted to establish an association between the identification of PIP by the STOPP criteria and potentially avoidable ADEs.[52, 54] Both studies found that the STOPP criteria was significantly more sensitive at identifying medication that may be associated with an ADE than with the Beers criteria. In the more recent study, each PIP as identified by STOPP increased the risk of ADEs by 84·7% (OR = 1·847, 95% CI 1·506–2·264; < 0·001); in contrast, PIPs identified by 2002 Beers criteria did not significantly increase the risk of an ADE (OR = 1·276, 95% CI: 0·945–1·722; = 0·11).[52]

Research involving the application of STOPP/START and the impact on the quality of life was not reported in any of the studies included in this review.

Economic outcomes

The direct costs of PIP were documented in three studies, two of which were performed in the Republic of Ireland[42, 44] and one was performed in both Northern Ireland and the Republic of Ireland.[17] Barry and colleagues determined that the wholesale cost of the PPO instances identified by the START criteria in their study population was € 188 per patient per year in 2007.[42] Also, in 2007, Cahir and colleagues reported that the cost associated with the PIP instances defined by a condensed version of the STOPP criteria and identified in their study population was € 318 per patient per year.[44] Byrne and colleagues determined that the cost associated with the PIP instances identified in their study population was € 263 per patient per year (excluding ‘prn’ medicines).[17] To date, no studies were found that performed a more detailed economic analysis relating to the cost-effectiveness of the intervention in terms of clinical or quality of life outcomes. (Table 2).

Table 2. Outcomes of studies included in systematic review of STOPP/START criteria
SourceCriteria appliedNo. of ptsPrevalenceMost freq criteria applied% Criteria detecting PIMs/PPOsPredictors of PIP: OR (95% CI), or Spearman's Rho (rs)Clinic, humanistic, economic outcomesOther outcomes
  1. STOPP, screening tool of older person's prescriptions; START, screening tool to alert doctors to right treatment; PPO, potential prescribing omissions; PIM, potentially inappropriate medication; PIP, Potentially inappropriate prescribing; BZD, benzodiazepines; PPI, proton pump inhibitors; ACE, angiotensin-converting enzyme; NSAID, non-steroidal anti-inflammatory drug; ASA, acetylsalicylic acid; Ca, calcium; DM, diabetes mellitus; CHF, congestive heart failure; CCI, Charlson Comorbidity Index; tx, treatment; RoI, Republic of Ireland; NI, Northern Ireland; RCT, randomized controlled trial.

  2. a

    Adjusted for gender.

Barry et al. (2007)[42]Full START60057·8% had 1 or more PPOsSTART: statins/vascular disease; Warfarin/chronic atrial fibrillation; antiplatelet tx/arterial disease Age ≥85: 2·08 (1·24–3·50), P < 0·01 female sex: 2·29 (1·65–3·19), P < 0·01Economic: cost to supply PPO3 min to apply START
Gallagher & O'Mahony (2008)[54]Full STOPP71535% had 1 or more PIMsSTOPP: long-term BZDs; duplicate drug class; BZDs/history of falls60% STOPP detected PIMsFemale sex: 1·87 (1·14–3·07), P = 0·014 5 or less medications: 0·59 (0·37–0·96), P = 0·032Hospitalization due to ADE 
Ryan et al. (2009)[57]Full STOPP/START132921·4% had 1 or more PIMs, 22·7% had 1 or more PPOsSTOPP: PPI at max tx > 8 wks; long-term BZDs; NSAIDs/hypertension. START: antiplatelet tx/arterial disease; vitamin D/osteoporosis; statins/vascular disease43·1% STOPP detected PIMs, 68·2% START-detected PPOsNumber of medications prescribed: rs = 0·356, P < 0·01; Age: rs = 0·071, P < 0·01, comorbidity: rs = 0·210, P < 0·01 3 min to apply STOPP; 1 min to apply START
Pyszka et al. (2010)[48]Modified STOPP/Full START11158·6% had 1 or more PIMs, 46·8% had 1 or more PPOs on admissionSTOPP: medications without appropriate diagnosis (added criteria); ASA dosages >150 mg daily. START: statins/vascular disease, ACE inhibitor/CHF; vitamin D/osteoporosis    
Conejos et al. (2010)[53]Modified STOPP/START15047% had 1 or more PIMs, 43% had 1 or more PPOsSTOPP: BZDs/history of falls; duplicate drug class. START: statins/vascular disease; statins/DM with cardiovascular risk51% STOPP detected PIMs, 82% STARTdetected PPOs   
Cahir et al. (2010)[44]Partial STOPP33880136% had 1 or more PIPsSTOPP: PPI at max tx > 8 wks; NSAIDS for > 3 consecutive months; long-term BZDs; duplicate drug class Female sex: 1·10 (1·08–1·12), ≥75 yearsa; 1·28 (1·26-1·30)Economic: cost of PIMs 
Liu et al. (2011)[47]Full STOPP/START52036·2% had 1 or more PIMs. 41·9% had 1 or more PPOsSTOPP: BZDs, neuroleptics, 1st generation antihistamines/history of falls; Ca channel blockers/chronic constipation. START: statins/DM with cardiovascular risk; antiplatelet tx/arterial disease; metformin/type 2 DM Age 75-84: 1·90 (1·16–3·12), P = 0·011; age ≥85:2·27 (1·26–4·07), P = 0·006; 5–8 medications 2·66 (1·58–4.46), P = 0·001, ≥9 medications 7·18 (4·12–12·50), P = 0·001  
Gallagher et al. (2011)[55]Full STOPP/START382    Mortality, GP visits, hospital readmissions, and fallsMedication Appropriateness Index (MAI) and Assessment of Underutilization (AOU) index at multiple times over 6-month period, 3 min to apply STOPP/START
Gallagher et al. (2011)[46]Full STOPP/START90051·3% (34·7 to 77·3% by country) had 1 or more PIMs, 59·4% (51·3 to 72·7% by country) had 1 or more PPOsSTOPP: BZDs, neuroleptics/history of falls; duplicate drug class; PPI at max tx >8 weeks. START: vitamin D/osteoporosis; statins/vascular disease; statins/DM with cardiovascular risk86·1% STOPP detected PIMs, 100% STARTdetected PPOsSTOPP: 6-10 medications: 2·31 (1·68–3·18), P < 0·001, >10 medications: 7·22 (4·30–12·12), P < 0·001, P < 0·001; START: Age ≥85: 1·80 (1·18–2·75), P = 0·006; CCI ≥2: 3·25 (2·01–5·26), P < 0·001; dementia: 0·70 (0·51–0·97), P = 0·030.  
Byrne et al. (2011)[17]Full STOPP630RoI: 73% had 1 or more PIMs. NI: 67% had 1 or more PIMsSTOPP: PPI at max tx >8 weeks; BZDs/history of falls; duplicate drug class; neuroleptics/history of falls69% STOPP detected PIMsRoI: total number of medications: rs = 0·356, P < 0·01; >5 medications rs = 0·135, P < 0·01) NI: total number of medications: rs = 0·356, P < 0·01; >5 medications rs = 0·256, P < 0·01)Economic: costs of PIMs 
García-Gollarte et al. (2011)[56]Full STOPP/START10079% had 1 or more PIMs. 74% had 1 or more PPOsSTOPP: PPI at max tx > 8 weeks; BZDs/history of falls; neuroleptics/history of falls. START: vitamin D/osteoporosis; statins/vascular disease; antiplatelet tx/arterial disease56·9% STOPP detected PIMs, 95·4% STARTdetected PPOs  3 min to apply STOPP/START
Hamilton et al. (2011)[52]Full STOPP60056·2% had 1 or more PIMsSTOPP: PPI at max tx > 8 weeks; ASA/no history of vascular disease; BZDs/history of falls; duplicate drug class Composite of age, sex, comorbidity, chronic cognitive impairment, baseline activities of daily living function, number of medications: 1·85 (1·51–2·26), P < 0·001Adverse drug events 
Parsons et al. (2012)[60]Partial STOPP11946·2% and 40·9% had 1 or more PIMs at 2 time pointsSTOPP: long-term neuroleptics; NSAIDS >3 weeks; PPI at max tx >8 weeks20% STOPP detected PIMsNumber of medications: rs = 0·335, P < 0·01  

Bias appraisal

Critical appraisal for study bias was performed. Four studies were judged to have a low risk of bias,[46, 54, 55, 57] two were rated as having moderate risk of bias[17, 56] and two were rated as having high risk of bias.[52, 53] We judged that seven studies adequately controlled for bias related to the study participation, outcome, application of STOPP/START and confounding measurement domains.[17, 46, 52-55, 57] We scored three as having a low risk of bias due to methods of data collection,[46, 54, 57] and five studies scored a low risk of bias due to approach for application of the STOPP/START tool.[17, 46, 54-56] One study was found to have a high risk of bias with regard to the application of the screening tool.[53] A moderate or high risk of bias was found among five of the eight assessed studies in the statistical analysis and data presentation domains.[17, 46, 52, 53, 57]


Reported funding was entirely by governmental or non-governmental organizations. The Health Research Board of Ireland supplied funding for six of the studies.[42, 44, 46, 52, 54, 55] Additionally, Enterprise Ireland funding assisted Hamilton and colleagues,[52] and the Czech Ministry of Health Internal Grant Agency assisted Gallagher and colleagues with their international study.[46] Byrne and colleagues' project was funded by the Centre for Ageing Research and Development in Ireland (CARDI).[17] The National Institute for Health Research assisted those working with Parsons and Johnston.[60] Pyszka reported no external funding or sponsorship,[48] and the remaining four studies did not report any source of funding.[47, 53, 56, 57]


The prevalence and predictors of PIP reported in this review may provide useful benchmarks for prescribing quality in older adults in the future. The generalizability of these findings may be limited by the marked variation and heterogeneity in the study design, PIP detection methodologies employed and study populations between the different studies.

An association between the application of STOPP criteria and the identification of potentially avoidable ADEs has been reported,[52, 54] and this may lead to an impact on clinical outcomes. Gallagher and colleagues provide evidence of improved and sustained prescribing appropriateness when STOPP and START criteria are applied.[55] However, as acknowledged by the authors, the study was not powered to detect a clinically significant difference between groups in regard to all-cause mortality, nor was the follow-up sufficiently long to allow detection of a potentially significant reduction in the prevalence of falls or readmission.[55] Overall, the evidence is not sufficiently robust to determine the impact that the STOPP/START criteria may have on clinical or humanistic outcomes.

Research on the use of STOPP/START appears to still be in its infancy, but it is gaining momentum. With agencies such as the European Union Geriatric Medicine Society providing their backing to these criteria,[51] it is likely that they will continue to be used. Future research should employ strong methodological design and be sufficiently powered. It will be interesting to see how the 2012 version of Beers criteria fares in comparative studies. These future studies should not only focus on PIP, but should also examine the relationship between PIP and patient-related outcomes. Future research could also focus on the development and evaluation of intervention strategies to improve prescribing.

There were limitations associated with this review at the study level, between studies and at the review level. With the exception of one publication[55], the STOPP/START studies used an observational design, five of which used retrospective data.[44, 47, 48, 53, 60] For the prospective studies, a strategy of consecutive sampling was employed in an additional six studies.[42, 46, 52, 54, 56, 57] Several studies had sample populations of 150 patients or less,[48, 53, 56, 60] and several studies had populations that were restricted to one hospital.[42, 47, 48, 52, 54]

The criteria applied varied between studies. Although referred to as ‘STOPP’ or ‘START’, some researchers used versions of the criteria that had been modified for their jurisdictional prescribing practices or formularies.[48, 53] The criteria were also shortened in two studies to apply the criteria to certain healthcare databases not holding or linked to clinical data such as diagnoses and laboratory results.[44, 60] Not all researchers had access to complete medication profiles including over-the-counter medications. One study reported that they had access to medication lists from the hospital studied, but that patients may have simultaneously been taking other medications prescribed by other physicians.[47] No study indicated an attempt to document or evaluate adherence to drug therapy. Researchers who had used pharmacy claims data were only able to confirm that patients had made a claim for medications, not that they have actually taken the medication. These inconsistencies may limit the generalizability of the results.

We were unable to assess studies published in languages other than English.[45],[61-64] Furthermore, at least 20 studies were only available as abstracts and were excluded.

Following the cut-off of our systematic review period (January 2012), researchers from the United Kingdom, Ireland, Malaysia, Spain, Belgium, Germany and Australia have published primary studies using the STOPP/START criteria.[12, 65-74] This work expands the number of jurisdictions researching and publishing on the criteria and increases the experience of the criteria in long-term care facilities. Two publications may warrant additional attention: Dalleur and colleagues established a relationship between STOPP-identified PIPs and hospital admissions,[69] and Ryan and colleagues compared the application of the STOPP/START criteria with and without clinical data.[72] This latter research has implications for those wishing to apply the criteria to digital databases. The majority of the work continues to evaluate the prevalence and predictors of PIP, however, and does not significantly change the results of our review. There were no comparisons between STOPP/START and the 2012 iteration of Beers criteria found.

What is New and Conclusion

  1. Top of page
  2. Summary
  3. What is Known and Objective
  4. Methods
  5. Results and Discussion
  6. What is New and Conclusion
  7. Funding
  8. References

The STOPP/START criteria provide a promising framework for assessment of PIP in older adults. They may be more applicable than other explicit criteria for the assessment of PIP across all care settings from community to long-term care. Further work is needed to evaluate the true transferability of this set of criteria across the different care settings and jurisdictions. Research using the STOPP/START criteria has documented the prevalence of PIP in older adults in multiple healthcare settings and jurisdictions. In two observational studies, there also appears to be an association between the identification of PIP by STOPP and potentially avoidable ADEs; however, the true extent of this association still has to be elucidated. To date, the clinical, humanistic and economic impacts of the application of the STOPP/START criteria have not been well explored.


  1. Top of page
  2. Summary
  3. What is Known and Objective
  4. Methods
  5. Results and Discussion
  6. What is New and Conclusion
  7. Funding
  8. References

This review was funded, in part, by the Drug Evaluation Alliance of Nova Scotia. Dr. Ingrid Sketris held a chair funded by CHSRF/CIHR and co-sponsored by NHSRF. Barbara Hill-Taylor received funding from this chair. David O'Sullivan received funding from the Health Research Board of Ireland grant no: HRA_HSR/2010/14 Dr. Stephen Byrne would like to acknowledge the support of The ‘Ireland Canada University Foundation- Dobbin Scholarship’.


  1. Top of page
  2. Summary
  3. What is Known and Objective
  4. Methods
  5. Results and Discussion
  6. What is New and Conclusion
  7. Funding
  8. References
  • 1
    United Nations, Department of Economic and Social Affairs, Population Division. World Population Ageing. Document ESA/P/WP/212. 2009. Available at: (accessed 22 November 2012).
  • 2
    Canadian Institutes of Health Research. Canadian Longitudinal Study on Aging. 2011. Available at: (accessed 22 November 2012).
  • 3
    Cruz-Jentoft A, Boland B, Rexach L. Drug therapy optimization at the end of life. Drugs Aging, 2012;29:511521.
  • 4
    Hanlon JT, Schmader KE, Ruby CM, Weinberger M. Suboptimal prescribing in older inpatients and outpatients. J Am Geriatr Soc, 2001;49:200209.
  • 5
    Reason B, Terner M, McKeag AM, Tipper B, Webster G. The impact of polypharmacy on the health of Canadian seniors. Fam Pract, 2012;29:427432.
  • 6
    O'Mahony D, Gallagher PF. Inappropriate prescribing in the older population; need for new criteria. Age Ageing, 2008;37:138141.
  • 7
    Spinewine A, Schmader KE, Barber N, Hughes C, Lapane K, Swine C, Hanlon JT. Appropriate prescribing in elderly people: how well can it be measured and optimised? Lancet, 2007;370:173184.
  • 8
    Konrat C, Boutron I, Trinquart L, Auleley GR, Ricordeau P, Ravaud P. Underrepresentation of elderly people in randomized controlled trials. The example of trials of 4 widely prescribed drugs. PLoS ONE, 2012;7:e33559.
  • 9
    Canadian Institute for Health Information. National Health Expenditure Trends, 1975 to 2010. 2010. Available at: (accessed 22 November 2012).
  • 10
    Hanley GE, Morgan S. Chronic catastrophes: exploring the concentration and sustained nature of ambulatory prescription drug expenditures in the population of British Columbia, Canada. Soc Sci Med, 2009;68:919924.
  • 11
    Hanley GE, Morgan S, Reid RJ. Explaining prescription drug use and expenditures using the adjusted clinical groups case-mix system in the population of British Columbia, Canada. Med Care, 2010;48:402408.
  • 12
    Wahab MSA, Nyfort-Hansen K, Kowalski SR. Inappropriate prescribing in hospitalized Australian elderly as determined by the STOPP criteria. Int J Clin Pharm, 2012;34:855862.
  • 13
    Budnitz DS, Lovegrove MC, Shehab N, Richards CL. Emergency hospitalizations for adverse drug events in older Americans. N Engl J Med, 2011;365:20022012.
  • 14
    Wu C, Bell CM, Wodchris WP. Incidence and economic burden of adverse drug reactions among elderly patients in Ontario emergency departments: a retrospective study. Drug Saf, 2012;35:769781.
  • 15
    O'Connor MN, Gallagher P, O'Mahony D. Inappropriate prescribing: criteria, detection and prevention. Drugs Aging, 2012;29:437452.
  • 16
    Lipton HL, Bero LA, Bird JA, McPhee SJ. Undermedication among geriatric outpatients: results of a randomized controlled trial. Annu Rev Gerontol Geriatr, 1992;12: 95108.
  • 17
    Byrne S, O'Mahony D, Hughes C, Parsons C, Pattterson S, McCormack B, Finn F. An Evaluation of the Inappropriate Prescribing in Older Residents in Long Term Care Facilities in the Greater Cork and Northern Ireland Regions Using the STOPP and Beers' Criteria. 2011. Centre for Ageing Research and Development in Ireland. Available at: (accessed 22 November 2012).
  • 18
    Cherubini A, Corsonello A, Lattanzio F. Underprescription of beneficial medicines in older people: causes, consequences and prevention. Drugs Aging, 2012;29:463475.
  • 19
    Tangiisuran B, Wright JE, van der Cammen TJM, Rajkumar C. Adverse drug reactions in the elderly: challenges in identification and improving preventative strategies. Age Ageing, 2009;38:358359.
  • 20
    Garfinkel D, Mangin D. Feasibility study of a systematic approach for discontinuation of multiple medications in older adults: addressing polypharmacy. Arch Intern Med, 2010;170:781787.
  • 21
    Beers MH, Ouslander JG, Rollingher I, Reuben DB, Brooks J, Beck JC. Explicit criteria for determining inappropriate medication use in nursing home residents. UCLA Division of Geriatric Medicine. Arch Intern Med, 1991;151:18251832.
  • 22
    Beers MH. Explicit criteria for determining potentially inappropriate medication use by the elderly. An update. Arch Intern Med, 1997;157:131136.
  • 23
    Fick DM, Cooper JW, Wade WE, Waller JL, Maclean JR, Beers MH. Updating the Beers criteria for potentially inappropriate medication use in older adults: results of a US consensus panel of experts. Arch Intern Med, 2003;163:27162724.
  • 24
    The American Geriatrics Society 2012 Beers Criteria Update Expert Panel. American geriatrics society updated Beers Criteria for potentially inappropriate medication use in older adults. J Am Geriatr Soc, 2012;60: 616631.
  • 25
    Martin CM. The updated Beers Criteria: use of evidence-based medication. Consult Pharm, 2012;27:602612.
  • 26
    Dimitrow MS, Airaksinen MS, Kivelä SL, Lyles A, Leikola SN. Comparison of prescribing criteria to evaluate the appropriateness of drug treatment in individuals aged 65 and older: a systematic review. J Am Geriatr Soc, 2011;59:15211530.
  • 27
    Page RL, Linnebur SA, Bryant LL, Ruscin JM. Inappropriate prescribing in the hospitalized elderly patient: defining the problem, evaluation tools, and possible solutions. Clin Interv Aging, 2010;5:7587.
  • 28
    Basger BJ, Chen TF, Moles RJ. Inappropriate medications use and prescribing indicators in elderly Australians: development of a prescribing indicators tool. Drugs Aging, 2008;25:777793.
  • 29
    Imai H, Beers MH, Fick DM, Njwata S, Obtaki K. Development of Japanese Beers criteria for inappropriate medication use in elderly patients [Japanese]. Japan Med Assoc J, 2008;137:8491.
  • 30
    Laroche ML, Charmes JP, Merle L. Potentially inappropriate medications in the elderly: a French consensus panel list. Eur J Clin Pharmacol, 2007;63:725731.
  • 31
    McLeod PJ, Huang AR, Tamblyn RM, Gayton DC. Defining inappropriate practices in prescribing for elderly people: a national consensus panel. CMAJ, 1997;156:385391.
  • 32
    Naugler CT, Brymer C, Stolee P, Arcese ZA. Development and validation of an improving prescribing in the elderly tool. Can J Clin Pharmacol, 2000;7:103107.
  • 33
    Pugh MJ, Hanlon JT, Zeber JE, Bierman A, Cornell J, Berlowitz DR. Assessing potentially inappropriate prescribing in the elderly Veterans Affairs population using the HEDIS 2006 quality measure. J Manag Care Pharm, 2006;12:537545.
  • 34
    Rancourt C, Moisan J, Baillargeon L, Verreault R, Danielle Laurin D, Grégoire JP. Potentially inappropriate prescriptions for older patients in long-term care. BMC Geriatr, 2004;4:9.
  • 35
    Winit-Watjana W, Sakulrat P, Kespichayawattana J. Criteria for high-risk medication use in Thai older patients. Arch Gerontol Geriatr, 2008;47:3551.
  • 36
    Zhan C, Sangi J, Bierman AS, Miller MR, Friedman B, Wickizer SW, Meyer GS. Potentially inappropriate medication use in the community-dwelling elderly: findings from the 1996 Medical Expenditure Panel Survey. JAMA, 2001;286:28232829.
  • 37
    Chang C, Chan D. Comparison of published explicit criteria for potentially inappropriate medications in older adults. Drugs Aging, 2010;27:947957.
  • 38
    Corsonello A, Pranno L, Garasto S, Fabietti P, Bustacchini S, Lattanzio F. Potentially inappropriate medication in elderly hospitalized patients. Drugs Aging, 2009;26:3139.
  • 39
    Gnjidic D, Hilmer SN. Use of potentially inappropriate medications in the care of frail older people. Aging Health, 2010;6: 705716.
  • 40
    Laroche ML, Charmes JP, Bouthier F, Merle L. Inappropriate medications in the elderly. Clin Pharmacol Ther, 2009;85:9497.
  • 41
    Levy HB, Marcus EL, Christen C. Beyond the Beers criteria: a comparative overview of explicit criteria. Ann Pharmacother, 2010; 44:19681975.
  • 42
    Barry PJ, Gallagher P, Ryan C, O'Mahony D. START (screening tool to alert doctors to the right treatment) – an evidence-based screening tool to detect prescribing omissions in elderly patients. Age Ageing, 2007;36:632638.
  • 43
    Gallagher P, Ryan C, Byrne S, Kennedy J, O'Mahony D. STOPP (Screening Tool of Older Person's Prescriptions) and START (Screening Tool to Alert doctors to Right Treatment). Consensus validation. Int J Clin Pharmacol Ther, 2008;46:7283.
  • 44
    Cahir C, Fahey T, Teeling M, Teljeur C, Feely J, Bennett K. Potentially inappropriate prescribing and cost outcomes for older people: a national inappropriate prescribing and cost outcomes for older people: a national population study. Br J Clin Pharmacol, 2010;69:543552.
  • 45
    Couderic AL, Bailly-Agaledes C, Camalet J et al. Adaptations des medicaments psychotropes chez les sujets ages de 75 ans et plus dans un service de medicine interne géeriatrique: à propos de 100 patients. [French]. Geriatr Psychol Neuropsychiatr Vieil, 2011;20:18.
  • 46
    Gallagher P, Lang PO, Cherubini A et al. Prevalence of potentially inappropriate prescribing in an acutely ill population of older patients admitted to six European hospitals. Eur J Clin Pharmacol, 2011a;67:11751188.
  • 47
    Liu CL, Peng LN, Chen YT, Lin MH, Liu LK, Chen LK. Potentially inappropriate prescribing (IP) for elderly medical inpatients in Taiwan: a hospital-based study. Arch Gerontol Geriatr, 2012;55:148151.
  • 48
    Pyszka LL, Seys RT, Milhans SM. Identification of inappropriate prescribing in geriatrics at a Veterans affairs hospital using STOPP/START screening tools. Consult Pharm, 2010;25:365373.
  • 49
    Alfaro Lara ER, Vega Coca MD, Galván Banqueri M et al. Selection of tools for reconciliation, compliance and appropriateness of treatment in patients with multiple chronic conditions. Eur J Intern Med, 2012;23:506512.
  • 50
    Vermeulen WTAM, Verduijn MM, Derijks HJ, van Marum RJ Detection of inappropriate medication use in the elderly; will the STOPP and START criteria become the new Dutch standards? [Dutch] Ned Tijdschr Geneeskd, 2012;156:A5076.
  • 51
    Cruz-Jentoft AJ. New therapies for an ageing Europe: 2011 EUGMS Málaga Congress. Eur Geriatr Med, 2011;2:128.
  • 52
    Hamilton H, Gallagher P, Ryan C, Byrne S, O'Mahony D. Potentially inappropriate medications defined by STOPP criteria and the risk of adverse drug events in older hospitalized patients. Arch Intern Med, 2011;171:10131019.
  • 53
    Conejos Miguel MD, Sanchez Cuervo M, Delgado Silveira E, Sevilla Machuca I, Gonzalez-Blazquez S, Montero Errasquin B, Cruz-Jentoft AJ Potentially inappropriate drug prescription in older subjects across health care settings. Eur Geriatr Med, 2010;1:914.
  • 54
    Gallagher P, O'Mahony D. STOPP (Screening Tool of Older Persons' potentially inappropriate Prescriptions): application to acutely ill elderly patients and comparison with Beers' criteria. Age Ageing, 2008;37:673679.
  • 55
    Gallagher PF, O'Connor MN, O'Mahony D. Prevention of potentially inappropriate prescribing for elderly patients: a randomized controlled trial using STOPP/START criteria. Clin Pharmacol Ther, 2011b;89:845854.
  • 56
    Garcia-Gollarte F, Baleriola-Julvez J, Ferrero-Lopez I, Cruz-Jentoft A. Inappropriate drug prescription at nursing home admission. J Am Med Dir Assoc, 2012;13:83.e9-83.e15.
  • 57
    Ryan C, O'Mahony D, Kennedy J, Weedle P, Byrne S. Potentially inappropriate prescribing in an Irish elderly population in primary care. Br J Clin Pharmacol, 2009;68:936947.
  • 58
    Hayden JA, van der Windt DA, Cartwright JL, Côté P, Bombardier C. Assessing bias in studies of prognostic factors. Ann Intern Med, 2013;158:280286.
  • 59
    Liberati A, Altman DG, Tetzlaff J et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ, 2009;339:b2700.
  • 60
    Parsons C, Johnston S, Mathie E, Baron N, Machen I, Amador S, Goodman C. Potentially inappropriate prescribing in older people with dementia in care homes: a retrospective analysis. Drugs Aging, 2012;29:143155.
  • 61
    Delgado Silveira E, Munoz Garcia M, Montero Errasquin B, Sanchez Castello C, Gallagher PF, Cruz-Jentoft AJ. Prescripcion inapropiada de medicamentos en los pacientes majors: los criterios STOPP/START. Rev Esp Geriatr Gerontol, 2009;44:273279.
  • 62
    Gutiérrez Rodríguez J, López Gaona V. Usefulness of a geriatric intervention program in the improvement of drug treatment for institutionalised patients. [Spanish] Rev Esp Geriatr Gerontol, 2010;45:278280.
  • 63
    Fernández-Regueiro R, Fonseca-Aizpuru E, López-Colina G, Alvarez-Uría A, Rodríguez-Ávila E, Morís-De-La-Tassa J. Inappropriate drug prescription and adverse drug effects in elderly patients. [Spanish]. Rev Clin Esp, 2011;211:400406.
  • 64
    Mera F, Mestre D, Almeda J, Ferrer A, Formiga F, Rojas Farreras S, Grupo de Estudio Octabaix. Inappropriate prescription in the community elderly, are we aware of? [Spanish] Rev Esp Geriatr Gerontol, 2011;46:125130.
  • 65
    Bradley MC, Fahey T, Cahir C, Bennett K, O'Reilly D, Parsons C, Hughes CM. Potentially inappropriate prescribing and cost outcomes for older people: a cross-sectional study using the Northern Ireland Enhanced Prescribing Database. Eur J Clin Pharmacol, 2012;68:14251433.
  • 66
    Candela Marroquin E, Mateos Iglesia N, Palomo Cobos L. Adequacy of medication in patients 65 years or older in teaching health centers in Cáceres, Spain. [Spanish] Rev Esp Salud Publica, 2012;86:419434.
  • 67
    Chen LL, Tangiisuran B, Shafie AA, Hassali MA. Evaluation of potentially inappropriate medications among older residents of Malaysian nursing homes. Int J Clin Pharm, 2012;34:596603.
  • 68
    Pinto Borges E, Morgado M, Macedo AF. Prescribing omissions in elderly patients admitted to a stroke unit: descriptive study using START criteria. Int J Clin Pharm, 2012;34:481491.
  • 69
    Dalleur O, Spinewine A, Henrard S, Losseau C, Speybroeck N, Boland B. Inappropriate prescribing and related hospital admissions in frail older persons according to the STOPP and START Criteria. Drugs Aging, 2012 Oct;29:829837.
  • 70
    O'Sullivan DP, O'Mahony D, Parsons C, Hughes C, Murphy K, Patterson S, Byrne S. A prevalence study of potentially inappropriate prescribing in Irish long-term care residents. Drugs Aging, 2013 Jan;30:3949.
  • 71
    Ryan C, O'Mahony D, Kennedy J et al. Potentially inappropriate prescribing in older residents in Irish nursing homes. Age Ageing, 2013 Jan;42:116120.
  • 72
    Ryan C, O'Mahony D, O'Donovan DO, O'Grady E, Weedle P, Kennedy J, Byrne S. A comparison of the application of STOPP/START to patients' drug lists with and without clinical information. Int J Clin Pharm, 2012; doi:10.1007/s11096-012-9733-0. [Epub ahead of print].
  • 73
    Sevilla-Sáchez D, Espaulella-Panicot J, de Andrés-Lazaro AM, Torres-Allezpuz R, Soldevila-Llagostera M, Codina-Jane C. Potentially inappropriate medication on admission to a medium-stay unit according to STOPP and START criteria. [Spanish]. Rev Esp Geriatr Gerontol, 2012;47:155157.
  • 74
    Siebert S, Elkeles B, Hempel G, Kruse J, Smollich M. The PRISCUS list in clinical routine: practicability and comparison to international PIM lists. [German]. Z Gerontol Geriatr, 2013 Jan;46:3547.