Polypharmazie in der nachstationären Versorgung: Eine Analyse mit Daten der AOK Sachsen-Anhalt

Tetzlaff, Fabian; Singer, A; Swart, Enno; Robra, Bernt‐Peter; Herrmann, Markus

doi:10.1055/s-0042-113599

Cited by 1 publication

(17 citation statements)

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“…The majority of studies ( n = 16) investigated the relationship between COC and MARO [ 43 – 47 , 51 , 56 – 58 , 60 , 61 , 63 , 64 , 66 , 68 , 69 ]. Seven studies focused on the relationship between COC and polypharmacy [ 48 , 53 , 54 , 62 , 65 , 67 ], and four studies investigated both the relationship between COC and MARO and between COC and polypharmacy [ 49 , 50 , 52 , 59 ].…”

Section: Resultsmentioning

confidence: 99%

“…Among studies using objective non-standard measures of COC ( n = 16), the majority ( n = 11) used the number of prescribers [ 46 , 48 , 51 , 55 , 56 , 59 – 61 , 63 , 68 , 69 ] to measure COC, with a high number of prescribers indicating low COC. Further measures were the number of treating physicians [ 49 , 61 ], the number of providers [ 57 , 67 ], the number of specialties [ 58 ], the tendency to visit multiple providers [ 62 ], and having a single primary care physician [ 61 ]. Exposure variables were treated as binary, ordinal, or continuous (Table 2 ; Tables S1 and S2 in the ESM).…”

Section: Resultsmentioning

confidence: 99%

“…Overall, seven categories of MARO were investigated: Potentially inappropriate medication (PIM) [ 44 , 46 , 47 , 49 , 52 , 56 , 59 , 64 , 69 ], drug–drug interaction (DDI) [ 45 , 50 , 57 , 64 , 66 , 68 ], adverse drug events (ADE) [ 58 , 63 ], duplicated medication [ 43 , 44 ], unnecessary drug use [ 60 ], overdose [ 51 ], and potential inappropriate drug combination (PIDC) [ 61 ] (Table 2 ).…”

Section: Resultsmentioning

confidence: 99%

“…Regarding the operationalization of PIM, different versions of the Beers criteria [ 71 ] were applied [ 46 , 47 , 64 ]. Other instruments were used, such as the Japanese STOPP-J list [ 59 ], the Norwegian General Practice (NORGEP) criteria, which are based on the Beers criteria [ 56 ], the German PRISCUS list [ 49 ], and the STOPP/START criteria [ 52 ]. PIM was always analyzed by using a binary (yes vs no) variable.…”

Section: Resultsmentioning

confidence: 99%

“…: lowest quartile) is significantly associated with reduced risk of extreme polypharmacy, but not with polypharmacy and having at least 1 PIM vs no PIM (no differences among COC indices) Patients in the highest quartile of the UPC, COCI and SECON Index had significantly fewer instances of PIM compared with the lowest quartile (effect size: IRR) Polypharmacy UPC: OR 0.93 (95% CI 0.78–1.11) COCI: OR 0.97 (95% CI 0.82–1.15) SECON: OR 0.89 (95% CI 0.75–1.06) Extreme polypharmacy UPC: OR 0.83 (95% CI 0.73–0.95) COCI: OR 0.84 (95% CI 0.73–0.95) SECON: OR 0.85 (95% CI 0.74–0.98) PIM UPC: OR 0.97 (95% CI 0.84–1.12); IRR 0.93 (95% CI 0.88–0.97) COCI: OR 0.96 (95% CI 0.83–1.11); IRR 0.93 (95% CI 0.88–0.97) SECON: OR 0.94 (95% CI 0.81–1.09); IRR 0.93 (95% CI 0.89–0.98) Fujie et al 2020 [ 59 ] Cross-sectional Register/claims data Japan Primary care/outpatient n = 8080 Age ≥ 75 years COC Dimension 1 Objective non-standard measure Number of prescribers Patients who were prescribed by ≥ 2 physicians had significantly higher percentages of polypharmacy The risk of experiencing polypharmacy increased each time the patient was prescribed by one additional physician. Multiple physicians prescribing for a patient showed a significant relationship with prescription of PIMs Polypharmacy: OR 5.73 (95% CI 5.11–6.42) PIM: OR 1.51 (95% CI 1.34–1.71) Tetzlaff et al 2018 [ 49 ] Cross-sectional Register/claims data Germany Primary care/outpatient n = 21,041 Age ≥ 60 years COC-Dimension 1 Objective non-standard measure Number of treating physicians Number of treating physicians is a predictor for polypharmacy risk (independent of multi-morbidity) for men and women. An increase in physicians involved in the treatment increased the risk of a PIM prescription for men and women Polypharmacy 2 physicians vs 1 physician: Men: OR 2.77 (95% CI 2.49–3.09) Women: OR 2.18 (95% CI 2.01–2.37) ≥ 3 physicians vs 1 physician: Men: OR 7.98 (95% CI 6.54–9.74) Women: OR 7.24 (95% CI 6.18–8.48) PIM 2 physicians vs 1 physician: Men: OR 1.38 (95% CI 1.17–1.62) Women: OR 1.27 (95% CI 1.13–1.43) ≥ 3 physicians vs 1 physician: Men: OR 1.59 (95% CI 1.24–2.03) Women: OR 1.62 (95% CI 1.35–1.94) Weng et al 2020 [ 50 ] Longitudin...…”

Section: Methodsmentioning

confidence: 99%

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The Relationship of Continuity of Care, Polypharmacy and Medication Appropriateness: A Systematic Review of Observational Studies

Lampe

Grosser

Gensorowsky³

et al. 2023

Drugs Aging

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Introduction Worldwide, polypharmacy and medication appropriateness-related outcomes (MARO) are growing public health concerns associated with potentially inappropriate prescribing, adverse health effects, and avoidable costs to health systems. Continuity of care (COC) is a cornerstone of high-quality care that has been shown to improve patient-relevant outcomes. However, the relationship between COC and polypharmacy/MARO has not been systematically explored. Objective The aim of this systematic review was to investigate the operationalization of COC, polypharmacy, and MARO as well as the relationship between COC and polypharmacy/MARO. Methods We performed a systematic literature search in PubMed, Embase, and CINAHL. Quantitative observational studies investigating the associations between COC and polypharmacy and/or COC and MARO by applying multivariate regression analysis techniques were eligible. Qualitative or experimental studies were not included. Information on the definition and operationalization of COC, polypharmacy, and MARO and reported associations was extracted. COC measures were assigned to the relational, informational, or management dimension of COC and further classified as objective standard, objective non-standard, or subjective. Risk of bias was assessed by using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Results Twenty-seven studies were included. Overall, substantial differences existed in terms of the COC dimensions and related COC measures. Relational COC was investigated in each study, while informational and management COC were only covered among three studies. The most frequent type of COC measure was objective non-standard ( n = 16), followed by objective standard ( n = 11) and subjective measures ( n = 3). The majority of studies indicated that COC is strongly associated with both polypharmacy and MARO, such as potentially inappropriate medication (PIM), potentially inappropriate drug combination (PIDC), drug–drug interaction (DDI), adverse drug events (ADE), unnecessary drug use, duplicated medication, and overdose. More than half of the included studies ( n = 15) had a low risk of bias, while five studies had an intermediate and seven studies a high risk of bias. Conclusions Differences regarding the methodological quality of included studies as well as the heterogeneity in terms of the operationalization and measurement of COC, polypharmacy, and MARO need to be considered when interpreting the results. Yet, our findings suggest that optimizing COC may be helpful in reducing polypharmacy and MARO. Therefore, COC should be acknowledged as an important risk factor for polypharmacy and MARO, and the importance of COC should be considered when designing future interventions targeting these outcomes. ...

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