905 resultados para hospital discharge


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BACKGROUND: Most healthcare in the US is delivered in the ambulatory care setting, but the epidemiology of errors and adverse events in ambulatory care is understudied. METHODS: Using the population-based data from the Colorado and Utah Medical Practices Study, we identified adverse events that occurred in an ambulatory care setting and led to hospital admission. Proportions with 95% CIs are reported. RESULTS: We reviewed 14,700-hospital discharge records and found 587 adverse events of which 70 were ambulatory care adverse events (AAEs) and 31 were ambulatory care preventable adverse events (APAEs). When weighted to the general population, there were 2608 AAEs and 1296 (44.3%) APAEs in Colorado and Utah, USA, in 1992. APAEs occurred most commonly in physicians' offices (43.1%, range 46.8-27.8), the emergency department (32.3%, 46.1-18.5) and at home (13.1%, 23.1-3.1). APAEs in day surgery were less common (7.1%, 13.6-0.6) but caused the greatest harm to patients. The types of APAEs were broadly distributed among missed or delayed diagnoses (36%, 50.2-21.8), surgery (24.1%, 36.7-11.5), non-surgical procedures (14.6%, 25.0-4.2), medication (13.1%, 23.1-3.1) and therapeutic events (12.3%, 22.0-2.6). Overall, 10% of the APAEs resulted in serious permanent injury or death. The proportion of APAEs that resulted in death was 31.8% for general internal medicine, 22.5% for family practice and 16.7% for emergency medicine. CONCLUSION: An estimated 75,000 hospitalisations per year are due to preventable adverse events that occur in outpatient settings in the US, resulting in 4839 serious permanent injuries and 2587 deaths.

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BACKGROUND Evidence suggests that EMS-physician-guided cardiopulmonary resuscitation (CPR) in out-of-hospital cardiac arrest (OOHCA) may be associated with improved outcomes, yet randomized controlled trials are not available. The goal of this meta-analysis was to determine the association between EMS-physician- versus paramedic-guided CPR and survival after OOHCA. METHODS AND RESULTS Studies that compared EMS-physician- versus paramedic-guided CPR in OOHCA published until June 2014 were systematically searched in MEDLINE, EMBASE and Cochrane databases. All studies were required to contain survival data. Data on study characteristics, methods, and as well as survival outcomes were extracted. A random-effects model was used for the meta-analysis due to a high degree of heterogeneity among the studies (I (2)  = 44 %). Return of spontaneous circulation [ROSC], survival to hospital admission, and survival to hospital discharge were the outcome measures. Out of 3,385 potentially eligible studies, 14 met the inclusion criteria. In the pooled analysis (n = 126,829), EMS-physician-guided CPR was associated with significantly improved outcomes compared to paramedic-guided CPR: ROSC 36.2 % (95 % confidence interval [CI] 31.0 - 41.7 %) vs. 23.4 % (95 % CI 18.5 - 29.2 %) (pooled odds ratio [OR] 1.89, 95 % CI 1.36 - 2.63, p < 0.001); survival to hospital admission 30.1 % (95 % CI 24.2 - 36.7 %) vs. 19.2 % (95 % CI 12.7 - 28.1 %) (pooled OR 1.78, 95 % CI 0.97 - 3.28, p = 0.06); and survival to discharge 15.1 % (95 % CI 14.6 - 15.7 %) vs. 8.4 % (95 % CI 8.2 - 8.5 %) (pooled OR 2.03, 95 % CI 1.48 - 2.79, p < 0.001). CONCLUSIONS This systematic review suggests that EMS-physician-guided CPR in out-of-hospital cardiac arrest is associated with improved survival outcomes.

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As the requirements for health care hospitalization have become more demanding, so has the discharge planning process become a more important part of the health services system. A thorough understanding of hospital discharge planning can, then, contribute to our understanding of the health services system. This study involved the development of a process model of discharge planning from hospitals. Model building involved the identification of factors used by discharge planners to develop aftercare plans, and the specification of the roles of these factors in the development of the discharge plan. The factors in the model were concatenated in 16 discrete decision sequences, each of which produced an aftercare plan.^ The sample for this study comprised 407 inpatients admitted to the M. D. Anderson Hospital and Tumor Institution at Houston, Texas, who were discharged to any site within Texas during a 15 day period. Allogeneic bone marrow donors were excluded from the sample. The factors considered in the development of discharge plans were recorded by discharge planners and were used to develop the model. Data analysis consisted of sorting the discharge plans using the plan development factors until for some combination and sequence of factors all patients were discharged to a single site. The arrangement of factors that led to that aftercare plan became a decision sequence in the model.^ The model constructs the same discharge plans as those developed by hospital staff for every patient in the study. Tests of the validity of the model should be extended to other patients at the MDAH, to other cancer hospitals, and to other inpatient services. Revisions of the model based on these tests should be of value in the management of discharge planning services and in the design and development of comprehensive community health services.^

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The National Health Planning and Resources Development Act of 1974 (Public Law 93-641) requires that health systems agencies (HSAs) plan for their health service areas by the use of existing data to the maximum extent practicable. Health planning is based on the identificaton of health needs; however, HSAs are, at present, identifying health needs in their service areas in some approximate terms. This lack of specificity has greatly reduced the effectiveness of health planning. The intent of this study is, therefore, to explore the feasibility of predicting community levels of hospitalized morbidity by diagnosis by the use of existing data so as to allow health planners to plan for the services associated with specific diagnoses.^ The specific objectives of this study are (a) to obtain by means of multiple regression analysis a prediction equation for hospital admission by diagnosis, i.e., select the variables that are related to demand for hospital admissions; (b) to examine how pertinent the variables selected are; and (c) to see if each equation obtained predicts well for health service areas.^ The existing data on hospital admissions by diagnosis are those collected from the National Hospital Discharge Surveys, and are available in a form aggregated to the nine census divisions. When the equations established with such data are applied to local health service areas for prediction, the application is subject to the criticism of the theory of ecological fallacy. Since HSAs have to rely on the availability of existing data, it is imperative to examine whether or not the theory of ecological fallacy holds true in this case.^ The results of the study show that the equations established are highly significant and the independent variables in the equations explain the variation in the demand for hospital admission well. The predictability of these equations is good when they are applied to areas at the same ecological level but become poor, predominantly due to ecological fallacy, when they are applied to health service areas.^ It is concluded that HSAs can not predict hospital admissions by diagnosis without primary data collection as discouraged by Public Law 93-641. ^

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This investigation compares two different methodologies for calculating the national cost of epilepsy: provider-based survey method (PBSM) and the patient-based medical charts and billing method (PBMC&BM). The PBSM uses the National Hospital Discharge Survey (NHDS), the National Hospital Ambulatory Medical Care Survey (NHAMCS) and the National Ambulatory Medical Care Survey (NAMCS) as the sources of utilization. The PBMC&BM uses patient data, charts and billings, to determine utilization rates for specific components of hospital, physician and drug prescriptions. ^ The 1995 hospital and physician cost of epilepsy is estimated to be $722 million using the PBSM and $1,058 million using the PBMC&BM. The difference of $336 million results from $136 million difference in utilization and $200 million difference in unit cost. ^ Utilization. The utilization difference of $136 million is composed of an inpatient variation of $129 million, $100 million hospital and $29 million physician, and an ambulatory variation of $7 million. The $100 million hospital variance is attributed to inclusion of febrile seizures in the PBSM, $−79 million, and the exclusion of admissions attributed to epilepsy, $179 million. The former suggests that the diagnostic codes used in the NHDS may not properly match the current definition of epilepsy as used in the PBMC&BM. The latter suggests NHDS errors in the attribution of an admission to the principal diagnosis. ^ The $29 million variance in inpatient physician utilization is the result of different per-day-of-care physician visit rates, 1.3 for the PBMC&BM versus 1.0 for the PBSM. The absence of visit frequency measures in the NHDS affects the internal validity of the PBSM estimate and requires the investigator to make conservative assumptions. ^ The remaining ambulatory resource utilization variance is $7 million. Of this amount, $22 million is the result of an underestimate of ancillaries in the NHAMCS and NAMCS extrapolations using the patient visit weight. ^ Unit cost. The resource cost variation is $200 million, inpatient is $22 million and ambulatory is $178 million. The inpatient variation of $22 million is composed of $19 million in hospital per day rates, due to a higher cost per day in the PBMC&BM, and $3 million in physician visit rates, due to a higher cost per visit in the PBMC&BM. ^ The ambulatory cost variance is $178 million, composed of higher per-physician-visit costs of $97 million and higher per-ancillary costs of $81 million. Both are attributed to the PBMC&BM's precise identification of resource utilization that permits accurate valuation. ^ Conclusion. Both methods have specific limitations. The PBSM strengths are its sample designs that lead to nationally representative estimates and permit statistical point and confidence interval estimation for the nation for certain variables under investigation. However, the findings of this investigation suggest the internal validity of the estimates derived is questionable and important additional information required to precisely estimate the cost of an illness is absent. ^ The PBMC&BM is a superior method in identifying resources utilized in the physician encounter with the patient permitting more accurate valuation. However, the PBMC&BM does not have the statistical reliability of the PBSM; it relies on synthesized national prevalence estimates to extrapolate a national cost estimate. While precision is important, the ability to generalize to the nation may be limited due to the small number of patients that are followed. ^

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Objective: To assess the medical and psychosocial effects of early hospital discharge after surgery for breast cancer on complication rate, patient satisfaction, and psychosocial outcomes.

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BACKGROUND The application of therapeutic hypothermia (TH) for 12 to 24 hours following out-of-hospital cardiac arrest (OHCA) has been associated with decreased mortality and improved neurological function. However, the optimal duration of cooling is not known. We aimed to investigate whether targeted temperature management (TTM) at 33 ± 1 °C for 48 hours compared to 24 hours results in a better long-term neurological outcome. METHODS The TTH48 trial is an investigator-initiated pragmatic international trial in which patients resuscitated from OHCA are randomised to TTM at 33 ± 1 °C for either 24 or 48 hours. Inclusion criteria are: age older than 17 and below 80 years; presumed cardiac origin of arrest; and Glasgow Coma Score (GCS) <8, on admission. The primary outcome is neurological outcome at 6 months using the Cerebral Performance Category score (CPC) by an assessor blinded to treatment allocation and dichotomised to good (CPC 1-2) or poor (CPC 3-5) outcome. Secondary outcomes are: 6-month mortality, incidence of infection, bleeding and organ failure and CPC at hospital discharge, at day 28 and at day 90 following OHCA. Assuming that 50 % of the patients treated for 24 hours will have a poor outcome at 6 months, a study including 350 patients (175/arm) will have 80 % power (with a significance level of 5 %) to detect an absolute 15 % difference in primary outcome between treatment groups. A safety interim analysis was performed after the inclusion of 175 patients. DISCUSSION This is the first randomised trial to investigate the effect of the duration of TTM at 33 ± 1 °C in adult OHCA patients. We anticipate that the results of this trial will add significant knowledge regarding the management of cooling procedures in OHCA patients. TRIAL REGISTRATION NCT01689077.

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Background: Few studies have examined the potential benefits of specialist nurse-led programs of care involving home and clinic-based follow-up to optimise the post-discharge management of chronic heart failure (CHF). Objective: To determine the effectiveness of a hybrid program of clinic plus home-based intervention (C+HBI) in reducing recurrent hospitalisation in CHF patients. Methods: CHF patients with evidence of left ventricular systolic dysfunction admitted to two hospitals in Northern England were assigned to a C+HBI lasting 6 months post-discharge (n=58) or to usual, post-discharge care (UC: n=48) via a cluster randomization protocol. The co-primary endpoints were death or unplanned readmission (event-free survival) and rate of recurrent, all-cause readmission within 6 months of hospital discharge. Results: During study follow-up, more UC patients had an unplanned readmission for any cause (44% vs. 22%: P=0.0191 OR 1.95 95% CI 1.10-3.48) whilst 7 (15%) versus 5 (9%) UC and C+HBI patients, respectively, died (P=NS). Overall, 15 (26%) C+HBI versus 21 (44%) UC patients experienced a primary endpoint. C+HBI was associated with a non-significant, 45% reduction in the risk of death or readmission when adjusting for potential confounders (RR 0.55, 95% CI 0.28-1.08: P=0.08). Overall, C+HBI patients accumulated significantly fewer unplanned readmissions (15 vs. 45: P

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Background: There have been no published studies observing what happens to children post hospital discharge and if medication discrepancies occurred between the hospital and General Practitioner (GP) interface.1 Objectives: To identify the type of discrepancies between hospital discharge prescription and the patient's medicines after their first GP prescription. Method: Over a 3 month period (March–June 2012) across two London NHS hospital sites, parents of children on long term medications aged 18 years and under, were approached and consented prior to discharge from the ward. The patients were followed up 21 days after discharge by telephone call or home visit depending on their preference. The parent was asked if they had contacted their GP for further medications during the follow up, and if not the follow up was rescheduled. The parents were interviewed to find out if there were any discrepancies that occurred post discharge by comparing the patient's hospital discharge letter and medication at follow up. All this information was captured on a data collection form. Results: Eighty-eight patients were consented and 60 patients (68%; 60/88) were followed up by telephone call 21 days post discharge. A total of 317 medications were ordered at discharge among the 60 patients. Of the 60 that were followed up, nine were lost to follow up, one died post discharge, one was excluded from the study, and 11 had not contacted the GP and were to be followed up at a later date. Of the 38 patients who were followed up, 254 medications were ordered. Of the 38 patients there were 12 (32%) patients who had discrepancies that occurred between the discharge letter and GP, 19 (50%) had no issues, and seven (18%) mentioned issues to do with post discharge that were not discrepancies. Of the 12 patients who had at least one medication discrepancy (total 34 medications, range 1–7 discrepancies per patient), six patients had GP discrepancies, four had discrepancies resulting from a hospital outpatient appointment, one related to the discharge letter order and one was a complex discrepancy. An example: a patient was discharged on amiodarone liquid 16.5 mg daily as opposed to 65 mg daily of amiodarone from the GP. Upon interview the parent used volume units to communicate dose as opposed to the actual dose itself and the strengths of liquid had changed. Conclusions: The preliminary results from the study have shown that discrepancies due to several causes occur when paediatric patients leave hospital.

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Objectives: NICE/NPSA excluded children under 16 from their guidance concerning medicines reconciliation (MR) upon admission.1 Our aims and objectives of conducting the literature review was to identify the epidemiology of medication discrepancies upon admission, transfer and discharge in children, and if they require MR. Method: Six bibliographical databases (Medline, Embase, CINAHL, International Pharmaceutical Abstracts, Web of Science and Biosis Previews) and selected key words were used to find epidemiological studies on medication discrepancies in children upon hospital admission, transfer and discharge (key words included ‘medication discrepancy’; ‘medication reconciliation’; ‘hospital admission’; ‘hospital discharge’; ‘hospital transfer’); studies where the data for children could be extracted were included. Results: From the 1239 articles found (in May 2011), eight of the articles had extractable paediatric information, (five from Canada, two from USA, one from UK). Five of the studies involved discrepancies on admission, one involved discrepancies on admission and transfer, one involved discrepancies at transfer and one considered discharge. The reference point used to compare against the admission, transfer and the discharge order differed in each of the studies. Four studies used a rating scale to assess the clinical significance of the discrepancies to demonstrate the potential adverse clinical outcome of patients in the absence of clinical intervention. Two studies2 3 used a rating scale that was used in adults.4 A study of paediatric neurosurgical patients found that initial hospital prescriptions for children differed from the preadmission prescriptions in 39% of occasions and 50% of all prescribing variations had the potential to cause moderate or severe discomfort or clinical deterioration.2 A study by Coffey et al in general paediatric admissions in Canada showed 22% of patients experienced at least one discrepancy and 29% of the discrepancies had the potential to cause moderate or severe discomfort or clinical deterioration.3 By comparison an epidemiological study in discrepancies in adults on admission had 38.6% of the discrepancies identified with a potential to cause moderate or severe discomfort or clinical deterioration.4 All the studies involved small samples or specific patient groups such as medically complex patients. However all of the studies demonstrated that discrepancies occurred among paediatric populations during transitions in care settings and mentioned MR as an intervention. Conclusion: The results have shown that discrepancies of medication upon hospital admission, transfer and discharge occur regularly in children. With only one published study in the UK looking at hospital admission in children, and no published articles on the incidence and epidemiology of medication discrepancies upon hospital transfer or discharge further research is required in a wider paediatric population. Further work is also required to define the required interventions to improve practice.

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The goal of this study was to evaluate general medicine physicians' ability to predict hospital discharge. We prospectively asked study subjects to predict whether each patient under their care would be discharged on the next day, on the same day, or neither. Discharge predictions were recorded at 3 time points: mornings (7-9 am), midday (12-2 pm), or afternoons (5-7 pm), for a total of 2641 predictions. For predictions of next-day discharge, the sensitivity (SN) and positive predictive value (PPV) were lowest in the morning (27% and 33%, respectively), but increased by the afternoon (SN 67%, PPV 69%). Similarly, for same-day discharge predictions, SN and PPV were highest at midday (88% and 79%, respectively). We found that although physicians have difficulty predicting next-day discharges in the morning prior to the day of expected discharge, their ability to correctly predict discharges continually improved as the time to actual discharge decreased. Journal of Hospital Medicine 2015;10:808-810. © 2015 Society of Hospital Medicine.

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Introduction: Patients who survive an intensive care unit admission frequently suffer physical and psychological morbidity for many months after discharge. Current rehabilitation pathways are often fragmented and little is known about the optimum method of promoting recovery. Many patients suffer reduced quality of life. Methods and analysis: The authors plan a multicentre randomised parallel group complex intervention trial with concealment of group allocation from outcome assessors. Patients who required more than 48 h of mechanical ventilation and are deemed fit for intensive care unit discharge will be eligible. Patients with primary neurological diagnoses will be excluded. Participants will be randomised into one of the two groups: the intervention group will receive standard ward-based care delivered by the NHS service with additional treatment by a specifically trained generic rehabilitation assistant during ward stay and via telephone contact after hospital discharge and the control group will receive standard ward-based care delivered by the current NHS service. The intervention group will also receive additional information about their critical illness and access to a critical care physician. The total duration of the intervention will be from randomisation to 3 months postrandomisation. The total duration of follow-up will be 12 months from randomisation for both groups. The primary outcome will be the Rivermead Mobility Index at 3 months. Secondary outcomes will include measures of physical and psychological morbidity and function, quality of life and survival over a 12-month period. A health economic evaluation will also be undertaken. Groups will be compared in relation to primary and secondary outcomes; quantitative analyses will be supplemented by focus groups with patients, carers and healthcare workers. Ethics and dissemination: Consent will be obtained from patients and relatives according to patient capacity. Data will be analysed according to a predefined analysis plan.

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Background: The ageing population, with concomitant increase in chronic conditions, is increasing the presence of older people with complex needs in hospital. People with dementia are one of these complex populations and are particularly vulnerable to complications in hospital. Registered nurses can offer simultaneous assessment and intervention to prevent or mitigate hospital-acquired complications through their skilled brokerage between patient needs and hospital functions. A range of patient outcome measures that are sensitive to nursing care has been tested in nursing work environments across the world. However, none of these measures have focused on hospitalised older patients. Method: This thesis explores nursing-sensitive complications for older patients with and without dementia using an internationally recognised, risk-adjusted patient outcome approach. Specifically explored are: the differences between rates of complications; the costs of complications; and cost comparisons of patient complexity. A retrospective cohort study of an Australian state’s 2006–07 public hospital discharge data was utilised to identify patient episodes for people over age 50 (N=222,440) where dementia was identified as a primary or secondary diagnosis (N=44,422). Extra costs for patient episodes were estimated based on length of stay (LOS) above the average for each patient’s Diagnosis Related Group (DRG) (N=157,178) and were modelled using linear regression analysis to establish the strongest patient complexity predictors of cost. Results: Hospitalised patients with a primary or secondary diagnosis of dementia had higher rates of complications than did their same-age peers. The highest rates and relative risk for people with dementia were found in four key complications: urinary tract infections; pressure injuries; pneumonia, and delirium. While 21.9% of dementia patients (9,751/44,488, p<0.0001) suffered a complication, only 8.8% of non-dementia patients did so (33,501/381,788, p<0.0001), giving dementia patients a 2.5 relative risk of acquiring a complication (p<0.0001). These four key complications in patients over 50 both with and without dementia were associated with an eightfold increase in length of stay (813%, or 3.6 days/0.4 days) and double the increased estimated mean episode cost (199%, or A$16,403/ A$8,240). These four complications were associated with 24.7% of the estimated cost of additional days spent in hospital in 2006–07 in NSW (A$226million/A$914million). Dementia patients accounted for 22.0% of these costs (A$49million/A$226million) even though they were only 10.4% of the population (44,488/426,276 episodes). Hospital-acquired complications, particularly for people with a comorbidity of dementia, cost more than other kinds of inpatient complexity but admission severity was a better predictor of excess cost. Discussion: Four key complications occur more often in older patients with dementia and the high rate of these complications makes them expensive. These complications are potentially preventable. However, the care that can prevent them (such as mobility, hydration, nutrition and communication) is known to be rationed or left unfinished by nurses. Older hospitalised people who have complex needs, such as those with dementia, are more likely to experience care rationing as their care tends to take longer, be less predictable and less curative in nature. This thesis offers the theoretical proposition that evidence-based nursing practices are rationed for complex older patients and that this rationed care contributes to functional and cognitive decline during hospitalisation. This, in turn, contributes to the high rates of complications observed. Thus four key complications can be seen as a ‘Failure to Maintain’ complex older people in hospital. ‘Failure to Maintain’ is the inadequate delivery of essential functional and cognitive care for a complex older person in hospital resulting in a complication, and is recommended as a useful indicator for hospital quality. Conclusions: When examining extra length of stay in hospital, complications and comorbid dementia are costly. Complications are potentially preventable, and dementia care in hospitals can be improved. Hospitals and governments looking to decrease costs can engage in risk-reduction strategies for common nurse sensitive complications such as healthy nursing work environments that minimise nurses’ rationing of functional and cognitive care. The conceptualisation of complex older patients as ‘business as usual’ rather than a ‘burden’ is likely necessary for sustainable health care services of the future. The use of the ‘Failure to Maintain’ indicators at institution and state levels may aid in embedding this approach for complex older patients into health organisations. Ongoing investigation is warranted into the relationships between the largest health services expense (hospitals), the largest hospital population (complex older patients), and the largest hospital expense (nurses). The ‘Failure to Maintain’ quality indicator makes a useful and substantive contribution to further clinical, administrative and research developments.

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BACKGROUND: Western studies have suggested that emotional stress and distress impacted on the morbidity and mortality in people following acute coronary events. Symptoms of anxiety and depression have been associated with re-infarction and death, prolonged recovery and disability and depression may precipitate the client's low self-esteem. This study examined perceived anxiety, depression and self-esteem of Hong Kong Chinese clients diagnosed with acute coronary syndrome (ACS) over a 6-month period following hospital admission. OBJECTIVES: To examine: DESIGN: A prospective, repeated measures design with measures taken on two occasions over a 6-month period; (1) within the 1st week of hospital admission following the onset of ACS and (2) at 6 months follow up. SETTING AND PARTICIPANTS: Convenient sample of 182 voluntary consented clients admitted with ACS to a major public hospital in Hong Kong who could communicate in Chinese, complete questionnaires, cognitive intact, and were haemodynamically stable and free from acute chest pain at the time of interview. METHODS: Baseline data were obtained within 1 week after hospital admission. The follow-up data was collected 6 months after hospital discharge. The Chinese version of the Hospital Anxiety and Depression Scale (HADS), State Self-esteem Scale (SSES), and Rosenberg's Self-Esteem Scale (RSES) were used to assess anxiety and depression, state self-esteem, and trait self-esteem, respectively. RESULTS: Findings suggested gender differences in clients' perception in anxiety, depression and self-esteem. Improvements in clients' perception of these variables were evident over the 6-month period following their acute coronary events. CONCLUSION: The study confirmed the western notion that psychosocial problems are common among coronary clients and this also applies to Hong Kong Chinese diagnosed with ACS. Further studies to explore effective interventions to address these psychosocial issues are recommended.

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Background:  The aims of this study were to determine the documentation of pharmacotherapy optimization goals in the discharge letters of patients with the principal diagnosis of chronic heart failure. Methods:  A retrospective practice audit of 212 patients discharged to the care of their local general practitioner from general medical units of a large tertiary hospital. Details of recommendations regarding ongoing pharmacological and non-pharmacological management were reviewed. The doses of medications on discharge were noted and whether they met current guidelines recommending titration of angiotensin-converting enzyme inhibitors and beta-blockers. Ongoing arrangements for specialist follow up were also reviewed. Results:  The mean age of patients whose letters were reviewed was 78.4 years (standard deviation ± 8.6); 50% were men. Patients had an overall median of six comorbidities and eight regular medications on discharge. Mean length of stay for each admission was 6 days. Discharge letters were posted a median of 4 days after discharge, with 25% not posted at 10 days. No discharge letter was sent in 9.4% (20) of the cases. Only six (2.8%) letters had any recommendations regarding future titration of angiotensin-converting enzyme inhibitors and 6.6% (14) for beta-blockers. Recommendations for future non-pharmacological management, for example, diuretic action plans, regular weight monitoring and exercise plans were not found in the letters in this audit. Conclusion:  Hospital discharge is an opportunity to communicate management plans for treatment optimization effectively, and while this opportunity is spurned, implementation gaps in the management of cardiac failure will probably remain.