Computerized Decision Support Improves Medication Review Effectiveness: An Experiment Evaluating the STRIP Assistant’s Usability

Meulendijk, Michiel; Spruit, Marco; Maanen, A. Clara Drenth-van; Numans, Mattijs E.; Brinkkemper, Sjaak; Jansen, Paul A. F.; Knol, Wilma

doi:10.1007/s40266-015-0270-0

Cited by 70 publications

(88 citation statements)

References 39 publications

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“…In evaluating patient-reported symptoms as drug associated, the probability of a drug-related symptom occurring has to be considered [21, 32]. The probability of drug-related symptoms occurring can be derived from the frequencies for the side effects as given in the SPCs.…”

Section: Discussionmentioning

confidence: 99%

“…The participating pharmacies were a convenience sample from 11 municipalities, urban as well as rural, spread over The Netherlands. All participating pharmacists were trained and experienced in performing CMRs according to the Systematic Tool to Reduce Inappropriate Prescribing (STRIP) [32], as described in the Dutch guideline for CMRs [14, 15]. Additionally, the pharmacists received written instructions for the sampling of patients and for the data collection for this study.…”

Section: Methodsmentioning

confidence: 99%

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Evaluation of Potentially Drug-Related Patient-Reported Common Symptoms Assessed During Clinical Medication Reviews: A Cross-Sectional Observational Study

Schoenmakers¹,

Teichert

Wensing

et al. 2017

Drug Saf

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IntroductionHealthcare professionals tend to consider common non-alarming drug-related symptoms to be of little clinical relevance. However, such symptoms can have a substantial impact on the individual patient. Insight into patient-reported symptoms could aid pharmacists to identify improvements in medication treatment, for instance in the patient interview at the start of a clinical medication review (CMR).ObjectiveThe objectives of this study were to describe the numbers and types of patient-reported symptoms assessed during a CMR and to elucidate their potential association with the drugs in use.MethodsThis observational study was performed using data from a clinical trial on patient-reported outcomes of CMRs. Patients taking at least five drugs and who were eligible for a CMR were selected by 15 community pharmacies. Patients were asked to fill in a structured instrument, the Patient Reported Outcome Measure, Inquiry into Side Effects (PROMISE). Among other domains, this instrument offers a list of 22 symptom categories to report symptoms and their relationship with the drugs in use. The results of the PROMISE instrument together with information on patients’ actual drug use were available for analysis. Besides descriptive analysis, associations with side effects as listed in the summary of product characteristics (SPC) of the drugs in use were assessed with logistic regression analysis.ResultsOf the 180 patients included, 168 patients (93.3%) reported at least one symptom via the PROMISE instrument, which could be discussed with the pharmacist during the patient interview. In total, the patients reported 1102 symptoms in 22 symptom categories. Of these patients, 101 (56.1%) assumed that at one or more of the symptoms experienced were related to the drugs in use and 107 (59.4%) reported at least one symptom that corresponded to a ‘very common’ side effect listed in the SPC of a drug in use. Each additional drug in use with a specific symptom listed as a ‘very common’ side effect in its SPC statistically significantly increased the probability of a patient reporting the symptoms of ‘dry mouth/thirst, mouth complaints’, ‘constipation’, ‘diarrhoea’ and ‘sweating’.ConclusionMany patient-reported symptoms and symptoms potentially related to drugs in use were identified by administering the PROMISE instrument to users of at least five drugs being taking long-term. This information can be used in CMRs to improve patients’ drug therapy.Electronic supplementary materialThe online version of this article (doi:10.1007/s40264-017-0504-7) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Evaluation of Potentially Drug-Related Patient-Reported Common Symptoms Assessed During Clinical Medication Reviews: A Cross-Sectional Observational Study

Schoenmakers¹,

Teichert

Wensing

et al. 2017

Drug Saf

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“…Medication optimization improved significantly when the STRIP Assistant was used: The proportion of appropriate decisions increased from 58% without the STRIP Assistant to 76% with it ( P < .01), and the proportion of inappropriate decisions decreased from 42% without the STRIP Assistant to 24% with it ( P < .01). While medication optimization took longer with the STRIP Assistant, it was hypothesized that this difference would disappear as doctors become more experienced in using the Assistant. This was demonstrated in a subsequent study involving 4 teams of experts (general practitioners and pharmacists) who used the STRIP Assistant to review the medications of patients in 13 general practices located in Amsterdam, the Netherlands.…”

Section: Systematic Tool To Reduce Inappropriate Prescribingmentioning

confidence: 99%

The Systematic Tool to Reduce Inappropriate Prescribing (STRIP): Combining implicit and explicit prescribing tools to improve appropriate prescribing

Maanen

Leendertse

Jansen

et al. 2017

Evaluation Clinical Practice

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Inappropriate prescribing is a major health care issue, especially regarding older patients on polypharmacy. Multiple implicit and explicit prescribing tools have been developed to improve prescribing, but these have hardly ever been used in combination. The Systematic Tool to Reduce Inappropriate Prescribing (STRIP) combines implicit prescribing tools with the explicit Screening Tool to Alert physicians to the Right Treatment and Screening Tool of Older People's potentially inappropriate Prescriptions criteria and has shared decision-making with the patient as a critical step. This article describes the STRIP and its ability to identify potentially inappropriate prescribing. The STRIP improved general practitioners' and final-year medical students' medication review skills. The Web-application STRIP Assistant was developed to enable health care providers to use the STRIP in daily practice and will be incorporated in clinical decision support systems. It is currently being used in the European Optimizing thERapy to prevent Avoidable hospital admissions in the Multimorbid elderly (OPERAM) project, a multicentre randomized controlled trial involving patients aged 75 years and older using multiple medications for multiple medical conditions. In conclusion, the STRIP helps health care providers to systematically identify potentially inappropriate prescriptions and medication-related problems and to change the patient's medication regimen in accordance with the patient's needs and wishes. This article describes the STRIP and the available evidence so far. The OPERAM study is investigating the effect of STRIP use on clinical and economic outcomes.

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“…A web‐based application was developed to help physicians carry out a medication review using the STRIP method: the STRIP Assistant. STRIP Assistant helps users to formulate medication recommendations based on STOPP/START criteria version 1 and G‐standaard . G‐standaard is a database comprising all medications registered in the Netherlands, and includes guidelines on established clinical interactions, duplicate medications, contraindications, dosage, and frequency of administration recommendations.…”

Section: Introductionmentioning

confidence: 99%

“…STRIP Assistant helps users to formulate medication recommendations based on STOPP/START criteria version 1 and G-standaard. 6,[12][13][14] G-standaard is a database comprising all medications registered in the Netherlands, and includes guidelines on established clinical interactions, duplicate medications, contraindications, dosage, and frequency of administration recommendations. The G-standaard forms the basis of pharmacovigilance in the Netherlands.…”

Section: Introductionmentioning

confidence: 99%

The effect of providing prescribing recommendations on appropriate prescribing: A cluster‐randomized controlled trial in older adults in a preoperative setting

Boersma

Huibers

Maanen

et al. 2019

Brit J Clinical Pharma

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Aims The Systematic Tool to Reduce Inappropriate Prescribing is a method to assess patient's medication and has been incorporated into a clinical decision support system: STRIP Assistant. Our aim was to evaluate the effect of recommendations generated using STRIP Assistant on appropriate prescribing and mortality in a preoperative setting. Methods This cluster‐randomized controlled trial was carried out at the preoperative geriatric outpatient clinic. Residents who performed a comprehensive geriatric assessment were randomized to the control group and intervention group in a 1:1 ratio. Visiting patients aged 70 years or older on 5 or more medications were included. Intervention: prescribing recommendations were generated by a physician using STRIP Assistant and given to the resident. Control group residents performed a medication review according to usual care. Primary outcome: number of medication changes made because of potential prescribing omissions (PPOs), potentially inappropriate medications (PIMs), and suboptimal dosages according to the prescribing recommendations. Secondary outcome: 3‐month postoperative mortality. Results 65 intervention and 59 control patients were included, attended by 34 residents. Significantly more medication changes because of PPOs and PIMs were made in the intervention group than in the control group (PPOs 26.2% vs 3.4%, odds ratio 0.04 [95% confidence interval 0.003–0.46] P < .05; PIMS 46.2% vs 15.3% odds ratio 0.14 [95% confidence interval 0.07–0.57] P < .005). There were no differences in dose adjustments or in postoperative mortality. Conclusion Prescribing recommendations generated with the help of STRIP Assistant improved appropriate prescribing in a preoperative geriatric outpatient clinic but did not affect postoperative mortality.

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Computerized Decision Support Improves Medication Review Effectiveness: An Experiment Evaluating the STRIP Assistant’s Usability

Cited by 70 publications

References 39 publications

Evaluation of Potentially Drug-Related Patient-Reported Common Symptoms Assessed During Clinical Medication Reviews: A Cross-Sectional Observational Study

Evaluation of Potentially Drug-Related Patient-Reported Common Symptoms Assessed During Clinical Medication Reviews: A Cross-Sectional Observational Study

The Systematic Tool to Reduce Inappropriate Prescribing (STRIP): Combining implicit and explicit prescribing tools to improve appropriate prescribing

The effect of providing prescribing recommendations on appropriate prescribing: A cluster‐randomized controlled trial in older adults in a preoperative setting

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