A mixed methods analysis of the medication review intervention centered around the use of the 'Systematic Tool to Reduce Inappropriate Prescribing' Assistant (STRIPA) in Swiss primary care practices.

BACKGROUND: Electronic clinical decision support systems (eCDSS), such as the 'Systematic Tool to Reduce Inappropriate Prescribing' Assistant (STRIPA), have become promising tools for assisting general practitioners (GPs) with conducting medication reviews in older adults. Little is known about how GPs perceive eCDSS-assisted recommendations for pharmacotherapy optimization. The aim of this study was to explore the implementation of a medication review intervention centered around STRIPA in the 'Optimising PharmacoTherapy In the multimorbid elderly in primary CAre' (OPTICA) trial. METHODS: We used an explanatory mixed methods design combining quantitative and qualitative data. First, quantitative data about the acceptance and implementation of eCDSS-generated recommendations from GPs (n = 21) and their patients (n = 160) in the OPTICA intervention group were collected. Then, semi-structured qualitative interviews were conducted with GPs from the OPTICA intervention group (n = 8), and interview data were analyzed through thematic analysis. RESULTS: In quantitative findings, GPs reported averages of 13 min spent per patient preparing the eCDSS, 10 min performing medication reviews, and 5 min discussing prescribing recommendations with patients. On average, out of the mean generated 3.7 recommendations (SD=1.8). One recommendation to stop or start a medication was reported to be implemented per patient in the intervention group (SD=1.2). Overall, GPs found the STRIPA useful and acceptable. They particularly appreciated its ability to generate recommendations based on large amounts of patient information. During qualitative interviews, GPs reported the main reasons for limited implementation of STRIPA were related to problems with data sourcing (e.g., incomplete data imports), preparation of the eCDSS (e.g., time expenditure for updating and adapting information), its functionality (e.g., technical problems downloading PDF recommendation reports), and appropriateness of recommendations. CONCLUSIONS: Qualitative findings help explain the relatively low implementation of recommendations demonstrated by quantitative findings, but also show GPs' overall acceptance of STRIPA. Our results provide crucial insights for adapting STRIPA to make it more suitable for regular use in future primary care settings (e.g., necessity to improve data imports). TRIAL REGISTRATION: Clinicaltrials.gov NCT03724539, date of first registration: 29/10/2018.

Improving Appropriate Prescribing For Geriatric Patients Using a Clinical Decision Support System.

Purpose: Polypharmacy is a known risk factor for potentially inappropriate prescribing. Recently there is an increasing interest in clinical decision support systems (CDSS) to improve prescribing. The objective of this study was to evaluate the impact of a CDSS, with the START-STOPP criteria as main content in the setting of a geriatric ward. Endpoints were 1) appropriateness of prescribing and 2) acceptance rate of recommendations. Methods: This prospective study comparing the use of a CDSS with usual care involved patients admitted to geriatric wards in two teaching hospitals in the Netherlands. Patients were included from January to May 2017. The medications of 64 patients in the first six weeks was assessed according to the current standard, whereas the medications of 61 patients in the second six weeks were also assessed by using a CDSS. Medication appropriateness was assessed with the Medication Appropriateness Index (MAI). Results: The medications of 125 patients (median age 83 years) were reviewed. In both the usual care group and the intervention group MAI scores decreased significantly from admission to discharge (within group analyses, p<0.001). This effect was significantly larger in the intervention group (p<0.05). MAI scores at discharge in the usual care group and the intervention group were respectively 9.95±6.70 and 7.26±5.07. The CDSS generated 193 recommendations, of which 71 concerned START criteria, 45 STOPP criteria, and 77 potential interactions. Overall, 31.6% of the recommendations were accepted. Conclusion: This study shows that a CDSS to improve prescribing has additional value in the setting of a geriatric ward. Almost one third of the software-generated recommendations were interpreted as clinically relevant and accepted, on average one per patient.

Optimizing Therapy to Prevent Avoidable Hospital Admissions in Multimorbid Older Adults (OPERAM): cluster randomised controlled trial.

OBJECTIVE: To examine the effect of optimising drug treatment on drug related hospital admissions in older adults with multimorbidity and polypharmacy admitted to hospital. DESIGN: Cluster randomised controlled trial. SETTING: 110 clusters of inpatient wards within university based hospitals in four European countries (Switzerland, Netherlands, Belgium, and Republic of Ireland) defined by attending hospital doctors. PARTICIPANTS: 2008 older adults (≥70 years) with multimorbidity (≥3 chronic conditions) and polypharmacy (≥5 drugs used long term). INTERVENTION: Clinical staff clusters were randomised to usual care or a structured pharmacotherapy optimisation intervention performed at the individual level jointly by a doctor and a pharmacist, with the support of a clinical decision software system deploying the screening tool of older person's prescriptions and screening tool to alert to the right treatment (STOPP/START) criteria to identify potentially inappropriate prescribing. MAIN OUTCOME MEASURE: Primary outcome was first drug related hospital admission within 12 months. RESULTS: 2008 older adults (median nine drugs) were randomised and enrolled in 54 intervention clusters (963 participants) and 56 control clusters (1045 participants) receiving usual care. In the intervention arm, 86.1% of participants (n=789) had inappropriate prescribing, with a mean of 2.75 (SD 2.24) STOPP/START recommendations for each participant. 62.2% (n=491) had ≥1 recommendation successfully implemented at two months, predominantly discontinuation of potentially inappropriate drugs. In the intervention group, 211 participants (21.9%) experienced a first drug related hospital admission compared with 234 (22.4%) in the control group. In the intention-to-treat analysis censored for death as competing event (n=375, 18.7%), the hazard ratio for first drug related hospital admission was 0.95 (95% confidence interval 0.77 to 1.17). In the per protocol analysis, the hazard ratio for a drug related hospital admission was 0.91 (0.69 to 1.19). The hazard ratio for first fall was 0.96 (0.79 to 1.15; 237 v 263 first falls) and for death was 0.90 (0.71 to 1.13; 172 v 203 deaths). CONCLUSIONS: Inappropriate prescribing was common in older adults with multimorbidity and polypharmacy admitted to hospital and was reduced through an intervention to optimise pharmacotherapy, but without effect on drug related hospital admissions. Additional efforts are needed to identify pharmacotherapy optimisation interventions that reduce inappropriate prescribing and improve patient outcomes. TRIAL REGISTRATION: ClinicalTrials.gov NCT02986425.

Usability aspects of medication-related decision support systems in the outpatient setting: A systematic literature review.

In this study, we evaluated the usability aspects of medication-related clinical decision support systems in the outpatient setting. Articles published between 2000 and 2016 in Scopus, PubMed and EMBASE were searched and classified into three usability aspects: Effectiveness, Efficiency and Satisfaction. Using Van Welie et al.'s usability model, we categorized usability aspects in terms of usage indicators and means. Out of the 1999 articles, 24 articles met the selection criteria of which the main focus was on reducing inappropriate medication, prescription rate and prescription errors. Evidence could mainly be found for Effectiveness and showed high rates of positive results in reducing medication errors. To date, the effects of Efficiency and Satisfaction of clinical decision support systems regarding medication prescription remain understudied. Usability aspects such as memorability, learnability, adaptability, shortcuts and consistency require more attention. Studies are needed for better insight into the user model and to design a knowledge/task model for clinical decision support systems regarding medication prescription.

'Optimising PharmacoTherapy In the multimorbid elderly in primary CAre' (OPTICA) to improve medication appropriateness: study protocol of a cluster randomised controlled trial.

INTRODUCTION: Multimorbidity and polypharmacy are major risk factors for potentially inappropriate prescribing (eg, overprescribing and underprescribing), and systematic medication reviews are complex and time consuming. In this trial, the investigators aim to determine if a systematic software-based medication review improves medication appropriateness more than standard care in older, multimorbid patients with polypharmacy. METHODS AND ANALYSIS: Optimising PharmacoTherapy In the multimorbid elderly in primary CAre is a cluster randomised controlled trial that will include outpatients from the Swiss primary care setting, aged ≥65 years with ≥three chronic medical conditions and concurrent use of ≥five chronic medications. Patients treated by the same general practitioner (GP) constitute a cluster, and clusters are randomised 1:1 to either a standard care sham intervention, in which the GP discusses with the patient if the medication list is complete, or a systematic medication review intervention based on the use of the 'Systematic Tool to Reduce Inappropriate Prescribing'-Assistant (STRIPA). STRIPA is a web-based clinical decision support system that helps customise medication reviews. It is based on the validated 'Screening Tool of Older Person's Prescriptions' (STOPP) and 'Screening Tool to Alert doctors to Right Treatment' (START) criteria to detect potentially inappropriate prescribing. The trial's follow-up period is 12 months. Outcomes will be assessed at baseline, 6 and 12 months. The primary endpoint is medication appropriateness, as measured jointly by the change in the Medication Appropriateness Index (MAI) and Assessment of Underutilisation (AOU). Secondary endpoints include the degree of polypharmacy, overprescribing and underprescribing, the number of falls and fractures, quality of life, the amount of formal and informal care received by patients, survival, patients' quality adjusted life years, patients' medical costs, cost-effectiveness of the intervention, percentage of recommendations accepted by GPs, percentage of recommendation rejected by GPs and patients' willingness to have medications deprescribed. ETHICS AND DISSEMINATION: The ethics committee of the canton of Bern in Switzerland approved the trial protocol. The results of this trial will be published in a peer-reviewed journal. MAIN FUNDING: Swiss National Science Foundation, National Research Programme (NRP 74) 'Smarter Healthcare'. TRIAL REGISTRATION NUMBERS: Clinicaltrials.gov (NCT03724539), KOFAM (Swiss national portal) (SNCTP000003060), Universal Trial Number (U1111-1226-8013).

Conversion of STOPP/START version 2 into coded algorithms for software implementation: A multidisciplinary consensus procedure.

BACKGROUND: The rapid digitalization of medical practice has attracted growing interest in developing software applications for clinical guidelines and explicit screening tools to detect potentially inappropriate prescribing, such as STOPP/START criteria. The aim of the current study was to develop and provide logically unambiguous algorithms of STOPP/START criteria version 2, encoded with international disease and medication classification codes, to facilitate the development of software applications for multiple purposes. METHODS: A four round multidisciplinary consensus and validation procedure was conducted to develop implementable coded algorithms for software applications of STOPP/START criteria version 2, based on ICD, ICPC, LOINC and ATC classification databases. RESULTS: Consensus was reached for all 34 START criteria and 76 out of 80 STOPP criteria. The resulting 110 algorithms, modeled as inference rules in decision tables, are provided as supplementary data. CONCLUSION: This is the first study providing implementable algorithms for software applications based on STOPP/START version 2, validated in a computer decision support system. These algorithms could serve as a template for applying STOPP/START criteria version 2 to any software application, allowing for adaptations of the included ICD, ICPC and ATC codes and changing the cut-off levels for laboratory measurements to match local guidelines or clinical expertise.

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

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.

Efficiency of Clinical Decision Support Systems Improves with Experience.

Efficiency, or the resources spent while performing a specific task, is widely regarded as one the determinants of usability. In this study, the authors hypothesize that having a group of users perform a similar task over a prolonged period of time will lead to improvements in efficiency of that task. This study was performed in the domain of decision-supported medication reviews. Data was gathered during a randomized controlled trial. Three expert teams consisting of an independent physician and an independent pharmacist conducted 150 computerized medication reviews on patients in 13 general practices located in Amsterdam, the Netherlands. Results were analyzed with a linear mixed model. A fixed effects test on the linear mixed model showed a significant difference in the time required to conduct medication reviews over time; F(31.145) = 14.043, p < .001. The average time in minutes required to conduct medication reviews up to the first quartile was M = 20.42 (SD = 9.00), while the time from the third quartile up was M = 9.81 (SD = 6.13). This leads the authors to conclude that the amount of time users needed to perform similar tasks decreased significantly as they gained experience over time.

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

BACKGROUND: Polypharmacy poses threats to patients' health. The Systematic Tool to Reduce Inappropriate Prescribing (STRIP) is a drug optimization process for conducting medication reviews in primary care. To effectively and efficiently incorporate this method into daily practice, the STRIP Assistant--a decision support system that aims to assist physicians with the pharmacotherapeutic analysis of patients' medical records--has been developed. It generates context-specific advice based on clinical guidelines. OBJECTIVE: The aim of this study was to validate the STRIP Assistant's usability as a tool for physicians to optimize medical records for polypharmacy patients. METHODS: In an online experiment, 42 physicians were asked to optimize medical records for two comparable polypharmacy patients, one in their usual manner and one using the STRIP Assistant. Changes in effectiveness were measured by comparing respondents' optimized medicine prescriptions with medication prepared by an expert panel of two geriatrician-pharmacologists. Efficiency was operationalized by recording the time the respondents took to optimize the two cases. User satisfaction was measured with the System Usability Scale (SUS). Independent and paired t tests were used for analysis. RESULTS: Medication optimization significantly improved with the STRIP Assistant. Appropriate decisions increased from 58% without the STRIP Assistant to 76% with it (p < 0.0001). Inappropriate decisions decreased from 42% without the STRIP Assistant to 24% with it (p < 0.0001). Participants spent significantly more time optimizing medication with the STRIP Assistant (24 min) than without it (13 min; p < 0.0001). They assigned it a below-average SUS score of 63.25. CONCLUSION: The STRIP Assistant improves the effectiveness of medication reviews for polypharmacy patients.

General practitioners' attitudes towards decision-supported prescribing: an analysis of the Dutch primary care sector.

The use of multiple drugs by patients increases the risk of medical problems. Clinical decision support could assist general practitioners with prescribing but is underused. This article aims to investigate the attitudes of general practitioners towards using decision support systems. A survey was distributed among 500 Dutch general practitioners. Virtually all 184 respondents indicated having a clinical information system, while only 21 percent indicated having a decision support plug-in; this correlated with their use of medical formularies. Only use of one of the medical formularies correlated with the number of recognized underprescription problems. General practitioners' attitudes toward a newly proposed system aiding them with polypharmacy prescribing were mainly positive (57%); the perceived usefulness correlated with output quality (p = .000), time investment (p = .000), and financial stimuli (payability: p = .000 and reimbursement: p = .015) but not with job relevance. Dutch general practitioners are thus likely to adopt the proposed system under the conditions that it improves prescription quality and does not require extensive investments of time or money.

AmI in good care? Developing design principles for ambient intelligent domotics for elderly.

The combination of ambient intelligence (AmI) and domotics has the potential to respond to elderly people's desire to live independent from extensive forms of care. Their slow adoption of technological aids shows reluctance, though. This article investigates their motivations to adopt ambient intelligent domotics, and proposes design principles specifically based on their preferences and experiences. Respondents appeared to be more acceptive of tangible problems they expected with AmI domotics than intangible ones. In addition, their opinions seemed to be profoundly influenced by the way they perceived their psychological quality of life, while their physical conditions did not seem to have noticeable impacts.