Using the hidden Markov model to capture quality of care in Lombardy geriatric wards

Quality of care is an important aspect of healthcare monitoring, which is used to ensure that the healthcare system is delivering care of the highest standard. With populations growing older there is an increased urgency in making sure that the healthcare delivered is of the highest standard. Healthcare providers are under increased pressure to ensure that this is the case with public and government demand expecting a healthcare system of the highest quality. Modelling quality of care is difficult to measure due to the many ways of defining it. This paper introduces a potential model which could be used to take quality of care into account when modelling length of stay. The Coxian phase-type distribution is used to model length of stay and the associated quality of care incorporated into the Coxian using a Hidden Markov model. Covariates are also introduced to determine their impact on the hidden level to find out what potentially can affect quality of care. This model is applied to geriatic patient data from the Lombardy region of Italy. The results obtained highlighted that bed numbers and the type of hospital (public or private) can have an effect on the quality of care delivered.

Modelling Patient Duration of Stay to Facilitate Resource Management of Geriatric Hospitals

A fundamental aspect of health care management is the effective allocation of resources. This is of particular importance in geriatric hospitals where elderly patients tend to have more complex needs. Hospital managers would benefit immensely if they had advance knowledge of patient duration of stay in hospital. Managers could assess the costs of patient care and make allowances for these in their budget. In this paper, we tackle this important problem via a model which predicts the duration of stay distribution of patients in hospital. The approach uses phase-type distributions conditioned on a Bayesian belief network.

Assessing length of stay and associated characteristics of geriatric patients in Northern Ireland

The effective provision of care for the elderly is becoming increasingly more difficult. This is due to the rising proportion of elderly in the population, increasing demands placed on the health services and the financial strain placed on an already stretched economy. The research presented in this paper uses three different models to represent the length of stay distribution of geriatric patients admitted to one of the six key acute hospitals in Northern Ireland and various patient characteristics associated with their respective length of stay. The accurate modelling of bed usage within wards would enable hospital managers to prepare patient discharge packages and rehabilitation services in advance. The models presented within the paper include a Cox proportional hazards model, a Bayesian network with a discrete variable to represent length of stay and a special conditional phase-type model (C-Ph) with a connecting outcome node. This research demonstrates the new efficient fitting algorithm employed for Coxian phase-type distributions while updating C-Ph models for recent elderly patient data.

Pain in care home residents with dementia: an exploration of frequency, prescribing and relatives' perspectives

Objectives: This study aims to determine pain frequency amongst care home residents with dementia, to investigate variables associated with pain, to explore analgesic use among residents and to seek residents' relatives' views on provision of care and management of pain by the care home. Methods: Structured face-to-face interviews were conducted with residents, nursing staff and relatives from nine dementia care homes in Northern Ireland, between May 2010 and March 2012. Demographic information was collected from participants, neuropsychiatric tests were used to assess residents' cognitive functioning, medication use was determined from care home records and residents' pain was assessed using a verbal descriptor scale. Relatives' views were sought on care provision and management of pain. Results: Forty-two residents, 16 nurses/care assistants and 35 relatives participated; the participation rate of residents was low (27.6%). Most residents were suffering moderate-severe dementia, and some residents (26.2%) were unable to provide a self-report of pain. A significantly higher proportion of relatives (57.1%) deemed residents to be experiencing pain at the time of the interview, compared with residents (23.8%, p = 0.005) and nurses/care assistants (42.9%, p = 0.035). Most residents (88.1%) were prescribed with analgesia; non-opioid analgesics were most commonly prescribed. High proportions of residents were prescribed with psychoactive medications. Antipsychotic drug use was associated with presence of pain (p = 0.046). Conclusions: This study has reinforced the challenge of assessing and managing pain in this resident population and highlighted issues to be addressed by long-term care providers and clinicians. Participation of people with dementia, and their families, in healthcare research needs to be improved.

Hospitalization in Geriatric Wards: Considerations on the Evaluation of the Outcome

Within a defined law framework, the Italian central health system dictates the standards for hospitalization to local care units, which are in turn allowed to establish their own effectiveness criteria. The appropriateness of the hospitalization decision is therefore predetermined at patients admission, whereas its effectiveness relies on the ex post patient well-being as a result of the complex system of reciprocal relations between patients and healthcare agents at the ward level. We consider the outcomes in geriatric wards referring to the national health system, with respect both to patients traits at the individual level and wards/hospital settings. The risk that models the healthcare outcome is accordingly adjusted for covariates at the different levels of analysis (Goldstein & Spiegelhalter, 1996), thus allowing to differentiate among outcomes in terms of the hospitalization structure and, when appropriate, of territorial aggregation.