You are viewing the site in preview mode

Skip to main content

Advertisement

A comparison of estimated drug costs of potentially inappropriate medications between older patients receiving nurse home visit services and patients receiving pharmacist home visit services: a cross-sectional and propensity score analysis

Abstract

Background

There have been no multicenter studies that estimated the relations of either nurse or pharmacist home visit program to drug costs of potentially inappropriate medications (PIMs). This study aimed to establish whether patients who used nurse or pharmacist home visit programs (nurse or pharmacist program) had lower drug costs of PIMs than those who did not use nurse or pharmacist programs for older patients living at home.

Methods

This cross-sectional study was conducted in home care settings in Japan, involving 430 patients aged 65 or older, of whom 276 were female. All received regular home visits from five clinics between May and December 2013. After the PIMs were identified with the Screening Tool of Older Persons' potentially inappropriate Prescriptions (STOPP) criteria, we estimated the drug costs based on actual pharmaceutical prices and measured against who using nurse or pharmacist programs after a propensity score weighted adjustment.

Results

Patients who used nurse programs had lower drug cost of PIMs than those who did not use, but it was not significantly different (5.9 ± 13.1 vs 7.1 ± 13.9 USD per month, P = 0.199). The cost of PIMs for patients who used pharmacist programs also had no difference. (7.2 ± 14.5 vs 5.5 ± 11.5 USD per month, P = 0.06). In the patient groups who used nurse programs, patients who also used pharmacist programs had significantly higher costs of PIMs than those who used only nurse programs (5.5 ± 13.9 vs 2.5 ± 6.0 USD per month, P = 0.006). In patients group who did not use pharmacist programs, patients who only used nurse programs had significantly lower costs of PIMs than those who did not use nurse programs (3.6 ± 7.7 vs 5.8 ± 12.7 USD per month, P = 0.022).

Conclusions

Patients who used nurse program have a trend towards lower drug costs of PIMs than those who used nurse and pharmacist program or pharmacist program alone. Although this study tried to adjust the potential confounders as possible as we could by using propensity score analysis, further studies are needed to confirm our results.

Background

Prescription medications are an essential component of the care of older patients. Although some medications can cure and prevent disease, inappropriate medication may have detrimental effects. Potentially inappropriate medications (PIMs) have been defined as medications that carry more risks than benefits, those with clinically significant drug–drug or drug–disease interactions [1,2].

Several studies have shown that PIMs among older patients are correlated with increased adverse drug reactions (ADRs) [3-6], health care utilization [7-9], death [10,11], poor adherence [12,13] and greater economic burden [7,14,15]. The cost of potentially inappropriate medications is estimated to be high [16-18], and this has become an important public health issue worldwide [2]. PIMs among older home care patients are common [19], and an important issue in developed countries with an aging population, such as Japan, where the number of older home care patients is predicted to increase rapidly in the future.

Several tools are used to detect PIMs in older people [20], such as the Beers’ criteria [21], the Screening Tool of Older Persons' potentially inappropriate Prescriptions (STOPP) [22,23] and the Improved Prescribing in the Elderly Tool (IPET) [24]. Recent studies showed that the STOPP criteria have high sensitivity for detecting potential drug-related problems [25] and are more sensitive in detecting PIMs than the Beers’ criteria [26].

Several intervention studies have revealed that a multidisciplinary approach for older patients could reduce the number of patients with PIMs [27,28] and detect a high proportion of clinically relevant DRPs [29,30]. One previous study conducted in home care settings revealed that a medication review by a community pharmacist could reduce the number of medications, but it was not clear about the relations of pharmacist intervention to drug costs of PIMs [31]. As far as we know, there has been no multicenter study that estimated the relations of either nurse or pharmacist home visit program to drug cost of PIMs identified by the STOPP criteria for older patients in home care settings. This study aimed to validate whether the patients who using either nurse or pharmacist home visit programs had lower drug costs of potentially inappropriate medication based on actual pharmaceutical prices than who not using nurse or pharmacist home visit programs for older patients in a home care setting.

Methods

This cross-sectional study was conducted at five clinics in Japan between May and December 2013. These clinics provide primary care by ambulatory service and home visit services for community residents, and each clinics collaborate with home visit nurses and pharmacists depending on the situation. None of these doctors were familiar with the STOPP criteria at the starting time of study. In general, nurse home visit programs in Japan provide hands-on care at home, for example to help bathing, to promote physical activity and to coordinate living environment. Pharmacist home visit programs in Japan usually consult with patient regarding expected or unexpected effects of drugs and monitor the adherence of prescription at home. The frequency of their home visit depended on patients’ conditions and needs for care, typically twice or four times a month by nurse and a once or twice a month by pharmacist.

Although, the primary care doctors responsible for care of individual patients typically recommend using the home visit program and patients or their family could decide to use or not, the patients and their family could use the programs whenever they requested.

The study was approved by the ethics committee of the Mito Kyodo General Hospital and was conducted according to the principles expressed in the Declaration of Helsinki. We included all patients who were 65 years or older and who satisfied our inclusion criteria, which were:

  1. 1)

    patients received home visit services regularly by their doctors at least twice a month for over a month, and

  2. 2)

    patients had been regularly prescribed medications by the clinic, excluding topical drugs.

We used medical records to collect patients' background information, which included age, sex, estimated glomerular filtration rate (eGFR: ml/min), serum albumin (mg/dl), availability of overview of ambulation and drug use, underlying medical conditions, whether they lived with or without family, and whether they used a home visit nurse or pharmacist.

We had collected the copies of prescription contents by single monthly basis during the survey period which was sent from each clinic and confirmed the medication.

We defined PIMs as having occurred when at least one of the original STOPP criteria was met (Table 1). We calculated the total monthly drug cost of all patients and the monthly drug cost of PIMs. We estimated the drug cost based on actual pharmaceutical prices listed by the regulatory committee at the Ministry of Health, Labour and Welfare, Japanese government.

Table 1 STOPP screening criteria [22]

Statistical methods

We used Student’s t test for continuous variables and Pearson’s χ2 test or Fisher’s exact test for categorical variables to test for significant associations between patients’ baseline characteristics and the use of the home visit nurse or pharmacist. We used a propensity score weighting technique to assess the association between the monthly drug cost of PIMs and the use of the home visit nurse or pharmacist and to adjust for confounding factors.

For the propensity score analysis, we selected the variables as those that 1) were hypothesized to be strongly associated with the use of the home visit nurse or pharmacist and PIMs, and 2) were hypothesized to be associated with PIMs, and excluded those that 1) were associated with other aspects as well as the use of the home visit nurse and pharmacist, 2) were affected by the use of the home visit nurse or pharmacist, 3) perfectly predict the use of the home visit nurse and pharmacist [32].

We then used logistic regression to calculate the propensity score, categorizing the patient age into three groups: 65–74, 75–84, and >85 years.

The logistic regression model for the propensity score for the use of the nurse home visit programs (PS for nurse) included age category, sex, availability of overview on ambulation and drug use, whether they lived with or without family, the use of the home visit pharmacist, number of prescriptions and underlying medical conditions (constipation, hypertension, dementia, cerebral infarction/transient ischemic attack, diabetes mellitus, atrial fibrillation, progressive malignancy, hyperuricemia/gout, heart failure, dyslipidemia, Parkinson’s Disease/Parkinson’s syndrome, osteoporosis, chronic obstructive pulmonary disease, peripheral artery occlusive disease, cerebral/subarachnoid hemorrhage, osteoarthritis) as variables.

We also developed the propensity score for the use of the pharmacist home visit programs (PS for pharmacist) using a logistic regression model that included the same variables as for the nurse home visit programs, except that use of the pharmacist home visit programs was changed to use of the nurse home visit program.

To examine the association between the monthly drug cost of PIMs and use of the nurse or pharmacist home visit programs, we used a multivariate logistic regression analysis and included use of the home visit programs with the propensity score as variables. All analyses were conducted using SPSS-J (ver. 22.0; IBM, Tokyo, Japan).

Results

Demography

We included 430 patients in this study, of whom 276 were female. Table 2 shows detailed patient background information. The mean patient age was 85.0 ± 8.3 years. The main underlying medical conditions were constipation in 243 patients (56.5%), hypertension in 228 patients (53.0%), and dementia in 218 patients (50.7%). Nearly half, 203 patients (47.2%), had used the nurse home visit programs and 182 (42.3%) had used the pharmacist home visit programs. Almost one fifth, 78 patients (18.1%), had used both nurse and pharmacist home visit programs (Table 2). Over one quarter, 123 patients (28.6%), had not used either program. Propensity score weighting successfully balanced the observed differences in patient background and the use of the two home visit programs (Table 2).

Table 2 Patient background (n = 430)

Specific prescriptions of PIMs

By the STOPP criteria, 34.0% of the study population received at least one PIM. We found that the most common prescriptions resulting in PIMs were (a) calcium-channel blockers in patients with chronic constipation (74 patients, 17.2%), (b) long-term use of NSAIDs for relief of mild joint pain in osteoarthritis (16 patients, 3.7%), (c) long-term use of long-acting benzodiazepines (15 patients, 3.5%), and (d) NSAIDs in patients with moderate-to-severe hypertension or with heart failure (14 patients, 3.3%) (Table 3).

Table 3 Most frequent prescriptions resulting in PIMs

The cost of PIMs after propensity score weighted adjustment

After propensity score weighted adjustment, we compared the total cost of PIMs per patient per month in USD (100 Japanese Yen = 1 USD) in all patients and each subgroup (Table 4, 5). Although it was not significantly different, patients who used the pharmacist home visit programs had higher drug costs of PIMs (7.2 ± 14.5 vs 5.5 ± 11.5 USD per month, P = 0.06) (Table 4). On the other hand, the drug cost of PIMs for patients who used the nurse home visit programs was lower than those who did not use, but it was not significantly different (5.9 ± 13.1 vs 7.1 ± 13.9 USD per month, P = 0.199) (Table 5). In the patient groups who used nurse home visiting programs, patients who also used pharmacist home visiting programs had significantly higher costs of PIMs than those who used only nurse home visit programs (5.5 ± 13.9 vs 2.5 ± 6.0 USD per month, P = 0.006) (Table 4). In the patient groups who did not use pharmacist home visit programs, patients who only used nurse home visit programs had significantly lower costs of PIMs than those who did not use nurse home visit programs (3.6 ± 7.7 vs 5.8 ± 12.7 USD per month, P = 0.022) (Table 5).

Table 4 The cost of PIMs in patients group who used nurse home visit or not
Table 5 The cost of PIMs in patients group who used pharmacist home visit or not

Discussion

As far as we know, this is the first study to estimate the relations of nurse and pharmacist home visit program to drug costs of PIMs identified by the STOPP criteria for older patients in home care settings.

The important finding of this study is that those who used nurse home visit program have a trend towards lower drug costs of PIMs than those who used nurse and pharmacist home visit program or pharmacist home visit program alone.

There are several explanations about this finding. First, pharmacist home visit programs tend to involve patients with complicated conditions and PIMs might have been actually appropriate in these circumstances.

Second, although pharmacists understood the concept and meaning of PIMs, pharmacist home visit programs may be more difficult to help for improving the prescription than nurse home visit programs. This hypothesis is based on the situation of pharmacist home visit programs in Japan. In general, pharmacist home visit programs in Japan are expected to encourage to keep the drug adherence and to identify the symptoms as possible drug side effects. On the other hand, pharmacists of home visit programs usually did not receive the details of patients’ medical history from doctors and were not expected to give advice to doctors about prescription, although nurse home visit program usually is provided about the details of patients’ medical history and often be required to give advice to their patients about prescriptions from doctors in Japan.

Third, there might have been other unidentified confounding variables that might affect the effectiveness of home visit programs to the drug costs of PIMs. We need to conduct further research to reveal factors, which may affect the drug costs of PIMs in home care setting prospectively.

This study had four main limitations. First, we might not be able to assess the all of potential confounders that might affect the drug cost of PIMs in home care setting and the effectiveness of home visit program.

Second, because of its cross-sectional nature, there might have been several potential confounders, we could assess in this study, which could affect the drug costs of PIMs and the effectiveness of home visit program. We performed our analysis to adjust the potential confounders as possible as we could by using propensity scores.

Third, our study sample may not be representative of older home care patients, because it was carried out at only a few institutions in Japan. Further work is needed to carry out a larger study with the greater number of institutions in Japan and other countries.

Finally, we cannot draw conclusions about the effectiveness of nurse and pharmacist home visit program to drug cost of PIMs, because our study was not an intervention study. We would need to carry out further research, including a longitudinal intervention study, to assess the effectiveness of nurse and pharmacist home visit program to drug cost of PIMs.

Conclusion

In conclusion, those who used nurse home visit program have a trend towards lower drug costs of PIMs than those who used nurse and pharmacist home visit program or pharmacist home visit program alone. Although, this study aimed to adjust the potential confounders as possible as we could by using propensity score analysis, caution may be needed about interpretation of this study. Further research is needed to consider all of potential confounders associated with the drug costs of PIMs in home care setting and using home visit program.

References

  1. 1.

    Gallagher P, O’Mahony D. Inappropriate prescribing in older people. Rev Clin Gerontol. 2008;18(01):65.

  2. 2.

    Spinewine A, Schmader KE, Barber N, Hughes C, Lapane KL, Swine C, et al. Appropriate prescribing in elderly people: how well can it be measured and optimised? Lancet. 2007;370(9582):173–84.

  3. 3.

    Gallagher PF, Barry PJ, Ryan C, Hartigan I, O’Mahony D. Inappropriate prescribing in an acutely ill population of elderly patients as determined by Beers’ Criteria. Age Ageing. 2008;37(1):96–101.

  4. 4.

    Chang C-M, Liu P-YY, Yang Y-HK, Yang Y-C, Wu C-F, Lu F-H. Use of the Beers criteria to predict adverse drug reactions among first-visit elderly outpatients. Pharmacotherapy. 2005;25(6):831–8.

  5. 5.

    Routledge PA, O’Mahony MS, Woodhouse KW. Adverse drug reactions in elderly patients. Br J Clin Pharmacol. 2004;57(2):121–6.

  6. 6.

    Lindley CM, Tully MP, Paramsothy V, Tallis RC. Inappropriate medication is a major cause of adverse drug reactions in elderly patients. Age Ageing. 1992;21(4):294–300.

  7. 7.

    Fick DM, Mion LC, Beers MH, Waller JL. Health outcomes associated with potentially inappropriate medication use in older adults. Res Nurs Health. 2008;31(1):42–51.

  8. 8.

    Passarelli MCG, Jacob-Filho W, Figueras A. Adverse drug reactions in an elderly hospitalised population: inappropriate prescription is a leading cause. Drugs Aging. 2005;22(9):767–77.

  9. 9.

    Schneeweiss S, Hasford J, Göttler M, Hoffmann A, Riethling A-K, Avorn J. Admissions caused by adverse drug events to internal medicine and emergency departments in hospitals: a longitudinal population-based study. Eur Jj Clin Pharmacol. 2002;58(4):285–91.

  10. 10.

    Klarin I, Wimo A, Fastbom J. The association of inappropriate drug use with hospitalisation and mortality: a population-based study of the very old. Drugs Aging. 2005;22(1):69–82.

  11. 11.

    Ebbesen J, Buajordet I, Erikssen J, Brørs O, Hilberg T, Svaar H, et al. Drug-related deaths in a department of internal medicine. Arch Intern Med. 2001;161(19):2317–23.

  12. 12.

    Kripalani S, Henderson LE, Jacobson TA, Vaccarino V. Medication use among inner-city patients after hospital discharge: patient-reported barriers and solutions. Mayo Clin Proc. 2008;83(5):529–35.

  13. 13.

    Mansur N, Weiss A, Beloosesky Y. Is there an association between inappropriate prescription drug use and adherence in discharged elderly patients? Ann Pharmacother. 2009;43(2):177–84.

  14. 14.

    Fick DM, Waller JL, Maclean JR, Heuvel RV, Tadlock JG, Gottlieb M, et al. Potentially inappropriate medication use in a Medicare managed care population: Association with higher costs and utilization. J Manag Care Pharm. 2001;7(5):407–13.

  15. 15.

    Bates DW, Spell N, Cullen DJ, Burdick E, Laird N, Petersen LA, et al. The costs of adverse drug events in hospitalized patients adverse drug events prevention study group. JAMA. 1997;277(4):307–11.

  16. 16.

    Al-Omar HA, Al-Sultan MS, Abu-Auda HS. Prescribing of potentially inappropriate medications among the elderly population in an ambulatory care setting in a Saudi military hospital: trend and cost. Geriatr Gerontol Int. 2013;13(3):616–21.

  17. 17.

    Cahir C, Fahey T, Teeling M, Teljeur C, Feely J, Bennett K. Potentially inappropriate prescribing and cost outcomes for older people: a national population study. Br J Clin Pharmacol. 2010;69(5):543–52.

  18. 18.

    Bradley MC, Fahey T, Cahir C, Bennett K, O’Reilly D, Parsons C, et al. 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(10):1425–33.

  19. 19.

    Hamano J, Tokuda Y. Inappropriate prescribing among elderly home care patients in Japan: prevalence and risk factors. J Prim Care Community Health. 2014;5(2):90–6.

  20. 20.

    Kaufmann CP, Tremp R, Hersberger KE, Lampert ML. Inappropriate prescribing: a systematic overview of published assessment tools. Eur J Cli Pharmacol. 2013;70(1):1–11.

  21. 21.

    American Geriatrics Society. Updated Beers criteria for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2012;60(4):616–31.

  22. 22.

    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(2):72–83.

  23. 23.

    Lam MPS, Cheung BMY. The use of STOPP/START criteria as a screening tool for assessing the appropriateness of medications in the elderly population. Expert Rev Clin Pharmacol. 2012;5(2):187–97.

  24. 24.

    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(2):103–7.

  25. 25.

    Curtain CM, Bindoff IK, Westbury JL, Peterson GM. A comparison of prescribing criteria when applied to older community-based patients. Drugs Aging. 2013;30(11):935–43.

  26. 26.

    Hill-Taylor B, Sketris I, Hayden J, Byrne S, O’Sullivan D, Christie R. Application of the STOPP/START criteria: a systematic review of the prevalence of potentially inappropriate prescribing in older adults, and evidence of clinical, humanistic and economic impact. J Clin Pharm Ther. 2013;38(5):360–72.

  27. 27.

    Milos V, Rekman E, Bondesson Å, Eriksson T, Jakobsson U, Westerlund T, et al. Improving the quality of pharmacotherapy in elderly primary care patients through medication reviews: a randomised controlled study. Drugs Aging. 2013;30(4):235–46.

  28. 28.

    Gillespie U, Alassaad A, Hammarlund-Udenaes M, Mörlin C, Henrohn D, Bertilsson M, et al. Effects of pharmacists’ interventions on appropriateness of prescribing and evaluation of the instruments' (MAI, STOPP and STARTs') ability to predict hospitalization–analyses from a randomized controlled trial. PLoS One. 2013;8(5):e62401.

  29. 29.

    Bergqvist M, Ulfvarson J, Karlsson EA. Nurse-led medication reviews and the quality of drug treatment of elderly hospitalized patients. Eur J Clin Pharmacol. 2009;65(11):1089–96.

  30. 30.

    Finkers F, Maring JG, Boersma F, Taxis K. A study of medication reviews to identify drug-related problems of polypharmacy patients in the Dutch nursing home setting. J Clin Pharm Ther. 2007;32(5):469–76.

  31. 31.

    Lenaghan E, Holland R, Brooks A. Home-based medication review in a high risk elderly population in primary care–the POLYMED randomised controlled trial. Age Ageing. 2007;36(3):292–7.

  32. 32.

    Garrido MM. Propensity scores: a practical method for assessing treatment effects in pain and symptom management research. J Pain Symptom Manage. 2014;48(4):711–8.

Download references

Acknowledgments

Research funds for this study were provided by a Clinical Research Grant from St. Luke’s Life Science Institute. We would also like to express our gratitude to Kazuhiro Hisajima, MD, Shohei Kawagoe, MD, Hiroyuki Beniya, MD, and Yasuyuki Arai, MD for data collection.

Author information

Correspondence to Jun Hamano.

Additional information

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

JH and YT participated in the design of the study and helped to perform the statistical analysis and draft the manuscript. SO contributed to interpretation of the data and manuscript revisions. All authors read and approved the final manuscript.

Sachiko Ozone and Yasuharu Tokuda contributed equally to this work.

Rights and permissions

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Keywords

  • Propensity Score
  • Home Visit
  • Drug Cost
  • Inappropriate Medication
  • Propensity Score Analysis